December 2025 arXiv papers — page 85

Andreas Chatziafratis

We analytically derive novel explicit integral representations for the solution of nonhomogeneous initial-boundary-value problems for a large category of evolution partial differential equations of Sobolev-Galpern type with generic temporally variable coefficients, satisfying suitable mild conditions, and with arbitrary data in classical function spaces. Thi

Rasim Volga Ovali, Taner Tarik Aytas, Ramazan Sahin, Mehmet Emre Tasgin

Apertureless scanning near-field optical microscopy (a-SNOM) is typically limited to ~10 nm resolution by the tip apex size. We demonstrate that ~1-nm resolution can be achieved under continuous-wave (CW) illumination by exploiting Fano path interference. A defect center that naturally forms at the apex of a metal-coated AFM tip acts as a quantum object and

Patrick Hinrichs, Douglas Singleton, Nader Inan

We study the effect of a time-varying solenoidal vector potential for a quantum particle confined to a ring. The setup appears to be a time-varying version of the Aharonov-Bohm effect, but since the particle moves in the presence of fields, it is not strictly an Aharonov-Bohm effect. The results are similar to the ac Stark effect, but with a time-varying ele

Kousar Raza, Faizan Ali

This paper presents a structured and comprehensive dataset corresponding to the 2025 Asia Cup T20 cricket tournament, designed to facilitate data-driven research in sports analytics. The dataset comprises records from all 19 matches of the tournament and includes 61 variables covering team scores, wickets, powerplay statistics, boundary counts, toss decision

Jiashuo Fan, Paul Rosu, Aaron T. Wang, Zeyu Michael Li

There has been significant recent interest in understanding the capacity of Transformers for in-context learning (ICL), yet most theory focuses on supervised settings with explicitly labeled pairs. In practice, Transformers often perform well even when labels are sparse or absent, suggesting crucial structure within unlabeled contextual demonstrations. We in

Dwip Dalal, Utkarsh Mishra, Narendra Ahuja, Nebojsa Jojic

Leveraging multimodal large language models (MLLMs) to develop embodied agents offers significant promise for addressing complex real-world tasks. However, current evaluation benchmarks remain predominantly language-centric or heavily reliant on simulated environments, rarely probing the nuanced, knowledge-intensive reasoning essential for practical, real-wo

Ping-Rui Tsai, Tzay-Ming Hong

The probabilistic interference fringes observed in the double slit experiment vividly demonstrate the quantum superposition principle, yet they also highlight a fundamental conceptual challenge: the relationship between a system before and after the measurement. According to Copenhagen interpretation, an unobserved quantum system evolves continuously based o

Tiancheng Gao, Scott C. Lowe, Brendan Furneaux, Angel X Chang

Accurate taxonomic classification from DNA barcodes is a cornerstone of global biodiversity monitoring, yet fungi present extreme challenges due to sparse labelling and long-tailed taxa distributions. Conventional supervised learning methods often falter in this domain, struggling to generalize to unseen species and to capture the hierarchical nature of the

Matthew Sinclair, Moeen Meigooni, Archit Vasan, Ozan Gokdemir

Intrinsically disordered proteins (IDPs) represent crucial therapeutic targets due to their significant role in disease -- approximately 80\% of cancer-related proteins contain long disordered regions -- but their lack of stable secondary/tertiary structures makes them "undruggable". While recent computational advances, such as diffusion models, can design h

Ethan N. Epperly

In recent years, randomized algorithms have established themselves as fundamental tools in computational linear algebra, with applications in scientific computing, machine learning, and quantum information science. Many randomized matrix algorithms proceed by first collecting information about a matrix and then processing that data to perform some computatio

Sukrut Mondkar, Sayan Mondal, Ujjwal Sen

Fluctuation theorems provide universal constraints on nonequilibrium energy and entropy fluctuations, making them a natural framework to assess how and to what extent quantum resources become thermodynamically relevant. We develop a unified framework for incorporating a generic quantum resource, including athermality, quantum coherence, and entanglement, int

Christophe Grojean, Minyuan Jiang, Pham Ngoc Hoa Vuong

We derive the shockwave metric in four-dimensional Einstein-Maxwell effective field theory (EFT) by performing an ultra-relativistic boost of the charged black hole solution accompanied by a rescaling of its mass and charge, including leading order EFT corrections. In contrast to the neutral (Schwarzschild) case, where higher derivative operators leave the s

Lucas Monteiro Paes, Nivedha Sivakumar, Yinong Oliver Wang, Masha Fedzechkina

Generative models are often deployed to make decisions on behalf of users, such as vision-language models (VLMs) identifying which person in a room is a doctor to help visually impaired individuals. Yet, VLM decisions are influenced by the perceived demographic attributes of people in the input, which can lead to biased outcomes like failing to identify wome

