November 2024 arXiv papers — page 114

Shovon Biswas, Julio Parra-Martinez

We revisit the calculation of classical observables from causal response functions, following up on recent work by Caron-Huot at al. [JHEP 01 (2024) 139]. We derive a formula to compute asymptotic in-in observables from a particular soft limit of five-point amputated response functions. Using such formula, we re-derive the formulas by Kosower, Maybee and O'C

Zachary Duah, Stian Du Preez, David Milan, Shreyas Ramamurthy

We investigate the use of labelled graphs as a Morita equivalence invariant for inverse semigroups. We construct a labelled graph from a combinatorial inverse semigroup $S$ with $0$ admitting a special set of idempotent $\mathcal{D}$-class representatives and show that $S$ is Morita equivalent to a labelled graph inverse semigroup. For the inverse hull $S$ o

R. A. Konoplya, Z. Stuchlík, A. Zhidenko

Unlike the perturbations of massless fields, the asymptotic tails of massive fields exhibit oscillations and decay slowly, following a power-law envelope. In this work, considering various scenarios admitting (either fundamental or effective) massive scalar and gravitational fields, we demonstrate that bump deformations in the effective potential, either in

Zhiqiang Miao, Zhenyu Zhu, Dong Lai

Quark stars are challenging to confirm or exclude observationally because they can have similar masses and radii as neutron stars. By performing the first calculation of the non-equilibrium equation of state of decompressed quark matter at finite temperature, we determine the properties of the ejecta from binary quark-star or quark star-black hole mergers. W

Tijmen de Haan, Yuan-Sen Ting, Tirthankar Ghosal, Tuan Dung Nguyen

AstroSage-Llama-3.1-8B is a domain-specialized natural-language AI assistant tailored for research in astronomy, astrophysics, cosmology, and astronomical instrumentation. Trained on the complete collection of astronomy-related arXiv papers from 2007 to 2024 along with millions of synthetically-generated question-answer pairs and other astronomical literatur

Yasuhiro Hasegawa, Riouhei Nakatani, Isabel Rebollido, Meredith MacGregor

Debris disks embrace the formation and evolution histories of planetary systems. Recent detections of gas in these disks have received considerable attention, as its origin ties up ongoing disk evolution and the present composition of planet-forming materials. Observations of the CO gas alone, however, cannot reliably differentiate between two leading, compe

Sayan Manna, Sushil K. Misra

It is shown theoretically how to use the EPR (Electron Paramagnetic Resonance) technique, using electron spins as qubits, coupled with each other by the exchange interaction, to set the configuration of n qubits (n=1,2,3,4) at resonance, in conjunction with pulses, to construct the NOT (one qubit), CNOT (two qubits), CCNOT (three qubits), CCCNOT (four qubits

Erik Wijmans, Brody Huval, Alexander Hertzberg, Vladlen Koltun

As language models grow ever larger, so do their vocabularies. This has shifted the memory footprint of LLMs during training disproportionately to one single layer: the cross-entropy in the loss computation. Cross-entropy builds up a logit matrix with entries for each pair of input tokens and vocabulary items and, for small models, consumes an order of magni

Alejandro Bravo-Doddoli, Philip Arathoon, Anthony M. Bloch

We analyse the geometry of the rubber-rolling distribution on the special orthogonal group and show that almost all the normal geodesics of any right-invariant sub-Riemannian metric defined on this distribution are completely integrable. Our argument is an adaptation of the method used to establish integrability of the Riemannian metric arising from the $n$-

Runze Hu, Zihao Huang, Xudong Li, Bohan Fu

Human visual perception naturally evaluates image quality across multiple scales, a hierarchical process that existing blind image quality assessment (BIQA) algorithms struggle to replicate effectively. This limitation stems from a fundamental misunderstanding: current multi-scale approaches fail to recognize that quality perception varies dramatically betwe

Junho Hong

We undertake a comprehensive analysis of the supersymmetric partition function of the $\text{U}(N)_k\times\text{U}(N)_{-k}$ ABJM theory on a Seifert manifold, evaluating it to all orders in the $1/N$-perturbative expansion up to exponentially suppressed corrections. Through holographic duality, our perturbatively exact result is successfully matched with the

K. K. Kataria, P. Vishwakarma

We study an immigration effect in the time-changed linear birth-death process where the immigration occurs only if the population goes extinct. We call this process as the time-fractional linear birth-death process with immigration (TFLBDPwI). Its transient probabilities are obtained using the Adomian decomposition method. In a particular case, we discuss th

