October 2025 arXiv papers — page 209

Gabriel Barrenechea, Abner J. Salgado

We consider the approximation to the solution of the initial boundary value problem for the heat equation with right hand side and initial condition that merely belong to $L^1$. Due to the low integrability of the data, to guarantee well-posedness, we must understand solutions in the renormalized sense. We prove that, under an inverse CFL condition, the solu

Yuanjie Lu, Mingyang Mao, Tong Xu, Linji Wang

Autonomous robot navigation systems often rely on hierarchical planning, where global planners compute collision-free paths without considering dynamics, and local planners enforce dynamics constraints to produce executable commands. This discontinuity in dynamics often leads to trajectory tracking failure in highly constrained environments. Recent approache

Qian Wang, Mohammad N. Bisheh, Kamran Paynabar

Modern sensing and metrology systems now stream terabytes of heterogeneous, high-dimensional (HD) data profiles, images, and dense point clouds, whose natural representation is multi-way tensors. Understanding such data requires regression models that preserve tensor geometry, yet remain expressive enough to capture the pronounced nonlinear interactions that

Nathan J. Szymanski, Kent J. Warren, Alan W. Weimer, Christopher J. Bartel

Solar thermochemical water splitting enables hydrogen production by cycling metal oxides between reduced and oxidized states, typically through an oxygen vacancy mechanism. However, recent experimental work suggests that cation vacancies have a greater influence on the redox behavior of iron aluminate spinels used in water splitting. This remains debated, as

Zahin Ibnat, Paul E. Calzada, Rasin Mohammed Ihtemam, Sujan Kumar Saha

As large language models (LLMs) continue to be integrated into modern technology, there has been an increased push towards code generation applications, which also naturally extends to hardware design automation. LLM-based solutions for register transfer level (RTL) code generation for intellectual property (IP) designs have grown, especially with fine-tuned

Jalal Ahmmed, Faruk Ahmed, Rashedul Hasan Shohan, Md. Mahabub Rana

Mango is an important fruit crop in South Asia, but its cultivation is frequently hampered by leaf diseases that greatly impact yield and quality. This research examines the performance of five pre-trained convolutional neural networks, DenseNet201, InceptionV3, ResNet152V2, SeResNet152, and Xception, for multi-class identification of mango leaf diseases acr

Valeriya Kirova, Dzerassa Kadieva, Daniil Vlasenko, Isak B. Blank

We analyze functional magnetic resonance imaging (fMRI) data from the Human Connectome Project (HCP) to match brain activities during a range of cognitive tasks. Our findings demonstrate that even basic linear machine learning models can effectively classify brain states and achieve state-of-the-art accuracy, particularly for tasks related to motor functions

Andrea Tramacere

Multiwavelength polarimetric observations of blazars reveal complex, energy-dependent polarization behavior, including a decrease in polarization fraction from X-rays to millimeter bands and significant variability in the electric vector position angle (EVPA). These trends challenge simple single-zone synchrotron models and suggest a more intricate, turbulen

Patrick Achenbach, Andrei Afanasev, Pawel Ambrozewicz, Adi Ashkenazi

This White Paper is exploring the potential of intense secondary muon, neutrino, and (hypothetical) light dark matter beams produced in interactions of high-intensity electron beams with beam dumps. Light dark matter searches with the approved Beam Dump eXperiment (BDX) are driving the realization of a new underground vault at Jefferson Lab that could be ext

Armand J. Lannerd, Nathan J. Szymanski, Christopher J. Bartel

La$_{1-x}$Sr$_{x}$CoO3-$\delta$ is a promising off-stoichiometric metal oxide that undergoes a topotactic perovskite ($\delta$ = 0) to brownmillerite ($\delta$ = 0.5) transition under electrochemical and thermochemical stimuli, with concomitant variations in its electrical, magnetic, thermal, and optical properties. Recent studies on thin-film cycling in ele

Leandro Candido

Motivated by recent work exhibiting a locally compact scattered space $L$ constructed under Ostaszewski's $\clubsuit$-principle, which yielded a complete classification of linear operators on $C_0(L\times L)$, we extend the analysis to the bilinear setting. We show that, for this space $L$, every bilinear operator $G:C_0(L)\times C_0(L)\to C_0(L)$ admits a u

Zachary Friggstad, Tobias Mömke

In Capacitated Vehicle Routing with Multiple Depots (CVRP-MD) we are given a set of client locations $C$ and a set of depots $R$ located in a metric space with costs $c(i,j)$ between $u,v \in C \cup R$. Additionally, we are given a capacity bound $k$. The goal is to find a collection of tours of minimum total cost such that each tour starts and ends at some

