[{"year":"2023","date_created":"2024-02-26T08:37:57Z","article_processing_charge":"No","oa":1,"date_published":"2023-12-13T00:00:00Z","publisher":"Figshare","ddc":["570"],"date_updated":"2026-09-24T10:27:35Z","license":"https://creativecommons.org/publicdomain/zero/1.0/","citation":{"ieee":"S. Curk, “aggregation_data.” Figshare, 2023.","ama":"Curk S. aggregation_data. 2023.","short":"S. Curk, (2023).","apa":"Curk, S. (2023). aggregation_data. Figshare.","mla":"Curk, Samo. Aggregation_data. Figshare, 2023.","ista":"Curk S. 2023. aggregation_data, Figshare.","chicago":"Curk, Samo. “Aggregation_data.” Figshare, 2023."},"tmp":{"name":"Creative Commons Public Domain Dedication (CC0 1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","image":"/images/cc_0.png","short":"CC0 (1.0)"},"department":[{"_id":"AnSa"}],"_id":"15027","author":[{"first_name":"Samo","orcid":"0000-0001-6160-9766","full_name":"Curk, Samo","id":"031eff0d-d481-11ee-8508-cd12a7a86e5b","last_name":"Curk"}],"abstract":[{"text":"This data repository underpins the paper, published in PNAS (doi pending) and bioarxiv (doi: https://doi.org/10.1101/2023.07.05.547777).","lang":"eng"}],"oa_version":"Published Version","related_material":{"record":[{"status":"public","id":"15001","relation":"used_in_publication"}]},"day":"13","month":"12","status":"public","corr_author":"1","type":"research_data_reference","title":"aggregation_data","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","OA_type":"gold","has_accepted_license":"1","OA_place":"publisher","main_file_link":[{"open_access":"1","url":"https://figshare.com/s/85798bba4ebc68d822ed"}]},{"department":[{"_id":"BjHo"}],"citation":{"mla":"Lemoult, Grégoire. Directed Percolation and Puff Jamming near the Transition to Pipe Turbulence. Zenodo, 2023, doi:10.5281/zenodo.10308791.","ista":"Lemoult G. 2023. Directed percolation and puff jamming near the transition to pipe turbulence, Zenodo, 10.5281/zenodo.10308791.","apa":"Lemoult, G. (2023). Directed percolation and puff jamming near the transition to pipe turbulence. Zenodo. https://doi.org/10.5281/zenodo.10308791","chicago":"Lemoult, Grégoire. “Directed Percolation and Puff Jamming near the Transition to Pipe Turbulence.” Zenodo, 2023. https://doi.org/10.5281/zenodo.10308791.","ama":"Lemoult G. Directed percolation and puff jamming near the transition to pipe turbulence. 2023. doi:10.5281/zenodo.10308791","ieee":"G. Lemoult, “Directed percolation and puff jamming near the transition to pipe turbulence.” Zenodo, 2023.","short":"G. Lemoult, (2023)."},"oa_version":"None","_id":"23012","abstract":[{"lang":"eng","text":"The onset of turbulence in pipe flow has defied detailed understanding ever since Reynolds' first observations revealed the spatially-heterogeneous nature of the transition. While recent theoretical studies and experiments in simpler, shear-driven flows suggest that the onset of turbulence is a directed percolation non-equilibrium phase transition, whether these findings are generic and apply also to open or pressure-driven flows is unknown. In pipe flow, the extremely long time scales near the transition make direct observations of critical behavior virtually impossible. Here, we circumvent these limitations by experimentally characterizing all pairwise interactions between localized patches of turbulence (\"puffs\"), and using these interactions as input to renormalization group and computer simulations of minimal models that extrapolate to long length and time scales. We show that the universality class of the transition is directed percolation, from which emerges a jammed phase of puffs above the critical point. The stronger interactions in the jamming regime enable us to explicitly measure the turbulent fraction and confirm model predictions. Our work shows that directed percolation scaling applies beyond simple closed shear flows, and underscores how statistical mechanics can lead to profound, quantitative and predictive insights on turbulent flows and their phases."}],"author":[{"last_name":"Lemoult","full_name":"Lemoult, Grégoire","first_name":"Grégoire"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"research_data_reference","title":"Directed percolation and puff jamming near the transition to pipe turbulence","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.10308791","open_access":"1"}],"OA_type":"green","OA_place":"repository","status":"public","day":"08","month":"12","related_material":{"record":[{"relation":"used_in_publication","id":"17128","status":"public"}]},"doi":"10.5281/zenodo.10308791","fulldoi":"https://doi.org/10.5281/zenodo.10308791","article_processing_charge":"No","year":"2023","date_created":"2026-10-01T07:47:57Z","publisher":"Zenodo","date_updated":"2026-10-01T07:50:31Z","oa":1,"date_published":"2023-12-08T00:00:00Z"},{"publisher":"Repository","date_updated":"2026-10-01T12:17:26Z","ddc":["570"],"oa":1,"date_published":"2023-04-23T00:00:00Z","fulldoi":"https://doi.org/10.6084/m9.figshare.22680433","doi":"10.6084/m9.figshare.22680433","article_processing_charge":"No","year":"2023","date_created":"2026-09-17T11:23:46Z","type":"research_data_reference","title":"Glutamate and GABA neurons share cascading Onecut3/NAV2-driven differentiation trajectories in the developing hypothalamus","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","main_file_link":[{"url":"https://doi.org/10.6084/m9.figshare.22680433","open_access":"1"}],"OA_place":"repository","OA_type":"green","related_material":{"record":[{"relation":"used_in_publication","id":"18445","status":"public"}]},"day":"23","month":"04","status":"public","citation":{"short":"M. Zupancic, E. Keimpema, E. Tretiakov, P. Bhandari, S. Eder, I. Lev, W. Härtig, M. Zimmer, F. Clotman, T. Harkany, (2023).","ieee":"M. Zupancic et al., “Glutamate and GABA neurons share cascading Onecut3/NAV2-driven differentiation trajectories in the developing hypothalamus.” Repository, 2023.","ama":"Zupancic M, Keimpema E, Tretiakov E, et al. Glutamate and GABA neurons share cascading Onecut3/NAV2-driven differentiation trajectories in the developing hypothalamus. 2023. doi:10.6084/m9.figshare.22680433","chicago":"Zupancic, Maja, Erik Keimpema, Evgenii Tretiakov, Pradeep Bhandari, Stephanie Eder, Itamar Lev, Wolfgang Härtig, Manuel Zimmer, Frederic Clotman, and Tibor Harkany. “Glutamate and GABA Neurons Share Cascading Onecut3/NAV2-Driven Differentiation Trajectories in the Developing Hypothalamus.” Repository, 2023. https://doi.org/10.6084/m9.figshare.22680433.","mla":"Zupancic, Maja, et al. Glutamate and GABA Neurons Share Cascading Onecut3/NAV2-Driven Differentiation Trajectories in the Developing Hypothalamus. Repository, 2023, doi:10.6084/m9.figshare.22680433.","ista":"Zupancic M, Keimpema E, Tretiakov E, Bhandari P, Eder S, Lev I, Härtig W, Zimmer M, Clotman F, Harkany T. 2023. Glutamate and GABA neurons share cascading Onecut3/NAV2-driven differentiation trajectories in the developing hypothalamus, Repository, 10.6084/m9.figshare.22680433.","apa":"Zupancic, M., Keimpema, E., Tretiakov, E., Bhandari, P., Eder, S., Lev, I., … Harkany, T. (2023). Glutamate and GABA neurons share cascading Onecut3/NAV2-driven differentiation trajectories in the developing hypothalamus. Repository. https://doi.org/10.6084/m9.figshare.22680433"},"department":[{"_id":"RySh"}],"_id":"22961","author":[{"first_name":"Maja","full_name":"Zupancic, Maja","last_name":"Zupancic"},{"full_name":"Keimpema, Erik","first_name":"Erik","last_name":"Keimpema"},{"last_name":"Tretiakov","full_name":"Tretiakov, Evgenii","first_name":"Evgenii"},{"last_name":"Bhandari","full_name":"Bhandari, Pradeep","first_name":"Pradeep"},{"first_name":"Stephanie","full_name":"Eder, Stephanie","last_name":"Eder"},{"last_name":"Lev","full_name":"Lev, Itamar","first_name":"Itamar"},{"last_name":"Härtig","full_name":"Härtig, Wolfgang","first_name":"Wolfgang"},{"full_name":"Zimmer, Manuel","first_name":"Manuel","last_name":"Zimmer"},{"full_name":"Clotman, Frederic","first_name":"Frederic","last_name":"Clotman"},{"last_name":"Harkany","first_name":"Tibor","full_name":"Harkany, Tibor"}],"abstract":[{"lang":"eng","text":"## Rationale:\r\nDifferentiation trajectories to generate specialized cellular features rely on sets of transcription factors (TFs) whose temporal dynamics and coexistence underlie morphological and neurochemical divergence among neurons and neuroendocrine cells. Even though transcriptional programs were extensively studied in the developing nervous system, the coupling of TFs to effector gene networks that time and shape the morphogenesis of these polarized cells is less known.\r\n\r\n## Results:\r\nHere, we make the curious observation that evolutionarily conserved Onecut3, a subordinate in the Onecut TF family known to control fate selection in progenitors, is instead expressed in fate-restricted neuroblasts in the vertebrate hypothalamus. In particular, a pool of Ascl1-containing progenitors in the midgestational mouse hypothalamus gives rise to both GABA and glutamate neurons destined to the periventricular and lateral hypothalamus, respectively, which uniformly upregulate Onecut3 only when exiting the proliferative zone of the 3rd ventricle. By combining single-cell RNA-seq, genetic Onecut3 reporters, gain-of-function models in vitro, and loss-of-function analysis in early-developing mice and C. elegans, we identify that Onecut3 instructs neuronal differentiation and maturation, through a Navigator-2 pathway to modulate neuritogenesis and leading process motility.\r\n\r\n\r\n## Conclusion:\r\nOnecut3 executes an unexpected function by inducing cytoskeletal modifications of key importance for neuronal maturation and network integration during the morphogenesis of many neuronal phenotypes in the vertebrate hypothalamus."