December 2024 arXiv papers — page 197

Valerio De Luca, Justin Khoury, Sam S. C. Wong

In general relativity, gravitational memory describes the lasting change in the separation and relative velocity of freely falling detectors after the passage of gravitational waves (GWs). In this paper, we elucidate the relation between Bondi-Metzner-Sachs transformations at future null infinity and the description of gravitational memory in local synchrono

Yasemin Karacora, Christina Chaccour, Aydin Sezgin, Walid Saad

As mission- and safety-critical wireless applications grow in complexity and diversity, next-generation wireless systems must meet increasingly stringent and multifaceted requirements. These systems demand resilience along with enhanced intelligence and adaptability to ensure reliable communication under diverse conditions. This paper proposes an event-based

Dimitrios Psaltis, Feryal Ozel, Yassine Ben Zineb

Increasing the angular resolution of an interferometric array requires placing its elements at large separations. This often leads to sparse coverage and introduces challenges to reconstructing images from interferometric data. We introduce a new interferometric imaging algorithm, KRISP, that is based on kernel methods, is statistically robust, and is agnost

Steffen Gielen, Rita B. Neves

We study the quantum dynamics of de Sitter space formulated as a minisuperspace model with flat spatial hypersurfaces in unimodular gravity, both in the Wheeler-DeWitt approach and in loop quantum cosmology (LQC). Time evolution is defined naturally in unimodular time, which appears as conjugate to the cosmological (integration) constant. We show that requir

Shikhar Asthana, Girish Kulkarni, Martin G. Haehnelt, James S. Bolton

Recent JWST observations have allowed for the first time to obtain comprehensive measurements of the ionizing photon production efficiency $\xi_\text{ion} $ for a wide range of reionization-epoch galaxies. We explore implications for the inferred UV luminosity functions and escape fractions of ionizing sources in our suite of simulations. These are run with

Adrián López-Raven

We study correlation functions of baryon and determinant operators for the chiral algebras obtained from the twist of N = 4 SYM with U(N) gauge group. In the context of Twisted Holography, we conjecture that a dual description should involve a D1-D5 brane system, and we construct from the correlators a candidate dual brane in the form of a derived coherent s

Yassine Ben Zineb, Feryal Ozel, Dimitrios Psaltis

Horizon-scale imaging with the Event Horizon Telescope (EHT) has provided transformative insights into supermassive black holes but its resolution and scope are limited by ground-based constraints such as the size of the Earth, its relatively slow rotation, and atmospheric delays. Space-based very long baseline interferometry (VLBI) offers the capability for

Josh Kirklin

We prove that the generalised second law (GSL), with an appropriate modification, holds in perturbative gravity to all orders beyond the semiclassical limit and without a UV cutoff imposed on the fields. Our proof uses algebraic techniques and builds on the recent work of Faulkner and Speranza, which combined Wall's proof of the GSL with the identification o

Erick Arguello Cruz, Grigory Tarnopolsky, Yuan Xin

We perform a numerical analysis of the massive Schwinger model in the presence of a background electric field. Using the Density Matrix Renormalization Group (DMRG) approach, we efficiently compute the spectrum of the Schwinger model on a staggered lattice with up to 3000 qubits. As a result, we achieve a precise computation of the critical mass of the massi

Maria Luisa Buzzo, Duncan A. Forbes, Thomas H. Jarrett, Francine R. Marleau

This study compiles stellar populations and internal properties of ultra-diffuse galaxies (UDGs) to highlight correlations with their local environment, globular cluster (GC) richness, and star formation histories. Complementing our sample of 88 UDGs, we include 36 low-surface brightness dwarf galaxies with UDG-like properties, referred to as NUDGes (nearly-

Debsubhra Chakraborty, Dhruv Sood, Archana Radhakrishnan, Nilmani Mathur

We present an efficient method for extracting energy levels from lattice QCD correlation functions by computing the eigenvalues of the transfer matrix associated with the lattice QCD Hamiltonian. While mathematically and numerically equivalent to the recently introduced Lanczos procedure, our approach introduces a novel prescription for removing spurious eig

Mikel Falxa, Hippolyte Quelquejay Leclere, Alberto Sesana

A large population of binary systems in the Universe emitting gravitational waves (GW) would produce a stochastic noise, known as the gravitational wave background (GWB). The properties of the GWB directly depend on the attributes of its constituents. If the binary systems are in eccentric orbits, it is well established that the GW power they radiate strongl

J. François, L. Ravera

We re-construe unconventional supersymmetry, a notion introduced by Alvarez-Valenzuela-Zanelli (AVZ), as an attempt to use the framework of supersymmetric field theory to describe fermionic matter fields and bosonic gauge fields in a unified way, as parts of a single superconnection. It hinges upon the so-called matter ansatz. Unfortunately, the formal and c

