February 2025 arXiv papers — page 21

Emanuele Contini, Sukyoung K. Yi, Jinsu Rhee, Seyoung Jeon

We build upon the state-of-the-art semi-analytic model \texttt{FEGA24} (Formation and Evolution of GAlaxies, \citealt{contini2024d}), which integrates the latest prescriptions relevant to galaxy formation and evolution, alongside a comprehensive AGN feedback model. This model incorporates three modes of feedback: negative (preventing excessive cooling), posi

Chudi Zhong, Panyu Chen, Cynthia Rudin

Faithful explanations are essential for machine learning models in high-stakes applications. Inherently interpretable models are well-suited for these applications because they naturally provide faithful explanations by revealing their decision logic. However, model designers often need to keep these models proprietary to maintain their value. This creates a

Daan Verraes, Tom Braeckevelt, Nick Bultinck, Veronique Van Speybroeck

We conduct first-principles simulations of La$_3$Ni$_2$O$_7$, a nickelate in which recent experiments have shown signs of high-temperature superconductivity. Within the hydrostatic pressure range where superconductivity is observed, we find a significant increase in effective on-site repulsion in the maximally localised Wannier functions comprising the Ni $e

Konstantina Christakopoulou, Iris Qu, John Canny, Andrew Goodridge

The language generation and reasoning capabilities of large language models (LLMs) have enabled conversational systems with impressive performance in a variety of tasks, from code generation, to composing essays, to passing STEM and legal exams, to a new paradigm for knowledge search. Besides those short-term use applications, LLMs are increasingly used to h

Héctor Sanchis, Gabriela Barenboim, Yuber F. Perez-Gonzalez

We investigate the impact of neutrino emission via Hawking radiation from primordial black holes (PBHs) on the cosmological effective number of neutrino species, $N_{\mathrm{eff}}$, after neutrino decoupling. By comparing this effect with observational limits, we derive bounds on the abundance of light PBHs. Our analysis incorporates two previously unaccount

Carlo Nipoti

Massive quiescent galaxies at high redshift are significantly more compact than their present-day counterparts. We investigate the roles, in determining this evolution, of major and minor mergers, and of the accretion of diffuse envelopes of stars and dark matter. We model the evolution in stellar mass ($M_\star$), effective radius ($R_{\rm e}$), and effecti

Ingrid Pelisoli, Jamie Williams

White dwarf stars are the most common final stage of stellar evolution. Since the serendipitous discovery of the first white dwarf by William Herschel and the first physical models by Subrahmanyan Chandrasekhar and Arthur Eddington, there have been a lot of advances in the field fueled by new observational data. With new astrometric measurements enabling us

E. Mamuzic, T. Ryu, S. H. Suyu, K. Szekerczes

In the coming years, surveys such as the Rubin Observatory's Legacy Survey of Space and Time (LSST) are expected to increase the number of observed Tidal Disruption Events (TDEs) substantially. We employ Monte Carlo integration to calculate the unlensed and lensed TDE rate as a function of limiting magnitude in $u$, $g$, $r$, and $i$-bands. We investigate th

Uri Keshet

Faint $\gamma$-ray signatures emerge in Fermi-LAT data stacked scaled to the characteristic $\theta_{500}$ angles of MCXC galaxy clusters. After Paper I of this series thus discovered virial shocks, later supported in other bands, this second paper focuses on cluster cores. Stacking $1$-$100$ GeV source-masked data around clusters shows a significant ($4.7\s

Madisen Johnson, Yeimy J. Rivera, Tatiana Niembro, Kristoff Paulson

Parker Solar Probe is a mission designed to explore properties of the solar wind closer than ever before. Detailed particle observations from the Solar Probe Cup (SPC) have primarily focused on examining the proton population in the solar wind. However, several periods throughout the Parker mission have indicated that SPC has observed a pronounced and distin

Francesco D'Eramo, Tommaso Sassi

We investigate the role of an axion-like particle (ALP) as a portal between the dark and visible sectors. Unlike conventional studies, which typically assume fermionic dark matter (DM), we explore the phenomenological implications of scalar DM within this ALP portal framework. A key challenge arises from the fact that the interaction between the ALP spacetim

Luka Matej Devenica, Zach Hadjri, Jan Kumlin, Runtong Li

Spontaneous symmetry breaking, arising from the competition of interactions and quantum fluctuations, is fundamental to understanding ordered electronic phases. Although electrically neutral, optical excitations like excitons can interact through their dipole moment, raising the possibility of optically active ordered phases. The effects of spontaneous order

J. P. Carvalho-Corrêa, I. M. Pereira, B. L. Sánchez-Vega, A. C. D. Viglioni

A complete assessment of any dark matter model requires confronting its low-energy phenomenology with its high-scale theoretical viability. We undertake such a dual analysis for a class of two-component scalar dark matter models stabilized by $\mathbb{Z}_{2n}$ symmetries, specifically the $\mathbb{Z}_4$, $\mathbb{Z}_6(23)$, and $\mathbb{Z}_6(13)$ frameworks.