}],"oa_version":"None"},{"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"citation":{"ista":"Binysh J, Chakraborty I, Chubynsky MV, Diaz Melian VL, Waitukaitis SR, Sprittles JE, Souslov A. 2023. Modeling Leidenfrost levitation of soft elastic solids. Physical Review Letters. 131(16), 168201.","mla":"Binysh, Jack, et al. “Modeling Leidenfrost Levitation of Soft Elastic Solids.” Physical Review Letters, vol. 131, no. 16, 168201, American Physical Society, 2023, doi:10.1103/PhysRevLett.131.168201.","apa":"Binysh, J., Chakraborty, I., Chubynsky, M. V., Diaz Melian, V. L., Waitukaitis, S. R., Sprittles, J. E., & Souslov, A. (2023). Modeling Leidenfrost levitation of soft elastic solids. Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.131.168201","chicago":"Binysh, Jack, Indrajit Chakraborty, Mykyta V. Chubynsky, Vicente L Diaz Melian, Scott R Waitukaitis, James E. Sprittles, and Anton Souslov. “Modeling Leidenfrost Levitation of Soft Elastic Solids.” Physical Review Letters. American Physical Society, 2023. https://doi.org/10.1103/PhysRevLett.131.168201.","ama":"Binysh J, Chakraborty I, Chubynsky MV, et al. Modeling Leidenfrost levitation of soft elastic solids. Physical Review Letters. 2023;131(16). doi:10.1103/PhysRevLett.131.168201","ieee":"J. Binysh et al., “Modeling Leidenfrost levitation of soft elastic solids,” Physical Review Letters, vol. 131, no. 16. American Physical Society, 2023.","short":"J. Binysh, I. Chakraborty, M.V. Chubynsky, V.L. Diaz Melian, S.R. Waitukaitis, J.E. Sprittles, A. Souslov, Physical Review Letters 131 (2023)."},"author":[{"last_name":"Binysh","first_name":"Jack","full_name":"Binysh, Jack"},{"first_name":"Indrajit","full_name":"Chakraborty, Indrajit","last_name":"Chakraborty"},{"first_name":"Mykyta V.","full_name":"Chubynsky, Mykyta V.","last_name":"Chubynsky"},{"last_name":"Diaz Melian","first_name":"Vicente L","full_name":"Diaz Melian, Vicente L","id":"b6798902-eea0-11ea-9cbc-a8e14286c631"},{"full_name":"Waitukaitis, Scott R","orcid":"0000-0002-2299-3176","id":"3A1FFC16-F248-11E8-B48F-1D18A9856A87","first_name":"Scott R","last_name":"Waitukaitis"},{"full_name":"Sprittles, James E.","first_name":"James E.","last_name":"Sprittles"},{"last_name":"Souslov","full_name":"Souslov, Anton","first_name":"Anton"}],"file_date_updated":"2023-11-13T09:12:58Z","license":"https://creativecommons.org/licenses/by/4.0/","type":"journal_article","issue":"16","article_number":"168201","publication_identifier":{"issn":["0031-9007"],"eissn":["1079-7114"]},"volume":131,"acknowledgement":"We are grateful to Dominic Vella, Jens Eggers, John Kolinski, Joshua Dijksman, and Daniel Bonn for insightful discussions. J. B. and A. S. acknowledge the support of the Engineering and Physical Sciences Research Council (EPSRC) through New Investigator Award No. EP/\r\nT000961/1. A. S. acknowledges the support of Royal Society under Grant No. RGS/R2/202135. J. E. S. acknowledges EPSRC Grants No. EP/N016602/1, EP/S022848/1, EP/S029966/1, and EP/P031684/1.","file":[{"date_created":"2023-11-13T09:12:58Z","access_level":"open_access","content_type":"application/pdf","relation":"main_file","checksum":"1a419e25b762aadffbcc8eb2e609bd97","success":1,"creator":"dernst","file_id":"14524","date_updated":"2023-11-13T09:12:58Z","file_name":"2023_PhysRevLetters_Binysh.pdf","file_size":724098}],"publisher":"American Physical Society","ddc":["530"],"oa":1,"language":[{"iso":"eng"}],"department":[{"_id":"ScWa"}],"_id":"14514","abstract":[{"text":"The elastic Leidenfrost effect occurs when a vaporizable soft solid is lowered onto a hot surface. Evaporative flow couples to elastic deformation, giving spontaneous bouncing or steady-state floating. The effect embodies an unexplored interplay between thermodynamics, elasticity, and lubrication: despite being observed, its basic theoretical description remains a challenge. Here, we provide a theory of elastic Leidenfrost floating. As weight increases, a rigid solid sits closer to the hot surface. By contrast, we discover an elasticity-dominated regime where the heavier the solid, the higher it floats. This geometry-governed behavior is reminiscent of the dynamics of large liquid Leidenfrost drops. We show that this elastic regime is characterized by Hertzian behavior of the solid’s underbelly and derive how the float height scales with materials parameters. Introducing a dimensionless elastic Leidenfrost number, we capture the crossover between rigid and Hertzian behavior. Our results provide theoretical underpinning for recent experiments, and point to the design of novel soft machines.","lang":"eng"}],"oa_version":"Published Version","external_id":{"pmid":["37925690"],"isi":["001164388300007"]},"title":"Modeling Leidenfrost levitation of soft elastic solids","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","has_accepted_license":"1","related_material":{"record":[{"relation":"research_data","id":"14523","status":"public"},{"relation":"dissertation_contains","id":"23005","status":"public"}]},"day":"20","month":"10","isi":1,"status":"public","fulldoi":"https://doi.org/10.1103/PhysRevLett.131.168201","doi":"10.1103/PhysRevLett.131.168201","article_processing_charge":"Yes (in subscription journal)","scopus_import":"1","year":"2023","article_type":"original","publication_status":"published","date_created":"2023-11-12T23:00:55Z","intvolume":" 131","date_updated":"2026-10-02T08:44:47Z","quality_controlled":"1","publication":"Physical Review Letters","pmid":1,"date_published":"2023-10-20T00:00:00Z"},{"oa_version":"Published Version","abstract":[{"lang":"eng","text":"GLACIER METEOROLOGICAL DATA SWISS ALPS -2022\r\n"}],"_id":"14919","author":[{"last_name":"Shaw","first_name":"Thomas","orcid":"0000-0001-7640-6152","full_name":"Shaw, Thomas","id":"3caa3f91-1f03-11ee-96ce-e0e553054d6e"},{"last_name":"Buri","id":"317987aa-9421-11ee-ac5a-b941b041abba","full_name":"Buri, Pascal","first_name":"Pascal"},{"full_name":"McCarthy, Michael","first_name":"Michael","last_name":"McCarthy"},{"full_name":"Miles, Evan","first_name":"Evan","last_name":"Miles"},{"last_name":"Pellicciotti","first_name":"Francesca","orcid":"0000-0002-5554-8087","full_name":"Pellicciotti, Francesca","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"}],"department":[{"_id":"FrPe"}],"citation":{"ieee":"T. Shaw, P. Buri, M. McCarthy, E. Miles, and F. Pellicciotti, “Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer.” Zenodo, 2023.","ama":"Shaw T, Buri P, McCarthy M, Miles E, Pellicciotti F. Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer. 2023. doi:10.5281/ZENODO.8277285","short":"T. Shaw, P. Buri, M. McCarthy, E. Miles, F. Pellicciotti, (2023).","apa":"Shaw, T., Buri, P., McCarthy, M., Miles, E., & Pellicciotti, F. (2023). Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer. Zenodo. https://doi.org/10.5281/ZENODO.8277285","ista":"Shaw T, Buri P, McCarthy M, Miles E, Pellicciotti F. 2023. Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer, Zenodo, 10.5281/ZENODO.8277285.","mla":"Shaw, Thomas, et al. Air Temperature and Near-Surface Meteorology Datasets on Three Swiss Glaciers - Extreme 2022 Summer. Zenodo, 2023, doi:10.5281/ZENODO.8277285.","chicago":"Shaw, Thomas, Pascal Buri, Michael McCarthy, Evan Miles, and Francesca Pellicciotti. “Air Temperature and Near-Surface Meteorology Datasets on Three Swiss Glaciers - Extreme 2022 Summer.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.8277285."},"corr_author":"1","status":"public","day":"23","related_material":{"record":[{"status":"public","id":"14885","relation":"used_in_publication"}]},"month":"08","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/ZENODO.8277285"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"research_data_reference","title":"Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer","date_created":"2024-01-31T12:08:26Z","year":"2023","article_processing_charge":"No","doi":"10.5281/ZENODO.8277285","fulldoi":"https://doi.org/10.5281/ZENODO.8277285","date_published":"2023-08-23T00:00:00Z","oa":1,"date_updated":"2026-10-02T08:57:44Z","ddc":["550"],"publisher":"Zenodo"},{"author":[{"last_name":"Shaw","first_name":"Thomas E.","full_name":"Shaw, Thomas E."},{"last_name":"Buri","full_name":"Buri, Pascal","first_name":"Pascal"},{"full_name":"McCarthy, Michael","first_name":"Michael","last_name":"McCarthy"},{"full_name":"Miles, Evan S.","first_name":"Evan S.","last_name":"Miles"},{"full_name":"Pelliciotti, Francesca","first_name":"Francesca","last_name":"Pelliciotti"}],"_id":"23030","abstract":[{"lang":"eng","text":"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\r\n GLACIER METEOROLOGICAL DATA\r\n SWISS ALPS -2022\r\n%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\r\nData gathered and structured by Thomas Shaw (WSL, Switzerland (until Oct 2022)).\r\n\r\nOn and off-glacier meteorological data were gathered and analysed as part of a Marie-Curie project 'TEMPEST' (tempestglacier.com).\r\nThe dataset consists of hourly low-cost AWS (Davis Vantage Pro2) and simple temperature ('T-')logger (Onset TidBitv2) sensor records on three glaciers in the Swiss Alps (Canton Valais).\r\n\r\nThe glaciers are:\r\nHaut Glacier d'Arolla (45.967°N, 7.526°E)\r\nGlacier d'Otemma (45.956°N, 7.454°E)\r\nGlacier du Corbassière (45.975°N, 7.303°E)\r\n\r\nData are provided in individual Excel files per glacier that contain all hourly data for the sub-period of comparison (11 August-18 September, 2022).\r\nData are quality controlled and checked for obvious errors. Any uncertain values are set to NaN.\r\nAir temperature data at 'T-Logger' stations were corrected for heating errors using the comparison of measurements in artificially (AWS) and naturally ventilated (T-Logger) radiation shields on Arolla and Corbassiere glaciers.