Miguel Gallego

Quantum mechanics is formulated on a Hilbert space that is assumed to be separable. However, there seems to be no clear reason justifying this assumption. Does it have physical implications? We answer in the positive by proposing a test that witnesses the non-separability of the Hilbert space, at the expense of requiring measurements with uncountably many ou

Luca Lumia, Gianni Aupetit-Diallo, Jérôme Dubail, Mario Collura

Unitary integrable models typically relax to a stationary Generalized Gibbs Ensemble (GGE), but in experimental realizations dissipation often breaks integrability. In this work, we use the recently introduced time-dependent GGE (t-GGE) approach to describe the open dynamics of a gas of bosons subject to atom losses and gains. We employ tensor network method

Andrew D. Sellek, Marissa Vlasblom, Ewine F. van Dishoeck

MIR spectra imply considerable chemical diversity in the inner regions of protoplanetary discs: some are H2O-dominated, others by CO2. Sublimating ices from radially drifting dust grains are often invoked to explain some of this diversity, particularly the H2O-rich discs. We use a 1D protoplanetary disc evolution code to model how radially drifting dust grai

Fu-Ming Chang, He-Yu Gao, Víctor Jaramillo, Xin Meng

Superradiance, the process by which waves are amplified through energy and angular momentum transfer, can also occur in horizonless objects like boson stars, due to both the real space and internal field space rotations. In this work, we study superradiance in the frequency and time domains for static and spinning boson stars, constructed within general rela

Thorbjørn Clausen, Charles L. Steinhardt, Arden Shao, Gaurav Senthil Kumar

The James Webb Space Telescope (JWST) has enabled the discovery of a significant population of galaxies at z > 10. Our understanding of the astrophysical properties of these galaxies relies on fitting templates developed using models predicting the differences between these first galaxies and lower-redshift counterparts. In this work, tests are performed on

Clelia Altomonte, Alan J. Barr, Michał Eckstein, Paweł Horodecki

In quantum information theory, the evolution of an open quantum system -- a unitary evolution followed by a measurement -- is described by a quantum channel or, more generally, a quantum instrument. In this work, we formulate spin and flavour measurements in collider experiments as quantum instruments. We demonstrate that the Choi matrix, which completely de

Javier Huenupi, Ellie Hughes, Gonzalo A. Palma, Spyros Sypsas

We analyze the computation of $n$-point correlation functions in de Sitter spacetime, including loop corrections, using the wavefunction of the universe approach. This method consists of two stages employing distinct Feynman rules. First, one must compute the wavefunction coefficients using interactions as vertices. Then, in the second stage, one computes co

Ian Holst, Gordan Krnjaic, Huangyu Xiao

If primordial black holes (PBH) are present in the early universe, their contribution to the energy budget grows relative to that of radiation and generically becomes dominant unless the initial abundance is exponentially small. This black hole domination scenario is largely unconstrained for PBHs with masses $\lesssim 10^9\,\mathrm{g}$, which evaporate prio

Miguel Murça, Paul K. Faehrmann, Yasser Omar

We introduce and investigate a data access model (approximate sample and query) that is satisfiable by the preparation and measurement of block encoded states, as well as in contexts such as classical quantum circuit simulation or Pauli sampling. We illustrate that this abstraction is compositional and has some computational power. We then apply these result

Mikhail M. Ivanov, Carolina Cuesta-Lazaro, Andrej Obuljen, Michael W. Toomey

Cosmological analyses of redshift space clustering data are primarily based on using luminous ``red'' galaxies (LRGs) and ``blue'' emission line galaxies (ELGs) to trace underlying dark matter. Using the large high-fidelity high-resolution MillenniumTNG (MTNG) and Astrid simulations, we study these galaxies with the effective field theory (EFT)-based field l

Guillermo Barro, Pablo G. Perez-Gonzalez, Dale D. Kocevski, Elizabeth J. McGrath

JWST has revealed a population of compact `Little Red Dots' (LRDs) at $z\gtrsim4$, with red rest-frame optical and blue UV colors. These objects are likely compact dusty starbursts or heavily reddened AGNs, playing a pivotal role in early black hole growth, dust production, and stellar assembly. We introduce a new photometric selection to identify LRDs over

Ryohei Kobayashi, Yuyang Li, Hanyu Xue, Po-Shen Hsin

The statistics of particles and extended excitations, such as loops and membranes, are fundamental to modern condensed matter physics, high-energy physics, and quantum information science, yet a comprehensive lattice-level framework for computing them remains elusive. In this work, we develop a universal microscopic method to determine the generalized statis

Iosif Bena, Raphaël Dulac, Pierre Heidmann, Zixia Wei

We construct asymptotically AdS$_3 \times$S$^3 \times$T$^4$ black holes that are localized on the S$^3$ and co-exist with the BTZ black hole at small positive energies. These black holes dominate the microcanonical ensemble for $ E\leq \frac{c}{24}\left(5\sqrt{5}-11\right)$, suggesting they could represent the endpoint of the BTZ instability at low energies.