Joel Mire, Maria Antoniak, Steven R. Wilson, Zexin Ma

Reading stories evokes rich interpretive, affective, and evaluative responses, such as inferences about narrative intent or judgments about characters. Yet, computational models of reader response are limited, preventing nuanced analyses. To address this gap, we introduce SocialStoryFrames, a formalism for distilling plausible inferences about reader respons

Ryan J. J. Connor, Preetma Soin, Callum W. Duncan, Andrew J. Daley

The dynamics of plasmas are governed by a set of non-linear differential equations which remain challenging to solve directly for large 2D and 3D problems. Here we investigate how tensor networks could be applied to plasmas described by the Vlasov-Maxwell system of equations and investigate parameter regimes which show promise for efficient simulations. We s

Nuria Alina Chandra, Yucen Lily Li, Alan N. Amin, Alex Ali

To model discrete sequences such as DNA, proteins, and language using diffusion, practitioners must choose between three major methods: diffusion in discrete space, Gaussian diffusion in Euclidean space, or diffusion on the simplex. Despite their shared goal, these models have disparate algorithms, theoretical structures, and tradeoffs: discrete diffusion ha

Lena Giebeler, Deepa Krishnaswamy, David Clunie, Jakob Wasserthal

Purpose AI-based methods for anatomy segmentation can help automate characterization of large imaging datasets. The growing number of similar in functionality models raises the challenge of evaluating them on datasets that do not contain ground truth annotations. We introduce a practical framework to assist in this task. Approach We harmonize the segmentatio

Deaglan J. Bartlett, Harry Desmond, Pedro G. Ferreira, Gabriel Kronberger

Symbolic regression (SR) has emerged as a powerful method for uncovering interpretable mathematical relationships from data, offering a novel route to both scientific discovery and efficient empirical modelling. This article introduces the Special Issue on Symbolic Regression for the Physical Sciences, motivated by the Royal Society discussion meeting held i

David Arroyo, Rafael Mata Milla, Marc Almeida Ros, Nikolaos Lykousas

Crime as a Service (CaaS) has evolved from isolated criminal incidents to a broad spectrum of illicit activities, including social media manipulation, foreign information manipulation and interference (FIMI), and the sale of disinformation toolkits. This article analyses how threat actors exploit specialised infrastructures ranging from proxy and VPN service

Albrecht Kurze, Karola Köferl, Andy Börner

A wide variety of simple sensors, e.g. for temperature, light, or humidity, is finding its way into smart homes. There are special features to consider with regard to the data collected by these sensors: a) the nature of the measured data as "thin but big data" that needs to be contextualized and interpreted, b) which both algorithms and humans are capable o

Jack-William Barotta, Caroline M. Barotta, Eli Silver, Daniel M. Harris

Brownian motion is the erratic motion of an object due to collisions with the fluid in which it is immersed. In this work, we detail a tabletop laboratory demonstration of underdamped Brownian motion wherein a macroscopic particle resting on a driven fluid interface exhibits ballistic motion at short times and diffusive motion at long times. We observe the t

Lican Huang

Hierarchical organization is a fundamental structure in real-world society, where authority and responsibility are delegated from managers to subordinates. The VIRGO network (Virtual Hierarchical Overlay Network for scalable grid computing) provides a scalable overlay for organizing distributed systems but lacks intrinsic security and privacy mechanisms. Thi

Saliha Kıvanç

Ozsv\'ath and Stipsicz showed that some Eliashberg-Chekanov twist knots, which are Whitehead doubles of the unknot, are not Legendrian simple. We extend their result by considering some Whitehead doubles of the trefoil: Using properties of knot Floer homology and the distinguished surgery triangle, we show that this family of knots is Legendrian non-simple i

Nadav Drukker, Ziwen Kong, Petr Kravchuk

Conformal defects -- extended objects in conformal field theories -- carry localised excitations inherited from symmetry currents, known as the displacements and tilts. They capture the linear response of the defect to deformations of its shape or of its profile along internal symmetry directions. There is no universal formula for deformations beyond the lin

Marek Balcerzak, Ľubica Holá, Olena Karlova, Piotr Szuca

We investigate classes of functions from a topological space to a metric space that are related to those of Borel class 1. Following the idea defining an equi-Baire 1 family (due to Lecomte) we define the respective equi-families of functions from the considered classes. We observe that studying of equi-families can be reduced to the exploration of a single

Sarah Burke-Spolaor, Tamara Bogdanović, Daniel J. D'Orazio, Michael Eracleous

Here we summarize discussions and conclusions from the conference ``The Era of Binary Supermassive Black Holes: Coordination of Nanohertz-Frequency Gravitational-Wave Follow-up,'' held at the Aspen Center for Physics from February 2-7, 2025. The meeting facilitated a crucial knowledge exchange between electromagnetic and gravitational-wave theorists, observe