\r\nA multiple linear regression model was applied to estimate these differences at all T-Loggers on all glaciers as a function of incoming shortwave radiation (MeteoSwiss station-derived) and wind speed (measured at AWS).\r\n\r\nEach Excel file contains a 'META' tab for simple metadata related to station locations (latitude 'LAT' (°), longitude 'LON' (°), elevation 'ELE' (m a.s.l.) and flowpath length 'FPL' (m)) and a 'DATA' tab for the hourly data. \r\nSuffixes to the station names in each column provide the variable measured at that site:\r\n'TA' - 2m air temperature (°C)\r\n'TA_Hi' - Maximum air temperature for timestep (°C)\r\n'TA_Lo' - Minimum air temperature for timestep (°C)\r\n'RH' - 2m relative humiditiy (%)\r\n'FF' - Wind speed (m s^-1)\r\n'FF_Hi' - Maximum wind speed for timestep (m s^-1)\r\n'FF_Lo' - Minimum wind speed for timestep (m s^-1)\r\n'DIR' - Wind direction (°)\r\n'DEW' - Dewpoint temperature (°C)\r\n'PRESS' - Air pressure (mbar)\r\n'CHILL' - Calculated wind chill temperature (°C)\r\n'Heat_idx' - Calculated heat index (°C)\r\n'THSW' - A calculated index that uses humidity and temperature like for the Heat Index, but also includes the heating effects of sunshine and the cooling effects of wind (like Wind Chill) to calculate an apparent temperature of what it \"feels\" like out in the shade\r\n\r\nWind speeds and direction measured at off-glacier sites 'OG' are for the lower off-glacier station ('OG_Low'). "}],"oa_version":"None","citation":{"ista":"Shaw TE, Buri P, McCarthy M, Miles ES, Pelliciotti F. 2023. Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer, Zenodo, 10.5281/zenodo.8277284.","mla":"Shaw, Thomas E., et al. Air Temperature and Near-Surface Meteorology Datasets on Three Swiss Glaciers - Extreme 2022 Summer. Zenodo, 2023, doi:10.5281/zenodo.8277284.","apa":"Shaw, T. E., Buri, P., McCarthy, M., Miles, E. S., & Pelliciotti, F. (2023). Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer. Zenodo. https://doi.org/10.5281/zenodo.8277284","chicago":"Shaw, Thomas E., Pascal Buri, Michael McCarthy, Evan S. Miles, and Francesca Pelliciotti. “Air Temperature and Near-Surface Meteorology Datasets on Three Swiss Glaciers - Extreme 2022 Summer.” Zenodo, 2023. https://doi.org/10.5281/zenodo.8277284.","ama":"Shaw TE, Buri P, McCarthy M, Miles ES, Pelliciotti F. Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer. 2023. doi:10.5281/zenodo.8277284","ieee":"T. E. Shaw, P. Buri, M. McCarthy, E. S. Miles, and F. Pelliciotti, “Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer.” Zenodo, 2023.","short":"T.E. Shaw, P. Buri, M. McCarthy, E.S. Miles, F. Pelliciotti, (2023)."},"department":[{"_id":"FrPe"}],"main_file_link":[{"url":"https://doi.org/10.5281/zenodo.8277284","open_access":"1"}],"OA_place":"repository","OA_type":"green","title":"Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer","type":"research_data_reference","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","month":"08","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"14885"}]},"day":"23","status":"public","article_processing_charge":"No","fulldoi":"https://doi.org/10.5281/zenodo.8277284","doi":"10.5281/zenodo.8277284","date_created":"2026-10-02T08:58:12Z","year":"2023","acknowledgement":"This work was funded by the EU Horizon 2020 Marie Skłodowska-Curie Actions Grant 101026058.","ddc":["550"],"date_updated":"2026-10-02T08:59:03Z","publisher":"Zenodo","date_published":"2023-08-23T00:00:00Z","oa":1},{"status":"public","related_material":{"record":[{"id":"18628","relation":"used_in_publication","status":"public"}]},"day":"05","month":"06","OA_type":"green","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.8005257"}],"OA_place":"repository","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","title":"A 3D glacier dynamics-line plume model to estimate the frontal ablation of Hansbreen","type":"research_data_reference","contributor":[{"last_name":"Muñoz Hermosilla","contributor_type":"contact_person","first_name":"José M"}],"oa_version":"None","abstract":[{"text":"There are 4 tar.xz files with the result of the model for the paper: A 3D glacier dynamics-line plume model to estimate the frontal ablation of Hansbreen, Svalbard. These archives can be unzipped on Linux using the tar command, or on other systems using a specific software.\r\n\r\nFrontPositions includes data files with the coordinates of the nodes of the front positons.\r\n\r\nCalvingStats includes txt files with some characteristics of the calving events.\r\n\r\nHydrologyOutput includes csv files with the main results of the hydrological model.\r\n\r\nModelOutput include output and visualization files of the model results. The .vtu and .pvtu files are best viewed in the software Paraview.","lang":"eng"}],"_id":"23031","author":[{"last_name":"Muñoz Hermosilla","first_name":"José M","full_name":"Muñoz Hermosilla, José M"}],"department":[{"_id":"FrPe"}],"citation":{"chicago":"Muñoz Hermosilla, José M. “A 3D Glacier Dynamics-Line Plume Model to Estimate the Frontal Ablation of Hansbreen.” Zenodo, 2023. https://doi.org/10.5281/zenodo.8005257.","apa":"Muñoz Hermosilla, J. M. (2023). A 3D glacier dynamics-line plume model to estimate the frontal ablation of Hansbreen. Zenodo. https://doi.org/10.5281/zenodo.8005257","mla":"Muñoz Hermosilla, José M. A 3D Glacier Dynamics-Line Plume Model to Estimate the Frontal Ablation of Hansbreen. Zenodo, 2023, doi:10.5281/zenodo.8005257.","ista":"Muñoz Hermosilla JM. 2023. A 3D glacier dynamics-line plume model to estimate the frontal ablation of Hansbreen, Zenodo, 10.5281/zenodo.8005257.","short":"J.M. Muñoz Hermosilla, (2023).","ieee":"J. M. Muñoz Hermosilla, “A 3D glacier dynamics-line plume model to estimate the frontal ablation of Hansbreen.” Zenodo, 2023.","ama":"Muñoz Hermosilla JM. 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We thank Marcel Verheijen for the support in the\r\nTEM analysis. This research and related results were made\r\npossible with the support of the NOMIS Foundation. It was\r\nsupported by the Scientific Service Units of ISTA through resources provided by the MIBA Machine Shop and the\r\nnanofabrication facility, the European Union’s Horizon 2020\r\nresearch and innovation programme under Grant Agreement\r\nNo 862046, the HORIZON-RIA 101069515 project and the\r\nFWF Projects #P-32235, #P-36507 and #F-8606. R.S.S.\r\nacknowledges Spanish CM “Talento Program” Project No.\r\n2022-T1/IND-24070.","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2306.07109"}],"article_number":"2306.07109","type":"preprint","author":[{"first_name":"Marco","full_name":"Valentini, Marco","id":"C0BB2FAC-D767-11E9-B658-BC13E6697425","last_name":"Valentini"},{"full_name":"Sagi, Oliver","id":"71616374-A8E9-11E9-A7CA-09ECE5697425","first_name":"Oliver","last_name":"Sagi"},{"last_name":"Baghumyan","first_name":"Levon","full_name":"Baghumyan, Levon"},{"full_name":"Gijsel, Thijs de","first_name":"Thijs de","last_name":"Gijsel"},{"last_name":"Jung","first_name":"Jason","full_name":"Jung, Jason","id":"4C9ACE7A-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Stefano","full_name":"Calcaterra, Stefano","last_name":"Calcaterra"},{"first_name":"Andrea","full_name":"Ballabio, Andrea","last_name":"Ballabio"},{"last_name":"Servin","first_name":"Juan Aguilera","full_name":"Servin, Juan Aguilera"},{"full_name":"Aggarwal, Kushagra","orcid":"0000-0001-9985-9293","id":"b22ab905-3539-11eb-84c3-fc159dcd79cb","first_name":"Kushagra","last_name":"Aggarwal"},{"first_name":"Marian","id":"396A1950-F248-11E8-B48F-1D18A9856A87","full_name":"Janik, Marian","orcid":"0009-0003-9037-8831","last_name":"Janik"},{"last_name":"Adletzberger","id":"38756BB2-F248-11E8-B48F-1D18A9856A87","full_name":"Adletzberger, Thomas","first_name":"Thomas"},{"first_name":"Rubén Seoane","full_name":"Souto, Rubén Seoane","last_name":"Souto"},{"last_name":"Leijnse","first_name":"Martin","full_name":"Leijnse, Martin"},{"first_name":"Jeroen","full_name":"Danon, Jeroen","last_name":"Danon"},{"last_name":"Schrade","first_name":"Constantin","full_name":"Schrade, Constantin"},{"full_name":"Bakkers, Erik","first_name":"Erik","last_name":"Bakkers"},{"full_name":"Chrastina, Daniel","first_name":"Daniel","last_name":"Chrastina"},{"last_name":"Isella","first_name":"Giovanni","full_name":"Isella, Giovanni"},{"last_name":"Katsaros","id":"38DB5788-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8342-202X","full_name":"Katsaros, Georgios","first_name":"Georgios"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"citation":{"ama":"Valentini M, Sagi O, Baghumyan L, et al. Radio frequency driven superconducting diode and parity conserving Cooper pair transport in a two-dimensional germanium hole gas. arXiv. doi:10.48550/arXiv.2306.07109","ieee":"M. Valentini et al., “Radio frequency driven superconducting diode and parity conserving Cooper pair transport in a two-dimensional germanium hole gas,” arXiv. .","short":"M. Valentini, O. Sagi, L. Baghumyan, T. de Gijsel, J. Jung, S. Calcaterra, A. Ballabio, J.A. Servin, K. Aggarwal, M. Janik, T. Adletzberger, R.S. Souto, M. Leijnse, J. Danon, C. Schrade, E. Bakkers, D. Chrastina, G. Isella, G. Katsaros, ArXiv (n.d.).","apa":"Valentini, M., Sagi, O., Baghumyan, L., Gijsel, T. de, Jung, J., Calcaterra, S., … Katsaros, G. (n.d.). Radio frequency driven superconducting diode and parity conserving Cooper pair transport in a two-dimensional germanium hole gas. arXiv. https://doi.org/10.48550/arXiv.2306.07109","mla":"Valentini, Marco, et al. “Radio Frequency Driven Superconducting Diode and Parity Conserving Cooper Pair Transport in a Two-Dimensional Germanium Hole Gas.” ArXiv, 2306.07109, doi:10.48550/arXiv.2306.07109.","ista":"Valentini M, Sagi O, Baghumyan L, Gijsel T de, Jung J, Calcaterra S, Ballabio A, Servin JA, Aggarwal K, Janik M, Adletzberger T, Souto RS, Leijnse M, Danon J, Schrade C, Bakkers E, Chrastina D, Isella G, Katsaros G. Radio frequency driven superconducting diode and parity conserving Cooper pair transport in a two-dimensional germanium hole gas. arXiv, 2306.07109.","chicago":"Valentini, Marco, Oliver Sagi, Levon Baghumyan, Thijs de Gijsel, Jason Jung, Stefano Calcaterra, Andrea Ballabio, et al. “Radio Frequency Driven Superconducting Diode and Parity Conserving Cooper Pair Transport in a Two-Dimensional Germanium Hole Gas.