March 2026 arXiv papers — page 61

Melanie Kaasinen, Francesca Rizzo, Francesco Valentino, Cecilia Bacchini

Today's most massive ellipticals are proposed to originate from starbursting galaxies in $z\gtrsim2$ overdensities. To discern what triggers these starbursts, and their $z=0$ descendants, we performed a detailed case study of five gas-rich galaxies in the $z=2.41$ overdensity, HATLAS J084933.4+021443. Using 0.15" resolution CO(4-3), [C I] 1-0, and dust-conti

Royden Wagner, Omer Sahin Tas, Jaime Villa, Felix Hauser

Handling rare events is the central open challenge in autonomous driving. Reasoning models, which generate explicit chains of reasoning before acting, promise to generalize to such events. Here we show that these models frequently do not follow their own reasoning: the actions they state in their reasoning often diverge from the actions they ultimately execu

Jonatan Bohr Brask, Nicolas Brunner, Jef Pauwels, Davide Rusca

A key aspect in quantum information is to understand the advantage offered by quantum systems over classical ones in communication tasks. In recent years, a fundamental approach to this problem has been developed, focusing on quantum correlations in prepare-and-measure scenarios. Inspired by the developments in Bell nonlocality and device-independent informa

L. J. Feije, G. M. Timmer, Y. Hu, R. Karababa

Solid-state spin defects are promising qubits for quantum network nodes. A key challenge towards larger networks is creating defects with high yield into nanophotonic devices, while maintaining good optical and spin properties. Here, we demonstrate the creation of V2 centers in nanopillars fabricated from commercial bulk-grown 4H-silicon carbide using a puls

Christopher L. Baldwin

Although quantum annealing is usually considered as a method for locating the ground states of difficult spin-glass and optimization problems, its use in approximate optimization -- finding low- but not zero-energy states in a reasonably short amount of time -- is no less important. Here we investigate the behavior of quantum annealing at approximate optimiz

Mark R. Lovell, Alexander H. Riley, Isabel Santos-Santos

Estimates for the total number of Milky Way (MW) satellites are often generated from a combination of the observed number of satellites in surveys, adjustments for the completeness of those surveys, and theoretical expectations from halo assembly modelling. One of the features of this modelling is disruption by the MW stellar disc. We examine the effect of d

Xiaolin Ma, Jie Sheng

We propose a quantum sensing protocol for coupled qubit-oscillator systems that surpasses the standard quantum limit by exploiting a geometric phase for dark matter searches. Instead of letting the cavity evolve freely under a weak dark matter background, we combine large coherent displacements and squeezing operations within the evolution protocol, thereby

Anne-Catherine de la Hamette

Quantum reference frames provide a relational description of multipartite quantum systems in which physical states and observables are defined relative to quantum observers. Yet different observers can assign different entropies to the same system, raising the question of how such observer-dependence is constrained. We identify a family of frame-independent

Arjun Srinivasan Kudinoor, Arthur Yi-Ting Lin, Daniel Pablos, Krishna Rajagopal

Ultra-relativistic oxygen-oxygen (OO) collisions are a promising arena in which to probe rare, large-angle, high momentum-transfer $2\rightarrow2$ Moli\`ere scatterings between energetic jet partons and quasiparticles in quark-gluon plasma (QGP). As a jet propagates through the droplet of QGP formed in the same collision, its constituents lose energy to and

Carlo Cepollaro, Andrea Di Biagio

Agreement theorems are no-go results about rational disagreement: if two agents start from a common prior and their posterior beliefs are common knowledge, they cannot assign different probabilities to the same event. Standard treatments of the result have the agents reason about an underlying state of the world, which has lead some to ask whether the result

Charles L. Steinhardt, Carter Meyerhoff, Alexander J. Luening

Because direct measurements require resolved stellar populations including low-mass stars, determining the stellar initial mass function (IMF) has been a historically difficult problem even within our own Galaxy and impossible everywhere else. As a result, even though it is predicted that the IMF should vary depending upon the properties of each individual s

Jordy de Vries, Emanuele Mereghetti, Saad el Morabit, Stefan Sandner

We use heavy-nucleus effective field theory to compute radiative corrections to two-neutrino double-$\beta$ decay ($2\nu\beta\beta$). Our main result is the first derivation of a universal radiative-correction factor for double-weak decays -- the analogue of the Sirlin function in single-$\beta$ decay -- independent of nuclear matrix elements and excitation

Michal Bílek, Florent Renaud, Srdjan Samurović

Most galaxies closely follow the radial acceleration relation (RAR), which tightly links the observed accelerations to those predicted by Newtonian gravity from visible baryonic matter. Galaxy clusters, however, deviate from this relation. Several explanations have been proposed. Some of them predict that even some galaxies in clusters should deviate, but th