Govind Menon

This article provides an expository account of training dynamics in the Deep Linear Network (DLN) from the perspective of the geometric theory of dynamical systems. Rigorous results by several authors are unified into a thermodynamic framework for deep learning. The analysis begins with a characterization of the invariant manifolds and Riemannian geometry in

Thomas Marshall, Adam Scherlis, Nora Belrose

We propose affine concept editing (ACE) as an approach for steering language models' behavior by intervening directly in activations. We begin with an affine decomposition of model activation vectors and show that prior methods for steering model behavior correspond to subsets of terms of this decomposition. We then provide a derivation of ACE and use it to

Ved G. Shah, Ryan J. Foley, Gautham Narayan

The discovery of a second electromagnetic counterpart to a gravitational wave event represents a critical goal in the field of multi-messenger astronomy. In order to determine the optimal strategy for achieving this goal, we perform comprehensive simulations comparing two potential paths forward: continuing the current LIGO-Virgo-KAGRA (LVK) observing run, O

Sadman Jashim Sakib, Baktiar Kabir Joy, Zahin Rydha, Md. Nuruzzaman

Online education's popularity has been continuously increasing over the past few years. Many universities were forced to switch to online education as a result of COVID-19. In many cases, even after more than two years of online instruction, colleges were unable to resume their traditional classroom programs. A growing number of institutions are considering

C. P. Burgess, Thomas Colas, R. Holman, Greg Kaplanek

Recent calculations in both flat and de Sitter spacetimes have highlighted a tension between the decoupling of high-energy physics from low-energy degrees of freedom and the expectation that quantum systems decohere due to interactions with unknown environments. In effective field theory (EFT), integrating out heavy fields should lead to Hamiltonian time evo

Jianye Xu, Bassam Alrifaee

We propose a learning-based Control Barrier Function (CBF) to reduce conservatism in collision avoidance for car-like robots. Traditional CBFs often use the Euclidean distance between robots' centers as a safety margin, which neglects their headings and approximates their geometries as circles. Although this simplification meets the smoothness and differenti

Zhao-Bang Hou, Jun-Duo Zhang, Yun-Da Li, Yong-Xia Jia

Samaras, a distinct category of fruit, are composed of heavier seeds and lighter wings. Diversity in morphologies and structures subtly contributes to the flight patterns of various seeds, thereby serving as a key factor in the reproductive strategies of plants. To explore the mechanisms underlying various samara flight behaviors, we proposed an effective sc

Jędrzej Tepper, Jan M. van Ruitenbeek

A reproducible procedure for creating STM tips with nanometrically defined apices out of 0.25mm iron wire is presented.

Maksym Zhelyeznuyakov, Johannes E. Fröch, Shane Colburn, Steven L. Brunton

Computer vision tasks require processing large amounts of data to perform image classification, segmentation, and feature extraction. Optical preprocessors can potentially reduce the number of floating point operations required by computer vision tasks, enabling low-power and low-latency operation. However, existing optical preprocessors are mostly learned a

Denis Cornaz, Sébastien Kerleau, Clément W. Royer

Positive spanning sets (PSSs) are families of vectors that span a given linear space through non-negative linear combinations. Despite certain classes of PSSs being well understood, a complete characterization of PSSs remains elusive. In this paper, we explore a relatively understudied relationship between positive spanning sets and strongly edge-connected d

Nicklas Boserup, Gefan Yang, Michael Lind Severinsen, Christy Anna Hipsley

We introduce a methodology for performing parameter inference in high-dimensional, non-linear diffusion processes. We illustrate its applicability for obtaining insights into the evolution of and relationships between species, including ancestral state reconstruction. Estimation is performed by utilising score matching to approximate diffusion bridges, which

Abdurahman Ali Mohammed, Catherine Fonder, Donald S. Sakaguchi, Wallapak Tavanapong

We present a new annotated microscopic cellular image dataset to improve the effectiveness of machine learning methods for cellular image analysis. Cell counting is an important step in cell analysis. Typically, domain experts manually count cells in a microscopic image. Automated cell counting can potentially eliminate this tedious, time-consuming process.