Diego Perez Daroca, Pablo Roura-Bas

The equilibrium thermoelectric and spectral properties of a double quantum dot system are investigated, with the geometry continuously tuned from series to parallel via a parameter $ p $. Within the non-crossing approximation in the infinite-$ U $ limit, the Kondo peak remains robust, while satellite features and the Kondo temperature show strong sensitivity

Diego Lobos

The category $\bcalNT$ was defined in \cite{Lobos2}, it is a category whose objects are commutative nil graded algebras over a field, defined by presentation encoded by triangular matrices. A natural problem related to this category is to reach a complete classification up to isomorphism of its objects. Based in some results coming from \cite{Lobos2}, we can

Tejas Anvekar, Junha Park, Aparna Garimella, Vivek Gupta

Evaluating the quality of tables generated by large language models (LLMs) remains an open challenge: existing metrics either flatten tables into text, ignoring structure, or rely on fixed references that limit generalization. We present TabReX, a reference-less, property-driven framework for evaluating tabular generation via graph-based reasoning. TabReX co

Jonathan A. Handler

Many large language models (LLMs) are trained on a massive body of knowledge present on the Internet. Darth Vecdor (DV) was designed to extract this knowledge into a structured, terminology-mapped, SQL database ("knowledge base" or "knowledge graph"). Knowledge graphs may be useful in many domains, including healthcare. Although one might query an LLM direct

Nik Bhatt

Training advanced denoising models requires large datasets of high-fidelity, physically accurate images. While heteroscedastic noise models can simulate realistic noise, methodologies for their calibration remain under-explored, and large-scale calibrated datasets are scarce. We present a rigorous calibration and tuning pipeline for building high-quality het

Borja Anguiano

Stellar multiplicity is a fundamental ingredient of stellar astrophysics, yet binary statistics across the Galaxy remain poorly constrained. The \emph{Gaia} mission has revolutionised binary star astrophysics by delivering high-precision astrometry, photometry and global radial velocities, and by providing hundreds of thousands of non-single-star solutions i

Roya Beheshti, Shibashis Mukhopadhyay, Eric Riedl

Let X be a smooth hypersurface of degree d in P^n over an algebraically closed field of characteristic p. We show that X must be separably rationally connected and must contain a free line if either p is at least d or if p is at least d-1 and the defining equation has some partial derivative that is not too singular. We also show that X must be separably rat

Leonardo Bohac

We study minimum-error identification of an unknown single-bit Boolean function given black-box (oracle) access with one allowed query. Rather than stopping at an abstract optimal measurement, we give a fully constructive solution: an explicit state preparation and an explicit measurement unitary whose computational-basis readout achieves the Helstrom-optima

Avais Jan, Prakash Chourasia, Sarwan Ali, Murray Patterson

Dimensionality reduction techniques are essential for visualizing and analyzing high-dimensional biological sequencing data. t-distributed Stochastic Neighbor Embedding (t-SNE) is widely used for this purpose, traditionally employing the Gaussian kernel to compute pairwise similarities. However, the Gaussian kernel's lack of data-dependence and computational

Bruno Le Floch, Gela Patashuri, Emilio Trevisani

Parisi-Sourlas supersymmetric models are known to undergo dimensional reduction; that is, their physics is captured by models in two fewer dimensions. In this work, we revisit dimensional reduction, providing new arguments and reformulating existing proofs in terms of the cohomology of a supercharge $Q$. We obtain three main results. First, we show that the

Sin-Myung Lee

We develop the theory of $q$-characters for quantum affine superalgebras of type $A$ in connection with deformed Cartan matrices. To achieve this, we establish a Khoroshkin-Tolstoy-type multiplicative formula of the universal $R$-matrix of the associated generalized quantum group, from which one can read off a 2-parameter deformation of Cartan matrices of su

Yuxun Guo, Werner Vogelsang, Feng Yuan, Wenbin Zhao

We study energy-energy correlators (EECs) in $e^+e^-$ annihilation and deep inelastic lepton-hadron scattering (DIS), focusing on aspects of nonperturbative physics in these observables. We introduce the EEC jet functions and investigate the infrared (IR) behavior of both small-angle EECs and angle-integrated EECs by performing explicit one-loop calculations

Yasna Ordenes-Briceño, Thomas H. Puzia, Paul Eigenthaler, Matias Blaña

Wide-field, multi-band surveys now detect millions of unresolved sources in nearby galaxy clusters, yet separating globular clusters (GCs) from foreground stars and background galaxies remains challenging. Scalable, automated classification is therefore essential to convert the forthcoming data from facilities such as the Vera C. Rubin/LSST, the Roman and Eu