Stefano Souza, Nadine Neumayer, Anil C. Seth, Zixian Wang

Omega Centauri ($\omega\,$Cen) is the most massive and chemically complex star cluster in the Milky Way and is widely regarded as the surviving nuclear star cluster of an accreted dwarf galaxy. However, its parent host remains uncertain. Here, we investigate a scenario in which Sequoia, Thamnos, and Gaia--Enceladus (GE) are debris from a single disrupted pro

Kiyan Tavangar, Kathryn V. Johnston, Jason A. S. Hunt, Axel Widmark

The vertical phase-space spirals in the Milky Way are clear evidence of disequilibrium. However, they are challenging to study because phase mixing signals evolve under the influence of many different dynamical processes and can be driven by many sources of disequilibrium. We characterize phase spirals in two simulations -- one test particle and one N-body -

C. Groeneveld, R. J. van Weeren, M. -L. Gendron-Marsolais, E. Osinga

The Perseus cluster is a nearby cool-core galaxy cluster that hosts an archetypal radio mini-halo. Recent Low Frequency Array (LOFAR) High Band Antenna (HBA) observations at 120 - 168 MHz have revealed the presence of a giant radio halo within the cluster with a size of 1.1 Mpc enveloping the mini-halo. By exploring the spectral properties of the radio emiss

Ufaq Khan, Umair Nawaz, L D M S S Teja, Numaan Saeed

Vision Language Models (VLMs) are increasingly used for tasks like medical report generation and visual question answering. However, fluent diagnostic text does not guarantee safe visual understanding. In clinical practice, interpretation begins with pre-diagnostic sanity checks: verifying that the input is valid to read (correct modality and anatomy, plausi

Jie Liu, Zilyu Ye, Linxiao Yuan, Shenhan Zhu

Unified models capable of interleaved generation have emerged as a promising paradigm, with the community increasingly converging on autoregressive modeling for text and flow matching for image generation. To advance this direction, we propose a unified reinforcement learning framework tailored for interleaved generation. We validate our approach on its fund

Jaewon Min, Jaeeun Lee, Yeji Choi, Paul Hyunbin Cho

Optical flow models trained on high-quality data often degrade severely when confronted with real-world corruptions such as blur, noise, and compression artifacts. To overcome this limitation, we formulate Degradation-Aware Optical Flow, a new task targeting accurate dense correspondence estimation from real-world corrupted videos. Our key insight is that th

Sukrut Mondkar, Giorgio Torrieri, Matthias Kaminski, René Meyer

We study the Hall viscosity of the quark gluon plasma (QGP) created in non-central heavy-ion collisions. In the presence of a strong magnetic field or vorticity, rotational symmetry is broken from O(3) to O(2), allowing for two independent Hall viscosities associated with shear deformations transverse and parallel to the symmetry-breaking direction. We find

Zhen Li, Zian Meng, Shuwei Shi, Wenshuo Peng

Dynamical systems theory and reinforcement learning view world evolution as latent-state dynamics driven by actions, with visual observations providing partial information about the state. Recent video world models attempt to learn this action-conditioned dynamics from data. However, existing datasets rarely match the requirement: they typically lack diverse

Chandler B. Smith, S. Hales Swift, Andrew Steyer, Ihab El-Kady

Accurate estimation of aerodynamic state variables such as freestream velocity and angle of attack (AoA) is important for aerodynamic load prediction, flight control, and model validation. This work presents a non-intrusive method for estimating vehicle velocity and AoA from structural vibration measurements rather than direct flow instrumentation such as pi

Adrian Bulat, Alberto Baldrati, Ioannis Maniadis Metaxas, Yassine Ouali

Existing approaches for improving the efficiency of Large Vision-Language Models (LVLMs) are largely based on the concept of visual token reduction. This approach, however, creates an information bottleneck that impairs performance, especially on challenging tasks that require fine-grained understanding and reasoning. In this work, we challenge this paradigm

Yuhan Liu, Jiaxin Xu, Renzheng Zhang, Meng Jiang

Polymers are attractive in applications like flexible electronics and thermal interface materials due to their mechanical compliance and processability. However, conventional polymers have low thermal conductivity (TC), limiting their heat dissipation performance. Identifying polymers that simultaneously achieve high intrinsic TC and mechanical flexibility (

