April 2026 arXiv papers — page 118

Ryotaro Sano, Fumihiro Murabayashi, Daigo Ichikawa, Thibaut Jonckheere

We propose a Hanbury Brown-Twiss interferometer for a $\nu=2/5$ fractional quantum Hall edge system, in which quasiparticles tunnel between two co-propagating edge modes. In contrast to the previously studied anyonic Fabry-P\'{e}rot and Mach-Zehnder interferometers, the proposed setup relies purely on two-particle interference rather than single-particle int

Shay Snyder, Hamed Poursiami, Maryam Parsa

Fourier Holographic Reduced Representations (FHRR) provide a compositional framework for encoding structured information with complex-valued hypervectors. FHRR rely on floating-point arithmetic, which limits their efficiency and applicability on resource-constrained hardware. We introduce qFHRR, a quantized phase formulation of FHRR. In this representation,

Georg Bergner, Masanori Hanada, Emanuele Mendicelli

We present a minimal implementation of SU($N$) pure Yang-Mills theory in $3+1$ dimensions for digital quantum simulation, designed to enable quantum advantage. Building on the orbifold lattice simulation protocol with logarithmic scaling in the local Hilbert-space truncation, we introduce further simplified Hamiltonians. Furthermore, we test simple methods t

Renhao Xue, Ruizhan Yan, Mansun Chan, Xiwen Liu

A limited remanent polarization (Pr) in HfO2-based FeRAM remains a key obstacle to density scaling and reliability, while material and process optimizations offer only incremental improvements. This limitation fundamentally originates from the thickness-constrained switchable polarization and the intrinsic polarization ceiling of HfO2-based ferroelectrics. H

Benjamin Ramhorst, Maximilian Jakob Heer, Luhao Liu, Heejae Kim

Although modern, AI-centric datacenters heavily rely on SmartNICs, existing devices impose a hard trade-off. Commercial SmartNICs provide high bandwidth and easy software integration, but offer limited support for customization and data processing offload. In contrast, research SmartNICs often suffer from low bandwidth, limited functionality, and poor softwa

Huanran Hu, Zihui Ren, Dingyi Yang, Liangyu Chen

Real-world video creation often involves a complex reasoning workflow of selecting relevant shots from noisy materials, planning missing shots for narrative completeness, and organizing them into coherent storylines. However, existing benchmarks focus on isolated sub-tasks and lack support for evaluating this full process. To address this gap, we propose Mul

Lukas Konecny, Muhammed A. Dada, Daniel R. Nascimento, Michal Repisky

We present a relativistic time-dependent density functional theory (TDDFT) approach for the simulation of resonant inelastic X-ray scattering (RIXS) spectra, based on both a full four-component (4c) Dirac-Coulomb Hamiltonian and a modern atomic mean-field exact two-component (amfX2C) Hamiltonian model. The approach builds on the pseudo-wavefunction formalism

Elizabeth Baldwin, Paul Duetting, Michal Feldman, Maya Schlesinger

In the combinatorial action model of contract design, a principal delegates a complex project to an agent, incentivizing a subset of actions from a ground set of $n$ actions, via a linear contract. Computing the optimal contract is a challenging problem that generally hinges on two factors: (i) the number of "critical values" - values of the linear contract

Zhijun Guo, Alvina Lai, Emmanouil Korakas, Aristeidis Vagenas

Continuous glucose monitoring (CGM) is central to diabetes care, but explaining CGM patterns clearly and empathetically remains time-intensive. Evidence for retrieval-grounded large language model (LLM) systems in CGM-informed counseling remains limited. To evaluate whether a retrieval-grounded LLM-based conversational agent (CA) could support patient unders

Ben Cardoen, Jeremy Budd, Enrico Amico, Ghassan Hamarneh

We characterize which local matrix structures saturate Weyl's eigenvalue perturbation bound for graph Laplacians under geometrically constrained vertex displacements. Geometric graphs with heavy-tailed vertex noise arise across sensor networks, biological imaging, and spatial omics, yet tractable predictions for noise-induced spectral error remain limited. W

L. X. Gutiérrez-Guerrero, Roger José Hernández-Pinto

We present an updated overview of the symmetry preserving Contact Interaction model in hadronic physics, developed a little over a decade ago to describe the mass spectrum and internal structure of mesons and diquarks composed of light and heavy quarks. Over the years, the Contact Interaction has evolved into a framework capable of treating both ground and e