D. T. Huong, A. E. Cárcamo Hernández, H. T. Hung, T. T. Hieu

We have developed an extension of the inert doublet model in which the CP-phases in the weak sector are generated from one-loop level corrections mediated by dark fields, while the strong-CP phase arises at three-loop. In this framework, the tiny masses of the active neutrinos are produced through a radiative inverse seesaw mechanism at a two-loop level, the

Michele Minervini, Dhrumil Patel, Mark M. Wilde

Parameterized quantum circuits (PQCs) are central to variational quantum algorithms (VQAs), yet their performance is hindered by complex loss landscapes that make their trainability challenging. Quantum natural gradient descent, which leverages the geometry of the parameterized space through quantum generalizations of the Fisher information matrix, offers a

M. Fournier, P. Grete, M. Brüggen, B. W. O'Shea

Significant theoretical and observational efforts are underway to investigate the properties of turbulence in the hot plasma that pervades galaxy clusters. Spectroscopy has been used to study the projected line-of-sight velocities in both the hot intracluster medium and the cold gas phase using optical and X-ray telescopes. In this paper, we characterize the

Pawel Caputa, Giuseppe Di Giulio

In this work, we investigate local quench dynamics in two-dimensional conformal field theories using Krylov space methods. We derive Lanczos coefficients, spread complexity, and Krylov entropies for local joining and splitting quenches in theories on an infinite line, a circle, a finite interval, and at finite temperature. We examine how these quantities dep

Madisen Johnson, Blakesley Burkhart, Francesco D'Eugenio, Jacques Le Bourlot

We present a theoretical framework for interpreting far-ultraviolet (FUV) fluorescent emission from molecular hydrogen (H$_2$) in high-redshift galaxies, motivated by the unique capabilities of the James Webb Space Telescope (JWST) to probe the rest frame FUV at cosmic dawn. Using the Meudon photodissociation region (PDR) code, we model the H$_2$ fluorescenc

Toshikaze Kariyado, Ashvin Vishwanath, Zhu-Xi Luo

We propose twisted homobilayer of a carbon allotrope, C$_{568}$, to be a promising platform to realize controllable square lattice single-band extended Hubbard model. This setup has the advantage of a widely tunable $t'/t$ ratio without adding external fields, and the intermediate temperature $t\ll T\ll U$ regime can be easily achieved. We first analyze the

Gautam K. Naik, Jonathan N. Hallén, Chris R. Laumann

$U(1)$ gauge theories, including conventional Maxwell electromagnetism, allow $\theta$-terms when parity and time-reversal symmetry are broken. In condensed matter systems, the physics of $\theta$ as a magnetoelectric response has been explored extensively within the context of topological insulators and multiferroics. We show how $\theta$-terms can arise in

Balpreet Kaur, Nissim Kanekar, Marcel Neeleman, Yongda Zhu

We use the Karl G. Jansky Very Large Array (VLA) and the Atacama Large Millimeter/submillimeter Array (ALMA) to detect $\rm CO(1-0)$, $\rm CO(3-2)$, and rest-frame 349-GHz continuum emission from an HI-selected galaxy, DLA1020+2733g, at $z\approx2.3568$ in the field of the $z=2.3553$ damped Lyman-$\alpha$ absorber (DLA) towards QSO J1020+2733. The VLA $\rm C

Mattias Blennow, Pilar Coloma, Enrique Fernández-Martínez, Josu Hernández-García

Deviations from unitarity of the CKM matrix in the quark sector are considered excellent windows to probe physics beyond the Standard Model. In its leptonic counterpart, the PMNS matrix, these searches are particularly motivated, as the new physics needed to generate neutrino masses often leads to non-unitary mixing among the standard neutrinos. It is then i

Carl Lehmann, Lorenzo Crippa, Giorgio Sangiovanni, Jan Carl Budich

Quantum tunneling experiments have provided deep insights into basic excitations occurring as Green's function poles in the realm of complex quantum matter. However, strongly correlated quantum materials also allow for Green's functions zeros (GFZ) that may be seen as an antidote to the familiar poles, and have so far largely eluded direct experimental study

Sowmiya Balan, Torsten Bringmann, Felix Kahlhoefer, Jonas Matuszak

Strong first-order phase transitions in a dark sector offer a compelling explanation for the stochastic gravitational wave background in the nano-Hertz range recently detected by pulsar timing arrays (PTAs). We explore the possibility that such a phase transition at the same time gives mass to a stable fermion that accounts for the observed dark matter abund

