October 2024 arXiv papers — page 70

Peter Garraghan, John Hutchinson, Adrian Friday

As Information and Communication Technology (ICT) use has become more prevalent, there has been a growing concern in how its associated greenhouse gas emissions will impact the climate. Estimating such ICT emissions is a difficult undertaking due to its complexity, its rapidly changing nature, and the lack of accurate and up-to-date data on individual stakeh

Frode S. Strand, Simon P. Cooil, Quinn T. Campbell, John J. Flounders

We investigate the electronic structure of high-density layers of Sb dopants in a silicon host, so-called Si:Sb $\delta$-layers. We show that, in spite of the known challenges in producing highly confined Sb $\delta$-layers, sufficient confinement is created such that the lowest conduction band states ($\Gamma$ states, studied in depth in other silicon $\del

Daegeun Jo, Dongwook Go, Yuriy Mokrousov, Peter M. Oppeneer

Altermagnets are magnetic materials with antiferromagnetic spin ordering but exhibit ferromagnetic properties. Understanding the microscopic origin of the latter is a central problem. Ferromagnet-like properties such as the anomalous Hall effect are linked with weak ferromagnetism, whose microscopic origin in altermagnets remains unclear however. We show the

Koustav Ghosal, Arun Singh, Samir Malakar, Shalivahan Srivastava

Deep learning (DL) methods have emerged as a powerful tool for the inversion of geophysical data. When applied to field data, these models often struggle without additional fine-tuning of the network. This is because they are built on the assumption that the statistical patterns in the training and test datasets are the same. To address this, we propose a DL

Zheyuan Zhang, Fengyuan Hu, Jayjun Lee, Freda Shi

Spatial expressions in situated communication can be ambiguous, as their meanings vary depending on the frames of reference (FoR) adopted by speakers and listeners. While spatial language understanding and reasoning by vision-language models (VLMs) have gained increasing attention, potential ambiguities in these models are still under-explored. To address th

Sascha Holl

We investigate the concatenation of Markov processes. Our primary concern is to utilize processes constructed in this manner for Monte Carlo integration. To enable this using conventional methods, it is essential to demonstrate the Markov property and invariance with respect to a given target distribution. We provide mild sufficient conditions for this. Our

Paulo F. Bedaque, Hersh Kumar, Andy Sheng

We apply a variational Ansatz based on neural networks to the problem of spin-$1/2$ fermions in a harmonic trap interacting through a short distance potential. We showed that standard machine learning techniques lead to a quick convergence to the ground state, especially in weakly coupled cases. Higher couplings can be handled efficiently by increasing the s

Amirhossein Afsharrad, Parisa Oftadeh, Ahmadreza Moradipari, Sanjay Lall

In this study, we explore a collaborative multi-agent stochastic linear bandit setting involving a network of $N$ agents that communicate locally to minimize their collective regret while keeping their expected cost under a specified threshold $\tau$. Each agent encounters a distinct linear bandit problem characterized by its own reward and cost parameters,

J. E. Méndez-Delgado, E. D. Skillman, E. Aver, C. Morisset

The physics of recombination lines (RLs) in the HeI singlet system is expected to be relatively simple, supported by accurate atomic models. We examine the intensities of HeI singlets $\lambda \lambda$3614, 3965, 5016, 6678, 7281 and the triplet HeI $\lambda$5876 in various types of ionized nebulae and compare them with theoretical predictions to test the va

Rao Li

Let $G = (V, E)$ be a graph. We define matrices $M(G; \alpha, \beta)$as $\alpha D + \beta A$, where $\alpha$, $\beta$ are real numbers such that $(\alpha, \beta) \neq (0, 0)$ and $D$ and $A$ are the diagonal matrix and adjacency matrix of $G$, respectively. Using the largest and smallest eigenvalues of $M(G; \alpha, \beta)$ with $\alpha \geq \beta > 0$, we p

Joseph W. Iverson, John Jasper, Dustin G. Mixon

We introduce a new infinite family of $d\times 2d$ equiangular tight frames. Many matrices in this family consist of two $d\times d$ circulant blocks. We conjecture that such equiangular tight frames exist for every $d$. We show that our conjecture holds for $d\leq 165$ by a computer-assisted application of a Newton-Kantorovich theorem. In addition, we suppl

Gabriel Gray, David Hovey, Brandt Kronholm, Emily Payne

Euler's classic partition identity states that the number of partitions of $n$ into odd parts equals the number of partitions of $n$ into distinct parts. We develop a new generalization of this identity, which yields a previous generalization of Franklin as a special case, and prove an accompanying Beck-type companion identity.

