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Arian Etemadi developed early prototypes for ideas in Sections 8.1 and 8.3 and helped write the paper. Huidong Yang developed early prototypes for isosurface extraction and visualization. Chris Wojtan helped conceive the project, helped write the paper, and provided supervision, prototype grid data structure code, and conceptual solutions throughout the project. We thank the anonymous reviewers for their helpful comments, the members of the Visual Computing Group at ISTA for their feedback, Christopher Batty for discussions about LosTopos, and SideFX for the Houdini Education software licenses.  This research was funded in part by the European Union (ERC-2021-COG 101045083 CoDiNA).","article_number":"54","supplementarymaterial":"no","fulldoi":"https://doi.org/10.1145/3658223","isi":1,"tmp":{"name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","image":"/images/cc_by_nc_sa.png"},"issue":"4","file":[{"date_updated":"2024-07-23T06:35:15Z","content_type":"application/pdf","checksum":"1917067d4b52d7729019b03560004e43","file_size":48763368,"relation":"main_file","file_name":"2024_ACMToG_HeissSynak.pdf","access_level":"open_access","file_id":"17317","creator":"dernst","date_created":"2024-07-23T06:35:15Z","success":1},{"file_name":"sdtopofixer_final.mp4","access_level":"open_access","file_id":"17221","creator":"akalinov","success":1,"date_created":"2024-07-10T12:23:44Z","date_updated":"2024-07-10T12:23:44Z","content_type":"video/mp4","file_size":48021463,"checksum":"a4f0e293184bfa034c0c585848806b17","relation":"main_file"},{"date_created":"2025-11-11T09:50:52Z","creator":"akalinov","file_id":"20633","access_level":"open_access","file_name":"SuperDuperTopoFixer.pdf","title":"Authors' version of the text","relation":"preprint","checksum":"18fc310a78ec91651148c45a8b89fa44","file_size":48639581,"content_type":"application/pdf","date_updated":"2025-11-11T09:50:52Z"}],"publisher":"Association for Computing Machinery","external_id":{"isi":["001289270900021"]},"publication_status":"published","has_accepted_license":"1","_id":"17219","month":"07","publication_identifier":{"eissn":["1557-7368"],"issn":["0730-0301"]},"year":"2024","abstract":[{"lang":"eng","text":"We introduce a multi-material non-manifold mesh-based surface tracking algorithm that converts self-intersections into topological changes. Our algorithm generalizes prior work on manifold surface tracking with topological changes: it preserves surface features like mesh-based methods, and it robustly handles topological changes like level set methods. Our method also offers improved efficiency and robustness over the state of the art. We demonstrate the effectiveness of the approach on a range of examples, including complex soap film simulations with thousands of interacting bubbles, and boolean unions of non-manifold meshes consisting of millions of triangles."}],"date_created":"2024-07-10T12:24:00Z","OA_type":"hybrid","article_type":"original","day":"01","citation":{"ista":"Synak P, Kalinov A, Strugaru I-M, Etemadi A, Yang H, Wojtan C. 2024. Multi-material mesh-based surface tracking with implicit topology changes. ACM Transactions on Graphics. 43(4), 54.","ama":"Synak P, Kalinov A, Strugaru I-M, Etemadi A, Yang H, Wojtan C. 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Association for Computing Machinery, 2024.","mla":"Synak, Peter, et al. “Multi-Material Mesh-Based Surface Tracking with Implicit Topology Changes.” <i>ACM Transactions on Graphics</i>, vol. 43, no. 4, 54, Association for Computing Machinery, 2024, doi:<a href=\"https://doi.org/10.1145/3658223\">10.1145/3658223</a>.","chicago":"Synak, Peter, Aleksei Kalinov, Irina-Malina Strugaru, Arian Etemadi, Huidong Yang, and Chris Wojtan. “Multi-Material Mesh-Based Surface Tracking with Implicit Topology Changes.” <i>ACM Transactions on Graphics</i>. Association for Computing Machinery, 2024. <a href=\"https://doi.org/10.1145/3658223\">https://doi.org/10.1145/3658223</a>.","short":"P. Synak, A. Kalinov, I.-M. Strugaru, A. Etemadi, H. Yang, C. Wojtan, ACM Transactions on Graphics 43 (2024)."},"project":[{"name":"Computational Discovery of Numerical Algorithms for Animation and Simulation of Natural Phenomena","grant_number":"101045083","_id":"34bc2376-11ca-11ed-8bc3-9a3b3961a088"}],"doi":"10.1145/3658223","license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","keyword":["surface tracking","topology change","non- manifold meshes","multi-material flows","solid modeling"],"quality_controlled":"1","intvolume":"        43","oa":1,"das_tickbox":"0","oa_version":"Published Version","date_updated":"2026-10-02T11:19:25Z","file_date_updated":"2025-11-11T09:50:52Z","OA_place":"publisher","related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"19630"},{"status":"public","relation":"dissertation_contains","id":"18301"}]},"researchdata_availability":"no","author":[{"last_name":"Synak","first_name":"Peter","id":"331776E2-F248-11E8-B48F-1D18A9856A87","full_name":"Synak, Peter"},{"first_name":"Aleksei","last_name":"Kalinov","full_name":"Kalinov, Aleksei","id":"44b7120e-eb97-11eb-a6c2-e1557aa81d02","orcid":"0000-0003-2189-3904"},{"full_name":"Strugaru, Irina-Malina","id":"2afc607f-f128-11eb-9611-8f2a0dfcf074","last_name":"Strugaru","first_name":"Irina-Malina"},{"id":"36cea3aa-f38e-11ec-8ae0-c65ae6f6098f","full_name":"Etemadihaghighi, Arian","last_name":"Etemadihaghighi","first_name":"Arian"},{"first_name":"Huidong","last_name":"Yang","full_name":"Yang, Huidong"},{"orcid":"0000-0001-6646-5546","last_name":"Wojtan","first_name":"Christopher J","full_name":"Wojtan, Christopher J","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87"}],"title":"Multi-material mesh-based surface tracking with implicit topology changes","type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_processing_charge":"Yes (via OA deal)","ddc":["004"],"volume":43,"publication":"ACM Transactions on Graphics"},{"doi":"10.15479/at:ista:18301","license":"https://creativecommons.org/licenses/by-sa/4.0/","keyword":["surface tracking","non-manifold","hole-filling","topology change","multi-material","solid-modeling"],"oa":1,"page":"39","day":"15","citation":{"apa":"Etemadi, A. (2024). <i>Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:18301\">https://doi.org/10.15479/at:ista:18301</a>","ama":"Etemadi A. Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:18301\">10.15479/at:ista:18301</a>","ista":"Etemadi A. 2024. Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking. Institute of Science and Technology Austria.","chicago":"Etemadi, Arian. “Filling the Holes of Non-Manifold Self-Intersecting Meshes for Implicit Topology Changes in Surface Tracking.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:18301\">https://doi.org/10.15479/at:ista:18301</a>.","short":"A. Etemadi, Filling the Holes of Non-Manifold Self-Intersecting Meshes for Implicit Topology Changes in Surface Tracking, Institute of Science and Technology Austria, 2024.","mla":"Etemadi, Arian. <i>Filling the Holes of Non-Manifold Self-Intersecting Meshes for Implicit Topology Changes in Surface Tracking</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:18301\">10.15479/at:ista:18301</a>.","ieee":"A. Etemadi, “Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking,” Institute of Science and Technology Austria, 2024."},"author":[{"full_name":"Etemadihaghighi, Arian","id":"36cea3aa-f38e-11ec-8ae0-c65ae6f6098f","first_name":"Arian","last_name":"Etemadihaghighi"}],"title":"Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking","type":"dissertation","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_processing_charge":"No","ddc":["000"],"degree_awarded":"MS","alternative_title":["ISTA Master's Thesis"],"date_updated":"2026-10-02T11:19:26Z","oa_version":"Published Version","das_tickbox":"0","file_date_updated":"2024-10-24T14:34:54Z","OA_place":"publisher","related_material":{"record":[{"relation":"part_of_dissertation","id":"17219","status":"public"}]},"researchdata_availability":"no","supplementarymaterial":"no","fulldoi":"https://doi.org/10.15479/at:ista:18301","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","image":"/images/cc_by_sa.png","name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)","short":"CC BY-SA (4.0)"},"status":"public","language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"ChWo"}],"corr_author":"1","date_published":"2024-10-15T00:00:00Z","doi_confirm":"1","publication_identifier":{"issn":["2791-4585"]},"year":"2024","abstract":[{"text":"Physics simulation in computer graphics can bring triangle meshes into topologically invalid states. The method in this thesis contributed to Heiss-Synak* and Kalinov* et al. [2024] who devised a non-manifold hybrid surface tracker—a surface tracker that repairs explicit non-manifold triangle meshes with the help of the implicit domain. Specifically, this thesis provides an algorithm for filling the holes that are left after removing problematic parts of the mesh.","lang":"eng"}],"date_created":"2024-10-11T19:52:20Z","file":[{"creator":"aetemadi","success":1,"date_created":"2024-10-24T14:34:42Z","file_name":"thesis-arian-etemadi.pdf","access_level":"open_access","file_id":"18469","file_size":8914218,"checksum":"80fb7923e229ad9d39253d7c8a8083d0","relation":"main_file","date_updated":"2024-10-24T14:34:42Z","content_type":"application/pdf"},{"file_size":9802650,"checksum":"1c02586ed7d441d5ec441867650568d1","relation":"source_file","date_updated":"2024-10-24T14:34:54Z","content_type":"application/x-zip-compressed","creator":"aetemadi","date_created":"2024-10-24T14:34:54Z","file_name":"thesis-arian-etemadi-latex-source.zip","access_level":"closed","file_id":"18470"}],"publisher":"Institute of Science and Technology Austria","publication_status":"published","has_accepted_license":"1","month":"10","_id":"18301","supervisor":[{"orcid":"0000-0001-6646-5546","last_name":"Wojtan","first_name":"Christopher J","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","full_name":"Wojtan, Christopher J"}]},{"_id":"12846","month":"09","has_accepted_license":"1","publication_status":"published","external_id":{"isi":["001342265800009"],"arxiv":["2303.14555"]},"publisher":"Society for Industrial and Applied Mathematics","date_created":"2023-04-18T19:16:06Z","OA_type":"green","abstract":[{"lang":"eng","text":"We present a formula for the signed area of a spherical polygon via prequantization. In contrast to the traditional formula based on the Gauss-Bonnet theorem that requires measuring angles, the new formula mimics Green's theorem and is applicable to a wider range of degenerate spherical curves and polygons."}],"year":"2024","publication_identifier":{"eissn":["2470-6566"]},"acknowledgement":"This work was funded by European Research Council Consolidator grant 101045083 CoDiNA and National Science Foundation CAREER award 2239062. Some figures in the article were generated by the software Houdini and its education license was provided by SideFX. The authors acknowledge anonymous referees for their reviews and insightful suggestions, and Chris Wojtan for his continuous support through discussions. The second author thanks Anna Sisak for a fruitful discussion on prequantum bundles.","date_published":"2024-09-23T00:00:00Z","corr_author":"1","scopus_import":"1","department":[{"_id":"GradSch"},{"_id":"ChWo"}],"language":[{"iso":"eng"}],"status":"public","issue":"3","isi":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"fulldoi":"https://doi.org/10.1137/23M1565255","supplementarymaterial":"no","arxiv":1,"related_material":{"record":[{"status":"public","id":"20551","relation":"dissertation_contains"}]},"researchdata_availability":"no","OA_place":"repository","das_tickbox":"0","date_updated":"2026-10-02T11:17:04Z","oa_version":"Preprint","publication":"SIAM Journal on Applied Algebra and Geometry","volume":8,"ddc":["516"],"article_processing_charge":"No","type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","title":"Area formula for spherical polygons via prequantization","author":[{"first_name":"Albert","last_name":"Chern","full_name":"Chern, Albert"},{"id":"6F7C4B96-A8E9-11E9-A7CA-09ECE5697425","full_name":"Ishida, Sadashige","last_name":"Ishida","first_name":"Sadashige","orcid":"0000-0002-3121-3100"}],"citation":{"ista":"Chern A, Ishida S. 2024. Area formula for spherical polygons via prequantization. SIAM Journal on Applied Algebra and Geometry. 8(3), 782–796.","ama":"Chern A, Ishida S. Area formula for spherical polygons via prequantization. <i>SIAM Journal on Applied Algebra and Geometry</i>. 2024;8(3):782-796. doi:<a href=\"https://doi.org/10.1137/23M1565255\">10.1137/23M1565255</a>","apa":"Chern, A., &#38; Ishida, S. (2024). Area formula for spherical polygons via prequantization. <i>SIAM Journal on Applied Algebra and Geometry</i>. Society for Industrial and Applied Mathematics. <a href=\"https://doi.org/10.1137/23M1565255\">https://doi.org/10.1137/23M1565255</a>","ieee":"A. Chern and S. Ishida, “Area formula for spherical polygons via prequantization,” <i>SIAM Journal on Applied Algebra and Geometry</i>, vol. 8, no. 3. Society for Industrial and Applied Mathematics, pp. 782–796, 2024.","mla":"Chern, Albert, and Sadashige Ishida. “Area Formula for Spherical Polygons via Prequantization.” <i>SIAM Journal on Applied Algebra and Geometry</i>, vol. 8, no. 3, Society for Industrial and Applied Mathematics, 2024, pp. 782–96, doi:<a href=\"https://doi.org/10.1137/23M1565255\">10.1137/23M1565255</a>.","short":"A. Chern, S. Ishida, SIAM Journal on Applied Algebra and Geometry 8 (2024) 782–796.","chicago":"Chern, Albert, and Sadashige Ishida. “Area Formula for Spherical Polygons via Prequantization.” <i>SIAM Journal on Applied Algebra and Geometry</i>. Society for Industrial and Applied Mathematics, 2024. <a href=\"https://doi.org/10.1137/23M1565255\">https://doi.org/10.1137/23M1565255</a>."},"day":"23","page":"782-796","article_type":"original","oa":1,"intvolume":"         8","quality_controlled":"1","doi":"10.1137/23M1565255","license":"https://creativecommons.org/licenses/by/4.0/","project":[{"name":"Computational Discovery of Numerical Algorithms for Animation and Simulation of Natural Phenomena","grant_number":"101045083","_id":"34bc2376-11ca-11ed-8bc3-9a3b3961a088"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2303.14555","open_access":"1"}]},{"alternative_title":["ISTA Thesis"],"oa_version":"Published Version","date_updated":"2026-10-02T11:19:46Z","das_tickbox":"0","file_date_updated":"2024-09-06T16:24:59Z","OA_place":"publisher","researchdata_availability":"no","related_material":{"record":[{"id":"17378","relation":"part_of_dissertation","status":"public"},{"status":"public","id":"17087","relation":"part_of_dissertation"},{"status":"public","id":"14458","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","id":"18061","status":"public"},{"status":"public","relation":"part_of_dissertation","id":"18062"}]},"title":"Compressing large neural networks: Algorithms, systems and scaling laws","author":[{"first_name":"Elias","last_name":"Frantar","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","full_name":"Frantar, Elias"}],"type":"dissertation","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_processing_charge":"No","ddc":["000"],"degree_awarded":"PhD","page":"129","day":"05","citation":{"ista":"Frantar E. 2024. Compressing large neural networks: Algorithms, systems and scaling laws. Institute of Science and Technology Austria.","apa":"Frantar, E. (2024). <i>Compressing large neural networks: Algorithms, systems and scaling laws</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:17485\">https://doi.org/10.15479/at:ista:17485</a>","ama":"Frantar E. Compressing large neural networks: Algorithms, systems and scaling laws. