@article{21762, abstract = {Bacteria, like eukaryotes, use conserved cytoskeletal systems for intracellular organization. The plasmid-encoded ParMRC system forms actin-like filaments that segregate low–copy number plasmids. In multicellular cyanobacteria such as Anabaena sp., we found that a chromosomally encoded ParMR system has evolved into a cytoskeletal system named CorMR with a function in cell shape control rather than DNA segregation. Live-cell imaging, in vitro reconstitution, and cryo–electron microscopy revealed that CorM formed dynamically unstable, antiparallel double-stranded filaments that were recruited to the membrane by CorR through an amphipathic helix conserved in multicellular cyanobacteria. CorMR filaments were regulated by MinC, which excluded them from the poles and division plane. Comparative genomics indicated that the repurposing of ParMR and Min systems coevolved with cyanobacterial multicellularity, highlighting the evolutionary plasticity of cytoskeletal systems in bacteria.}, author = {Springstein, Benjamin L and Javoor, Manjunath and Megrian, Daniela and Hajdu, Roman and Hanke, Dustin M. and Zens, Bettina and Weiss, Gregor L. and Schur, Florian Km and Loose, Martin}, issn = {1095-9203}, journal = {Science}, number = {6795}, publisher = {AAAS}, title = {{Repurposing of a DNA segregation machinery into a cytoskeletal system controlling cell shape}}, doi = {10.1126/science.aea6343}, volume = {392}, year = {2026}, } @article{21763, abstract = {Reactive oxygen species (ROS) have been implicated in multiple signaling processes in plants, but the underlying mechanisms and roles remain enigmatic. In this study, we developed a method of live imaging of apoplastic ROS at the root surface. Distinct signals, including auxin, extracellular adenosine triphosphate, and rapid alkalinization factor 1 peptide, induce cytosolic calcium transients and apoplastic ROS bursts. Genetic and optogenetic manipulations of Arabidopsis identified calcium transients as necessary and sufficient for ROS bursts through activation of reduced nicotinamide adenine dinucleotide phosphate (NADPH) oxidases RBOHC and RBOHF. Apoplastic ROS bursts are not required, but they do limit gravity-induced root bending. Root bending is sensed by the stretch-activated calcium channel MCA1, leading to NADPH oxidase activation. The resulting ROS production stiffens cell walls to facilitate soil penetration. Apoplastic ROS thus provides a means to balance tissue flexibility and stiffness to navigate soil.}, author = {Kulich, Ivan and Vladimirtsev, Dmitrii and Randuch, Marek and Gao, Shiqiang and Citterico, Matteo and Konrad, Kai R. and Nagel, Georg and Wrzaczek, Michael and Cascaro, Léa and Vinet, Pauline and Durand, Pauline and Asnacios, Atef and Verma, Lokesh and Bennett, Malcolm J. and Pandey, Bipin K. and Friml, Jiří}, issn = {1095-9203}, journal = {Science}, number = {6795}, pages = {296--300}, publisher = {AAAS}, title = {{Calcium-triggered apoplastic ROS bursts balance gravity and mechanical signals for soil navigation}}, doi = {10.1126/science.adu8197}, volume = {392}, year = {2026}, } @article{21764, abstract = {Colloidal fluids can exhibit complex phase behavior and determining phase diagrams via experiments or computer simulations can be laborious. We demonstrate that the dispersion relation ω(k), obtained from dynamical density functional theory for the uniform density system, is a highly versatile tool for predicting where in the phase diagram complex crystals form. The sign of ω(k) determines whether density modes with wave number k grow or decay over time. We demonstrate the predictive power by investigating the complex phase behavior of particles interacting via core-shoulder pair potentials. With complementary Monte Carlo simulations, we show that regions of the phase diagram where ωðkÞ has one or several unstable (growing) wave numbers are also where crystalline phases occur. Going further, by tuning these unstable wave numbers via the interaction-potential and state-point parameters, we design systems with quasicrystals in the phase diagram. We identify a system with a certain shoulder range exhibiting at least ten different phases. Our general approach accelerates considerably the mapping of complex phase diagrams, crucial for the design of new materials.}, author = {Wassermair, Michael and Kahl, Gerhard and Roth, Roland and Archer, Andrew J.