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2306.07109."},"acknowledged_ssus":[{"_id":"M-Shop"},{"_id":"NanoFab"}],"date_updated":"2026-10-02T10:23:31Z","date_published":"2023-06-13T00:00:00Z","publication":"arXiv","article_processing_charge":"No","doi":"10.48550/arXiv.2306.07109","fulldoi":"https://doi.org/10.48550/arXiv.2306.07109","date_created":"2023-07-26T11:17:20Z","publication_status":"draft","year":"2023","OA_place":"repository","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Radio frequency driven superconducting diode and parity conserving Cooper pair transport in a two-dimensional germanium hole gas","corr_author":"1","keyword":["Mesoscale and Nanoscale Physics"],"status":"public","day":"13","month":"06","related_material":{"record":[{"status":"public","id":"13286","relation":"dissertation_contains"},{"status":"public","id":"14793","relation":"later_version"}]},"oa_version":"Preprint","_id":"13312","ec_funded":1,"abstract":[{"lang":"eng","text":"Superconductor/semiconductor hybrid devices have attracted increasing\r\ninterest in the past years. Superconducting electronics aims to complement\r\nsemiconductor technology, while hybrid architectures are at the forefront of\r\nnew ideas such as topological superconductivity and protected qubits. In this\r\nwork, we engineer the induced superconductivity in two-dimensional germanium\r\nhole gas by varying the distance between the quantum well and the aluminum. We\r\ndemonstrate a hard superconducting gap and realize an electrically and flux\r\ntunable superconducting diode using a superconducting quantum interference\r\ndevice (SQUID). This allows to tune the current phase relation (CPR), to a\r\nregime where single Cooper pair tunneling is suppressed, creating a $ \\sin\r\n\\left( 2 \\varphi \\right)$ CPR. Shapiro experiments complement this\r\ninterpretation and the microwave drive allows to create a diode with $ \\approx\r\n100 \\%$ efficiency. The reported results open up the path towards monolithic\r\nintegration of spin qubit devices, microwave resonators and (protected)\r\nsuperconducting qubits on a silicon technology compatible platform."}],"project":[{"grant_number":"862046","_id":"237E5020-32DE-11EA-91FC-C7463DDC885E","call_identifier":"H2020","name":"TOPOLOGICALLY PROTECTED AND SCALABLE QUANTUM BITS"},{"_id":"237B3DA4-32DE-11EA-91FC-C7463DDC885E","grant_number":"P32235","name":"Towards scalable hut wire quantum devices","call_identifier":"FWF"},{"_id":"bd8bd29e-d553-11ed-ba76-f0070d4b237a","grant_number":"P36507","name":"Merging spin and superconducting qubits in planar Ge"},{"name":"Center for Correlated Quantum Materials and Solid State Quantum Systems: Conventional and unconventional topological superconductors","_id":"34a66131-11ca-11ed-8bc3-a31681c6b03e","grant_number":"F8606"},{"name":"Protected states of quantum matter","_id":"eb9b30ac-77a9-11ec-83b8-871f581d53d2"}],"department":[{"_id":"GeKa"},{"_id":"M-Shop"}],"external_id":{"arxiv":["2306.07109"]}},{"oa_version":"None","_id":"23036","author":[{"full_name":"Valentini, Marco","first_name":"Marco","last_name":"Valentini"}],"department":[{"_id":"GeKa"}],"citation":{"ama":"Valentini M. Data repository for “Parity-conserving Cooper-pair transport and ideal superconducting diode in planar Germanium.” 2023. doi:10.5281/zenodo.10119345","ieee":"M. Valentini, “Data repository for ‘Parity-conserving Cooper-pair transport and ideal superconducting diode in planar Germanium.’” Zenodo, 2023.","short":"M. Valentini, (2023).","apa":"Valentini, M. (2023). Data repository for “Parity-conserving Cooper-pair transport and ideal superconducting diode in planar Germanium.” Zenodo. https://doi.org/10.5281/zenodo.10119345","ista":"Valentini M. 2023. Data repository for ‘Parity-conserving Cooper-pair transport and ideal superconducting diode in planar Germanium’, Zenodo, 10.5281/zenodo.10119345.","mla":"Valentini, Marco. Data Repository for “Parity-Conserving Cooper-Pair Transport and Ideal Superconducting Diode in Planar Germanium.” Zenodo, 2023, doi:10.5281/zenodo.10119345.","chicago":"Valentini, Marco. “Data Repository for ‘Parity-Conserving Cooper-Pair Transport and Ideal Superconducting Diode in Planar Germanium.’” Zenodo, 2023. https://doi.org/10.5281/zenodo.10119345."},"status":"public","day":"13","related_material":{"record":[{"status":"public","id":"14793","relation":"used_in_publication"}]},"month":"11","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.10119345"}],"OA_type":"green","OA_place":"repository","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"research_data_reference","title":"Data repository for 'Parity-conserving Cooper-pair transport and ideal superconducting diode in planar Germanium'","date_created":"2026-10-02T10:23:47Z","year":"2023","article_processing_charge":"No","doi":"10.5281/zenodo.10119345","fulldoi":"https://doi.org/10.5281/zenodo.10119345","date_published":"2023-11-13T00:00:00Z","oa":1,"date_updated":"2026-10-02T10:23:54Z","ddc":["530"],"publisher":"Zenodo"},{"oa":1,"language":[{"iso":"eng"}],"ddc":["000"],"publisher":"International Conference on Learning Representations","file":[{"checksum":"aacbf11dbd8b02a3e0bfd942a33e0593","relation":"main_file","access_level":"open_access","date_created":"2024-08-05T07:52:44Z","content_type":"application/pdf","file_size":437492,"file_name":"2023_ICLR_Frantar.pdf","date_updated":"2024-08-05T07:52:44Z","file_id":"17385","creator":"dernst","success":1}],"acknowledgement":"Elias Frantar and Dan Alistarh gratefully acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 programme (grant agreement No. 805223 ScaleML), as well as experimental support from Eldar Kurtic, and from the IST Austria IT department, in particular Stefano Elefante, Andrei Hornoiu, and Alois Schloegl. The work of Saleh Ashkboos and Torsten Hoefler was supported by the PASC DaCeMI project, received EuroHPC-JU funding under grant MAELSTROM, No. 955513. We thank the Swiss National Supercomputing Center (CSCS) for supporting us with compute infrastructure.","type":"conference","acknowledged_ssus":[{"_id":"ScienComp"}],"file_date_updated":"2024-08-05T07:52:44Z","author":[{"last_name":"Frantar","first_name":"Elias","full_name":"Frantar, Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f"},{"first_name":"Saleh","full_name":"Ashkboos, Saleh","last_name":"Ashkboos"},{"last_name":"Hoefler","full_name":"Hoefler, Torsten","first_name":"Torsten"},{"last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian"}],"citation":{"chicago":"Frantar, Elias, Saleh Ashkboos, Torsten Hoefler, and Dan-Adrian Alistarh. “OPTQ: Accurate Post-Training Quantization for Generative Pre-Trained Transformers.” In 11th International Conference on Learning Representations . International Conference on Learning Representations, 2023.","apa":"Frantar, E., Ashkboos, S., Hoefler, T., & Alistarh, D.-A. (2023). OPTQ: Accurate post-training quantization for generative pre-trained transformers. In 11th International Conference on Learning Representations . Kigali, Rwanda: International Conference on Learning Representations.","ista":"Frantar E, Ashkboos S, Hoefler T, Alistarh D-A. 2023. OPTQ: Accurate post-training quantization for generative pre-trained transformers. 11th International Conference on Learning Representations . ICLR: International Conference on Learning Representations.","mla":"Frantar, Elias, et al. “OPTQ: Accurate Post-Training Quantization for Generative Pre-Trained Transformers.” 11th International Conference on Learning Representations , International Conference on Learning Representations, 2023.","short":"E. Frantar, S. Ashkboos, T. Hoefler, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , International Conference on Learning Representations, 2023.","ama":"Frantar E, Ashkboos S, Hoefler T, Alistarh D-A. OPTQ: Accurate post-training quantization for generative pre-trained transformers. In: 11th International Conference on Learning Representations . International Conference on Learning Representations; 2023.","ieee":"E. Frantar, S. Ashkboos, T. Hoefler, and D.-A. Alistarh, “OPTQ: Accurate post-training quantization for generative pre-trained transformers,” in 11th International Conference on Learning Representations , Kigali, Rwanda, 2023."