March 2025 arXiv papers — page 20

Sergei Dyda

We study line driven stellar winds using multifrequency, time-dependent radiation hydrodynamics. We compute the radiation force due to lines, the so called force multiplier, using precomputed photoionization tables and a time-dependent, local SED using a three band approximation within the hydro. We find that accounting for changes in the local SED changes t

Kausik Ghosh, Miguel F. Paulos, Noé Suchel

We provide an effective solution of the 1D crossing equation. We begin by arguing that crossing constraints can be recast in terms of bases of sum rules associated to special sets of CFT data -- extremal solutions -- which solve these constraints in a minimal way and naturally saturate positivity bounds on the space of CFTs. We conjecture, argue and check ex

Ayse Kotil, Elijah Pelofske, Stephanie Riedmüller, Daniel J. Egger

The goal of multi-objective optimization is to understand optimal trade-offs between competing objective functions by finding the Pareto front, i.e., the set of all Pareto optimal solutions, where no objective can be improved without degrading another one. Multi-objective optimization can be challenging classically, even if the corresponding single-objective

Hanling Zhang, Rundong Su, Zhihang Yuan, Pengtao Chen

Text-to-image generation models, especially Multimodal Diffusion Transformers (MMDiT), have shown remarkable progress in generating high-quality images. However, these models often face significant computational bottlenecks, particularly in attention mechanisms, which hinder their scalability and efficiency. In this paper, we introduce DiTFastAttnV2, a post-

Jane C. Bright

This paper explores an unexpected yet compelling parallel between the evolution of the universe, as described by cosmological eras, and the artistic evolution of Taylor Swift, delineated by her distinct album eras. By mapping key characteristics and transitions in the universe's history to corresponding themes and milestones in Swift's career, I offer a nove

Shuai Zhang, Zhiheng Huang, Muchen Du, Tianping Ying

Phonons are quanta of lattice vibrations, and their modes (linear, circular, or stationary) are symmetry-determined. Circularly polarized phonons, possessing nonzero angular momentum (AM), have drawn widespread attention recently. Despite widespread use of pseudo-angular momentum (PAM) and circularly polarized light polarization flips to identify chiral phon

Ji Wang

Johannes Kepler's attempt to explain the arrangement of the six innermost planets of the Solar System using his Platonic Solid Model-which postulates that planetary orbits are nested within the five Platonic solids-was ultimately unsuccessful. However, while his model failed to describe our own planetary system, Kepler was remarkably prescient in hypothesizi

Xu Yang, Ryan Buechele, Nandini Trivedi

We show that the braiding of anyons in a quantum spin liquid leaves a distinct dynamical signature in the nonlinear pump-probe response. Using a combination of exact diagonalization and matrix product state techniques, we study the nonlinear pump-probe response of the toric code in a magnetic field, a model which hosts mobile electric $e$ and magnetic $m$ an

Erin Kara, Javier García

X-rays are a critical wavelength for understanding supermassive black holes (SMBHs). X-rays probe the inner accretion flow, closest to the event horizon, where gas inspirals, releasing energy and driving black hole growth. This region also governs the launching of outflows and jets that regulate galaxy evolution and link SMBH growth to their host galaxies. T

Rikab Gambhir

In this new era of large data, it is important to make sure we do not miss any signs of new physics. Using the publicly-available open data collected by the arXiv.org experiment in the \texttt{hep-ph} channel, corresponding to a raw total integrated $\mathcal{L}$iterature of 65,276 papers, we perform a search for ``New Physics'' and related signals. In the w

Yiqiu Han, Xiaoyang Huang, Zohar Komargodski, Andrew Lucas

Ordered phases of matter, such as solids, ferromagnets, superfluids, or quantum topological order, typically only exist at low temperatures. Despite this conventional wisdom, we present explicit local models in which all such phases persist to arbitrarily high temperature. This is possible since order in one degree of freedom can enable other degrees of free

Angelo George, Ivana Damjanov, Marcin Sawicki, Devin J. Williams

We investigate the impact of environment on quiescent galaxy (QG) size evolution using the CLAUDS+HSC imaging covering 18.6~deg$^2$ in five broad filters ($Ugriz$) and the effective radius of a single-S\'{e}rsic fit as a proxy for galaxy size. We estimate sizes in two rest-frame wavelengths -- 3000\r{A} (UV) and 5000\r{A} (optical) -- for $\sim86,000$ massiv

Maximilian Detering, Victor Enguita, Belen Gavela, Thomas Steingasser

New physics at the TeV scale or lower may destabilise the electroweak vacuum. How low could the vacuum instability scale be? This fundamental question may be tied to a deeper understanding of the Higgs potential and its associated hierarchy problem. The scale of vacuum instability can be viewed as an upper bound on the Higgs mass-the so-called vacuum metasta