Shay Snyder, Andrew Capodieci, David Gorsich, Maryam Parsa

Sequential associative memories (SAMs) are difficult to build and maintain in real-world streaming environments, where observations arrive incrementally over time, have imbalanced sampling, and non-stationary temporal dynamics. Vector Symbolic Architectures (VSAs) provide a biologically-inspired framework for building SAMs. Entities and attributes are encode

Sida Tian, Naoto Tsuji, Dirk Manske

We extend the well-established action of the Higgs mode in $s$-wave superconductors to include quantum fluctuations (QFs). We find that already one-loop quantum corrections to the Higgs propagator shift its eigenfrequency below the superconducting energy gap $2\Delta$. Consequently, the Higgs mode appears as an undamped pole below the quasiparticle continuum

N. Parmiggiani, A. Bulgarelli, G. Panebianco, E. Burns

The Compton Spectrometer and Imager is a NASA satellite mission under development that will survey the entire sky in the 0.2-5 MeV range using a wide-field germanium detector array, surrounded on the sides and bottom by active shields (the Anticoincidence Subsystem, ACS). The ACS aims to suppress and monitor background events, as well as detect transient sou

Hailu Kuang, Xiaoqi Li, Wenkai Li, Zongwei Li

Permission control vulnerabilities in Non-fungible token (NFT) contracts can result in significant financial losses, as attackers may exploit these weaknesses to gain unauthorized access or circumvent critical permission checks. In this paper, we propose NFTDELTA, a framework that leverages static analysis and multi-view learning to detect permission control

Vladimir Bashmakov

In this note we explore monodromy defects for non-invertible symmetries in Maxwell theory, exploiting the conformal mapping to $AdS_{3} \times S^{1}$. With this approach we recover the spectrum of the defect conformal primaries. We also dedicate some time discussing the behaviour of Wilson/'t Hooft lines in the presence of such a monodromy defect, and highli

Joubine Aghili

We introduce a Hybrid High-Order (HHO) method for the Schr\"odinger equation in the presence of a magnetic vector potential. In quantum mechanics, physical observables are invariant under continuous gauge transformations, which must be kept at the discrete level to avoid unphysical artifacts. To address this, we construct a discrete covariant gradient operat

He Yang, Dongyi Lv, Wei Xi, Song Ma

Most existing Byzantine-robust federated learning (FL) methods suffer from slow and unstable convergence. Moreover, when handling a substantial proportion of colluded malicious clients, achieving robustness typically entails compromising model utility. To address these issues, this work introduces FedIDM, which employs distribution matching to construct trus

Minh-Phuc Truong, Khai Nguyen

We propose a novel amortized optimization method for predicting optimal transport (OT) plans across multiple pairs of measures by leveraging Kantorovich potentials derived from sliced OT. We introduce two amortization strategies: regression-based amortization (RA-OT) and objective-based amortization (OA-OT). In RA-OT, we formulate a functional regression mod

Shay Snyder, Andrew Capodieci, David Gorsich, Maryam Parsa

Vector Symbolic Architectures (VSAs) provide a well-defined algebraic framework for compositional representations in hyperdimensional spaces. We introduce HyperSpace, an open-source framework that decomposes VSA systems into modular operators for encoding, binding, bundling, similarity, cleanup, and regression. Using HyperSpace, we analyze and benchmark two

Arthur S. Morris, Daniel Malz

Executing a logical quantum circuit fault-tolerantly incurs a large spacetime overhead. Recent work has proposed and investigated phantom codes, defined by the property that every in-block logical $\mathrm{CNOT}$ circuit can be implemented with a physical permutation, a property that has the potential to greatly reduce the depth of compiled circuits. Here we

Haozhi Fan, Jinhao Duan, Kaidi Xu

Despite the rapid advancement of Large Language Models (LLMs), uncertainty quantification in LLM generation is a persistent challenge. Although recent approaches have achieved strong performance by restricting LLMs to produce short or constrained answer sets, many real-world applications require long-form and free-form text generation. A key difficulty in th

Zhijun Qiu

Regulated enterprises in the United States -- banks, telecommunications providers, large technology companies -- operate across heterogeneous systems that were rarely designed to interoperate. ERP platforms, billing engines, supply chain tools, and financial reporting infrastructure coexist within the same organization, but they do not talk to each other wel

Sven Serneels

Cellwise Robust Twoblock (CRTB) is introduced, the first cellwise robust method for simultaneous dimension reduction of multivariate predictor and response blocks, in both a dense and a sparse variable-selecting variant. Classical robust methods protect against casewise outliers by downweighting or removing entire observations, a strategy that becomes ineffi