Vahideh Zolfaghari

Large language models (LLMs) are increasingly consulted by parents for pediatric guidance, yet their safety under real-world adversarial pressures is poorly understood. Anxious parents often use urgent language that can compromise model safeguards, potentially causing harmful advice. PediatricAnxietyBench is an open-source benchmark of 300 high-quality queri

Gabriela Barenboim, Julien Froustey, Cyril Pitrou, Héctor Sanchis

Thermal distribution functions can only be of the Fermi-Dirac or Bose-Einstein types, whereas distorted spectra encompass any possible deviations from these shapes. It is fruitful to devise parametrizations of these distortions with only a few parameters which depend on the physical system considered. A method proposed by Stebbins consists in describing a di

Artem Grigor, Christian Schroeder de Witt, Simon Birnbach, Ivan Martinovic

Recent advances in large language models (LLMs) have enabled a new generation of autonomous agents that operate over sustained periods and manage sensitive resources on behalf of users. Trusted for their ability to act without direct oversight, such agents are increasingly considered in high-stakes domains including financial management, dispute resolution,

Jiyuan Fang, Qicheng Tang, Xueda Wen

Exploring universal entanglement structure in many-body systems is both fundamental and challenging, particularly when the system undergoes non-unitary operations. In this work, we uncover a universal mechanism for realizing maximal entanglement swapping in fermionic Gaussian states subjected to projective Bell measurements. We consider two initially decoupl

Yanbing Zhou, Pablo A. M. Casares, Diksha Dhawan, Ignacio Loaiza

Photodynamic therapy (PDT) is a targeted cancer treatment that uses light-activated photosensitizers to generate reactive oxygen species that selectively destroy tumor cells, generally causing less collateral damage than conventional treatments. However, its clinical success hinges on the availability of photosensitizers with strong optical sensitivity and h

Nicholas Storm, Maria Bergemann, Tomasz Różański, Victor F. Ksoll

We present the 4MOST-HR resolution Non-Local Thermal Equilibrium (NLTE) Payne artificial neural network (ANN), trained on $404\,793$ new FGK spectra with 16 elements computed in NLTE. This network will be part of the Stellar Abundances and atmospheric Parameters Pipeline (SAPP), which will analyse 4 million stars during the five year long 4MOST consortium 4:

Jaron Skovsted Gundersen, Rene Bødker Christensen, Petar Popovski, Rafał Wisniewski

In this work, we introduce a technique for reducing the length of a quantum stabilizer code, and we call this deflation of the code. Deflation can be seen as a generalization of the well-known puncturing and shortening techniques in cases where more than a single qudit is removed. We show that the parameters of the deflated quantum code can be controlled, an

Davide Caffagni, Sara Sarto, Marcella Cornia, Lorenzo Baraldi

Multimodal Large Language Models (MLLMs) have recently demonstrated impressive capabilities in connecting vision and language, yet their proficiency in fundamental visual reasoning tasks remains limited. This limitation can be attributed to the fact that MLLMs learn visual understanding primarily from textual descriptions, which constitute a subjective and i

Yanxuan Shao, Jannik L. Wyss, Don Towsley, Adilson E. Motter

Existing protocols for quantum communication networks usually assume an initial allocation of quantum entanglement resources, which are then manipulated through local operations and classical communication (LOCC) to establish high-fidelity entanglement between distant parties. It is generally held that the resulting fidelity would increase monotonically with

Massimiliano Romanello, Giulia Despali, Federico Marulli, Carlo Giocoli

Warm and self-interactive dark matter cosmologies have been proposed as nonbaryonic solutions to the tensions between the $\Lambda$ cold dark matter model and observations at the kiloparsec scale. In this paper, we used the dark matter-only runs of the \textsc{aida-tng} project, a set of cosmological simulations of different sizes and resolutions, to analyze

Julien Wolf, Eduardo Bañados, Xiaohui Fan, Antoine Dumont

Luminous quasars at the redshift frontier z>7 serve as stringent probes of super-massive black hole formation and they are thought to undergo much of their growth obscured by dense gas and dust in their host galaxies. Fully characterizing the symbiotic evolution of SMBHs and hosts requires rest-frame optical observations that span spatial scales from the bro

Tomohiro Oishi, Masaaki Kimura

We show that a two-proton emitter with a diproton-correlated initial state can act as a source of spin-correlated proton pairs. Using a time-dependent three-body model, we investigate the two-proton emission of $^{16}$Ne ($^{14}$O$+2p$) and analyze the spin correlation of the emitted protons. We find that, when the emission proceeds as a democratic three-bod