Rishi Paresh Joshi, Sanchayan Banerjee, Sneha Narasimha Moorthy, Tapan Mishra

We study a periodically driven spin-$1/2$ Ising chain with a nearest-neighbour coupling and longitudinal field while a weak transverse field induces single-spin flips. Through Floquet perturbation theory (FPT), we obtain signatures of Hilbert space fragmentation (HSF) and an unconventional form of dynamical localisation which we call the Floquet freezing. Ou

Brian Chao, Lior Yariv, Howard Xiao, Gordon Wetzstein

Diffusion and flow matching models have unlocked unprecedented capabilities for creative content creation, such as interactive image and streaming video generation. The growing demand for higher resolutions, frame rates, and context lengths, however, makes efficient generation increasingly challenging, as computational complexity grows quadratically with the

Sujoy Bhore, Jonathan Conroy, Arnold Filtser

A $t$-spanner of a point set $X$ in a metric space $(\mathcal{X}, \delta)$ is a graph $G$ with vertex set $P$ such that, for any pair of points $u,v \in X$, the distance between $u$ and $v$ in $G$ is at most $t$ times $\delta(u,v)$. We study the problem of maintaining a spanner for a dynamic point set $X$ -- that is, when $X$ undergoes a sequence of insertio

Woojeong Jin, Jaeho Lee, Heeseong Shin, Seungho Jang

Referring Video Object Segmentation (RVOS) aims to segment a target object throughout a video given a natural language query. Training-free methods for this task follow a common pipeline: a MLLM selects keyframes, grounds the referred object within those frames, and a video segmentation model propagates the results. While intuitive, this design asks the MLLM

Adrien Ramanana Rahary, Nicolas Dufour, Patrick Perez, David Picard

Monocular novel-view synthesis has long required multi-view image pairs for supervision, limiting training data scale and diversity. We argue it is not necessary: one view is enough. We present OVIE, trained entirely on unpaired internet images. We leverage a monocular depth estimator as a geometric scaffold at training time: we lift a source image into 3D,

Jini Yang, Eunbeen Hong, Soowon Son, Hyunkoo Lee

Event cameras capture per-pixel brightness changes with microsecond resolution, offering continuous motion information lost between RGB frames. However, existing event-based motion estimators depend on large-scale synthetic data that often suffers from a significant sim-to-real gap. We propose TETO (Tracking Events with Teacher Observation), a teacher-studen

Utsa Dastidar, Arvind Kumar, Harleen Dahiya, Suneel Dutt

Understanding the novel QCD phenomenon under high external magnetic fields of hot and dense medium help us to develop a better understanding of the underlying quark dynamics of baryons. Using a hybrid approach based on the effective field theory that treats quarks as the fundamental degrees of freedom and calculating the individual contribution of valence, s

Aiden Ross, Sankalpa Hazra, Albert Suceava, Dylan Sotir

Future quantum computing architectures require electro-optic materials that maintain a strong, stable performance at cryogenic temperatures. In conventional electro-optic materials, large electro-optic coefficients are often confined to narrow temperature windows near structural phase transitions, where small changes in temperature lead to large changes in t

Andrea Nützi

We show that to every small and decaying solution of the linearized constraint equations about Minkowski spacetime, one can add a quadratically small correction to obtain a solution of the full constraint equations. Near spacelike infinity, the correction is given by Kerr black hole initial data, up to a term that decays faster than the linearized solution,

Nitin Choudhury, Bikrant Bikram Pratap Maurya, Bhavinkumar Vinodbhai Kuwar, Arun Balaji Buduru

Large Language Models (LLMs) trained on massive code corpora are now increasingly capable of generating code that is hard to distinguish from human-written code. This raises practical concerns, including security vulnerabilities and licensing ambiguity, and also motivates a forensic question: 'Who (or which LLM) wrote this piece of code?' We present GoCoMA,

Muhammad Khalid, Manuel Oriol, Yilmaz Uygun

Requirements engineering is a vital, yet labor-intensive, stage in the software development process. This article introduces ReqFusion: an AI-enhanced system that automates the extraction, classification, and analysis of software requirements utilizing multiple Large Language Model (LLM) providers. The architecture of ReqFusion integrates OpenAI GPT, Anthrop

Haoran Yuan, Weigang Yi, Zhenyu Zhang, Wendi Chen

Video-Action Models (VAMs) have emerged as a promising framework for embodied intelligence, learning implicit world dynamics from raw video streams to produce temporally consistent action predictions. Although such models demonstrate strong performance on long-horizon tasks through visual reasoning, they remain limited in contact-rich scenarios where critica

Elliot Jones, Toshiko Matsui, William Knottenbelt

Stablecoins serve as the fundamental infrastructure for Decentralised Finance (DeFi), acting as the primary bridge between fiat currencies and the digital asset ecosystem. While peg stability is well-documented, the structural role stablecoins play in transmitting systemic risk to the broader market remains under-explored. This study uses copula-based approa