Samuel Voss, Philipp Berg, Janneck Stahl, Daniel Behme

Flow diversion has become a key treatment modality for selected intracranial aneurysms, relying on the principle that a dense mesh of stent wires disrupts blood flow into the aneurysm sac, promoting thrombosis and vessel reconstruction. Despite its clinical success, a subset of patients experiences incomplete occlusion or complications. This study investigat

Lucas Böttcher

Control problems frequently arise in scientific and industrial applications, where the objective is to steer a dynamical system from an initial state to a desired target state. Recent advances in deep learning and automatic differentiation have made applying these methods to control problems increasingly practical. In this paper, we examine the use of neural

Mingliang Xie

We discover a frozen state in decaying turbulent coagulation where the moment ratio M_C stabilizes at 4.5, defying the theoretical prediction of 2 for homogeneous systems. This persistent state emerges from historical memory effects that freeze spatial correlations, challenging the reduction of spatially extended systems to zero-dimensional models. Our findi

Nan Huo, Xiaohan Xu, Jinyang Li, Per Jacobsson

Large language models (LLMs) have demonstrated remarkable performance on single-turn text-to-SQL tasks, but real-world database applications predominantly require multi-turn interactions to handle ambiguous queries, execution errors, and evolving user requirements. Existing multi-turn benchmarks fall short by treating conversation histories as static context

Zhenyu Liu, Varun Ojha

Adversarial training is the most effective defense against adversarial attacks. The effectiveness of the adversarial attacks has been on the design of its loss function and regularization term. The most widely used loss function in adversarial training is cross-entropy and mean squared error (MSE) as its regularization objective. However, MSE enforces overly

James Bartusek, Ruta Jawale, Justin Raizes, Kabir Tomer

We construct a publicly-verifiable non-interactive zero-knowledge argument system for QMA with the following properties. 1. Transparent setup. Our protocol only requires a uniformly random string (URS) setup. The only prior publicly-verifiable NIZK for QMA (Bartusek and Malavolta, ITCS 2022) requires an entire obfuscated program as the common reference strin

Yousef Yeganeh, Maximilian Frantzen, Michael Lee, Kun-Hsing Yu

While Whole Slide Imaging (WSI) scanners remain the gold standard for digitizing pathology samples, their high cost limits accessibility in many healthcare settings. Other low-cost solutions also face critical limitations: automated microscopes struggle with consistent focus across varying tissue morphology, traditional auto-focus methods require time-consum

Thomas A. Trainor

Identified-hadron (PID) spectra from 2.76 TeV Pb-Pb and $p$-$p$ collisions are analyzed via a two-component (soft + hard) model (TCM) of hadron production in high-energy nuclear collisions. The Pb-Pb TCM is adopted with minor changes from a recent analysis of PID hadron spectra from 5 TeV $p$-Pb collisions. The object of study is evidence for jet suppression

Vinicius Maron Sauer

This work presents an analytical investigation of the hydrodynamic entrance region in laminar flows through slender converging pipes. Extending previous analyses for straight pipes, the model radially divides the flow into a viscous wall region and a central core where both inertia and viscous effects are important. The study analyzes the impact of the inlet

Micheli T. Moura, Anna Ferré-Mateu, Ana L. Chies-Santos, Cristina Furlanetto

The properties of massive and compact early-type galaxies provide important constraints on early galaxy formation. Among these, massive relic galaxies, characterized by old stellar populations and minimal late-time accretion, are considered preserved compact galaxies from the high-$z$ Universe. We investigate compact and massive galaxies (CMGs) using the TNG

J. G. F. Campos, Azadeh Mohammadi, T. Romanczukiewicz

We consider a rational scalar field model in (1+1)-dimensions where the long-range character of the kinks is controllable. We show via numerical simulations that kinks with long-range tails on both sides can exhibit resonance windows. The resonant energy exchange mechanism occurs via the excitation of quasinormal modes, which we obtain via a spectral analysi

Yining She, Daniel W. Peterson, Marianne Menglin Liu, Vikas Upadhyay

With the increasing adoption of large language models (LLMs), ensuring the safety of LLM systems has become a pressing concern. External LLM-based guardrail models have emerged as a popular solution to screen unsafe inputs and outputs, but they are themselves fine-tuned or prompt-engineered LLMs that are vulnerable to data distribution shifts. In this paper,

Kevin Player

We study the cosine similarity of sentence transformer embeddings and observe that they are well modeled by gamma mixtures. From a fixed corpus, we measure similarities between all document embeddings and a reference query embedding. Empirically we find that these distributions are often well captured by a gamma distribution shifted and truncated to [-1,1],

