@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title = {{Panza: Investigating the feasibility of fully-local personalized text generation}}, year = {2026}, } @unpublished{21859, abstract = {As artificial neural networks, and specifically large language models, have improved rapidly in capabilities and quality, they have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{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{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}, } @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}, } @misc{21145, abstract = {Protein conformational energy landscapes are shaped not only by intramolecular interactions but also by their environment. In protein crystals and protein-protein complexes, intermolecular contacts alter this energy landscape, but the exact nature of this alteration is difficult to decipher. Understanding how the crystal lattice affects protein dynamics is crucial for crystallography-based studies of motion, yet its influence on collective motions remains unclear. Aromatic ring flips in the hydrophobic core represent sensitive probes of such dynamics. Here, we compare the kinetics of aromatic ring flips in the protein GB1 in crystals, in complex with its binding partner IgG, and in solution, combining advanced isotope labeling with quantitative NMR methods. We show that rings in the core flip nearly a thousand times less frequently in crystals than in solution. Enhanced-sampling molecular dynamics simulations, based on a new crystal structure, reproduce these elevated barriers and reveal how the crystal restrains motions. }, author = {Becker, Lea Marie and Schanda, Paul and Chipot, Christophe}, publisher = {Institute of Science and Technology Austria}, title = {{Additional Data for "Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes"}}, doi = {10.15479/AT-ISTA-21145}, year = {2026}, } @article{20840, abstract = {Probing the possibility of entanglement generation through gravity offers a path to tackle the question of whether gravitational fields possess a quantum mechanical nature. A potential realization necessitates systems with low-frequency dynamics at an optimal mass scale, for which the microgram-to-milligram range is a strong contender. Here, after refining a figure-of-merit for the problem, we present a 1-milligram torsional pendulum operating at 18 Hz. We demonstrate laser cooling its motion from room temperature to 240 microkelvins, surpassing by over 20-fold the coldest motions attained for oscillators ranging from micrograms to kilograms. We quantify and contrast the utility of the current approach with other platforms. The achieved performance and large improvement potential highlight milligram-scale torsional pendulums as a powerful platform for precision measurements relevant to future studies at the quantum-gravity interface.}, author = {Agafonova, Sofya and Rosello, Pere and Mekonnen, Manuel and Hosten, Onur}, issn = {2399-3650}, journal = {Communications Physics}, publisher = {Springer Nature}, title = {{One-milligram torsional pendulum toward experiments at the quantum-gravity interface}}, doi = {10.1038/s42005-026-02514-w}, volume = {9}, year = {2026}, } @misc{21284, abstract = {The advantageous characteristics attributed to the 19F nucleus have made it a popular target for NMR once again in recent years. Aside from solution NMR, an increasing number of studies have been conducted applying solid-state magic-angle-spinning NMR to fluorine-labeled samples. Here, the high chemical shift anisotropy and strong dipolar couplings can be utilized 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-labeled biological samples. We study the effect of Gd(DTPA) and Gd(DTPA-BMA) on 19F and 13C T1 and T2 relaxation in a [5-19F13C]-tryptophan-labeled 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 using a mutagenesis approach.}, author = {Becker, Lea Marie and Schanda, Paul}, publisher = {Institute of Science and Technology Austria}, title = {{Research data for "Accelerated 19F biomolecular magic-angle spinning NMR with paramagnetic dopants"}}, doi = {10.15479/AT-ISTA-21284}, year = {2026}, } @phdthesis{21360, author = {Riegler, Stefan}, issn = {2663-337X}, pages = {185}, publisher = {Institute of Science and Technology Austria}, title = {{Root system plasticity under nutrient limitation : Investigating hormonal and molecular drivers in Arabidopsis thaliana and Coffea species}}, doi = {10.15479/AT-ISTA-21360}, year = {2026}, } @misc{21363, abstract = {The data contains information on coffee differential gene expression as well as co-expression and trait correlations in two separate experiments. First, contrasting nitrogen supply, second, intra- and interspecific grafting.}, author = {Riegler, Stefan}, publisher = {Institute of Science and Technology Austria}, title = {{Thesis Data for Root System Plasticity under Nutrient Limitation: Investigating Hormonal and Molecular Drivers in Arabidopsis thaliana and Coffea species}}, doi = {10.15479/AT-ISTA-21363}, year = {2026}, } @phdthesis{21423, author = {Dunajova, Zuzana}, isbn = {978-3-99078-076-3}, issn = {2663-337X}, pages = {110}, publisher = {Institute of Science and Technology Austria}, title = {{Geometry-driven self-organization of migrating cells and chiral filaments}}, doi = {10.15479/AT-ISTA-21423}, year = {2026}, } @misc{21137, author = {Naik, Suyash}, publisher = {Institute of Science and Technology Austria}, title = {{Data associated with Keratins coordinate tissue spreading }}, doi = {10.15479/AT-ISTA-21137}, year = {2026}, } @misc{21439, abstract = {These files contain supplementary movies accompanying the PhD thesis “Geometry-driven self-organization of migrating cells and chiral filaments” by Zuzana Dunajova (2026). The videos provide additional visual material supporting the experiments and results described in the thesis.}, author = {Dunajova, Zuzana}, publisher = {Institute of Science and Technology Austria}, title = {{Supplementary movies to PhD thesis “Geometry-driven self-organization of migrating cells and chiral filaments”}}, doi = {10.15479/AT-ISTA-21439}, 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}, } @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}, } @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}, } @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{21983, abstract = {Promoters and enhancers are cis-regulatory elements (CREs), DNA sequences that bind transcription factor (TF) proteins to up- or down-regulate target genes. Decades-long efforts yielded TF-DNA interaction models that predict how strongly an individual TF binds arbitrary DNA sequences and how individual binding events on the CRE combine to affect gene expression. These insights can be synthesized into a global, biophysically realistic, and quantitative genotype–phenotype map for gene regulation, a ‘holy grail’ for the application of evolutionary theory. A global map provides a rare opportunity to simulate the long-term evolution of regulatory sequences and pose several fundamental questions: How long does it take to evolve CREs de novo? How many non-trivial regulatory functions exist in sequence space? How connected are they? For which regulatory architecture is CRE evolution most rapid and evolvable? In this article, the first of a two-part series, we briefly review the pertinent modeling and simulation efforts for a unique system that enables close, quantitative, and mechanistic links between biophysics, as well as systems, synthetic, and evolutionary biology.}, author = {Mascolo, Elia and Körei, Reka E and Herrera-Álvarez, Santiago and Guet, Calin C and Crocker, Justin and Tkačik, Gašper}, issn = {1879-0380}, journal = {Current Opinion in Genetics & Development}, publisher = {Elsevier}, title = {{Long-term evolution of regulatory DNA sequences. Part 1: Simulations on global, biophysically-realistic genotype–phenotype maps}}, doi = {10.1016/j.gde.2026.102483}, volume = {99}, year = {2026}, }