Mariana Carrillo González, Sebastián Céspedes

Effective field theories (EFTs) parametrize our ignorance of the underlying UV theory through their Wilson coefficients. However, not all values of these coefficients are consistent with fundamental physical principles. In this paper, we explore the consequences of imposing causal propagation on the comoving curvature perturbation in the EFT of inflation, pa

P. Carenza, J. A. García Pascual, M. Giannotti, I. G. Irastorza

We investigate the potential of IAXO and its intermediate version, BabyIAXO, to detect axions produced in core-collapse supernovae (SNe). Our study demonstrates that these experiments have realistic chances of identifying SN axions, offering crucial insights into both axion physics and SN dynamics. IAXO's sensitivity to SN axions allows for the exploration o

Raphaël Errani, Matthew G. Walker, Simon Rozier, Jorge Peñarrubia

We study the response of mono-energetic stellar populations with initially isotropic kinematics to impulsive and adiabatic changes to an underlying dark matter potential. Half-light radii expand and velocity dispersions decrease as enclosed dark matter is removed. The details of this expansion and cooling depend on the time scale on which the underlying pote

Guillermo Parra-Martinez, Alejandro Jimeno-Pozo, Vo Tien Phong, Hector Sainz-Cruz

Recently, exotic superconductivity emerging from a spin-and-valley-polarized metallic phase has been discovered in rhombohedral tetralayer graphene. To explain this observation, we study the role of electron-electron interactions in driving flavor symmetry breaking, using the Hartree-Fock (HF) approximation, and in stabilizing superconductivity mediated by r

Pierre Kervella, Pasquale Panuzzo, Alexandre Gallenne, Antoine Mérand

The recent astrometric discovery of the nearby (590 pc) massive ($33 M_\odot$) dormant black hole candidate Gaia BH3 offers the possibility to angularly resolve the black hole from its companion star by using optical interferometry. Our aim is to detect emission in the near-infrared K band from the close-in environment of Gaia BH3 caused by accretion. Gaia B

A. Marasco, S. M. Fall, E. M. Di Teodoro, P. E. Mancera Piña

The study of scaling relations of disc galaxies and their evolution across cosmic time requires accurate estimates of galaxy stellar masses $M_\star$ over broad redshift ranges. While photometric $M_\star$ estimates ($M_{\rm phot}$) based on spectral energy distribution (SED) modelling methods are employed routinely at high-$z$, it is unclear to what extent

Dominic V. Else

I review some recent results on understanding the physics of metals in an exact non-perturbative way through the powerful field-theoretic concepts of emergent symmetries and 't Hooft anomalies. A 't Hooft anomaly is a discrete topological property that quantum field theories with global symmetries can have. I explain how many of the properties of metals can

Paweł Horodecki, Kazuki Sakurai, Abhyoudai S. Shaleena, Michael Spannowsky

The exploration of entanglement and Bell non-locality among multi-particle quantum systems offers a profound avenue for testing and understanding the limits of quantum mechanics and local real hidden variable theories. In this work, we examine non-local correlations among three massless spin-1/2 particles generated from the three-body decay of a massive part

A. Gagliano, V. A. Villar, T. Matsumoto, D. O. Jones

We present ultraviolet to infrared observations of the extraordinary Type IIn supernova 2023zkd (SN 2023zkd). Photometrically, it exhibits persistent and luminous precursor emission spanning $\sim$4 years preceding discovery ($M_r\approx-15$ mag, 1,500~days in the observer frame), followed by a secondary stage of gradual brightening in its final year. Post-d

Zihni Kaan Baykara, Héctor Parra De Freitas, Houri-Christina Tarazi

The complete classification of the landscape of 6D $\mathcal{N} = (1,1)$ string vacua remains an open problem. In this work we prove a classification theorem for 6D $\mathcal{N} = (1,1)$ asymmetric orbifolds utilizing a correspondence with orbifolds of chiral 2D SCFTs with $c= 24$ (or $c= 12$). Interestingly, this class of theories can give rise to 6D vacua

Nina M. Coyle, Shirley Weishi Li, Pedro A. N. Machado

The challenges in neutrino-nucleus cross section modeling and its impact on neutrino oscillation experiments are widely recognized. However, a comprehensive and theoretically robust estimation of cross section uncertainties has been lacking, and few studies have quantitatively examined their impact on oscillation measurements. In this work, we evaluate the e

Vijay Balasubramanian, Charlie Cummings

We study the patterns of multipartite entanglement in Chern-Simons theory with compact simple gauge group $G$ and level $k$ for states defined by the path integral on ``link complements'', i.e., compact manifolds whose boundaries consist of $n$ topologically linked tori. We focus on link complements which can be described topologically as fibrations over a S

Donghyeon J. Khim, Dennis Zaritsky, Loraine Sandoval Ascencio, M. C. Cooper

We present a spectroscopic study of the ``Disco Ball'' (SMDG0038365-064207), a rotationally-supported, red-sequence, ultra-diffuse galaxy (UDG) with a nuclear star cluster (NSC), multiple stellar clusters, and active star-forming regions using data obtained with KCWI on the Keck II Telescope. We calculate that the galaxy hosts $34\pm11$ ``globular" clusters.

