April 2026 arXiv papers — page 116

Hilton Marques Souza Santana, João Carlos Virgolino Soares, Sven Goffin, Ylenia Nisticò

Kalman filter-based algorithms are fundamental for mobile robots, as they provide a computationally efficient solution to the challenging problem of state estimation. However, they rely on two main assumptions that are difficult to satisfy in practice: (a) the system dynamics must be linear with Gaussian process noise, and (b) the measurement model must also

Koyena Pal, Serdar Kadioglu

Foundational optimization embeddings have recently emerged as powerful pre-trained representations for mixed-integer programming (MIP) problems. These embeddings were shown to enable cross-domain transfer and reduce reliance on solver-generated labels. In this work, we investigate whether such representations generalize beyond optimization to decision proble

Sajad Salami

Zeckendorf's theorem establishes a unique representation for positive integers as sums of non-consecutive Fibonacci numbers. This result has been generalized to Positive Linear Recurrence Sequences (PLRS), where key statistical properties, such as the Gaussian distribution of summands, depend on strictly positive recurrence coefficients. This paper investiga

Katie Anders, Madeline L. Dawsey, Joseph Vandehey

We study $B(n;k)$, the number of ways of writing $n$ as a sum or difference of the first $k$ Fibonacci numbers. We show that $B(0;k)$ satisfies the Tribonacci-like recurrence $B(0;k+1)=B(0;k)+B(0;k-1)+B(0;k-2)$ and that $B(n;k)$ satisfies a modified version of this recurrence.

Carlos Argüelles, Gabriela Barenboim, Gonzalo Herrera, Tanvi Krishnan

When a quantum system couples to a scale-invariant environment, what form must its decoherence take? We prove that the answer is unique: under locality, Lorentz invariance, unitarity, and continuous scale invariance, the effect of any such environment is mathematically equivalent to that of an \emph{unparticle bath} -- a scale-invariant continuum of states -

Yonggeun Jung

This paper combines synthetic aperture radar imagery, nighttime lights, and port characteristics to measure port-level maritime trade using only publicly available data. We evaluate the framework at ports the model has never observed, training on United States ports and testing on European ports and then reversing the exercise, and find that the mapping tran

Anindya Ganguly, Anupreeta More

Identification and characterisation of Kilonovae (KNe) can be instrumental in improving our understanding of cosmology and astrophysics. However, their detection poses unique challenges due to rarity and faintness. Upcoming telescopes, with their deep imaging capabilities and wide field-of-views, will provide a unique opportunity to observe these rare and fa

A. Iosevich, C. Park

We establish uncertainty principles on compact Riemannian manifolds without boundary in the setting of Laplace-Beltrami operators, including the case of real-valued singular potentials. We replace the classical homogeneity assumption by a quantitative spectral condition and obtain corresponding stability versions of uncertainty inequalities. In particular, w

Tomohiro Hashizume, Zhengjun Wang, Frank Schlawin, Dieter Jaksch

A key challenge in classical machine learning is to mitigate overparameterization by selecting sparse solutions. We translate this concept to the quantum domain, introducing quantum sparsity as a principle based on minimizing quantum information shared across multiple parties. This allows us to address fundamental issues in quantum data processing and conver

Panos Tsimpos, Daniel Sharp, Youssef Marzouk

We study dynamic measure transport for generative modeling, focusing on transport maps that connect a source measure $P_0$ to a target measure $P_1$ by integrating a velocity field of the form $v_t(x) = \mathbb{E}[\dot X_t \mid X_t = x]$, where $X_\bullet = (X_t)_t$ is a stochastic process satisfying $(X_0,X_1)\sim{P_0}\otimes{P_1}$ and $\dot X_t$ is its tim

Mallory D. Thorp, Antonio Usero, Frank Bigiel, Ina Galić

Active Galactic Nuclei (AGN) are intertwined with galaxy evolution, injecting energy into the interstellar medium (ISM) that could regulate star formation as a galaxy evolves. However, the phenomena through which we observe AGN are multiphase and multiscale, which can lead to conflicting results for how significantly AGN influence the ISM. We endeavor to cha

Federico Crudu, Giovanni Mellace, Zsolt Sándor

This paper introduces a class of jackknife-based test statistics for linear regression models with endogeneity and heteroskedasticity in the presence of many potentially weak instrumental variables. The tests may be used when considering hypotheses on the full parameter vector or hypotheses defined as linear restrictions. We show that in the limit and under

Konstantin Tiurev, Christoph Fleckenstein, Christophe Goeller, Paul Schnabl

We introduce the parity-unfolded architecture, a fault-tolerant quantum computing scheme that relies on direct preparation and teleportation of small-angle rotations $ Z^{1/2^{k}}$ rather than approximating them with the conventional (Clifford + $T$) gate set. The architecture is enabled by efficient distillation of gates from an arbitrary level of the Cliff