Connor Hainje, David W. Hogg

Any permutation-invariant function of data points $\vec{r}_i$ can be written in the form $\rho(\sum_i\phi(\vec{r}_i))$ for suitable functions $\rho$ and $\phi$. This form - known in the machine-learning literature as Deep Sets - also generates a map-reduce algorithm. The area of a triangle is a permutation-invariant function of the locations $\vec{r}_i$ of t

Weiqi Li, Xuanyu Zhang, Shijie Zhao, Yabin Zhang

Image quality assessment (IQA) focuses on the perceptual visual quality of images, playing a crucial role in downstream tasks such as image reconstruction, compression, and generation. The rapid advancement of multi-modal large language models (MLLMs) has significantly broadened the scope of IQA, moving toward comprehensive image quality understanding that i

Mohammad Almansoori, Komal Kumar, Hisham Cholakkal

In this work, we introduce MedAgentSim, an open-source simulated clinical environment with doctor, patient, and measurement agents designed to evaluate and enhance LLM performance in dynamic diagnostic settings. Unlike prior approaches, our framework requires doctor agents to actively engage with patients through multi-turn conversations, requesting relevant

Ruining Li, Chuanxia Zheng, Christian Rupprecht, Andrea Vedaldi

Most 3D object generators prioritize aesthetic quality, often neglecting the physical constraints necessary for practical applications. One such constraint is that a 3D object should be self-supporting, i.e., remain balanced under gravity. Previous approaches to generating stable 3D objects relied on differentiable physics simulators to optimize geometry at

Jiakai Tang, Sunhao Dai, Teng Shi, Jun Xu

Sequential Recommendation (SeqRec) aims to predict the next item by capturing sequential patterns from users' historical interactions, playing a crucial role in many real-world recommender systems. However, existing approaches predominantly adopt a direct forward computation paradigm, where the final hidden state of the sequence encoder serves as the user re

Belinda Z. Li, Been Kim, Zi Wang

Large language models (LLMs) have shown impressive performance on reasoning benchmarks like math and logic. While many works have largely assumed well-defined tasks, real-world queries are often underspecified and only solvable by acquiring missing information. We formalize this information-gathering problem as a constraint satisfaction problem (CSP) with mi

Jianguo Zhang, Thai Hoang, Ming Zhu, Zuxin Liu

Large Action models are essential for enabling autonomous agents to perform complex tasks. However, training such models remains challenging due to the diversity of agent environments and the complexity of noisy agentic data. Existing infrastructure offers limited support for scalable, agent-specific fine-tuning and standardized agent data processing. We int

Francesca Pezzuti, Sean MacAvaney, Nicola Tonellotto

State-of-the-art cross-encoders can be fine-tuned to be highly effective in passage re-ranking. The typical fine-tuning process of cross-encoders as re-rankers requires large amounts of manually labelled data, a contrastive learning objective, and a set of heuristically sampled negatives. An alternative recent approach for fine-tuning instead involves teachi

Xenia Flamm, Anne Parreau

We develop a theory of Hilbert geometry over general ordered valued fields, associating with an open convex subset of the projective space a quotient Hilbert metric space. Under natural non-degeneracy assumptions, we prove that the ultralimit of a sequence of rescaled real Hilbert geometries is isometric to the Hilbert metric space of an open convex projecti

Pietro Metuh, Athanasios Paralikis, Paweł Wyborski, Sherwan Jamo

We present superconducting nanowire single-photon detectors (SNSPDs) based on few-layer NbSe$_2$ fully encapsulated with hexagonal boron nitride (hBN), demonstrating single-photon sensitivity. Our fabrication process preserves the superconducting properties of NbSe$_2$ in nanowires, as confirmed by low-temperature transport measurements that show a critical

Hsien-Chih Chang, Jonathan Conroy, Hung Le, Shay Solomon

A $(1+\varepsilon)$-stretch tree cover of an edge-weighted $n$-vertex graph $G$ is a collection of trees, where every pair of vertices has a $(1+\varepsilon)$-stretch path in one of the trees. The celebrated Dumbbell Theorem by Arya et. al. [STOC'95] states that any set of $n$ points in $d$-dimensional Euclidean space admits a $(1+\varepsilon)$-stretch tree

Sindhu B Hegde, K R Prajwal, Taein Kwon, Andrew Zisserman

Co-speech gestures play a vital role in non-verbal communication. In this paper, we introduce a new framework for co-speech gesture understanding in the wild. Specifically, we propose three new tasks and benchmarks to evaluate a model's capability to comprehend gesture-speech-text associations: (i) gesture based retrieval, (ii) gesture word spotting, and (ii