Lucy Xiaoyang Shi, Brian Ichter, Michael Equi, Liyiming Ke

Generalist robots that can perform a range of different tasks in open-world settings must be able to not only reason about the steps needed to accomplish their goals, but also process complex instructions, prompts, and even feedback during task execution. Intricate instructions (e.g., "Could you make me a vegetarian sandwich?" or "I don't like that one") req

Akshat Gupta, Christine Fang, Atahan Ozdemir, Maochuan Lu

This study investigates the impact of localized updates to large language models (LLMs), specifically in the context of knowledge editing - a task aimed at incorporating or modifying specific facts without altering broader model capabilities. We first show that across different post-training interventions like continuous pre-training, full fine-tuning and LO

Masaaki Otsuka

We conduct a detailed study of the planetary nebula (PN) DdDm1 in the Galactic halo field. DdDm1 is a metal-deficient and the most carbon-poor PN (C/O = 0.11 +/- 0.02) identified in the Galaxy. We aim to verify whether it evolved into a PN without experiencing the third dredge-up (TDU) during the thermal pulse asymptotic giant branch (AGB) phase and to inves

Shiven Sinha, Shashwat Goel, Ponnurangam Kumaraguru, Jonas Geiping

There is growing excitement about the potential of Language Models (LMs) to accelerate scientific discovery. Falsifying hypotheses is key to scientific progress, as it allows claims to be iteratively refined over time. This process requires significant researcher effort, reasoning, and ingenuity. Yet current benchmarks for LMs predominantly assess their abil

Dihang Sun, Zhigang Hu, Biao Wu

We investigate the mixed-state entanglement between two spins embedded in the XXZ Heisenberg chain under thermal equilibrium. By deriving an analytical expression for the entanglement of two-spin thermal states and extending this analysis to larger spin chains, we demonstrate that mixed-state entanglement is profoundly shaped by both disorder and temperature

Christoph Schuhmann, Gollam Rabby, Ameya Prabhu, Tawsif Ahmed

Paywalls, licenses and copyright rules often restrict the broad dissemination and reuse of scientific knowledge. We take the position that it is both legally and technically feasible to extract the scientific knowledge in scholarly texts. Current methods, like text embeddings, fail to reliably preserve factual content, and simple paraphrasing may not be lega

Shir Ashury-Tahan, Yifan Mai, Rajmohan C, Ariel Gera

Despite its real-world significance, model performance on tabular data remains underexplored, leaving uncertainty about which model to rely on and which prompt configuration to adopt. To address this gap, we create ToRR, a benchmark for Table Reasoning and Robustness, measuring model performance and robustness on table-related tasks. The benchmark includes 1

Sarmistha Das, Basha Mujavarsheik, R E Zera Lyngkhoi, Sriparna Saha

In today's competitive marketing landscape, effective complaint management is crucial for customer service and business success. Video complaints, integrating text and image content, offer invaluable insights by addressing customer grievances and delineating product benefits and drawbacks. However, comprehending nuanced complaint aspects within vast daily mu

Dayu Yang, Tianyang Liu, Daoan Zhang, Antoine Simoulin

In large language models (LLMs), code and reasoning reinforce each other: code offers an abstract, modular, and logic-driven structure that supports reasoning, while reasoning translates high-level goals into smaller, executable steps that drive more advanced code intelligence. In this study, we examine how code serves as a structured medium for enhancing re

Xinru Wang, Mengjie Yu, Hannah Nguyen, Michael Iuzzolino

Large Language Models (LLMs) have shown remarkable potential in recommending everyday actions as personal AI assistants, while Explainable AI (XAI) techniques are being increasingly utilized to help users understand why a recommendation is given. Personal AI assistants today are often located on ultra-small devices such as smartwatches, which have limited sc

Danae Sánchez Villegas, Ingo Ziegler, Desmond Elliott

Reasoning over sequences of images remains a challenge for multimodal large language models (MLLMs). While recent models incorporate multi-image data during pre-training, they still struggle to recognize sequential structures, often treating images independently. This work introduces ImageChain, a framework that enhances MLLMs with sequential reasoning capab