Weizhen Tang, Amir Shee, Zhangang Han, Pawel Romanczuk

We study dense mixtures of passive and active self-aligning disks with isotropic or anisotropic mobility. We find that the passive fraction controls an order-disorder transition that is continuous in the isotropic case and discontinuous in the anisotropic one. A mean-field equation derived from the microscopic heading dynamics captures this dichotomy. Near t

Hiroya Morita, Shunichiro Orihara, Fumitaka Shimizu, Masataka Taguri

In propensity score weighted analysis, robust variance that does not account for weight estimation is commonly used. In propensity score weighted Cox models (CoxPSW), the robust variance is known to be conservative when weights for the average treatment effect (ATE) are used, but it remains unclear whether this conservativeness also holds for other weighting

Xue Lu, Haibo Yuan, Bowen Huang, Tao Wang

Omega Centauri is the most massive and chemically complex multi-population globular cluster with a wide metallicity range that has been extensively studied photometrically and spectroscopically. Using the wide metallicity range of omega Cen, HST photometry (F275W, F336W, F435W, F625W), and MUSE spectroscopy ([M/H]), we derive [M/H]- and M_{F625W}-dependent s

Llorenç Balada Gaggioli

We present a framework based on the determinantal geometry of two-qubit gates. Combining the Weyl chamber representation with operator Schmidt theory, we interpret gate synthesis as a distance problem to determinantal varieties. This gives an operational geometry to the Weyl chamber, quantifying nonlocal complexity. We show that the square root iSWAP gate is

Camilo Gomez, Pengyang Wang, Yanjie Fu

Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents based on their relevance or importance to a given query or context. Despite significant success in real-world information retrieval systems, current LTR methods rely on one prefix ranking metric (e.g., such as Nor

Matthew Pugh, Jo Grundy, Corina Cirstea, Nick Harris

This paper develops a methodology for representing machine learning models as models of formal theories, grounded in the perspective that machine learning models are a form of database and that databases are models of theories in coherent logic. Two intermediate results support this approach: any functorial database schema has an associated $\kappa$-coherent

Chenghong Zhu, Xian Wu, Jiahan Chen, Keming He

Toward the large-scale, practical realization of quantum computing, quantum error correction is essential. Among various quantum error-correcting codes, the surface code stands out as a leading candidate, and lattice surgery based on surface codes has emerged as a promising technique for fault-tolerant quantum computation (FTQC). However, implementing quantu

Simon Böhi, Irene Cannistraci, Sergio Muñoz Gonzalez, Moritz Vandenhirtz

Echocardiography is a widely used modality for cardiac assessment due to its non-invasive and cost-effective nature, but the sparse and heterogeneous spatiotemporal views of the heart pose distinct challenges. Existing masked autoencoder (MAE) approaches typically process images or short clips independently, failing to capture the inherent multi-view structu

Mikhail Misko, Natalia Starkova, Pavlos G. Lagoudakis

Kardar-Parisi-Zhang (KPZ) scaling has been observed in discrete polariton lattices, enabled by engineered band structures that stabilize the condensate. Whether this universality extends to intrinsically continuous systems with natural noise regularization remains an open question. We propose and numerically demonstrate KPZ scaling in a continuous quasi-one-

Yu Zhu, Qiming Du, Yuqiong Jin, Woji He

To address the urgent need in the NISQ era for high-performance, scalable quantum compilers and to advance the integration of classical and quantum computing, we present QLLVM, an advanced Quantum-Classical co-compilation framework built on LLVM. To our knowledge, QLLVM delivers an end-to-end, LLVM-based compilation workflow that unifies the build of classic

Kanzhi Cheng, Zehao Li, Zheng Ma, Nuo Chen

Mobile agents powered by vision-language models have demonstrated impressive capabilities in automating mobile tasks, with recent leading models achieving a marked performance leap, e.g., nearly 70% success on AndroidWorld. However, these systems keep their training data closed and remain opaque about their task and trajectory synthesis recipes. We present O

Carlo Alberto De Bernardi, Tommaso Russo, Şeyda Sezgek, Jacopo Somaglia

A famous result of Klee from 1981 is that the Banach space $\ell_1(\kappa)$ admits a disjoint tiling by balls of radius $1$, for all cardinals $\kappa$ with $\kappa^\omega =\kappa$. Klee also observed that the smallest cardinal in which such a tiling might exist is $\kappa= 2^{\aleph_0}$, leaving open the question whether, for $\kappa< 2^{\aleph_0}$, $\ell_1