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:17485\">10.15479/at:ista:17485</a>","ieee":"E. Frantar, “Compressing large neural networks: Algorithms, systems and scaling laws,” Institute of Science and Technology Austria, 2024.","short":"E. Frantar, Compressing Large Neural Networks: Algorithms, Systems and Scaling Laws, Institute of Science and Technology Austria, 2024.","chicago":"Frantar, Elias. “Compressing Large Neural Networks: Algorithms, Systems and Scaling Laws.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:17485\">https://doi.org/10.15479/at:ista:17485</a>.","mla":"Frantar, Elias. <i>Compressing Large Neural Networks: Algorithms, Systems and Scaling Laws</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:17485\">10.15479/at:ista:17485</a>."},"project":[{"call_identifier":"H2020","_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning"}],"doi":"10.15479/at:ista:17485","oa":1,"file":[{"content_type":"application/zip","date_updated":"2024-09-05T12:04:11Z","relation":"source_file","checksum":"5d785645805a78c5b4ce7cc3df557b09","file_size":1615167,"file_id":"17570","access_level":"closed","file_name":"thesis-final.zip","date_created":"2024-09-05T12:04:11Z","creator":"efrantar"},{"creator":"efrantar","success":1,"date_created":"2024-09-06T16:24:59Z","file_name":"frantar_thesis_final.pdf","access_level":"open_access","file_id":"17880","file_size":2376611,"checksum":"a9dd1c2d23734986924eb44ebb55fd8f","relation":"main_file","date_updated":"2024-09-06T16:24:59Z","content_type":"application/pdf"}],"publisher":"Institute of Science and Technology Austria","publication_status":"published","acknowledged_ssus":[{"_id":"ScienComp"}],"has_accepted_license":"1","_id":"17485","month":"09","supervisor":[{"last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X"}],"publication_identifier":{"issn":["2663-337X"]},"year":"2024","abstract":[{"text":"Large language models (LLMs) have made tremendous progress in the past few years, from being able to generate coherent text to matching or surpassing humans in a wide variety of creative, knowledge or reasoning tasks. Much of this can be attributed to massively increased scale, both in the size of the model as well as the amount of training data, from 100s of millions to 100s of billions, or even trillions. This trend is expected to continue, which, although exciting, also raises major practical concerns. Already today's 100+ billion parameter LLMs require top-of-the-line hardware just to run. Hence, it is clear that sustaining these developments will require significant efficiency advances.\r\n\r\nHistorically, one of the most practical ways of improving model efficiency has been compression, especially in the form of sparsity or quantization. While this has been studied extensively in the past, existing accurate methods are all designed for models around 100 million parameters; scaling them up to ones literally 1000x larger is highly challenging. In this thesis, we introduce a new unified sparsification and quantization approach OBC, which through additional algorithmic enhancements leads to GPTQ and SparseGPT, the first techniques fast and accurate enough to compress 100+ billion parameter models to 4- or even 3-bit precision and 50% weight-sparsity, respectively. Additionally, we show how weight-only quantizion does not just bring space savings but also up to 4.5x faster generation speed, via custom GPU kernels.\r\n\r\nIn fact, we show for the first time that it is possible to develop an FP16 times INT4 mixed-precision matrix multiplication kernel, called Marlin, which comes close to simultaneously maximizing both memory and compute utilization, making weight-only quantization highly practical even for multi-user serving. Further, we demonstrate that GPTQ can be scaled to widely overparametrized trillion-parameter models, where extreme sub-1-bit compression rates can be achieved without any inference slow-down, by co-designing a bespoke entropy coding scheme together with an efficient kernel.\r\n\r\nFinally, we also study compression from the perspective of someone with access to massive amounts of compute resources for training large models completely from scratch. Here the key questions evolve around the joint scaling behavior between compression, model size, and amount of training data used. Based on extensive experimental results for both vision and text models, we introduce the first scaling law which accurately captures the relationship between weight-sparsity, number of non-zero weights and data. This further allows us to characterize the optimal sparsity, which we find to increase the longer a fixed cost model is being trained.\r\n\r\nOverall, this thesis presents contributions to three different angles of large model efficiency: affordable but accurate algorithms, highly efficient systems implementations, and fundamental scaling laws for compressed training.","lang":"eng"}],"date_created":"2024-09-02T11:01:48Z","status":"public","language":[{"iso":"eng"}],"corr_author":"1","department":[{"_id":"GradSch"},{"_id":"DaAl"}],"doi_confirm":"1","date_published":"2024-09-05T00:00:00Z","supplementarymaterial":"no","fulldoi":"https://doi.org/10.15479/at:ista:17485","ec_funded":1},{"_id":"18062","month":"01","external_id":{"arxiv":["2309.08520"]},"publication_status":"published","year":"2024","date_created":"2024-09-13T10:31:08Z","abstract":[{"lang":"eng","text":"We explore the impact of parameter sparsity on the scaling behavior of Transformers trained on massive datasets (i.e., \"foundation models\"), in both vision and language domains. In this setting, we identify the first scaling law describing the relationship between weight sparsity, number of non-zero parameters, and amount of training data, which we validate empirically across model and data scales; on ViT/JFT-4B and T5/C4. These results allow us to characterize the \"optimal sparsity\", the sparsity level which yields the best performance for a given effective model size and training budget. For a fixed number of non-zero parameters, we identify that the optimal sparsity increases with the amount of data used for training. We also extend our study to different sparsity structures (such as the hardware-friendly n:m pattern) and strategies (such as starting from a pretrained dense model). Our findings shed light on the power and limitations of weight sparsity across various parameter and computational settings, offering both theoretical understanding and practical implications for leveraging sparsity towards computational efficiency improvements. We provide pruning and scaling law fitting code at: github.com/google-research/jaxpruner/tree/main/jaxpruner/projects/bigsparse."}],"scopus_import":"1","corr_author":"1","department":[{"_id":"DaAl"}],"date_published":"2024-01-16T00:00:00Z","status":"public","language":[{"iso":"eng"}],"supplementarymaterial":"no","arxiv":1,"related_material":{"record":[{"status":"public","id":"17485","relation":"dissertation_contains"}]},"researchdata_availability":"no","date_updated":"2026-10-02T11:19:46Z","das_tickbox":"0","oa_version":"Published Version","ddc":["000"],"publication":"The Twelfth International Conference on Learning Representations","type":"conference","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","conference":{"end_date":"2024-05-07","location":"Vienna, Austria","name":"ICLR: International Conference on Learning Representations","start_date":"2024-05-07"},"author":[{"first_name":"Elias","last_name":"Frantar","full_name":"Frantar, Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f"},{"full_name":"Ruiz, Carlos Riquelme","first_name":"Carlos Riquelme","last_name":"Ruiz"},{"full_name":"Houlsby, Neil","last_name":"Houlsby","first_name":"Neil"},{"last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X"},{"full_name":"Evci, Utku","first_name":"Utku","last_name":"Evci"}],"title":"Scaling laws for sparsely-connected foundation models","article_processing_charge":"No","citation":{"ama":"Frantar E, Ruiz CR, Houlsby N, Alistarh D-A, Evci U. Scaling laws for sparsely-connected foundation models. In: <i>The Twelfth International Conference on Learning Representations</i>. ; 2024.","apa":"Frantar, E., Ruiz, C. R., Houlsby, N., Alistarh, D.-A., &#38; Evci, U. (2024). Scaling laws for sparsely-connected foundation models. In <i>The Twelfth International Conference on Learning Representations</i>. Vienna, Austria.","ista":"Frantar E, Ruiz CR, Houlsby N, Alistarh D-A, Evci U. 2024. Scaling laws for sparsely-connected foundation models. The Twelfth International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","mla":"Frantar, Elias, et al. “Scaling Laws for Sparsely-Connected Foundation Models.” <i>The Twelfth International Conference on Learning Representations</i>, 2024.","chicago":"Frantar, Elias, Carlos Riquelme Ruiz, Neil Houlsby, Dan-Adrian Alistarh, and Utku Evci. “Scaling Laws for Sparsely-Connected Foundation Models.” In <i>The Twelfth International Conference on Learning Representations</i>, 2024.","short":"E. Frantar, C.R. Ruiz, N. Houlsby, D.-A. Alistarh, U. Evci, in:, The Twelfth International Conference on Learning Representations, 2024.","ieee":"E. Frantar, C. R. Ruiz, N. Houlsby, D.-A. Alistarh, and U. Evci, “Scaling laws for sparsely-connected foundation models,” in <i>The Twelfth International Conference on Learning Representations</i>, Vienna, Austria, 2024."},"day":"16","quality_controlled":"1","oa":1,"main_file_link":[{"open_access":"1","url":"https://openreview.net/forum?id=i9K2ZWkYIP"}]},{"publication":"Proceedings of Machine Learning and Systems","volume":6,"ddc":["000"],"article_processing_charge":"No","conference":{"name":"MLSys: Machine Learning and Systems","start_date":"2024-05-13","end_date":"2024-05-16","location":"Santa Clara, CA, United States"},"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"conference","author":[{"last_name":"Frantar","first_name":"Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","full_name":"Frantar, Elias"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X"}],"title":"QMoE: Sub-1-bit compression of trillion parameter models","researchdata_availability":"yes","related_material":{"record":[{"relation":"dissertation_contains","id":"17485","status":"public"}]},"date_updated":"2026-10-02T11:19:46Z","das_tickbox":"0","oa_version":"Published Version","oa":1,"intvolume":"         6","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://proceedings.mlsys.org/paper_files/paper/2024/hash/c74b624843218d9b6713fcf299d6d5e4-Abstract-Conference.html"}],"citation":{"ista":"Frantar E, Alistarh D-A. 2024. QMoE: Sub-1-bit compression of trillion parameter models. Proceedings of Machine Learning and Systems. MLSys: Machine Learning and Systems vol. 6.","ama":"Frantar E, Alistarh D-A. QMoE: Sub-1-bit compression of trillion parameter models. In: <i>Proceedings of Machine Learning and Systems</i>. Vol 6. ; 2024.","apa":"Frantar, E., &#38; Alistarh, D.-A. (2024). QMoE: Sub-1-bit compression of trillion parameter models. In <i>Proceedings of Machine Learning and Systems</i> (Vol. 6). Santa Clara, CA, United States.","ieee":"E. Frantar and D.-A. Alistarh, “QMoE: Sub-1-bit compression of trillion parameter models,” in <i>Proceedings of Machine Learning and Systems</i>, Santa Clara, CA, United States, 2024, vol. 6.","mla":"Frantar, Elias, and Dan-Adrian Alistarh. “QMoE: Sub-1-Bit Compression of Trillion Parameter Models.” <i>Proceedings of Machine Learning and Systems</i>, vol. 6, 2024.","short":"E. Frantar, D.-A. Alistarh, in:, Proceedings of Machine Learning and Systems, 2024.","chicago":"Frantar, Elias, and Dan-Adrian Alistarh. “QMoE: Sub-1-Bit Compression of Trillion Parameter Models.” In <i>Proceedings of Machine Learning and Systems</i>, Vol. 6, 2024."},"day":"01","date_created":"2024-09-13T10:01:38Z","abstract":[{"text":"Mixture-of-Experts (MoE) architectures offer a general solution to the high inference costs of large language models (LLMs) via sparse routing, bringing faster and more accurate models, at the cost of massive parameter counts. For example, the SwitchTransformer-c2048 model has 1.6 trillion parameters, requiring 3.2TB of accelerator memory to run efficiently, which makes practical deployment challenging and expensive. In this paper, we present a solution to this memory problem, in form of a new compression and execution framework called QMoE. Specifically, QMoE consists of a scalable algorithm which accurately compresses trillion-parameter MoEs to less than 1 bit per parameter, in a custom format co-designed with bespoke GPU decoding kernels to facilitate efficient end-to-end compressed inference, with minor runtime overheads relative to uncompressed execution. Concretely, QMoE can compress the 1.6 trillion parameter SwitchTransformer-c2048 model to less than 160GB (20x compression, 0.8 bits per parameter) at only minor accuracy loss, in less than a day on a single GPU. This enables, for the first time, the execution of a trillion-parameter model on affordable commodity hardware, like a single server with 4x NVIDIA A6000 or 8x NVIDIA 3090 GPUs, at less than 5% runtime overhead relative to ideal uncompressed inference. The anonymized code is available at: github.com/mlsys24-qmoe/qmoe.","lang":"eng"}],"year":"2024","month":"05","_id":"18061","publication_status":"published","supplementarymaterial":"no","date_published":"2024-05-01T00:00:00Z","department":[{"_id":"DaAl"}],"corr_author":"1","language":[{"iso":"eng"}],"status":"public"},{"abstract":[{"text":"Deep learning is essential in numerous applications nowadays, with many recent advancements made possible by training very large models. Despite their broad applicability, training neural networks is often time-intensive, and it is usually impractical to manage large models and datasets on a single machine. To address these issues, distributed deep learning training has become increasingly important. However, distributed training requires synchronization among nodes, and the mini-batch stochastic gradient descent algorithm places a significant load on network connections. A possible solution to tackle the synchronization bottleneck is to reduce a message size by lossy compression.\r\n\r\nIn this thesis, we investigate systems and algorithmic approaches to communication compression during training. From the systems perspective, we demonstrate that a common approach of expensive hardware overprovisioning can be replaced through a thorough system design. We introduce a framework that introduces efficient software support for compressed communication in machine learning applications, applicable to both multi-GPU single-node training and larger-scale multi-node training. Our framework integrates with popular ML frameworks, providing up to 3x speedups for multi-GPU nodes based on commodity hardware and order-of-magnitude improvements in the multi-node setting, with negligible impact on accuracy.