Tim Gräfnitz, Helge Ruddat, Eric Zaslow, Benjamin Zhou

We interpret the $q$-refined theta function $\vartheta_1$ of a log Calabi-Yau surface $(\mathbb{P},E)$ as a natural $q$-refinement of the open mirror map, defined by quantum periods of mirror curves for outer Aganagic-Vafa branes on the local Calabi-Yau $K_{\mathbb{P}}$. The series coefficients are all-genus logarithmic two-point invariants, directly extendi

Hasnain Heickal, Andrew Lan

Providing effective feedback for programming assignments in computer science education can be challenging: students solve problems by iteratively submitting code, executing it, and using limited feedback from the compiler or the auto-grader to debug. Analyzing student debugging behavior in this process may reveal important insights into their knowledge and i

Hsiang-Ku Lin, Xingrui Liu, Pak Kau Lim, Leonid P. Pryadko

Generalized-bicycle (GB) and more general two-block group-algebra (2BGA) quantum error-correcting codes have naturally redundant minimum-weight stabilizer generators. To use this redundancy, we constructed a large number of ``planar'' 2BGA codes over abelian groups with one and two generators, with each block row of weight 3, relatively large dimensions, dis

Arasu Arun, Adam St. Arnaud, Alexey Titov, Brian Wilcox

Machine learning programs, such as those performing inference, fine-tuning, and training of LLMs, are commonly delegated to untrusted compute providers. To provide correctness guarantees for the client, we propose adapting the cryptographic notion of refereed delegation to the machine learning setting. This approach enables a computationally limited client t

Asifur Rahman, Kevin R. Mackie

A novel implementation of the traditional node-to-node Coulomb contact-friction problem is presented that utilizes run-time parameter updates on conventional elasto-plastic elements. The two-noded elements are defined by an independent uniaxial force-deformation (or constitutive) relation in each degree of freedom. The location of the two nodes may or may no

J. P. Pridham

We develop a formulation for non-commutative derived analytic geometry built from differential graded (dg) algebras equipped with free entire functional calculus (FEFC), relating them to simplicial FEFC algebras and to locally multiplicatively convex complete topological dg algebras. The theory is optimally suited for accommodating analytic morphisms between

Seungwook Han, Jyothish Pari, Samuel J. Gershman, Pulkit Agrawal

Large Language Models (LLMs) have demonstrated impressive real-world utility, exemplifying artificial useful intelligence (AUI). However, their ability to reason adaptively and robustly -- the hallmarks of artificial general intelligence (AGI) -- remains fragile. While LLMs seemingly succeed in commonsense reasoning, programming, and mathematics, they strugg

David-Alexandre Poissant, Alexis Lussier Desbiens, François Ferland, Louis Petit

Autonomous robotic inspection missions require balancing multiple conflicting objectives while navigating near costly obstacles. Current multi-objective path planning (MOPP) methods struggle to adapt to evolving risks like localization errors, weather, battery state, and communication issues. This letter presents an Adaptive Risk-aware and Energy-efficient N

Max Ku, Thomas Chong, Jonathan Leung, Krish Shah

Understanding domain-specific theorems often requires more than just text-based reasoning; effective communication through structured visual explanations is crucial for deeper comprehension. While large language models (LLMs) demonstrate strong performance in text-based theorem reasoning, their ability to generate coherent and pedagogically meaningful visual

Abhimanyu Kumar, Ramprasath S., Chris H. Kim, Ulya R. Karpuzcu

Many combinatorial problems can be mapped to Ising machines, i.e., networks of coupled oscillators that settle to a minimum-energy ground state, from which the problem solution is inferred. This work proposes DROID, a novel event-driven method for simulating the evolution of a CMOS Ising machine to its ground state. The approach is accurate under general del

Amirreza Ahmadnejad, Somayyeh Koohi, Abolhassan Vaezi

We propose a novel topological photonic memory that encodes information through dynamically controllable Chern numbers in a two-band topological photonic system. Utilizing a honeycomb lattice photonic crystal, the memory leverages topologically protected edge states that remain robust against fabrication imperfections and environmental perturbations. By appl

Rafael R. Del Grande, David A. Strubbe

The Bethe-Salpeter Equation (BSE) is the workhorse method to study excitons in materials. The BSE Hamiltonian size, which depends on how many valence-to-conduction band transitions are considered, needs to be chosen to be sufficiently large to converge excitons' energies and wavefunctions but should be minimized to make calculations tractable, as BSE calcula

Thaddeus D. Komacek

Over the past two decades, a coherent picture has emerged of the atmospheric dynamics of hot Jupiters from a combination of three-dimensional general circulation models (GCMs) and astronomical observations. This paradigm consists of hot Jupiters being spin-synchronized due to their close-in orbit, with a resulting large day-to-night irradiation gradient driv

Emil E. B. Østergaard, Niklas Budinger, Mikkel V. Larsen, Peter van Loock

Macronode cluster states are promising for fault-tolerant continuous-variable quantum computation, combining gate teleportation via homodyne detection with the Gottesman-Kitaev-Preskill code for universality and error correction. While the two-dimensional Quad-Rail Lattice offers flexibility and low noise, it lacks the dimensionality required for topological

Wasim Akram, Sagar Gautam, Deepanshu Verma, Manil T. Mohan

The article focuses on error estimates as well as stability analysis of deep learning methods for stationary and non-stationary viscous Burgers equation in two and three dimensions. The local well-posedness of homogeneous boundary value problem for non-stationary viscous Burgers equation is established by using semigroup techniques and fixed point arguments.