}, issn = {1079-7114}, journal = {Physical Review Letters}, number = {14}, publisher = {American Physical Society}, title = {{Navigating complex phase diagrams in soft matter systems}}, doi = {10.1103/nbvt-fgjy}, volume = {136}, year = {2026}, } @article{21776, abstract = {Pyridyl motifs equipped with N-substituents can be powerful ligands for catalysis, yet their broader adoption is limited by the lack of a practical method to prepare these scaffolds. We report a modular, robust, and versatile Buchwald–Hartwig amination protocol that enables the rapid synthesis of bipyridine, phenanthroline, terpyridine, and pybox ligands bearing dialkylamine, diarylamine, and heteroaromatic N-substituents. These conditions streamline ligand library synthesis and will facilitate systematic studies in catalysis and related applications.}, author = {Petrik, Adam and Bena, Aleksander and Baunis, Haralds and Kelch, Riley M. and Yoon, Tehshik P. and Pieber, Bartholomäus}, issn = {1615-4169}, journal = {Advanced Synthesis & Catalysis}, number = {9}, publisher = {Wiley}, title = {{Facile access to N-substituted pyridyl ligands}}, doi = {10.1002/adsc.70417}, volume = {368}, year = {2026}, } @article{21777, abstract = {The advantageous characteristics attributed to the 19F nucleus have made it a popular target for nuclear magnetic resonance (NMR) once again in recent years. Aside from solution NMR, an increasing number of studies have been conducted applying solid-state magic-angle spinning (MAS) NMR to fluorine-labelled samples. Here, the high chemical shift anisotropy and strong dipolar couplings can be utilised to get structural insights into proteins and measure long distances. Despite increasing popularity and promising benefits, the sensitivity of biomolecular 19F MAS NMR often suffers from slow longitudinal T1 relaxation and therefore long recycle delays. In this work, we expand paramagnetic doping, an approach commonly used to reduce proton T1 relaxation times, to 19F-labelled biological samples. We study the effect of Gd(DTPA) and Gd(DTPA-BMA) on 19F T1 and T2, and 13C T1 and T2 relaxation in a [5-19F13C]-tryptophan-labelled protein via 19F-detected MAS NMR experiments. The observed paramagnetic relaxation enhancement substantially reduces measurement times of 19F MAS NMR experiments without compromising resolution. Additionally, we report the chemical shift assignments of all four fluorotryptophan signals in the 12×39 kDa-large protein TET2 using a mutagenesis approach.}, author = {Becker, Lea Marie and Toscano, Giorgia and Kapitonova, Anna and Singh, Rajkumar and Guillerm, Undina and Lichtenecker, Roman J. and Schanda, Paul}, issn = {2699-0016}, journal = {Magnetic Resonance}, number = {1}, pages = {29--37}, publisher = {Copernicus Publications}, title = {{Accelerated 19F biomolecular magic-angle spinning NMR with paramagnetic dopants}}, doi = {10.5194/mr-7-29-2026}, volume = {7}, year = {2026}, } @article{21845, abstract = {UTe2 exhibits the remarkable phenomenon of re-entrant superconductivity, whereby the zero-resistance state reappears above 40 tesla after being suppressed with a field of around 10 tesla. One potential pairing mechanism, invoked in the related re-entrant superconductors UCoGe and URhGe, involves transverse fluctuations of a ferromagnetic order parameter. However, the requisite ferromagnetic order—present in both UCoGe and URhGe—is absent in UTe2, and neutron scattering shows instead that the magnetic susceptibility is peaked at an antiferromagnetic wavevector. Here, we measure the magnetotropic susceptibility of UTe2 across two field-angle planes. This quantity is sensitive to the magnetic susceptibility in a direction transverse to the applied magnetic field—a quantity that is not accessed in conventional magnetization measurements. We observe a very large decrease in the magnetotropic susceptibility over a broad range of field orientations, indicating a large increase in the transverse magnetic susceptibility. Because our technique probes the magnetic susceptibility in the long wavelength (q = 0) limit, this suggests that the strong transverse susceptibility arises from ferromagnetic spin fluctuations. These ferromagnetic fluctuations are likely important for understanding the pairing mechanism in UTe2, as all three superconducting phases of UTe2 surround this region of enhanced susceptibility in the field-angle phase diagram.