\r\n\r\nAlso, we consider an application of our framework to different communication schemes, such as Fully Sharded Data Parallel. We provide strong convergence guarantees for the compression in such a setup. Empirical validation shows that our method preserves model accuracy for GPT-family models with up to 1.3 billion parameters, while completely removing the communication bottlenecks of non-compressed alternatives, providing up to 2.2x speedups end-to-end.\r\n\r\nFrom the algorithmic side, we propose a general framework that dynamically adjusts the degree of compression across a model's layers during training. This approach enhances overall compression and results in significant speedups without compromising accuracy. Our algorithm utilizes an adaptive algorithm that automatically selects the optimal compression parameters for model layers, ensuring the best compression ratio while adhering to an error constraint. Our method is effective across all existing families of compression methods. It achieves up to 2.5x faster training and up to a 5x improvement in compression compared to efficient implementations of current approaches. Additionally, LGreCo can complement existing adaptive algorithms.\r\n","lang":"eng"}],"date_created":"2024-09-04T08:51:11Z","year":"2024","publication_identifier":{"issn":["2663-337X"]},"month":"09","_id":"17490","supervisor":[{"full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X"}],"publication_status":"published","has_accepted_license":"1","acknowledged_ssus":[{"_id":"ScienComp"}],"publisher":"Institute of Science and Technology Austria","file":[{"file_size":43327753,"checksum":"77609f4835d2730e46fa0d42d9134ed9","relation":"source_file","date_updated":"2024-09-04T08:35:35Z","content_type":"application/x-zip-compressed","creator":"imarkov","date_created":"2024-09-04T08:35:35Z","file_name":"Thesis.zip","file_id":"17491","access_level":"closed"},{"access_level":"open_access","file_id":"17492","file_name":"Thesis_final_version_pdfa2.pdf","date_created":"2024-09-04T08:36:06Z","success":1,"creator":"imarkov","content_type":"application/pdf","date_updated":"2024-09-04T08:36:06Z","relation":"main_file","checksum":"9e68f7217570f756ceb8f70b980938cd","file_size":2756082}],"tmp":{"name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","image":"/images/cc_by_nc_sa.png"},"ec_funded":1,"fulldoi":"https://doi.org/10.15479/at:ista:17490","supplementarymaterial":"no","doi_confirm":"1","date_published":"2024-09-04T00:00:00Z","department":[{"_id":"GradSch"},{"_id":"DaAl"}],"corr_author":"1","language":[{"iso":"eng"}],"status":"public","degree_awarded":"PhD","ddc":["000"],"article_processing_charge":"No","title":"Communication-efficient distributed training of deep neural networks : An algorithms and systems perspective","author":[{"id":"D0CF4148-C985-11E9-8066-0BDEE5697425","full_name":"Markov, Ilia","last_name":"Markov","first_name":"Ilia"}],"type":"dissertation","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","related_material":{"record":[{"status":"public","id":"14461","relation":"part_of_dissertation"},{"status":"public","id":"12780","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","id":"17456","status":"public"}]},"researchdata_availability":"no","file_date_updated":"2024-09-04T08:36:06Z","OA_place":"publisher","alternative_title":["ISTA Thesis"],"das_tickbox":"0","oa_version":"Published Version","date_updated":"2026-10-02T11:20:06Z","oa":1,"doi":"10.15479/at:ista:17490","project":[{"name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","call_identifier":"H2020","_id":"268A44D6-B435-11E9-9278-68D0E5697425"}],"citation":{"ieee":"I. Markov, “Communication-efficient distributed training of deep neural networks : An algorithms and systems perspective,” Institute of Science and Technology Austria, 2024.","chicago":"Markov, Ilia. “Communication-Efficient Distributed Training of Deep Neural Networks : An Algorithms and Systems Perspective.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:17490\">https://doi.org/10.15479/at:ista:17490</a>.","short":"I. Markov, Communication-Efficient Distributed Training of Deep Neural Networks : An Algorithms and Systems Perspective, Institute of Science and Technology Austria, 2024.","mla":"Markov, Ilia. <i>Communication-Efficient Distributed Training of Deep Neural Networks : An Algorithms and Systems Perspective</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:17490\">10.15479/at:ista:17490</a>.","ista":"Markov I. 2024. Communication-efficient distributed training of deep neural networks : An algorithms and systems perspective. Institute of Science and Technology Austria.","apa":"Markov, I. (2024). <i>Communication-efficient distributed training of deep neural networks : An algorithms and systems perspective</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:17490\">https://doi.org/10.15479/at:ista:17490</a>","ama":"Markov I. Communication-efficient distributed training of deep neural networks : An algorithms and systems perspective. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:17490\">10.15479/at:ista:17490</a>"},"day":"04","page":"102"},{"main_file_link":[{"url":"https://proceedings.mlsys.org/paper_files/paper/2024/hash/9069a8976ff06f6443e7f4172990a580-Abstract-Conference.html","open_access":"1"}],"oa":1,"intvolume":"         6","quality_controlled":"1","day":"01","citation":{"ama":"Markov I, Alimohammadi K, Frantar E, Alistarh D-A. L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning. In: Gibbons P, Pekhimenko G, De Sa C, eds. <i>Proceedings of Machine Learning and Systems </i>. Vol 6. Association for Computing Machinery; 2024.","apa":"Markov, I., Alimohammadi, K., Frantar, E., &#38; Alistarh, D.-A. (2024). L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning. In P. Gibbons, G. Pekhimenko, &#38; C. De Sa (Eds.), <i>Proceedings of Machine Learning and Systems </i> (Vol. 6). Athens, Greece: Association for Computing Machinery.","ista":"Markov I, Alimohammadi K, Frantar E, Alistarh D-A. 2024. L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning. Proceedings of Machine Learning and Systems . MLSys: Machine Learning and Systems vol. 6.","mla":"Markov, Ilia, et al. “L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient Data-Parallel Deep Learning.” <i>Proceedings of Machine Learning and Systems </i>, edited by P. Gibbons et al., vol. 6, Association for Computing Machinery, 2024.","chicago":"Markov, Ilia, Kaveh Alimohammadi, Elias Frantar, and Dan-Adrian Alistarh. “L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient Data-Parallel Deep Learning.” In <i>Proceedings of Machine Learning and Systems </i>, edited by P. Gibbons, G. Pekhimenko, and C. De Sa, Vol. 6. Association for Computing Machinery, 2024.","short":"I. Markov, K. Alimohammadi, E. Frantar, D.-A. Alistarh, in:, P. Gibbons, G. Pekhimenko, C. De Sa (Eds.), Proceedings of Machine Learning and Systems , Association for Computing Machinery, 2024.","ieee":"I. Markov, K. Alimohammadi, E. Frantar, and D.-A. Alistarh, “L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning,” in <i>Proceedings of Machine Learning and Systems </i>, Athens, Greece, 2024, vol. 6."},"article_processing_charge":"No","editor":[{"full_name":"Gibbons, P.","first_name":"P.","last_name":"Gibbons"},{"last_name":"Pekhimenko","first_name":"G.","full_name":"Pekhimenko, G."},{"last_name":"De Sa","first_name":"C.","full_name":"De Sa, C."}],"type":"conference","conference":{"end_date":"2024-04-22","location":"Athens, Greece","name":"MLSys: Machine Learning and Systems","start_date":"2024-04-22"},"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","title":"L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning","author":[{"last_name":"Markov","first_name":"Ilia","id":"D0CF4148-C985-11E9-8066-0BDEE5697425","full_name":"Markov, Ilia"},{"last_name":"Alimohammadi","first_name":"Kaveh","full_name":"Alimohammadi, Kaveh"},{"last_name":"Frantar","first_name":"Elias","full_name":"Frantar, Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f"},{"full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X"}],"publication":"Proceedings of Machine Learning and Systems ","volume":6,"ddc":["000"],"das_tickbox":"0","oa_version":"Published Version","date_updated":"2026-10-02T11:20:05Z","researchdata_availability":"no","related_material":{"record":[{"relation":"dissertation_contains","id":"17490","status":"public"}]},"supplementarymaterial":"no","arxiv":1,"language":[{"iso":"eng"}],"status":"public","date_published":"2024-04-01T00:00:00Z","department":[{"_id":"DaAl"}],"corr_author":"1","date_created":"2024-08-22T08:29:25Z","abstract":[{"text":"Data-parallel distributed training of deep neural networks (DNN) has gained very widespread adoption, but can still experience communication bottlenecks. To address this issue, entire families of compression mechanisms have been developed, including quantization, sparsification, and low-rank approximation, some of which are seeing significant practical adoption. Despite this progress, almost all known compression schemes apply compression uniformly across DNN layers, although layers are heterogeneous in terms of parameter count and their impact on model accuracy.In this work, we provide a general framework for adapting the degree of compression across the model's layers dynamically during training, improving the overall compression, while leading to substantial speedups, without sacrificing accuracy. Our framework, called L-GreCo, is based on an adaptive algorithm, which automatically picks the optimal compression parameters for model layers guaranteeing the best compression ratio while satisfying an error constraint. Extensive experiments over image classification and language modeling tasks shows that L-GreCo is effective across all existing families of compression methods, and achieves up to 2.5\r\n×\r\n training speedup and up to 5\r\n×\r\n compression improvement over efficient implementations of existing approaches, while recovering full accuracy. Moreover, L-GreCo is complementary to existing adaptive algorithms, improving their compression ratio by 50\\% and practical throughput by 66\\%. An anonymized implementation is available at https://github.com/LGrCo/L-GreCo.","lang":"eng"}],"year":"2024","publication_status":"published","external_id":{"arxiv":["2210.17357"]},"publisher":"Association for Computing Machinery","month":"04","_id":"17456"},{"publication_identifier":{"isbn":["978-3-99078-049-7"],"issn":["2663-337X"]},"year":"2024","abstract":[{"text":"Poxviruses are large pleomorphic double-stranded DNA viruses that include well known members such as variola virus, the causative agent of smallpox, Mpox virus, as well as Vaccinia virus (VACV), which serves as a vaccination strain for formerly mentioned viruses. VACV is a valuable model for studying large pleomorphic DNA viruses in general and poxviruses specifically, as many features, such as core morphology and structural proteins, are well conserved within this family. Despite decades of research, our understanding of the structural components and proteins that comprise the poxvirus core in mature virions remains limited. Although major core proteins were identified via indirect experimental evidence, the core's complexity, with its large size, structure and number of involved proteins, has hindered efforts to achieve high-resolution insights and to define the roles of the individual proteins. The specific protein composition of the core's individual layers, including the palisade layer and the inner core wall, has remained unclear. In this study, we have merged multiple approaches, including single particle cryo electron microscopy of purified virus cores, cryo-electron tomography and subtomogram averaging of mature virions and molecular modeling to elucidate the structural determinants of the VACV core. Due to the lack of experimentally derived structures, either in situ or reconstituted in vitro, we used Alphafold to predict models of the putative major core protein candidates, A10, 23k, A3, A4, and L4. Our results show that the VACV core is composed of several layers with varying local symmetries, forming more intricate interactions than observed previously. This allowed us to identify several molecular building blocks forming the viral core lattice. In particular, we identified trimers of protein A10 as a major core structure that forms the palisade layer of the viral core. Additionally, we revealed that six petals of a flower shaped core pore within the core wall are composed of A10 trimers. Furthermore, we obtained a cryo-EM density for the inner core wall that could potentially accommodate an A3 dimer. Integrating descriptions of protein interactions from previous studies enabled us to provide a detailed structural model of the poxvirus core wall, and our findings indicate that the interactions within A10 trimers are likely consistent across orthopox- and parapoxviruses. This combined application of cryo-SPA and cryo-ET can help overcome obstacles in studying complex virus structures in the future, including their key assembly proteins, interactions, and the formation into a core lattice. Our work provides important fundamental new insights into poxvirus core architecture, also considering the recent re-emergence of poxviruses.","lang":"eng"}],"date_created":"2025-01-07T10:23:12Z","file":[{"date_created":"2025-01-07T12:15:11Z","creator":"jstanger","access_level":"closed","file_id":"18769","file_name":"PhD_thesis_Julia_Datler.docx","relation":"source_file","checksum":"3e51cab327c754045c3d29c1a50cc9a9","file_size":38814932,"content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","date_updated":"2025-01-07T12:15:11Z"},{"date_updated":"2025-01-07T12:15:14Z","content_type":"application/pdf","checksum":"22fabe5b97950bf852212f6edb555173","file_size":12044865,"relation":"main_file","file_name":"PhD_thesis_Julia_Datler.pdf","access_level":"open_access","file_id":"18770","creator":"jstanger","date_created":"2025-01-07T12:15:14Z","success":1}],"publisher":"Institute of Science and Technology Austria","publication_status":"published","has_accepted_license":"1","acknowledged_ssus":[{"_id":"EM-Fac"},{"_id":"LifeSc"},{"_id":"ScienComp"}],"month":"12","_id":"18766","supervisor":[{"orcid":"0000-0003-4790-8078","id":"48AD8942-F248-11E8-B48F-1D18A9856A87","full_name":"Schur, Florian KM","last_name":"Schur","first_name":"Florian KM"}],"supplementarymaterial":"no","fulldoi":"https://doi.org/10.15479/at:ista:18766","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png"},"status":"public","language":[{"iso":"eng"}],"corr_author":"1","department":[{"_id":"GradSch"},{"_id":"FlSc"}],"date_published":"2024-12-30T00:00:00Z","doi_confirm":"1","acknowledgement":"This work was funded by the Austrian Science Fund (FWF) grant P31445 and ISTA. I\r\nwould like to express my gratitude to the Scientific Service Units, particularly the Lab\r\nSupport Facility, the Scientific Computing Facility and the Electron Microscopy Facility\r\nfor their tremendous support. I want to especially thank Alois for assisting me with the\r\ninstallation of countless new software and for troubleshooting cluster issues. A special\r\nthanks goes to Valentin for his outstanding support in cryo-EM data acquisition and\r\nhis ongoing help in improving the process to ensure that I obtained the best possible\r\ndata from my sample.","title":"Elucidating the structural determinants of the poxvirus core using multi-modal cryo-EM","author":[{"first_name":"Julia","last_name":"Datler","full_name":"Datler, Julia","id":"3B12E2E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-3616-8580"}],"type":"dissertation","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_processing_charge":"No","ddc":["570"],"degree_awarded":"PhD","das_tickbox":"1","date_updated":"2026-10-02T11:21:19Z","oa_version":"Published Version","alternative_title":["ISTA thesis"],"file_date_updated":"2025-01-07T12:15:14Z","OA_place":"publisher","researchdata_availability":"yes","related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"12334"},{"relation":"part_of_dissertation","id":"14979","status":"public"}]},"project":[{"grant_number":"P31445","name":"Structural conservation and diversity in retroviral capsid","call_identifier":"FWF","_id":"26736D6A-B435-11E9-9278-68D0E5697425"}],"license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","keyword":["cryo-EM","cryo-ET","cryo-SPA","Structural Virology","Poxvirus","Vaccinia Virus","Structural Biology"],"doi":"10.15479/at:ista:18766","oa":1,"page":"106","day":"30","citation":{"ieee":"J. Datler, “Elucidating the structural determinants of the poxvirus core using multi-modal cryo-EM,” Institute of Science and Technology Austria, 2024.","short":"J. Datler, Elucidating the Structural Determinants of the Poxvirus Core Using Multi-Modal Cryo-EM, Institute of Science and Technology Austria, 2024.","chicago":"Datler, Julia. “Elucidating the Structural Determinants of the Poxvirus Core Using Multi-Modal Cryo-EM.