Mircea Bejan, Benjamin Béri, Max McGinley

We study the ensemble of states generated by performing projective measurements on the output of a random matchgate (or free-fermionic) quantum circuit. We rigorously show that this `projected ensemble' exhibits deep thermalization: For large system sizes, it converges towards a universal ensemble that is uniform over the manifold of Gaussian fermionic state

Adam Yanis Chaou, Mateo Moreno-Gonzalez, Alexander Altland, Piet W. Brouwer

The imposition of crystalline symmetries is known to lead to a rich variety of insulating and superconducting topological phases. These include higher-order topological phases and obstructed atomic limits with and without filling anomalies. We here comprehensively classify such topological crystalline phases (TCPs) with mirror, twofold rotation, and inversio

T. Ak, R. Canbay, T. Yontan

UBV CCD observations of standard stars selected from Landolt (2009, 2013) were performed using the 1-meter telescope (T100) of the T\"{U}B\.{I}TAK National Observatory equipped with a back-illuminated and UV enhanced CCD camera and Bessell UBV filters. Observations span a long time from the years 2012 to 2024, 50 photometric nights in total. Photometric meas

M A. M. Smith, Vasileios Paschalidis, Gabriele Bozzola

In a previous paper, arXiv:2411.11960 [gr-qc], we initiated a study of high-energy interactions of charged binary black holes near the scattering threshold, focusing on zoom-whirl orbits. In this second paper in our series, we focus on merger remnant properties and energetics with new simulations of equal-mass, equal-charge, nonspinning binary black holes wi

Tao Zhou, Ryan Plestid, Kevin J. Kelly, Nikita Blinov

We simulate dark-vector, $V$, production from electromagnetic cascades at the recently approved SHiP experiment. The cascades (initiated by photons from $\pi^0\rightarrow \gamma \gamma$) can lead to 3-4 orders of magnitude increase of the event rate relative to using primary production alone. We provide new SHiP sensitivity projections for dark photons and e

Tereza Constantinou, Oliver Shorttle, Paul B. Rimmer

Venus's climatic history provides powerful constraint on the location of the inner-edge of the liquid-water habitable zone. However, two very different histories of water on Venus have been proposed: one where Venus had a temperate climate for billions of years, with surface liquid water, and the other where a hot early Venus was never able to condense surfa

Benjamin C. Kaiser, J. Christopher Clemens, Simon Blouin, Erik Dennihy

The bulk abundances of exoplanetesimals can be measured when they are accreted by white dwarfs. Recently, lithium from the accretion of exoplanetesimals was detected in relatively high levels in multiple white dwarfs. There are presently three proposed hypotheses to explain the detection of excess lithium in white dwarf photospheres: Big Bang and Galactic nu

Clay Cordova, Diego García-Sepúlveda

The coset construction of two-dimensional conformal field theory (2D CFT) defines a 2D CFT by taking the quotient of two previously known chiral algebras. In this work, we use the methods of non-abelian (non-invertible) anyon condensation to describe 2D topological cosets, defined by the special case where the quotient of chiral algebras is a conformal embed

Jonathan C. Tan, Jasbir Singh, Vieri Cammelli, Mahsa Sanati

The origin of supermassive black holes (SMBHs) is a key open question for contemporary astrophysics and cosmology. Here we review the features of a cosmological model of SMBH formation from Pop III.1 seeds, i.e., remnants of metal-free stars forming in locally-isolated minihalos, where energy injection from dark matter particle annihilation alters the struct

Ziqi Pang, Tianyuan Zhang, Fujun Luan, Yunze Man

We introduce RandAR, a decoder-only visual autoregressive (AR) model capable of generating images in arbitrary token orders. Unlike previous decoder-only AR models that rely on a predefined generation order, RandAR removes this inductive bias, unlocking new capabilities in decoder-only generation. Our essential design enables random order by inserting a "pos

Savya Khosla, Sethuraman T, Alexander Schwing, Derek Hoiem

We present RELOCATE, a simple training-free baseline designed to perform the challenging task of visual query localization in long videos. To eliminate the need for task-specific training and efficiently handle long videos, RELOCATE leverages a region-based representation derived from pretrained vision models. At a high level, it follows the classic object l

