October 2024 arXiv papers — page 80

Pedro De la Torre Luque, Shyam Balaji, Malcolm Fairbairn, Filippo Sala

We propose that a dark matter (DM) spike around the Galactic Center's (GC) supermassive black hole, Sgr A*, could account for most of the bulge's measured 511 keV line intensity while remaining cosmologically compatible. DM annihilation can be the primary source of the 511 keV line emission without violating constraints from disk emission observations and in

Xing-Yu Yang, Tan Chen, Rong-Gen Cai

Gravitational waves (GWs) offer a new observational window into the universe, providing insights into compact objects and cosmic structures. Gravitational lensing, commonly studied in electromagnetic waves, also affects GWs, introducing magnification, time delays, and multiple images. While existing studies focus on static lenses, many astrophysical lenses a

Noam Levi

Neural scaling laws have garnered significant interest due to their ability to predict model performance as a function of increasing parameters, data, and compute. In this work, we propose a simple statistical ansatz based on memorization to study scaling laws in the context of inference, specifically how performance improves with multiple inference attempts

Francesco Ferrari, Josef Willsher, Urban F. P. Seifert, Roser Valentí

Algebraic spin liquids are quantum disordered phases of insulating magnets which exhibit fractionalized gapless excitations and power-law correlations. Quantum spin liquids in this category include the experimentally established 1D Luttinger liquid, as well as the U(1) Dirac spin liquid (DSL) which has been a focus of recent candidate materials searches. Mos

Matthew C. O'Brien, Eduardo Fradkin

The interplay between quantum and thermal fluctuations in the presence of quenched random disorder is a long-standing open theoretical problem which has been made more urgent by advances in modern experimental techniques. The fragility of charge density wave order to impurities makes this problem of particular interest in understanding a host of real materia

Danny Horta, Ricardo P. Schiavon

Unravelling galaxy formation theory requires understanding galaxies both at high and low redshifts. A possible way to connect both realms is by studying the oldest stars in the Milky Way (i.e., the proto-Galaxy). We use the $APOGEE$-$Gaia$ surveys to perform a purely chemical dissection of Milky Way (MW) stellar populations, and identify samples of stars lik

Aniket Khairnar, Leo C. Stein, Michael Boyle

The inspiral of a circular, non-precessing binary exhibits an approximate helical symmetry. The effects of eccentricity, precession, and radiation reaction break the exact symmetry. We estimate the failure of this symmetry using the flux of the BMS charge corresponding to helical symmetry carried away by gravitational waves. We analytically compute the helic

Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda

Observations suggest that filaments in molecular clouds can grow by mass accretion while forming cores via fragmentation. Here we present one of the first large sample studies of filament accretion using velocity gradient measurements of star-forming filaments on the $\sim 0.05$ pc scale with NH$_3$ observations of the Perseus Molecular Cloud, primarily obta

Xiaohui Liu, Werner Vogelsang, Feng Yuan, Hua Xing Zhu

We investigate the energy-energy correlator (EEC) of hadrons produced on the same side in $e^+e^-$ annihilation or in leading jets in $pp$ collisions. We observe a remarkable universality of the correlator. Using a non-perturbative transverse momentum dependent (TMD) fragmentation function to model the transition from the ``free-hadron" region to the perturb

Francesco Belfiore, Michele Ginolfi, Guillermo Blanc, Mederic Boquien

Classifying ionised nebulae in nearby galaxies is crucial to studying stellar feedback mechanisms and understanding the physical conditions of the interstellar medium. This classification task is generally performed by comparing observed line ratios with photoionisation simulations of different types of nebulae (HII regions, planetary nebulae, and supernova

Wolfgang Brandner, Artur Sorg, Siegfried Röser, Elena Schilbach

Gaia characterizes the stellar populations of nearby open clusters with unprecedented precision. We investigate the B\"ohm-Vitense gap, which has been found as a prominent feature in the stellar sequence of open clusters. Using PARSEC isochrone fitting, we derive astrophysical parameters for more than 1100 stars in Praesepe, identify more than 1100 bona fide

Samuel Alipour-fard, Ankita Budhraja, Jesse Thaler, Wouter J. Waalewijn

Energy correlators have recently come to the forefront of jet substructure studies at colliders due to their remarkable properties: they naturally separate physics at different scales, are robust to contamination from soft radiation, and offer a direct connection with quantum field theory. The current parametrization used for energy correlators, however, is

Ramiro Cayuso, Adrien Kuntz, Miguel Bezares, Enrico Barausse

We explore scalar radiation from neutron star-black hole binaries in scalar-tensor theories with kinetic screening ($K$-essence). Using 3+1 numerical relativity simulations in the decoupling limit, we investigate scalar dipole and quadrupole radiation for different values of the strong coupling constant $\Lambda$. Our results show that kinetic screening effe

Hugo Lévy, Jean-Philippe Uzan

In any scalar-tensor theory of gravity exhibiting a screening mechanism, the fifth force mediated by the scalar field is dynamically suppressed at sub-Solar system scales, allowing it to pass existing tests of gravity. As a result, a major research effort has been carried out over the past decades to `outsmart' screened scalars in this game of hide-and-seek.