}, author = {Zambra, Valeska and Nathwani, Amit and Nauman, Muhammad and Lewin, Sylvia K. and Frank, Corey E. and Butch, Nicholas P. and Shekhter, Arkady and Ramshaw, B. J. and Modic, Kimberly A}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Giant transverse magnetic fluctuations at the edge of re-entrant superconductivity in UTe2}}, doi = {10.1038/s41467-026-71899-7}, volume = {17}, year = {2026}, } @phdthesis{21854, abstract = {As neural-network-based models grow both in size and popularity, interest has grown in making the models smaller and more efficient to train. To that end, many methods have been proposed to prune models by reducing their number of nonzero parameters. Additionally, parameter-efficient fine-tuning, in which a much smaller number of parameters than the total contained in the model is updated during training, has become very popular, especially in the space of Large Language Models. At the same time, the increasingly routine deployment of machine learning in real-world applications has spurred a drive to make them more trustworthy - in the sense of, among other things, being unbiased, interpretable, and editable. In this thesis, we examine the interplay between efficiency and trustworthiness. First, we analyze the effects of model pruning on bias in computer vision models, demonstrating that increased sparsity leads to greater bias, largely as a function of increased model uncertainty in marginal cases. Based on this observation, we propose several bias mitigation techniques. Then, we demonstrate that example-specific model pruning can improve model interpretation methods while improving pruning efficiency to make example-specific model pruning feasible in real time. Then, we investigate the effectiveness of parameter-efficient and data-efficient model personalization via fine-tuning, demonstrating that it is highly feasible with very small computational and data resources. Finally, we consider efficiency in editing model knowledge using a custom synthetic data framework, demonstrating that parameter-efficient, low-rank fine-tuning frequently outperforms full-rank fine-tuning, and, additionally, that restricting which model blocks are fine-tuned frequently improves results. Together, the results in this thesis provide new insights and techniques for combining trustworthiness and efficiency during neural network inference and training. -----------------“In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of [name of university or educational entity]’s products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. If applicable, University Microfilms and/or ProQuest Library, or the Archives of Canada may supply single copies of the dissertation.”}, author = {Iofinova, Eugenia B}, issn = {2663-337X}, pages = {237}, publisher = {Institute of Science and Technology Austria}, title = {{On the utility and effects of efficiency in artificial neural networks}}, doi = {10.15479/AT-ISTA-21854}, year = {2026}, } @misc{21857, abstract = {The availability of powerful open-source large language models (LLMs) opens exciting use cases, such as using personal data to fine-tune these models to imitate a user’s unique writing style. Two key requirements for this functionality are personalization–in the sense that the output should recognizably reflect the user’s own writing style—and privacy–users may justifiably be wary of uploading extremely personal data, such as their email archive, to a third-party service. In this paper, we demonstrate the feasibility of training and running such an assistant, which we call Panza, on commodity hardware, for the specific use case of email generation. Panza’s personalization features are based on a combination of parameter-efficient fine-tuning using a variant of the Reverse Instructions technique [1] and Retrieval-Augmented Generation (RAG) [2]. We demonstrate that this combination allows us to fine-tune an LLM to reflect a user’s writing style using limited data, while executing on extremely limited resources, e.g. on a free Google Colab instance. Our key methodological contribution is the first detailed study of evaluation metrics for this task, and of how different choices of system components–the use of RAG and of different fine-tuning approaches–impact the system’s performance. Additionally, we demonstrate that very little data - under 100 email samples - are sufficient to create models that convincingly imitate humans, showcasing a previously unknown attack vector in language models. We are releasing the full Panza code as well as three new email datasets licensed for research use.