Minjoo Lim, Bogyeong Kang, Tae-Eui Kam

Multi-modal magnetic resonance imaging (MRI) is essential for providing complementary information about brain anatomy and pathology, leading to more accurate diagnoses. However, obtaining high-quality multi-modal MRI in a clinical setting is difficult due to factors such as time constraints, high costs, and patient movement artifacts. To overcome this diffic

Ziqiao Wang, Serhat Demirtas, Fabio Zuliani, Jamie Paik

Intelligence lies not only in the brain (decision-making processes) but in the body (physical morphology). The morphology of robots can significantly influence how they interact with the physical world, crucial for manipulating objects in real-life scenarios. Conventional robotic manipulation strategies mainly rely on finger-shaped end effectors. However, ac

Kevin Batz, Joost-Pieter Katoen, Francesca Randone, Tobias Winkler

We lay out novel foundations for the computer-aided verification of guaranteed bounds on expected outcomes of imperative probabilistic programs featuring (i) general loops, (ii) continuous distributions, and (iii) conditioning. To handle loops we rely on user-provided quantitative invariants, as is well established. However, in the realm of continuous distri

Hamdan Al Ahbabi, Gautier Marti, Saeed AlMarri, Ibrahim Elfadel

Self-supervised learning models for speech processing, such as wav2vec2, HuBERT, WavLM, and Whisper, generate embeddings that capture both linguistic and paralinguistic information, making it challenging to analyze tone independently of spoken content. In this work, we introduce a method for disentangling paralinguistic features from linguistic content by re

Ziqiao Weng, Weidong Cai, Bo Zhou

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder impacting social and behavioral development. Resting-state fMRI, a non-invasive tool for capturing brain connectivity patterns, aids in early ASD diagnosis and differentiation from typical controls (TC). However, previous methods, which rely on either mean time series or full 4D data, are limite

Oğuzhan Ersoy, Jari Kolehmainen, Gabriel Passamani Andrade

Training dense LLMs requires enormous amounts of data and centralized compute, which introduces fundamental bottlenecks and ever-growing costs for large models. Several studies aim to reduce this dependency on centralization by reducing the communication overhead of training dense models. Taking this idea of reducing communication overhead to a natural extre

Cynthia Trendafilova, Ali Rida Khalife, Silvia Galli

The precision of Cosmic Microwave Background (CMB) experiments, specifically its lensing reconstruction, has reached the limit where non-linear corrections cannot be ignored. Neglecting these corrections results in biased constraints on cosmological parameters. In this work, we use lensing data from Planck and the South Pole Telescope third generation camera

F. Hautmann, L. Keersmaekers, A. Lelek, S. Sadeghi Barzani

Soft-gluon resolution scales characterize parton branching Monte Carlo implementations of the evolution equations for parton distribution functions in Quantum Chromodynamics (QCD). We examine scenarios with dynamical, i.e., branching-scale dependent, resolution scale, and discuss physical implications for both collinear and transverse-momentum dependent (TMD

Ranjeev Misra, Hritwik Bora, Rupjyoti Gogoi

We present a formalism to predict the Polarization Degree (PD) for synchrotron emission from particles having a specified energy distribution in the presence of an ordered and random magnetic field configuration. The broad band spectral energy distribution as well as the X-ray and optical PD data for Mrk 501 have been fitted using the formalism. As reported

Vandana Tripathi, B. Longfellow, A. Volya, E. Rubino

In this paper, $\beta^-$ and $\beta$-delayed neutron decays of $^{46,47}$Cl are reported from an experiment carried out at the National Superconducting Cyclotron Laboratory using the Beta Counting System. The half-lives of both $^{46}$Cl and $^{47}$Cl were extracted. Based on the delayed $\gamma$-ray transitions observed, the level structure of $N = 28$ $^{4

Arman Mielke, Uwe Bauknecht, Thilo Strauss, Mathias Niepert

Combinatorial optimization (CO) problems arise across a broad spectrum of domains, including medicine, logistics, and manufacturing. While exact solutions are often computationally infeasible, many practical applications require high-quality solutions within a given time budget. To address this, we propose a learning-based approach that enhances existing non