Matthew De Furio, Marie Ygouf, Alexandra Greenbaum, Graça Rocha

The James Webb Space Telescope is orders of magnitude more sensitive than any other facility across the near to mid-infrared wavelengths. Many approved programs take advantage of its highly stable point spread function (PSF) to directly detect faint companions using diverse high-contrast imaging (HCI) techniques. However, periodic re-phasing of the Optical T

Jieyu Zhou, Aryan Roy, Sneh Gupta, Daniel Weitekamp

Existing AI agents typically execute multi-step tasks autonomously and only allow user confirmation at the end. During execution, users have little control, making the confirm-at-end approach brittle: a single error can cascade and force a complete restart. Confirming every step avoids such failures, but imposes tedious overhead. Balancing excessive interrup

Chris Godsil, Steve Kirkland, Sarojini Mohapatra, Hermie Monterde

A weighted graph $G$ with countable vertex set is bounded if there is an upper bound on the maximum of the sum of absolute values of all edge weights incident to a vertex in $G$. In this paper, we prove a fundamental result on equitable partitions of bounded weighted graphs with twin subgraphs and use this fact to construct finite and bounded infinite graphs

Xi Xuan, Xuechen Liu, Wenxin Zhang, Yi-Cheng Lin

Modern front-end design for speech deepfake detection relies on full fine-tuning of large pre-trained models like XLSR. However, this approach is not parameter-efficient and may lead to suboptimal generalization to realistic, in-the-wild data types. To address these limitations, we introduce a new family of parameter-efficient front-ends that fuse prompt-tun

Yuxiang Gao, Yichen Zhang, Shiming Lei, Neil Harrison

A Berry phase of odd multiples of $\pi$ inferred from quantum oscillations (QOs) has often been treated as evidence for nontrivial reciprocal space topology. However, disentangling the Berry phase values from the Zeeman effect and the orbital magnetic moment is often challenging. In centrosymmetric compounds, the case is simpler as the orbital magnetic momen

Bojan Kuzma, Chi-Kwong Li, Edward Poon

We determine the structure of linear maps on complex (real) square matrices sending unitary (orthogonal) matrices to multiples of unitary (orthogonal) matrices. The result is used to determine the linear preservers of matrix pairs satisfying the extremal norm properties $\|AB\| = \|A\| \|B\|$, $\|A^*B\| = \|A\| \|B\|$, or $\|AB^*\| = \|A\| \|B\|$, for the sp

Fahimeh Rahimi, Zeinab Rezaei, Adamu Issifu

Scalar-tensor gravity models are among the prime candidates to explain cosmic acceleration, and compact stars provide unique laboratories for testing such theories. Predictions of scalar-tensor gravity in compact stars can be examined during the evolution of neutron stars. Spontaneous scalarization in relativistic stars is influenced by different properties

Carlos Sagaseta, María José Calderón, José Carlos Abadillo-Uriel

Spin qubits in semiconductor quantum dots offer a gate-tunable platform for quantum information processing. While two-qubit interactions are typically realized through exchange coupling between neighboring spins, coupling spin qubits to photons via hybrid spin-cQED devices enables long-range interactions and integration with other cQED platforms. Here, we in

M. Sajid, Mushir Akhtar, A. Quadir, M. Tanveer

Recent advancements in neural networks, supported by foundational theoretical insights, emphasize the superior representational power of complex numbers. However, their adoption in randomized neural networks (RNNs) has been limited due to the lack of effective methods for transforming real-valued tabular datasets into complex-valued representations. To addre

Paul Maurer, Jérémy Zurcher

In this paper, we establish an Alekseev--Gr\"obner formula for stochastic differential equations (SDEs) driven by a Poisson random measure, which express the global error between a functional of two processes solution of SDEs started at the same initial condition, in terms of the infinitesimal error (i.e, the difference between the SDEs coefficients). In par

P. Cataldi, S. Pedrosa, L. J. Pellizza, D. Ceverino

The James Webb Space Telescope has found an unexpected population of high-mass galaxies ($\log (M^\star / {\rm M} _\odot) \gtrsim 10$) with extremely small effective radii ($\sim 100\,\rm pc$) at $z \gtrsim 6$. Also, the existence of an unusual size--mass relation has been claimed. These observations are only partially reproduced by current models, and the p

Donovan Snyder

Expanding upon the rich history of algebraic techniques in probability, we show the existence of and construct a Markov chain using the Hopf square map on a quantum group that is both non-commutative and non-cocommutative. This extends the work of Diaconis, Pang, and Ram to other Hopf algebras. The new, one-dimensional chain requires different analytical app

Andrew J. Levan

Gamma-ray bursts are flashes of high-energy radiation lasting from a fraction of a second to several hours. Military satellites made the first detections of GRBs in the late 1960s. The $\gamma$-ray emission forms from shocks in a relativistic jet launched from a compact central engine. In addition to the emission of $\gamma$-rays, the interaction of the jet