John Burke, Ciaran McGoldrick

Quantum search is among the most important algorithms in quantum computing. At its core is quantum amplitude amplification, a technique that achieves a quadratic speedup over classical search by combining two global reflections: the oracle, which marks the target, and the diffusion operator, which reflects about the initial state. We show that this speedup c

Himanish Ganjoo, Yann Rasera, Emilio Bellini, Michel-Andrès Breton

Modified gravity theories constitute viable alternatives to the standard cosmological model for explaining the observed late-time accelerated expansion of the Universe. The Effective Field Theory of Dark Energy (EFTofDE) is an efficient framework to describe a wide range of such theories with a limited number of parameters. To robustly constrain them by comp

Prerak Gupta, Auditya Sharma, Bharadwaj Vedula, J. Yeo

We investigate the balanced $M=4$, $p=4$ spin-glass model for a one-dimensional long-range proxy for the finite dimensional short-range $p$-spin glass model to examine the nature of the glass transition beyond mean-field theory. We perform large-scale Monte Carlo equilibrated simulations for both fully connected and power-law diluted versions of the model. T

Xuntao Wu, Haoxiong Yan, Gustav Andersson, Alexander Anferov

Quantum algorithms on near-term quantum processors are typically executed using shallow quantum circuits composed of one- and two-qubit gates. However, as circuit depth and gate number increase, gate imperfections and qubit decoherence begin to dominate, limiting algorithmic complexity. An alternative approach is to explore gates involving more than two qubi

Nishkal Rao, Gregorio Carullo

We present numerically-informed closed-form expressions for the dominant $(\ell,m)=(2,2)$ waveform harmonic of the post-merger emission from mergers of non-spinning binary black holes with comparable masses on highly eccentric orbits. Using 233 non-spinning eccentric simulations from the RIT catalog, we construct time-dependent complex quasinormal mode ampli

Saurabh, Maciek Wielgus, Parth Bambhaniya, Elisabete M. de Gouveia Dal Pino

We present the first three-dimensional general relativistic magnetohydrodynamic simulation of sustained accretion onto a horizonless singularity in which matter reaches the central object rather than being accumulated outside of it or expelled in outflows. We consider a Joshi-Malafarina-Narayan (JMN-1) spacetime, a well-motivated black hole mimicker that ari

Jarryd Bath, W. A. Horowitz

We introduce a novel regularization scheme: Systematic Analytic Regularization (SAR). SAR regularizes a theory at the level of the action by analytically continuing the power of the kinetic operator, ensuring that the theory is formally finite before any terms in the Dyson series are evaluated. We demonstrate that SAR fully and self-consistently regularizes

Pablo Bermejo, Benjamin Villalonga, Brayden Ware, Guifre Vidal

In the recent quantum echoes experiment, Google Quantum AI showed that out-of-time-order correlators (OTOCs) for random-circuit time evolution can be measured using a quantum processor more than 10,000x faster than they can be computed to similar accuracy via classical computation. This claim was substantiated by comparison with a variety of state-of-the-art

Cedric Verstege

Recent measurements of Standard Model W and Z boson production performed by the ATLAS and CMS Collaborations at the CERN Large Hadron Collider are reviewed. These include a search for charged lepton flavour violating decays of Z and Z' bosons, a measurement of W-boson angular coefficients and transverse momentum distributions, a triple-differential measureme

M. A. Arroyo-Ureña, J. Hernández-Sánchez, C. G. Honorato, S. Moretti

A $ Z_3 $ symmetric 3-Higgs Doublet Model (3HDM) with two inert doublets and one active doublet (which plays the role of the Higgs doublet), the so-called I(2+1)HDM, is studied. We discuss the behaviour of this 3HDM realisation when one allows for a $ Z_3 $ soft-breaking term. In this setup, the lightest $Z_3$ charged neutral scalar can be a Dark Matter (DM)

Federico Ambrosino, Alessandro Duci, Pietro Antonio Grassi, Silvia Penati

We propose a manifestly supersymmetric formulation of the Symmetry Topological Field Theory (SuSymTFT) for theories with supersymmetry. The SymTFT is a framework that helps organizing symmetries and anomalies of a QFT. Albeit a lot of activity in the field has been devoted to the construction of the SymTFT for the bosonic symmetry structure, the fermionic ca

Francesco Calisto, Clifford Cheung, Grant N. Remmen, Francesco Sciotti

We show that the tree-level spectrum of heavy particles can be directly extracted from the Wilson coefficients of the corresponding effective field theory at low energies. This procedure is exact when the number of resonances is finite, and otherwise approximate. Our results are derived from a new class of analytic dispersion relations that depend nonlinearl