Ciprian-Octavian Truică, Elena-Simona Apostol, Marius Marogel, Adrian Paschke

In today's digital age, fake news has become a major problem that has serious consequences, ranging from social unrest to political upheaval. To address this issue, new methods for detecting and mitigating fake news are required. In this work, we propose to incorporate contextual and network-aware features into the detection process. This involves analyzing

Zeyi Sun, Ziyang Chu, Pan Zhang, Tong Wu

In-context generation is a key component of large language models' (LLMs) open-task generalization capability. By leveraging a few examples as context, LLMs can perform both in-domain and out-of-domain tasks. Recent advancements in auto-regressive vision-language models (VLMs) built upon LLMs have showcased impressive performance in text-to-image generation.

Yunzhou Song, Heguang Lin, Jiahui Lei, Lingjie Liu

Recent advancements in neural rendering, particularly 2D Gaussian Splatting (2DGS), have shown promising results for jointly reconstructing fine appearance and geometry by leveraging 2D Gaussian surfels. However, current methods face significant challenges when rendering at arbitrary viewpoints, such as anti-aliasing for down-sampled rendering, and texture d

Byung-Kwan Lee, Ryo Hachiuma, Yu-Chiang Frank Wang, Yong Man Ro

The recent surge in high-quality visual instruction tuning samples from closed-source vision-language models (VLMs) such as GPT-4V has accelerated the release of open-source VLMs across various model sizes. However, scaling VLMs to improve performance using larger models brings significant computational challenges, especially for deployment on resource-const

Qihang Zhang, Shuangfei Zhai, Miguel Angel Bautista, Kevin Miao

Recent advancements in diffusion models have set new benchmarks in image and video generation, enabling realistic visual synthesis across single- and multi-frame contexts. However, these models still struggle with efficiently and explicitly generating 3D-consistent content. To address this, we propose World-consistent Video Diffusion (WVD), a novel framework

Jiayuan Rao, Haoning Wu, Hao Jiang, Ya Zhang

As a globally celebrated sport, soccer has attracted widespread interest from fans all over the world. This paper aims to develop a comprehensive multi-modal framework for soccer video understanding. Specifically, we make the following contributions in this paper: (i) we introduce SoccerReplay-1988, the largest multi-modal soccer dataset to date, featuring v

Anton Voronov, Denis Kuznedelev, Mikhail Khoroshikh, Valentin Khrulkov

This work presents Switti, a scale-wise transformer for text-to-image generation. We start by adapting an existing next-scale prediction autoregressive (AR) architecture to T2I generation, investigating and mitigating training stability issues in the process. Next, we argue that scale-wise transformers do not require causality and propose a non-causal counte

Qizhe Zhang, Aosong Cheng, Ming Lu, Renrui Zhang

Large vision-language models (LVLMs) generally contain significantly more visual tokens than their textual counterparts, resulting in a considerable computational burden. Recent efforts have been made to tackle this issue by pruning visual tokens early within the language model. Most existing works use attention scores between text and visual tokens to asses

Matin Mortaheb, Mohammad A. Amir Khojastepour, Sennur Ulukus

Transformers, known for their attention mechanisms, have proven highly effective in focusing on critical elements within complex data. This feature can effectively be used to address the time-varying channels in wireless communication systems. In this work, we introduce a channel-aware adaptive framework for semantic communication, where different regions of

Boya Zeng, Yida Yin, Zhuang Liu

A recent study has shown that large-scale visual datasets are very biased: they can be easily classified by modern neural networks. However, the concrete forms of bias among these datasets remain unclear. In this study, we propose a framework to identify the unique visual attributes distinguishing these datasets. Our approach applies various transformations

John Schultz, Jakub Adamek, Matej Jusup, Marc Lanctot

Advancing planning and reasoning capabilities of Large Language Models (LLMs) is one of the key prerequisites towards unlocking their potential for performing reliably in complex and impactful domains. In this paper, we aim to demonstrate this across board games (Chess, Fischer Random / Chess960, Connect Four, and Hex), and we show that search-based planning

William G. Bass, Jack S. Calcut

Ends and end cohomology are powerful invariants for the study of noncompact spaces. We present a self-contained exposition of the topological theory of ends and prove novel extensions including the existence of an exhaustion of a proper map. We define reduced end cohomology as the relative end cohomology of a ray-based space. We use those results to prove a