Petra Awad, Ting S. Li, Denis Erkal, Reynier F. Peletier

As globular clusters (GCs) orbit the Milky Way, their stars are tidally stripped forming tidal tails that follow the orbit of the clusters around the Galaxy. The morphology of these tails is complex and shows correlations with the phase of the orbit and the orbital angular velocity, especially for GCs on eccentric orbits. Here, we focus on two GCs, NGC 1261

Govind Dayal, Dheeraj Pratap

The absorption and emission spectrum arising from the vibrational motion of a molecule is mostly in the infrared region. These fingerprint absorptions of polar bonds enable us to acquire bond-specific chemical information from specimens. However, the mode mismatch between the atomic-scale dimensions of the chemical bonds and the resonance wavelength limits t

Yiqiao Bao, Sampath Kannan, Erik Waingarten

Given a non-negative $n \times n$ matrix viewed as a set of distances between $n$ points, we consider the property testing problem of deciding if it is a metric. We also consider the same problem for two special classes of metrics, tree metrics and ultrametrics. For general metrics, our paper is the first to consider these questions. We prove an upper bound

A. Akintunde, P. Bayati, H. Row, S. A. Mallory

Single-file diffusion (SFD) is a key mechanism underlying transport phenomena in confined physical and biological systems. In a typical SFD process, microscopic particles are restricted to moving in a narrow channel where they cannot pass one another, resulting in constrained motion and anomalous long-time diffusion. In this study, we use Brownian dynamics s

Juan Pablo Contreras, Cristóbal Guzmán, David Martínez-Rubio

We develop algorithms for the optimization of convex objectives that have H\"older continuous $q$-th derivatives by using a $q$-th order oracle, for any $q \geq 1$. Our algorithms work for general norms under mild conditions, including the $\ell_p$-settings for $1\leq p\leq \infty$. We can also optimize structured functions that allow for inexactly implement

Jorge Reyes, Ping-Hsuan Tsai, Julia Novo, Traian Iliescu

The a priori error analysis of reduced order models (ROMs) for fluids is relatively scarce. In this paper, we take a step in this direction and conduct numerical analysis of the recently introduced time relaxation ROM (TR-ROM), which uses spatial filtering to stabilize ROMs for convection-dominated flows. Specifically, we prove stability, an a priori error b

Víctor Jaramillo, Shuang-Yong Zhou

We construct static axisymmetric multisolitons in the Einstein-Friedberg-Lee-Sirlin model. This theory features a complex scalar field which gains mass through its interaction with a real scalar field that has a non-zero vacuum expectation value. By performing three-dimensional numerical relativity simulations, we identify stable dipolar boson stars in speci

Changyu Shen, Menglan Pang, Ling Zhu, Lu Tian

In comparative studies of progressive diseases, such as randomized controlled trials (RCTs), the mean Change From Baseline (CFB) of a continuous outcome at a pre-specified follow-up time across subjects in the target population is a standard estimand used to summarize the overall disease progression. Despite its simplicity in interpretation, the mean CFB may

C. Daoutis, A. Zezas, E. Kyritsis, K. Kouroumpatzakis

Context. A major challenge in astrophysics is classifying galaxies by their activity. Current methods often require multiple diagnostics to capture the full range of galactic activity. Furthermore, overlapping excitation sources with similar observational signatures complicate the analysis of a galaxy's activity. Aims. This study aims to create an activity d

Saurabh Mishra, Anand Rao, Ramayya Krishnan, Bilal Ayyub

As AI systems become integral to critical operations across industries and services, ensuring their reliability and safety is essential. We offer a framework that integrates established reliability and resilience engineering principles into AI systems. By applying traditional metrics such as failure rate and Mean Time Between Failures (MTBF) along with resil

Xinming Zhao, Guoliang Guo, Chengyu Yan, Noah F. Q. Yuan

Symmetry breaking in a layered superconductor with Ising spin-orbit coupling has offered an opportunity to realize unconventional superconductivity. To be more specific, orbital Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state, exhibiting layer-dependent finite-momentum pairing, may emerge in transition metal dichalcogenides materials (TMDC) in the presence of

Mohammad Mahdi Mohajeri, Mohammad Javad Dousti, Majid Nili Ahmadabadi

Text classification is a fundamental task in natural language processing (NLP), and large language models (LLMs) have demonstrated their capability to perform this task across various domains. However, the performance of LLMs heavily depends on the quality of their input prompts. Recent studies have also shown that LLMs exhibit remarkable results in code-rel

Bailey Forster, Tyler J. Foster, Roland Kothes, Alex S. Hill

Observations of the Milky Way and external galaxies support the idea that large-scale magnetic fields are concentrated in galactic disks, with halo magnetic fields at least an order of magnitude weaker. However, very little is known about the transition between the two. We present the discovery of linearly polarized radio emission at the interface between in