Anjan Giri

We discuss the possible implications of physics beyond the standard model in the neutrino sector applying non-standard interaction. Recently, the NOvA and T2K neutrino experiments have announced their measurements for the CP violating parameter $\delta_{CP}$. The observed value of T2K is around 1.5$\pi$, while NOvA gives the same parameter value around 0.8$\

Caitriona S. Leedham, Richard A. Booth, Cathie J. Clarke

Young protoplanetary discs are expected to be gravitationally unstable, which can drive angular momentum transport as well as be a potential mechanism for planet formation. Gravitational instability is most prevalent in the outer disc where cooling timescales are short. At large radii, stellar irradiation makes a significant contribution to disc heating and

Matteo Straccamore, Matteo Bruno, Andrea Tacchella

Debates over the trade-offs between specialization and diversification have long intrigued scholars and policymakers. Specialization can amplify an economy by concentrating on core strengths, while diversification reduces vulnerability by distributing investments across multiple sectors. In this paper, we use patent data and the framework of Economic Complex

Melissa Ewing, Maxime Parra, Guglielmo Mastroserio, Alexandra Veledina

We report the first detection of the X-ray polarisation of the transient black hole X-ray binary IGRJ17091-3624 taken with the Imaging X-ray polarimetry Explorer (IXPE) in March 2025, and present the results of an X-ray spectro-polarimetric analysis. The polarisation was measured in the 2--8 keV band with 5.2$\sigma$ statistical confidence. We report a polar

Elitza Hristova, Thiago Castilho de Mello

In this paper, we consider the relatively free algebra of rank $n$, $F_n(\mathfrak{N}_p)$, in the variety of Lie nilpotent associative algebras of index $p$, denoted by $\mathfrak{N}_p$, over a field of characteristic zero. We describe an explicit minimal basis for the polynomial identities of $F_n(\mathfrak{N}_p)$ when $p=3$ and $p=4$, for all $n$, except f

Andrew Chu, Xi Jiang, Shinan Liu, Arjun Bhagoji

Access to raw network traffic data is essential for many computer networking tasks, from traffic modeling to performance evaluation. Unfortunately, this data is scarce due to high collection costs and governance rules. Previous efforts explore this challenge by generating synthetic network data, but fail to reliably handle multi-flow sessions, struggle to re

Amaury Lambert, Emmanuel Schertzer, Yannic Wenzel

Species complexes are groups of closely related populations exchanging genes through dispersal. We study the dynamics of the structure of species complexes in a class of metapopulation models where demes can exchange genetic material through migration and diverge through the accumulation of new mutations. Importantly, we model the ecological feedback of diff

Ángel Castro, Liangchen Zou

We consider the three-phase Muskat problem with different densities and the same viscosities. The lifespan of the solutions with respect to the width of the strip between interfaces is studied. Indeed, the interfaces are parameterized by the graph of two functions $f(x,t)$ and $g(x,t)$ and we impose that $||f(\cdot,0)-g(\cdot,0)||_{L^\infty}\leq C\sigma$ and

S. Mariani, L. Audouin, E. Berti, P. Coppin

The latest generation of cosmic-ray direct detection experiments is providing a wealth of high-precision data, stimulating a very rich and active debate in the community on the related strong discovery and constraining potentials on many topics, namely dark matter nature, and the sources, acceleration, and transport of Galactic cosmic rays. However, interpre

Danish Khan

We develop a non-linear and non-empirical (nlane) double hybrid density functional derived from an accurate interpolation of the adiabatic connection in density functional theory, incorporating the correct asymptotic expansions. By bridging the second-order perturbative weak correlation limit with the fully interacting limit from the semi-local SCAN function

I. Samuel Akinwande, Chelsea Sidrane, Mykel J. Kochenderfer, Clark Barrett

As dynamical systems equipped with neural network controllers (neural feedback systems) become increasingly prevalent, it is critical to develop methods to ensure their safe operation. Verifying safety requires extending control theoretic analysis methods to these systems. Although existing techniques can efficiently handle linear neural feedback systems, re

M. Matushko, A. Mostovskii, A. Zotov

We consider the elliptic Calogero-Inozemtsev system of ${\rm BC}_n$ type with five arbitrary constants and propose $R$-matrix valued generalization for $2n\times 2n$ Takasaki's Lax pair. For this purpose we extend the Kirillov's ${\rm B}$-type associative Yang-Baxter equations to the similar relations depending on the spectral parameters and the Planck const