Kaley Brauer, Andrew Emerick, Jennifer Mead, Alexander P. Ji

The AEOS project introduces a series of high-resolution cosmological simulations that model star-by-star chemical enrichment and galaxy formation in the early Universe, achieving 1 pc resolution. These simulations capture the complexities of galaxy evolution within the first ~300 Myr by modeling individual stars and their feedback processes. By incorporating

Julian Ingham, Armando Consiglio, Domenico di Sante, Ronny Thomale

We argue that kagome metals can feature an excitonic condensate of unconventional nature. Studying the recently discovered variants ScV$_6$Sn$_6$ and LuNb$_6$Sn$_6$ we identify electron and hole pockets due to a pair of van Hove singularities (vHS) close to the Fermi level, with an approximate spectral particle-hole symmetry. A significant fraction of the Fe

Ioannis D. Gialamas, Kyriakos Tamvakis

We consider Weyl-invariant quadratic Einstein-Cartan gravity coupled to a scalar field and study the inflationary behaviour of the coupled system of the scalar field and the pseudoscalar associated with the Holst invariant. We find that the model is characterized by effective single-field inflation occurring at small field values and analyze its predictions

Cenk Tüysüz, Maria Demidik, Luuk Coopmans, Enrico Rinaldi

In recent years, researchers have been exploring ways to generalize Boltzmann machines (BMs) to quantum systems, leading to the development of variations such as fully-visible and restricted quantum Boltzmann machines (QBMs). Due to the non-commuting nature of their Hamiltonians, restricted QBMs face trainability issues, whereas fully-visible QBMs have emerg

Gereon Koßmann, Mark M. Wilde

This paper introduces a method for calculating the quantum relative entropy of channels, an essential quantity in quantum channel discrimination and resource theories of quantum channels. By building on recent developments in the optimization of relative entropy for quantum states [Ko{\ss}mann and Schwonnek, arXiv:2404.17016], we introduce a discretized line

Isabel Medlock, Chloe Neufeld, Daisuke Nagai, Daniel Anglés Alcázar

The baryonic physics shaping galaxy formation and evolution are complex, spanning a vast range of scales and making them challenging to model. Cosmological simulations rely on subgrid models that produce significantly different predictions. Understanding how models of stellar and active galactic nuclei (AGN) feedback affect baryon behavior across different h

Itay M. Bloch, Or Katz

Many extensions of the Standard Model propose the existence of new particles or forces, aiming to answer mysteries such as the identity of the elusive dark matter. Atomic-based detectors are at the forefront of technologies designed to search for these particles or forces through their couplings to fermions, enabling the testing of well-motivated models, suc

Soubhik Kumar, Hanwen Tai, Lian-Tao Wang

Large curvature perturbations can source an observable amount of stochastic gravitational wave background (SGWB). We consider several scenarios where small-scale curvature perturbations are naturally enhanced due to the presence of additional spectator fields during inflation. The same spectator fields can lead to a period of early matter domination (EMD) af

Imran Sultan, Claude-André Faucher-Giguère, Jonathan Stern, Shaked Rotshtein

The circumgalactic medium (CGM) in $\gtrsim 10^{12}$ $\mathrm{M}_{\odot}$ halos is dominated by a hot phase ($T \gtrsim 10^{6}$ K). While many models exist for the hot gas structure, there is as yet no consensus. We compare cooling flow models, in which the hot CGM flows inward due to radiative cooling, to the CGM of $\sim 10^{12}-10^{13}$ $\mathrm{M}_{\odot

Anton Chudaykin, Mikhail M. Ivanov, Takahiro Nishimichi

Parameter estimation from galaxy survey data from the full-shape method depends on scale cuts and priors on EFT parameters. The effects of priors, including the so-called ''prior volume'' phenomenon have been originally studied in Ivanov et al. (2019) and subsequent works. In this note, we repeat and extend these tests and also apply them to other priors use