Reyhaneh Taj

Scientific machine learning (SciML) represents a significant advancement in integrating machine learning (ML) with scientific methodologies. At the forefront of this development are Physics-Informed Neural Networks (PINNs), which offer a promising approach by incorporating physical laws directly into the learning process, thereby reducing the need for extens

Shayan Alipour, Indira Sen, Mattia Samory, Tanushree Mitra

Large language models (LLMs) are known to exhibit demographic biases, yet few studies systematically evaluate these biases across multiple datasets or account for confounding factors. In this work, we examine LLM alignment with human annotations in five offensive language datasets, comprising approximately 220K annotations. Our findings reveal that while dem

Aigars Atvars, Dmitry Kostrichkin, Sergey Rudenko, Mihails Lapkis

Operational amplifiers are critical components in modern analog electronics, widely used across applications such as signal conditioning, instrumentation, voltage regulation, and analog-to-digital conversion. This paper presents the design, development, and evaluation of the aRD820, a low-power, rail-to-rail operational amplifier, as a cost-effective alterna

Marc Harary, Eliezer M. Van Allen, William Lotter

Though multiple instance learning (MIL) has been a foundational strategy in computational pathology for processing whole slide images (WSIs), current approaches are designed for traditional hematoxylin and eosin (H&E) slides rather than emerging multiplexed technologies. Here, we present an MIL strategy, the Fluoroformer module, that is specifically tailored

Maya H. Debski, Gregory R. Zeimann, Gary J. Hill, Donald P. Schneider

We combine the power of blind integral field spectroscopy from the Hobby-Eberly Telescope (HET) Dark Energy Experiment (HETDEX) with sources detected by the Low Frequency Array (LOFAR) to construct the HETDEX-LOFAR Spectroscopic Redshift Catalog. Starting from the first data release of the LOFAR Two-metre Sky Survey (LoTSS), including a value-added catalog w

Marianne C. Reddan, Luke Chang, Philip Kragel, Tor D. Wager

Emotion is often described as something people 'feel' in their bodies. Embodied emotion theorists propose that this connection is not purely linguistic; perceiving an emotion may require somatosensory and motor re-experiencing. However, it remains unclear whether self-reports of emotion-related bodily sensations (i.e., 'lump in my throat') are related to neu

Prommy Sultana Hossain, Xintong Wang, Fang-Yi Yu

Designing automated market makers (AMMs) for prediction markets on combinatorial securities over large outcome spaces poses significant computational challenges. Prior research has primarily focused on combinatorial prediction markets within specific set systems (e.g., intervals, permutations). We introduce a framework for designing AMMs on arbitrary set sys

Raphael Skalidis

Dust polarization, which comes from the alignment of aspherical grains to magnetic fields, has been widely employed to study the interstellar medium (ISM) dust properties. The wavelength dependence of the degree of optical polarization, known as the Serkowski relation, was a key observational discovery that advanced grain modeling and alignment theories. How

S. Elaheh Hosseini, Andreas Eckart, Michal Zajaček, Silke Britzen

We focus on a sample of 42 sources in the vicinity of the bow-shock source IRS 1W (N-sources), located at the distance of $6.05''$ north-east of the supermassive black hole (SMBH) Sagittarius A* (Sgr A*), within the radius of $1.35''$. We present the first proper motion measurements of N-sources and find that a larger subset of N-sources (28 sources) exhibit

Jay D. Sau, Shuyang Wang

Motivated by recent experiments showing evidence for chiral superconductivity in an anomalous Hall phase of tetralayer graphene, we study the relation between the normal state anomalous Hall conductivity and that in the phase disordered state above the critical temperature of the superconductor. By a numerical calculation of superconductivity in an anomalous

Sasha Doubov, Nikhil Sardana, Vitaliy Chiley

Small, highly trained, open-source large language models are widely used due to their inference efficiency, but further improving their quality remains a challenge. Sparse upcycling is a promising approach that transforms a pretrained dense model into a Mixture-of-Experts (MoE) architecture, increasing the model's parameter count and quality. In this work, w

Graham L. Giller

In this short note the theory for multivariate asset allocation with elliptically symmetric distributions of returns, as developed in the author's prior work, is specialized to the case of returns drawn from a multivariate Laplace distribution. This analysis delivers a result closely, but not perfectly, consistent with the conjecture presented in the author'

Misha Schmalian

Given a fibred hyperbolic 3-manifold with boundary, we coarsely relate the Euclidean geometry of its cusps to the classical fractional Dehn twist coefficient of its monodromy. This result fits into the broader programme of coarsely describing the geometry of a hyperbolic 3-manifold via combinatorial data. We are thus able to study the hyperbolic geometry of