Krzysztof Ptaszynski, Maciej Chudak, Massimiliano Esposito

Collective spin systems -- spin ensembles coupled to a common reservoir and effectively described by a single macrospin -- play an important role in both atomic and solid-state physics. Their intrinsic nonlinearity gives rise to multiple long-lived metastable states that ultimately relax to a unique most probable state. This dominant state can change with a

Jiaxuan Li, Xin Wen, Zhihang Li

Any-Time Person Re-identification (AT-ReID) necessitates the robust retrieval of target individuals under arbitrary conditions, encompassing both modality shifts (daytime and nighttime) and extensive clothing-change scenarios, ranging from short-term to long-term intervals. However, existing methods are highly relying on pure visual features, which are prone

Aidi Fang, Zhiwei Chen, Lin Du, Sheng Zheng

We report on the discovery of an FUor-like Class I protostar in NGC~7538. The source, named NGC~7538~MIR, exhibited a giant luminosity burst ($\Delta K_s\sim5$) and a prolonged high-luminosity state lasting at least five years. Its mid-infrared (mid-IR) light curves, constructed from WISE/NEOWISE multiepoch data, presented a rapid rise and slight fading afte

Feifei Sang, Wei Lu, Hongruixuan Chen, Sibao Chen

Building extraction from optical Remote Sensing (RS) imagery suffers from performance degradation under real-world hazy and low-light conditions. However, existing optical methods and benchmarks focus primarily on ideal clear-weather conditions. While SAR offers all-weather sensing, its side-looking geometry causes geometric distortions. To address these cha

Hokuto Konno

This article provides a survey of gauge theory for families, with a particular focus on its applications to diffeomorphism groups of $4$-manifolds that were developed during the period 2021--2025.

Jianxuan Yang, Xinyue Guo, Zhi Cheng, Kai Wang

Recent advances in video-to-audio (V2A) generation enable high-quality audio synthesis from visual content, yet achieving robust and fine-grained controllability remains challenging. Existing methods suffer from weak textual controllability under visual-text conflict and imprecise stylistic control due to entangled temporal and timbre information in referenc

Rocio Borrego Varillas, Pierre Agostini, Fernando Ardana-Lamas, Cord L. Arnold

Twenty-five years have passed since the first experimental demonstration of attosecond pulses, marking the advent of our ability to resolve and control electron motion in real time. What began as a technological breakthrough - generating the shortest flashes ever produced - has evolved into a powerful approach for probing and steering electronic dynamics in

Morten Møller, Philipp Rahe, Sadegh Ghaderzadeh, Elena Besley

Processes involving bursts of activity separated by quiescent periods occur across diverse systems and scales. In human dynamics, these phenomena have been described by power-law inter-event time distributions, $P(t)\sim t^{-\alpha}$, with putative universality classes $\alpha=1$ and $\alpha=\frac{3}{2}$ having been proposed. Whether the observed $\alpha = 1

Tianrun Qi, Cheng-Xiang Wang, Chen Huang, Jiayue Shi

In the sixth generation (6G) wireless communication networks, the device density, antenna number, and the complexity of communication scenarios will significantly increase, which brings great challenges for system design and network optimization. By obtaining channel information in advance, channel map has become a promising solution to these challenges in 6

Cunxi Yu, Haoxing Ren

This paper introduces the first \emph{self-evolving} logic synthesis framework, which leverages Large Language Model (LLM) agents to autonomously improve the source code of \textsc{ABC}, the widely adopted logic synthesis system. Our framework operates on the \emph{entire integrated ABC codebase}, and the output repository preserves its single-binary executi

Johanna van Gent Gonzalez, Ewout van der Veer, Yulei Li, Daniel A. Chaney

Since its discovery, ferroelectric hafnia has been extensively studied due to its CMOS-compatibility and ability to remain polarized at sub-10 nm thicknesses. The ferroelectric behaviour is generally attributed to a polar orthorhombic (OIII) phase. However, a second polar phase with rhombohedral symmetry (R-phase) has also been reported in epitaxial films. T

Amit Berman, Yaron Shany, Itzhak Tamo

Products of MDS codes are of major practical importance; for a recent example, they are used in Data Availability Sampling (DAS) in blockchain networks such as Celestia and as part of the Ethereum roadmap. This motivates us to consider subcodes of such codes with the goal of obtaining a larger minimum distance. In this paper, we present explicit construction

Cheng-Chiang Tsai

We present a short proof, based on local character expansions, of the celebrated theorem of Harish-Chandra about local integrability of complex characters of $p$-adic reductive groups. The proof gives an algebraic incarnation of the local integrability that works for some coefficients different from $\mathbb{C}$, verifies local integrability in cases that ap