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:18766\">https://doi.org/10.15479/at:ista:18766</a>.","mla":"Datler, Julia. <i>Elucidating the Structural Determinants of the Poxvirus Core Using Multi-Modal Cryo-EM</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:18766\">10.15479/at:ista:18766</a>.","ista":"Datler J. 2024. Elucidating the structural determinants of the poxvirus core using multi-modal cryo-EM. Institute of Science and Technology Austria.","apa":"Datler, J. (2024). <i>Elucidating the structural determinants of the poxvirus core using multi-modal cryo-EM</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:18766\">https://doi.org/10.15479/at:ista:18766</a>","ama":"Datler J. Elucidating the structural determinants of the poxvirus core using multi-modal cryo-EM. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:18766\">10.15479/at:ista:18766</a>"}},{"status":"public","language":[{"iso":"eng"}],"scopus_import":"1","corr_author":"1","department":[{"_id":"FlSc"},{"_id":"ScienComp"},{"_id":"EM-Fac"}],"date_published":"2024-07-01T00:00:00Z","acknowledgement":"We thank A. Bergthaler (Research Center for Molecular Medicine of the Austrian Academy of Sciences) for providing VACV WR. We thank A. Nicholas and his team at the ISTA proteomics facility, and S. Elefante at the ISTA Scientific Computing facility for their support. We also thank F. Fäßler, D. Porley, T. Muthspiel and other members of the Schur group for support and helpful discussions. We also thank D. Castaño-Díez for support with Dynamo. We thank D. Farrell for his help optimizing the Rosetta protocol to refine the atomic model into the cryo-EM map with symmetry.\r\n\r\nF.K.M.S. acknowledges support from ISTA and EMBO. F.K.M.S. also received support from the Austrian Science Fund (FWF) grant P31445. This publication has been made possible in part by CZI grant DAF2021-234754 and grant https://doi.org/10.37921/812628ebpcwg from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation (funder https://doi.org/10.13039/100014989) awarded to F.K.M.S.\r\n\r\nThis research was also supported by the Scientific Service Units (SSUs) of ISTA through resources provided by Scientific Computing (SciComp), the Life Science Facility (LSF), and the Electron Microscopy Facility (EMF). We also acknowledge the use of COSMIC45 and Colabfold46.","supplementarymaterial":"yes","pmid":1,"fulldoi":"https://doi.org/10.1038/s41594-023-01201-6","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"isi":1,"publisher":"Springer Nature","file":[{"creator":"dernst","success":1,"date_created":"2024-07-22T11:27:22Z","file_name":"2024_NatureStrucBio_Datler.pdf","access_level":"open_access","file_id":"17307","file_size":17485494,"checksum":"bda7bf65d81455480efaed8ca293b0db","relation":"main_file","date_updated":"2024-07-22T11:27:22Z","content_type":"application/pdf"}],"external_id":{"isi":["001158144600002"],"pmid":["38316877"]},"publication_status":"published","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"LifeSc"},{"_id":"EM-Fac"}],"has_accepted_license":"1","month":"07","_id":"14979","publication_identifier":{"issn":["1545-9993"],"eissn":["1545-9985"]},"year":"2024","abstract":[{"text":"Poxviruses are among the largest double-stranded DNA viruses, with members such as variola virus, monkeypox virus and the vaccination strain vaccinia virus (VACV). Knowledge about the structural proteins that form the viral core has remained sparse. While major core proteins have been annotated via indirect experimental evidence, their structures have remained elusive and they could not be assigned to individual core features. Hence, which proteins constitute which layers of the core, such as the palisade layer and the inner core wall, has remained enigmatic. Here we show, using a multi-modal cryo-electron microscopy (cryo-EM) approach in combination with AlphaFold molecular modeling, that trimers formed by the cleavage product of VACV protein A10 are the key component of the palisade layer. This allows us to place previously obtained descriptions of protein interactions within the core wall into perspective and to provide a detailed model of poxvirus core architecture. Importantly, we show that interactions within A10 trimers are likely generalizable over members of orthopox- and parapoxviruses.","lang":"eng"}],"date_created":"2024-02-12T09:59:45Z","OA_type":"hybrid","article_type":"original","page":"1114-1123","day":"01","citation":{"apa":"Datler, J., Hansen, J., Thader, A., Schlögl, A., Bauer, L. W., Hodirnau, V.-V., &#38; Schur, F. K. (2024). Multi-modal cryo-EM reveals trimers of protein A10 to form the palisade layer in poxvirus cores. <i>Nature Structural &#38; Molecular Biology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41594-023-01201-6\">https://doi.org/10.1038/s41594-023-01201-6</a>","ama":"Datler J, Hansen J, Thader A, et al. Multi-modal cryo-EM reveals trimers of protein A10 to form the palisade layer in poxvirus cores. <i>Nature Structural &#38; Molecular Biology</i>. 2024;31:1114-1123. doi:<a href=\"https://doi.org/10.1038/s41594-023-01201-6\">10.1038/s41594-023-01201-6</a>","ista":"Datler J, Hansen J, Thader A, Schlögl A, Bauer LW, Hodirnau V-V, Schur FK. 2024. Multi-modal cryo-EM reveals trimers of protein A10 to form the palisade layer in poxvirus cores. Nature Structural &#38; Molecular Biology. 31, 1114–1123.","chicago":"Datler, Julia, Jesse Hansen, Andreas Thader, Alois Schlögl, Lukas W Bauer, Victor-Valentin Hodirnau, and Florian KM Schur. “Multi-Modal Cryo-EM Reveals Trimers of Protein A10 to Form the Palisade Layer in Poxvirus Cores.” <i>Nature Structural &#38; Molecular Biology</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41594-023-01201-6\">https://doi.org/10.1038/s41594-023-01201-6</a>.","short":"J. Datler, J. Hansen, A. Thader, A. Schlögl, L.W. Bauer, V.-V. Hodirnau, F.K. Schur, Nature Structural &#38; Molecular Biology 31 (2024) 1114–1123.","mla":"Datler, Julia, et al. “Multi-Modal Cryo-EM Reveals Trimers of Protein A10 to Form the Palisade Layer in Poxvirus Cores.” <i>Nature Structural &#38; Molecular Biology</i>, vol. 31, Springer Nature, 2024, pp. 1114–23, doi:<a href=\"https://doi.org/10.1038/s41594-023-01201-6\">10.1038/s41594-023-01201-6</a>.","ieee":"J. Datler <i>et al.</i>, “Multi-modal cryo-EM reveals trimers of protein A10 to form the palisade layer in poxvirus cores,” <i>Nature Structural &#38; Molecular Biology</i>, vol. 31. Springer Nature, pp. 1114–1123, 2024."},"project":[{"name":"Structural conservation and diversity in retroviral capsid","grant_number":"P31445","call_identifier":"FWF","_id":"26736D6A-B435-11E9-9278-68D0E5697425"}],"doi":"10.1038/s41594-023-01201-6","keyword":["Molecular Biology","Structural Biology"],"quality_controlled":"1","dataavailabilitystatement":"The electron microscopy density maps of the A10 trimer and the hexameric flower-shaped pore, the subtomogram average of the palisade layer and representative tomograms for complete viruses as well as isolated cores have been deposited in the Electron Microscopy Data Bank under accession codes: EMD-17410, EMD-17411, EMD-17412, EMD-17413, EMD-17414 and EMD-18452.\r\n\r\nThe refined model of the A10 trimer has been deposited in the Protein Data Bank accession code: PDB 8P4K.\r\n\r\nThe UniProt codes of VACV core proteins used for structure prediction are: A10 (P16715), A3 (P06440), A4 (P29191) and L4 (P03295).\r\n\r\nGenBank Protein IDs of variola virus A10 (ABF23487.1), monkeypox virus A10 (YP_010377118.1), rabbitpox virus A10 (AAS49831.1), cowpox virus A10 (ADZ29251.1), ectromelia virus A10 (NP_671631.1), orf virus P4a (AY386264.1), Amsacta moorei entomopoxvirus AMV139 (NP_064921.1) and Melanoplus sanguinipes entomopoxvirus putative core protein P4a homolog (AF063866.1) were used for protein sequence alignment. Source data for MS experiments are provided as Supplementary Information accompanying this manuscript.","intvolume":"        31","oa":1,"das_tickbox":"1","date_updated":"2026-10-02T11:21:19Z","oa_version":"Published Version","file_date_updated":"2024-07-22T11:27:22Z","OA_place":"publisher","researchdata_availability":"yes","related_material":{"record":[{"id":"18766","relation":"dissertation_contains","status":"public"}],"link":[{"description":"News on ISTA Website","url":"https://ista.ac.at/en/news/down-to-the-core-of-poxviruses/","relation":"press_release"}]},"title":"Multi-modal cryo-EM reveals trimers of protein A10 to form the palisade layer in poxvirus cores","author":[{"orcid":"0000-0002-3616-8580","full_name":"Datler, Julia","id":"3B12E2E6-F248-11E8-B48F-1D18A9856A87","last_name":"Datler","first_name":"Julia"},{"orcid":"0000-0001-7967-2085","id":"1063c618-6f9b-11ec-9123-f912fccded63","full_name":"Hansen, Jesse","last_name":"Hansen","first_name":"Jesse"},{"last_name":"Thader","first_name":"Andreas","full_name":"Thader, Andreas","id":"3A18A7B8-F248-11E8-B48F-1D18A9856A87"},{"id":"45BF87EE-F248-11E8-B48F-1D18A9856A87","full_name":"Schlögl, Alois","last_name":"Schlögl","first_name":"Alois","orcid":"0000-0002-5621-8100"},{"id":"0c894dcf-897b-11ed-a09c-8186353224b0","full_name":"Bauer, Lukas W","last_name":"Bauer","first_name":"Lukas W"},{"full_name":"Hodirnau, Victor-Valentin","id":"3661B498-F248-11E8-B48F-1D18A9856A87","first_name":"Victor-Valentin","last_name":"Hodirnau","orcid":"0000-0003-3904-947X"},{"full_name":"Schur, Florian KM","id":"48AD8942-F248-11E8-B48F-1D18A9856A87","first_name":"Florian KM","last_name":"Schur","orcid":"0000-0003-4790-8078"}],"APC_amount":"11700 EUR","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"journal_article","article_processing_charge":"Yes (in subscription journal)","ddc":["570"],"volume":31,"publication":"Nature Structural & Molecular Biology"},{"publication_identifier":{"issn":["2663-337X"]},"abstract":[{"lang":"eng","text":"Understanding the relationship between a given phenotype and its underlying genotype or genotypes is one of the most pressing challenges of biology, as it lies at the heart of not only basic understanding of evolutionary theory, but also of practical applications in medicine and bioengineering. Understanding this relationship is complicated by the ubiquitous phenomenon of epistasis, wherein mutation effects are dependent on their genetic context. Fitness landscapes — representations of phenotype as a function of genotype — are being increasingly used as a tool to study the effects and interactions of thousands of mutations, but are experimentally limited to exploring a small fraction of a protein’s theoretical sequence space. Furthermore, not all regions of said sequence space are necessarily equally informative. Thus, gene selection for landscape surveys should be carefully considered in order to maximize the usable output of necessarily limited data.\r\n\r\nIn this work, we analyzed the fitness landscapes of orthologous green fluorescent proteins from four different species, by systematically measuring the phenotype, fluorescence, of tens of thousands of mutant genotypes from each protein. These landscapes were highly heterogeneous, with some genes being mutationally robust and displaying epistasis only rarely, and others being highly epistatic and mutationally fragile. We used this data to train machine learning models to predict fluorescence from genotype. Although the training data contained almost exclusively genotypes with less than 3% sequence divergence from the original wild-type sequences, we were able to create novel, functional genotypes with up to 20% sequence divergence. Counterintuitively however, genes with high mutational robustness and rare epistasis were more difficult to introduce large numbers of mutations into, not less. This represents the first study of large-scale fitness landscapes of a protein family, and provides insights into how to approach future landscape surveys and their applications in novel protein design."