}, author = {Nicolicioiu, Armand and Iofinova, Eugenia B and Jovanovic, Andrej and Kurtic, Eldar and Nikdan, Mahdi and Panferov, Andrei and Markov, Ilia and Shavit, Nir and Alistarh, Dan-Adrian}, booktitle = {Third Conference on Parsimony and Learning (Proceedings Track)}, keywords = {LLMs, PEFT, LoRA, personalization, efficient ML}, location = {Tübíngen, Germany}, publisher = {OpenReview}, title = {{Panza: Investigating the feasibility of fully-local personalized text generation}}, year = {2026}, } @unpublished{21859, abstract = {As artificial neural networks, and specifically large language models, have improved rapidly in capabilities and quality, they have increasingly been deployed in real-world applications, from customer service to Google search, despite the fact that they frequently make factually incorrect or undesirable statements. This trend has inspired practical and academic interest in model editing, that is, in adjusting the weights of the model to modify its likely outputs for queries relating to a specific fact or set of facts. This may be done either to amend a fact or set of facts, for instance, to fix a frequent error in the training data, or to suppress a fact or set of facts entirely, for instance, in case of dangerous knowledge. Multiple methods have been proposed to do such edits. However, at the same time, it has been shown that such model editing can be brittle and incomplete. Moreover the effectiveness of any model editing method necessarily depends on the data on which the model is trained, and, therefore, a good understanding of the interaction of the training data distribution and the way it is stored in the network is necessary and helpful to reliably perform model editing. However, working with large language models trained on real-world data does not allow us to understand this relationship or fully measure the effects of model editing. We therefore propose Behemoth, a fully synthetic data generation framework. To demonstrate the practical insights from the framework, we explore model editing in the context of simple tabular data, demonstrating surprising findings that, in some cases, echo real-world results, for instance, that in some cases restricting the update rank results in a more effective update.}, author = {Iofinova, Eugenia B and Alistarh, Dan-Adrian}, booktitle = {arXiv}, title = {{Behemoth: Benchmarking unlearning in LLMs using fully synthetic data}}, doi = {10.48550/arXiv.2601.23153}, year = {2026}, } @phdthesis{21863, abstract = {Atoms and photons, two things so different but yet so alike. The former, the building block of matter, something we learn about in school and imagine it as some tiny marbles encircled by other tinier marbles. The latter, an electromagnetic wave, a light particle or an excitation of the electromagnetic field. Quantum mechanics tells us about the properties of these two entities. And even if it sounds, looks and writes counter-intuitive, it has proven right for over a century now. In this work, I elaborate on how we tested the laws of quantum mechanics and how we used them learn more about the tiny building blocks of nature and the fields they use to talk to each other. The atoms we use, are artificial. Superconducting qubits, small electrical circuits with quantized energy levels behave like electrons that transition between different orbitals in an atom. One of the qubits' advantages, is also a big disadvantage. We design the circuits' energy levels and fabricate them in a cleanroom. This allows for arbitrary spaced energy levels but in contrast to real atoms, prevents two superconducting qubits from being alike. Still, this qubit platform is one of the frontrunners for future quantum computing technology and testing fundamental physics due to their scalability. We interface superconducting qubits, which operate in the GHz regime, with microwave photons. We use 3D aluminum cavities as mediators between qubits and photons. The cavities allow for non-destructive readout of the qubit state, they shield the qubits from noise at the qubit frequency and they give us an easy way to frequency-tune these joint systems. We need to operate superconducting qubits and their cavities at millikelvin temperatures in dilution refrigerators. At higher temperatures, superconductivity suffers and even worse, the environment is filled with thermal noise photons. This poses a fundamental limitation on the scalability of superconducting qubit devices. Also connecting multiple devices in different fridges does not work over room temperature links because the