Jahmall Bersini, Domenico Orlando, Susanne Reffert, Jesse Woods

We study cusped Wilson line operators in the Abelian Higgs model in $ d = 4 - \epsilon $ at large external charges. Using a double-scaling limit $ Q \to \infty $, $ \epsilon \to 0 $ with $ Q\epsilon $ fixed, we develop a semiclassical framework that provides analytic control beyond fixed-order perturbation theory. We compute the cusp anomalous dimension for

Christopher Monaghan, Björn Benneke, Nicholas J. Connors, Louis-Philippe Coulombe

Secondary eclipse observations are a powerful way to investigate whether or not a rocky exoplanet hosts an atmosphere, as an atmospheric presence would transport heat to the nightside and render the dayside colder than anticipated. The interpretation of the secondary eclipse observations relies, however, on models based on imperfect knowledge of the host sta

Ludo Fraser-Taliente

Many CFTs can be extended to lines of nonlocal CFTs parametrised by the scaling dimension $\Delta$ of the fundamental field appearing in the action. $\Delta=\frac{d}{2}-\zeta$ is set by the exponent of the kinetic term $(-\partial^2)^{\zeta}$, which is nonlocal for noninteger $\zeta$. If $\Delta$ is tuned to $\Delta_\mathrm{local}$, the scaling dimension of

Ripalta Amoruso, Ginevra Braga, Alice Garoffolo, Francescopaolo Lopez

We develop a framework to describe gravitational wave propagation through a stochastic distribution of weak gravitational lenses beyond the geometric optics limit. We model the lens distribution as a static random background field and formulate the problem in the language of quenched disorder, treating the disorder averaged density matrix as the fundamental

Ninghui Xu, Fabio Tosi, Lihui Wang, Jiawei Han

Conventional frame-based cameras capture rich contextual information but suffer from limited temporal resolution and motion blur in dynamic scenes. Event cameras offer an alternative visual representation with higher dynamic range free from such limitations. The complementary characteristics of the two modalities make event-frame asymmetric stereo promising

Zhanhao Liang, Tao Yang, Jie Wu, Chengjian Feng

This paper focuses on the alignment of flow matching models with human preferences. A promising way is fine-tuning by directly backpropagating reward gradients through the differentiable generation process of flow matching. However, backpropagating through long trajectories results in prohibitive memory costs and gradient explosion. Therefore, direct-gradien

Sumit Chaturvedi, Yannick Hold-Geoffroy, Mengwei Ren, Jingyuan Liu

This paper presents a method for image relighting that enables precise and continuous control over multiple illumination attributes in a photograph. We formulate relighting as a conditional image generation task and introduce attribute tokens to encode distinct lighting factors such as intensity, color, ambient illumination, diffuse level, and 3D light posit

Yan Li, Zezi Zeng, Yifan Yang, Yuqing Yang

The rapid progress of Artificial Intelligence Generated Content (AIGC) tools enables images, videos, and visualizations to be created on demand for webpage design, offering a flexible and increasingly adopted paradigm for modern UI/UX. However, directly integrating such tools into automated webpage generation often leads to style inconsistency and poor globa

Hao Gao, Shaoyu Chen, Yifan Zhu, Yuehao Song

High-level autonomous driving requires motion planners capable of modeling multimodal future uncertainties while remaining robust in closed-loop interactions. Although diffusion-based planners are effective at modeling complex trajectory distributions, they often suffer from stochastic instabilities and the lack of corrective negative feedback when trained p

Kenta Kasai

This paper investigates certified upper bounds on the minimum distance of an explicit family of Calderbank-Shor-Steane quantum LDPC codes constructed from affine permutation matrices. All codes considered here have active Tanner graphs of girth eight. Rather than attempting to prove a general lower bound for the full code distance, we focus on constructing l

Yao Tong, Jiayuan Ye, Anastasia Borovykh, Reza Shokri

Whether language models can systematically generalize remains actively debated. Yet empirical performance is jointly shaped by multiple factors such as training data, training paradigms, and inference-time strategies, making failures difficult to interpret. We introduce a controlled synthetic environment based on shortest-path planning, a canonical composabl

Boon Suan Ho

Erd\H{o}s asked whether every $n$-point set in Euclidean space whose $\binom{n}{2}$ pairwise distances are mutually at least $1$ apart must have diameter at least $(1+o(1))n^2$. We disprove this statement by constructing for every prime power $q$ a set $\mathcal X_q\subset \mathbb R^{q^2+q}$ of $n=q+1$ points such that all pairwise distances in $\mathcal X_q