},"conference":{"end_date":"2023-05-05","location":"Kigali, Rwanda","name":"ICLR: International Conference on Learning Representations","start_date":"2023-05-01"},"date_published":"2023-05-01T00:00:00Z","publication":"11th International Conference on Learning Representations ","quality_controlled":"1","date_updated":"2026-10-02T11:19:46Z","publication_status":"published","date_created":"2024-08-04T22:01:22Z","year":"2023","article_processing_charge":"No","scopus_import":"1","corr_author":"1","status":"public","month":"05","related_material":{"link":[{"url":"https://github.com/IST-DASLab/gptq","relation":"software"}],"record":[{"id":"17485","relation":"dissertation_contains","status":"public"}]},"day":"01","has_accepted_license":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"OPTQ: Accurate post-training quantization for generative pre-trained transformers","oa_version":"Published Version","ec_funded":1,"_id":"17378","abstract":[{"text":"Generative Pre-trained Transformer models, known as GPT or OPT, set themselves apart through breakthrough performance across complex language modelling tasks, but also by their extremely high computational and storage costs. Specifically, due to their massive size, even inference for large, highly-accurate GPT models may require multiple performant GPUs, which limits the usability of such models. While there is emerging work on relieving this pressure via model compression, the applicability and performance of existing compression techniques is limited by the scale and complexity of GPT models. In this paper, we address this challenge, and propose OPTQ, a new one-shot weight quantization method based on approximate second-order information, that is both highly-accurate and highly-efficient. Specifically, OPTQ can quantize GPT models with 175 billion parameters in approximately four GPU hours, reducing the bitwidth down to 3 or 4 bits per weight, with negligible accuracy degradation relative to the uncompressed baseline. Our method more than doubles the compression gains relative to previously-proposed one-shot quantization methods, preserving accuracy, allowing us for the first time to execute an 175 billion-parameter model inside a single GPU for generative inference. Moreover, we also show that our method can still provide reasonable accuracy in the extreme quantization regime, in which weights are quantized to 2-bit or even ternary quantization levels. We show experimentally that these improvements can be leveraged for end-to-end inference speedups over FP16, of around 3.25x when using high-end GPUs (NVIDIA A100) and 4.5x when using more cost-effective ones (NVIDIA A6000). The implementation is available at https://github.com/IST-DASLab/gptq.","lang":"eng"}],"project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020"}],"department":[{"_id":"DaAl"}]},{"title":"SparseGPT: Massive language models can be accurately pruned in one-shot","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"07","related_material":{"record":[{"status":"public","id":"17485","relation":"dissertation_contains"}]},"day":"30","status":"public","corr_author":"1","department":[{"_id":"DaAl"}],"project":[{"grant_number":"805223","_id":"268A44D6-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"Elastic Coordination for Scalable Machine Learning"}],"abstract":[{"lang":"eng","text":"We show for the first time that large-scale generative pretrained transformer (GPT) family models can be pruned to at least 50% sparsity in one-shot, without any retraining, at minimal loss of accuracy. This is achieved via a new pruning method called SparseGPT, specifically designed to work efficiently and accurately on massive GPT-family models. We can execute SparseGPT on the largest available open-source models, OPT-175B and BLOOM-176B, in under 4.5 hours, and can reach 60% unstructured sparsity with negligible increase in perplexity: remarkably, more than 100 billion weights from these models can be ignored at inference time. SparseGPT generalizes to semi-structured (2:4 and 4:8) patterns, and is compatible with weight quantization approaches. The code is available at: https://github.com/IST-DASLab/sparsegpt."}],"_id":"14458","ec_funded":1,"oa_version":"Preprint","external_id":{"arxiv":["2301.00774"]},"alternative_title":["PMLR"],"intvolume":" 202","date_updated":"2026-10-02T11:19:46Z","quality_controlled":"1","publication":"Proceedings of the 40th International Conference on Machine Learning","date_published":"2023-07-30T00:00:00Z","scopus_import":"1","article_processing_charge":"No","year":"2023","publication_status":"published","date_created":"2023-10-29T23:01:16Z","type":"conference","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2301.00774"}],"conference":{"location":"Honolulu, Hawaii, HI, United States","name":"ICML: International Conference on Machine Learning","start_date":"2023-07-23","end_date":"2023-07-29"},"citation":{"short":"E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 10323–10337.","ieee":"E. Frantar and D.-A. Alistarh, “SparseGPT: Massive language models can be accurately pruned in one-shot,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 10323–10337.","ama":"Frantar E, Alistarh D-A. SparseGPT: Massive language models can be accurately pruned in one-shot. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10323-10337.","chicago":"Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” In Proceedings of the 40th International Conference on Machine Learning, 202:10323–37. ML Research Press, 2023.","apa":"Frantar, E., & Alistarh, D.-A. (2023). SparseGPT: Massive language models can be accurately pruned in one-shot. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 10323–10337). Honolulu, Hawaii, HI, United States: ML Research Press.","mla":"Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 10323–37.","ista":"Frantar E, Alistarh D-A. 2023. SparseGPT: Massive language models can be accurately pruned in one-shot. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 10323–10337."},"author":[{"id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","full_name":"Frantar, Elias","first_name":"Elias","last_name":"Frantar"},{"last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X","first_name":"Dan-Adrian"}],"acknowledged_ssus":[{"_id":"ScienComp"}],"publisher":"ML Research Press","arxiv":1,"oa":1,"language":[{"iso":"eng"}],"page":"10323-10337","publication_identifier":{"eissn":["2640-3498"]},"volume":202,"acknowledgement":"The authors gratefully acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 programme (grant agreement No. 805223 ScaleML), as well as experimental support from Eldar Kurtic, and from the IST Austria IT department, in particular Stefano Elefante, Andrei Hornoiu, and Alois Schloegl."},{"author":[{"first_name":"Ilia","id":"D0CF4148-C985-11E9-8066-0BDEE5697425","full_name":"Markov, Ilia","last_name":"Markov"},{"last_name":"Vladu","first_name":"Adrian","full_name":"Vladu, Adrian"},{"full_name":"Guo, Qi","first_name":"Qi","last_name":"Guo"},{"first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh"}],"citation":{"short":"I. Markov, A. Vladu, Q. Guo, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 24020–24044.","ieee":"I. Markov, A. Vladu, Q. Guo, and D.-A. Alistarh, “Quantized distributed training of large models with convergence guarantees,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 24020–24044.","ama":"Markov I, Vladu A, Guo Q, Alistarh D-A. Quantized distributed training of large models with convergence guarantees. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:24020-24044.","chicago":"Markov, Ilia, Adrian Vladu, Qi Guo, and Dan-Adrian Alistarh. “Quantized Distributed Training of Large Models with Convergence Guarantees.” In Proceedings of the 40th International Conference on Machine Learning, 202:24020–44. ML Research Press, 2023.","apa":"Markov, I., Vladu, A., Guo, Q., & Alistarh, D.-A. (2023). Quantized distributed training of large models with convergence guarantees. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 24020–24044). Honolulu, Hawaii, HI, United States: ML Research Press.","mla":"Markov, Ilia, et al. “Quantized Distributed Training of Large Models with Convergence Guarantees.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 24020–44.","ista":"Markov I, Vladu A, Guo Q, Alistarh D-A. 2023. Quantized distributed training of large models with convergence guarantees. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 24020–24044."},"conference":{"end_date":"2023-07-29","location":"Honolulu, Hawaii, HI, United States","start_date":"2023-07-23","name":"ICML: International Conference on Machine Learning"},"acknowledged_ssus":[{"_id":"ScienComp"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2302.02390"}],"type":"conference","volume":202,"publication_identifier":{"eissn":["2640-3498"]},"acknowledgement":"The authors gratefully acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), as well as experimental support from the IST Austria IT department, in particular Stefano Elefante, Andrei Hornoiu, and Alois Schloegl. AV acknowledges the support of the French Agence Nationale de la Recherche (ANR), under grant ANR-21-CE48-0016 (project COMCOPT), the support of Fondation Hadamard with a PRMO grant, and the support of CNRS with a CoopIntEER IEA grant (project ALFRED).","publisher":"ML Research Press","page":"24020-24044","arxiv":1,"oa":1,"language":[{"iso":"eng"}],"ec_funded":1,"_id":"14461","abstract":[{"text":"Communication-reduction techniques are a popular way to improve scalability in data-parallel training of deep neural networks (DNNs). The recent emergence of large language models such as GPT has created the need for new approaches to exploit data-parallelism. Among these, fully-sharded data parallel (FSDP) training is highly popular, yet it still encounters scalability bottlenecks. One reason is that applying compression techniques to FSDP is challenging: as the vast majority of the communication involves the model’s weights, direct compression alters convergence and leads to accuracy loss. We present QSDP, a variant of FSDP which supports both gradient and weight quantization with theoretical guarantees, is simple to implement and has essentially no overheads. To derive QSDP we prove that a natural modification of SGD achieves convergence even when we only maintain quantized weights, and thus the domain over which we train consists of quantized points and is, therefore, highly non-convex. We validate this approach by training GPT-family models with up to 1.3 billion parameters on a multi-node cluster. Experiments show that QSDP preserves model accuracy, while completely removing the communication bottlenecks of FSDP, providing end-to-end speedups of up to 2.2x.","lang":"eng"}],"oa_version":"Preprint","department":[{"_id":"DaAl"}],"project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020"}],"alternative_title":["PMLR"],"external_id":{"arxiv":["2302.02390"]},"title":"Quantized