Simeon Allmendinger, Luca Deck, Lucas Mueller

Rapid advances in Generative AI are giving rise to increasingly sophisticated Multi-Agent AI (MAAI) systems. While AI fairness has been extensively studied in traditional predictive scenarios, its examination in MAAI remains nascent and fragmented. This scoping review critically synthesizes existing research on fairness in MAAI systems. Through a qualitative

Gael Chauvin, Oscar Carrion Gonzalez, Iva Laginja, Daniel Dicken

The European Research and Development for Space based High Contrast Imaging II Workshop, held at MPIA in May 2025, advanced Europe strategic coordination in support of future exoplanet imaging missions such as the Habitable Worlds Observatory and the Large Interferometer for Exoplanets mission. Building on the first 2024 workshop, this meeting defined concre

Hibatallah Meliani, Khadija Slimani, Samira Khoulji

To navigate a space, the brain makes an internal representation of the environment using different cells such as place cells, grid cells, head direction cells, border cells, and speed cells. All these cells, along with sensory inputs, enable an organism to explore the space around it. Inspired by these biological principles, we developed NEATNC, a Neuro-Evol

Naryeong Kim, Shin Yoo

Open-weight Small Language Models(SLMs) can provide faster local inference at lower financial cost, but may not achieve the same performance level as commercial Large Language Models (LLMs) that are orders of magnitudes larger. Consequently, many of the latest applications of LLMs, such as software engineering agents, tend to be evaluated on larger models on

Jianqiao Yu, Jia Li, Tianhua Gao

This paper presents a two-stage trajectory planning framework for a multi-UAV rigid-payload cascaded transportation system, aiming to address planning challenges in densely cluttered environments. In Stage I, an Enhanced Tube-RRT* algorithm is developed by integrating active hybrid sampling and an adaptive expansion strategy, enabling rapid generation of a s

Tanvir Rahman, Shuvagata Saha, Ahmed Y. Alhurubi, Sujan Kumar Saha

Increasing system-on-chip (SoC) heterogeneity, deep hardware/software integration, and the proliferation of third-party intellectual property (IP) have brought security validation to the forefront of semiconductor design. While simulation and formal verification remain indispensable, they often struggle to expose vulnerabilities that emerge only under realis

Sami Halaseh, Victor Magron, Mateusz Skomra

The generalized moment problem (GMP) is an infinite dimensional linear problem over the cone of finite nonnegative Borel measures. When a GMP instance involves finitely many polynomial moment constraints, moment/sum-of-squares hierarchies provide a sequence of bounds converging to the optimal value. We consider GMP instances with measures supported over a co

Hokuto Konno

This article surveys gauge theory for families and its applications to the comparison between the diffeomorphism group and the homeomorphism group of $4$-manifolds, up to 2021.

Fuzhi Xu, Weijuan Liang, Shuangge Ma, Qingzhao Zhang

Incorporation of external information into high-dimensional modeling for gene expression data has been shown, both theoretically and empirically, to substantially enhance performance. Such external information, sometimes referred to as prior information or priors, has become increasingly accessible from multiple sources, yet its reliability may vary consider

Zhaobo Hu, Vincent Gauthier, Mehdi Naima

Graph Neural Networks (GNNs) conventionally rely on standard Laplacian or adjacency matrices for structural message passing. In this work, we substitute the traditional Laplacian with a Doubly Stochastic graph Matrix (DSM), derived from the inverse of the modified Laplacian, to naturally encode continuous multi-hop proximity and strict local centrality. To o

Liam Wigney, Frank Neumann

Pareto optimization via evolutionary multi-objective algorithms has been shown to efficiently solve constrained monotone submodular functions. Traditionally when solving multiple problems, the algorithm is run for each problem separately. We introduce multitasking formulations of these problems that are an effective way to solve multiple related problems wit

Cornelia Gruber, Henri Funk, Magdalena Mittermeier, Helmut Küchenhoff

Internal climate variability arises from the climate system's inherently chaotic dynamics. Quantifying it is essential for climate science, as it enables risk-based decision-making and differentiates between externally forced change and internal fluctuations. In statistical terms, natural variability corresponds to aleatoric uncertainty, i.e., irreducible st

Yangchen Zeng, Zhenyu Yu, Dongming Jiang, Wenbo Zhang

Transformer-based detectors have advanced small-object detection, but they often remain inefficient and vulnerable to background-induced query noise, which motivates deep decoders to refine low-quality queries. We present HELP (Heatmap-guided Embedding Learning Paradigm), a noise-aware positional-semantic fusion framework that studies where to embed position