}],"date_created":"2024-09-06T12:57:44Z","year":"2024","publication_status":"published","has_accepted_license":"1","acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"ScienComp"}],"file":[{"access_level":"open_access","file_id":"18151","file_name":"louisa_thesis_draft__240904b.pdf","date_created":"2024-09-27T10:32:33Z","creator":"lgonzale","content_type":"application/pdf","date_updated":"2024-09-27T10:32:33Z","relation":"main_file","file_size":11219837,"checksum":"d3303724e8d3c91321d71bbad4062048"},{"file_name":"louisa_thesis_draft__240904b.docx","file_id":"18152","access_level":"closed","creator":"lgonzale","date_created":"2024-09-27T10:34:34Z","date_updated":"2024-09-27T10:34:34Z","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","checksum":"22e63f7f9014dffde2af7a47e7d1d014","file_size":43338677,"relation":"source_file"}],"publisher":"Institute of Science and Technology Austria","month":"09","_id":"17850","supervisor":[{"orcid":"0000-0001-8243-4694","id":"44FDEF62-F248-11E8-B48F-1D18A9856A87","full_name":"Kondrashov, Fyodor","last_name":"Kondrashov","first_name":"Fyodor"}],"supplementarymaterial":"no","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png"},"ec_funded":1,"fulldoi":"https://doi.org/10.15479/at:ista:17850","language":[{"iso":"eng"}],"status":"public","doi_confirm":"1","date_published":"2024-09-06T00:00:00Z","department":[{"_id":"GradSch"},{"_id":"FyKo"}],"corr_author":"1","article_processing_charge":"No","author":[{"orcid":"0000-0001-9139-5383","full_name":"Gonzalez Somermeyer, Louisa","id":"4720D23C-F248-11E8-B48F-1D18A9856A87","last_name":"Gonzalez Somermeyer","first_name":"Louisa"}],"title":"Fitness landscapes of orthologous green fluorescent proteins","type":"dissertation","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","degree_awarded":"PhD","ddc":["570"],"date_updated":"2026-10-02T11:21:41Z","oa_version":"Published Version","das_tickbox":"0","alternative_title":["ISTA Thesis"],"researchdata_availability":"no","related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"11448"}],"link":[{"relation":"software","url":"https://github.com/aequorea238/Orthologous_GFP_Fitness_Peaks"}]},"file_date_updated":"2024-09-27T10:34:34Z","OA_place":"publisher","doi":"10.15479/at:ista:17850","project":[{"call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","name":"International IST Doctoral Program"},{"grant_number":"771209","name":"Characterizing the fitness landscape on population and global scales","_id":"26580278-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"oa":1,"day":"06","page":"89","citation":{"ista":"Gonzalez Somermeyer L. 2024. Fitness landscapes of orthologous green fluorescent proteins. Institute of Science and Technology Austria.","ama":"Gonzalez Somermeyer L. Fitness landscapes of orthologous green fluorescent proteins. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:17850\">10.15479/at:ista:17850</a>","apa":"Gonzalez Somermeyer, L. (2024). <i>Fitness landscapes of orthologous green fluorescent proteins</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:17850\">https://doi.org/10.15479/at:ista:17850</a>","ieee":"L. Gonzalez Somermeyer, “Fitness landscapes of orthologous green fluorescent proteins,” Institute of Science and Technology Austria, 2024.","mla":"Gonzalez Somermeyer, Louisa. <i>Fitness Landscapes of Orthologous Green Fluorescent Proteins</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:17850\">10.15479/at:ista:17850</a>.","short":"L. Gonzalez Somermeyer, Fitness Landscapes of Orthologous Green Fluorescent Proteins, Institute of Science and Technology Austria, 2024.","chicago":"Gonzalez Somermeyer, Louisa. “Fitness Landscapes of Orthologous Green Fluorescent Proteins.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:17850\">https://doi.org/10.15479/at:ista:17850</a>."}},{"article_type":"original","day":"11","citation":{"ista":"Nomura K, Rella S, Merritt H, Baltussen M, Bird D, Tjuka A, Falk D. 2024. Tipping points of space debris in low earth orbit. International Journal of the Commons. 18(1).","apa":"Nomura, K., Rella, S., Merritt, H., Baltussen, M., Bird, D., Tjuka, A., &#38; Falk, D. (2024). Tipping points of space debris in low earth orbit. <i>International Journal of the Commons</i>. Ubiquity Press. <a href=\"https://doi.org/10.5334/ijc.1275\">https://doi.org/10.5334/ijc.1275</a>","ama":"Nomura K, Rella S, Merritt H, et al. Tipping points of space debris in low earth orbit. <i>International Journal of the Commons</i>. 2024;18(1). doi:<a href=\"https://doi.org/10.5334/ijc.1275\">10.5334/ijc.1275</a>","ieee":"K. Nomura <i>et al.</i>, “Tipping points of space debris in low earth orbit,” <i>International Journal of the Commons</i>, vol. 18, no. 1. Ubiquity Press, 2024.","chicago":"Nomura, Keiko, Simon Rella, Haily Merritt, Mathieu Baltussen, Darcy Bird, Annika Tjuka, and Dan Falk. “Tipping Points of Space Debris in Low Earth Orbit.” <i>International Journal of the Commons</i>. Ubiquity Press, 2024. <a href=\"https://doi.org/10.5334/ijc.1275\">https://doi.org/10.5334/ijc.1275</a>.","short":"K. Nomura, S. Rella, H. Merritt, M. Baltussen, D. Bird, A. Tjuka, D. Falk, International Journal of the Commons 18 (2024).","mla":"Nomura, Keiko, et al. “Tipping Points of Space Debris in Low Earth Orbit.” <i>International Journal of the Commons</i>, vol. 18, no. 1, Ubiquity Press, 2024, doi:<a href=\"https://doi.org/10.5334/ijc.1275\">10.5334/ijc.1275</a>."},"keyword":["Sociology and Political Science"],"doi":"10.5334/ijc.1275","quality_controlled":"1","intvolume":"        18","oa":1,"oa_version":"Published Version","das_tickbox":"0","date_updated":"2026-10-02T11:22:03Z","file_date_updated":"2024-02-05T10:06:35Z","researchdata_availability":"no","title":"Tipping points of space debris in low earth orbit","author":[{"last_name":"Nomura","first_name":"Keiko","full_name":"Nomura, Keiko"},{"full_name":"Rella, Simon","id":"B4765ACA-AA38-11E9-AC9A-0930E6697425","last_name":"Rella","first_name":"Simon"},{"first_name":"Haily","last_name":"Merritt","full_name":"Merritt, Haily"},{"full_name":"Baltussen, Mathieu","last_name":"Baltussen","first_name":"Mathieu"},{"last_name":"Bird","first_name":"Darcy","full_name":"Bird, Darcy"},{"first_name":"Annika","last_name":"Tjuka","full_name":"Tjuka, Annika"},{"first_name":"Dan","last_name":"Falk","full_name":"Falk, Dan"}],"type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_processing_charge":"Yes","ddc":["550"],"volume":18,"publication":"International Journal of the Commons","status":"public","language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"GaTk"}],"scopus_import":"1","date_published":"2024-01-11T00:00:00Z","acknowledgement":"The authors would like to thank the special issue co-editors, Marco Janssen and Xiao-Shan Yap, and the anonymous reviewers for their comments that helped improve the manuscript. The paper also benefited from suggestions by other author participants in this special issue. We would also like to thank the 2022 Santa Fe Institute Complex Systems Summer School for providing space to initiate this study.","supplementarymaterial":"yes","fulldoi":"https://doi.org/10.5334/ijc.1275","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"issue":"1","file":[{"file_name":"2023_IntJourCommons_Nomura.pdf","file_id":"14939","access_level":"open_access","creator":"dernst","success":1,"date_created":"2024-02-05T10:06:35Z","date_updated":"2024-02-05T10:06:35Z","content_type":"application/pdf","file_size":1305786,"checksum":"b80ebc889033c365d8f8c05a0c655382","relation":"main_file"}],"publisher":"Ubiquity Press","publication_status":"published","has_accepted_license":"1","month":"01","_id":"14901","publication_identifier":{"issn":["1875-0281"]},"year":"2024","abstract":[{"lang":"eng","text":"Global services like navigation, communication, and Earth observation have increased dramatically in the 21st century due to advances in outer space industries. But as orbits become increasingly crowded with both satellites and inevitable space debris pollution, continued operations become endangered by the heightened risks of debris collisions in orbit. Kessler Syndrome is the term for when a critical threshold of orbiting debris triggers a runaway positive feedback loop of debris collisions, creating debris congestion that can render orbits unusable. As this potential tipping point becomes more widely recognized, there have been renewed calls for debris mitigation and removal. Here, we combine complex systems and social-ecological systems approaches to study how these efforts may affect space debris accumulation and the likelihood of reaching Kessler Syndrome. Specifically, we model how debris levels are affected by future launch rates, cleanup activities, and collisions between extant debris. We contextualize and interpret our dynamic model within a discussion of existing space debris governance and other social, economic, and geopolitical factors that may influence effective collective management of the orbital commons. In line with previous studies, our model finds that debris congestion may be reached in less than 200 years, though a holistic management strategy combining removal and mitigation actions can avoid such outcomes while continuing space activities. Moreover, although active debris removal may be particularly effective, the current lack of market and governance support may impede its implementation. Research into these critical dynamics and the multi-faceted variables that influence debris outcomes can support policymakers in curating impactful governance strategies and realistic transition pathways to sustaining debris-free orbits. Overall, our study is useful for communicating about space debris sustainability in policy and education settings by providing an exploration of policy portfolio options supported by a simple and clear social-ecological modeling approach."}],"date_created":"2024-01-30T11:58:02Z"},{"page":"111","day":"18","citation":{"ista":"Sagi O. 2024. Hybrid circuits on planar Germanium. Institute of Science and Technology Austria.","ama":"Sagi O. Hybrid circuits on planar Germanium. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:18076\">10.15479/at:ista:18076</a>","apa":"Sagi, O. (2024). <i>Hybrid circuits on planar Germanium</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:18076\">https://doi.org/10.15479/at:ista:18076</a>","ieee":"O. Sagi, “Hybrid circuits on planar Germanium,” Institute of Science and Technology Austria, 2024.","mla":"Sagi, Oliver. <i>Hybrid Circuits on Planar Germanium</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:18076\">10.15479/at:ista:18076</a>.","chicago":"Sagi, Oliver. “Hybrid Circuits on Planar Germanium.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:18076\">https://doi.org/10.15479/at:ista:18076</a>.","short":"O. Sagi, Hybrid Circuits on Planar Germanium, Institute of Science and Technology Austria, 2024."},"project":[{"_id":"bd8bd29e-d553-11ed-ba76-f0070d4b237a","name":"Merging spin and superconducting qubits in planar Ge","grant_number":"P36507"},{"_id":"c0977eea-5a5b-11eb-8a69-a862db0cf4d1","grant_number":"I05060","name":"High impedance circuit quantum electrodynamics with hole spins"},{"name":"Hybrid Semiconductor - Superconductor Quantum Devices","_id":"262116AA-B435-11E9-9278-68D0E5697425"},{"grant_number":"862046","name":"TOPOLOGICALLY PROTECTED AND SCALABLE QUANTUM BITS","call_identifier":"H2020","_id":"237E5020-32DE-11EA-91FC-C7463DDC885E"}],"doi":"10.15479/at:ista:18076","oa":1,"alternative_title":["ISTA Thesis"],"das_tickbox":"0","oa_version":"Published Version","date_updated":"2026-10-02T11:22:29Z","file_date_updated":"2024-09-19T09:20:33Z","OA_place":"publisher","related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"17202"}]},"researchdata_availability":"no","title":"Hybrid circuits on planar Germanium","author":[{"id":"71616374-A8E9-11E9-A7CA-09ECE5697425","full_name":"Sagi, Oliver","first_name":"Oliver","last_name":"Sagi"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"dissertation","article_processing_charge":"No","ddc":["539"],"degree_awarded":"PhD","status":"public","language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"GeKa"}],"corr_author":"1","doi_confirm":"1","date_published":"2024-09-18T00:00:00Z","supplementarymaterial":"yes","fulldoi":"https://doi.org/10.15479/at:ista:18076","tmp":{"name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","image":"/images/cc_by_nc_sa.png"},"ec_funded":1,"publisher":"Institute of Science and Technology Austria","file":[{"file_id":"18093","access_level":"open_access","file_name":"OliverSagi_Thesis_pdfa.pdf","date_created":"2024-09-18T14:13:01Z","success":1,"creator":"osagi","content_type":"application/pdf","date_updated":"2024-09-18T14:13:01Z","relation":"main_file","checksum":"d01d0e2846c2f3ac5bb14d321554a4cd","file_size":86679095},{"access_level":"local","file_id":"18094","file_name":"Thesis_OliverSagi.zip","date_created":"2024-09-18T14:14:02Z","creator":"osagi","content_type":"application/x-zip-compressed","date_updated":"2024-09-19T09:20:33Z","relation":"source_file","file_size":172098524,"checksum":"0543f473d509ee545f4ed3a56f742f4b"}],"publication_status":"published","acknowledged_ssus":[{"_id":"NanoFab"},{"_id":"M-Shop"}],"has_accepted_license":"1","month":"09","_id":"18076","supervisor":[{"first_name":"Georgios","last_name":"Katsaros","id":"38DB5788-F248-11E8-B48F-1D18A9856A87","full_name":"Katsaros, Georgios","orcid":"0000-0001-8342-202X"}],"publication_identifier":{"issn":["2663-337X"]},"year":"2024","abstract":[{"lang":"eng","text":"The new era of Ge has opened up new possibilities in quantum computing. The maturity of Ge\r\nspin qubits is unquestioned, while hybrid semiconductor-superconductor Ge circuits are on track\r\nto enter the game. Gate-tunable transmons (gatemons) employing semiconductor Josephson\r\njunctions have recently emerged as building blocks for such hybrid quantum circuits. In this\r\nthesis, we present a gatemon fabricated in planar Germanium. We induce superconductivity\r\nin a two-dimensional hole gas by evaporating aluminum atop a thin spacer, which separates\r\nthe superconductor from the Ge quantum well. The Josephson junction is then integrated\r\ninto an Xmon circuit and capacitively coupled to a transmission line resonator. We showcase\r\nthe qubit tunability in a broad frequency range with resonator and two-tone spectroscopy.\r\nTime-domain characterizations reveal energy relaxation and coherence times up to 75 ns. Our\r\nresults, combined with the recent advances in the spin qubit field, pave the way towards novel\r\nhybrid and protected qubits in a group IV, CMOS-compatible material."}],"date_created":"2024-09-16T12:58:36Z"},{"publication_identifier":{"eissn":["1868-8969"],"isbn":["9783959773164"]},"year":"2024","date_created":"2024-06-25T11:45:58Z","abstract":[{"text":"In this article we extend and strengthen the seminal work by Niyogi, Smale, and Weinberger on the learning of the homotopy type from a sample of an underlying space. In their work, Niyogi, Smale, and Weinberger studied samples of C² manifolds with positive reach embedded in ℝ^d. We extend their results in the following ways: - As the ambient space we consider both ℝ^d and Riemannian manifolds with lower bounded sectional curvature. - In both types of ambient spaces, we study sets of positive reach - a significantly more general setting than C² manifolds - as well as general manifolds of positive reach. - The sample P of a set (or a manifold) 𝒮 of positive reach may be noisy. We work with two one-sided Hausdorff distances - ε and δ - between P and 𝒮. We provide tight bounds in terms of ε and δ, that guarantee that there exists a parameter r such that the union of balls of radius r centred at the sample P deformation-retracts to 𝒮. We exhibit their tightness by an explicit construction. We carefully distinguish the roles of δ and ε. This is not only essential to achieve tight bounds, but also sensible in practical situations, since it allows one to adapt the bound according to sample density and the amount of noise present in the sample separately.","lang":"eng"}],"external_id":{"arxiv":["2206.10485"]},"file":[{"checksum":"6a2ddc8b51aa58f197a8b294750f1f8d","file_size":20886142,"relation":"main_file","date_updated":"2024-06-25T11:47:26Z","content_type":"application/pdf","creator":"cfillmor","date_created":"2024-06-25T11:47:26Z","success":1,"file_name":"LIPIcs.SoCG.2024.11.pdf","access_level":"open_access","file_id":"17171"}],"publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","has_accepted_license":"1","publication_status":"published","month":"06","_id":"17170","supplementarymaterial":"no","arxiv":1,"fulldoi":"https://doi.org/10.4230/LIPIcs.SoCG.2024.11","ec_funded":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"status":"public","language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"HeEd"}],"scopus_import":"1","acknowledgement":"This research has been supported by the European Research Council (ERC), grant No. 788183, by the Wittgenstein Prize, Austrian Science Fund (FWF), grant No. Z 342-N31, and by the DFG Collaborative Research Center TRR 109, Austrian Science Fund (FWF), grant No. I 02979-N35.