Laszlo Rassaert, Tomás Ramos, Tommaso Roscilde, Diego Porras

We introduce a driven-dissipative Bose-Hubbard chain describing coupled lossy photonic modes, in which time-reversal symmetry is broken by a coherent drive with a uniform phase gradient. We investigate this model by means of a Gaussian variational ansatz and numerically prove that the steady-state solution is stabilized by an inhomogeneous profile of the dri

Benjamin Kass, Spenser Talkington, Ajit Srivastava, Martin Claassen

The strong coupling regime of photons and quantum materials inside optical cavities has emerged as a promising environment for manipulating states of matter with light. Here, in turn, we show that photons bear witness to cavity quantum-electrodynamical modifications of the material, leading to profoundly non-classical properties of light passing through the

Matias Blaña, Andreas Burkert, Michael Fellhauer, Diego Calderón

The impact of the dynamical state of gas-rich satellite galaxies at the early moments of their infall into their host systems and the relation to their quenching process are not completely understood at the low-mass regime. Two such nearby systems are the infalling Milky Way (MW) dwarfs Leo~T and Phoenix located near the MW virial radius at $414 {\rm kpc}\,(

Debsubhra Chakraborty, Piyush Srivastava, Arpith Kumar, Nilmani Mathur

Exploring nuclear physics through the fundamental constituents of the strong force -- quarks and gluons -- is a formidable challenge. While numerical calculations using lattice quantum chromodynamics offer the most promising approach for this pursuit, practical implementation is arduous, especially due to the uncontrollable growth of quark-combinatorics, the

Nicolás Abate, Gonzalo Torroba

We prove the C, F and A irreversibility theorems in de Sitter spacetime for quantum field theories that are obtained as renormalization group flows from ultraviolet conformal fixed points. The proof is based on strong subadditivity of the entanglement entropy, de Sitter invariance, and the Markov property of conformal field theory.

Douglas R. Alves, James S. Jenkins, Jose I. Vines, Matthew P. Battley

In the last few decades planet search surveys have been focusing on solar type stars, and only recently the high-mass regimes. This is mostly due to challenges arising from the lack of instrumental precision, and more importantly, the inherent active nature of fast rotating massive stars. Here we report NGTS-33b (TOI-6442b), a super-Jupiter planet with mass,

L. M. Stapper, M. R. Hogerheijde, E. F. van Dishoeck, A. S. Booth

Disks around intermediate mass stars called Herbig disks are the formation sites of giant exoplanets. Obtaining a complete inventory of these disks will therefore give insights into giant planet formation. However, until now no complete disk survey has been done on Herbig disks in a single star-forming region. Orion is the only nearby region with a significa

Lingrui Lin, Federico Lelli, Carlos De Breuck, Allison Man

The gas dynamics of galaxies provide critical insights into the evolution of both baryons and dark matter (DM) across cosmic time. In this context, galaxies at cosmic noon -- the period characterized by the most intense star formation and black hole activities -- are particularly significant. In this work, we present an analysis of the gas dynamics of PKS 05

Kai Lehman, Sven Krippendorf, Jochen Weller, Klaus Dolag

How much cosmological information can we reliably extract from existing and upcoming large-scale structure observations? Many summary statistics fall short in describing the non-Gaussian nature of the late-time Universe in comparison to existing and upcoming measurements. In this article we demonstrate that we can identify optimal summary statistics and that

Dominik Leier, Ignacio Ferreras, Andrea Negri, Prasenjit Saha

The concentration-virial mass (c-M) relation is a fundamental scaling relation within the standard cold dark matter ($\Lambda$CDM) framework well established in numerical simulations. However, observational constraints of this relation are hampered by the difficulty of characterising the properties of dark matter haloes. Recent comparisons between simulation

Alexander Schuckert, Eleanor Crane, Alexey V. Gorshkov, Mohammad Hafezi

Simulating the dynamics of electrons and other fermionic particles in quantum chemistry, materials science, and high-energy physics is one of the most promising applications of fault-tolerant quantum computers. However, the overhead in mapping time evolution under fermionic Hamiltonians to qubit gates renders this endeavor challenging. We introduce fermionic

Noël Vouitsis, Rasa Hosseinzadeh, Brendan Leigh Ross, Valentin Villecroze

Although diffusion models can generate remarkably high-quality samples, they are intrinsically bottlenecked by their expensive iterative sampling procedure. Consistency models (CMs) have recently emerged as a promising diffusion model distillation method, reducing the cost of sampling by generating high-fidelity samples in just a few iterations. Consistency