Ryuma Nakahata, Shehtab Zaman, Mingyuan Zhang, Fake Lu

Ptychography is a computational method of microscopy that recovers high-resolution transmission images of samples from a series of diffraction patterns. While conventional phase retrieval algorithms can iteratively recover the images, they require oversampled diffraction patterns, incur significant computational costs, and struggle to recover the absolute ph

D. S. Cabral, L. A. S. Evangelista, J. C. R. de Souza, L. H. A. R. Ferreira

This paper addresses Yukawa theory, focusing on the scattering between two identical fermions mediated by an intermediate scalar boson, considering the effects of thermal contributions and Lorentz symmetry breaking. Temperature is introduced into the theory through the TFD formalism, while Lorentz violation arises from a background tensor coupled to the kine

Bradley McDanel

Large language models typically generate tokens autoregressively, using each token as input for the next. Recent work on Speculative Decoding has sought to accelerate this process by employing a smaller, faster draft model to more quickly generate candidate tokens. These candidates are then verified in parallel by the larger (original) verify model, resultin

Klara Baś, Christian Lambert, John Ashburner

Quantitative magnetic resonance imaging (qMRI) allows images to be compared across sites and time points, which is particularly important for assessing long-term conditions or for longitudinal studies. The multiparametric mapping (MPM) protocol is used to acquire images with conventional clinical contrasts, namely PD-, T1-, and MT-weighted volumes. Through m

Dongsu Lee, Minhae Kwon

Understanding cognitive processes in multi-agent interactions is a primary goal in cognitive science. It can guide the direction of artificial intelligence (AI) research toward social decision-making in multi-agent systems, which includes uncertainty from character heterogeneity. In this paper, we introduce an episodic future thinking (EFT) mechanism for a r

Yutong Zhao, Lu Xiao, Chenhao Wei, Rick Kazman

Software architecture is the foundation of a system's ability to achieve various quality attributes, including software performance. However, there lacks comprehensive and in-depth understanding of why and how software architecture and performance analysis are integrated to guide related future research. To fill this gap, this paper presents a systematic map

Jingxu Wu, Congyu Li, Chenjia Li, Polyakova Polina

We investigate the phenomenon of CP violation in the weak decay of bottom hadrons (B mesons) through comprehensive theoretical analysis and mathematical derivations. We analyze the fundamental mechanisms of B meson decay, emphasizing the interplay between CP symmetry breaking and the contributions from the quark level. By examining the role of the weak Hamil

Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen

Model-Driven Engineering (MDE) has seen significant advancements with the integration of Machine Learning (ML) and Deep Learning (DL) techniques. Building upon the groundwork of previous investigations, our study provides a concise overview of current Language Large Models (LLMs) applications in MDE, emphasizing their role in automating tasks like model repo

V. A. Boehm, N. K. Lewis, C. E. Fairman, S. E. Moran

Ultraviolet wavelengths offer unique insights into aerosols in exoplanetary atmospheres. However, only a handful of exoplanets have been observed in the ultraviolet to date. Here, we present the ultraviolet-visible transmission spectrum of the inflated hot Jupiter WASP-127b. We observed one transit of WASP-127b with WFC3/UVIS G280 as part of the Hubble Ultra

C. Tyler Diggans, Abd AlRahman R. AlMomani

The recent introduction of geometric partition entropy brought a new viewpoint to non-parametric entropy quantification that incorporated the impacts of informative outliers, but its original formulation was limited to the context of a one-dimensional state space. A generalized definition of geometric partition entropy is now provided for samples within a bo

Tomas Espana, Victor Le Coz, Matteo Smerlak

Markowitz's optimal portfolio relies on the accurate estimation of correlations between asset returns, a difficult problem when the number of observations is not much larger than the number of assets. Using powerful results from random matrix theory, several schemes have been developed to "clean" the eigenvalues of empirical correlation matrices. By contrast