Dinghan Wang

In this paper, we construct finite-time type-II blow-up solutions for the focusing energy-critical wave equation with an inverse-square potential $$\partial_t^2 u-\Delta u+\frac{\alpha}{|x|^2}u = u^5,$$ with discussions of the influence of the potential being made. The key ingredients include an approxiamte construction of solutions and spectral analysis of

Sanghwan Kim, Rui Xiao, Mariana-Iuliana Georgescu, Stephan Alaniz

Vision-Language Models (VLMs) trained with contrastive loss have achieved significant advancements in various vision and language tasks. However, the global nature of the contrastive loss makes VLMs focus predominantly on foreground objects, neglecting other crucial information in the image, which limits their effectiveness in downstream tasks. To address th

Alexandros Maragkoudakis, Christiaan Boersma, Pasquale Temi, Jesse D. Bregman

We have conducted a sensitivity analysis on the mid-infrared spectral decomposition of galaxies and the modeling of the PAH emission spectrum with the NASA Ames PAH Infrared Spectroscopic Database (PAHdb) to assess the variance on the average galaxy PAH population properties under a grid of different modeling parameters. We find that the SL and SL+LL Spitzer

Michael Novack, Daniel Restrepo, Anna Skorobogatova

We study a class of semilinear free boundary problems in which admissible functions $u$ have a topological constraint, or spanning condition, on their 1-level set. This constraint forces $\{u=1\}$, which is the free boundary, to behave like a surface with some special types of singularities attached to a fixed boundary frame, in the spirit of the Plateau pro

Zewei Zhou, Hao Xiang, Zhaoliang Zheng, Seth Z. Zhao

Vehicle-to-everything (V2X) technologies offer a promising paradigm to mitigate the limitations of constrained observability in single-vehicle systems. Prior work primarily focuses on single-frame cooperative perception, which fuses agents' information across different spatial locations but ignores temporal cues and temporal tasks (e.g., temporal perception

Joaquín Moraga, Wern Yeong

Let $X$ be a $n$-dimensional smooth projective variety and $L$ be an ample Cartier divisor on $X$. We conjecture that a very general element of the linear system $|K_X+(3n+1)L|$ is a hyperbolic algebraic variety. This conjecture holds for some classical varieties: surfaces, products of projective spaces, and Grassmannians. In this article, we investigate the

Ashwat Jain, Wojciech J. Jankowski, Robert-Jan Slager

We investigate Riemannian quantum-geometric structures in semiclassical transport features of two-dimensional multigap topological phases. In particular, we study nonlinear Hall-like bulk electric current responses and, accordingly, semiclassical equations of motion induced by the presence of a topological Euler invariant. We provide analytic understanding o

Uktamjon Uktamov, Mirzabek Alloqulov, Sanjar Shaymatov, Tao Zhu

In this paper, we study the motion of magnetic dipoles and electrically charged particles in the vicinity of a self-dual black hole in Loop Quantum Gravity (LQG) immersed in an external asymptotically uniform magnetic field. We explore the effects of the quantum correction parameter and electromagnetic interactions on the particle geodesics. We derive the fi

Joseph Lap, Berndt Mueller, Andreas Schaefer, Clemens Seidl

We elaborate on the method introduced in arXiv:2403.02165 for holographic duals of Boundary Conformal Field Theories (BCFTs) with multiple boundaries. Using these advances we calculate the entanglement entropy as a function of time for 1+1-dimensional CFTs that are split into $N$ subsystems. We give explicit results for $N = 4$ and $N = 17$. We find that all

Jiahuan Cheng, Jan-Nico Zaech, Luc Van Gool, Danda Pani Paudel

TL;DR: Gaussian Splatting is a widely adopted approach for 3D scene representation, offering efficient, high-quality reconstruction and rendering. A key reason for its success is the simplicity of representing scenes with sets of Gaussians, making it interpretable and adaptable. To enhance understanding beyond visual representation, recent approaches extend

Weishun Zhong, Tankut Can, Antonis Georgiou, Ilya Shnayderman

Traditional studies of memory for meaningful narratives focus on specific stories and their semantic structures but do not address common quantitative features of recall across different narratives. We introduce a statistical ensemble of random trees to represent narratives as hierarchies of key points, where each node is a compressed representation of its d

Julia Liebert, Federico Castillo, Jean-Philippe Labbé, Tomasz Maciazek

The Pauli exclusion principle is fundamental to understanding electronic quantum systems. It namely constrains the expected occupancies $n_i$ of orbitals $\varphi_i$ according to $0 \leq n_i \leq 2$. In this work, we first refine the underlying one-body $N$-representability problem by taking into account simultaneously spin symmetries and a potential degree