Frank J. Brooks, Rucha Deshpande

Super-resolution, in-painting, whole-image generation, unpaired style-transfer, and network-constrained image reconstruction each include an aspect of machine-learned image synthesis where the actual ground truth is not known at time of use. It is generally difficult to quantitatively and authoritatively evaluate the quality of synthetic images; however, in

Anowar J. Shajib, Nafis Sadik Nihal, Chin Yi Tan, Vedant Sahu

Strong gravitational lensing is a powerful tool for probing the internal structure and evolution of galaxies, the nature of dark matter, and the expansion history of the Universe, among many other scientific applications. For almost all of these science cases, modeling the lensing mass distribution is essential. For that, forward modeling of imaging data to

Annie Paine, Casper Gyurik, Antonio Andrea Gentile

Quantum computers have been proposed as a solution for efficiently solving non-linear differential equations (DEs), a fundamental task across diverse technological and scientific domains. However, a crucial milestone in this regard is to design protocols that are hardware-aware, making efficient use of limited available quantum resources. We focus here on pr

Gabriella Contardo, Roberto Trotta, Serafina Di Gioia, David W. Hogg

Recent analyses of cosmological hydrodynamic simulations from CAMELS have shown that machine learning models can predict the parameter describing the total matter content of the universe, $\Omega_{\rm m}$, from the features of a single galaxy. We investigate the statistical properties of two of these simulation suites, IllustrisTNG and ASTRID, confirming tha

Gillian Grindstaff, Julia Lindberg, Daniela Schkoda, Miruna-Stefana Sorea

Pasque et al. showed that using a tropical symmetric metric as an activation function in the last layer can improve the robustness of convolutional neural networks (CNNs) against state-of-the-art attacks, including the Carlini-Wagner attack. This improvement occurs when the attacks are not specifically adapted to the non-differentiability of the tropical lay

Nikhil Kodali, Kartick Ramakrishnan, Phani Motamarri

Chebyshev Filtered Subspace Iteration (ChFSI) is widely used for computing a small subset of extremal eigenpairs from large matrices, particularly when the eigenpairs must be computed repeatedly as the system matrix evolves within an outer nonlinear iteration. In this work, we propose R-ChFSI, a residual-based reformulation that recasts the Chebyshev polynom

Samuel Dai, Ray Li, Eugene Tang

We study the tradeoffs between the locality and parameters of subsystem codes. We prove lower bounds on both the number and lengths of interactions in any $D$-dimensional embedding of a subsystem code. Specifically, we show that any embedding of a subsystem code with parameters $[[n,k,d]]$ into $\mathbb{R}^D$ must have at least $M^*$ interactions of length a

Maxim van den Berg, Matthias Christandl, Vladimir Lysikov, Harold Nieuwboer

Free tensors are tensors which, after a change of bases, have free support: any two distinct elements of its support differ in at least two coordinates. They play a distinguished role in the theory of bilinear complexity, in particular in Strassen's duality theory for asymptotic rank. Within the context of quantum information theory, where tensors are interp

Tianyi Chu, Oliver T. Schmidt

A stochastic data-driven reduced-order model applicable to a wide range of turbulent natural and engineering flows is presented. Combining ideas from Koopman theory and spectral model order reduction, the stochastic low-dimensional inflated convolutional Koopman model (SLICK) accurately forecasts short-time transient dynamics while preserving long-term stati

Jose María Ezquiaga, Rico K. L. Lo, Luka Vujeva

Gravitational lensing magnification is maximal around caustics. At these source locations, an incoming wave from a point source would formally experience an infinite amplification in the high-frequency or geometric optics limit. This divergence reflects the break-down of the mathematical formalism, which is regularized by either the finite size of the source

Maxime Faure, Pierre-Henri Conze, Béatrice Cochener, Anas-Alexis Benyoussef

Real-time prediction of technical errors from cataract surgical videos can be highly beneficial, particularly for telementoring, which involves remote guidance and mentoring through digital platforms. However, the rarity of surgical errors makes their detection and analysis challenging using artificial intelligence. To tackle this issue, we leveraged videos

Semaan Douglas Wehbe, Stanley Bak

Simulation-based approaches are among the most practical means to search for safety violations, bugs, and other unexpected events in cyber-physical systems (CPS). Where existing approaches search for simulations violating a formal specification or maximizing a notion of coverage, in this work we propose a new goal for testing: to discover unknown rare behavi