Fabrizio Corelli, Enrico Cannizzaro, Andrea Caputo, Paolo Pani

Many motivated extensions of the standard model include new light bosons, such as axions and dark photons, which can mix with the ordinary photon. This latter, when in a dilute plasma, can be dressed by an effective plasma mass. If this is equal to the mass of the new degree of freedom, then a resonance takes place and the probability of transition between s

Luke Corcoran, Marius de Leeuw

We construct the first integrable models based on the Haagerup fusion category $H_3$. We introduce a Haagerup version of the anyonic spin chain and use the boost operator formalism to identify two integrable Hamiltonians of PXP type on this chain. The first of these is an analogue of the golden chain; it has a topological symmetry based on $H_3$ and satisfie

Marco Tesoro, Ilaria Siloi, Daniel Jaschke, Giuseppe Magnifico

Classical public-key cryptography standards rely on the Rivest-Shamir-Adleman (RSA) encryption protocol. The security of this protocol is based on the exponential computational complexity of the most efficient classical algorithms for factoring large semiprime numbers into their two prime components. Here, we address RSA factorization building on Schnorr's m

Natalie Allen, Pascal A. Oesch, Sune Toft, Jasleen Matharu

The evolution of galaxy sizes in different wavelengths provides unique insights on galaxy build-up across cosmic epochs. Such measurements can now finally be done at $z>3$ thanks to the exquisite spatial resolution and multi-wavelength capability of the JWST. With the public data from the CEERS, PRIMER-UDS, and PRIMER-COSMOS surveys, we measure the sizes of

Julius F. Grimminger, William Harding, Noppadol Mekareeya

Non-simply laced quivers, despite the lack of complete Lagrangian descriptions, play an important role in characterising moduli spaces of supersymmetric field theories. Notably, the moduli space of instantons in non-simply laced gauge groups can be understood by means of such quivers. We generalise the notion of non-simply laced unitary quivers to those whos

Dan Mao, Juan Felipe Mendez-Valderrama, Debanjan Chowdhury

Inspired by the discovery of a variety of correlated insulators in the moir\'e universe, controlled by interactions projected to a set of isolated bands with a narrow bandwidth, we examine here a partial sum-rule associated with the inverse frequency-weighted optical conductivity restricted to low-energies. Unlike standard sum-rules that extend out to $infin

T. J. L. C. Bakx, A. Amvrosiadis, G. J. Bendo, H. S. B. Algera

We use the Atacama Large sub/Millimetre Array (ALMA) to efficiently observe spectral lines across Bands 3, 4, 5, 6, 7, and 8 at high-resolution (0.5" - 0.1") for 16 bright southern Herschel sources at $1.5 < z < 4.2$. With only six and a half hours of observations, we reveal 66 spectral lines in 17 galaxies. These observations detect emission from CO (3-2) t

Ali Rostami-Shirazi, Akram Hasani Zonoozi, Hosein Haghi, Malihe Rabiee

The bimodal metallicity distribution of globular clusters (GCs) in massive galaxies implies two distinct sub-populations: metal-poor and metal-rich. Using the recent data of \textit{Gaia} we highlighted three distinct dissimilarities between metal-poor and metal-rich GCs in the Milky Way (MW). Half-mass (light) radii of metal-poor GCs exhibit, on average, $\

Subhaditya Bhattacharya, Lipika Kolay, Dipankar Pradhan

More than one dark sector particle transforming under the same symmetry provides one stable dark matter (DM) component which undergoes co-annihilation with the heavier particle(s) decaying to DM. Specific assumptions on the kinematics and on the coupling parameters may render the heavier component(s) stable and contribute as DM. The choices of the charges of

Giorgio Mentasti, Carlo R. Contaldi

We introduce a novel approach for detecting gravitational waves through their influence on the shape of resolved astronomical objects. This method, complementary to pulsar timing arrays and astrometric techniques, explores the time-dependent distortions caused by gravitational waves on the shapes of celestial bodies, such as galaxies or any resolved extended

Daniel Hey, John Tonry, Benjamin Shappee, Daniel Huber

Period-luminosity relations of long period variables (LPVs) are a powerful tool to map the distances of stars in our galaxy, and are typically calibrated using stars in the Large Magellanic Cloud (LMC). Recent results demonstrated that these relations show a strong dependence on the amplitude of the variability, which can be used to greatly improve distance

Honghua Chen, Yushi Lan, Yongwei Chen, Yifan Zhou

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing explicit spatial transformations or relying on implicit latent optimization within limited-capacity 3D generative models, fa

Chin-Yang Lin, Chung-Ho Wu, Chang-Han Yeh, Shih-Han Yen

Neural Radiance Fields (NeRF) face significant challenges in extreme few-shot scenarios, primarily due to overfitting and long training times. Existing methods, such as FreeNeRF and SparseNeRF, use frequency regularization or pre-trained priors but struggle with complex scheduling and bias. We introduce FrugalNeRF, a novel few-shot NeRF framework that levera