Thomas S. Robinson, Mats Ahrenshop, Spyros Kosmidis

Forced-choice conjoint designs have become a staple method in the experimentalist's toolkit. However, the forced-choice outcome is neither always consistent with the types of choices individuals make in real political contexts, nor is it statistically efficient. In this paper, we formalize how ranked outcomes can be integrated into the conjoint framework. We

Francesco Diana, Chuan Xu, André Nusser, Giovanni Neglia

Gradient inversion attacks threaten client privacy in federated learning by reconstructing training samples from clients' shared gradients. Gradients aggregate contributions from multiple records and existing attacks may fail to disentangle them, yielding incorrect reconstructions with no intrinsic way to certify success. In vision and language, attackers ma

Santosh Kumar Chaudhary, Sarikul Islam, Nitin Gupta

Weighted extropy has recently emerged as a flexible information measure for quantifying uncertainty, with particular relevance to order statistics. In this paper, we introduce and study a weighted cumulative analogue of extropy, extending the framework of weighted cumulative residual and cumulative past entropies to extreme order statistics. Specifically, we

Chinmay Bakhale, Anil Sao

Motion artifacts present a significant challenge in structural MRI (sMRI), often compromising clinical diagnostics and large-scale automated analysis. While manual quality control (QC) remains the gold standard, it is increasingly unscalable for massive longitudinal studies. To address this, we propose a hybrid CNN-Attention framework designed for robust, si

Yushang Yang, Fanxu Meng, Fiona Fui-Hoon Nah, RAY LC

The ways people remember and recall places reveal an invisible aspect of cultural heritage (CH), reflecting how individuals and communities relate to these places. Heritage is communal, emerging through collaboratively constructed narratives rather than individual records. To probe how people may share collective memories, we designed an immersive two-person

David C. Luo

Let $\text{E}/\text{F}$ be a quadratic extension of non-archimedean local fields with odd residual characteristic. In this paper, we give equivalent conditions for a simple supercuspidal representation $π$ of $\text{GL}(n, \text{E})$ to be distinguished by $\text{GL}(n, \text{F})$ in terms of its defining maximal simple type and twisted gamma factors. Furthe

Shao-Hang Shi, Zhengzhi Wu, Jiangping Hu, Zi-Xiang Li

The condensation of electron quartets, known as charge-4e superconductivity (SC), represents a novel quantum state of matter beyond the standard paradigm of Cooper pairing. However, concrete microscopic models realizing this phase in two dimensions remain a central challenge. Here, we introduce a non-engineered and sign-problem-free model, unambiguously demo

David Valdivia, Elsa Cazelles, Cédric Févotte

Time-frequency representations, such as the short-time Fourier transform (STFT), are fundamental tools for analyzing non-stationary signals. However, their ability to achieve sharp localization in both time and frequency is inherently limited by the Gabor-Heisenberg uncertainty principle. In this paper, we address this limitation by introducing a method to g

Raigo Nagashima, Chihiro Mamiya, Naoto Tsuji

Lifshitz invariant is a symmetry-allowed term in the Ginzburg-Landau free energy of an ordered phase, involving the order parameters and a single spatial derivative, which serves as a source of unusual optical responses. Here we introduce a ``type II" Lifshitz invariant for superconductors, which changes its sign under the particle-hole transformation and ca

Elena Kopylova

We improve previous results on dispersive decay for 1D Klein- Gordon equation. We develop a novel approach, which allows us to establish the decay in more strong norms and weaken the assumption on the potential.

Giacomo Franchini, David Rodríguez-Martínez, Alfonso Martínez-Petersen, C. J. Pérez-del-Pulgar

Autonomous robots operating in natural karstic caves face perception and navigation challenges that are qualitatively distinct from those encountered in mines or tunnels: irregular geometry, reflective wet surfaces, near-zero ambient light, and complex branching passages. Yet publicly available datasets targeting this environment remain scarce and offer limi

Jonathon Sendall

This paper develops a conditional framework for understanding the emergence of measurable physical structure from a pre-metric domain. Contemporary physics provides powerful and precise descriptions of relations among already-defined observables, yet offers comparatively little on the prior question of how observability, separability, and metric structure th

Xuanyu Liu, Pinhui Ke, Zuling Chang

Sequences exhibiting favorable ambiguity function characteristics play a critical role in radar detection systems and modern mobile communication applications. As a newly developed sequence family, Doppler resilient complementary sequence sets (DRCSSs) can effectively suppress ambiguity function sidelobes by coherently combining the ambiguity functions of th

