IST Austria: PubRep (Institute of Science and Technology)
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Near, far: Patch-ordering enhances vision foundation models' scene understanding
No full textWe introduce NeCo: Patch Neighbor Consistency, a novel self-supervised training loss that enforces patch-level nearest neighbor consistency across a student and teacher model. Compared to contrastive approaches that only yield binary learning signals, i.e. "attract" and "repel", this approach benefits from the more fine-grained learning signal of sorting spatially dense features relative to reference patches. Our method leverages differentiable sorting applied on top of pretrained representations, such as DINOv2-registers to bootstrap the learning signal and further improve upon them. This dense post-pretraining leads to superior performance across various models and datasets, despite requiring only 19 hours on a single GPU. This method generates high-quality dense feature encoders and establishes several new state-of-the-art results such as +2.3 % and +4.2% for non-parametric in-context semantic segmentation on ADE20k and Pascal VOC, +1.6% and +4.8% for linear segmentation evaluations on COCO-Things and -Stuff and improvements in the 3D understanding of multi-view consistency on SPair-71k, by more than 1.5%
LNCS
No full textCertification was made mandatory for the first time in the latest hardware model checking competition. In this case study, we investigate the trade-offs of requiring certificates for both passing and failing properties in the competition. Our evaluation shows that participating model checkers were able to produce compact, correct certificates that could be verified with minimal overhead. Furthermore, the certifying winner of the competition outperforms the previous non-certifying state-of-the-art model checker, demonstrating that certification can be adopted without compromising model checking efficiency
Arginine Dynamics Probed by Magic-Angle Spinning NMR with a Specific Isotope-Labeling Scheme
No full textThe specific introduction of 1H-13C or 1H-15N moieties into otherwise deuterated proteins holds great potential for high-resolution solution and magic-angle spinning (MAS) NMR studies of protein structure and dynamics. Arginine residues play key roles for example at active sites of enzymes. Taking advantage of a chemically synthesized Arg with a 13C-1H2 group in an otherwise deuterated backbone, we demonstrate here the usefulness of proton-detected arginine MAS NMR approaches to probe arginine dynamics. In experiments on crystalline ubiquitin and the 134 kDa tetrameric enzyme malate dehydrogenase we detected a wide range of motions, from sites that are rigid on time scales of at least tens of milliseconds to residues undergoing predominantly nanosecond motions. Spin-relaxation and dipolar-coupling measurements enabled quantitative determination of these dynamics. We observed microsecond dynamics of residue Arg54 in crystalline ubiquitin, whose backbone is known to sample different β-turn conformations on this time scale. The labeling scheme and experiments presented here expand the toolkit for high-resolution proton-detected MAS NM
ISTA Thesis
No full textComplex 3D shapes can be created by morphing flat 2D configurations. Such deformations
either preserve the intrinsic material geometry (e.g., folding paper) or modify it through
localized contraction. Once transformed, the 3D shape can be further controlled to achieve a
target functionality. A key challenge is to take the material specifications and the actuation
process as input to automatically design the target 3D shape and its functionality. This thesis
presents two novel computational pipelines for the design and control of shape-morphing
structures used to create functional prototypes.
The first pipeline borrows from the art of origami to fold paper into intricate shapes and
applies this principle to make 3D lighting displays. We introduce, PCBend a computational
design approach that covers a surface with individually addressable RGB LEDs, effectively
forming a low-resolution surface by folding rigid printed circuit boards (PCBs). We optimize
cut patterns on PCBs to act as hinges and co-design LED placement, circuit routing, and
fabrication constraints to produce PCB blueprints. The PCBs are fabricated using automated
standard manufacturing services with LEDs embedded on them. Finally, the fabricated PCBs
are cut along the contour and folded onto a 3D-printed support. The 3D lighting display is
then controlled to display complex surface light patterns.
Creating 3D shapes through folding is only possible if their planar configuration, called ”unfolding” exists without any distortion or overlap. Existing methods often permit distortion
or require multiple patches, which are unsuitable for fabrication pipelines that rely on folding
non-stretchable materials. We reinforce such fabrication pipelines by providing a geometric
relaxation to the problem, where the input shape is modified to admit overlap-free unfolding.