distributed training of large models with convergence guarantees","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","corr_author":"1","day":"30","related_material":{"record":[{"relation":"dissertation_contains","id":"17490","status":"public"}]},"month":"07","status":"public","article_processing_charge":"No","scopus_import":"1","publication_status":"published","date_created":"2023-10-29T23:01:17Z","year":"2023","date_updated":"2026-10-02T11:20:05Z","quality_controlled":"1","intvolume":" 202","date_published":"2023-07-30T00:00:00Z","publication":"Proceedings of the 40th International Conference on Machine Learning"},{"author":[{"last_name":"Fäßler","id":"404F5528-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7149-769X","full_name":"Fäßler, Florian","first_name":"Florian"},{"last_name":"Javoor","first_name":"Manjunath","full_name":"Javoor, Manjunath","orcid":"0000-0003-2311-2112","id":"305ab18b-dc7d-11ea-9b2f-b58195228ea2"},{"full_name":"Datler, Julia","orcid":"0000-0002-3616-8580","id":"3B12E2E6-F248-11E8-B48F-1D18A9856A87","first_name":"Julia","last_name":"Datler"},{"full_name":"Döring, Hermann","first_name":"Hermann","last_name":"Döring"},{"last_name":"Hofer","id":"b9d234ba-9e33-11ed-95b6-cd561df280e6","full_name":"Hofer, Florian","first_name":"Florian"},{"first_name":"Georgi A","orcid":"0000-0001-8370-6161","full_name":"Dimchev, Georgi A","id":"38C393BE-F248-11E8-B48F-1D18A9856A87","last_name":"Dimchev"},{"last_name":"Hodirnau","id":"3661B498-F248-11E8-B48F-1D18A9856A87","full_name":"Hodirnau, Victor-Valentin","orcid":"0000-0003-3904-947X","first_name":"Victor-Valentin"},{"first_name":"Jan","full_name":"Faix, Jan","last_name":"Faix"},{"last_name":"Rottner","full_name":"Rottner, Klemens","first_name":"Klemens"},{"id":"48AD8942-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4790-8078","full_name":"Schur, Florian KM","first_name":"Florian KM","last_name":"Schur"}],"file_date_updated":"2023-01-23T07:45:54Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"citation":{"ama":"Fäßler F, Javoor M, Datler J, et al. ArpC5 isoforms regulate Arp2/3 complex–dependent protrusion through differential Ena/VASP positioning. Science Advances. 2023;9(3). doi:10.1126/sciadv.add6495","ieee":"F. Fäßler et al., “ArpC5 isoforms regulate Arp2/3 complex–dependent protrusion through differential Ena/VASP positioning,” Science Advances, vol. 9, no. 3. American Association for the Advancement of Science, 2023.","short":"F. Fäßler, M. Javoor, J. Datler, H. Döring, F. Hofer, G.A. Dimchev, V.-V. Hodirnau, J. Faix, K. Rottner, F.K. Schur, Science Advances 9 (2023).","mla":"Fäßler, Florian, et al. “ArpC5 Isoforms Regulate Arp2/3 Complex–Dependent Protrusion through Differential Ena/VASP Positioning.” Science Advances, vol. 9, no. 3, add6495, American Association for the Advancement of Science, 2023, doi:10.1126/sciadv.add6495.","ista":"Fäßler F, Javoor M, Datler J, Döring H, Hofer F, Dimchev GA, Hodirnau V-V, Faix J, Rottner K, Schur FK. 2023. ArpC5 isoforms regulate Arp2/3 complex–dependent protrusion through differential Ena/VASP positioning. Science Advances. 9(3), add6495.","apa":"Fäßler, F., Javoor, M., Datler, J., Döring, H., Hofer, F., Dimchev, G. A., … Schur, F. K. (2023). ArpC5 isoforms regulate Arp2/3 complex–dependent protrusion through differential Ena/VASP positioning. Science Advances. American Association for the Advancement of Science. https://doi.org/10.1126/sciadv.add6495","chicago":"Fäßler, Florian, Manjunath Javoor, Julia Datler, Hermann Döring, Florian Hofer, Georgi A Dimchev, Victor-Valentin Hodirnau, Jan Faix, Klemens Rottner, and Florian KM Schur. “ArpC5 Isoforms Regulate Arp2/3 Complex–Dependent Protrusion through Differential Ena/VASP Positioning.” Science Advances. American Association for the Advancement of Science, 2023. https://doi.org/10.1126/sciadv.add6495."},"acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"LifeSc"},{"_id":"Bio"},{"_id":"EM-Fac"}],"article_number":"add6495","issue":"3","type":"journal_article","volume":9,"publication_identifier":{"issn":["2375-2548"]},"file":[{"success":1,"file_id":"12335","creator":"dernst","date_updated":"2023-01-23T07:45:54Z","file_name":"2023_ScienceAdvances_Faessler.pdf","file_size":1756234,"content_type":"application/pdf","date_created":"2023-01-23T07:45:54Z","access_level":"open_access","relation":"main_file","checksum":"ce81a6d0b84170e5e8c62f6acfa15d9e"}],"acknowledgement":"We would like to thank K. von Peinen and B. Denker (Helmholtz Centre for Infection Research, Braunschweig, Germany) for experimental and technical assistance, respectively.\r\nThis research was supported by the Scientific Service Units (SSUs) of ISTA through resources provided by Scientific Computing (SciComp), the Life Science Facility (LSF), the Imaging and Optics facility (IOF), and the Electron Microscopy Facility (EMF). We acknowledge support from ISTA and from the Austrian Science Fund (FWF) (P33367) to F.K.M.S., from the Research Training Group GRK2223 and the Helmholtz Society to K.R,. and from the Deutsche Forschungsgemeinschaft (DFG) to J.F. and K.R.","ddc":["570"],"publisher":"American Association for the Advancement of Science","language":[{"iso":"eng"}],"oa":1,"abstract":[{"text":"Regulation of the Arp2/3 complex is required for productive nucleation of branched actin networks. An emerging aspect of regulation is the incorporation of subunit isoforms into the Arp2/3 complex. Specifically, both ArpC5 subunit isoforms, ArpC5 and ArpC5L, have been reported to fine-tune nucleation activity and branch junction stability. We have combined reverse genetics and cellular structural biology to describe how ArpC5 and ArpC5L differentially affect cell migration. Both define the structural stability of ArpC1 in branch junctions and, in turn, by determining protrusion characteristics, affect protein dynamics and actin network ultrastructure. ArpC5 isoforms also affect the positioning of members of the Ena/Vasodilator-stimulated phosphoprotein (VASP) family of actin filament elongators, which mediate ArpC5 isoform–specific effects on the actin assembly level. Our results suggest that ArpC5 and Ena/VASP proteins are part of a signaling pathway enhancing cell migration.","lang":"eng"}],"_id":"12334","oa_version":"Published Version","department":[{"_id":"FlSc"},{"_id":"EM-Fac"}],"project":[{"name":"Structure and isoform diversity of the Arp2/3 complex","_id":"9B954C5C-BA93-11EA-9121-9846C619BF3A","grant_number":"P33367"}],"external_id":{"isi":["000964550100015"],"pmid":["36662867"]},"has_accepted_license":"1","title":"ArpC5 isoforms regulate Arp2/3 complex–dependent protrusion through differential Ena/VASP positioning","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","corr_author":"1","keyword":["Multidisciplinary"],"month":"01","related_material":{"record":[{"id":"14562","relation":"research_data","status":"public"},{"status":"public","relation":"dissertation_contains","id":"22744"},{"status":"public","id":"18766","relation":"dissertation_contains"}]},"day":"20","isi":1,"status":"public","article_processing_charge":"No","scopus_import":"1","fulldoi":"https://doi.org/10.1126/sciadv.add6495","doi":"10.1126/sciadv.add6495","date_created":"2023-01-23T07:26:42Z","article_type":"original","publication_status":"published","year":"2023","date_updated":"2026-10-02T11:21:19Z","quality_controlled":"1","intvolume":" 9","date_published":"2023-01-20T00:00:00Z","publication":"Science Advances","pmid":1},{"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2308.00516"}],"OA_place":"repository","article_number":"2308.00516","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"preprint","title":"Contractive coupling rates and curvature lower bounds for Markov chains","corr_author":"1","status":"public","related_material":{"record":[{"relation":"later_version","id":"20040","status":"public"},{"status":"public","id":"17336","relation":"dissertation_contains"}]},"day":"02","month":"08","oa_version":"Preprint","_id":"17351","author":[{"last_name":"Pedrotti","full_name":"Pedrotti, Francesco","id":"d3ac8ac6-dc8d-11ea-abe3-e2a9628c4c3c","first_name":"Francesco"}],"abstract":[{"lang":"eng","text":"Contractive coupling rates have been recently introduced by Conforti as a\r\ntool to establish convex Sobolev inequalities (including modified log-Sobolev\r\nand Poincar\\'{e} inequality) for some classes of Markov chains. In this work,\r\nwe show how contractive coupling rates can also be used to prove stronger\r\ninequalities, in the form of curvature lower bounds for Markov chains and\r\ngeodesic convexity of entropic functionals. We illustrate this in several\r\nexamples discussed by Conforti, where in particular, after appropriately\r\nchoosing a parameter function, we establish positive curvature in the entropic\r\nand (discrete) Bakry--\\'{E}mery sense. In addition, we recall and give\r\nstraightforward generalizations of some notions of coarse Ricci curvature, and\r\nwe discuss some of their properties and relations with the concepts of\r\ncouplings and coupling rates: as an application, we show exponential\r\ncontraction of the $p$-Wasserstein distance for the heat flow in the\r\naforementioned examples."}],"department":[{"_id":"JaMa"}],"citation":{"chicago":"Pedrotti, Francesco. “Contractive Coupling Rates and Curvature Lower Bounds for Markov Chains.