microwave photons used for this purpose will be covered in noise and the quantum information they carry, will be unusable. Infrared photons do not suffer from this noise problem since there are close to zero thermal noise photons at their frequencies at room temperature. We cannot simply interface superconducting devices with optical photons due their frequency mismatch and the destructive effect of optical photons on superconductors. Therefore, we use microwave-to-optics transducers that allow to convert microwave photons into optical ones and vice-versa. The transducers that we use are macroscopic electro-optic transducers using the Pockels effect in a disk-shaped Lithium Niobate whispering gallery mode resonator. By using a strong optical pump, photons from the two frequency domains experience a beam-splitter interaction and get converted from one to the other. We measure the generated optical photons using elaborate optical setups, optical heterodyning and single photon detectors to gain knowledge about the qubit state or the converted microwave photons. Bridging the microwave and the optical world allows us to take advantage of both of their strengths but it also requires deep knowledge about both of their working principles. In this work, we describe two experiments that our group conducted to showcase the opportunities that arise from interfacing superconducting qubits with optical photons but also the pitfalls, one may encounter on the way. In the first experiment, we managed to all-optically read out a superconducting qubit. We show that the assignment fidelity, the probability that a measurement of the qubit state matches the prepared state, is close to equal for all-optical, microwave-to-optics and conventional microwave readout. We show T1 and T2 measurements for all three readout types and give an analysis of the noise caused by the optics. Finally, we show that the infrared light does not affect the qubit performance in a negative way but that the heating it causes does. This is an important insight that we used in the next experiment. The second experiment is the upconversion of itinerant single microwave photons to the optical domain. We show that we can generate single microwave photons from a qubit-cavity system. We upconvert these single photons, measure them with a single photon detector and reconstruct their shape. By conducting a single photon Rabi measurement, we show correlations between the microwave and the optical domain. And by thorough signal-to-noise measurements and noise analysis, we find that we can generate single infrared photons with high signal-to-noise ratio 5.1 and low transducer added noise (<0.012 quanta). We show that this measurement creates a path towards entanglement of a superconducting qubit and an optical photon and what parameters need to be improved to achieve it. Additionally, this experiment is a proof of principle for an on-demand infrared single photon source. More generally, it allows to link microwave quantum technology in general to the optical domain.}, author = {Werner, Thomas}, issn = {2663-337X}, keywords = {Superconducting qubits, Quantum optics, Single photons and quantum effects, Nonlinear optics}, pages = {97}, publisher = {Institute of Science and Technology Austria}, title = {{Interfacing superconducting qubits with optical photons}}, doi = {10.15479/AT-ISTA-21863}, year = {2026}, } @unpublished{21870, abstract = {Superconducting qubits are a leading candidate for utility-scale quantum computing due to their fast gate speeds and steadily decreasing error rates. The requirement for millikelvin operating temperatures, however, creates a significant scaling bottleneck. Modular architectures using optical fiber links could bridge separate cryogenic nodes, but superconducting circuits do not have coherent optical transitions and microwave-to-optical conversion has not been shown for any non-classical photon state. In this work, we demonstrate the on-demand generation and tomographic reconstruction of itinerant single microwave photons at 8.9 GHz from a superconducting qubit. We upconvert this non-Gaussian state with a transducer added noise below 0.012 quanta and count the converted telecom photons at 193.4 THz with a signal-to-noise ratio of up to 5.1$\pm$1.1. We characterize the trade-offs between throughput and noise, and establish a viable path toward heralded entanglement distribution and gate teleportation. Looking ahead, these results empower existing superconducting devices to take a key role in distributed quantum technologies and heterogeneous quantum systems.