Sean Eberhard, Elena Maini, Luca Sabatini, Gareth Tracey

We prove a strong general-purpose bound for the diameter of a finite group depending only on the diameters of its composition factors and the maximal exponent of a normal abelian section. There are a number of notable applications: (1) if $G$ is a finite soluble group of exponent $e$, $\mathrm{diam}(G) \ll e (\log |G|)^8$, (2) anabelian groups with bounded-r

Nathan L. Foulk, Katharina Laubscher, Silas Hoffman, Sankar Das Sarma

Singlet-only always-on gapless exchange (SAGE) spin qubits are an alternative type of exchange-only (EO) qubits that encode a single qubit in the spins of four electrons located in four tunnel-coupled quantum dots. While conventional EO qubits are susceptible to local magnetic field gradients caused by local nuclear environments and $g$-factor variations, th

Manan Gupta, Dhruv Kumar

LLM-as-judge frameworks are increasingly used for automatic NLG evaluation, yet their per-instance reliability remains poorly understood. We present a two-pronged diagnostic toolkit applied to SummEval: $\textbf{(1)}$ a transitivity analysis that reveals widespread per-input inconsistency masked by low aggregate violation rates ($\bar{\rho} = 0.8$-$4.1\%$),

Yiyang Jiang, Li Zhang, Xiao-Yong Wei, Li Qing

Many SLT systems quietly assume that brief chunks of signing map directly to spoken-language words. That assumption breaks down because signers often create meaning on the fly using context, space, and movement. We revisit SLT and argue that it is mainly a cross-modal reasoning task, not just a straightforward video-to-text conversion. We thus introduce a re

Leyi Wu, Pengjun Fang, Kai Sun, Yazhou Xing

Video generation has advanced rapidly, with recent methods producing increasingly convincing animated results. However, existing benchmarks-largely designed for realistic videos-struggle to evaluate animation-style generation with its stylized appearance, exaggerated motion, and character-centric consistency. Moreover, they also rely on fixed prompt sets and

Yury Gorishniy, Ivan Rubachev, Dmitrii Feoktistov, Artem Babenko

MLP is a heavily used backbone in modern deep learning (DL) architectures for supervised learning on tabular data, and AdamW is the go-to optimizer used to train tabular DL models. Unlike architecture design, however, the choice of optimizer for tabular DL has not been examined systematically, despite new optimizers showing promise in other domains. To fill

Guillaume Terradot, Vincent Danos

All cells must sustain ionic motive forces (IMFs) -- the electrochemical gradients of permeant ions, together with the membrane potential they produce -- to regulate intracellular pH, drive secondary transport, and power ATP synthesis. Because membranes are imperfectly impermeable, IMFs continuously dissipate through passive leakage, and active transport mus

Franziska Babel, Shane Saunderson, Shalaleh Rismani

This paper presents a preliminary draft of a framework around the use of anthropomorphic deception, defined here as misleading users towards humanlike affordances in the design of autonomous systems. The goal is to promote reflection among HCI and HRI researchers, as well as industry practitioners, to think about levels of anthropomorphic design that are: a)

Spenser Talkington, Benjamin Kass, Martin Claassen

The ultrastrong coupling regime of cavity photons and quantum materials has emerged as a pathway to modify materials properties, however definitive signatures of ultrastrong coupling remain elusive. Focusing on the quantum photon statistics of light transmitted through a cavity-embedded superconductor, we show that a two-photon Higgs polariton at strong coup

Henry D. Pfister, Navin Kashyap, Jean-Francois Chamberland, Galen Reeves

We study reliable communication over finite-state channels (FSCs) using Reed--Muller (RM) codes. Building on recent symmetry-based analyses for memoryless channels, we show that a sequence of binary RM codes (with some random scrambling) can achieve the symmetric capacity (or uniform-input information rate) of a binary-input indecomposable FSC. Our approach

Dingzhi Yu, Rui Pan, Yuxing Liu, Difan Zou

Sign-based optimization algorithms, such as SignSGD, have garnered attention for their performance in distributed learning and training large foundation models. Despite their empirical superiority, SignSGD is known to diverge on non-smooth objectives, which are ubiquitous due to ReLUs, max-pools, and mixture-of-experts. To overcome this limitation, we propos

Zhen Yang, Ping Jian, Zhongbin Guo, Zuming Zhang

Over the past year, spatial intelligence has drawn increasing attention. Many prior works study it from the perspective of visual-spatial intelligence, where models have access to visuospatial information from visual inputs. However, in the absence of visual information, whether linguistic intelligence alone is sufficient to endow models with spatial intelli