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2308.00516.","mla":"Pedrotti, Francesco. “Contractive Coupling Rates and Curvature Lower Bounds for Markov Chains.” ArXiv, 2308.00516, doi:10.48550/arXiv.2308.00516.","ista":"Pedrotti F. Contractive coupling rates and curvature lower bounds for Markov chains. arXiv, 2308.00516.","apa":"Pedrotti, F. (n.d.). Contractive coupling rates and curvature lower bounds for Markov chains. arXiv. https://doi.org/10.48550/arXiv.2308.00516","short":"F. Pedrotti, ArXiv (n.d.).","ieee":"F. Pedrotti, “Contractive coupling rates and curvature lower bounds for Markov chains,” arXiv. .","ama":"Pedrotti F. Contractive coupling rates and curvature lower bounds for Markov chains. arXiv. doi:10.48550/arXiv.2308.00516"},"external_id":{"arxiv":["2308.00516"]},"date_updated":"2026-10-02T11:25:17Z","date_published":"2023-08-02T00:00:00Z","oa":1,"language":[{"iso":"eng"}],"arxiv":1,"publication":"arXiv","article_processing_charge":"No","doi":"10.48550/arXiv.2308.00516","fulldoi":"https://doi.org/10.48550/arXiv.2308.00516","publication_status":"draft","date_created":"2024-07-31T08:02:16Z","year":"2023"},{"type":"journal_article","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"E-Lib"},{"_id":"LifeSc"},{"_id":"M-Shop"}],"file_date_updated":"2025-02-26T08:01:57Z","author":[{"last_name":"Velicky","first_name":"Philipp","id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","full_name":"Velicky, Philipp","orcid":"0000-0002-2340-7431"},{"last_name":"Miguel Villalba","first_name":"Eder","orcid":"0000-0001-5665-0430","full_name":"Miguel Villalba, Eder","id":"3FB91342-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Julia M","id":"443DB6DE-F248-11E8-B48F-1D18A9856A87","full_name":"Michalska, Julia M","orcid":"0000-0003-3862-1235","last_name":"Michalska"},{"first_name":"Julia","full_name":"Lyudchik, Julia","id":"46E28B80-F248-11E8-B48F-1D18A9856A87","last_name":"Lyudchik"},{"last_name":"Wei","full_name":"Wei, Donglai","first_name":"Donglai"},{"first_name":"Zudi","full_name":"Lin, Zudi","last_name":"Lin"},{"first_name":"Jake","orcid":"0000-0002-8698-3823","full_name":"Watson, Jake","id":"63836096-4690-11EA-BD4E-32803DDC885E","last_name":"Watson"},{"full_name":"Troidl, Jakob","first_name":"Jakob","last_name":"Troidl"},{"first_name":"Johanna","full_name":"Beyer, Johanna","last_name":"Beyer"},{"last_name":"Ben Simon","first_name":"Yoav","id":"43DF3136-F248-11E8-B48F-1D18A9856A87","full_name":"Ben Simon, Yoav"},{"first_name":"Christoph M","full_name":"Sommer, Christoph M","orcid":"0000-0003-1216-9105","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","last_name":"Sommer"},{"last_name":"Jahr","orcid":"0000-0003-0201-2315","full_name":"Jahr, Wiebke","id":"425C1CE8-F248-11E8-B48F-1D18A9856A87","first_name":"Wiebke"},{"last_name":"Cenameri","full_name":"Cenameri, Alban","id":"9ac8f577-2357-11eb-997a-e566c5550886","first_name":"Alban"},{"first_name":"Johannes","full_name":"Broichhagen, Johannes","last_name":"Broichhagen"},{"last_name":"Grant","first_name":"Seth G.N.","full_name":"Grant, Seth G.N."},{"last_name":"Jonas","first_name":"Peter M","id":"353C1B58-F248-11E8-B48F-1D18A9856A87","full_name":"Jonas, Peter M","orcid":"0000-0001-5001-4804"},{"last_name":"Novarino","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7673-7178","full_name":"Novarino, Gaia","first_name":"Gaia"},{"first_name":"Hanspeter","full_name":"Pfister, Hanspeter","last_name":"Pfister"},{"last_name":"Bickel","id":"49876194-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6511-9385","full_name":"Bickel, Bernd","first_name":"Bernd"},{"id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","full_name":"Danzl, Johann G","orcid":"0000-0001-8559-3973","first_name":"Johann G","last_name":"Danzl"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"citation":{"apa":"Velicky, P., Miguel Villalba, E., Michalska, J. M., Lyudchik, J., Wei, D., Lin, Z., … Danzl, J. G. (2023). Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. Springer Nature. https://doi.org/10.1038/s41592-023-01936-6","mla":"Velicky, Philipp, et al. “Dense 4D Nanoscale Reconstruction of Living Brain Tissue.” Nature Methods, vol. 20, Springer Nature, 2023, pp. 1256–65, doi:10.1038/s41592-023-01936-6.","ista":"Velicky P, Miguel Villalba E, Michalska JM, Lyudchik J, Wei D, Lin Z, Watson J, Troidl J, Beyer J, Ben Simon Y, Sommer CM, Jahr W, Cenameri A, Broichhagen J, Grant SGN, Jonas PM, Novarino G, Pfister H, Bickel B, Danzl JG. 2023. Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. 20, 1256–1265.","chicago":"Velicky, Philipp, Eder Miguel Villalba, Julia M Michalska, Julia Lyudchik, Donglai Wei, Zudi Lin, Jake Watson, et al. “Dense 4D Nanoscale Reconstruction of Living Brain Tissue.” Nature Methods. Springer Nature, 2023. https://doi.org/10.1038/s41592-023-01936-6.","ieee":"P. Velicky et al., “Dense 4D nanoscale reconstruction of living brain tissue,” Nature Methods, vol. 20. Springer Nature, pp. 1256–1265, 2023.","ama":"Velicky P, Miguel Villalba E, Michalska JM, et al. Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. 2023;20:1256-1265. doi:10.1038/s41592-023-01936-6","short":"P. Velicky, E. Miguel Villalba, J.M. Michalska, J. Lyudchik, D. Wei, Z. Lin, J. Watson, J. Troidl, J. Beyer, Y. Ben Simon, C.M. Sommer, W. Jahr, A. Cenameri, J. Broichhagen, S.G.N. Grant, P.M. Jonas, G. Novarino, H. Pfister, B. Bickel, J.G. Danzl, Nature Methods 20 (2023) 1256–1265."},"page":"1256-1265","oa":1,"language":[{"iso":"eng"}],"ddc":["570"],"publisher":"Springer Nature","file":[{"success":1,"file_id":"19088","creator":"dernst","date_updated":"2025-02-26T08:01:57Z","file_name":"2023_NatureMethods_Velicky.pdf","file_size":14103039,"content_type":"application/pdf","access_level":"open_access","date_created":"2025-02-26T08:01:57Z","relation":"main_file","checksum":"a68e845780a82ea36d0d4d3212a87c10"}],"acknowledgement":"We thank J. Vorlaufer, N. Agudelo and A. Wartak for microscope maintenance and troubleshooting, C. Kreuzinger and A. Freeman for technical assistance, M. Šuplata for hardware control support and M. Cunha dos Santos for initial exploration of software. We\r\nthank P. Henderson for advice on deep-learning training and M. Sixt, S. Boyd and T. Weiss for discussions and critical reading of the manuscript. L. Lavis (Janelia Research Campus) generously provided the JF585-HaloTag ligand. We acknowledge expert support by IST\r\nAustria’s scientific computing, imaging and optics, preclinical, library and laboratory support facilities and by the Miba machine shop. We gratefully acknowledge funding by the following sources: Austrian Science Fund (F.W.F.) grant no. I3600-B27 (J.G.D.), grant no. DK W1232\r\n(J.G.D. and J.M.M.) and grant no. Z 312-B27, Wittgenstein award (P.J.); the Gesellschaft für Forschungsförderung NÖ grant no. LSC18-022 (J.G.D.); an ISTA Interdisciplinary project grant (J.G.D. and B.B.); the European Union’s Horizon 2020 research and innovation programme,\r\nMarie-Skłodowska Curie grant 665385 (J.M.M. and J.L.); the European Union’s Horizon 2020 research and innovation programme, European Research Council grant no. 715767, MATERIALIZABLE (B.B.); grant no. 715508, REVERSEAUTISM (G.N.); grant no. 695568, SYNNOVATE (S.G.N.G.); and grant no. 692692, GIANTSYN (P.J.); the Simons\r\nFoundation Autism Research Initiative grant no. 529085 (S.G.N.G.); the Wellcome Trust Technology Development grant no. 202932 (S.G.N.G.); the Marie Skłodowska-Curie Actions Individual Fellowship no. 101026635 under the EU Horizon 2020 program (J.F.W.);\r\nthe Human Frontier Science Program postdoctoral fellowship LT000557/2018 (W.J.); and the National Science Foundation grant no. IIS-1835231 (H.P.) and NCS-FO-2124179 (H.P.).","volume":20,"publication_identifier":{"eissn":["1548-7105"],"issn":["1548-7091"]},"corr_author":"1","isi":1,"status":"public","month":"08","related_material":{"record":[{"relation":"research_data","id":"12817","status":"public"},{"id":"14770","relation":"shorter_version","status":"public"},{"relation":"earlier_version","id":"11943","status":"public"},{"id":"18674","relation":"dissertation_contains","status":"public"}],"link":[{"relation":"software","url":"https://github.com/danzllab/LIONESS"}]},"day":"01","has_accepted_license":"1","OA_type":"hybrid","OA_place":"publisher","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Dense 4D nanoscale reconstruction of living brain tissue","external_id":{"isi":["001025621500001"],"pmid":["37429995"]},"oa_version":"Published Version","_id":"13267","abstract":[{"text":"Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.","lang":"eng"}],"ec_funded":1,"project":[{"name":"Optical control of synaptic function via adhesion molecules","call_identifier":"FWF","_id":"265CB4D0-B435-11E9-9278-68D0E5697425","grant_number":"I03600"},{"name":"Molecular Drug Targets","call_identifier":"FWF","_id":"2548AE96-B435-11E9-9278-68D0E5697425","grant_number":"W1232"},{"grant_number":"Z00312","_id":"25C5A090-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Synaptic communication in neuronal microcircuits"},{"name":"High content imaging to decode human immune cell interactions in health and allergic disease","grant_number":"LS18-022","_id":"23889792-32DE-11EA-91FC-C7463DDC885E"},{"name":"International IST Doctoral Program","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"},{"name":"MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and Modeling","call_identifier":"H2020","_id":"24F9549A-B435-11E9-9278-68D0E5697425","grant_number":"715767"},{"name":"Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo and in vitro Models","call_identifier":"H2020","_id":"25444568-B435-11E9-9278-68D0E5697425","grant_number":"715508"},{"name":"Biophysics and circuit function of a giant cortical glutamatergic synapse","call_identifier":"H2020","_id":"25B7EB9E-B435-11E9-9278-68D0E5697425","grant_number":"692692"},{"grant_number":"101026635","_id":"fc2be41b-9c52-11eb-aca3-faa90aa144e9","call_identifier":"H2020","name":"Synaptic computations of the hippocampal CA3 circuitry"},{"_id":"2668BFA0-B435-11E9-9278-68D0E5697425","grant_number":"LT00057","name":"High-speed 3D-nanoscopy to study the role of adhesion during 3D cell