Enrico Cannizzaro, Marco Palleschi, Laura Sberna, Richard Brito

Massive scalar fields on black hole backgrounds generally admit two families of modes: quasi-bound states (QBS) and quasinormal modes (QNM). We demonstrate the orthogonality between the two mode families with respect to a relativistic product. We also find that, although the two families appear on different Riemann sheets of the Green's function of massive s

Paul Aigner, Wolfgang Dür

We show that a single moving quantum sensor provides complete access to spatially correlated scalar fields. We demonstrate that with either trajectory or internal state control, one can selectively measure any linear functional, e.g. a gradient or a spatial Fourier series coefficient, while successfully eliminating {\it all} noise signals with orthogonal spa

P. Iwanek, D. M. Skowron, G. Pojmański, I. Soszyński

Long secondary period (LSP) variable stars are a subclass of long-period variables (LPV) that exhibit additional long-term variability alongside pulsations. Despite being observed in over 30% of LPVs, the reason behind the LSP phenomenon is still debated. The most favoured explanation, supported by recent growing evidence, is binarity, where the pulsating gi

Jakob Stegmann, Fabio Antonini, Aleksandra Olejak, Sylvia Biscoveanu

The spin-orbit tilt angles $\theta_{1(2)}$ of merging stellar-mass black holes provide key insights into their astrophysical origin. Non-parametric population modelling of The LIGO, Virgo, and KAGRA Collaborations (2025a, arXiv:2508.18083) shows that the spin-orbit tilt distribution of mergers in the latest Gravitational-Wave Transient Catalog 4.0 exhibits a

Andres Perez Fadon, David Pfau, James S. Spencer, Wan Tong Lou

Fractional quantum Hall states host emergent anyons with exotic exchange statistics, but obtaining direct access to their topological properties in real systems remains a challenge. Neural-network wavefunctions provide a flexible computational approach, as they can represent highly correlated states without requiring a tailored basis. Here we use the neural-

Michael A. Rampp, Suhail A. Rather, Pieter W. Claeys

In recent years dual-unitary circuits and their multi-unitary generalizations have emerged as exactly solvable yet chaotic models of quantum many-body dynamics. However, a systematic picture for the solvability of multi-unitary dynamics remains missing. We present a framework encompassing a large class of such non-integrable models with exactly solvable dyna

Mathias Garny, Florian Niedermann, Martin S. Sloth

DESI DR2 data have been widely interpreted as evidence for late-time evolving dark energy (DE) with an apparent phantom crossing. Here we investigate an alternative explanation, based on early-Universe physics. If dark acoustic oscillations (DAO) are close in scale to baryon acoustic oscillations (BAO), they can bias the extraction of the BAO scale from the

Giulia Despali, Carlo Giocoli, Lauro Moscardini, Annalisa Pillepich

In the standard Cold Dark Matter (CDM) scenario, the density profiles of dark matter haloes are well described by analytical models linking their concentration to halo mass. Alternative scenarios, such as warm dark matter (WDM) and self-interacting dark matter (SIDM), modify the inner structure of haloes and predict different profile shapes and central slope

Campbell McLauchlan, Vedant Motamarri, Benjamin Béri

Floquet systems display rich phenomena, such as time crystals, with many-body localisation (MBL) protecting the phases from heating. While several types of Floquet phases have been classified, a unified picture of Floquet MBL is still emerging. Static phases have been fruitfully studied via "symmetry topological field theory" (SymTFT), wherein the universal

Renato M. Fonseca, Pablo Olgoso, José Santiago

Renormalization group equations play a central role in effective field theories, both maintaining perturbative control and allowing one to determine the correct low-energy phenomenology. In this work, we complete the one-loop renormalization of the recently developed general effective field theory up to mass dimension six by providing the beta functions for

Hooman Davoudiasl, Hongkai Liu, Sonny Mantry, Ethan T. Neil

Determining the weak charge form factor, $F_W(Q^2)$, of nuclei over a continuous range of momentum transfers, $0\lesssim Q^2 \lesssim 0.1$ GeV$^2$, is essential for mapping out the distribution of neutrons in nuclei. The neutron density distribution has significant implications for a broad range of areas, including studies of nuclear structure, neutron stars

Geneviève Bélanger, Nicolás Bernal, Andreas Goudelis, Alexander Pukhov

The inert doublet model is a two-Higgs-doublet extension of the standard model that provides a minimal and versatile framework for frozen-out dark matter. Assuming standard cosmology, if the dark matter mass ranges between approximately 120 GeV and 500 GeV then it turns out to be underabundant, as gauge interactions render its annihilation too efficient. In