Zahra Maleki, Amirhossein Akbari, Amirhossein Binesh, Babak Khalaj

Remote photoplethysmography (rPPG) is an innovative method for monitoring heart rate and vital signs by using a simple camera to record a person, as long as any part of their skin is visible. This low-cost, contactless approach helps in remote patient monitoring, emotion analysis, smart vehicle utilization, and more. Over the years, various techniques have b

M. Sajid, Deepanshu Gupta, Yash Modi, Sanskriti Jain

In this paper, we propose AUREXA-SE (Audio-Visual Unified Representation Exchange Architecture with Cross-Attention and Squeezeformer for Speech Enhancement), a progressive bimodal framework tailored for audio-visual speech enhancement (AVSE). AUREXA-SE jointly leverages raw audio waveforms and visual cues by employing a U-Net-based 1D convolutional encoder

Zhenkun Li, Shunyu Wan, Hugo Zhou

For any knot $K$ in $S^3$ and any positive rational $r$, we show that smooth $(-r)$-surgery on $K$ always admits a tight contact structure. More specifically, the tightness is detected by the non-vanishing Heegaard Floer contact invariant.

Peng Wang, Luis Badesa

Synchronous Generators (SGs) currently provide important levels of Short-Circuit Current (SCC), a critical ancillary service that ensures line protections trip during short-circuit faults. Given the ongoing replacement of SGs by power-electronics-based generation, which has a hard limit on current injection, it has become relevant to optimize the procurement

Vyoma Raman, Judy Hanwen Shen, Andy K. Zhang, Lindsey Gailmard

Despite conflicting definitions and conceptions of fairness, AI fairness researchers broadly agree that fairness is context-specific. However, when faced with general-purpose AI, which by definition serves a range of contexts, how should we think about fairness? We argue that while we cannot be prescriptive about what constitutes fair outcomes, we can specif

Manuel Eppler, Steffen Lindner, Lukas Osswald, Thomas Stüber

Time-Sensitive Networking (TSN) is a collection of mechanisms to enhance the realtime transmission capability of Ethernet networks. TSN combines priority queuing, traffic scheduling, and the Time-Aware Shaper (TAS) to carry periodic traffic with ultra-low latency and jitter. That is, so-called Talkers send periodic traffic with highest priority according to

Ruoxing Yang

Large language models (LLMs) such as ChatGPT have evolved into powerful and ubiquitous tools. Fine-tuning on small datasets allows LLMs to acquire specialized skills for specific tasks efficiently. Although LLMs provide great utility in both general and task-specific use cases, they are limited by two security-related concerns. First, traditional LLM hardwar

S. Ku, C. S. Chang, R. Hager, L. W. Schmitz

The neoclassical baseline study of a strongly negative triangularity (NT) plasma and the corresponding positive triangularity plasma is performed using the edge-specialized, total-f gyrokinetic code XGC. A DIII-D-like plasma is used, based on the negative triangularity discharge of DIII-D \#193793. An artificial positive triangularity (PT) equilibrium has be

Joel Wendin, Erik G. Larsson, Claudio Altafini

For the signed graph associated to a deep neural network, one can compute the frustration level, i.e., test how close or distant the graph is to structural balance. For all the pretrained deep convolutional neural networks we consider, we find that the frustration is always less than expected from null models. From a statistical physics point of view, and in

Rui Lin, Yiwen Zhang, Zhicheng Peng, Minghao Lyu

Decision Transformer (DT), which integrates reinforcement learning (RL) with the transformer model, introduces a novel approach to offline RL. Unlike classical algorithms that take maximizing cumulative discounted rewards as objective, DT instead maximizes the likelihood of actions. This paradigm shift, however, presents two key challenges: stitching traject

Unnati Kashyap, Thomas J. Maccarone, Eliot C. Pattie, Mason Ng

We report the first polarimetric results of the neutron star (NS) low-mass X-ray binary (LMXB) Z-source GX 17+2 using the Imaging X-ray Polarimetry Explorer (IXPE) and the Very Large Array (VLA). We find that the X-ray source was polarized at PD = 1.9 +/- 0.3 % (1-sigma errors) with a polarization angle of PA = 11 +/- 4 degree (1-sigma errors). Simultaneous

Radha Gulhane, Sathish Reddy Indurthi

Aligning multimodal large language models (MLLMs) with human preferences often relies on single-signal, model-based reward methods. Such monolithic rewards often lack confidence calibration across domain-specific tasks, fail to capture diverse aspects of human preferences, and require extensive data annotation and reward model training. In this work, we prop