migration"}],"department":[{"_id":"PeJo"},{"_id":"GaNo"},{"_id":"BeBi"},{"_id":"JoDa"},{"_id":"Bio"}],"date_published":"2023-08-01T00:00:00Z","pmid":1,"publication":"Nature Methods","date_updated":"2026-10-02T11:27:12Z","quality_controlled":"1","intvolume":" 20","date_created":"2023-07-23T22:01:13Z","publication_status":"published","article_type":"original","year":"2023","article_processing_charge":"Yes (in subscription journal)","scopus_import":"1","doi":"10.1038/s41592-023-01936-6","fulldoi":"https://doi.org/10.1038/s41592-023-01936-6"},{"intvolume":" 14","date_updated":"2026-10-02T11:28:16Z","quality_controlled":"1","pmid":1,"publication":"Nature Communications","date_published":"2023-07-05T00:00:00Z","doi":"10.1038/s41467-023-39656-2","fulldoi":"https://doi.org/10.1038/s41467-023-39656-2","scopus_import":"1","article_processing_charge":"No","year":"2023","article_type":"original","date_created":"2023-07-16T22:01:08Z","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Inductively shunted transmons exhibit noise insensitive plasmon states and a fluxon decay exceeding 3 hours","has_accepted_license":"1","isi":1,"status":"public","day":"05","month":"07","related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"17133"}]},"corr_author":"1","project":[{"_id":"2622978C-B435-11E9-9278-68D0E5697425","name":"Hybrid Semiconductor - Superconductor Quantum Devices"},{"name":"QUANTUM INFORMATION SYSTEMS BEYOND CLASSICAL CAPABILITIES / P5- Integration of Superconducting Quantum Circuits","grant_number":"F07105","_id":"bdb108fd-d553-11ed-ba76-83dc74a9864f"}],"department":[{"_id":"JoFi"}],"oa_version":"Published Version","_id":"13227","abstract":[{"lang":"eng","text":"Currently available quantum processors are dominated by noise, which severely limits their applicability and motivates the search for new physical qubit encodings. In this work, we introduce the inductively shunted transmon, a weakly flux-tunable superconducting qubit that offers charge offset protection for all levels and a 20-fold reduction in flux dispersion compared to the state-of-the-art resulting in a constant coherence over a full flux quantum. The parabolic confinement provided by the inductive shunt as well as the linearity of the geometric superinductor facilitates a high-power readout that resolves quantum jumps with a fidelity and QND-ness of >90% and without the need for a Josephson parametric amplifier. Moreover, the device reveals quantum tunneling physics between the two prepared fluxon ground states with a measured average decay time of up to 3.5 h. In the future, fast time-domain control of the transition matrix elements could offer a new path forward to also achieve full qubit control in the decay-protected fluxon basis."}],"external_id":{"pmid":["37407570"],"isi":["001024729900009"]},"publisher":"Springer Nature","ddc":["530"],"oa":1,"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["2041-1723"]},"volume":14,"acknowledgement":"The authors thank J. Koch for discussions and support with the scQubits python package, I. Rozhansky and A. Poddubny for important insights into photon-assisted tunneling, S. Barzanjeh and G. Arnold for theory, E. Redchenko, S. Pepic, the MIBA workshop and the IST nanofabrication facility for technical contributions, as well as L. Drmic, P. Zielinski and R. Sett for software development. We acknowledge the prompt support of Quantum Machines to implement active state preparation with their OPX+. This work was supported by a NOMIS foundation research grant (J.F.), the Austrian Science Fund (FWF) through BeyondC F7105 (J.F.) and IST Austria.","file":[{"date_created":"2023-07-18T08:43:07Z","content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"a85773b5fe23516f60f7d5d31b55c200","success":1,"creator":"dernst","file_id":"13248","date_updated":"2023-07-18T08:43:07Z","file_name":"2023_NatureComm_Hassani.pdf","file_size":2899592}],"type":"journal_article","article_number":"3968","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"citation":{"mla":"Hassani, Farid, et al. “Inductively Shunted Transmons Exhibit Noise Insensitive Plasmon States and a Fluxon Decay Exceeding 3 Hours.” Nature Communications, vol. 14, 3968, Springer Nature, 2023, doi:10.1038/s41467-023-39656-2.","ista":"Hassani F, Peruzzo M, Kapoor L, Trioni A, Zemlicka M, Fink JM. 2023. Inductively shunted transmons exhibit noise insensitive plasmon states and a fluxon decay exceeding 3 hours. Nature Communications. 14, 3968.","apa":"Hassani, F., Peruzzo, M., Kapoor, L., Trioni, A., Zemlicka, M., & Fink, J. M. (2023). Inductively shunted transmons exhibit noise insensitive plasmon states and a fluxon decay exceeding 3 hours. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-023-39656-2","chicago":"Hassani, Farid, Matilda Peruzzo, Lucky Kapoor, Andrea Trioni, Martin Zemlicka, and Johannes M Fink. “Inductively Shunted Transmons Exhibit Noise Insensitive Plasmon States and a Fluxon Decay Exceeding 3 Hours.” Nature Communications. Springer Nature, 2023. https://doi.org/10.1038/s41467-023-39656-2.","ieee":"F. Hassani, M. Peruzzo, L. Kapoor, A. Trioni, M. Zemlicka, and J. M. Fink, “Inductively shunted transmons exhibit noise insensitive plasmon states and a fluxon decay exceeding 3 hours,” Nature Communications, vol. 14. Springer Nature, 2023.","ama":"Hassani F, Peruzzo M, Kapoor L, Trioni A, Zemlicka M, Fink JM. Inductively shunted transmons exhibit noise insensitive plasmon states and a fluxon decay exceeding 3 hours. Nature Communications. 2023;14. doi:10.1038/s41467-023-39656-2","short":"F. Hassani, M. Peruzzo, L. Kapoor, A. Trioni, M. Zemlicka, J.M. Fink, Nature Communications 14 (2023)."},"file_date_updated":"2023-07-18T08:43:07Z","author":[{"last_name":"Hassani","first_name":"Farid","full_name":"Hassani, Farid","orcid":"0000-0001-6937-5773","id":"2AED110C-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Peruzzo","first_name":"Matilda","id":"3F920B30-F248-11E8-B48F-1D18A9856A87","full_name":"Peruzzo, Matilda","orcid":"0000-0002-3415-4628"},{"id":"84b9700b-15b2-11ec-abd3-831089e67615","orcid":"0000-0001-8319-2148","full_name":"Kapoor, Lucky","first_name":"Lucky","last_name":"Kapoor"},{"last_name":"Trioni","id":"42F71B44-F248-11E8-B48F-1D18A9856A87","full_name":"Trioni, Andrea","first_name":"Andrea"},{"last_name":"Zemlicka","first_name":"Martin","id":"2DCF8DE6-F248-11E8-B48F-1D18A9856A87","full_name":"Zemlicka, Martin","orcid":"0009-0005-0878-3032"},{"id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8112-028X","full_name":"Fink, Johannes M","first_name":"Johannes M","last_name":"Fink"}],"acknowledged_ssus":[{"_id":"M-Shop"},{"_id":"NanoFab"}]},{"publication":"arXiv","date_published":"2023-12-23T00:00:00Z","date_updated":"2026-10-02T11:31:29Z","year":"2023","date_created":"2024-06-26T08:56:52Z","publication_status":"draft","fulldoi":"https://doi.org/10.48550/arXiv.2310.06677","doi":"10.48550/arXiv.2310.06677","article_processing_charge":"No","month":"12","related_material":{"record":[{"id":"18764","relation":"later_version","status":"public"},{"id":"20575","relation":"dissertation_contains","status":"public"},{"status":"public","relation":"dissertation_contains","id":"17164"}]},"day":"23","status":"public","corr_author":"1","title":"Prethermalization for deformed Wigner Matrices","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","OA_place":"repository","external_id":{"arxiv":["2310.06677"]},"project":[{"grant_number":"101020331","_id":"62796744-2b32-11ec-9570-940b20777f1d","call_identifier":"H2020","name":"Random matrices beyond Wigner-Dyson-Mehta"}],"department":[{"_id":"LaEr"}],"ec_funded":1,"abstract":[{"lang":"eng","text":"We prove that a class of weakly perturbed Hamiltonians of the form $H_λ= H_0 + λW$, with $W$ being a Wigner matrix, exhibits prethermalization. That is, the time evolution generated by $H_λ$ relaxes to its ultimate thermal state via an intermediate prethermal state with a lifetime of order $λ^{-2}$. Moreover, we obtain a general relaxation formula, expressing the perturbed dynamics via the unperturbed dynamics and the ultimate thermal state. The proof relies on a two-resolvent law for the deformed Wigner matrix $H_λ$."}],"_id":"17174","oa_version":"Preprint","arxiv":1,"language":[{"iso":"eng"}],"oa":1,"type":"preprint","article_number":"2310.06677","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2310.06677","open_access":"1"}],"citation":{"short":"L. Erdös, S.J. Henheik, J. Reker, V. Riabov, ArXiv (n.d.).","ieee":"L. Erdös, S. J. Henheik, J. Reker, and V. Riabov, “Prethermalization for deformed Wigner Matrices,” arXiv. .","ama":"Erdös L, Henheik SJ, Reker J, Riabov V. Prethermalization for deformed Wigner Matrices. arXiv. doi:10.48550/arXiv.2310.06677","chicago":"Erdös, László, Sven Joscha Henheik, Jana Reker, and Volodymyr Riabov. “Prethermalization for Deformed Wigner Matrices.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2310.06677.","ista":"Erdös L, Henheik SJ, Reker J, Riabov V. Prethermalization for deformed Wigner Matrices. arXiv, 2310.06677.","mla":"Erdös, László, et al. “Prethermalization for Deformed Wigner Matrices.” ArXiv, 2310.06677, doi:10.48550/arXiv.2310.06677.","apa":"Erdös, L., Henheik, S. J., Reker, J., & Riabov, V. (n.d.). Prethermalization for deformed Wigner Matrices. arXiv. https://doi.org/10.48550/arXiv.2310.06677"},"author":[{"id":"4DBD5372-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5366-9603","full_name":"Erdös, László","first_name":"László","last_name":"Erdös"},{"first_name":"Sven Joscha","full_name":"Henheik, Sven Joscha","orcid":"0000-0003-1106-327X","id":"31d731d7-d235-11ea-ad11-b50331c8d7fb","last_name":"Henheik"},{"first_name":"Jana","full_name":"Reker, Jana","id":"e796e4f9-dc8d-11ea-abe3-97e26a0323e9","last_name":"Reker"},{"full_name":"Riabov, Volodymyr","id":"1949f904-edfb-11eb-afb5-e2dfddabb93b","first_name":"Volodymyr","last_name":"Riabov"}]}]