Chung Ming Loi, Anne Reinarz, Mikkel Lykkegaard, William Hornsby

Uncertainty Quantification (UQ) workloads are becoming increasingly common in science and engineering. They involve the submission of thousands or even millions of similar tasks with potentially unpredictable runtimes, where the total number is usually not known a priori. A static one-size-fits-all batch script would likely lead to suboptimal scheduling, and

Nina Weng, Aasa Feragen, Siavash Bigdeli

Uncovering the opacity of diffusion-based generative models is urgently needed, as their applications continue to expand while their underlying procedures largely remain a black box. With a critical question -- how can the diffusion generation process be interpreted and understood? -- we proposed Patronus, an interpretable diffusion model that incorporates a

Daniel Grier, Debbie Leung, Zhi Li, Hakop Pashayan

Given multiple copies of a mixed quantum state with an unknown, nondegenerate principal eigenspace, quantum state purification is the task of recovering a quantum state that is closer to the principal eigenstate. A streaming protocol relying on recursive swap tests has been proposed and analysed for noisy depolarized states with arbitrary dimension and noise

Francesco Versaci, Giovanni Busonera

In the last decades, the computational power of GPUs has grown exponentially, allowing current deep learning (DL) applications to handle increasingly large amounts of data at a progressively higher throughput. However, network and storage latencies cannot decrease at a similar pace due to physical constraints, leading to data stalls, and creating a bottlenec

Maria E. Steinrueck, Vivien Parmentier, Laura Kreidberg, Peter Gao

Measuring the atmospheric composition of hazy sub-Neptunes like GJ~1214b through transmission spectroscopy is difficult because of the degeneracy between mean molecular weight and haziness. It has been proposed that phase curve observations can break this degeneracy because of the relationship between mean molecular weight (MMW) and phase curve amplitude. Ho

Helena Coggan, Pradip Chaudhari, Yuval Barak-Corren, Andrew M. Fine

Objective: To describe the association of demographic factors with triage acuity, hospital admission rates, and length of stay (LOS) for adult patients in the emergency department (ED). Methods: We performed a retrospective cross-sectional analysis using publicly available electronic health records describing visits to the ED of a single US medical center du

Gabriel Pontolillo, Mohammad Reza Mousavi, Marek Grzesiuk

Property-based testing has been previously proposed for quantum programs in Q# with QSharpCheck; however, this implementation was limited in functionality, lacked extensibility, and was evaluated on a narrow range of programs using a single property. To address these limitations, we propose QuCheck, an enhanced property-based testing framework in Qiskit. By

Yuhao Yan, R. Adam Bayliss, Adam R. Burr, Andrew M. Baschnagel

Purpose: To evaluate a Deep-Learning-enhanced MUlti-PArametric MR sequence (DL-MUPA) for treatment response assessment for brain metastases patients undergoing stereotactic radiosurgery (SRS) and head-and-neck (HnN) cancer patients undergoing conventionally fractionation adaptive radiation therapy. Methods: DL-MUPA derives quantitative T1 and T2 maps from a

Yohan John, Vade Shah, James A. Preiss, Mahnoosh Alizadeh

What is the performance cost of using simple, decoupled control policies in inherently coupled systems? Motivated by industrial refrigeration systems, where centralized compressors exhibit economies of scale yet traditional control employs decoupled room-by-room temperature regulation, we address this question through the lens of multi-location inventory con

Friederike Ihssen, Jan M. Pawlowski

We use the physics-informed renormalisation group (PIRG) for the construction of gauge invariant renormalisation group flows. The respective effective action is a sum of a gauge invariant quantum part and the classical gauge fixing part which arranges for invertibility of the gauge field two-point function. Thus, the BRST transformations simply accommodate t

J. C. Esmenda, E. A. Laird, I. Bailey, N. Du

Superconducting microwave cavities have found applications in many areas including quantum computing, particle accelerators, and dark matter searches. Their extremely high quality factors translate to very narrow bandwidth, which makes them key components of sensitive detectors. In this study, we aim to understand the loss mechanisms of an aluminium cavity a

Melody Chan, Emily Clader, Caroline Klivans, Dustin Ross

This paper studies rings of integral piecewise-exponential functions on rational fans. Motivated by lattice-point counting in polytopes, we introduce a special class of unimodular fans called Ehrhart fans, whose rings of integral piecewise-exponential functions admit a canonical linear functional that behaves like a lattice-point count. In particular, we ver

Vladimir Yushutin

Continuous data assimilation addresses time-dependent problems with unknown initial conditions by incorporating observations of the solution into a nudging term. For the prototypical heat equation with variable conductivity and the Neumann boundary condition, we consider data assimilation schemes with non-interpolant observables unlike previous studies. Thes