Andrew M. Kingston, Alaleh Aminzadeh, Lindon Roberts, Jeremy M. C. Brown

We present a method to shape a neutron beam and project any specified target image using a single universal patterned mask that is transversely displaced. The method relies on ``ghost projection'', which is a reversed form of classical ghost imaging. A set of sub-mask regions that combine to construct the required beam shape is computed; illumination of each

Mohammed-Khalil Ghali, Abdelrahman Farrag, Sarah Lam, Daehan Won

Thematic analysis of social media posts provides a major understanding of public discourse, yet traditional methods often struggle to capture the complexity and nuance of unstructured, large-scale text data. This study introduces a novel methodology for thematic analysis that integrates tweet embeddings from pre-trained language models, dimensionality reduct

André Baião Raposo, Raúl A Briceño, Maxwell T Hansen, Andrew W Jackura

We derive a general formalism that relates the spectrum of two-particle systems in a finite volume to physical scattering amplitudes, taking into account the presence of any left-hand branch cuts due to single-particle exchanges. The method first relates the finite-volume spectrum to an infinite-volume short-range quantity, denoted \mathcal{M}_0, and then re

Niclas Vödisch, Giovanni Cioffi, Marco Cannici, Wolfram Burgard

LiDAR registration is a fundamental task in robotic mapping and localization. A critical component of aligning two point clouds is identifying robust point correspondences using point descriptors. This step becomes particularly challenging in scenarios involving domain shifts, seasonal changes, and variations in point cloud structures. These factors substant

Carlo Maccaferri, Riccardo Poletti, Alberto Ruffino, Jakub Vošmera

We discuss the construction of boundary contributions to free string field theory actions in the context of the bosonic string. We show that it is generally possible to obtain a well-defined variational principle by adding a simple boundary term (which only depends on the value of the bulk fields at the boundary) to the original bulk action. However, it is i

Tawfiq Hamed, Mohammad Saleh

Cellular automata are a fundamental computational model with applications in mathematics, computer science, and physics. In this work, we explore the study of cellular automata to cases where the universe is a group, introducing the concept of \( \phi \)-cellular automata. We establish new theoretical results, including a generalized Uniform Curtis-Hedlund T

Lovy Sharma, Manisha Thakurathi

Recently discovered phase of collinear magnet called, altermagnet breaks time reversal symmetry (TRS), exhibits momentum-dependent spin-splitting of band structure with zero net magnetization. In this work, we theoretically investigate the Josephson junction (JJ) of spin singlet superconductor (SC)/altermagnet/spin triplet SC and demonstrate that it manifest

Alexander Altland, Dmitry Bagrets, Nele Callebaut, Konstantin Weisenberger

A celebrated realization of the holographic principle posits an approximate duality between the $(0+1)$-dimensional quantum mechanical SYK model and two-dimensional Jackiw-Teitelboim gravity, mediated by the Schwarzian action as an effective low energy theory common to both systems. We here propose a generalization of this correspondence to one dimension hig

Tamal K. Dey, Michał Lipiński, Andrew Haas

Morse decompositions partition the flows in a vector field into equivalent structures. Given such a decomposition, one can define a further summary of its flow structure by what is called a connection matrix.These matrices, a generalization of Morse boundary operators from classical Morse theory, capture the connections made by the flows among the critical s

Matan Vax, Peleg Emanuel, Eyal Cornfeld, Israel Reichental

Quantum computing hardware is advancing at a rapid pace, yet the lack of high-level programming abstractions remains a serious bottleneck in the development of new applications. Widely used frameworks still rely on gate-level circuit descriptions, causing the algorithm's functional intent to become lost in low-level implementation details, and hindering flex

Christos Chatzis, Carla Schenker, Jérémy E. Cohen, Evrim Acar

Multiway datasets are commonly analyzed using unsupervised matrix and tensor factorization methods to reveal underlying patterns. Frequently, such datasets include timestamps and could correspond to, for example, health-related measurements of subjects collected over time. The temporal dimension is inherently different from the other dimensions, requiring me

A. A. Araújo Filho

In this paper, we examine particle production, evaporation, and greybody factors for a Lorentzian non-commutative black hole. We begin by analyzing particle creation for bosons, considering scalar perturbations to compute the Bogoliubov coefficients, which enable the determination of the Hawking temperature $T_{\Theta}$. Subsequently, we describe Hawking rad

Surat Layek, Subhajit Sinha, Atasi Chakraborty, Ayshi Mukherjee

Exploring the topological characteristics of electronic bands is essential in condensed matter physics. Moir\'e materials featuring flat bands provide a versatile platform for engineering band topology and correlation effects. In moir\'e materials that break either time-reversal symmetry or inversion symmetry or both, electronic bands exhibit Berry curvature