}, author = {Werner, Thomas and Riyazi, Erfan and Hawaldar, Samarth and Sahu, Rishabh and Arnold, Georg M and Paul Falthansl-Scheinecker, Paul Falthansl-Scheinecker and Naranjo, Jennifer A. Sánchez and Loi, Dante and Kapoor, Lucky N. and Zemlicka, Martin and Qiu, Liu and Militaru, Andrei and Fink, Johannes M}, booktitle = {arXiv}, title = {{Electro-optic conversion of itinerant Fock states}}, doi = {10.48550/arXiv.2602.00928}, year = {2026}, } @article{21917, abstract = {A defining feature of quantum many-body systems is the exponential scaling of the Hilbert space with the number of degrees of freedom. This exponential complexity naïvely renders a complete state characterization, for instance via the complete set of bipartite Renyi entropies for all disjoint regions, a challenging task. Recently, a compact way of storing subregions' purities by encoding them as amplitudes of a fictitious quantum wave function, known as entanglement feature, was proposed. Notably, the entanglement feature can be a simple object even for highly entangled quantum states. However the complexity and practical usage of the entanglement feature for general quantum states has not been explored. In this work, we demonstrate that the entanglement feature can be efficiently learned using only a polynomial amount of samples in the number of degrees of freedom through the so-called tensor cross interpolation (TCI) algorithm, assuming it is expressible as a finite bond dimension MPS. We benchmark this learning process on Haar and random MPS states, confirming analytic expectations. Applying the TCI algorithm to quantum eigenstates of various one dimensional quantum systems, we identify cases where eigenstates have entanglement feature learnable with TCI. We conclude with possible applications of the learned entanglement feature, such as quantifying the distance between different entanglement patterns and finding the optimal one-dimensional ordering of physical indices in a given state, highlighting the potential utility of the proposed purity interpolation method.}, author = {Kolisnyk, Dmytro and Medina Ramos, Raimel A and Vasseur, Romain and Serbyn, Maksym}, issn = {2521-327X}, journal = {Quantum}, publisher = {Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften}, title = {{Tensor cross interpolation of purities in quantum many-body systems}}, doi = {10.22331/q-2026-05-22-2114}, volume = {10}, year = {2026}, } @phdthesis{21918, author = {Khudiakova, Kseniia}, issn = {2663-337X}, pages = {89}, publisher = {Institute of Science and Technology Austria}, title = {{How epistasis and purifying selection shape genetic diversity}}, doi = {10.15479/AT-ISTA-21918}, year = {2026}, } @article{21923, abstract = {The appearance of simulated natural phenomena heavily depends on the way surfaces are textured. However, applying texture maps to dynamic deformable surfaces presents a significant challenge, due to ever-shifting differences in length scales involved. When these surfaces move and advect the texture along with them, their final appearance degrades as deformed regions dramatically distort their texture map. Modifications to the texture directly at the pixel level in response to the deformation may introduce ghosting artifacts and look unnatural. In the real world, the appearance of surface details on a deforming material changes through the interplay of physical processes such as rupturing, exposure of internal structure, or wrinkling. Motivated by these behaviors, in this work we explore how physical principles can guide the texturing methods based on the measure of surface deformation. We present two novel wave-based procedural texturing algorithms which reproduce common physical properties like advection and self-similarity, enabling the plausible animation of deforming objects with extreme texture map distortions. Our algorithms are fully procedural, require no actual physics simulation, and store no state or history of deformation besides the input UV map, making them highly parallelizable on the GPU and efficient enough for real-time applications. We show the versatility of the method by animating physical phenomena with extreme deformations such as flowing lava, stretching putty and outpouring sludge.