Xavier Andrade, Jacopo Simoni, Yuan Ping, Tadashi Ogitsu

The authors present SHarmonic, a new implementation of the spherical harmonics targeted for electronic-structure calculations. Their approach is to use explicit formulas for the harmonics written in terms of normalized Cartesian coordinates. This approach results in a code that is as precise as other implementations while being at least one order of magnitud

Maggie A. Thompson, Paolo A. Sossi, Dan J. Bower, Anat Shahar

Rocky planet atmospheres form and evolve through interactions between the planet's surface and interior. If a growing rocky planet acquires enough mass prior to the dissipation of the nebular gas disk, it can gravitationally capture a `primary' atmosphere dominated by H2. At the same time, these young, rocky bodies are likely to have partial or global magma

Xiaxing Cai

The anisotropic $s$-fractional area measures are introduced as the first variation of the anisotropic fractional $s$-perimeter $P_s(K,L)$, with $L$ an origin symmetric convex body and $s\in(0,1)$. As $s\rightarrow 1^-$, the anisotropic $s$-fractional area measure converges to the mixed area measure of $K$ and the moment body of $L$. The Minkowski problem of

Paloma García-de-Herreros, Philipp Slusallek, Dietrich Klakow, Vagrant Gautam

While large language models are primarily used on natural language tasks, they have also shown great promise when adapted to new modalities, e.g., for scientific machine learning tasks. Most proposed approaches for such cross-modal adaptation of language models focus on encoder-only transformer model architectures, despite decoder-only architectures being fa

Daigo Ito, John S. Nolan

By a classic theorem of Beilinson, the perfect derived category $\operatorname{Perf}(\mathbb{P}^n)$ of projective space is equivalent to the category of derived representations of a certain quiver with relations. The vertex-wise tensor product of quiver representations corresponds to a symmetric monoidal structure $\otimes_{\mathsf{Q}}$ on $\operatorname{Per

Damiano Anselmi, Gianluca Calcagni

Theories with purely virtual particles (fakeons) do not possess a classical action in the strict sense, but rather a "classicized" one, obtained by integrating out the fake particles at tree level. Although this procedure generates nonlocal interactions, we show that the resulting classicized equations of motion are not burdened with the need to specify infi

Mohammad Ghomi, Matteo Raffaelli

We show that smooth curves with prescribed curvature satisfy a $C^1$-dense $h$-principle in the space of immersed curves in Euclidean space. More precisely, every $C^{\alpha \geq 2}$ curve with nonvanishing curvature in $R^{n\geq 3}$ can be $C^1$-approximated by $C^\alpha$ curves of any larger curvature, prescribed as a function of arclength. It follows that

D. Simeoni, G. Parise, A. R. Rossi, A. Frazzitta

We investigate the impact of a non-negligible background temperature on relativistic plasma wake-fields generated when a beam of charged particles passes through a neutral plasma at rest. We focus on the blowout regime, wherein the plasma response is highly non-linear: plasma electrons are radially blown out and expelled away from the propagation axis of the

Qiuyu Ren, Ian Sullivan, Paul Wedrich, Michael Willis

We construct a variant of Khovanov skein lasagna modules, which takes the Khovanov homology in connected sums of $S^1\times S^2$ defined by Rozansky and Willis as the input link homology. To carry out the construction, we prove functoriality of Rozansky-Willis's homology for cobordisms in a class of $4$-manifolds that we call $4$-dimensional relative $1$-han

Quan-Yi Hu, Zhi-Bin Duan

In this work, we study the contribution of invisible light particles to $\Lambda_b \to \Lambda E_{\mathrm{miss}}$, particularly the three-body decays $\Lambda_b \to \Lambda \phi \bar\phi$ and $\Lambda_b \to \Lambda \psi \bar\psi$. The differential branching ratio of $\Lambda_b \to \Lambda E_{\mathrm{miss}}$ and the $q^2$-dependent longitudinal polarization a

Prashanth Arun, Vinita Vader, Erya Xu, Brent McCready-Branch

AI-assisted learning has seen a remarkable uptick over the last few years, mainly due to the rise in popularity of Large Language Models (LLMs). Their ability to hold long-form, natural language interactions with users makes them excellent resources for exploring school- and university-level topics in a dynamic, active manner. We compare students' experience

Brian Greene, Daniel Kabat, Janna Levin, Massimo Porrati

In higher dimensional theories, we often assume that the extra dimensions form an orientable space, perhaps with singularities. However, many physical theories are well-defined on non-orientable spaces, and many spaces are not orientable, so it is reasonable to explore what happens if the assumption of orientability is relaxed. Here we consider the simplest