The second fabrication pipeline extends shape morphing to soft robotics by emulating nature’s
blueprint of distributed actuation. Inspired by vertebrates, we build musculoskeletal robots
using modular active actuators, employing Liquid Crystal Elastomers (LCEs) as shrinkable
artificial muscles integrated with 3D-printed bones. The chemical composition of LCEs is
altered to enable untethered actuation through infrared radiation, allowing active control of
individual muscles and their corresponding bones. The combined motion of individual bones
defines the robot’s overall shape and functionality. Our proposed system significantly expands
both the design and control spaces of soft robots, which we harness using our computational
design tools. We build several physical robots that exhibit complex shape morphing and varied
terrain navigation, showcasing the versatility of our pipeline.
This thesis explores applications ranging from intricate light patterns displayed on 3D shapes
formed by folding rigid PCBs to untethered robots that use contractile muscles to exhibit
shape morphing and locomotion. Through these examples, the thesis highlights how computational design and distributed actuation, integrated with novel materials, can transform
passive structures into functional prototypes
ISTA Thesis
No full textGame Theory is the mathematical formalization of social dynamics - systems where agents interact over time and the evolution of the state of the system depends on the decisions of every player.
This thesis takes the perspective of a single player and focuses on what they can guarantee in the worst case over the behavior of other players.
In other words, we consider that the objective of every other player in the game is exactly the opposite to the player.
We focus on sustained interactions over time, where the players repeatedly obtain quantitative rewards over time, and they are interested in maximizing their long-term performance.
Formally, this thesis focuses on zero-sum games with the liminf average objective.
Two fundamental questions that Game Theory aims to answer are the following.
1. How much can a player guarantee to obtain after the interaction?
2. How to act in order to obtain the previously mentioned guarantee?
These questions are formalized by the concepts of "value" and "optimal strategies".
We study their properties on games that exhibit one or more of the following properties.
1. Partial Observation:
the players can not perfectly observe the current state of the system during the game. We consider the model of (finite) Partially Observable Markov Decision Processes and prove that finite-memory strategies are sufficient to approximately guarantee the value.
2. Perturbed Description:
the formal description of the game is perturbed by a small parameter.
We consider the model of (finite) Perturbed Matrix Games, and provide algorithms to check various robustness properties and to compute the parameterized value and optimal strategies.
3. Stochastic Transitions:
the actions of the players determine the behavior of the evolution of the system, described as a probability distribution over the next state.
We consider the model of (finite) Perturbed Stochastic Games and provide formulas for the marginal value.
4. Infinite States:
the system can be in infinitely many states.
We consider the model of Random Dynamic Games on a class of infinite graphs, prove the existence of the value, and quantify the concentration of finite-horizon values
Liquid-solid interface reactions drive enhanced thermoelectric performance in Ag2Se
No full textAg2Se is a promising n-type thermoelectric material, but its performance is limited by excessive carrier concentration, compositional inhomogeneity, and phase instability, challenges rooted in a narrow homogeneity range and uncontrolled Ag+ diffusion in the superionic phase. Here, we address these issues by exploiting liquid–solid interface reactions using CdSe complexes that remove surface excess Ag to yield stoichiometric Ag2Se and generate CdSe nanodomains that inhibit Ag+ diffusion and constrain grain growth. The resulting Ag2Se-CdSe nanocomposites exhibit a reproducible, stable figure of merit (zT) of 1.04 between 300 and 390 K. Beyond demonstrating high performance, we elucidate the interfacial chemical reactions that give rise to the observed microstructure and transport properties, providing a foundation for rationally engineering interfacial chemistry to tailor transport properties across diverse thermoelectric material systems
Mass-assisted local deconfinement in a confined Z2 lattice gauge theory
No full textConfinement is a prominent phenomenon in condensed-matter and high-energy physics that has recently become the focus of quantum-simulation experiments of lattice gauge theories (LGTs). As such, a theoretical understanding of the effect of confinement on LGT dynamics is not only of fundamental importance but also can lend itself to upcoming experiments. Here we show how confinement in a Z2 LGT can be avoided by proximity to a resonance between the fermion mass and the electric field strength. Furthermore, we show that this local deconfinement can become global for certain initial conditions, where information transport occurs over the entire chain. In addition, we show how this can lead to strong quantum many-body scarring starting in different initial states. Our findings provide deeper insights into the nature of confinement in Z2 LGTs and can be tested on current and near-term quantum devices
Cusp universality for correlated random matrices