Lingyu Li, Yixu Wang, Haiquan Zhao, Shuqi Kong

With large language models (LLMs) increasingly deployed as cognitive engines for AI agents, the reliability and effectiveness critically hinge on their intrinsic epistemic agency, which remains understudied. Epistemic agency, the ability to flexibly construct, adapt, and monitor beliefs about dynamic environments, represents a base-model-level capacity indep

M. M. Arora, L. Balogh, C. Beaufort, A. Brossard

Spherical proportional counters (SPCs) are gaseous particle detectors sensitive to single ionization electrons in their target media, with large detector volumes and low background rates. The $\mbox{NEWS-G}$ collaboration employs this technology to search for low-mass dark matter, having previously performed searches with detectors at the Laboratoire Souterr

Jesse C. Hoke, Yifan Li, Yuwen Hu, Julian May-Mann

In twisted van der Waals materials, local atomic relaxation can alter the underlying electronic structure. Characterizing lattice reconstruction and its susceptibility to strain is essential for understanding emergent electronic states, especially in multilayers in which interference between moir\'e lattices yields larger supermoir\'e patterns whose energy i

Shuangrui Ding, Rui Qian, Xiaoyi Dong, Pan Zhang

The Segment Anything Model 2 (SAM 2) has emerged as a powerful foundation model for object segmentation in both images and videos, paving the way for various downstream video applications. The crucial design of SAM 2 for video segmentation is its memory module, which prompts object-aware memories from previous frames for current frame prediction. However, it

Michael S. Ryoo, Honglu Zhou, Shrikant Kendre, Can Qin

We present xGen-MM-Vid (BLIP-3-Video): a multimodal language model for videos, particularly designed to efficiently capture temporal information over multiple frames. BLIP-3-Video takes advantage of the 'temporal encoder' in addition to the conventional visual tokenizer, which maps a sequence of tokens over multiple frames into a compact set of visual tokens

Xi Liu, Chaoyi Zhou, Siyu Huang

Novel-view synthesis aims to generate novel views of a scene from multiple input images or videos, and recent advancements like 3D Gaussian splatting (3DGS) have achieved notable success in producing photorealistic renderings with efficient pipelines. However, generating high-quality novel views under challenging settings, such as sparse input views, remains

Haomu Yuan, Christopher K. Long, Hugo V. Lepage, Crispin H. W. Barnes

We present a quantum algorithm for portfolio optimisation. Specifically, We present an end-to-end quantum approximate optimisation algorithm (QAOA) to solve the discrete global minimum variance portfolio (DGMVP) model. This model finds a portfolio of risky assets with the lowest possible risk contingent on the number of traded assets being discrete. We provi

Farid Thaalba, Nicola Franchini, Miguel Bezares, Thomas P. Sotiriou

We study spherical evolution in scalar-Gauss-Bonnet gravity with additional Ricci coupling and use the gauge-invariant approach of Ref.~\cite{Reall:2021voz} to track well-posedness. Our results show that loss of hyperbolicity when it occurs, is due to the behaviour of physical degrees of freedom. They provide further support to the idea that this behaviour c

Yvan Klaver, Randy te Morsche, Roel A. Botter, Batoul Hashemi

Seamlessly integrating stimulated Brillouin scattering (SBS) in a low-loss and mature photonic integration platform remains a complicated task. Virtually all current approaches fall short in simultaneously achieving strong SBS, low losses, and technological scalability. In this work we incorporate stong SBS into a standard silicon nitride platform by a simpl

Fraser Douglas, Mona Pei, Calvin Kuo

This study investigates the impact of electrode shift and sensor reapplication on common surface electromyography (sEMG) features in lower limb muscles, factors which have, thus far, precluded clinicians from being able to attribute inter-session changes in sEMG signal properties to physiological changes in patients under the context of stroke recovery monit

Zhangwei Gao, Zhe Chen, Erfei Cui, Yiming Ren

Multimodal large language models (MLLMs) have demonstrated impressive performance in vision-language tasks across a broad spectrum of domains. However, the large model scale and associated high computational costs pose significant challenges for training and deploying MLLMs on consumer-grade GPUs or edge devices, thereby hindering their widespread applicatio

Gengshan Yang, Andrea Bajcsy, Shunsuke Saito, Angjoo Kanazawa

We present Agent-to-Sim (ATS), a framework for learning interactive behavior models of 3D agents from casual longitudinal video collections. Different from prior works that rely on marker-based tracking and multiview cameras, ATS learns natural behaviors of animal and human agents non-invasively through video observations recorded over a long time-span (e.g.