Supratim Das Bakshi, T. J. Hobbs, Brandon Kriesten

We develop a demonstrator foundation model for collider-scale explorations of the Standard Model Effective Field Theory (SMEFT), constructed from contrastive representations of theoretically simulated neutral-current Drell-Yan cross sections. Using a controlled sampling of the Warsaw-basis dimension-6 Wilson-coefficient space at $O(\Lambda^{-2})$, we generat

Paul Kalas, Jason J. Wang, Maxwell A. Millar-Blanchaer, Bin B. Ren

The nearby star Fomalhaut is orbited by a compact source, Fomalhaut b, which has previously been interpreted as either a dust-enshrouded exoplanet or a dust cloud generated by the collision of two planetesimals. Such collisions are rarely observed but their debris can appear in direct imaging. We report Hubble Space Telescope observations that show the appea

Kristoffer Leraand, Kristian Mæland, Asle Sudbø

We investigate many-body effects on the spin-split electron bands in altermagnets by computing the electron self-energy arising from interactions with magnons, phonons, and hybridized magnon-phonon modes. These interactions lead to band broadening, which can obscure the intrinsic spin-splitting in spectroscopic measurements. We consider a $d$-wave Lieb latti

Thomas O. Winterhalder, Antoine Mérand, Sylvestre Lacour, Jens Kammerer

Despite numerous search campaigns based on a diverse set of observational techniques, exomoons - prospective satellites of extrasolar planets - remain an elusive and hard-to-pin-down class of objects. Yet, the case for intensifying this search is compelling: as in the Solar System, moons can act as proxies for studying planet formation and evolution, provide

Le-Chen Qu

We establish a direct correspondence between the Lanczos approach and the orthogonal polynomials approach in random matrix theory. In the large-$N$ and continuum limits, the average Lanczos coefficients and the recursion coefficients become equivalent, with the precise mapping $b(1-x)=\sqrt{R(x)}$ and $a(1-x)=S(x)$. As a result, the two formalisms yield iden

C. Giocoli, G. Despali, L. Moscardini, M. Meneghetti

Context. The shapes of dark matter halos can be used to constrain the fundamental properties of dark matter. In standard Cold Dark Matter (CDM) cosmologies, halos are typically triaxial, with a preference for prolate configurations, particularly at low masses and high redshift. Aims. We focus on the characterization of total matter 3D shape in alternative da

Georges Obied, Mario Reig

We study some implications of $SU(N)\times U(1)$ theories coupled to gravity in the large-$N$ limit. We find that in theories with quarks transforming as $q\sim (\mathbf{N},1)$, black holes (BH) with charge larger than a critical value approach extremality $(M_{\rm BH}=\sqrt{2} M_{\rm Pl} Q_{\rm BH})$ as they evaporate. This occurs because BHs in this theory

Enzo Bavaro, Javier M. Magan, Leandro Martinek

We introduce a new way to produce infinite families of bases of a quantum system's Hilbert space, as well as methods to find its dimension. These families are constructed via Brownian motions in the Hilbert space, defined using disordered, time-dependent couplings. The dimension spanned by them has zero variance over the ensemble of disordered couplings, and

Guillermo Barro, Pablo G. Perez-Gonzalez, Dale Kocevski, Jonathan R. Trump

One of JWST's most unexpected discoveries is the emergence of "Little Red Dots'' (LRDs): compact sources at $z \gtrsim 3$ with blue rest-frame UV continua, red optical slopes, and broad Balmer emission lines that challenge standard models and suggest a population of early, unusual active galactic nuclei (AGNs). Using a comprehensive photometric selection and

Jin Dong, Stephan Stieberger

Celestial amplitudes are multiple Mellin transforms w.r.t. conformal dimensions. For arbitrary multiplicity $n$ of massless states in sufficiently high space--time dimension $D$ we perform all Mellin integrations and find an associahedron description in celestial space. The latter expresses celestial tree--level $ϕ^3$ amplitudes as the canonical forms associ

Naoto Nakatsuji, Jennifer Cano, Valentin Crépel

Van der Waals heterostructures promise on-demand designer quantum phases through control of monolayer composition, stacking, twist angle, and external fields. Yet, experimental efforts have been narrowly focused, leaving much of this vast moir\'e landscape unexplored and potential promises unrealized. Here, we present a scalable workflow for high-throughput

Cole Meyer, Maria Camarca, Katherine de Kleer, Alexander Thelen

Thermal images at different wavelengths probe varying subsurface depths of planetary bodies, and therefore can inform us about their compositions, thermophysical properties, and impact histories. We identified six archival observations of Callisto obtained by the Atacama Large Millimeter/submillimeter Array (ALMA) between 2012 July 17 and 2012 November 4 at