Iliana Carmona-Moreno, Grover Andrade-Sánchez, Hugo A Lara-García, Giuseppe Pirruccio

Intercavity polaritons, hybrid quasiparticles with spatially separated photonic and excitonic components, provide a platform to engineer structured light-matter states. We show that resonant driving of the middle polariton branch leads to a qualitatively distinct dynamical regime in which coherent Rabi oscillations are suppressed, and the system evolves mono

Jiaying Lin, Dan Xu

Functionality segmentation in 3D scenes requires an agent to ground implicit natural-language instructions into precise masks of fine-grained interactive elements. Existing methods rely on fragmented pipelines that suffer from visual blindness during initial task parsing. We observe that these methods are limited by single-scale, passive and heuristic frame

Sirui Ning, Yannick A. D. Omar, Karthik Shekhar, Kranthi K. Mandadapu

Understanding how electric fields destabilize biological membranes is important for electroporation-based technologies and bioelectronic interfaces. However, theoretical descriptions of this phenomenon remain fragmented. Existing theories treat either electrostatics in membranes of finite thickness or electrohydrodynamic flows at idealized zero-thickness int

Subhankar Banerjee, Stavros Mitrolaris, Sennur Ulukus

We consider a quantum switch with a finite number of quantum memory registers that aims to serve multipartite entanglement requests among $N$ users. We propose scheduling policies that aim to optimize the average number of requests served per unit time by efficiently utilizing the switch's available memory. To measure the performance of the scheduling polici

Íris Damião, Paulo Almeida, João Franco, Nuno Santos

Search engines (SEs) and large language models (LLMs) are central to political information access, yet their algorithmic decisions and potential underlying biases remain underexplored. We developed a standardized, privacy-preserving, bot-and-proxy methodology to audit four SEs and two LLMs before the 2024 European Parliament and US presidential elections. We

Carlo R. Contaldi, Mauro Pieroni

We propose the Locally Pumped Dark Energy (LPDE) mechanism in which cosmic acceleration is triggered by the emergence of non-linear dark matter structure. In an effective-field-theory description, coarse-graining over the density contrast profile, whose short-wavelength modes grow during halo formation, induces a shift in the local equilibrium point of a sec

Rustem Islamov, Grigory Malinovsky, Alexander Gaponov, Aurelien Lucchi

Federated Learning (FL) enables heterogeneous clients to collaboratively train a shared model without centralizing their raw data, offering an inherent level of privacy. However, gradients and model updates can still leak sensitive information, while malicious servers may mount adversarial attacks such as Byzantine manipulation. These vulnerabilities highlig

Md Mahbubur Rahman, Hengbo Tong, Wei Le

Large language models (LLMs) have shown promising results for software engineering applications, but still struggle with code reasoning tasks such as vulnerability detection (VD). We introduce ConceptCoder, a fine-tuning method that simulates human code inspection: models are trained to first recognize code concepts and then perform reasoning on top of these

Jakob Bannister, Katja Klobas, Colin Rylands, Bruno Bertini

We ask under what conditions a finite brickwork circuit of random gates retains local information about the initial state. To answer this question we measure the averaged Frobenius distance between the reduced states obtained by evolving two arbitrary initial states and tracing out a portion of the system. By characterising this distance exactly at all times

Yiming Lu, Sriram Bharadwaj, Dikshant Rathore, Di Luo

We establish an information-theoretic scaling law for generic autoregressive neural quantum states, determined by the middle-cut mutual information of the wavefunction amplitude. By formalizing the virtual bond as an effective information channel across a sequence bipartition, we rigorously prove that exact autoregressive representation of a quantum state re

Benjamin Bakker

We survey recent advances in non-abelian Hodge theory in the "mixed" setting of non-proper algebraic varieties. We then describe how these tools are used to construct algebraic Shafarevich morphisms and prove a version of the linear Shafarevich conjecture for any algebraic variety.