L. M. Stapper, M. R. Hogerheijde, E. F. van Dishoeck, M. Vioque

The precursors of Herbig stars are called Intermediate Mass T Tauri (IMTT) stars, which have spectral types later than F, but stellar masses between 1.5 and 5 M_\odot, and will eventually become Herbig stars with spectral types of A and B. ALMA Band 6 and 7 archival data are obtained for 34 IMTT disks with continuum observations, 32 of which have at least 12

Sally Dawson, Matthew Forslund, Pier Paolo Giardino

Some of the most precise measurements of Higgs boson couplings are from the Higgs decays to 4 leptons, where deviations from the Standard Model predictions can be quantified in the framework of the Standard Model Effective Field Theory (SMEFT). In this work, we present a complete next-to-leading order (NLO) SMEFT electroweak calculation of the rate for $H\ri

Oliver Gould, Paul Saffin

We perform a state-of-the-art study of the cosmological phase transitions of the real-scalar extended Standard Model. We carry out a broad scan of the parameter space of this model at next-to-next-to-leading order in powers of couplings. We use effective field theory to account for the necessary higher-order resummations, and to construct consistent real and

Urko Petralanda, Yi Jiang, B. Andrei Bernevig, Nicolas Regnault

We adapt the topological quantum chemistry formalism to layer groups, and apply it to study the band topology of 8,872 entries from the computational two-dimensional (2D) materials databases C2DB and MC2D. In our analysis, we find 4,073 topologically non-trivial or obstructed atomic insulator entries, including 905 topological insulators, 602 even-electron n

L. Hernández-García, A. M. Muñoz-Arancibia, P. Lira, G. Bruni

With a growing number of facilities able to monitor the entire sky and produce light curves with a cadence of days, in recent years there has been an increased rate of detection of sources whose variability deviates from standard behavior, revealing a variety of exotic nuclear transients. The aim of the present study is to disentangle the nature of the trans

Pawel Caputa, Bowen Chen, Tadashi Takayanagi, Takashi Tsuda

In this work, we develop a generalisation of the thermal entropy to complex inverse temperatures, which we call the thermal pseudo-entropy. We show that this quantity represents the pseudo-entropy of the transition matrix between Thermofield Double states at different times. We have studied its properties in various quantum mechanical setups, Schwarzian theo

Maxim Dzero, Jaglul Hasan, Alex Levchenko

We consider the nonlinear response of a disordered two-dimensional electronic system, lacking inversion symmetry, to an external alternating electric field. The application of an in-plane static magnetic field induces local contributions to the current density that are quadratic in the electric field and linear in the magnetic field. This current oscillates

Jose Angel Silva-Guillén, Enric Canadell

Charge density waves (CDW) in single-layer 1$T$-MTe$_2$ (M= Nb, Ta) recently raised large attention because of the contrasting structural and physical behavior with the sulfide and selenide analogues. A first-principles study of fourteen different 1$T$-type TaTe$_2$ single-layers is reported. The importance of Te to Ta electron transfer and multicenter metal

Z. Sharbaf, I. Ferreras, A. Negri, J. Angthopo

Cosmological hydrodynamical simulations provide valuable insights on galaxy evolution when coupled with observational data. Comparisons with real galaxies are typically performed via scaling relations of the observables. Here we follow an alternative approach based on the spectral covariance in a model-independent way. We build upon previous work by Sharbaf

Chris Hamilton, Shaunak Modak, Scott Tremaine

The bulk of old stars in the Galactic disk have migrated radially by up to several kpc in their lifetimes, yet the disk has remained relatively cool, i.e., the ratio of radial heating to migration has been small. Here, we demonstrate that this small ratio places very strong constraints on which mechanisms could have been responsible for orbital transport in

Nathan Jamieson, Aaron Smith, Meredith Neyer, Rahul Kannan

The growth of ionized hydrogen bubbles in the intergalactic medium around early luminous objects is a fundamental process during the Epoch of Reionization (EoR). In this study, we analyze bubble sizes and their evolution using the state-of-the-art THESAN radiation-hydrodynamics simulation suite, which self-consistently models radiation transport and realisti

Yves H. Kwan, Tixuan Tan, Trithep Devakul

We propose the realization of a fractional Chern mosaic: a state characterized by a spatially varying topological order. This state is enabled by a separation of length scales that emerges when three graphene sheets are sequentially rotated by a small twist angle. The resulting structure features not only conventional moir\'e lattices, but also a much larger