Hjalte Frellesvig

In this paper, we discuss the Baikov representation of Feynman integrals in its standard and loop-by-loop variants. The Baikov representation is a parametric representation, which has as its defining feature the fact that the integration variables are the propagators of the Feynman integral. For the loop-by-loop Baikov representation, we discuss in detail a

Steven Charlton, Anna Medvedovsky, Pieter Moree

The Euler-Kronecker constants related to congruences of Fourier coefficients of modular forms that have been computed so far, involve logarithmic derivatives of Dirichlet $L$-series as most complicated functions (to the best of our knowledge). However, generically the more complicated Artin $L$-series will make their appearance. Here we work out some simple

Jesse Thorner, Zhuo Zhang

We unconditionally improve the uniformity in the Chebotarev density theorem for Galois extensions of number fields using nonabelian base change. This leads to the first theoretical improvement over Weiss's bound for the least norm of an unramified prime ideal with given Artin symbol.

Alexey Bokhovkin, Quan Meng, Shubham Tulsiani, Angela Dai

We present SceneFactor, a diffusion-based approach for large-scale 3D scene generation that enables controllable generation and effortless editing. SceneFactor enables text-guided 3D scene synthesis through our factored diffusion formulation, leveraging latent semantic and geometric manifolds for generation of arbitrary-sized 3D scenes. While text input enab

Meng Cao, Haoran Tang, Haoze Zhao, Hangyu Guo

Recent advancements in video-based large language models (Video LLMs) have witnessed the emergence of diverse capabilities to reason and interpret dynamic visual content. Among them, gameplay videos stand out as a distinctive data source, often containing glitches that defy physics commonsense. This characteristic renders them an effective benchmark for asse

Beomchang Kim, Zongqi Xia, Priyam Das

Treatment switching is a common occurrence in the management of Multiple Sclerosis (MS), where patients transition across various disease-modifying therapies (DMTs) due to heterogeneous treatment responses, differences in disease progression, patient characteristics, and therapy-associated adverse effects. To investigate how patient-level covariates influenc

Jacky Kwok, Shulu Li, Marten Lohstroh, Edward A. Lee

The rise of intelligent autonomous systems, especially in robotics and autonomous agents, has created a critical need for robust communication middleware that can ensure real-time processing of extensive sensor data. Current robotics middleware like Robot Operating System (ROS) 2 faces challenges with nondeterminism and high communication latency when dealin

Lan Wang, Yujia Chen, Du Tran, Vishnu Naresh Boddeti

Long video understanding presents challenges due to the inherent high computational complexity and redundant temporal information. An effective representation for long videos must efficiently process such redundancy while preserving essential contents for downstream tasks. This paper introduces SEmantic Attention Learning (SEAL), a novel unified representati

Michael M. Shara, Kenneth M. Lanzetta, Alexandra Masegian, James T. Garland

A century or less separates the thermonuclear-powered eruptions of recurrent novae in the hydrogen-rich envelopes of massive white dwarfs. The colliding ejecta of successive recurrent nova events are predicted to always generate very large (tens of parsecs) super-remnants; only two examples are currently known. T CrB offers an excellent opportunity to test t

A. Mallet, S. Eriksson, M. Swisdak, J. Juno

We analyse the collisionless tearing mode instability of a current sheet with a strong shear flow across the layer. The growth rate decreases with increasing shear flow, and is completely stabilized as the shear flow becomes Alfv\'enic. We also show that in the presence of strong flow shear, the tearing mode growth rate decreases with increasing background i

E. Vardoulaki, V. Backöfer, A. Finoguenov, F. Vazza

We studied bent radio sources within X-ray galaxy groups in the COSMOS and XMM-LSS fields, using radio data from the MeerKAT International GHz Tiered Extragalactic Explorations data release 1 (MIGHTEE-DR1) at 1.2-1.3 GHz (angular resolutions of 8.9" and 5"; <rms> ~ 3.5 and 5.5 uJy/beam). Bent radio active galactic nuclei (AGN) were identified via visual insp

Khaled Abud, Sergey Lavrushkin, Alexey Kirillov, Dmitriy Vatolin

Diffusion-based models have recently revolutionized image generation, achieving unprecedented levels of fidelity. However, consistent generation of high-quality images remains challenging partly due to the lack of conditioning mechanisms for perceptual quality. In this work, we propose methods to integrate image quality assessment (IQA) models into diffusion

Changshun Hou, Ziwei Zhai, Nilotpal Choudhury, Tom Harris

A thulium-doped fiber laser operating quasi-continuous-wave generated 198 W of instantaneous output power in 0.2-ms pulses at 50 Hz repetition rate. The duty cycle becomes 1% and the average output power 2.0 W. This was cladding-pumped with 408 W from 0.79-um diode lasers (average pump power 4.1 W). The pump switch-on time was ~10 us at full power, with the