Abdellah Atanane, Abdallah Mkhadri, Karim Oualkacha

Quantiles and expectiles are determined by different loss functions: asymmetric least absolute deviation for quantiles and asymmetric squared loss for expectiles. This distinction ensures that quantile regression methods are robust to outliers but somewhat less effective than expectile regression, especially for normally distributed data. However, expectile

Aurélie Champagne, Olugbenga Adeniran, Jonah B. Haber, Antonios M. Alvertis

van der Waals stacking of two-dimensional (2D) materials offers a powerful platform for engineering material interfaces with tailored electronic and optical properties. While most van der Waals multilayers have featured inorganic monolayers, incorporating molecular monolayers introduces new degrees of tunability and functionality. Here, we investigate hybrid

Christina Thrainer, Md Meftahul Ferdaus, Mahdi Abdelguerfi, Christian Guetl

Few-shot semantic segmentation is vital for deep learning-based infrastructure inspection applications, where labeled training examples are scarce and expensive. Although existing deep learning frameworks perform well, the need for extensive labeled datasets and the inability to learn new defect categories with little data are problematic. We present our Enh

Waseem Hussain, Haoyun Huang, Loren N. Pfeiffer, Kenneth W. West

Strong interactions in Landau flat bands are known to stabilize correlated states that do not form in other types of flat bands. We report hallmarks of topological protection at the Landau level filling factor v=7/11 in a two-dimensional electron system. The $\nu=7/11$ filling factor is the particle-hole conjugate of $\nu=4/11$, a filling factor intensely st

Sanhita Parihar, Gurmeet Singh Punia

In this work, we study the holographic entanglement entropy (HEE) and holographic complexity (HC) for three-dimensional dyonic quantum black holes, incorporating corrections arising from bulk quantum fields in the setup of double holography. We investigate the holographic entanglement entropy through the holographic Ryu-Takayanagi (RT) prescription and the i

J. Michael Shull, Rachel M. Curran, Michael W. Topping, Jonathan D. Slavin

The dominant sources of photoionizing radiation in the extreme ultraviolet (EUV) incident on the exterior of the local interstellar clouds include two nearby early B-type stars, $\epsilon$ CMa ($124\pm2$ pc) and $\beta$ CMa ($151\pm5$ pc), three hot dwarfs, and the local hot bubble (LHB). Line emission (170-912A) from highly ionized metals (Fe, Ne, Mg) in mi

Abhinav Deshpande, Bill Fefferman, Soumik Ghosh, Michael Gullans

A key issue of current quantum advantage experiments is that their verification requires a full classical simulation of the ideal computation. This limits the regime in which the experiments can be verified to precisely the regime in which they are also simulatable. An important outstanding question is therefore to find quantum advantage schemes that are als

Yuezhu Xu, S. Sivaranjani

The Lipschitz constant is a key measure for certifying the robustness of neural networks to input perturbations. However, computing the exact constant is NP-hard, and standard approaches to estimate the Lipschitz constant involve solving a large matrix semidefinite program (SDP) that scales poorly with network size. Further, there is a potential to efficient

The CEPC Study Group

The Circular Electron Positron Collider (CEPC) is a large international scientific project initiated by China's particle physicists to study the Higgs boson and perform critical tests of the Standard Model. Housed in a 100-km circumference tunnel in China, the CEPC will primarily operate as a Higgs factory, producing electron-positron collisions at a center-

L. Adamczyk, Y. Ali, J. J. Chwastowski, A. B. Kowalewska

Direct detection of bremsstrahlung photons, in principle, offers the most straightforward and most robust method of luminosity determination at the EIC, but requires an extraordinary performance of the photon detector. In this paper, we first discuss the extreme working conditions for such detectors at the EIC and the resulting technology choices. Then, we r

Thales A. Gutcke, Giulia Despali, Stephanie O'Neil, Mark Vogelsberger

We present a detailed comparison of a Local Group dwarf galaxy analogue evolved in two cosmological models: the standard $\Lambda$CDM and a self-interacting dark matter (SIDM) model with a velocity-dependent cross-section. Both simulations are run with the high-resolution, hydrodynamical LYRA galaxy formation model, allowing us to explore the global and subs

J. Alimena, J. Boyd, G. Cacciapaglia, A. Casais Vidal

With the establishment and maturation of the experimental programs searching for new physics with sizeable couplings at the LHC, there is an increasing interest in the broader particle and astrophysics community for exploring the physics of light and feebly-interacting particles as a paradigm complementary to a New Physics sector at the TeV scale and beyond.