Ali Ismail-Fawaz

Time series data, defined by equally spaced points over time, is essential in fields like medicine, telecommunications, and energy. Analyzing it involves tasks such as classification, clustering, prototyping, and regression. Classification identifies normal vs. abnormal movements in skeleton-based motion sequences, clustering detects stock market behavior pa

Ru Peng, Kexin Yang, Yawen Zeng, Junyang Lin

The performance emergence of large language models (LLMs) driven by data scaling laws makes the selection of pre-training data increasingly important. However, existing methods rely on limited heuristics and human intuition, lacking comprehensive and clear guidelines. To address this, we are inspired by ``reverse thinking'' -- prompting LLMs to self-identify

Jørgen Ellegaard Andersen, Shan Shan

Gaussian Boson Sampling (GBS), which can be realized with a photonic quantum computing model, perform some special kind of sampling tasks. In [4], we introduced algorithms that use GBS samples to approximate Gaussian expectation problems. We found a non-empty open subset of the problem space where these algorithms achieve exponential speedup over the standar

Yancheng He, Shilong Li, Jiaheng Liu, Weixun Wang

Recently, o1-like models have drawn significant attention, where these models produce the long Chain-of-Thought (CoT) reasoning steps to improve the reasoning abilities of existing Large Language Models (LLMs). In this paper, to understand the qualities of these long CoTs and measure the critique abilities of existing LLMs on these long CoTs, we introduce th

Kathleen Gregory, Jonathan Zurbach, Kalpana Shankar, Matthew Mayernik

Sustaining knowledge infrastructures remains a persistent issue that requires continued engagement from diverse stakeholders as new questions and values arise in relation to KI maintenance. We draw on existing academic literature, practical experience with KI projects, and our discussions at a 2024 workshop for researchers and practitioners exploring KI eval

Aileen N. Carroll-Godfrey, Eric I. Corwin

Photon transport through turbid media has typically been modeled through diffusion or telegraph equations. These models describe behavior of the average, or typical, photon with remarkable accuracy, however, we show here that they fail to capture the Extreme First Passage Times (EFPTs) of photon transport. By sending ultra-fast bursts of photons through a sc

Sayani Bera

Let $H$ be a H\'enon map of the form $H(x,y)=(y,p(y)-ax)$. We prove that the escaping set $U^+$ (or equivalently, the non-escaping set $K^+$), of $H$ is rigid under the actions of automorphisms of $\mathbb{C}^2$ if the degree of $H=d\le |a|$. Specifically, every automorphism of $\mathbb{C}^2$ that preserves $U^+$, essentially takes the form $C \circ H^s$ whe

Aidan Furlong, Xingang Zhao, Robert Salko, Xu Wu

Critical heat flux is a key quantity in boiling system modeling due to its impact on heat transfer and component temperature and performance. This study investigates the development and validation of an uncertainty-aware hybrid modeling approach that combines machine learning with physics-based models in the prediction of critical heat flux in nuclear reacto

Jan-Hendrik Ewers, David Anderson, Douglas Thomson

Wilderness search and rescue operations are often carried out over vast landscapes. The search efforts, however, must be undertaken in minimum time to maximize the chance of survival of the victim. Whilst the advent of cheap multicopters in recent years has changed the way search operations are handled, it has not solved the challenges of the massive areas a

Nisarg Vyas, M. S. Santhanam

Due to the unitary evolution, quantum walks display different dynamical features from that of classical random walks. In contrast to this expectation, in this work, we show that extreme events can arise in unitary dynamics and its properties are qualitatively similar to that of random walks. We consider quantum walks on a ring lattice and a scale-free graph.

Harish K. Dureppagari, R. Michael Buehrer, Harpreet S. Dhillon

In this paper, we propose a two-stage weighted projection method (TS-WPM) for time-difference-of-arrival (TDOA)-based localization, providing provable improvements in positioning accuracy, particularly under high geometric dilution of precision (GDOP) and low signal-to-noise ratio (SNR) conditions. TS-WPM employs a two-stage iterative refinement approach tha

Vetle A. Vikenes, Cheng-Zong Ruan, David F. Mota

Data from the ongoing \textit{Euclid} survey will map out billions of galaxies in the Universe, covering more than a third of the sky. This data will provide a wealth of information about the large-scale structure (LSS) of the Universe and will have a significant impact on cosmology in the coming years. In this paper, we introduce an emulator-based halo mode

Johannes Gedeon, Izzatjon Allayarov, Emadeldeen Hassan, Antonio Calà Lesina

We demonstrate a computational inverse design method for optimizing broadband-absorbing metasurfaces made of arbitrary dispersive media. Our figure of merit is the time-averaged instantaneous power dissipation in a single unit cell within a periodic array. Its time-domain formulation allows capturing the response of arbitrary dispersive media over any desire