Jiashu Liang, Martin Head-Gordon

Density functional theory (DFT) offers an exceptional balance between accuracy and efficiency, but practical density functional approximations face an unavoidable trade-off among simplicity, accuracy, and transferability. A systematic protocol is therefore needed to develop functionals that are reliably most accurate within a chosen application domain. Here

Anne Somalwar, Bruce D. Lee, George J. Pappas, Nikolai Matni

Compounding error, where small prediction mistakes accumulate over time, presents a major challenge in learning-based control. A common remedy is to train multi-step predictors directly instead of rolling out single-step models. However, it is unclear when the benefits of multi-step predictors outweigh the difficulty of learning a more complex model. We prov

Guram Bezhanishvili, Wesley H. Holliday

Funayama proved that a lattice embeds into a complete Boolean algebra in such a way that all existing joins and meets are preserved if and only if the lattice satisfies the join-infinite and meet-infinite distributive laws. There are several proofs of this classic result in the literature. In this note, we provide a new and purely order-theoretic proof of Fu

Duc Vu, Kien Nguyen, Trong-Tung Nguyen, Ngan Nguyen

Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-to-image models offer faster generation, but naively applying them to inpainting yields poor harmonization and artifacts between the background and inpainted region. We trace this cause to random Gaussian noise initial

Dana Cohen-Bar, Ido Sobol, Raphael Bensadoun, Shelly Sheynin

State-of-the-art video generation models produce remarkable photorealism, but they lack the precise control required to align generated content with specific scene requirements. Furthermore, without an underlying explicit geometry, these models cannot guarantee 3D consistency. Conversely, 3D engines offer granular control over every scene element and provide

Abdul Rahman

Cybersecurity data remains fragmented across vendors, formats, schemas, and deployment environments, forcing AI and analytics programs to spend disproportionate effort on ingestion, normalization, and brittle source-specific engineering. This paper introduces the Canonical Security Telemetry Substrate (CSTS), a canonical, AI-ready telemetry foundation design

Alejandro Ranchal-Pedrosa, Benjamin Marsh

The TRAP protocol solves rational agreement by combining accountable consensus with a one-shot BFTCR finalization phase. We present SNARE (Scalable Nash Agreement via Reward and Exclusion), the adaptation of TRAP to $n=5f{+}1$, and prove $\epsilon$-$(k,t)$-robustness for rational agreement tolerating coalitions up to ${\approx}73\%$ with deposits under $0.5\

Manishankar Ailiga, Gaurav Narain

In this note we consider no-boundary instantons and wine-glass geometries which are of interest in the context of quantum cosmology. While the former usually appears as a dominant saddle in the path-integral, the wineglass geometry can become dominant saddle in some situations. The later has been argued to have a longer inflationary phase of the Universe. Ko

Jason Bell, Daniel Smertnig

We prove that every Mahler series, over a field of characteristic $0$, with multiplicative coefficients is regular in the sense of Allouche and Shallit. We also obtain an explicit characterization of such series. This yields a joint extension of the characterization of rational series with multiplicative coefficients (by B\'ezivin and Bell--Bruin--Coons) and

CMS Collaboration

A search for new particles decaying to top quark-antiquark pairs is performed using proton-proton collision data at a centre-of-mass energy of 13 TeV. The data set recorded with the CMS detector between 2016 and 2018 is used, corresponding to an integrated luminosity of 138 fb$^{-1}$. Final states with 0, 1, and 2 leptons are analyzed, covering all decay mod

Steffen Schmidt

We study perturbations of relative cubic Dirac operators for basic classical Lie superalgebras within the uniform formalism of the colour quantum Weil algebra. This perspective leads to three complementary classes of perturbations and resulting invariants. First, we define semisimple perturbations that assign to each finite-dimensional simple supermodule a f

Marc Coppens

For a general $k$-gonal curve $C$ with a morphism $f: C \rightarrow \mathbb{P}^1$ of degree $k$, we consider the refinement of the Brill-Noether schemes $W^r_d(C)$ by means of the Brill-Noether degeneracy schemes $\overline{\Sigma}_{\overrightarrow {e}}(C,f)$. The schemes $\overline{\Sigma}_{\overrightarrow {e}}(C,f)$ as sets are closures of subsets $\Sigma_

Sumukha Udupa, Jie Fu

This work studies the synthesis of active perception policies for predictive safety monitoring in partially observable stochastic systems. Operating under strict sensing and communication budgets, the proposed monitor dynamically schedules sensor queries to maximize information gain about the safety of future states. The underlying stochastic dynamics are ca

Yuntong Zhang, Zhiyuan Pan, Imam Nur Bani Yusuf, Haifeng Ruan

Software engineering agents have shown significant promise in writing code. As AI agents permeate code writing, and generate huge volumes of code automatically -- the matter of code quality comes front and centre. As the automatically generated code gets integrated into huge code-bases -- the issue of code review and broadly quality assurance becomes importa

Azam Nouri

We address LLM serving workloads where repeated requests share a common solution structure but differ in localized constraints, such as output schema, variable names, or numeric constants. Prior caching approaches typically reuse either full responses (semantic caching) or model-internal KV/prefix states, which are respectively brittle under partial changes