\r\nWintraecken, Mathijs: Supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754411, the Austrian science fund (FWF) grant No. M-3073, and the welcome package from IDEX of the Université Côte d'Azur.","date_published":"2024-06-06T00:00:00Z","conference":{"location":"Athens, Greece","end_date":"2024-06-14","start_date":"2024-06-11","name":"SoCG: Symposium on Computational Geometry"},"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"conference","author":[{"full_name":"Attali, Dominique","last_name":"Attali","first_name":"Dominique"},{"last_name":"Kourimska","first_name":"Hana","full_name":"Kourimska, Hana","id":"D9B8E14C-3C26-11EA-98F5-1F833DDC885E","orcid":"0000-0001-7841-0091"},{"first_name":"Christopher D","last_name":"Fillmore","full_name":"Fillmore, Christopher D","id":"35638A5C-AAC7-11E9-B0BF-5503E6697425"},{"full_name":"Ghosh, Ishika","id":"ee449b28-344d-11ef-a6d5-9ca430e9e9ff","first_name":"Ishika","last_name":"Ghosh"},{"full_name":"Lieutier, André","last_name":"Lieutier","first_name":"André"},{"orcid":"0000-0002-6862-208X","first_name":"Elizabeth R","last_name":"Stephenson","full_name":"Stephenson, Elizabeth R","id":"2D04F932-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-7472-2220","full_name":"Wintraecken, Mathijs","id":"307CFBC8-F248-11E8-B48F-1D18A9856A87","last_name":"Wintraecken","first_name":"Mathijs"}],"title":"Tight bounds for the learning of homotopy à la Niyogi, Smale, and Weinberger for subsets of euclidean spaces and of Riemannian manifolds","article_processing_charge":"No","ddc":["516"],"publication":"40th International Symposium on Computational Geometry","volume":293,"oa_version":"Published Version","alternative_title":["LIPIcs"],"das_tickbox":"0","date_updated":"2026-10-02T11:23:43Z","file_date_updated":"2024-06-25T11:47:26Z","researchdata_availability":"no","project":[{"name":"Alpha Shape Theory Extended","grant_number":"788183","call_identifier":"H2020","_id":"266A2E9E-B435-11E9-9278-68D0E5697425"},{"grant_number":"Z00342","name":"Mathematics, Computer Science","_id":"268116B8-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"},{"call_identifier":"FWF","_id":"2561EBF4-B435-11E9-9278-68D0E5697425","name":"Persistence and stability of geometric complexes","grant_number":"I02979-N35"},{"grant_number":"M03073","name":"Learning and triangulating manifolds via collapses","_id":"fc390959-9c52-11eb-aca3-afa58bd282b2"}],"doi":"10.4230/LIPIcs.SoCG.2024.11","quality_controlled":"1","oa":1,"intvolume":"       293","page":"11:1-11:19","day":"06","citation":{"ama":"Attali D, Kourimska H, Fillmore CD, et al. Tight bounds for the learning of homotopy à la Niyogi, Smale, and Weinberger for subsets of euclidean spaces and of Riemannian manifolds. In: <i>40th International Symposium on Computational Geometry</i>. Vol 293. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2024:11:1-11:19. doi:<a href=\"https://doi.org/10.4230/LIPIcs.SoCG.2024.11\">10.4230/LIPIcs.SoCG.2024.11</a>","apa":"Attali, D., Kourimska, H., Fillmore, C. D., Ghosh, I., Lieutier, A., Stephenson, E. R., &#38; Wintraecken, M. (2024). Tight bounds for the learning of homotopy à la Niyogi, Smale, and Weinberger for subsets of euclidean spaces and of Riemannian manifolds. In <i>40th International Symposium on Computational Geometry</i> (Vol. 293, p. 11:1-11:19). Athens, Greece: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.SoCG.2024.11\">https://doi.org/10.4230/LIPIcs.SoCG.2024.11</a>","ista":"Attali D, Kourimska H, Fillmore CD, Ghosh I, Lieutier A, Stephenson ER, Wintraecken M. 2024. Tight bounds for the learning of homotopy à la Niyogi, Smale, and Weinberger for subsets of euclidean spaces and of Riemannian manifolds. 40th International Symposium on Computational Geometry. SoCG: Symposium on Computational Geometry, LIPIcs, vol. 293, 11:1-11:19.","mla":"Attali, Dominique, et al. “Tight Bounds for the Learning of Homotopy à La Niyogi, Smale, and Weinberger for Subsets of Euclidean Spaces and of Riemannian Manifolds.” <i>40th International Symposium on Computational Geometry</i>, vol. 293, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024, p. 11:1-11:19, doi:<a href=\"https://doi.org/10.4230/LIPIcs.SoCG.2024.11\">10.4230/LIPIcs.SoCG.2024.11</a>.","chicago":"Attali, Dominique, Hana Kourimska, Christopher D Fillmore, Ishika Ghosh, André Lieutier, Elizabeth R Stephenson, and Mathijs Wintraecken. “Tight Bounds for the Learning of Homotopy à La Niyogi, Smale, and Weinberger for Subsets of Euclidean Spaces and of Riemannian Manifolds.” In <i>40th International Symposium on Computational Geometry</i>, 293:11:1-11:19. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024. <a href=\"https://doi.org/10.4230/LIPIcs.SoCG.2024.11\">https://doi.org/10.4230/LIPIcs.SoCG.2024.11</a>.","short":"D. Attali, H. Kourimska, C.D. Fillmore, I. Ghosh, A. Lieutier, E.R. Stephenson, M. Wintraecken, in:, 40th International Symposium on Computational Geometry, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024, p. 11:1-11:19.","ieee":"D. Attali <i>et al.</i>, “Tight bounds for the learning of homotopy à la Niyogi, Smale, and Weinberger for subsets of euclidean spaces and of Riemannian manifolds,” in <i>40th International Symposium on Computational Geometry</i>, Athens, Greece, 2024, vol. 293, p. 11:1-11:19."}},{"oa":1,"intvolume":"        15","quality_controlled":"1","dataavailabilitystatement":"All experimental data included in this work will be available at the ISTA Research Data Repository","doi":"10.1038/s41467-024-50763-6","project":[{"grant_number":"P36507","name":"Merging spin and superconducting qubits in planar Ge","_id":"bd8bd29e-d553-11ed-ba76-f0070d4b237a"},{"grant_number":"I05060","name":"High impedance circuit quantum electrodynamics with hole spins","_id":"c0977eea-5a5b-11eb-8a69-a862db0cf4d1"},{"_id":"262116AA-B435-11E9-9278-68D0E5697425","name":"Hybrid Semiconductor - Superconductor Quantum Devices"},{"name":"FWF Open Access Fund","_id":"3AC91DDA-15DF-11EA-824D-93A3E7B544D1","call_identifier":"FWF"}],"citation":{"ista":"Sagi O, Crippa A, Valentini M, Janik M, Baghumyan L, Fabris G, Kapoor L, Hassani F, Fink JM, Calcaterra S, Chrastina D, Isella G, Katsaros G. 2024. A gate tunable transmon qubit in planar Ge. Nature Communications. 15, 6400.","apa":"Sagi, O., Crippa, A., Valentini, M., Janik, M., Baghumyan, L., Fabris, G., … Katsaros, G. (2024). A gate tunable transmon qubit in planar Ge. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-024-50763-6\">https://doi.org/10.1038/s41467-024-50763-6</a>","ama":"Sagi O, Crippa A, Valentini M, et al. A gate tunable transmon qubit in planar Ge. <i>Nature Communications</i>. 2024;15. doi:<a href=\"https://doi.org/10.1038/s41467-024-50763-6\">10.1038/s41467-024-50763-6</a>","ieee":"O. Sagi <i>et al.</i>, “A gate tunable transmon qubit in planar Ge,” <i>Nature Communications</i>, vol. 15. Springer Nature, 2024.","short":"O. Sagi, A. Crippa, M. Valentini, M. Janik, L. Baghumyan, G. Fabris, L. Kapoor, F. Hassani, J.M. Fink, S. Calcaterra, D. Chrastina, G. Isella, G. Katsaros, Nature Communications 15 (2024).","chicago":"Sagi, Oliver, Alessandro Crippa, Marco Valentini, Marian Janik, Levon Baghumyan, Giorgio Fabris, Lucky Kapoor, et al. “A Gate Tunable Transmon Qubit in Planar Ge.” <i>Nature Communications</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41467-024-50763-6\">https://doi.org/10.1038/s41467-024-50763-6</a>.","mla":"Sagi, Oliver, et al. “A Gate Tunable Transmon Qubit in Planar Ge.” <i>Nature Communications</i>, vol. 15, 6400, Springer Nature, 2024, doi:<a href=\"https://doi.org/10.1038/s41467-024-50763-6\">10.1038/s41467-024-50763-6</a>."},"day":"30","article_type":"original","publication":"Nature Communications","volume":15,"ddc":["530"],"article_processing_charge":"Yes","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"journal_article","author":[{"last_name":"Sagi","first_name":"Oliver","full_name":"Sagi, Oliver","id":"71616374-A8E9-11E9-A7CA-09ECE5697425"},{"last_name":"Crippa","first_name":"Alessandro","full_name":"Crippa, Alessandro","id":"1F2B21A2-F6E7-11E9-9B82-F7DBE5697425","orcid":"0000-0002-2968-611X"},{"id":"C0BB2FAC-D767-11E9-B658-BC13E6697425","full_name":"Valentini, Marco","last_name":"Valentini","first_name":"Marco"},{"orcid":"0009-0003-9037-8831","id":"396A1950-F248-11E8-B48F-1D18A9856A87","full_name":"Janik, Marian","first_name":"Marian","last_name":"Janik"},{"last_name":"Baghumyan","first_name":"Levon","full_name":"Baghumyan, Levon","id":"7aa1f788-b527-11ee-aa9e-e6111a79e0c7"},{"last_name":"Fabris","first_name":"Giorgio","full_name":"Fabris, Giorgio","id":"298cf6f3-1ff6-11ee-9fa6-d94cfa0b3352"},{"first_name":"Lucky","last_name":"Kapoor","full_name":"Kapoor, Lucky","id":"84b9700b-15b2-11ec-abd3-831089e67615","orcid":"0000-0001-8319-2148"},{"first_name":"Farid","last_name":"Hassani","id":"2AED110C-F248-11E8-B48F-1D18A9856A87","full_name":"Hassani, Farid","orcid":"0000-0001-6937-5773"},{"full_name":"Fink, Johannes M","id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","first_name":"Johannes M","last_name":"Fink","orcid":"0000-0001-8112-028X"},{"last_name":"Calcaterra","first_name":"Stefano","full_name":"Calcaterra, Stefano"},{"full_name":"Chrastina, Daniel","last_name":"Chrastina","first_name":"Daniel"},{"last_name":"Isella","first_name":"Giovanni","full_name":"Isella, Giovanni"},{"orcid":"0000-0001-8342-202X","last_name":"Katsaros","first_name":"Georgios","full_name":"Katsaros, Georgios","id":"38DB5788-F248-11E8-B48F-1D18A9856A87"}],"title":"A gate tunable transmon qubit in planar Ge","APC_amount":"6828 EUR","related_material":{"link":[{"relation":"erratum","url":"https://doi.org/10.1038/s41467-024-53910-1"}],"record":[{"id":"18076","relation":"dissertation_contains","status":"public"},{"id":"17196","relation":"research_data","status":"public"}]},"researchdata_availability":"yes","OA_place":"publisher","file_date_updated":"2024-08-05T08:38:01Z","oa_version":"Published Version","date_updated":"2026-10-02T11:23:23Z","das_tickbox":"1","isi":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"fulldoi":"https://doi.org/10.1038/s41467-024-50763-6","pmid":1,"supplementarymaterial":"yes","arxiv":1,"article_number":"6400","acknowledgement":"We acknowledge Lucas Casparis, Jeroen Danon, Valla Fatemi, Morten Kjaergard and Javad Shabani for their valuable insights and comments. This research was supported by the Scientific Service Units of ISTA through resources provided by the MIBA Machine Shop\r\nand the Nanofabrication facility. This research and related results were made possible with the support of the NOMIS Foundation and the FWF Projects with DOI:10.55776/I5060 and DOI:10.55776/P36507. We also acknowledge the NextGenerationEU PRIN project\r\n2022A8CJP3 (GAMESQUAD) for partial financial support.","date_published":"2024-07-30T00:00:00Z","corr_author":"1","scopus_import":"1","department":[{"_id":"GeKa"},{"_id":"JoFi"},{"_id":"GradSch"}],"DOAJ_listed":"1","language":[{"iso":"eng"}],"status":"public","OA_type":"gold","date_created":"2024-07-04T11:40:45Z","abstract":[{"text":"Gate-tunable transmons (gatemons) employing semiconductor Josephson junctions have recently emerged as building blocks for hybrid quantum circuits. In this study, we present a gatemon fabricated in planar Germanium. We induce superconductivity in a two-dimensional hole gas by evaporating aluminum atop a thin spacer, which separates the superconductor from the Ge quantum well. The Josephson junction is then integrated into an Xmon circuit and capacitively coupled to a transmission line resonator. We showcase the qubit tunability in a broad frequency range with resonator and two-tone spectroscopy. Time-domain characterizations reveal energy relaxation and coherence times up to 75 ns. Our results, combined with the recent advances in the spin qubit field, pave the way towards novel hybrid and protected qubits in a group IV, CMOS-compatible material.","lang":"eng"}],"year":"2024","publication_identifier":{"eissn":["2041-1723"]},"_id":"17202","month":"07","has_accepted_license":"1","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"M-Shop"},{"_id":"NanoFab"}],"publication_status":"published","external_id":{"isi":["001281271000022"],"pmid":["39080279"],"arxiv":["2403.16774"]},"publisher":"Springer Nature","file":[{"file_size":1928001,"checksum":"ddf5361dcb6c543e2cea818501c09910","relation":"main_file","date_updated":"2024-08-05T08:38:01Z","content_type":"application/pdf","creator":"dernst","success":1,"date_created":"2024-08-05T08:38:01Z","file_name":"2024_NatureComm_Sagi.pdf","access_level":"open_access","file_id":"17388"}]},{"title":"A gate-tunable transmon in planar Ge","author":[{"full_name":"Sagi, Oliver","id":"71616374-A8E9-11E9-A7CA-09ECE5697425","first_name":"Oliver","last_name":"Sagi"}],"type":"research_data","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_processing_charge":"No","ddc":["530"],"oa_version":"Published Version","date_updated":"2026-10-02T11:23:23Z","file_date_updated":"2024-07-04T10:11:40Z","related_material":{"record":[{"id":"17202","relation":"used_in_publication","status":"public"}]},"project":[{"_id":"c0977eea-5a5b-11eb-8a69-a862db0cf4d1","name":"High impedance circuit quantum electrodynamics with hole spins","grant_number":"I05060"},{"name":"Hybrid Semiconductor - Superconductor Quantum Devices","_id":"262116AA-B435-11E9-9278-68D0E5697425"},{"grant_number":"P36507","name":"Merging spin and superconducting qubits in planar Ge","_id":"bd8bd29e-d553-11ed-ba76-f0070d4b237a"}],"doi":"10.15479/AT:ISTA:17196","oa":1,"day":"04","contributor":[{"orcid":"0000-0002-2968-611X","contributor_type":"project_member","id":"1F2B21A2-F6E7-11E9-9B82-F7DBE5697425","last_name":"Crippa","first_name":"Alessandro"},{"contributor_type":"project_member","id":"C0BB2FAC-D767-11E9-B658-BC13E6697425","last_name":"Valentini","first_name":"Marco"},{"contributor_type":"project_member","id":"396A1950-F248-11E8-B48F-1D18A9856A87","first_name":"Marian","last_name":"Janik"},{"contributor_type":"project_member","last_name":"Baghumyan","first_name":"Levon","id":"7aa1f788-b527-11ee-aa9e-e6111a79e0c7"},{"id":"298cf6f3-1ff6-11ee-9fa6-d94cfa0b3352","first_name":"Giorgio","last_name":"Fabris","contributor_type":"project_member"},{"contributor_type":"project_member","first_name":"Lucky","last_name":"Kapoor","id":"84b9700b-15b2-11ec-abd3-831089e67615"},{"last_name":"Hassani","first_name":"Farid","id":"2AED110C-F248-11E8-B48F-1D18A9856A87","contributor_type":"project_member","orcid":"0000-0001-6937-5773"},{"id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","first_name":"Johannes M","last_name":"Fink","orcid":"0000-0001-8112-028X","contributor_type":"project_member"},{"contributor_type":"project_member","first_name":"Stefano","last_name":"Calcaterra"},{"first_name":"Daniel","last_name":"Chrastina","contributor_type":"project_member"},{"last_name":"Isella","first_name":"Giovanni","contributor_type":"project_member"},{"first_name":"Georgios","last_name":"Katsaros","id":"38DB5788-F248-11E8-B48F-1D18A9856A87","contributor_type":"supervisor","orcid":"0000-0001-8342-202X"}],"citation":{"short":"O. Sagi, (2024).","chicago":"Sagi, Oliver. “A Gate-Tunable Transmon in Planar Ge.