Kangrae Park

For each $d \in {1,2,3,7,11}$, let $T_d$ be the nearest-integer complex continued fraction map associated with the Euclidean ring $\mathcal{O}*d$, and let $(a_n)$ be its digit sequence. We prove two metric results for this five-system family. First, for every sequence $(u_n)*{n\ge 1}$ with $u_n \ge 1$, the set of points for which $|a_n| \ge u_n$ for infinite

L. Nortmann, D. Cont, F. Lesjak, A. D. Rains

Sub-Neptune exoplanets frequently exhibit muted transmission spectra, with GJ 1214 b being the most prominent example. Following years of intense observing campaigns yielding featureless planetary spectra, recent observations with JWST revealed the first possible atmospheric signatures. We present high-resolution transmission spectroscopy of GJ 1214 b based

Fabrizio Genilotti, Arianna Stropeni, Gionata Grotto, Francesco Borsatti

The reliability of a machine vision system for autonomous driving depends heavily on its training data distribution. When a vehicle encounters significantly different conditions, such as atypical obstacles, its perceptual capabilities can degrade substantially. Unlike many domains where errors carry limited consequences, failures in autonomous driving transl

Yunfu Deng, Yuhao Li, Josiah P. Hanna

In recent years, reinforcement learning (RL) has shown remarkable success in robotics when a fast and accurate simulator is available for a given task. When using RL and simulation, more simulator realism is generally beneficial but becomes harder to obtain as robots are deployed in increasingly complex and widescale domains. In such settings, simulators wil

Carol Wu, Elina Robeva

Pearl's front-door criterion provides a set of sufficient conditions for estimating the total causal effect from observational data in the presence of latent confounding, using the functional P(y | do(x := x*)) = \sum_z P(z | x*) \sum_x P(y | x, z) P(x). An open question is whether these conditions can be generalized to be both necessary and sufficient for t

Sourav Pal, Supratik Pal

Neutrino self-interactions delay the onset of free-streaming in the early universe, leaving distinct, scale-dependent signatures on the matter power spectrum. We investigate these signatures in post-reionization 21-cm intensity mapping and the Lyman-$α$ (Ly$α$) forest at redshifts $z \sim 2$--$3.5$, and forecast the constraints achievable with upcoming surve

Peter Danchev, Esther García, Miguel Gómez Lozano

We investigate the problem asking when any square matrix whose entries lie in a finite field of characteristic 2 is decomposable into the sum of a diagonalizable matrix and a nilpotent matrix with index of nilpotency at most 2 and, as a result, we completely resolve this question in the affirmative for any finite field of characteristic 2 having strictly mor

Víctor Soto-Larrosa, Nuria Torrado, Edmundo J. Huertas

We study post-training interpretability for Support Vector Machines (SVMs) built from truncated orthogonal polynomial kernels. Since the associated reproducing kernel Hilbert space is finite-dimensional and admits an explicit tensor-product orthonormal basis, the fitted decision function can be expanded exactly in intrinsic RKHS coordinates. This leads to Or

Roni Itkin, Noam Issachar, Yehonatan Keypur, Xingyu Chen

The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representation compactness, reconstruction speed, and rendering fidelity. Previous solutions, whether based on iterative optimization or feed-forward inference, suffer from significant trade-offs between these goals, m

Thomas Jun Jewell, Samuel W. S. Johnson, Ruth E. Baker, Philip K. Maini

Cell-cell adhesion is widely hypothesised to maintain cohesion within the long streams of follower cells that trail leader subpopulations during collective migration, including in neural crest cell migration, angiogenesis, and cancer cell invasion. Mathematically, non-local advection-diffusion equations provide the canonical continuum framework within which

Saransh Chopra, Shubhransh Singhvi, K. V. Rashmi

Recent studies have shown that distributed storage systems can achieve significant space savings by adapting redundancy levels to varying disk failure rates. This adaptation is performed via code conversion, wherein data encoded under an initial code are transformed to data encoded under a final code. While this process is typically resource-intensive, conve

Zhengdong Hong, Shenrui Wu, Haozhe Cui, Boyi Zhao

3D policy learning promises superior generalization and cross-embodiment transfer, but progress has been hindered by training instabilities and severe overfitting, precluding the adoption of powerful 3D perception models. In this work, we systematically diagnose these failures, identifying the omission of 3D data augmentation and the adverse effects of Batch

Ricard S. García-Raigada, Josep Jorba, Sergio Iserte

Hybrid High-performance Computing (HPC)-quantum workloads based on circuit cutting decompose large quantum circuits into independent fragments, but existing frameworks tightly couple cutting logic to execution orchestration, preventing HPC centers from applying mature resource management policies to Noisy Intermediate-Scale Quantum (NISQ) workloads. We prese