Orion Ning, Kailash Raman, Benjamin R. Safdi

Axion-like particles can be abundantly produced through scattering processes in the cores of neutron stars (NSs). If they are ultralight ($m_a \lesssim 10^{-4}$ eV), then they can efficiently convert to detectable photons in the external NS magnetospheres, and if they are heavy ($m_a \gtrsim 1$ eV), then they can decay into photons before reaching Earth. In

Michal Zimmerman, Daniel Podolsky, Ronen Rapaport, Snir Gazit

Recent experiments on trilayer transition-metal dichalcogenide heterostructures have revealed the rich behavior of dipolar excitons. Motivated by these experimental observations, we investigate the collective dynamics of planar quantum dipoles whose orientation fluctuates due to charge tunneling between the outer layers. Using large-scale quantum Monte Carlo

Samuel Cupp, Leonardo R. Werneck, Terrence Pierre Jacques, Samuel Tootle

Interpreting multimessenger signals from neutron stars and black holes requires reliable general relativistic magnetohydrodynamics (GRMHD) simulations across rapidly evolving high-performance computing platforms, yet key algorithms are routinely rewritten within infrastructure-specific numerical relativity codes, hindering verification and reuse. We present

Rebecca Bisset, Luke C. Rhodes, Hugo Decitre, Matthew J. Neat

Superconductivity, a state in which electrical currents can flow without resistance, occurs because of pairing of electrons into quasiparticles with integer spin $S$. In practically all known superconducting materials, these pairs form a singlet with $S=0$. Finding a material that has triplet pairing, $S=1$, would have profound fundamental and technological

Frances E. Rigby, Nikku Madhusudhan, Subhajit Sarkar, Lorenzo Pica-Ciamarra

In recent years, JWST has facilitated detections of carbon-bearing molecules in the atmospheres of temperate sub-Neptunes orbiting M dwarfs, ushering in a new era in the characterization of this intriguing planetary regime. We report the transmission spectrum of the temperate sub-Neptune TOI-732 c, observed with JWST NIRISS, NIRSpec G395H and MIRI LRS betwee

Jinjing Zhao, Fangyun Wei, Zhening Liu, Hongyang Zhang

Existing video generation models struggle to maintain long-term spatial and temporal consistency due to the dense, high-dimensional nature of video signals. To overcome this limitation, we propose Spatia, a spatial memory-aware video generation framework that explicitly preserves a 3D scene point cloud as persistent spatial memory. Spatia iteratively generat

Lihe Yang, Shang-Wen Li, Yang Li, Xinjie Lei

At the most basic level, pixels are the source of the visual information through which we perceive the world. Pixels contain information at all levels, ranging from low-level attributes to high-level concepts. Autoencoders represent a classical and long-standing paradigm for learning representations from pixels or other raw inputs. In this work, we demonstra

Tizian Blatz, Sebastian Paeckel, Ulrich Schollwöck, Fabian Grusdt

Spin-charge stripes belong to the most prominent low-temperature orders besides superconductivity in high-temperature superconductors. This phase is particularly challenging to study numerically due to finite-size effects. By investigating the formation of long, isolated stripes, we offer a perspective complementary to typical finite-doping phase diagrams. W

Lunbin Zeng, Jingfeng Yao, Bencheng Liao, Hongyuan Tao

Diffusion-based decoding has recently emerged as an appealing alternative to autoregressive (AR) generation, offering the potential to update multiple tokens in parallel and reduce latency. However, diffusion vision language models (dVLMs) still lag significantly behind mainstream autoregressive vision language models. This is due to the scarcity and weaker

Vincent Huang, Dami Choi, Daniel D. Johnson, Sarah Schwettmann

Interpreting the internal activations of neural networks can produce more faithful explanations of their behavior, but is difficult due to the complex structure of activation space. Existing approaches to scalable interpretability use hand-designed agents that make and test hypotheses about how internal activations relate to external behavior. We propose to

Divam Gupta, Anuj Pahuja, Nemanja Bartolovic, Tomas Simon

We present Gaussian Pixel Codec Avatars (GPiCA), photorealistic head avatars that can be generated from multi-view images and efficiently rendered on mobile devices. GPiCA utilizes a unique hybrid representation that combines a triangle mesh and anisotropic 3D Gaussians. This combination maximizes memory and rendering efficiency while maintaining a photoreal

Shuai Liu, Yiqing Tian, Yang Chen, Mar Canet Sola

This paper proposes a dual-engine AI architectural method designed to address the complex problem of exploring potential trajectories in the evolution of art. We present two interconnected components: AIDA (an artificial artist social network) and the Ismism Machine, a system for critical analysis. The core innovation lies in leveraging deep learning and mul