Quintino Francesco Lotito, Alberto Vendramini, Alberto Montresor, Federico Battiston

Many real-world complex systems are characterized by non-pairwise -- higher-order -- interactions among system's units, and can be effectively modeled as hypergraphs. Directed hypergraphs distinguish between source and target sets within each hyperedge, and allow to account for the directional flow of information between nodes. Here, we provide a framework t

Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu

The success of autoregressive (AR) language models in text generation has inspired the computer vision community to adopt Large Language Models (LLMs) for image generation. However, considering the essential differences between text and image modalities, the design space of language models for image generation remains underexplored. We observe that image tok

Maosong Cao, Alexander Lam, Haodong Duan, Hongwei Liu

Efficient and accurate evaluation is crucial for the continuous improvement of large language models (LLMs). Among various assessment methods, subjective evaluation has garnered significant attention due to its superior alignment with real-world usage scenarios and human preferences. However, human-based evaluations are costly and lack reproducibility, makin

Sukanya Patra, Souhaib Ben Taieb

Industrial anomaly detection is crucial for quality control and predictive maintenance, but it presents challenges due to limited training data, diverse anomaly types, and external factors that alter object appearances. Existing methods commonly detect structural anomalies, such as dents and scratches, by leveraging multi-scale features from image patches ex

Ayisha M Ashruf, Ankush Bhaskar, C Vineeth, Tarun Kumar Pant

This study investigates the orbital decay and subsequent reentries of 12 Starlink satellites from 16 April to 15 May 2024. By examining Two-Line Element data, we observed a significant increase in orbital decay following the geomagnetic storm on 10 May 2024, consistent with expectations of increased thermospheric density. An unexpected increase in decay rate

Nick Rittler, Kamalika Chaudhuri

Generative models at times produce "invalid" outputs, such as images with generation artifacts and unnatural sounds. Validity-constrained distribution learning attempts to address this problem by requiring that the learned distribution have a provably small fraction of its mass in invalid parts of space -- something which standard loss minimization does not

Vlad Cărare, Volker L. Deringer, Gábor Csányi

Training interatomic potentials for spin-polarized systems continues to be a difficult task for the molecular modeling community. In this note, a proof-of-concept, random initial spin committee approach is proposed for obtaining the ground state of spin-polarized systems with a controllable degree of accuracy. The approach is tested on two toy models of elem

Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani

Large Language Models (LLMs) suffer from hallucinations, referring to the non-factual information in generated content, despite their superior capacities across tasks. Meanwhile, knowledge editing has been developed as a new popular paradigm to correct erroneous factual knowledge encoded in LLMs with the advantage of avoiding retraining from scratch. However

Nikolas P. Breuckmann, Margarita Davydova, Jens N. Eberhardt, Nathanan Tantivasadakarn

We take initial steps towards a general framework for constructing logical gates in general quantum CSS codes. Viewing CSS codes as cochain complexes, we observe that cohomology invariants naturally give rise to diagonal logical gates. We show that such invariants exist if the quantum code has a structure that relaxes certain properties of a differential gra

Benjamin Grimmer, Kevin Shu, Alex L. Wang

Recent works by Altschuler and Parrilo and the authors have shown that it is possible to accelerate the convergence of gradient descent on smooth convex functions, even without momentum, just by picking special stepsizes. In this paper, we provide a general theory for composing stepsize schedules capturing all recent advances in this area and more. We propos

Juan Cruz-Martinez, Aaron Jansen, Gijs van Oord, Tanjona R. Rabemananjara

Deep learning models are defined in terms of a large number of hyperparameters, such as network architectures and optimiser settings. These hyperparameters must be determined separately from the model parameters such as network weights, and are often fixed by ad-hoc methods or by manual inspection of the results. An algorithmic, objective determination of hy

Santhosh Karnik, Anna Veselovska, Mark Iwen, Felix Krahmer

We provide a rigorous analysis of implicit regularization in an overparametrized tensor factorization problem beyond the lazy training regime. For matrix factorization problems, this phenomenon has been studied in a number of works. A particular challenge has been to design universal initialization strategies which provably lead to implicit regularization in

Emmanouil Zaranis, Nuno M. Guerreiro, André F. T. Martins

Large language models (LLMs) have achieved state-of-the-art performance in machine translation (MT) and demonstrated the ability to leverage in-context learning through few-shot examples. However, the mechanisms by which LLMs use different parts of the input context remain largely unexplored. In this work, we provide a comprehensive analysis of context utili