Yiping Chen, Jinpeng Li, Wenyu Ke, Yang Luo

While multi-modality large language models excel in object-centric or indoor scenarios, scaling them to 3D city-scale environments remains a formidable challenge. To bridge this gap, we propose 3DCity-LLM, a unified framework designed for 3D city-scale vision-language perception and understanding. 3DCity-LLM employs a coarse-to-fine feature encoding strategy

Melina Filzinger, Martin R. Steinel, Jian Jiang, Daniel Bennett

Today's most accurate clocks are based on laser spectroscopy of electronic transitions in single trapped ions and feature fractional frequency uncertainties below $1\times10^{-18}$. Scaling these systems to multiple, simultaneously interrogated ions reduces measurement times, driving recent advances in multi-ion clocks. However, maintaining state-of-the-art

Jiacheng Liu, Bohan Chen, Qian Wang, Weichao Song

Acupoint therapy is a core therapeutic method of Traditional Chinese Medicine (TCM), and it requires a high level of expertise and skills to detect acupoints and perform acupuncture and moxibustion. Existing mixed reality (MR)-based training methods often fall short in accurate real-time detection and visualization of acupoints on the hand, limb, or torso of

Maureen Mghambi Mwadime

Ethical discourse on AI in healthcare has focused predominantly on back-end concerns such as bias, fairness and explainability, while the front-end interface, where patients and clinicians actually encounter AI outputs, remains under explored. This paper identifies imbalanced user-AI relationships as a distinct class of front-end ethical failure: patients ar

Rahul Chakraborty, Aaron Miller, Anton Nykänen, Özlem Salehi

We introduce the Adaptive Derivative-Assembled Pseudo-Trotter ansatz Variational Majorana Propagation Eigensolver (ADAPT-VMPE), a quantum-inspired classical algorithm that exploits Majorana Propagation (MP) to produce circuits for approximating the ground state of molecular Hamiltonians. Equipped with the theoretical guarantees of MP, which provide controlla

Sabaat Haroon, Mohammad Taha Khan, Muhammad Ali Gulzar

Large Language Models (LLMs) are increasingly used for automated unit test generation. However, it remains unclear whether these tests reflect genuine reasoning about program behavior or simply reproduce superficial patterns learned during training. If the latter dominates, LLM-generated tests may exhibit weaknesses such as reduced coverage, missed regressio

Manoj Settem, Emanuele Telari, Antonio Tinti, Riccardo Ferrando

Nanoalloys (or alloy nanoparticles) are an important class of materials that are promising for their functional properties. However, designing synthesis protocols to control their structure and chemical ordering is rather challenging. Part of this difficulty stems from the lack of information on their metastable and stable structures. Here, we develop a gene

Gerardo Iuliano, Daniele Carangelo, Carmine Calabrese, Dario Di Nucci

Mutation testing is a technique to assess the effectiveness of test suites by introducing artificial faults into programs. Although mutation testing plugins are available for many platforms and languages, none is currently available for Remix-IDE, the most widely used Integrated Development Environment for the entire contract development journey, used by use

Francesco Costantino, Nathan Geer, Benjamin Haïoun, Bertrand Patureau-Mirand

For G a group, we present a G-graded version of chromatic maps and skein modules and use them to define a 2+1-G-HQFT out of a G-chromatic category. The construction applies to the representations of unrestricted quantum groups at root of unity and recovers the modified Turaev-Viro 3-dimensional invariants.

Bao Truong, Quang Nguyen, Baoru Huang, Jinpei Han

Seismic images reconstruct subsurface reflectivity from field recordings, guiding exploration and reservoir monitoring. Gas chimneys are vertical anomalies caused by subsurface fluid migration. Understanding these phenomena is crucial for assessing hydrocarbon potential and avoiding drilling hazards. However, accurate detection is challenging due to strong s

Islam Debicha, Tayeb Kenaza, Ishak Charfi, Salah Mosbah

The integration of machine learning (ML) algorithms into Internet of Things (IoT) applications has introduced significant advantages alongside vulnerabilities to adversarial attacks, especially within IoT-based intrusion detection systems (IDS). While theoretical adversarial attacks have been extensively studied, practical implementation constraints have oft

Siyuan Ma, Jérémie Szeftel

In this paper, we prove energy and Morawetz estimates for solutions to Teukolsky equations in spacetimes with metrics that are perturbations, compatible with nonlinear applications, of Kerr metrics in the full subextremal range. The Teukolsky equations are written in tensorial form using the non-integrable formalism in \cite{GKS22}, and we follow the approac