Ignasi Sole

Empirical performance analysis depends on the accurate extraction of tempo data from recordings, yet standard computational tools, designed for monophonic audio or modern studio conditions, fail systematically when applied to historical polyphonic chamber music. This paper documents the failure of automated beat-detection software on duo recordings of Beetho

Henrique S. Lima, Rodrigo M. Pereira, Luca Moriconi, Katepalli R. Sreenivasan

Recent investigations of turbulent circulation fluctuations have uncovered substantial insights into the statistical organization of flow structures and revealed unexpected geometric features of turbulent intermittency. Of particular interest here is the observation that circulation probability distribution functions admit a superstatistical representation,

Ranjit Singh, Alexander E. Teretenkov

We theoretically investigate the generation of non-Gaussian quantum states, specifically Schr\"odinger cat-like states (SCLSs), via degenerate dual-pump spontaneous four-wave mixing in a $\chi^{(3)}$-based microring resonator. By introducing a unitary transformation that exactly decouples the self-phase modulation (SPM) and cross-phase modulation (XPM) terms

Antonio Lauerbach, Konstanty Junosza-Szaniawski, Marie Diana Sieper, Alexander Wolff

A mixed graph contains (undirected) edges as well as (directed) arcs, thus generalizing undirected and directed graphs. A proper coloring $c$ of a mixed graph $G$ assigns a positive integer to each vertex such that $c(u)\neq c(v)$ for every edge $\{u,v\}$ and $c(u)<c(v)$ for every arc $(u,v)$ of $G$. As in classical coloring, the objective is to minimize the

Nouhaila Innan, Antonello Rosato, Alberto Marchisio, Muhammad Shafique

Node embeddings act as the information interface for graph neural networks, yet their empirical impact is often reported under mismatched backbones, splits, and training budgets. This paper provides a controlled benchmark of embedding choices for graph classification, comparing classical baselines with quantum-oriented node representations under a unified pi

Meisam Mohammady

We introduce a deficiency-based representation and approximation framework for values of the Riemann zeta function. The method is based on comparing two nonlinear accumulation mechanisms: global transformation of a base partial sum and local transformation of each term. Their gap defines a cumulative deficiency functional that yields the exact identity \[ \z

Mengdi Wu, Xiaoyu Jiang, Oded Padon, Zhihao Jia

This paper presents Prism, the first symbolic superoptimizer for tensor programs. The key idea is sGraph, a symbolic, hierarchical representation that compactly encodes large classes of tensor programs by symbolically representing some execution parameters. Prism organizes optimization as a two-level search: it constructs symbolic graphs that represent famil

Zoe Fingleton, Nazanin Siavash, Armin Moin

In this paper, we focus on automating two of the widely used Verification and Validation (V&V) activities in the Software Development Lifecycle (SDLC): Software testing and software inspection (also known as review). Concerning the former, we concentrate on automated test case generation using Large Language Models (LLMs). For the latter, we enable inspectio

Nikhil Bansal, Matthias C. Caro, Gaurav Mahajan

The impossibility of simultaneously cloning non-orthogonal states lies at the foundations of quantum theory. Even when allowing for approximation errors, cloning an arbitrary unknown pure state requires as many initial copies as needed to fully learn the state. Rather than arbitrary unknown states, modern quantum learning theory often considers structured cl

Arnau Lira-Solanilla, Sreemayee Aditya, Xhek Turkeshi, Silvia Pappalardi

We introduce a systematic framework to construct nonlocal observables with extensive quantum Fisher information (QFI) density in stabilizer codes. The construction maps stabilizer generators to dual Ising spins whose correlators equal string order parameters, converting hidden nonlocal order into a metrologically accessible observable. Applying this to monit

Eden Frenkel, Kenneth L. McMillan, Oded Padon, Sharon Shoham

We propose an incremental approach for safety proofs that decomposes a proof with a complex inductive invariant into a sequence of simpler proof steps. Our proof system combines rules for (i) forward reasoning using inductive invariants, (ii) backward reasoning using inductive invariants of a time-reversed system, and (iii) prophecy steps that add witnesses

Meritxell Vila-Miñana, Robert Jankowski, Aina Ferrà Marcús, Rubén Ballester

Determining whether two graphs are isomorphic is a fundamental problem with practical applications in areas such as molecular chemistry or social network analysis, yet it remains a challenging task, with exact solutions often being computationally expensive. We address this task using persistent homology built on motif-based filtrations of graphs, a method f

Joongwon Kim, Wannan Yang, Kelvin Niu, Hongming Zhang

Test-time scaling has become a powerful way to improve large language models. However, existing methods are best suited to short, bounded outputs that can be directly compared, ranked or refined. Long-horizon coding agents violate this premise: each attempt produces an extended trajectory of actions, observations, errors, and partial progress taken by the ag

Alex A. T. Rathke

We show that a rational agent with true and refinable knowledge of events cannot know if she knows everything or not. This epistemic limitation is not resolved by introspection about tautologies or by learning about new events.