Marzia Bordone, Claudia Cornella, Joe Davighi

The rare semi-leptonic decays $B\to K^\ast \ell^+\ell^-$, with $\ell=e, \mu$, are highly sensitive to new physics (NP) due to their suppression in the Standard Model (SM). Current LHCb measurements in the muon channel exhibit a significant tension with state-of-the-art SM theory predictions. The proposed tera-$Z$ run at FCC-ee provides a unique opportunity t

Adam Wei, Abhinav Agarwal, Boyuan Chen, Rohan Bosworth

Cotraining with demonstration data generated both in simulation and on real hardware has emerged as a promising recipe for scaling imitation learning in robotics. This work seeks to elucidate basic principles of this sim-and-real cotraining to inform simulation design, sim-and-real dataset creation, and policy training. Our experiments confirm that cotrainin

Maxim van den Berg, Matthias Christandl, Vladimir Lysikov, Harold Nieuwboer

Moment polytopes of tensors, the study of which is deeply rooted in invariant theory, representation theory and symplectic geometry, have found relevance in numerous places, from quantum information (entanglement polytopes) and algebraic complexity theory (GCT program and the complexity of matrix multiplication) to optimization (scaling algorithms). Towards

Richard J Anslow, Amy Bonsor, Zoe R Todd, Robin Wordsworth

Cometary impacts play an important role in the early evolution of Earth, and other terrestrial exoplanets. Here, we present a numerical model for the interaction of weak, low-density cometary impactors with planetary atmospheres, which includes semi-analytical parameterisations for the ablation, deformation, and fragmentation of comets. Deformation is descri

Nicolas L. Guidotti, Per-Gunnar Martinsson, Juan A. Acebrón, José Monteiro

Many scientific applications require the evaluation of the action of the matrix function over a vector and the most common methods for this task are those based on the Krylov subspace. Since the orthogonalization cost and memory requirement can quickly become overwhelming as the basis grows, the Krylov method is often restarted after a few iterations. This p

Stefano Grassi

Central bank communication plays a critical role in shaping economic expectations and monetary policy effectiveness. This study applies supervised machine learning techniques to classify the sentiment of press releases from the Bank of Thailand, addressing gaps in research that primarily focus on lexicon-based approaches. My findings show that supervised lea

C. Maier, B. L. Ziegler, T. Kodama

We explore the massive cluster XMMXCS J2215.9-1738 at z about 1.46 with MUSE and KMOS integral field spectroscopy. Using MUSE spectroscopy we traced the kinematics of the ionized gas using [OII] in the central 500x500 square kpc area of the cluster, which contains 28 spectroscopically identified cluster galaxies. We detected [OII] emission lines in the integ

Benjamin Musci, Berengere Dubrulle, Jean LeBris, Damien Geneste

This work experimentally explores the alignment of the vorticity vector and the strain-rate tensor eigenvectors at locations of extreme upscale and downscale energy transfer. We show that the turbulent von Karman flow displays vorticity-strain alignment behavior across a large range of Reynolds numbers, which are very similar to previous studies on homogeneo

David Chodounský, Natasha Dobrinen, Thilo Weinert

We prove that each finite chain in the two-branching countable ultrahomogeneous pseudotree has finite big Ramsey degrees. This is in contrast to the recent result of Chodounský, Eskew, and Weinert that antichains of size two have infinite big Ramsey degree in the pseudotree. Combining a lower bound result of theirs with work in this paper shows that chains o

Alex Gu, Naman Jain, Wen-Ding Li, Manish Shetty

AI for software engineering has made remarkable progress recently, becoming a notable success within generative AI. Despite this, there are still many challenges that need to be addressed before automated software engineering reaches its full potential. It should be possible to reach high levels of automation where humans can focus on the critical decisions

J. C. Acevedo-Muñoz, F. D. Lora-Clavijo, A. Cruz-Osorio

The hypothesis that classical scalar fields could constitute dark matter on galactic and cosmic scales has garnered significant interest. In scenarios where supermassive black holes (SMBHs) form through the accretion of matter onto black hole seeds, a critical question arises: what role does dark matter play in this process? We conduct a numerical investigat

Shiva Gaur, Akash Kumar, Himanshu Bangar, Utkarsh Shashank

While the growing utilization of polymers in flexible electronic devices has sparked significant interest in polymer/metal interfaces, spintronic studies of such interfaces remain limited. Here, we systematically study spin pumping across a polymer/ferromagnet metal interface between hydrogen silsesquioxane (HSQ) oligomer layers ($t_\mathit{HSQ} = 30, 36, 48