}, author = {Kalinov, Aleksei and Ly, Mickaël and Hafner, Christian and Wojtan, Christopher J}, issn = {0730-0301}, journal = {ACM Transactions on Graphics}, keywords = {Procedural animation}, location = {Los Angeles, CA, United States}, number = {4}, publisher = {ACM}, title = {{Physics-inspired procedural texturing of extremely deformable surfaces}}, doi = {10.1145/3811353}, volume = {45}, year = {2026}, } @article{21929, abstract = {The import of proteins into mitochondria poses fundamental mechanistic challenges: aggregation-prone precursor proteins must be maintained in aqueous compartments and threaded through narrow pores without becoming stuck or mislocalized. Recent evidence from mitochondrial protein import studies and other chaperone systems underscores the critical role of dynamics in balancing sufficiently tight binding, promiscuity, specificity, and release. Dynamic binding of client precursor proteins to import machinery components arises naturally from the avidity of their interactions. Conformational entropy enhances their stability, while the multivalent nature of these interactions ensures that client transfer to downstream insertases occurs without a substantial energy barrier. Here, we discuss this emerging paradigm of dynamic protein handling, using examples where dynamic structures have been resolved and highlight outstanding questions.}, author = {Schneider, Jakob and Guillerm, Undina and Simoes Pereira, Caroline and Schanda, Paul}, issn = {1469-896X}, journal = {Protein Science}, number = {6}, publisher = {Wiley}, title = {{Dynamic disorder is crucial for mitochondrial protein import}}, doi = {10.1002/pro.70630}, volume = {35}, year = {2026}, } @phdthesis{21957, abstract = {This thesis investigates algorithmic certification and approximation methods for degenerate semidefinite programs (SDPs) and the singular roots of polynomial systems. In the first part, we present a hybrid symbolic-numeric algorithm for certifying the feasibility of weakly feasible, degenerate SDPs. By reformulating linear matrix inequalities (LMIs) into a structured polynomial system via facial reduction and incidence varieties, we guarantee the existence of an isolated exact solution. This algebraic reduction enables the certification of maximum-rank numerical approximations using methods from algebraic geometry. In the second part, we address the severe ill-conditioning and loss of quadratic convergence that plague standard path-tracking methods near isolated singular roots. To overcome this, we propose tracking algorithms that achieve superlinear convergence without the computational bloat characteristic of classical deflation techniques. By modeling the solution path as a generalized fractional Puiseux series, our approach combines an explicitly derived algebraic predictor with a localized hyperplane desingularization phase during the corrector step. Furthermore, we introduce a continuous path-limit method and an extension of the geometric sequence rule to directly extract exact fractional exponents. This bypasses traditional heuristic trial-and-error methods and explicitly accommodates sparse series expansions. Numerical experiments confirm that our method significantly reduces the cumulative number of matrix inversions while achieving high-accuracy root approximations, even for heavily degenerate systems exhibiting higher coranks.}, author = {Zapata, Jeferson}, isbn = {978-3-99078-079-4}, issn = {2663-337X}, pages = {89}, publisher = {Institute of Science and Technology Austria}, title = {{Overcoming degeneracy and singularity : Techniques for semidefinite programs and homotopy continuation endgames}}, doi = {10.15479/AT-ISTA-21957}, year = {2026}, } @misc{21960, abstract = {Solitons - localized wave packets that travel without spreading - play a central role in understanding transport and properties of nonlinear systems. In quantum many-body systems, however, such robust excitations are typically destroyed by thermalization. Here, we theoretically demonstrate the existence of solitonic excitations in high-energy states of Rydberg atom chains in the regime of strong nearest-neighbor Rydberg blockade. These localized wave packets propagate directionally atop a special class of reviving initial states related to quantum many-body scars and are capable of carrying energy. Exhibiting long coherence times, these states constitute a form of non-ergodic quantum dynamics and can be efficiently implemented on Rydberg atom simulators. In this work, in addition to a phenomenological description of solitons, we identify their counterpart in a classical nonlinear dynamical system, demonstrate their potential use in quantum information transfer, and conjecture their relevance for anomalous energy transport reported in numerical studies of Rydberg atom arrays.