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/AT:ISTA:17196\">https://doi.org/10.15479/AT:ISTA:17196</a>.","mla":"Sagi, Oliver. <i>A Gate-Tunable Transmon in Planar Ge</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:17196\">10.15479/AT:ISTA:17196</a>.","ieee":"O. Sagi, “A gate-tunable transmon in planar Ge.” Institute of Science and Technology Austria, 2024.","apa":"Sagi, O. (2024). A gate-tunable transmon in planar Ge. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:17196\">https://doi.org/10.15479/AT:ISTA:17196</a>","ama":"Sagi O. A gate-tunable transmon in planar Ge. 2024. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:17196\">10.15479/AT:ISTA:17196</a>","ista":"Sagi O. 2024. A gate-tunable transmon in planar Ge, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:17196\">10.15479/AT:ISTA:17196</a>."},"year":"2024","abstract":[{"text":"This .zip File contains the data for the figures presented in the main text and supplementary material of \"A gate tunable transmon qubit in planar Ge\" by O.Sagi et al. The measurements were done using Qcodes. The description of the files and the instructions on opening the data can be found in the Readme. An additional Jupyter Notebook is attached that walks through the data analysis.","lang":"eng"}],"date_created":"2024-07-04T10:14:34Z","publisher":"Institute of Science and Technology Austria","file":[{"date_created":"2024-07-04T10:01:51Z","success":1,"creator":"osagi","access_level":"open_access","file_id":"17197","file_name":"GeGatemon_DataAnalysis.ipynb","relation":"main_file","checksum":"a9f640a0b72a92171353f3ea14406f0b","file_size":1960182,"content_type":"application/octet-stream","date_updated":"2024-07-04T10:01:51Z"},{"success":1,"date_created":"2024-07-04T10:01:50Z","creator":"osagi","access_level":"open_access","file_id":"17198","file_name":"OlSa_Readme.pptx","relation":"main_file","file_size":34194,"checksum":"f0feec931233e8e845ade56165c1588f","content_type":"application/vnd.openxmlformats-officedocument.presentationml.presentation","date_updated":"2024-07-04T10:01:50Z"},{"file_size":72939292,"checksum":"92bb11e3a508d736d01ff0738a1172c7","relation":"main_file","date_updated":"2024-07-04T10:11:16Z","content_type":"application/x-zip-compressed","creator":"osagi","success":1,"date_created":"2024-07-04T10:11:16Z","file_name":"Al_Transmon.zip","access_level":"open_access","file_id":"17199"},{"success":1,"date_created":"2024-07-04T10:11:40Z","creator":"osagi","file_id":"17200","access_level":"open_access","file_name":"Gatemon_RT_5nm_1.zip","relation":"main_file","file_size":465618029,"checksum":"871e96fe0ecc97581196e883045cd516","content_type":"application/x-zip-compressed","date_updated":"2024-07-04T10:11:40Z"},{"content_type":"application/x-zip-compressed","date_updated":"2024-07-04T10:11:35Z","relation":"main_file","file_size":281503513,"checksum":"a3e141af90f0104b7269c8a72370848a","file_id":"17201","access_level":"open_access","file_name":"Gatemon_RT_5nm_2.zip","success":1,"date_created":"2024-07-04T10:11:35Z","creator":"osagi"}],"has_accepted_license":"1","acknowledged_ssus":[{"_id":"NanoFab"},{"_id":"M-Shop"}],"month":"07","_id":"17196","fulldoi":"https://doi.org/10.15479/AT:ISTA:17196","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"status":"public","corr_author":"1","department":[{"_id":"GradSch"},{"_id":"GeKa"},{"_id":"JoFi"}],"doi_confirm":"1","date_published":"2024-07-04T00:00:00Z","acknowledgement":"This research was supported by the Scientific Service Units of ISTA through resources provided by the MIBA Machine Shop and the Nanofabrication facility. "},{"doi":"10.1093/jxb/erae246","quality_controlled":"1","oa":1,"intvolume":"        75","article_type":"original","day":"27","citation":{"ama":"Zhang Z, Chen H, Peng S, Han H. Slow and rapid auxin responses in Arabidopsis. <i>Journal of Experimental Botany</i>. 2024;75(18). doi:<a href=\"https://doi.org/10.1093/jxb/erae246\">10.1093/jxb/erae246</a>","apa":"Zhang, Z., Chen, H., Peng, S., &#38; Han, H. (2024). Slow and rapid auxin responses in Arabidopsis. <i>Journal of Experimental Botany</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/jxb/erae246\">https://doi.org/10.1093/jxb/erae246</a>","ista":"Zhang Z, Chen H, Peng S, Han H. 2024. Slow and rapid auxin responses in Arabidopsis. Journal of Experimental Botany. 75(18), erae246.","mla":"Zhang, Zilin, et al. “Slow and Rapid Auxin Responses in Arabidopsis.” <i>Journal of Experimental Botany</i>, vol. 75, no. 18, erae246, Oxford University Press, 2024, doi:<a href=\"https://doi.org/10.1093/jxb/erae246\">10.1093/jxb/erae246</a>.","chicago":"Zhang, Zilin, Huihuang Chen, Shuaiying Peng, and Huibin Han. “Slow and Rapid Auxin Responses in Arabidopsis.” <i>Journal of Experimental Botany</i>. Oxford University Press, 2024. <a href=\"https://doi.org/10.1093/jxb/erae246\">https://doi.org/10.1093/jxb/erae246</a>.","short":"Z. Zhang, H. Chen, S. Peng, H. Han, Journal of Experimental Botany 75 (2024).","ieee":"Z. Zhang, H. Chen, S. Peng, and H. Han, “Slow and rapid auxin responses in Arabidopsis,” <i>Journal of Experimental Botany</i>, vol. 75, no. 18. Oxford University Press, 2024."},"type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","author":[{"last_name":"Zhang","first_name":"Zilin","full_name":"Zhang, Zilin"},{"full_name":"Chen, Huihuang","id":"83c96512-15b2-11ec-abd3-b7eede36184f","last_name":"Chen","first_name":"Huihuang"},{"full_name":"Peng, Shuaiying","last_name":"Peng","first_name":"Shuaiying"},{"last_name":"Han","first_name":"Huibin","full_name":"Han, Huibin"}],"title":"Slow and rapid auxin responses in Arabidopsis","article_processing_charge":"No","ddc":["580"],"publication":"Journal of Experimental Botany","volume":75,"oa_version":"Published Version","date_updated":"2026-10-02T11:25:38Z","das_tickbox":"0","OA_place":"publisher","file_date_updated":"2025-01-02T10:26:22Z","researchdata_availability":"no","supplementarymaterial":"no","fulldoi":"https://doi.org/10.1093/jxb/erae246","pmid":1,"issue":"18","isi":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"status":"public","language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"JiFr"}],"scopus_import":"1","article_number":"erae246","acknowledgement":"We thank other lab members for their critical comments on this manuscript. We also thank the editor and reviewers for their constructive comments to improve our manuscript. We apologize to authors whose important work we could not include due to space limitations.\r\nThis work is supported by funding from Jiangxi Agricultural University (9232308314) and the Science and Technology Department of Jiangxi Province (20223BCJ25037) to HBH, and the Science and Technology Department of Jiangxi Province (20202ACB215002) to SYP.","date_published":"2024-09-27T00:00:00Z","publication_identifier":{"issn":["0022-0957"]},"year":"2024","date_created":"2024-06-15T19:50:15Z","OA_type":"hybrid","abstract":[{"text":"The TIR1/AFB–Aux/IAA–ARF canonical auxin signaling pathway is widely accepted to (de)active transcriptional regulation, thus controlling auxin-associated developmental processes. However, the theme of a rapid auxin response has emerged since the 2018 Auxins and Cytokinin in Plant Development conference. To date, a few signaling components have been identified to mediate both slow and rapid auxin responses, which unveils the complexity of auxin signaling.","lang":"eng"}],"external_id":{"isi":["001270051200001"],"pmid":["38794966"]},"publisher":"Oxford University Press","file":[{"creator":"dernst","success":1,"date_created":"2025-01-02T10:26:22Z","file_name":"2024_JourExperimentalBotany_Zhang.pdf","file_id":"18720","access_level":"open_access","file_size":763097,"checksum":"91b9435ed0f6640809c7588df19abf2f","relation":"main_file","date_updated":"2025-01-02T10:26:22Z","content_type":"application/pdf"}],"has_accepted_license":"1","publication_status":"published","_id":"17141","month":"09"},{"quality_controlled":"1","intvolume":"        42","oa":1,"project":[{"call_identifier":"FWF","_id":"265CB4D0-B435-11E9-9278-68D0E5697425","grant_number":"I03600","name":"Optical control of synaptic function via adhesion molecules"},{"_id":"2548AE96-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Molecular Drug Targets","grant_number":"W1232"},{"_id":"25C5A090-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Synaptic communication in neuronal microcircuits","grant_number":"Z00312"},{"_id":"23889792-32DE-11EA-91FC-C7463DDC885E","name":"High content imaging to decode human immune cell interactions in health and allergic disease","grant_number":"LS18-022"},{"name":"Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo and in vitro Models","grant_number":"715508","call_identifier":"H2020","_id":"25444568-B435-11E9-9278-68D0E5697425"},{"_id":"25B7EB9E-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"692692","name":"Biophysics and circuit function of a giant cortical glutamatergic synapse"},{"call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","name":"International IST Doctoral Program"},{"call_identifier":"H2020","_id":"fc2be41b-9c52-11eb-aca3-faa90aa144e9","grant_number":"101026635","name":"Synaptic computations of the hippocampal CA3 circuitry"}],"doi":"10.1038/s41587-023-01911-8","citation":{"ieee":"J. M. Michalska <i>et al.</i>, “Imaging brain tissue architecture across millimeter to nanometer scales,” <i>Nature Biotechnology</i>, vol. 42. Springer Nature, pp. 1051–1064, 2024.","mla":"Michalska, Julia M., et al. “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.” <i>Nature Biotechnology</i>, vol. 42, Springer Nature, 2024, pp. 1051–64, doi:<a href=\"https://doi.org/10.1038/s41587-023-01911-8\">10.1038/s41587-023-01911-8</a>.","chicago":"Michalska, Julia M, Julia Lyudchik, Philipp Velicky, Hana Korinkova, Jake Watson, Alban Cenameri, Christoph M Sommer, et al. “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.” <i>Nature Biotechnology</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41587-023-01911-8\">https://doi.org/10.1038/s41587-023-01911-8</a>.","short":"J.M. Michalska, J. Lyudchik, P. Velicky, H. Korinkova, J. Watson, A. Cenameri, C.M. Sommer, N. Amberg, A. Venturino, K. Roessler, T. Czech, R. Höftberger, S. Siegert, G. Novarino, P.M. Jonas, J.G. Danzl, Nature Biotechnology 42 (2024) 1051–1064.","ista":"Michalska JM, Lyudchik J, Velicky P, Korinkova H, Watson J, Cenameri A, Sommer CM, Amberg N, Venturino A, Roessler K, Czech T, Höftberger R, Siegert S, Novarino G, Jonas PM, Danzl JG. 2024. Imaging brain tissue architecture across millimeter to nanometer scales. Nature Biotechnology. 42, 1051–1064.","ama":"Michalska JM, Lyudchik J, Velicky P, et al. Imaging brain tissue architecture across millimeter to nanometer scales. <i>Nature Biotechnology</i>. 2024;42:1051-1064. doi:<a href=\"https://doi.org/10.1038/s41587-023-01911-8\">10.1038/s41587-023-01911-8</a>","apa":"Michalska, J. M., Lyudchik, J., Velicky, P., Korinkova, H., Watson, J., Cenameri, A., … Danzl, J. G. (2024). Imaging brain tissue architecture across millimeter to nanometer scales. <i>Nature Biotechnology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41587-023-01911-8\">https://doi.org/10.1038/s41587-023-01911-8</a>"},"article_type":"original","page":"1051-1064","day":"01","ddc":["570"],"volume":42,"publication":"Nature Biotechnology","author":[{"first_name":"Julia M","last_name":"Michalska","id":"443DB6DE-F248-11E8-B48F-1D18A9856A87","full_name":"Michalska, Julia M","orcid":"0000-0003-3862-1235"},{"full_name":"Lyudchik, Julia","id":"46E28B80-F248-11E8-B48F-1D18A9856A87","first_name":"Julia","last_name":"Lyudchik"},{"orcid":"0000-0002-2340-7431","full_name":"Velicky, Philipp","id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","first_name":"Philipp","last_name":"Velicky"},{"first_name":"Hana","last_name":"Korinkova","full_name":"Korinkova, Hana","id":"ee3cb6ca-ec98-11ea-ae11-ff703e2254ed"},{"first_name":"Jake","last_name":"Watson","full_name":"Watson, Jake","id":"63836096-4690-11EA-BD4E-32803DDC885E","orcid":"0000-0002-8698-3823"},{"first_name":"Alban","last_name":"Cenameri","full_name":"Cenameri, Alban","id":"9ac8f577-2357-11eb-997a-e566c5550886"},{"orcid":"0000-0003-1216-9105","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","full_name":"Sommer, Christoph M","first_name":"Christoph M","last_name":"Sommer"},{"orcid":"0000-0002-3183-8207","full_name":"Amberg, Nicole","id":"4CD6AAC6-F248-11E8-B48F-1D18A9856A87","last_name":"Amberg","first_name":"Nicole"},{"last_name":"Venturino","first_name":"Alessandro","id":"41CB84B2-F248-11E8-B48F-1D18A9856A87","full_name":"Venturino, Alessandro","orcid":"0000-0003-2356-9403"},{"full_name":"Roessler, Karl","first_name":"Karl","last_name":"Roessler"},{"full_name":"Czech, Thomas","last_name":"Czech","first_name":"Thomas"},{"first_name":"Romana","last_name":"Höftberger","full_name":"Höftberger, Romana"},{"orcid":"0000-0001-8635-0877","full_name":"Siegert, Sandra","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","first_name":"Sandra","last_name":"Siegert"},{"orcid":"0000-0002-7673-7178","first_name":"Gaia","last_name":"Novarino","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","full_name":"Novarino, Gaia"},{"orcid":"0000-0001-5001-4804","last_name":"Jonas","first_name":"Peter M","full_name":"Jonas, Peter M","id":"353C1B58-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0001-8559-3973","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","full_name":"Danzl, Johann G","first_name":"Johann G","last_name":"Danzl"}],"title":"Imaging brain tissue architecture across millimeter to nanometer scales","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","article_processing_charge":"Yes (in subscription journal)","file_date_updated":"2025-01-09T07:48:01Z","OA_place":"publisher","related_material":{"link":[{"url":"https://github.com/danzllab/CATS","relation":"software"}],"record":[{"status":"deleted","relation":"dissertation_contains","id":"18660"},{"relation":"research_data","id":"13126","status":"public"},{"relation":"dissertation_contains","id":"18674","status":"public"}]},"oa_version":"Published Version","date_updated":"2026-10-02T11:27:12Z","pmid":1,"fulldoi":"https://doi.org/10.1038/s41587-023-01911-8","isi":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"ec_funded":1,"department":[{"_id":"SaSi"},{"_id":"GaNo"},{"_id":"PeJo"},{"_id":"JoDa"},{"_id":"Bio"},{"_id":"RySh"}],"corr_author":"1","scopus_import":"1","date_published":"2024-07-01T00:00:00Z","acknowledgement":"We thank J. Vorlaufer, N. Agudelo-Dueñas, W. Jahr and A. Wartak for microscope maintenance and troubleshooting; C. Kreuzinger, A. Freeman and I. Erber for technical assistance; and M. Tomschik for support with obtaining human samples. We gratefully acknowledge E. Miguel for setting up