Mijeong Kim, Jongwoo Lim, Bohyung Han

Novel view synthesis of dynamic scenes is becoming important in various applications, including augmented and virtual reality. We propose a novel 4D Gaussian Splatting (4DGS) algorithm for dynamic scenes from casually recorded monocular videos. To overcome the overfitting problem of existing work for these real-world videos, we introduce an uncertainty-aware

Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet

We discuss some consistent issues on how RepNet has been evaluated in various papers. As a way to mitigate these issues, we report RepNet performance results on different datasets, and release evaluation code and the RepNet checkpoint to obtain these results. Code URL: https://github.com/google-research/google-research/blob/master/repnet/

Mathieu Bozzio, Claude Crépeau, Petros Wallden, Philip Walther

Owing to its fundamental principles, quantum theory holds the promise to enhance the security of modern cryptography, from message encryption to anonymous communication, digital signatures, online banking, leader election, one-time passwords and delegated computation. While quantum key distribution (QKD) has already enabled secure key exchange over hundreds

Yasin Abdulkadir, Justin Hink, Peter Boyle, Dishane Luximon

Aggregating large-scale radiotherapy planning and delivery data is crucial for advancing radiation oncology research and improving clinical practice, yet challenges persist due to the diversity of treatment planning systems (TPS), record and verify (R&V) systems, and complex data formats lacking standardized retrieval methods. We developed a robust software

Wen Zhang, Aurojit Panda, Mooly Sagiv, Scott Shenker

Query determinacy is decidable for project-select views and a project-select-join query with no self joins, as long as the selection predicates are in a first-order theory for which satisfiability is decidable.

Julián Rey

We show that the anisotropies in the spectrum of gravitational waves induced by scalar modes after the end of inflation in canonical, single-field models are completely determined by the tilt of the scalar and tensor power spectra. The latter contains information about anisotropies produced due to the propagation of the tensor modes in an inhomogeneous Unive

Elana Simon, James Zou

Protein language models (PLMs) have demonstrated remarkable success in protein modeling and design, yet their internal mechanisms for predicting structure and function remain poorly understood. Here we present a systematic approach to extract and analyze interpretable features from PLMs using sparse autoencoders (SAEs). By training SAEs on embeddings from th

Sadjad Alikhani, Gouranga Charan, Ahmed Alkhateeb

This paper presents Large Wireless Model (LWM) -- the world's first foundation model for wireless channels. Designed as a task-agnostic model, LWM generates universal, rich, contextualized channel embeddings (features) that potentially enhance performance across a wide range of downstream tasks in wireless communication and sensing systems. Towards this obje

Hong Wang, Shukun Wu

We propose to study the restriction conjecture using decoupling theorems and two-ends Furstenberg inequalities. Specifically, we pose a two-ends Furstenberg conjecture, which implies the restriction conjecture. As evidence, we prove this conjecture in the plane by using the Furstenberg set estimate. Moreover, we use this planar result to prove a restriction

Daniel P. Jeong, Pranav Mani, Saurabh Garg, Zachary C. Lipton

Several recent works seek to adapt general-purpose large language models (LLMs) and vision-language models (VLMs) for medical applications through continued pretraining on publicly available biomedical corpora. These works typically claim that such domain-adaptive pretraining improves performance on various downstream medical tasks, such as answering medical

Prem Kumar, K. P. Athulya, Sibasish Ghosh

When the coupling of a quantum system to its environment is non-negligible, its steady state is known to deviate from the textbook Gibbs state. The Bloch-Redfield quantum master equation, one of the most widely adopted equations to solve the open quantum dynamics, cannot predict all the deviations of the steady state of a quantum system from the Gibbs state.

Wissam Antoun, Francis Kulumba, Rian Touchent, Éric de la Clergerie

French language models, such as CamemBERT, have been widely adopted across industries for natural language processing (NLP) tasks, with models like CamemBERT seeing over 4 million downloads per month. However, these models face challenges due to temporal concept drift, where outdated training data leads to a decline in performance, especially when encounteri

Kushankur Ghosh, Murilo Coelho Naldi, Jörg Sander, Euijin Choo

In machine learning and data mining, outliers are data points that significantly differ from the dataset and often introduce irrelevant information that can induce bias in its statistics and models. Therefore, unsupervised methods are crucial to detect outliers if there is limited or no information about them. Global-Local Outlier Scores based on Hierarchies