Kai He, Chin-Hsuan Wu, Igor Gilitschenski

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D scenes remains a significant challenge. Previous work is largely constrained by its editing backbones, resulting in incon

Fabian Hervas Peters, Martin Kilbinger, Romain Paviot, Lucie Baumont

During their formation, galaxies are subject to tidal forces, which create correlations between their shapes and the large-scale structure of the Universe, known as intrinsic alignment. This alignment is a contamination for cosmic-shear measurements as one needs to disentangle correlations induced by external lensing effects from those intrinsically present

Jie Zhang, Min-Te Sun

Recent advancements in Spectral Graph Convolutional Networks (SpecGCNs) have led to state-of-the-art performance in various graph representation learning tasks. To exploit the potential of SpecGCNs, we analyze corresponding graph filters via polynomial interpolation, the cornerstone of graph signal processing. Different polynomial bases, such as Bernstein, C

Laura Andrianopoli, Giuseppe Casale, Lucrezia Ravera, Alberto Santambrogio

We explore the properties of a set of free double-tensor multiplets in $N=2$ supersymmetry, focusing on their behavior within rigid superspace. These multiplets can be obtained from hypermultiplets by Hodge-dualizing half of their scalars, and feature an off-shell matching of bosonic and fermionic degrees of freedom. Despite this fact, the supersymmetry alge

Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari

Generative models that satisfy hard constraints are critical in many scientific and engineering applications, where physical laws or system requirements must be strictly respected. Many existing constrained generative models, especially those developed for computer vision, rely heavily on gradient information, which is often sparse or computationally expensi

Domenico Valloni

We study $p$-torsion Brauer classes in positive characteristic arising from differential forms. We relate this construction to the Brauer group of supersingular K3 surfaces and analyze the contribution of these classes to the Brauer-Manin obstruction. As an application, we examine the Brauer-Manin set of supersingular K3 surfaces and of varieties admitting m

Evan Xiang, Thomas Wang, Vivan Poddar

Sudden Cardiac Arrest (SCA) is the leading cause of death among athletes of all age levels worldwide. Current prescreening methods for cardiac risk factors are largely ineffective, and implementing the International Olympic Committee recommendation for 12-lead ECG screening remains prohibitively expensive. To address these challenges, a preliminary comprehen

Cameron Tice, Philipp Alexander Kreer, Nathan Helm-Burger, Prithviraj Singh Shahani

Capability evaluations play a crucial role in assessing and regulating frontier AI systems. The effectiveness of these evaluations faces a significant challenge: strategic underperformance, or ``sandbagging'', where models deliberately underperform during evaluation. Sandbagging can manifest either through explicit developer intervention or through unintende

Alireza Nadali, Bingzhuo Zhong, Ashutosh Trivedi, Majid Zamani

Transfer learning is an umbrella term for machine learning approaches that leverage knowledge gained from solving one problem (the source domain) to improve speed, efficiency, and data requirements in solving a different but related problem (the target domain). The performance of the transferred model in the target domain is typically measured via some notio

Young-Jin Park, Carson Sobolewski, Navid Azizan

DETR and its variants have emerged as promising architectures for object detection, offering an end-to-end prediction pipeline. In practice, however, DETRs generate hundreds of predictions that far outnumber the actual objects present in an image. This raises a critical question: which of these predictions could be trusted? This is particularly important for

Serena Gambino, Francesco Pace

We analyse the implications of the presence of spatial curvature in modified gravity models. As it is well known, the current standard cosmological model, the $\Lambda$CDM, is assumed to be spatially flat based on the results of many experiments. However, this statement does not necessarily hold for a modified gravity (MG) model, and this leads to couplings

Edna Jones

We develop a version of the Kloosterman circle method with a bump function that is used to provide asymptotics for weighted representation numbers of nonsingular integral quadratic forms. Unlike many applications of the Kloosterman circle method, we explicitly state some constants in the error terms that depend on the quadratic form. This version of the Kloo

Nathaniel Bottman, Katrin Wehrheim

We develop a robust functional analytic framework for adiabatic limits. This framework consist of a notion of adiabatic Fredholm family, several possible regularity properties, and an explicit construction that provides finite dimensional reductions that fit into all common regularization theories. We show that thhese finite dimensional reductions inherit gl

Lajos Muzsai, David Imolai, András Lukács

We introduce HackSynth, a novel Large Language Model (LLM)-based agent capable of autonomous penetration testing. HackSynth's dual-module architecture includes a Planner and a Summarizer, which enable it to generate commands and process feedback iteratively. To benchmark HackSynth, we propose two new Capture The Flag (CTF)-based benchmark sets utilizing the

Alberto Abbondandolo, Oliver Edtmair, Jungsoo Kang

We prove that every closed characteristic of minimal action on the boundary of a uniformly convex domain in $\R^4$ bounds a disk-like global surface of section. A corollary is that the cylindrical symplectic capacity of a convex body in $\R^4$ coincides with the minimal action of a closed generalized characteristic on its boundary.