Petr Sramek

We report a hardware validation of the DAGI (Directed Acyclic Graph Information) framework on IBM Quantum hardware using a small, controlled experiment whose ideal output distribution is constrained to a low-dimensional modular manifold (a "ridge"). For two $n$-bit registers $(u,v)$ with $n=4$ (modulus 16), each key instance $k$ induces an ideal relation $v

Matthew S. Povich, Leisa K. Townsley, Patrick S. Broos, Aldair E. Bonilla

We map the three-dimensional structure and large-scale kinematics of the young stellar populations in the G352 giant molecular cloud (GMC) complex. In radio and infrared images, G352 appears as long filament extending ~$3^{\circ}$ (~150 pc) parallel to the Galactic midplane. It connects the NGC 6357 and NGC 6334 giant H II regions and the GM1-24 compact H II

Andrea Malara

Searches at high object masses probe both resonant production of new particles and nonresonant distortions of Standard Model spectra. This contribution follows the material presented in the Moriond Electroweak 2026 talk and summarizes recent CMS results in this regime: the Run~2 combination of heavy vector boson searches, the Run~3 search for $W^\prime \to \

Tasnim Ahmed, Alberto Marchisio, Muhammad Kashif, Nouhaila Innan

Hybrid Quantum Neural Networks (HQNNs) combine classical learning with parameterized quantum circuits, but their practical performance is often limited by (i) the noise of Noisy Intermediate-Scale Quantum (NISQ) devices and (ii) the large, discrete design space of quantum circuit architectures. Moreover, HQNNs are commonly trained using a fixed circuit and a

Dhananjaya Jayasundara, Vishal M. Patel

Implicit neural representations (INRs) mark a fundamental shift in signal modeling, moving from discrete sampled data to continuous functional representations. By parameterizing signals as neural networks, INRs provide a unified framework for representing images, audio, video, 3D geometry, and beyond as continuous functions of their coordinates. This functio

A. Sladkov, T. Waltenspiel, H. Ahmed, A. Alexandrova

Plasmoid-driven magnetic reconnection in elongated current sheets is suspected to be an ubiquitous phenomenon in space and astrophysical plasmas, but the mechanisms driving its onset and dynamics are still debated. Deciphering the physical mechanisms dominating the destabilization and fragmentation of the current sheet, as well as its evolution, would have a

Xiao Dong, Paul Koh, Devesh Raval, Dominic Smith

Antitrust authorities frequently rely on structural divestitures to address competitive concerns raised by mergers. Using census-level establishment data and proprietary transaction records from the U.S. grocery sector, we provide systematic evidence on the long-run effects of such remedies. Divested stores experience an average 31 percent decline in employm

Chase McDonald, Cleotilde Gonzalez

The increasing integration of artificial intelligence (AI) in everyday life brings with it new challenges and questions for regarding how humans interact with autonomous agents. Multi-agent experiments, where humans and AI act together, can offer important opportunities to study social decision making, but there is a lack of accessible tooling available to r

George Umbrarescu, David Amaro

The classical simulation of universal quantum circuits is crucial both fundamentally and practically for quantum computation. We propose SyQMA, a simulator with several convenient features, particularly suited for quantum error correction (QEC). SyQMA simulates universal quantum circuits with incoherent Pauli noise and computes exact expectation values and m

Murat Moran

Classical symbolic protocol verification under Dolev--Yao uses binary attacker knowledge (known/unknown). This abstraction misses cumulative side-channel settings, where repeated noisy observations progressively improve attacker knowledge. We model this process with a graded attacker view \(\mu_K\in[0,1]\), product T-norm leak updates, and finite-grid explic

Hanyun Jiang, Peisen Yao, Kaiyue Li, Tingting Lin

Code optimization remains a core objective in software development, yet modern compilers struggle to navigate the enormous optimization spaces. While recent research has looked into employing large language models (LLMs) to optimize source code directly, these techniques can introduce semantic errors and miss fine-grained compiler-level optimization opportun

Ruoyu Qin, Weiran He, Yaoyu Wang, Zheming Li

Prefill-decode (PD) disaggregation has become the standard architecture for large-scale LLM serving, but in practice its deployment boundary is still determined by KVCache transfer. In conventional dense-attention models, prefill generates huge KVCache traffics that keep prefill and decode tightly coupled within a single high-bandwidth network domain, limiti

Ke Xu, Yuhao Wang, Yu Wang

Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existing benchmarks primarily focus on reactive responses, overlooking the complexities of proactive intervention and monitoring. To bridge this gap, we introduce ProVoice-Bench, the first evaluation framework specif