Andrés Chirre, Harald Andrés Helfgott

Let $A(s) = \sum_n a_n n^{-s}$ be a Dirichlet series admitting meromorphic continuation to the complex plane. Assume we know the location of the poles of $A(s)$ with $|\Im s| \leq T$, and their residues, for some large constant $T$. It is natural to ask how such finite spectral information may be best used to estimate partial sums $\sum_{n\leq x} a_n$. Here,

Leo Segre, Or Hirschorn, Shai Avidan

Foundation models are vital tools in various Computer Vision applications. They take as input a single RGB image and output a deep feature representation that is useful for various applications. However, in case we have multiple views of the same 3D scene, they operate on each image independently and do not always produce consistent features for the same 3D

Yu Wang, Juhyung Ha, Frangil M. Ramirez, Yuchen Wang

Active Speaker Detection (ASD) aims to identify who is currently speaking in each frame of a video. Most state-of-the-art approaches rely on late fusion to combine visual and audio features, but late fusion often fails to capture fine-grained cross-modal interactions, which can be critical for robust performance in unconstrained scenarios. In this paper, we

Kayode Olumoyin, Lamees El Naqa, Katarzyna Rejniak

In a mathematical model of interacting biological organisms, where external interventions may alter behavior over time, traditional models that assume fixed parameters usually do not capture the evolving dynamics. In oncology, this is further exacerbated by the fact that experimental data are often sparse and sometimes are composed of a few time points of tu

Xuting Liu, Daniel Alexander, Siva Kesava Reddy Kakarla, Behnaz Arzani

Early-Exit (EE) is a Large Language Model (LLM) architecture that accelerates inference by allowing easier tokens to be generated using only a subset of the model's layers. However, traditional batching frameworks are ill-suited for EE LLMs, as not all requests in a batch may be ready to exit at the same time. Existing solutions either force a uniform decisi

Erika Ye, Chao Yang

Quantized tensor trains (QTTs) are a low-rank and multiscale framework that allows for efficient approximation and manipulation of multi-dimensional, high resolution data. One area of active research is their use in numerical simulation of hyperbolic systems such as the Navier-Stokes equations and the Vlasov equations. One popular time integration scheme is

Kyle Sargent, Ruiqi Gao, Philipp Henzler, Charles Herrmann

Evaluations of image compression performance which include human preferences have generally found that naive distortion functions such as MSE are insufficiently aligned to human perception. In order to align compression models to human perception, prior work has employed differentiable perceptual losses consisting of neural networks calibrated on large-scale

Qiuyang Mang, Wenhao Chai, Zhifei Li, Huanzhi Mao

We introduce FrontierCS, a benchmark of 156 open-ended problems across diverse areas of computer science, designed and reviewed by experts, including CS PhDs and top-tier competitive programming participants and problem setters. Unlike existing benchmarks that focus on tasks with known optimal solutions, FrontierCS targets problems where the optimal solution

Alberto Brollo, Dennis le Plat, Alessandro Sfondrini

We revisit the numerical solution of the mirror TBA equations for pure--Ramond-Ramond strings on $AdS_3\times S^3\times T^4$ in the tensionless limit. Our analysis uses the recently-proposed modification of the dressing factors which account for non-trivial exchange relations of the massless modes. At leading order in the tension, the dynamics is driven by t

L. N. Fletcher, Z. Zhang, S. Brown, F. A. Oyafuso

Sprawling, turbulent cloud formations dominate the meteorology of Jupiter's mid-to-high latitudes, known as Folded Filamentary Regions (FFRs). A multi-wavelength characterisation by Juno reveals the spatial distribution, vertical structure, and energetics of the FFRs. The cloud tops display multiple lobes of stratiform aerosols, separated by darker, cloud-fr

Dimitrios Kranas, Andleeb Zahra, Friedrich König

The optical fiber is a revolutionary technology of the past century. It enables us to manipulate single modes in nonlinear interactions with precision at the quantum level without involved setups. This setting is useful in the field of analogue gravity (AG), where gravitational phenomena are investigated in accessible analogue lab setups. These lecture notes

Reinis Irmejs, J. Ignacio Cirac

Efficient simulation of interacting fermionic systems is a key application of near-term quantum computers, but is hindered by the overhead required to encode fermionic operators on qubit hardware. Here, we consider models with $N$ fermionic modes in which each participates in at most a constant number $d$ of interactions and study the circuit depth required

Orkun Furat, Vinay Chakravarthi Gogineni, Henrik Bindslev, Esmaeil S. Nadimi

Metasurfaces, typically realized as arrays of nanopillars, transform electromagnetic (EM) fields depending on their geometry and spatial arrangement. For solving the inverse problem of designing new metasurfaces that transform EM fields in a desirable manner, it is often necessary to explore large design spaces through full-wave simulations that can be compu