Jangho Park, Taesung Kwon, Jong Chul Ye

Multi-view or 4D video generation has emerged as a significant research topic. Nonetheless, recent approaches to 4D generation still struggle with fundamental limitations, as they primarily rely on harnessing multiple video diffusion models with additional training or compute-intensive training of a full 4D diffusion model with limited real-world 4D data and

Maximilian Ruff

We prove optimal convergence rates for certain low-regularity integrators applied to the one-dimensional periodic nonlinear Schr\"odinger and wave equations under the assumption of $H^1$ solutions. For the Schr\"odinger equation we analyze the exponential-type scheme proposed by Ostermann and Schratz in 2018, whereas in the wave case we treat the corrected L

Dmitri Fomin

The history of the very first mathematical contests for high school students is discussed. The main body of the article is dedicated to the mathematical and scientific contests held in imperial Russia in the XIX century. More specifically, we discuss and analyze the recently discovered evidence of the city-level official "olympiads" in several school subject

Yiyang Jia

We demonstrate how contact chord diagrams can arise from certain Fock-space models and compute the corresponding correlation functions using the chord path integral technique. In particular, our three-point functions are in the right form dictated by conformal symmetry, and some of our four-point functions match the results of some AdS$_2$ contact Witten dia

Alessio Paviglianiti, Alessandro Silva

Quantum many-body scarred systems exhibit atypical dynamical behavior, evading thermalization and featuring periodic state revivals. In this Letter, we investigate the impact of projective measurements on the dynamics in the scar subspace for the paradigmatic PXP model, revealing that they can either disrupt or enhance the revivals. Local measurements perfor

Fatemeh Fazel Hesar, Mojtaba Raouf, Peyman Soltani, Bernard Foing

This study examines the mineral composition of volcanic samples similar to lunar materials, focusing on olivine and pyroxene. Using hyperspectral imaging from 400 to 1000 nm, we created data cubes to analyze the reflectance characteristics of samples from samples from Vulcano, a volcanically active island in the Aeolian Archipelago, north of Sicily, Italy, c

Anket Mehra, Malte Prieß, Marian Himstedt

This paper shows that further evaluation metrics during model training are needed to decide about its applicability in inference. As an example, a LayoutLM-based model is trained for token classification in documents. The documents are German receipts. We show that conventional classification metrics, represented by the F1-Score in our experiments, are insuf

Kuan-Hsun Wu, Li-Pang Chen

In this paper, we introduce a unified estimator to analyze various treatment effects in causal inference, including but not limited to the average treatment effect (ATE) and the quantile treatment effect (QTE). The proposed estimator is developed under the statistical functional and cumulative distribution function structure, which leads to a flexible and ro

Evgeny V. Ferapontov, Mats Vermeeren

We demonstrate that interesting examples of Lagrangian multiforms appear naturally in the theory of multidimensional dispersionless integrable systems as (a) higher-order conservation laws of linearly degenerate PDEs in 3D, and (b) in the context of Gibbons-Tsarev equations governing hydrodynamic reductions of heavenly type equations in 4D.

L. K. R. Duarte, L. G. Rizzi

In a recent Letter, Shirai and Sakumichi [Phys. Rev. Lett. 130, 148101 (2023), arXiv:2202.12483] presented a study focusing on the origin of a temperature-dependent negative contribution $G_U(T)$ to the elastic modulus $G(T)$ of hydrogels [Yoshikawa et al., Phys. Rev. X 11, 011045 (2021)]. The authors support their findings through an energy-related stiffnes

Satish Rao

A classical algorithm by Bellman and Ford from the 1950's computes shortest paths in weighted graphs on $n$ vertices and $m$ edges with possibly negative weights in $O(mn)$ time. Indeed, this algorithm is taught regularly in undergraduate Algorithms courses. In 2023, after nearly 70 years, Fineman \cite{fineman2024single} developed an $\tilde{O}(m n^{8/9})$

Jayaprakashreddy Cheenepalli, John D. Hastings, Khandaker Mamun Ahmed, Chad Fenner

This study evaluates the adoption of DevSecOps among small and medium-sized enterprises (SMEs), identifying key challenges, best practices, and future trends. Through a mixed methods approach backed by the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI) theory, we analyzed survey data from 405 SME professionals, revealing that while 68%

Hannah Janmohamed, Antoine Cully

Quality-Diversity algorithms are powerful tools for discovering diverse, high-performing solutions. Recently, Multi-Objective Quality-Diversity (MOQD) extends QD to problems with several objectives while preserving solution diversity. MOQD has shown promise in fields such as robotics and materials science, where finding trade-offs between competing objective

Zizhou Liu, Ziwei Gong, Lin Ai, Zheng Hui

Psychological insights have long shaped pivotal NLP breakthroughs, from attention mechanisms to reinforcement learning and social modeling. As Large Language Models (LLMs) develop, there is a rising consensus that psychology is essential for capturing human-like cognition, behavior, and interaction. This paper reviews how psychological theories can inform an

Olaf Post, Jan Simmer

The purpose of this article is to give a short introduction to the concept of quasi-unitary equivalence of quadratic forms and its consequences. In particular, we improve an estimate concerning the transitivity of quasi-unitary equivalence for forms. We illustrate the abstract setting by two classes of examples.