webKnossos and M. Šuplata for computational support and hardware control. We are grateful to R. Shigemoto and B. Bickel for generous support and M. Sixt and S. Boyd (Stanford University) for discussions and critical reading of the paper. PSD95-HaloTag mice were kindly provided by S. Grant (University of Edinburgh). We acknowledge expert support by Institute of Science and Technology Austria’s scientific computing, imaging and optics, preclinical and lab support facilities and by the Miba machine shop and library. We gratefully acknowledge funding by the following sources: Austrian Science Fund (FWF) grant I3600-B27 (J.G.D.); Austrian Science Fund (FWF) grant DK W1232 (J.G.D. and J.M.M.); Austrian Science Fund (FWF) grant Z 312-B27, Wittgenstein award (P.J.); Austrian Science Fund (FWF) projects I4685-B, I6565-B (SYNABS) and DOC 33-B27 (R.H.); Gesellschaft für Forschungsförderung NÖ (NFB) grant LSC18-022 (J.G.D.); European Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 715508 – REVERSEAUTISM (G.N.); European Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 692692 – GIANTSYN (P.J.); Marie Skłodowska-Curie Actions Fellowship GA no. 665385 under the EU Horizon 2020 program (J.M.M. and J.L.); and Marie Skłodowska-Curie Actions Individual Fellowship no. 101026635 under the EU Horizon 2020 program (J.F.W.).","status":"public","language":[{"iso":"eng"}],"year":"2024","abstract":[{"text":"Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.","lang":"eng"}],"OA_type":"hybrid","date_created":"2023-09-03T22:01:15Z","publication_identifier":{"issn":["1087-0156"],"eissn":["1546-1696"]},"_id":"14257","month":"07","publisher":"Springer Nature","file":[{"date_updated":"2025-01-09T07:48:01Z","content_type":"application/pdf","file_size":26065165,"checksum":"57d5fafb16f02dcb9f7dddb1bd7e2a71","relation":"main_file","file_name":"2024_NatureBiotech_Michalska.pdf","file_id":"18784","access_level":"open_access","creator":"dernst","success":1,"date_created":"2025-01-09T07:48:01Z"}],"external_id":{"pmid":["37653226"],"isi":["001065254200001"]},"publication_status":"published","has_accepted_license":"1","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"LifeSc"},{"_id":"M-Shop"},{"_id":"E-Lib"}]},{"fulldoi":"https://doi.org/10.1101/2024.02.21.581330","ec_funded":1,"tmp":{"name":"Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)","short":"CC BY-NC (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","image":"/images/cc_by_nc.png"},"supplementarymaterial":"no","department":[{"_id":"EvBe"},{"_id":"JoDa"},{"_id":"JiFr"}],"corr_author":"1","acknowledgement":"We gratefully acknowledge support by the Scientific Service Units at ISTA, including the Imaging and Optics and Lab Support facilities and the mechanical workshop and Library. We thank Philipp Velicky for STED microscope alignment.\r\n\r\nThis project has received funding from the Austrian Science Fund (FWF): I 3630-B25 (J.G.D) and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 742985, J.F.). It has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. S.T. has received funding as an ISTplus Fellow from the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie grant agreement no. 754411 and from an EMBO Long-Term Fellowship (grant number ALTF 679-2018). It has further received funding from the Austrian Science Fund (FWF) grant DK W1232 (M.T, N.A-D., J.G.D). W.J. received funding via a Human Frontier Science Program postdoctoral fellowship LT000557/2018.\r\n\r\nThe funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.","date_published":"2024-02-21T00:00:00Z","status":"public","language":[{"iso":"eng"}],"year":"2024","date_created":"2024-12-19T12:28:00Z","abstract":[{"text":"Multiplexed fluorescence microscopy imaging is widely used in biomedical applications. However, simultaneous imaging of multiple fluorophores can result in spectral leaks and overlapping, which greatly degrades image quality and subsequent analysis. Existing popular spectral unmixing methods are mainly based on computational intensive linear models and the performance is heavily dependent on the reference spectra, which may greatly preclude its further applications. In this paper, we propose a deep learning-based blindly spectral unmixing method, termed AutoUnmix, to imitate the physical spectral mixing process. A tranfer learning framework is further devised to allow our AutoUnmix adapting to a variety of imaging systems without retraining the network. Our proposed method has demonstrated real-time unmixing capabilities, surpassing existing methods by up to 100-fold in terms of unmixing speed. We further validate the reconstruction performance on both synthetic datasets and biological samples. The unmixing results of AutoUnmix achieve a highest SSIM of 0.99 in both three- and four-color imaging, with nearly up to 20% higher than other popular unmixing methods. Due to the desirable property of data independency and superior blind unmixing performance, we believe AutoUnmix is a powerful tool to study the interaction process of different organelles labeled by multiple fluorophores.","lang":"eng"}],"_id":"18689","month":"02","acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"M-Shop"},{"_id":"E-Lib"}],"publication_status":"draft","oa":1,"main_file_link":[{"url":"https://doi.org/10.1101/2024.02.21.581330","open_access":"1"}],"project":[{"grant_number":"742985","name":"Tracing Evolution of Auxin Transport and Polarity in Plants","_id":"261099A6-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"},{"grant_number":"665385","name":"International IST Doctoral Program","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"},{"_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships"},{"grant_number":"W1232-B24","name":"Molecular Drug Targets","call_identifier":"FWF","_id":"26AA4EF2-B435-11E9-9278-68D0E5697425"},{"name":"UltraX - achieving sub-nanometer resolution in light microscopy using iterative X10 microscopy in combination with nanobodies and STED","grant_number":"ALTF 679-2018","_id":"269B5B22-B435-11E9-9278-68D0E5697425"}],"doi":"10.1101/2024.02.21.581330","license":"https://creativecommons.org/licenses/by-nc/4.0/","citation":{"ieee":"M. C. Gallei <i>et al.</i>, “Super-resolution expansion microscopy in plant roots,” <i>bioRxiv</i>. .","mla":"Gallei, Michelle C., et al. “Super-Resolution Expansion Microscopy in Plant Roots.” <i>BioRxiv</i>, doi:<a href=\"https://doi.org/10.1101/2024.02.21.581330\">10.1101/2024.02.21.581330</a>.","short":"M.C. Gallei, S.M. Truckenbrodt, C. Kreuzinger, S. Inumella, V. Vistunou, C.M. Sommer, M. Tavakoli, N. Agudelo Duenas, J. Vorlaufer, W. Jahr, M. Randuch, A.J. Johnson, E. Benková, J. Friml, J.G. Danzl, BioRxiv (n.d.).","chicago":"Gallei, Michelle C, Sven M Truckenbrodt, Caroline Kreuzinger, Syamala Inumella, Vitali Vistunou, Christoph M Sommer, Mojtaba Tavakoli, et al. “Super-Resolution Expansion Microscopy in Plant Roots.” <i>BioRxiv</i>, n.d. <a href=\"https://doi.org/10.1101/2024.02.21.581330\">https://doi.org/10.1101/2024.02.21.581330</a>.","ista":"Gallei MC, Truckenbrodt SM, Kreuzinger C, Inumella S, Vistunou V, Sommer CM, Tavakoli M, Agudelo Duenas N, Vorlaufer J, Jahr W, Randuch M, Johnson AJ, Benková E, Friml J, Danzl JG. Super-resolution expansion microscopy in plant roots. bioRxiv, <a href=\"https://doi.org/10.1101/2024.02.21.581330\">10.1101/2024.02.21.581330</a>.","ama":"Gallei MC, Truckenbrodt SM, Kreuzinger C, et al. Super-resolution expansion microscopy in plant roots. <i>bioRxiv</i>. doi:<a href=\"https://doi.org/10.1101/2024.02.21.581330\">10.1101/2024.02.21.581330</a>","apa":"Gallei, M. C., Truckenbrodt, S. M., Kreuzinger, C., Inumella, S., Vistunou, V., Sommer, C. M., … Danzl, J. G. (n.d.). Super-resolution expansion microscopy in plant roots. <i>bioRxiv</i>. <a href=\"https://doi.org/10.1101/2024.02.21.581330\">https://doi.org/10.1101/2024.02.21.581330</a>"},"day":"21","publication":"bioRxiv","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"preprint","author":[{"last_name":"Gallei","first_name":"Michelle C","id":"35A03822-F248-11E8-B48F-1D18A9856A87","full_name":"Gallei, Michelle C","orcid":"0000-0003-1286-7368"},{"id":"45812BD4-F248-11E8-B48F-1D18A9856A87","full_name":"Truckenbrodt, Sven M","first_name":"Sven M","last_name":"Truckenbrodt"},{"id":"382077BA-F248-11E8-B48F-1D18A9856A87","full_name":"Kreuzinger, Caroline","first_name":"Caroline","last_name":"Kreuzinger"},{"first_name":"Syamala","last_name":"Inumella","full_name":"Inumella, Syamala","id":"F8660870-D756-11E9-98C5-34DFE5697425","orcid":"0009-0002-5890-120X"},{"full_name":"Vistunou, Vitali","id":"7e146587-8972-11ed-ae7b-d7a32ea86a81","first_name":"Vitali","last_name":"Vistunou"},{"orcid":"0000-0003-1216-9105","full_name":"Sommer, Christoph M","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph M","last_name":"Sommer"},{"orcid":"0000-0002-7667-6854","first_name":"Mojtaba","last_name":"Tavakoli","full_name":"Tavakoli, Mojtaba","id":"3A0A06F4-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Agudelo Duenas, Nathalie","id":"40E7F008-F248-11E8-B48F-1D18A9856A87","first_name":"Nathalie","last_name":"Agudelo Duenas"},{"orcid":"0009-0000-7590-3501","full_name":"Vorlaufer, Jakob","id":"937696FA-C996-11E9-8C7C-CF13E6697425","last_name":"Vorlaufer","first_name":"Jakob"},{"full_name":"Jahr, Wiebke","id":"425C1CE8-F248-11E8-B48F-1D18A9856A87","last_name":"Jahr","first_name":"Wiebke","orcid":"0000-0003-0201-2315"},{"id":"6ac4636d-15b2-11ec-abd3-fb8df79972ae","full_name":"Randuch, Marek","first_name":"Marek","last_name":"Randuch"},{"orcid":"0000-0002-2739-8843","full_name":"Johnson, Alexander J","id":"46A62C3A-F248-11E8-B48F-1D18A9856A87","first_name":"Alexander J","last_name":"Johnson"},{"orcid":"0000-0002-8510-9739","id":"38F4F166-F248-11E8-B48F-1D18A9856A87","full_name":"Benková, Eva","first_name":"Eva","last_name":"Benková"},{"id":"4159519E-F248-11E8-B48F-1D18A9856A87","full_name":"Friml, Jiří","first_name":"Jiří","last_name":"Friml","orcid":"0000-0002-8302-7596"},{"id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","full_name":"Danzl, Johann G","first_name":"Johann G","last_name":"Danzl","orcid":"0000-0001-8559-3973"}],"title":"Super-resolution expansion microscopy in plant roots","article_processing_charge":"No","OA_place":"repository","related_material":{"record":[{"id":"19003","relation":"later_version","status":"public"},{"relation":"dissertation_contains","id":"18681","status":"public"}]},"researchdata_availability":"no","date_updated":"2026-10-02T11:27:43Z","das_tickbox":"0","oa_version":"Preprint"},{"day":"18","page":"217","citation":{"mla":"Lyudchik, Julia. <i>Image Analysis for Brain Tissue Reconstruction with Super-Resolution Light Microscopy</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:18674\">10.15479/at:ista:18674</a>.","short":"J. Lyudchik, Image Analysis for Brain Tissue Reconstruction with Super-Resolution Light Microscopy, Institute of Science and Technology Austria, 2024.","chicago":"Lyudchik, Julia. “Image Analysis for Brain Tissue Reconstruction with Super-Resolution Light Microscopy.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:18674\">https://doi.org/10.15479/at:ista:18674</a>.","ieee":"J. Lyudchik, “Image analysis for brain tissue reconstruction with super-resolution light microscopy,” Institute of Science and Technology Austria, 2024.","ama":"Lyudchik J. Image analysis for brain tissue reconstruction with super-resolution light microscopy. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:18674\">10.15479/at:ista:18674</a>","apa":"Lyudchik, J. (2024). <i>Image analysis for brain tissue reconstruction with super-resolution light microscopy</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:18674\">https://doi.org/10.15479/at:ista:18674</a>","ista":"Lyudchik J. 2024. Image analysis for brain tissue reconstruction with super-resolution light microscopy. Institute of Science and Technology Austria."},"doi":"10.15479/at:ista:18674","project":[{"call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","name":"International IST Doctoral Program"}],"oa":1,"date_updated":"2026-10-02T11:27:13Z","das_tickbox":"0","oa_version":"Published Version","alternative_title":["ISTA Thesis"],"related_material":{"record":[{"id":"11160","relation":"part_of_dissertation","status":"public"},{"status":"public","id":"13267","relation":"part_of_dissertation"},{"id":"14257","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","id":"18677","status":"public"}]},"researchdata_availability":"no","file_date_updated":"2024-12-18T14:41:53Z","OA_place":"publisher","article_processing_charge":"No","author":[{"last_name":"Lyudchik","first_name":"Julia","full_name":"Lyudchik, Julia","id":"46E28B80-F248-11E8-B48F-1D18A9856A87"}],"title":"Image analysis for brain tissue reconstruction with super-resolution light microscopy","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"dissertation","degree_awarded":"PhD","ddc":["004"],"language":[{"iso":"eng"}],"status":"public","doi_confirm":"1","date_published":"2024-12-18T00:00:00Z","department":[{"_id":"GradSch"},{"_id":"JoDa"}],"corr_author":"1","supplementarymaterial":"no","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png"},"ec_funded":1,"fulldoi":"https://doi.org/10.15479/at:ista:18674","publication_status":"published","acknowledged_ssus":[{"_id":"Bio"}],"has_accepted_license":"1","file":[{"content_type":"application/pdf","date_updated":"2024-12-18T14:17:34Z","relation":"main_file","file_size":160536833,"checksum":"1b42b8073e2bc09fc504da52372248c1","access_level":"open_access","file_id":"18675","file_name":"18122024_PhDthesis_corrected_final_pdfa.pdf","success":1,"date_created":"2024-12-18T14:17:34Z","creator":"jlyudchi"},{"creator":"jlyudchi","date_created":"2024-12-18T14:21:06Z","file_name":"18122024_PhDthesis_corrected_final_JL_markup.docx","access_level":"closed","file_id":"18676","checksum":"b4da84624060745519723698f7ddf54b","file_size":99172203,"relation":"source_file","date_updated":"2024-12-18T14:41:53Z","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document"}],"publisher":"Institute of Science and Technology Austria","month":"12","_id":"18674","supervisor":[{"full_name":"Danzl, Johann G","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","first_name":"Johann G","last_name":"Danzl","orcid":"0000-0001-8559-3973"}],"publication_identifier":{"isbn":[" 978-3-99078-051-0"],"issn":["2663-337X"]},"abstract":[{"text":"Mapping the complex and dense arrangement of cells and their connectivity in brain tissue requires volumetric imaging at nanoscale spatial resolution. While light microscopy excels at visualizing specific molecules and individual cells, achieving dense, synapse-level circuit reconstruction has not been possible with any light microscopy technique. Thus, the goal of my work was to develop image and data analysis pipelines for brain tissue visualization and reconstruction with light microscopy. To achieve dense circuit reconstruction with single-synapse resolution, I developed both conventional and deep-learning-based synapse detection algorithms, as well as connectivity analysis pipelines that integrate synapse detection with volumetric segmentation of brain tissue.","lang":"eng"}],"date_created":"2024-12-18T14:24:43Z","year":"2024"}]