Paul Regazzi, Marc Leonetti

Drop deformation in shear flow is determined up to second order theory in Ca while considering kinetic effects on surfactants distributions in steady state. Surfactants inside the drop are adsorbed faster than those on the surface leading to an increase in total surfactants concentration on the semi-minor axis of the ellipsoidal droplet. New expressions for

Jibeom Seo, Beom Jun Kim

We propose a simple model to explore an educational phenomenon where the correct answer emerges from group discussion. We construct our model based on several plausible assumptions: (i) We tend to follow peers' opinions. However, if a peer's opinion is too different from yours, you are not much influenced. In other words, your opinion tends to align with pee

Miguel Contreras, Sumit Kapoor, Jiaqing Zhang, Andrea Davidson

Delirium is an acute confusional state that has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection of this condition could lead to more timely interventions and improved health outcomes. While artificial intelligence (AI) models have shown great potential for ICU delirium prediction using structured electronic health

Stefano Boccelli, Shane R. Carberry Mogan, Robert E. Johnson, Orenthal J. Tucker

Fractures and vents in the ice crust of Europa, exposing the sub-surface ocean or liquid-water inclusions to the vacuum, might be responsible for the generation of water-vapor plumes. During its passage through the ice, the plume vapor is expected to partially condense on the cold ice walls. Together with other effects (water spillage, compression forces, et

Sathvik Prasad, Aleksandr Nahapetyan, Bradley Reaves

Telephone spam has been among the highest network security concerns for users for many years. In response, industry and government have deployed new technologies and regulations to curb the problem, and academic and industry researchers have provided methods and measurements to characterize robocalls. Have these efforts borne fruit? Are the research characte

Thomas A. Trainor

In this study fixed-target spectra obtained by the Chicago-Princeton (C-P) collaboration at Fermilab in the mid seventies are analyzed with a two-component spectrum model (TCM) that has been applied successfully to a number of collision systems at the RHIC and LHC in the past. It is from C-P data that the Cronin effect was first inferred. TCM analysis leads

Charalambos G. Makridakis, Aaron Pim, Tristan Pryer

In this work, we present a numerical solver for optimal control problems constrained by linear and semi-linear second-order elliptic PDEs. The approach is based on recasting the problem and includes an extension of Uzawa's algorithm to build approximating sequences for these constrained optimal control problems. We prove strong convergence of the iterative s

Rohan Sukumaran, Aarash Feizi, Adriana Romero-Sorian, Golnoosh Farnadi

Recent advances in parameter-efficient fine-tuning methods, such as Low Rank Adaptation (LoRA), have gained significant attention for their ability to efficiently adapt large foundational models to various downstream tasks. These methods are appreciated for achieving performance comparable to full fine-tuning on aggregate-level metrics, while significantly r

Gefen Dawidowicz, Elad Hirsch, Ayellet Tal

The paper proposes a novel evaluation metric for automatic medical report generation from X-ray images, VLScore. It aims to overcome the limitations of existing evaluation methods, which either focus solely on textual similarities, ignoring clinical aspects, or concentrate only on a single clinical aspect, the pathology, neglecting all other factors. The key

Naim Shandi, Jason M. Merlo, Jeffrey A. Nanzer

Phase, time, and frequency coordination are crucial for the coherent operation of distributed antenna arrays. This paper demonstrates a high accuracy decentralized time synchronization method for arrays with dynamic connectivity. To overcome challenges such as alteration in network topology, system scaling, and single- or multiple-node failures, we present a

Advait Deshmukh, Ashwin Umadi, Dananjay Srinivas, Maria Leonor Pacheco

Due to their capacity to acquire world knowledge from large corpora, pre-trained language models (PLMs) are extensively used in ultra-fine entity typing tasks where the space of labels is extremely large. In this work, we explore the limitations of the knowledge acquired by PLMs by proposing a novel heuristic to approximate the pre-training distribution of e

Chika Maduabuchi, Ericmoore Jossou, Matteo Bucci

High-speed video (HSV) segmentation is essential for analyzing dynamic physical processes in scientific and industrial applications, such as boiling heat transfer. Existing models like U-Net struggle with generalization and accurately segmenting complex bubble formations. We present VideoSAM, a specialized adaptation of the Segment Anything Model (SAM), fine