Shalev Ben-David, Srijita Kundu

We study the query complexity analogue of the class TFNP of total search problems. We give a way to convert partial functions to total search problems under certain settings; we also give a way to convert search problems back into partial functions. As an application, we give new separations for degree-like measures. We give an exponential separation between

David Pomaranski, Ryo Ito, Ngoc Han Tu, Arne Ludwig

Standard approaches to quantum computing require significant overhead to correct for errors. The hardware size for conventional quantum processors in solids often increases linearly with the number of physical qubits, such as for transmon qubits in superconducting circuits or electron spin qubits in quantum dot arrays. While photonic circuits based on flying

Denis Bouyssou, Thierry Marchant, Marc Pirlot

We establish one-to-one correspondences between maximal antichains in products of two finite linear orders and other mathematical objects, such as certain alignments of two strings, walks on a grid, lattice paths, words of two or three letters. Leaning on these correspondences, we gather what is known about the number of maximal antichains in products of two

Nishat Raihan, Mohammed Latif Siddiq, Joanna C. S. Santos, Marcos Zampieri

Large language models (LLMs) are becoming increasingly better at a wide range of Natural Language Processing tasks (NLP), such as text generation and understanding. Recently, these models have extended their capabilities to coding tasks, bridging the gap between natural languages (NL) and programming languages (PL). Foundational models such as the Generative

Sunny Gupta, Manoj N. Mattur, Boris I. Yakobson

Materials with large unidirectional Rashba spin-orbit coupling (SOC), resulting in persistent-spin helix states with small spin-precession length, are critical for advancing spintronics. We demonstrate a design principle achieving it through specific undulations of 2D materials. Analytical model and first-principles calculations reveal that bending-induced a

Savithri H. Ezhikode, Hema Anilkumar, R. Arun, Blesson Mathew

Weak-line T Tauri stars (WTTS) exhibit X-ray flares, likely resulting from magnetic reconnection that heats the stellar plasma to very high temperatures. These flares are difficult to identify through targeted observations. Here, we report the serendipitous detection of the brightest X-ray flaring state of KM Ori in the eROSITA DR1 survey. Observations from

Kishan Srinivasan, Heath Hofmann, Jing Sun

This paper proposes a nonlinear magnetics model for Permanent Magnet Synchronous Machines (PMSMs) that accurately captures the effects of magnetic saturation in the machine iron and variations in rotor temperature on the permanent magnet excitation. The proposed model considers the permanent magnet as a current source rather than the more commonly used flux-

Samrajya Thapa, Koushik Howlader, Subhankar Bhattacharjee, Wei le

In this paper, we introduce a novel Multi-Modal Contrastive Pre-training Framework that synergistically combines X-rays, electrocardiograms (ECGs), and radiology/cardiology reports. Our approach leverages transformers to encode these diverse modalities into a unified representation space, aiming to enhance diagnostic accuracy and facilitate comprehensive pat

G. A. Nketiah, M. R. Sunoqrot, E. Sandsmark, S. Langørgen

Objective: To develop and evaluate a deep radiomics model for clinically significant prostate cancer (csPCa, grade group >= 2) detection and compare its performance to Prostate Imaging Reporting and Data System (PI-RADS) assessment in a multicenter cohort. Materials and Methods: This retrospective study analyzed biparametric (T2W and DW) prostate MRI sequenc

Yihuan Mao, Yipeng Kang, Peilun Li, Ning Zhang

As large language model (LLM) agents increasingly integrate into our infrastructure, their robust coordination and message synchronization become vital. The Byzantine Generals Problem (BGP) is a critical model for constructing resilient multi-agent systems (MAS) under adversarial attacks. It describes a scenario where malicious agents with unknown identities

Yuxuan Cai, Jiangning Zhang, Haoyang He, Xinwei He

The success of Large Language Models (LLMs) has inspired the development of Multimodal Large Language Models (MLLMs) for unified understanding of vision and language. However, the increasing model size and computational complexity of large-scale MLLMs (l-MLLMs) limit their use in resource-constrained scenarios. Although small-scale MLLMs (s-MLLMs) are design

Zhikun Xu, Ming Shen, Jacob Dineen, Zhaonan Li

We introduce thoughts of words (ToW), a novel training-time data-augmentation method for next-word prediction. ToW views next-word prediction as a core reasoning task and injects fine-grained thoughts explaining what the next word should be and how it is related to the previous contexts in pre-training texts. Our formulation addresses two fundamental drawbac