Simon Becker, Cambyse Rouzé, Robert Salzmann

We develop a quantum algorithm for estimating the free energy as well as the total Gibbs state of interacting quantum Coulomb gases and molecular systems in dimensions $d \in \{2,3\}$ at finite temperature. These systems lie beyond the reach of existing methods due to their singular interactions and infinite-dimensional Hilbert space structure. First, we sho

Sushovan Majhi, Atish Mitra, Santanu Nandi, Md Nurujjaman

We develop a framework for detecting regime transitions in dynamical systems using the Mixup Euler Characteristic Profile (Mixup ECP) -- the Euler characteristic of the geometric intersection of ball unions around adjacent delay-embedded trajectory segments, viewed as a function of filtration scale. The Mixup ECP provides a detection statistic with a built-i

Shreyansh Agrawal, Panagiotis Charalambous, Laura Donnay, Stefano Liberati

Stationary black hole geometries with non-degenerate Cauchy horizons are classically unstable due to mass inflation. At extremality, mass inflation is absent, but a different dynamical instability arises: the Aretakis instability. In this work, we investigate the properties of degenerate horizons and their associated Aretakis instabilities. By studying examp

Asher Labovich

Looped transformers promise test-time compute scaling by spending more iterations on harder problems, but it remains unclear which architectural choices let them extrapolate to harder problems at test time rather than memorize training-specific solutions. We introduce a fixed-point based framework for analyzing looped architectures along three axes of stabil

Zoltán Kolarovszki, Ágoston Kaposi, Zoltán Zimborás, Michał Oszmaniec

Photonic architectures are one of the leading platforms for demonstrating quantum computational advantage, with Boson Sampling and Gaussian Boson Sampling as the primary schemes. Yet, we lack for these photonic primitives a systematic theoretical understanding of linear cross-entropy benchmarking (LXEB), which is a central tool for testing quantum advantage

Kavin Kumar N R, Saili Keshri, Sudhanshu Barway

We investigate the stellar population properties of pseudo-bulges in barred galaxies drawn from the Sloan Digital Sky Survey (SDSS DR7) to assess how bars regulate central star formation and secular evolution. Our sample comprises barred spiral and barred lenticular (S0) galaxies with reliable spectroscopic indices obtained from multicomponent structural dec

D. Bečirević, R. Di Palma, R. Frezzotti, G. Gagliardi

We present a lattice QCD study of dilepton production in charmonium transitions, specifically focusing on the $1^{+-} \to 0^{-+}$ and $1^{++} \to 1^{--}$ processes: $h_c \to \eta_c \ell^+ \ell^-$ and $\chi_{c1} \to J/\psi \ell^+ \ell^-$, where $\ell = e, \mu$. The relevant hadronic matrix elements are computed using gauge field configurations generated by th

Ryo Murakami, Yichuan Tang, Haichong K. Zhang

Real-time multi-spectral photoacoustic imaging (RT-mPAI) often suffers from synchronization instabilities when interfacing fast-tuning lasers with data acquisition platforms executing on non-real-time operating systems. To overcome this, we establish an open-source hardware-software architecture tailored for the widely adopted combination of the OPOTEK Phocu

Matthias Beck, Caroline Klivans, Dustin Ross

Brion's Formula realizes the Laurent polynomial of lattice points in a lattice polytope P as the sum of rational functions associated to the vertices of P. In this paper, we consider the special case where P is a generalized permutohedron. We study a modification of the rational functions associated to the vertices of P depending on a given matroid M. Upon s

Yukun Jiang, Yage Zhang, Michael Backes, Xinyue Shen

Large language models (LLMs) have evolved into autonomous agents that rely on open skill ecosystems (e.g., ClawHub and Skills.Rest), hosting numerous publicly reusable skills. Existing security research on these ecosystems mainly focuses on vulnerabilities within skills, such as prompt injection. However, there is a critical gap regarding skills that may be

Paolo Maranzano, Pietro Colombo, Felicetta Carillo, Riccardo Borgoni

We present "Sequestering CARbon through Forests, AgriCulture, and land usE (SCARFACE)", a harmonized spatio-temporal dataset that integrates climate, air quality, airborne pollutant emissions, land cover, soil properties, agro-industry dynamics and socio-economic indicators, to jointly investigate interconnected processes linking agricultural systems, atmosp