Huan Zhao, Saban Hus, Jinli Chen, Xiaodong Yan

The development of robust and efficient single photon emitters (SPEs) at telecom wavelengths is critical for advancements in quantum information science. Two-dimensional (2D) materials have recently emerged as promising sources for SPEs, owing to their high photon extraction efficiency, facile coupling to external fields, and seamless integration into photon

Teimour Hosseinalizadeh, Nima Monshizadeh

In the recent years, we have observed three significant trends in control systems: a renewed interest in data-driven control design, the abundance of cloud computational services and the importance of preserving privacy for the system under control. Motivated by these factors, this work investigates privacy-preserving outsourcing for the design of a stabiliz

Vanni Noferini, Spyridon Vrontos, Ryan Wood

We discuss efficient computation of $f$-centralities and nonbacktracking centralities for time-evolving networks with nonnegative weights. We present a node-level formula for its combinatorially exact computation which proves to be more tractable than previously existing formulae at edge-level for dense networks. Additionally, we investigate the impact of th

Aditya Vikram Singh, Ethan Rathbun, Emma Graham, Lisa Oakley

Recent advances in multi-agent reinforcement learning (MARL) have created opportunities to solve complex real-world tasks. Cybersecurity is a notable application area, where defending networks against sophisticated adversaries remains a challenging task typically performed by teams of security operators. In this work, we explore novel MARL strategies for bui

Tatiana Latychevskaia

In this study, quantitative criteria for reconstruction of objects from their hologram and diffraction patterns, and in particular for the phase objects in digital holography, are derived. The criteria that allow distinguishing the hologram and diffraction pattern are outlined. Gabor derived his criterion for objects suitable for holography based on the cond

Kunal Talwar

A Private Repetition algorithm takes as input a differentially private algorithm with constant success probability and boosts it to one that succeeds with high probability. These algorithms are closely related to private metaselection algorithms that compete with the best of many private algorithms, and private hyperparameter tuning algorithms that compete w

Alfredo Amador-Portes, Abigail García-Pérez, Vahram Chavushyan, Victor M. Patiño-Álvarez

The flat spectrum radio quasar PKS 1510-089 is one of the most active blazars in $\gamma$-rays, exhibiting phases of very high activity. This study investigates its variability over a decade across a wide range of wavelengths, from radio to $\gamma$-rays. Utilizing the non-thermal dominance parameter, we analyze the H$\beta$, H$\gamma$, and $\lambda5100\text

Akos Nagy, Yannis Spyridis, Gregory J Mills, Vasileios Argyriou

The paper introduces an innovative approach to industrial maintenance leveraging augmented reality (AR) technology, focusing on enhancing the user experience and efficiency. The shift from traditional to proactive maintenance strategies underscores the significance of maintenance in industrial systems. The proposed solution integrates AR interfaces, particul

Edward Hardy, Anton Sokolov, Henry Stubbs

We study supernova cooling constraints on new light scalars that mix with the Higgs, couple only to nucleons, or couple only to leptons. We show that in all these cases scalars with masses smaller than the plasma frequency in the supernova core are efficiently produced by resonant mixing with the in-medium longitudinal degree of freedom of the photon. The re

Michael Mazur, Margaret Campbell-Brown, Peter Brown, Denis Vida

The Canadian Automated Meteor Observatory (CAMO) mirror tracking system has been in operation since 2009 and has, to date, produced more than 20,000 two-station meteor observations at meter-level spatial and 10 ms temporal resolution. In 2020, a spectral tracking camera was added in parallel at one of the CAMO stations. To date, it has recorded the spectra o

Andrea Ottolini, Ray Chen

We analyze the mixing time of a popular shuffling machine known as the shelf shuffler. It is a modified version of a $2m$-handed riffle shuffle ($m=10$ in casinos) in which a deck of $n$ cards is split multinomially into $2m$ piles, the even-numbered piles are reversed, and then cards are dropped from piles proportionally to their sizes. We prove that $\frac

K. K. Kataria, P. Vishwakarma

We study a fractional birth-death process with state dependent birth and death rates. It is defined using a system of fractional differential equations that generalizes the classical birth-death process introduced by Feller (1939). We obtain the closed form expressions for its transient probabilities using Adomian decomposition method. In this way, we obtain

Zekun Jiang, Wei Dai, Qu Wei, Ziyuan Qin

Multi-channel EEG signals are commonly used for the diagnosis and assessment of diseases such as epilepsy. Currently, various EEG diagnostic algorithms based on deep learning have been developed. However, most research efforts focus solely on diagnosing and classifying current signal data but do not consider the prediction of future trends for early warning.