Stéphane Munier

Light-cone perturbation theory is a powerful tool for calculating high-energy scattering amplitudes, particularly for quantum particles such as electrons, photons, or protons scattering off heavy nuclei, a process analogous to potential scattering. Central to these computations are the light-cone wave functions of incoming and outgoing particles, representin

Filipp Sporykhin, Holger Homann

This work discusses the performance of a modern numerical scheme for fluid dynamical problems on modern high-performance computing architectures. Our code implements a spatial nodal discontinuous Galerkin scheme that we test up to an order of convergence of eight. It is temporally coupled to a set of Runge-Kutta methods of orders up to six. The code integrat

Federico Battiston, Christian Bick, Maxime Lucas, Ana P. Millán

Higher-order interactions that nonlinearly couple more than two nodes are important in many networked systems, and their effects on collective dynamics are increasingly being studied. Here we provide an overview of this rapidly growing field, and of the techniques that can be used to describe and analyze them. We focus in particular on new phenomena and chal

Fan Zou, Elena Gallo, Anil C. Seth, Edmund Hodges-Kluck

The black-hole occupation fraction ($f_\mathrm{occ}$) defines the fraction of galaxies that harbor central massive black holes (MBHs), irrespective of their accretion activity level. While it is widely accepted that $f_\mathrm{occ}$ is nearly 100% in local massive galaxies with stellar masses $M_\star \gtrsim 10^{10}~M_\odot$, it is not yet clear whether MBH

Chenghao Yang, Lin Gui, Chenxiao Yang, Victor Veitch

Reinforcement learning with verifiable rewards (RLVR) is a powerful paradigm for enhancing the reasoning capabilities of large language models (LLMs), yet its success hinges on effective exploration. An ideal exploration strategy must navigate two fundamental challenges: it must preserve sample quality while also ensuring training stability. While standard f

Praveen Pai, Aron W. Cummings, Alexander Cerjan, Wei Pan

Nano-patterned semiconductor interfaces offer a versatile platform for creating quantum metamaterials and exploring novel electronic phenomena. In this study, we illustrate this concept using artificial graphene--a metamaterial featuring distinctive properties including Dirac and saddle points. We demonstrate that introducing additional nano-patterning can o

Bhavya Matam, Adamay Mann, Kachina Studer, Christian Gabbianelli

With the growing need to effectively support workforce upskilling in the manufacturing sector, virtual reality is gaining popularity as a scalable training solution. However, most current systems are designed as static, step-by-step tutorials and do not adapt to a learner's needs or cognitive load, which is a critical factor in learning and longterm retentio

Daniel Loughran, Ross Paterson

A conjecture of Malle predicts the quantity of number fields with bounded discriminant of given Galois group. We present a lower bound matching this in the case of quartic fields with Galois group $A_4$.

Debadri Bhattacharjee, Pradip Kumar Chattopadhyay

The correct choice for the matter Lagrangian $(\mathcal{L_{M}})$ in the framework of $f(R,T)$ theory of gravity, has been a fundamental yet often overlooked ambiguity. It has been a long-standing issue, whether to choose $\mathcal{L_{M}}=p$ or $-\rho$ as the proper definition of matter sector. In this work, we show that both choices lead to the same energy-m

Yue Pan, Zihan Xia, Po-Kai Hsu, Lanxiang Hu

As Large Language Models (LLMs) continue to evolve, Mixture of Experts (MoE) architecture has emerged as a prevailing design for achieving state-of-the-art performance across a wide range of tasks. MoE models use sparse gating to activate only a handful of expert sub-networks per input, achieving billion-parameter capacity with inference costs akin to much s

Rishika Bhagwatkar, Kevin Kasa, Abhay Puri, Gabriel Huang

AI agents are vulnerable to indirect prompt injection attacks, where malicious instructions embedded in external content or tool outputs cause unintended or harmful behavior. Inspired by the well-established concept of firewalls, we show that a simple, modular, and model-agnostic defense operating at the agent--tool interface achieves perfect security with h

Ana P Millán, David Poyato, David N Reynolds, Francesco Tudisco

We study the collective dynamics of coupled Stuart--Landau oscillators, which model limit-cycle behavior near a Hopf bifurcation and serve as the amplitude-phase analogue of the Kuramoto model. Unlike the well-studied phase-reduced systems, the full Stuart--Landau model retains amplitude dynamics, enabling the emergence of rich phenomena such as amplitude de

Peter A. Noordman, Lucas Maisel Licerán, Henk T. C. Stoof

Bound electron-hole pairs in semiconductors known as excitons are the subject of intense research due to their potential for optoelectronic devices and applications, especially in the realm of two-dimensional materials. While the properties of free excitons in these systems are well understood, a general description of the interactions between these quasipar

Mehdi Rabiee, Sergio Greco, Reza Shahbazian, Irina Trubitsyna

Focal Cortical Dysplasia (FCD) is a primary cause of drug-resistant epilepsy and is difficult to detect in brain {magnetic resonance imaging} (MRI) due to the subtle and small-scale nature of its lesions. Accurate segmentation of FCD regions in 3D multimodal brain MRI images is essential for effective surgical planning and treatment. However, this task remai