Chi Wang, David Angeli

This paper presents a tractable tube-based robust data-driven predictive control scheme that uses only a single finite noisy input-state trajectory of an unknown discrete-time linear time-invariant (LTI) system. A simplex constraint is imposed on the Hankel coefficient vector, yielding explicit polyhedral bounds on the prediction mismatch induced by bounded

Nathan Belrhali, Arthur Poisson, Sébastien Renaux-Petel, Denis Werth

In this work, we build a novel frequency-momentum space for $(d+1)$-dimensional de Sitter (dS) correlators from first principles. This construction follows directly from the decomposition into unitary irreducible representations (UIRs) of the spacetime isometry group $\mathrm{SO}(1,d+1)$. While the spatial momentum space is given by the standard $d$-dimensio

M. Bielewicz, M. Kiecana, A. Bancer, J. Grzyb

The MCORD detector is a modular scintillator-based system employing silicon photomultipliers (SiPMs) and FPGA-based digital signal processing, designed for applications such as cosmic muon detection, veto systems, and detector calibration support. In this work, we investigate the influence of ambient temperature variations on detector performance, with parti

Ray Iskander, Khaled Kirah

Post-quantum cryptographic (PQC) accelerators implementing ML-KEM (FIPS 203) and ML-DSA (FIPS 204) require side-channel resistance evidence for FIPS 140-3 certification. However, exact masking-verification tools scale only to gadgets of a few thousand cells. We present a four-stage verification hierarchy, D0/D1 structural dependency analysis, fresh-mask refi

Quentin Buzet, André Chailloux

The 2-Forrelation problem provides an optimal separation between classical and quantum query complexity and is also the problem used for separating $\mathsf{BQP}$ and $\mathsf{PH}$ relative to an oracle. A natural question is therefore to ask what are the minimal quantum resources needed to solve this problem. We show that 2-Forrelation can be solved using I

Jaehoon Chung

We study a variant of a polygon partition problem, introduced by Chung, Iwama, Liao, and Ahn [ISAAC'25]. Given orthogonal unit vectors $\mathbf{u},\mathbf{v}\in \mathbb{R}^2$ and a polygon $P$ with $n$ vertices, we partition $P$ into connected pieces by cuts parallel to $\mathbf{v}$ such that each resulting subpolygon has width at most one in direction $\mat

Christophe Pallier, Julie Bonnaire, Marie-France Fourcade

We introduce `Goxpyriment', a new open-source software framework for programming behavioral and cognitive experiments using the Go programming language. The library is designed to address some limitations of existing Python-based experiment tools, particularly the runtime environment complexity that frequently complicates deployment across laboratories. Beca

Kiran Purohit, Ramasuri Narayanam, Soumyabrata Pal

Speculative decoding (SD) accelerates large language model inference by allowing a lightweight draft model to propose outputs that a stronger target model verifies. However, its token-centric nature allows erroneous steps to propagate. Prior approaches mitigate this using external reward models, but incur additional latency, computational overhead, and limit

Come Fiegel, Pierre Menard, Tadashi Kozuno, Michal Valko

We study the problem of learning minimax policies in zero-sum matrix games. Fiegel et al. (2025) recently showed that achieving last-iterate convergence in this setting is harder when the players are uncoupled, by proving a lower bound on the exploitability gap of Omega(t^{-1/4}). Some online mirror descent algorithms were proposed in the literature for this

Jeff A. Dror, Antonios Kyriazis

If the Universe underwent a cosmic phase transition, it may have left behind a network of cosmic strings. When these strings arise from the breaking of a gauge symmetry, their decay produces a significant stochastic background of gravitational waves. In contrast, if they originate from the breaking of a global symmetry, their decay predominantly yields Nambu

Zhuan Ning

We present a numerical-relativity study of comparable-mass boson star-black hole (BS-BH) head-on collisions, focusing on both initial-data construction and gravitational-wave (GW) phenomenology. We show that plain superposition can strongly perturb the BS core, leading to large constraint violations and unphysical radial oscillations. To remedy this problem,

Jiawei Ren, Michal Jan Tyszkiewicz, Jiahui Huang, Zan Gojcic

In this work, we revisit several key design choices of modern Transformer-based approaches for feed-forward 3D Gaussian Splatting (3DGS) prediction. We argue that the common practice of regressing Gaussian means as depths along camera rays is suboptimal, and instead propose to directly regress 3D mean coordinates using only a self-supervised rendering loss.

Anand Gokhale, Anton V. Proskurnikov, Yu Kawano, Francesco Bullo

This paper establishes a nonlinear separation principle based on contraction theory and derives sharp stability conditions for recurrent neural networks (RNNs). First, we introduce a nonlinear separation principle that guarantees global exponential stability for the interconnection of a contracting state-feedback controller and a contracting observer, alongs