Alessandro Pini

We consider the four-dimensional $\mathcal{N}=2$ quiver gauge theory arising from a $\mathbb{Z}_2$ orbifold of $\mathcal{N}=4$ super Yang-Mills with gauge group $SU(2N)$. We study the integrated correlator between a half-BPS Wilson line and two Higgs branch operators of conformal dimension 2. Using supersymmetric localization, we resum the perturbative serie

Theo J. O'Neill, Alyssa A. Goodman, Juan D. Soler, Catherine Zucker

Clustered stellar feedback creates expanding voids in the magnetized interstellar medium known as superbubbles. Although theory suggests that superbubble expansion is influenced by interstellar magnetic fields, direct observational data on 3D superbubble magnetic field geometry is limited. The Sun's location inside the Local Bubble provides a unique opportun

Sudhir Pujahari, Neelam Saikia

The number of points on a certain one parameter family of algebraic surface over a finite field $\F_p$ can be expressed as $p^2+A_p(\lambda),$ where $A_p(\lambda)$ is a character sum and $\lambda$ is an element of the finite field $\F_p.$ In this paper, we study the distribution of the term $A_p(\lambda)$ as the surface varies over a large family of algebrai

Kristina Giesel, Viktoria Kabel, Wolfgang Wieland

Reference frames are crucial for describing local observers in general relativity. In quantum gravity, different proposals exist for how to treat reference frames. There are models with either classical or quantum reference frames. Recently, different choices appeared for investigating these possibilities at the level of the classical and quantum algebra of

M. Tanveer, R. K. Sharma, A. Quadir, M. Sajid

In the domain of machine learning, least square twin support vector machine (LSTSVM) stands out as one of the state-of-the-art models. However, LSTSVM suffers from sensitivity to noise and outliers, overlooking the SRM principle and instability in resampling. Moreover, its computational complexity and reliance on matrix inversions hinder the efficient proces

W. Osman, A. Sadek, M. R. Altahhan, C. Liu

The High Temperature Reactor Code Package provides sophisticated modeling and simulation capabilities for high temperature gas cooled reactors like the HTR-200 Modul. However, HCP currently lacks integrated methods for uncertainty quantification and sensitivity analysis. This work aims to couple HCP with the DAKOTA toolkit to enable UQ workflows for quantify

Xinyi Ling, Hanwen Du, Bo Peng, Zhihui Zhu

Leveraging multimodal data to drive breakthroughs in e-commerce applications through Multimodal Foundation Models (MFMs) is gaining increasing attention from the research community. However, there are significant challenges that hinder the optimal use of multimodal e-commerce data by foundation models: (1) the scarcity of large-scale, high-quality multimodal

Khashayar Gatmiry, Jon Schneider, Stefanie Jegelka

Follow-the-Regularized-Leader (FTRL) algorithms are a popular class of learning algorithms for online linear optimization (OLO) that guarantee sub-linear regret, but the choice of regularizer can significantly impact dimension-dependent factors in the regret bound. We present an algorithm that takes as input convex and symmetric action sets and loss sets for

Alexander V. Kochin

Monitoring the performance of humidity sensors has become particularly relevant due to the lack of in-house production of humidity sensors in the Russian Federation and the logistical problems that have arisen. Humidity is subject to high spatial variability, therefore, standard methods for monitoring data quality based on the difference with the field of th

Cara Battersby, Daniel L. Walker, Ashley Barnes, Adam Ginsburg

The Central Molecular Zone (CMZ) is the largest reservoir of dense molecular gas in the Galaxy and is heavily obscured in the optical and near-IR. We present an overview of the far-IR dust continuum, where the molecular clouds are revealed, provided by Herschel in the inner 40\deg($|l| <$ 20\deg) of the Milky Way with a particular focus on the CMZ. We report