Connor Mclaughlin, Nigel Lee, Lili Su

Machine learning models often need to adapt to new data after deployment due to structured or unstructured real-world dynamics. The Continual Learning (CL) framework enables continuous model adaptation, but most existing approaches either assume each task contains sufficiently many data samples or that the learning tasks are non-overlapping. In this paper, w

Robert Cass, Thibaud van den Hove, Jakob Scholbach

We develop a notion of exponential motives on general prestacks equipped with a $\mathbf{G}_a$-action, and compare them with Whittaker motives via Gaitsgory's Kirillov model. We then establish foundational results for exponential motives on affine flag varieties concerning Tate motives and t-structures. We use this to prove a motivic Casselman-Shalika equiva

Gopal P. Sarma, Sunny D. Bhatt, Michael Jacob, Rachel Steratore

In this report, we review the current state of methodologies to forecast the arrival of artificial general intelligence, assess their reliability, and analyze the implications for strategy and policy. We synthesize diverse forecasting approaches, document significant limitations in existing methods, and propose a research agenda for developing more-robust fo

Marco Origlia, Erdem Eray Cil, Laurent Schmalen, Marco Secondini

We recently introduced a reverse reconciliation scheme with soft information. In this paper, we assess its performance at ultra-low SNR, thus proving that such scheme is a versatile solution to the reverse reconciliation problem.

Xinmin Hou, Xujun Liu, Xiangyang Wang

For a non-decreasing sequence $S = (s_1, s_2, \ldots, s_k)$ of positive integers, a packing $S$-coloring of a graph $G$ is a partition of $V(G)$ into $V_1, V_2, \ldots, V_k$ such that each $V_i$ has pairwise distance at least $s_i+1$. The packing chromatic number (PCN) of a graph $G$ is the minimum $k$ such that $G$ has a packing $(1,2, \ldots, k)$-coloring.

Mikhail Freer, Thilo Klein, Josué Ortega

We conduct the first laboratory school choice experiment in which parents-the relevant decision makers in the field-are the experimental subjects. We compare Deferred Acceptance (DA) with two manipulable but potentially more efficient alternatives: Efficiency-Adjusted Deferred Acceptance (EADA) and the Rank-Minimizing mechanism (RM). We find that all mechani

Valentin Link

Dynamics of open quantum systems with structured reservoirs can often be simulated efficiently with tensor network influence functionals. The standard variants of the time-evolving matrix product operator (TEMPO) method are applicable when the systems is coupled to Gaussian bosonic baths via hermitian coupling operators that mutually commute. In this work we

Tao Jiang, Sean Longbrake, Liana Yepremyan

In this paper we show that for any poset $P$ that is not an antichain, the number of induced $P$-free families in the Boolean lattice $2^{[n]}$ is at most $ 2^{O(\mathrm{La}^*(n,P))}$, where $\mathrm{La}^*(n,P)$ denotes the the largest size of an induced $P$-free subfamily of $2^{[n]}$. We also obtain related supersaturation results.

Nathan Reading, Salvatore Stella

We characterize the theta functions for vectors in the imaginary wall in a cluster algebra of acyclic affine type and compute some of their structure constants. One of the structure constant computations can be interpreted as new "imaginary" exchange relations among cluster variables. We show that theta functions in the imaginary wall span a subalgebra of th

Giovanni Antonio Chirilli

I develop a mixed-space formulation of high-energy deep-inelastic scattering in the shock-wave formalism at sub-eikonal order. Starting from the quark propagator in the background field, I derive the corresponding mixed-space Feynman rules from the LSZ reduction formula in the presence of a shock wave, including the instantaneous contributions generated by t

M. M. Sharma, Ankush Saxena, S. M. Huang, Santosh Karki Chhetri

Materials that intrinsically possess both magnetism and topological states represent a key frontier of quantum materials research. Recently, Mn2(Bi/Sb)2Te5 has emerged as a promising candidate for hosting topological surface states coupled with intrinsic magnetic order, making it a potential magnetic Weyl semimetal. In this study, we investigate the magnetic

Alexander Jung, Cezar Crăciunoiu, Nikolaos Karaolidis, Hugo Lefeuvre

Specializing an OS to optimize the performance of a particular application is typically a manual process that requires great expertise. Specialization through configuration lends itself well to automation; however, it is challenging due to the sheer size of the configuration space of modern OSes, the difficulty to quantify that space, the long time it takes

Oleg Alekseev

We study the mixed Hessian of the dispersionless Toda $\tau$-function for the one-harmonic $s$-fold symmetric conformal map $f(w)=rw+aw^{1-s}$. This Hessian is the susceptibility matrix generated by the inverse conformal map. Our spectral statements are formulated for its weighted symmetry-block realizations on a fixed Hilbert space. In that realization, the