Antonia Karamolegkou, Malvina Nikandrou, Georgios Pantazopoulos, Danae Sanchez Villegas

This paper explores the effectiveness of Multimodal Large Language models (MLLMs) as assistive technologies for visually impaired individuals. We conduct a user survey to identify adoption patterns and key challenges users face with such technologies. Despite a high adoption rate of these models, our findings highlight concerns related to contextual understa

Giuseppe Gaetano Luciano

We present a $f(G,T)$ gravity-based reconstruction of Barrow Holographic Dark Energy (BHDE). This approach extends the conventional HDE model by replacing the Bekenstein-Hawking entropy with Barrow entropy, which encapsulates quantum gravitational corrections to the geometry of black hole horizons. We explore the cosmological dynamics of a flat FRW backgroun

Isaac Malsky, Emily Rauscher, Kevin Stevenson, Arjun B. Savel

The sub-Neptune GJ 1214b has an infamously flat transmission spectrum, likely due to thick aerosols in its atmosphere. A recent JWST MIRI spectroscopic phase curve of GJ 1214 b added to this picture, suggesting a highly reflective and metal-rich atmosphere. Using a 3D General Circulation Model with both photochemical hazes and condensate clouds, we character

Rebecca von Kuk, Kyle Lee, Johannes K. L. Michel, Zhiquan Sun

We pioneer the application of quantum information theory to experimentally distinguish between classes of hadronization models. We adapt the CHSH inequality to the fragmentation of a single parton to hadron pairs, a violation of which would rule out classical dynamics of hadronization altogether. Furthermore, we apply and extend the theory of quantum context

Yu Jun Loo, Silas Alben

We develop a new numerical method for thin plates falling in inviscid fluid that allows for leading-edge vortex shedding. The inclusion of leading-edge shedding restores physical dynamics to vortex-sheet models of falling bodies, and for the first time large-amplitude fluttering and tumbling are observed in inviscid simulations. Leading-edge shedding is achi

Shuai Shen, Wanhua Li, Yunpeng Zhang, Yap-Peng Tan

Talking head synthesis has emerged as a prominent research topic in computer graphics and multimedia, yet most existing methods often struggle to strike a balance between generation quality and computational efficiency, particularly under real-time constraints. In this paper, we propose a novel framework that integrates Gaussian Splatting with a structured A

Caio Silva, Giuseppe Romano

The rising computational demand of modern workloads has renewed interest in energy-efficient paradigms such as neuromorphic and analog computing. A fundamental operation in these systems is matrix-vector multiplication (MVM), ubiquitous in signal processing and machine learning. Here, we demonstrate MVM using inverse-designed metastructures that exploit heat

Francesco Marzioni, Riccardo Natali, Michele Bonaldi, Antonio Borrielli

The quantum transduction of an rf/microwave signal to the optical domain, and vice versa, paves the way for technologies that exploit the advantages of each domain to perform quantum operations. Since electro-optomechanical devices implement a simultaneous coupling of a mechanical oscillator to both an rf/microwave field and an optical field, they are suitab

Mahrokh G. Boroujeni, Laura Meroi, Leonardo Massai, Clara L. Galimberti

Neural networks have demonstrated remarkable success in modeling nonlinear dynamical systems. However, identifying these systems from closed-loop experimental data remains a challenge due to the correlations induced by the feedback loop. Traditional nonlinear closed-loop system identification methods struggle with reliance on precise noise models, robustness

Zijie Li, Anthony Zhou, Amir Barati Farimani

Autoregressive next-step prediction models have become the de-facto standard for building data-driven neural solvers to forecast time-dependent partial differential equations (PDEs). Denoise training that is closely related to diffusion probabilistic model has been shown to enhance the temporal stability of neural solvers, while its stochastic inference mech

Luc Nguyen

We give an existence and classification result for zero-homogeneous and $O(2)$-equivariant critical points of the Oseen-Frank energy with multiple Frank constants. These critical points carry a topological defect of degree one and are minimizing with respect to $O(2)$-equivariant perturbations supported away from the axis of symmetry.