Yu-Dong Nie, Yong Shao, Jian-Guo He, Ze-Lin Wei

We present detailed evolutionary simulations of wide binary systems with high-mass ($8-20\,M_{\odot}$) donor stars and a $1.4\,M_{\odot}$ neutron star. Mass transfer in such binaries is dynamically unstable and common envelope (CE) evolution is followed. We use a recently developed prescription to deal with CE evolution and consider various CE ejection effic

Alexandre Sac-Morane, Hadrien Rattez, Manolis Veveakis

Pressure-solution is a chemo-mechanical process, involving dissolution at grain/asperity contacts and precipitation away from them. It induces a compaction in time of rocks and sediments. The present study investigates numerically the impact of precipitation on the slowdown of creep behavior induced by pressure-solution. A recently published framework, calle

Sean Keel, Logan White

We give a canonical basis of theta functions for the Cox ring of two dimensional Looijenga pairs with affine interior, with structure constants naive counts of k-analytic disks in the total space of the universal deformation of the mirror (which, as this is dimension two, is isomorphic to the log Calabi-Yau surface itself)

Lisha Chen, AFM Saif, Yanning Shen, Tianyi Chen

Finding specific preference-guided Pareto solutions that represent different trade-offs among multiple objectives is critical yet challenging in multi-objective problems. Existing methods are restrictive in preference definitions and/or their theoretical guarantees. In this work, we introduce a Flexible framEwork for pREfeRence-guided multi-Objective learnin

Seou Choi, Yannick Salamin, Charles Roques-Carmes, Jamison Sloan

Quantum states at optical frequencies are often generated inside cavities to facilitate strong nonlinear interactions. However, measuring these quantum states with traditional homodyne techniques poses a challenge, as outcoupling from the cavity disturbs the state's quantum properties. Here, we propose a framework for reconstructing quantum states generated

Massimo Bianchi, Claudio Gambino, Paolo Pani, Fabio Riccioni

Working in momentum space and at linear order in the gravitational coupling, we derive the most general class of energy-momentum tensors associated with a given multipolar structure of the spacetime in arbitrary dimensions, and built out of a mass and an angular momentum, at any order in the spin expansion. In this formalism, we are able to derive directly t

Marcel Torne, Arhan Jain, Jiayi Yuan, Vidaaranya Macha

Scaling robot learning requires data collection pipelines that scale favorably with human effort. In this work, we propose Crowdsourcing and Amortizing Human Effort for Real-to-Sim-to-Real(CASHER), a pipeline for scaling up data collection and learning in simulation where the performance scales superlinearly with human effort. The key idea is to crowdsource

Wenting Zhao, Nan Jiang, Celine Lee, Justin T Chiu

With the goal of benchmarking generative systems beyond expert software development ability, we introduce Commit0, a benchmark that challenges AI agents to write libraries from scratch. Agents are provided with a specification document outlining the library's API as well as a suite of interactive unit tests, with the goal of producing an implementation of th

Peter Koymans, Carlo Pagano

For all infinite rings $R$ that are finitely generated over $\mathbb{Z}$, we show that Hilbert's tenth problem has a negative answer. This is accomplished by constructing elliptic curves $E$ without rank growth in certain quadratic extensions $L/K$. To achieve such a result unconditionally, our key innovation is to use elliptic curves $E$ with full rational

Samuel G. Leitch, Qasim Zeeshan Ahmed, Ben Van Herbruggen, Mathias Baert

One significant challenge in research is to collect a large amount of data and learn the underlying relationship between the input and the output variables. This paper outlines the process of collecting and validating a dataset designed to determine the angle of arrival (AoA) using Bluetooth low energy (BLE) technology. The data, collected in a laboratory se

Ashley J. Ruiter, Ivo R. Seitenzahl

Type Ia supernovae (SNe Ia) are runaway thermonuclear explosions in white dwarfs that result in the disruption of the white dwarf star, and possibly its nearby stellar companion. SNe Ia occur over an immense range of stellar population age and host galaxy environments, and play a critical role in the nucleosynthesis of intermediate-mass and iron-group elemen