No full textFor correlated real symmetric or complex Hermitian random matrices, we prove that the local eigenvalue statistics at any cusp singularity are universal. Since the density of states typically exhibits only square root edge or cubic root cusp singularities, our result completes the proof of the Wigner–Dyson–Mehta universality conjecture in all spectral regimes for a very general class of random matrices. Previously only the bulk and the edge universality were established in this generality (Alt et al. in Ann Probab 48(2):963–1001, 2020), while cusp universality was proven only for Wigner-type matrices with independent entries (Cipolloni et al. in Pure Appl Anal 1:615–707, 2019; Erdős et al. in Commun. Math. Phys. 378:1203–1278, 2018). As our main technical input, we prove an optimal local law at the cusp using the Zigzag strategy, a recursive tandem of the characteristic flow method and a Green function comparison argument. Moreover, our proof of the optimal local law holds uniformly in the spectrum, thus we also provide a significantly simplified alternative proof of the local eigenvalue universality in the previously studied bulk (Erdős et al. in Forum Math. Sigma 7:E8, 2019) and edge (Alt et al. in Ann Probab 48(2):963–1001, 2020) regimes
LieDetect: Detection of representation orbits of compact Lie groups from point clouds
No full textWe suggest a new algorithm to estimate representations of compact Lie groups from finite samples of their orbits. Different from other reported techniques, our method allows the retrieval of the precise representation type as a direct sum of irreducible representations. Moreover, the knowledge of the representation type permits the reconstruction of its orbit, which is useful for identifying the Lie group that generates the action, from a finite list of candidates. Our algorithm is general for any compact Lie group, but only instantiations for SO(2), T^d, SU(2), and SO(3) are considered. Theoretical guarantees of robustness in terms of Hausdorff and Wasserstein distances are derived. Our tools are drawn from geometric measure theory, computational geometry, and optimization on matrix manifolds. The algorithm is tested for synthetic data up to dimension 32, as well as real-life applications in image analysis, harmonic analysis, density estimation, equivariant neural networks, chemical conformational spaces, and classical mechanics systems, achieving very accurate results
ISTA Thesis
No full textQuantum mechanics reveals a world that defies classical determinism, where uncertainty, superposition, and fluctuations are fundamental aspects. Engineering devices that harness these quantum features requires not only precision, but also a deep understanding of how they interact with their surrounding environment. Superconducting circuits, which exploit
macroscopic quantum coherence in low-loss superconducting materials, provide a scalable platform for implementing such systems. Among the critical elements in these circuits, superinductors—high-impedance, dissipation-free inductive components—play a central role by suppressing charge fluctuations. They allow quantum states to be delocalized in phase space, protect qubits from environmental noise, and facilitate access to phenomena such as dual Josephson physics and ultra-strong coupling regimes.
This thesis explores two complementary implementations of high-impedance circuits: geometric superinductors, demonstrating that high impedance can be achieved beyond kinetic inductance,
and Josephson junction chains, used to investigate both microwave mode properties and DC transport across the superconductor-to-insulator transition.
Part I addresses geometric superinductors. Contrary to the common belief that high-impedance superconducting circuits require kinetic inductance, we demonstrate that purely geometric designs can achieve characteristic impedance exceeding the resistance quantum. By exploiting mutual coupling between adjacent turns, coil-based inductors achieve enhanced self-inductance, creating a reliable platform for qubits and resonators. Modeling, simulation, fabrication, and
characterization confirm that these elements behave as superinductor. With low loss, high linearity, and minimal stray capacitance, these elements are reproducible, free of uncontrolled tunneling events, and capable of strong magnetic coupling. This establishes geometric superinductors as robust, single-wave-function superconducting devices suitable for hardware protected qubits and hybrid systems.
Part II presents classical numerical simulations of a Quantum Phase Slip circuit to study dual Shapiro steps. The circuit consists of an ideal Quantum Phase Slip element embedded in a resistive-inductive environment with a parasitic capacitance.
Part III extends the investigation of high characteristic-impedance circuit elements to one-dimensional Josephson junction chains, which act as a quantum simulator for many-body physics and the superconductor–insulator transition. Different devices are realized on both sides of the DC phase transition, showing either a supercurrent branch or Coulomb blockade at zero bias. The effect of the crossover on microwave modes, however, remains insufficiently investigated. Studying these modes provides insight into the interplay between disorder and phase-slip events. Small differences in circuit component sizes determine which side of the transition a device falls on, making these results relevant not only for fundamental understanding but also for the design of quantum devices, emphasizing the crucial role of the
electromagnetic environment in stabilizing and controlling fragile quantum states.
Together, these results illustrate how carefully engineered high characteristic-impedance elements provide a link between macroscopic circuits and the inherently uncertain quantum world, enabling experiments that probe, control, and ultimately exploit quantum fluctuations for applications in quantum information, metrology, solid state physics and beyond