Gabriel Finneran, Laura Cotter, Antonio Martin-Carrillo

This paper presents the GRBSN webtool, an open-source data repository coupled to a web interface that hosts the most complete dataset of GRB-SN associations to date. In contrast to repositories of supernova (SN) or gamma-ray burst (GRB) data, this tool provides a multi-wavelength view of each GRB-SN association. GRBSN allows users to view and interact with p

Pietro Antonio Grassi, Massimo Porrati

Powerful techniques have been developed in quantum field theory that employ algebras of local operators, yet local operators cannot create physical charged states in gauge theory or physical nonzero-energy states in perturbative quantum gravity. A common method to obtain physical operators out of local ones is to dress the latter using appropriate Wilson lin

Graham L. Giller

This note discusses some of the aspects of a model for the covariance of equity returns based on a simple "isotropic" structure in which all pairwise correlations are taken to be the same value. The effect of the structure on feasible values for the common correlation of returns and on the "effective degrees of freedom" within the equity cross-section are di

Grayson Plumpton

We give a probabilistic interpretation of the Dedekind zeta functions of $\mathbb{Q}(\sqrt{-1})$ and $\mathbb{Q}(\sqrt{-2})$ using zeta integrals and use this to show that the first two Li coefficients of these zeta functions are positive. This extends a result of Biane, Pitman, and Yor (2001) which considered the case of the Riemann zeta function.

Piyush Jha, Arnav Arora, Vijay Ganesh

We introduce LLMStinger, a novel approach that leverages Large Language Models (LLMs) to automatically generate adversarial suffixes for jailbreak attacks. Unlike traditional methods, which require complex prompt engineering or white-box access, LLMStinger uses a reinforcement learning (RL) loop to fine-tune an attacker LLM, generating new suffixes based on

Drago Plecko

Relationships of cause and effect are of prime importance for explaining scientific phenomena. Often, rather than just understanding the effects of causes, researchers also wish to understand how a cause $X$ affects an outcome $Y$ mechanistically -- i.e., what are the causal pathways that are activated between $X$ and $Y$. For analyzing such questions, a ran

Catherine McGeoch

In 1991, David Bailey wrote an article describing techniques for overstating the performance of massively parallel computers. Intended as a lighthearted protest against the practice of inflating benchmark results in order to ``fool the masses" and boost sales, the paper sparked development of procedural standards that help benchmarkers avoid methodological e

Mahsa Nasri, Uttkarsh Narayan, Mustafa Feyyaz Sonbudak, Aubrey Simonson

Apprenticeship and training programs in advanced manufacturing frequently encounter safety and accessibility concerns due to using heavy machinery. Virtual Reality (VR) training addresses such constraints while maintaining the spatial and procedural learning requirements of such training. However, designing effective VR training is challenging because advanc

Ibrahima Bah, Patrick Jefferson, Konstantinos Roumpedakis, Thomas Waddleton

We argue that topological operators for continuous symmetries written in terms of currents need regularization, which effectively gives them a small but finite width. The regulated operator is a finite tension object which fluctuates. In the zero-width limit these fluctuations freeze, recovering the properties of a topological operator. When gravity is turne

Bilal Khalid, Sabre Kais

It is widely believed that quantum mechanics cannot exhibit chaos, since unitarity of time evolution ensures that distances between quantum states are preserved. However, a parallel argument can be constructed in classical mechanics that would seem to deny the existence of classical chaos too. The argument works by describing classical states as probability

G. Leckenby, R. S. Sidhu, R. J. Chen, R. Mancino

Radioactive nuclei with lifetimes on the order of millions of years can reveal the formation history of the Sun and active nucleosynthesis occurring at the time and place of its birth. Among such nuclei whose decay signatures are found in the oldest meteorites, $^{205}$Pb is a powerful example, as it is produced exclusively by slow neutron captures (the s pr

Filippo Glerean, Enrico Maria Rigoni, Giacomo Jarc, Shahla Yasmin Mathengattil

Measuring fluctuations in matter's low energy excitations is the key to unveil the nature of the nonequilibrium response of materials. A promising outlook in this respect is offered by spectroscopic methods that address matter fluctuations by exploiting the statistical nature of light-matter interactions with weak few-photon probes. Here we report the first

Devanshu Sharma

Stochastic inflation, together with the $\Delta N$ formalism, provides a powerful tool for estimating the large-scale behaviour of primordial fluctuations. In this work, we develop a numerical code to capture the non-perturbative statistics of these fluctuations and validate it to obtain the exponential non-Gaussian tail of the curvature perturbations. We pr