Mohammad Mahdi Ahmadi, Erfan Yazdandoost Hamedani

We study a class of misspecified saddle point (SP) problems, where the optimization objective depends on an unknown parameter that must be learned concurrently from data. Unlike existing studies that assume parameters are fully known or pre-estimated, our framework integrates optimization and learning into a unified formulation, enabling a more flexible prob

Morgan Saidel, Shreyas Vissapragada, Heather Knutson, Ethan Schreyer

Hydrodynamic escape can strip the envelopes of close-in exoplanets, but most observations of atmospheric mass loss to date have been confined to planets orbiting K and M dwarfs. A growing body of detections of atmospheric escape from planets orbiting early-type stars indicates that they may have significantly stronger and more extended outflows than planets

P. Tiwari, B. Banerjee, D. Miceli, G. Oganesyan

Gamma-ray Bursts (GRBs) generate powerful relativistic jets that inject a large amount of energy into their surrounding environment, producing blast waves that accelerate particles to high energies. The GRB afterglow radiation provides a powerful means to investigate the microphysics of relativistic shocks and to probe the medium surrounding the progenitor o

Ziqi Ling, Minghui Liwang, Xianbin Wang, Seyyedali Hosseinalipour

Timely resource allocation in edge-assisted vehicular networks is essential for compute-intensive services such as autonomous driving and navigation. However, vehicle mobility leads to spatio-temporal unpredictability of resource demands, while real-time double auctions incur significant latency. To address these challenges, we propose a look-ahead contract-

Reagan R. D. Weeks, Ryan A. Lane, Brian M. Anderson

We present an all-fiber design for a Tm-based fiber amplifier that can tune over 1992-2065 nm with 300-350 W single-frequency (<100 kHz) output. Over 180 W is achieved out to 2085 nm with <10% ASE content without utilizing ASE spectral filters. The amplifier employs both Tm- and Tm/Ho-doped gain fibers in two preamplifier stages in addition to longer section

Maximilian Bachmaier, Gia Dvali, Juan Sebastián Valbuena-Bermúdez

The $\theta$-vacua of a gauge theory admit an equivalent formulation as vacua of a massless Chern-Simons $3$-form, which originate from the topological susceptibility of the vacuum. This formulation provides a framework in which the physical manifestations of the $\theta$-angle, which are quantum in origin, can be captured at the level of effective classical

James B. Dent, Bhaskar Dutta, Mudit Rai

Primordial black holes (PBHs) formed during first-order phase transitions provide a powerful link between the early-universe microphysics and observable signatures today, including dark matter and gravitational waves. In this work we develop a unified description of PBH formation based on the Israel junction conditions, which capture collapse dynamics withou

Edgar Ortiz Manrique, Médéric Boquien

The increasing use of ML in astronomy introduces important questions about interpretability. Due to their complexity and non-linear nature, it can be challenging to understand their decision-making process. While these models can effectively identify unusual spectra, interpreting the physical nature of the flagged outliers remains a major challenge. We aim t

Alex Friedlan, Hae-Young Kee

The recently-discovered family of Kagome metals has attracted significant interest due to reports of charge-bond order, orbital magnetism, and superconductivity. Some of these phases may exhibit time-reversal symmetry breaking. More recently, experiments have reported the emergence of nematic order that lowers the rotational symmetry of the system from sixfo

Ryan Curry, Jasmine Kozar, Alexandros Gezerlis

We have used the auxiliary-field quantum Monte Carlo (AFQMC) many-body approach on the lattice to study the equation of state for a fermionic impurity interacting with a background sea of spin-polarized fermions. The impurity, or polaron, is an interesting system in both cold atomic and nuclear physics. Our approach is general, and we are able to straightfor

Martin P. Rey, Harley Katz, Corentin Cadiou, Mahsa Sanati

We study the stellar mass-iron metallicity relation of dwarf galaxies in the new high-resolution MEGATRON cosmological radiation-hydrodynamics simulations. These simulations model galaxy formation up to $z\approx8$ in a region that will collapse into a Milky-Way-like galaxy at $z=0$, while self-consistently tracking Population III and II (Pop.~III, Pop.~II)

Dario Antolini, Guido Montúfar, Alessandro Oneto

Motivated by the study of decompositions of tensors as Hadamard products (i.e., coefficient-wise products) of low-rank tensors, we introduce the notion of Hadamard rank of a given point with respect to a projective variety: if it exists, it is the smallest number of points in the variety such that the given point is equal to their Hadamard product. We prove