Yannis Angelopoulos, Christoph Kehle, Ryan Unger

In this paper, we prove the codimension-one nonlinear asymptotic stability of the extremal Reissner-Nordstr\"om family of black holes in the spherically symmetric Einstein-Maxwell-neutral scalar field model, up to and including the event horizon. More precisely, we show that there exists a teleologically defined, codimension-one "submanifold" $\mathfrak M_\m

Domagoj Bradač, Micha Christoph

A folklore result attributed to P\'olya states that there are $(1 + o(1))2^{\binom{n}{2}}/n!$ non-isomorphic graphs on $n$ vertices. Given two graphs $G$ and $H$, we say that $G$ is a unique subgraph of $H$ if $H$ contains exactly one subgraph isomorphic to $G$. For an $n$-vertex graph $H$, let $f(H)$ be the number of non-isomorphic unique subgraphs of $H$ d

Ryan Li, Yanzhe Zhang, Diyi Yang

Sketches are a natural and accessible medium for UI designers to conceptualize early-stage ideas. However, existing research on UI/UX automation often requires high-fidelity inputs like Figma designs or detailed screenshots, limiting accessibility and impeding efficient design iteration. To bridge this gap, we introduce Sketch2Code, a benchmark that evaluate

Tina Radvand, Alireza Talebpour, Homa Khosravian

Electric vehicles (EVs) play a significant role in enhancing the sustainability of transportation systems. However, their widespread adoption is hindered by inadequate public charging infrastructure, particularly to support long-distance travel. Identifying optimal charging station locations in large transportation networks presents a well-known NP-hard comb

Krishna Shende, Arvind, Kavita Dorai

Thermodynamic uncertainty relations (TURs) arise from the bounds on fluctuations of thermodynamics quantities during a non-equilibrium process and they impose constraints on the corresponding process. We experimentally implement a quantum SWAP engine on a nuclear magnetic resonance setup and demonstrate that a Gibbs thermal state can be prepared in two diffe

Xinze Li, Hanbin Wang, Zhenghao Liu, Shi Yu

Pretrained language models have shown strong effectiveness in code-related tasks, such as code retrieval, code generation, code summarization, and code completion tasks. In this paper, we propose COde assistaNt viA retrieval-augmeNted language model (CONAN), which aims to build a code assistant by mimicking the knowledge-seeking behaviors of humans during co

Georg Stettinger

In this short paper we want to generalize some recent concepts related to stubs in open string field theory. First, we modify the auxiliary field method by Erbin and Firat [#Erbin2023] to non-BPZ even sliver frame stubs. We then also show that the construction is consistent at the full quantum level without any additional assumptions. Finally, we apply the m

Alexander Krentsel, Peter Schafhalter, Joseph E. Gonzalez, Sylvia Ratnasamy

Prevailing wisdom asserts that one cannot rely on the cloud for critical real-time control systems like self-driving cars. We argue that we can, and must. Following the trends of increasing model sizes, improvements in hardware, and evolving mobile networks, we identify an opportunity to offload parts of time-sensitive and latency-critical compute to the clo

Guillem Cazassus, Alexander Hock, Thibaut Mazuir

We introduce a new family of oriented manifolds with boundaries called the forest biassociahedra and forest bimultiplihedra, generalizing the standard biassociahedra. They are defined as moduli spaces of ascending-descending biforests and are expected to act as parameter spaces for operations defined on Morse and Floer chains in the context of compact Lie gr

Joonas Ilmavirta, Antti Kykkänen, Matti Lassas, Teemu Saksala

We prove that the reconstruction of a certain type of length spaces from their travel time data on a closed subset is Lipschitz stable. The travel time data is the set of distance functions from the entire space, measured on the chosen closed subset. The case of a Riemannian manifold with boundary with the boundary as the measurement set appears is a classic

Ankit Gupta, P. S. Burada

We numerically investigate the diffusive behavior of active Brownian particles in a two-dimensional confined channel filled with soft obstacles, whose softness is controlled by a parameter $K$. Here, active particles are subjected to external bias $F$. Particle diffusion is influenced by entropic barriers that arise due to variations in the shape of the chos

Valentyn Boreiko, Alexander Panfilov, Vaclav Voracek, Matthias Hein

A plethora of jailbreaking attacks have been proposed to obtain harmful responses from safety-tuned LLMs. These methods largely succeed in coercing the target output in their original settings, but their attacks vary substantially in fluency and computational effort. In this work, we propose a unified threat model for the principled comparison of these metho

Parinthapat Pengpun, Krittamate Tiankanon, Amrest Chinkamol, Jiramet Kinchagawat

Machine translation (MT) in the medical domain plays a pivotal role in enhancing healthcare quality and disseminating medical knowledge. Despite advancements in English-Thai MT technology, common MT approaches often underperform in the medical field due to their inability to precisely translate medical terminologies. Our research prioritizes not merely impro