Francesco Buonemani, Alvaro Gómez-León, Marco Schirò, Olesia Dmytruk

Quantum dot based platforms offer a promising route towards realizing the Kitaev chain Hamiltonian hosting Majorana bound states (MBSs). Poor man's MBSs arise in a two-site Kitaev chain when the parameters of the system are fine-tuned to the sweet spot. Based on our previous work [Phys. Rev. B 111, 155410 (2025)], we consider a microscopic model for the Kita

Andrei Gudkov, Elizaveta Ponomareva, Alexis Pospelov

Increasing demand for computational power has led cloud providers to employ multi-NUMA servers and offer multi-NUMA virtual machines to their customers. However, multi-NUMA VMs introduce additional complexity to scheduling algorithms. Beyond merely selecting a host for a VM, the scheduler has to map virtual NUMA topology onto the physical NUMA topology of th

Bastian Heinlein, Timo Jakumeit, Robert Schober, Maximilian Schäfer

In nature, estimating the location of a molecule source in turbulent airflow is a central, and yet highly challenging problem for mate search and foraging. Recently, it has also received increasing attention in synthetic molecular communication (SMC), e.g., for leakage detection. One important aspect of source localization is to estimate the distance to the

Natalie Gibson, Niklas Keckman, Andrea Marchesin, Matti Raasakka

We present a novel lackadaisical alternating quantum walk (LAQW) algorithm whose circuit depth scales as $\mathcal{O}(n^2+nt)$ for a $n\times n$ lattice over $t$ time steps. We show that this is a significant depth reduction compared to the existing controlled alternating quantum walk (CAQW) model, which has a circuit depth that scales as $\mathcal{O}(n^2t)$

Julian Eisfeld, Nikolai Wyderka

The certification of quantum systems is essential for emerging quantum technologies, particularly in quantum communication, networks, and distributed computing, where maintaining a common reference frame across distant nodes poses significant challenges. Reference frame independent approaches, such as randomized measurement schemes, offer a promising route b

Fabrizio Guillaro, Vincenzo De Rosa, Davide Cozzolino, Luisa Verdoliva

Significant progress has been made in detecting synthetic images, however most existing approaches operate on a single image instance and overlook a key characteristic of real-world dissemination: as viral images circulate on the web, multiple near-duplicate versions appear and lose quality due to repeated operations like recompression, resizing and cropping

Maoxin Gao, Yan Chang

Where is the true boundary of the quantum advantage region of decoded quantum interferometry (DQI)? The best existing answer is provided by Theorem 7.1 in the Supplementary Material of Jordan et al. (2025), yet we show that this answer systematically underestimates the extent of quantum advantage. On the standard partial-win LDPC benchmark instance, there ex

Ningfei Chen, Thomas Hayward-Schneider, Fulvio Zonca, Zhiyong Qiu

The nonlinear saturation of toroidal Alfven eigenmode (TAE) due to thermal plasma nonlinearities is investigated using gyrokinetic particle-in-cell simulations and theoretical analysis. In the single toroidal mode number simulations with zonal fields filtered out, we find that the saturation level of TAE is governed by thermal plasma nonlinearities for gamma

Ziyu Shan, Yuheng Zhou, Gaoyuan Wu, Ziheng Ji

Mobile manipulation is a fundamental capability that enables robots to interact in expansive environments such as homes and factories. Most existing approaches follow a two-stage paradigm, where the robot first navigates to a docking point and then performs fixed-base manipulation using powerful visuomotor policies. However, real-world mobile manipulation of

Haochun Tang, Yuliang Yan, Jiahua Lu, Huaxiao Liu

Cost-aware routing dynamically dispatches user queries to models of varying capability to balance performance and inference cost. However, the routing strategy introduces a new security concern that adversaries may manipulate the router to consistently select expensive high-capability models. Existing routing attacks depend on either white-box access or heur

T. C. M. Stevens, A. van der Sluis, I. K. Voets, P. G. Moerman

DNA-coated particles are promising as building blocks for functional and finite-sized assemblies because they can be programmed with orthogonal interactions owing to the sequence-specific hybridization of DNA strands. To fully exploit this programmability, it is important to develop particles with coatings that incorporate multiple distinct DNA sequences in

Ka Ching Chan

Generative AI is changing how research software is developed, but rapid AI-assisted development can weaken continuity, traceability, and methodological clarity. SHAPR (Solo, Human-centred, AI-assisted PRactice) was proposed as a framework for structuring AI-assisted research software development. This paper presents a documented case of applying SHAPR to the