}, author = {Kerschbaumer, Aron}, publisher = {Institute of Science and Technology Austria}, title = {{Research Data: "Quasi-solitons in Rydberg atom chains"}}, doi = {10.15479/AT-ISTA-21960}, year = {2026}, } @unpublished{21963, abstract = {The cerebral cortex consists of immense numbers of neuronal and glial cell-types derived from radial glial progenitor (RGP) cells. How RGPs generate appropriate quantities of distinct cortical cell-types to safeguard a brain of correct size, is not well understood. However, genetic aberration in human, including mutations in PTEN, lead to cortical malformation such as macrocephaly, albeit with unknown etiology. Here we utilized Mosaic Analysis with Double Markers (MADM)-based clonal analysis and single cell phenotyping to decipher the role of Pten in neurogenic and gliogenic RGP lineage progression during cortical ontogeny. While neurogenic RGP lineage progression and projection neuron production was moderately altered in the absence of Pten, cortical astrocyte production was drastically increased. Through genetic epistasis experiments we show that the loss of Pten uncouples astrocyte generation from essential growth factor signaling hubs, funneling into MAPK. Collectively, our results suggest that Pten regulates RGP lineage progression with distinct sequential functions in cortical projection neurogenesis and astrocyte production to ensure the emergence of a correctly-sized cerebral cortex.}, author = {Miranda, Osvaldo and Contreras, Ximena and Pauler, Florian and Davaatseren, Amarbayasgalan and Amberg, Nicole and Streicher, Carmen and Villalba Requena, Ana and Heger, Anna-Magdalena and Marie, Corentine and Hassan, Bassem A. and Rülicke, Thomas and Hippenmeyer, Simon}, booktitle = {bioRxiv}, title = {{Pten orchestrates neurogenic radial glia lineage progression and tunes neocortical astrocyte production}}, doi = {10.64898/2026.05.01.722191}, year = {2026}, } @article{21980, abstract = {Despite significant progress in the field of molecular electronics over the last two decades, the quantitative prediction of metal-molecule-metal junction conductance remains a challenge. The standard computational framework combines density functional theory (DFT) with nonequilibrium Green’s functions (NEGF) using low-rung exchange-correlation functionals such as PBE, which overestimate the conductances. More advanced correction methods exist but require complex workflows and high computational cost, limiting their accessibility. Here, we introduce a physically motivated approach that approximates results obtained with high-rung functionals. Our method fits the PBE-calculated transmission to a Breit-Wigner form and subsequently refines the fit parameters using molecular orbital energies and metal densities of states computed for the isolated subsystems with high-rung functionals. This approach is applicable to a broad range of molecular junctions yielding conductance values in quantitative agreement with experiments. Our approach is simple, low-cost, and accurate, making it well-suited for routine and large-scale prediction of single-molecule junction conductance.}, author = {Gulyaev, Artem and Hazarika, Jyotisman and Liu, Zhen-Fei and Venkataraman, Latha}, issn = {1530-6992}, journal = {Nano Letters}, number = {22}, pages = {7429–7434}, publisher = {American Chemical Society}, title = {{A computationally efficient and accurate method for predicting conductance of single-molecule junctions}}, doi = {10.1021/acs.nanolett.6c01462}, volume = {26}, year = {2026}, } @article{21981, abstract = {For Hamiltonian actions of semidirect products G = FxH, we study 2-cocycles arising from residual Hamiltonian actions of F on Hamiltonian reductions for H. The motivation comes from the study of Teichmüller spaces for surfaces with boundary, which carry Hamiltonian actions of the Virasoro algebra. In this paper, we give a general setup for the problem, and we suggest an easier way to obtain the Gelfand-Fuchs 2-cocycles for Hamiltonian actions on Teichmüller spaces.}, author = {Goncharov, Viacheslav}, issn = {1879-1662}, journal = {Journal of Geometry and Physics}, publisher = {Elsevier}, title = {{An easier way to compute 2-cocycles coming from a reduction for semidirect products}}, doi = {10.1016/j.geomphys.2026.105878}, volume = {227}, year = {2026}, }