Kaustav Mukherjee, Hatem Barghathi, Adrian Del Maestro, Rick Mukherjee

Motzkin spin chain is a well-known mathematical model with connections to symmetry-protected topological phases, such as the Haldane phase, as well as to concepts in the AdS/CFT correspondence. They exhibit highly entangled ground states that violate the area law and are exceptionally difficult to simulate with conventional numerical methods. Numerical simul

Erick J Canales-Rodríguez, Chantal M. W. Tax, Juan Manuel Górriz, Derek K. Jones

Pulsed-gradient spin-echo (PGSE) MRI experiments probe molecular self-diffusion through spin phase accumulation under time-dependent magnetic field gradients. For diffusion confined to cylindrical surfaces, existing analytical signal models typically rely on the narrow-pulse limit, approximate treatments of finite gradient durations, or the Gaussian phase ap

Teerthaa Parakh, Karen M. Feigh

Human decision-making is strongly influenced by cognitive biases, particularly under conditions of uncertainty and risk. While prior work has examined bias in single-step decisions with immediate outcomes and in human interaction with a single autonomous agent, comparatively little attention has been paid to decision-making under delayed outcomes involving m

Chunhua Li, Wanting Liu, Linfa Tang, Ying Ding

We analysis the $\sqrt{s}$-dependent line shapes of the $e^+e^-\to D_s^{+}D_{s1}^{*-}(2536)$, $D_s^{+}D_{s2}^{*-}(2573)$, $\phi\chi_{c1,2}$, $K^+K^-J/\psi$, $K_S^0 K_S^0 J/\psi$, and $K^+K^-\psi(2S)$ cross sections measured by the BESIII experiment using the four resonant structures $\psi(4230)$, $\psi(4500)$, $\psi(4660)$, and $\psi(4710)$, by performing a

Rabsan Galib Ahmed, Graeme Smith, Peixue Wu

The one-way distillable entanglement is a central operational measure of bipartite entanglement, quantifying the optimal rate at which maximally entangled pairs can be extracted by one-way LOCC. Despite its importance, it is notoriously hard to compute, since it is defined by a regularized optimization over many copies and adaptive one-way protocols. At pres

Pierluigi Masai, Lorenzo Carta, Mateusz Miroslaw Lis

The integration of Generative AI (GenAI) into audio-visual production is often presented as a radical break from past traditions. However, through a sociomaterial and historical lens, this paper argues that GenAI represents a new development in the long-standing negotiation between creative labor and technological possibilities. Moving beyond the limiting fr

Yiqi Zhang, Huiqiang Jiang, Xufang Luo, Zhihe Yang

Scaling reinforcement learning (RL) has shown strong promise for enhancing the reasoning abilities of large language models (LLMs), particularly in tasks requiring long chain-of-thought generation. However, RL training efficiency is often bottlenecked by the rollout phase, which can account for up to 70% of total training time when generating long trajectori

D. J. McKenna, E. F. Keane

Here we report null results in the search for radio emission below $200$~MHz from six known fast radio burst sources. The observations reported here were taken using the Irish LOFAR station's high-band antennas over the course of 2020, 2021 and 2022; the cumulative observing time was $218$~h.

K. A. Toshchenko, P. V. Baklanov, K. M. Belotsky, S. I. Blinnikov

Numerous microlensing survey programs have constrained the possibility of dark matter existing in the form of compact objects within the Galactic halo. These constraints on the dark matter fraction were derived under the assumption of isolated, widely separated objects. This work investigates microlensing by primordial black holes (PBHs) organized into clust

Bing-Sheng Lin, Tai-Hua Heng

In order to quantize systems involving second-class constraints, one should use Dirac bracket instead of Poisson bracket. Furthermore, one can specify a star product in which the term linear in $\hbar$ is proportional to the Dirac bracket. In this way an oscillator system in a deformed fermionic phase space is analyzed and the corresponding energy level and

Sina Kalweit, Ricardo Fernandes, Alberto Alamia, Marta Victoria

Achieving climate neutrality in Europe requires rapid electrification alongside carbon management strategies for residual emissions. Existing analyses of the European energy system often focus on collocated carbon capture and geological sequestration, with limited attention to the interactions among carbon capture and utilization, transport, sequestration, a

Joelle Hanna, Damian Falk, Stella X. Yu, Damian Borth

Recent advances in remote sensing have led to an increase in the number of available foundation models; each trained on different modalities, datasets, and objectives, yet capturing only part of the vast geospatial knowledge landscape. While these models show strong results within their respective domains, their capabilities remain complementary rather than