Marco Giordano, Christoph Leitner, Christian Vogt, Luca Benini

This work explores the feasibility of employing ultrasound (US) US technology in a wrist-worn IoT device for low-power, high-fidelity heart-rate (HR) extraction. US offers deep tissue penetration and can monitor pulsatile arterial blood flow in large vessels and the surrounding tissue, potentially improving robustness and accuracy compared to PPG. We present

Md Tahmidul Alam, Swarnav Mukhopadhyay, Md Mobinul Haque, Shubhra S. Pasayat

More than 3 kV breakdown voltage was demonstrated in monolithic bidirectional GaN HEMTs for the first time having potential applications in 1200V or 1700V-class novel power converters. The on resistance of the fabricated transistors was ~20 ohm.mm or ~11 mili ohm.cm^2. Breakdown voltage was optimized by utilizing two field plates in either side of the transi

Luya Wang

This note provides the first example of a nontrivial connected component of the space of symplectic structures standard at infinity in dimension four.

Hao Peng, Xin Lv, Yushi Bai, Zijun Yao

Knowledge distillation (KD) aims to transfer knowledge from a large teacher model to a smaller student model. Previous work applying KD in the field of large language models (LLMs) typically focused on the post-training phase, where the student LLM learns directly from instructions and corresponding responses generated by the teacher model. In this paper, we

Florian Huber, Karin Klieber, Massimiliano Marcellino, Luca Onorante

This paper analyzes nonlinearities in the international transmission of financial shocks originating in the US. To do so, we develop a flexible nonlinear multi-country model. Our framework is capable of producing asymmetries in the responses to financial shocks for shock size and sign, and over time. We show that international reactions to US-based financial

R. N. Balasanyan, S. G. Minasyan, I. G. Grigoryan, V. S. Arakelyan

The results of studies on the properties of ordinary and heavy water subjected to sharp mechanical impacts at acoustic repetition frequency are presented. Experimental evidence for the phenomenon of acoustically induced nuclear processes in water is provided, supported by direct measurements of radiation emission and the formation of new elements, which cann

L. I. Zablocki, L. A. Bugnon, M. Gerard, L. Di Persia

Inspired by the success of large language models (LLM) for DNA and proteins, several LLM for RNA have been developed recently. RNA-LLM uses large datasets of RNA sequences to learn, in a self-supervised way, how to represent each RNA base with a semantically rich numerical vector. This is done under the hypothesis that obtaining high-quality RNA representati

Nishat Raihan

This technical report presents CiteClick, a browser extension designed to monitor and track Google Scholar citation counts for multiple researchers in real-time. We discuss the motivation behind the tool, its key features, implementation details, and potential impact on the academic community. The report covers installation procedures, usage guidelines, and

Ankit Anand, Ruben Campos Delgado, Daris Samart

This paper investigates the massive gauge field within spacetime context from a $\mathbb{Z}_2$ quotient of the constant curvature black hole. We investigate how the matter field's back reaction affects the spacetime geometry, considering perturbations in the metric up to the first order. The stress-energy tensor's expectation value can be precisely calculate

Yeongtae Jang, Seokwoo Kim, Dongwoo Lee, Eunho Kim

We theoretically investigate and experimentally demonstrate that genuine bound states in the continuum (BICs) -- polarization-protected BICs -- can be completely localized within finite-size solid resonators. This bound mode is realized in a highly tunable mechanical system made of cylindrical granular crystals, where tunning the contact boundaries enables t

Junjie Oscar Yin, Alexander M. Rush

Data selection can reduce the amount of training data needed to finetune LLMs; however, the efficacy of data selection scales directly with its compute. Motivated by the practical challenge of compute-constrained finetuning, we consider the setting in which both the cost of selecting data and training are budgeted for. We first formalize the problem of data

Kumar Manas, Stefan Zwicklbauer, Adrian Paschke

Autonomous agents often face the challenge of interpreting uncertain natural language instructions for planning tasks. Representing these instructions as Linear Temporal Logic (LTL) enables planners to synthesize actionable plans. We introduce CoT-TL, a data-efficient in-context learning framework for translating natural language specifications into LTL repr

Hitansh Shah, Mauricio Hippert, Jorge Noronha, Claudia Ratti

We propose a new method to investigate the existence and location of the conjectured high-temperature critical point of strongly interacting matter via contours of constant entropy density. By approximating these lines as a power series in the baryon chemical potential $\mu_B$, one can extrapolate them from first-principle results at zero net-baryon density,