Ruiping Ren, Yingwei, Xu, Xing Yao

As large language models (LLMs) become increasingly integral to the hospitality and tourism industry, concerns about their fairness in serving diverse identity groups persist. Grounded in social identity theory and sociotechnical systems theory, this study examines ethnic and gender biases in travel recommendations generated by LLMs. Using fairness probing,

Cara Battersby, Daniel L. Walker, Ashley Barnes, Adam Ginsburg

The Central Molecular Zone (CMZ) is the way station at the heart of our Milky Way Galaxy, connecting gas flowing in from Galactic scales with the central nucleus. Key open questions remain about its 3-D structure, star formation properties, and role in regulating this gas inflow. In this work, we identify a hierarchy of discrete structures in the CMZ using c

Negar Arabzadeh, Fernando Diaz, Junfeng He

Text-to-Image (TTI) systems often support people during ideation, the early stages of a creative process when exposure to a broad set of relevant images can help explore the design space. Since ideation is an important subclass of TTI tasks, understanding how to quantitatively evaluate TTI systems according to how well they support ideation is crucial to pro

C. Karoumpis, B. Magnelli, E. Romano-Díaz, K. Garcia

Context. The Fred Young Submillimeter Telescope (FYST) line intensity mapping (LIM) survey will measure the power spectrum (PS) of the singly ionized carbon 158 $\rm \mu$m fine-structure line, [CII], to trace the appearance of the first galaxies that emerged during and right after the epoch of reionization (EoR, $6<z<9$). Aims. We aim to quantify the contami

Tristan. M. Lawrie, Gregor. Tanner, Gregory. J. Chaplain

We conceptualise and numerically simulate a resonant metamaterial interface incorporating non-local, or beyond nearest neighbour, coupling that acts as a discrete angular filter. It can be designed to yield perfect transmission at customizable angles of incidence, without diffraction, allowing for tailored transmission in arbitrarily narrow wavenumber window

Krishna R. Akhil, Sreeja S Kartha, Namitha Kizhuprakkat, K. Ujjwal

The UV upturn refers to the increase in UV flux at wavelengths shorter than 3000 {\AA} observed in quiescent early-type galaxies (ETGs), which still remains a puzzle. In this study, we aim to identify ETGs showing the UV upturn phenomenon within the Virgo galaxy cluster. We utilized a color-color diagram to identify all potential possible UV upturn galaxies.

Marbely Micolta, Nuria Calvet, Thanawuth Thanathibodee, Gladis Magris C.

We present a study of the abundance of calcium in the innermost disk of 70 T Tauri stars in the star-forming regions of Chamaeleon I, Lupus and Orion OB1b. We use calcium as a proxy for the refractory material that reaches the inner disk. We used magnetospheric accretion models to analyze the Ca II emission lines and estimate abundances in the accretion flow

Bridget Ratcliffe, Sergey Khoperskov, Ivan Minchev, Nathan D. Lee

Recent works identified a way to recover the time evolution of a galaxy's disk metallicity gradient from the shape of its age--metallicity relation. However, the success of the method is dependent on how the width of the star-forming region evolves over time, which in turn is dependent on a galaxy's present-day bar strength. In this paper, we account for the

Viola De Renzis, Francesco Iacovelli, Davide Gerosa, Michele Mancarella

Third-generation gravitational-wave detectors will observe up to millions of merging binary black holes. With such a vast dataset, stacking events into population analyses will arguably be more important than analyzing single sources. We present the first application of population-level Fisher-matrix forecasts tailored to third-generation gravitational-wave

Benedikt Diemer

In the previous paper of this series, we proposed a new function to fit halo density profiles out to large radii. This truncated Einasto profile models the inner, orbiting matter as $\rho_{\rm orb} \propto \exp \left[-2/\alpha\ (r / r_{\rm s})^\alpha - 1/\beta\ (r / r_{\rm t})^\beta \right]$ and the outer, infalling term as a power-law overdensity. In this p

Federico Fantoccoli, Jordan Barber, Fani Dosopoulou, Debatri Chattopadhyay

We investigate black hole-star binaries formed in $N$-body simulations of massive, dense star clusters. We simulate 32 clusters with varying initial masses ($10^{4}~\rm M_{\odot}$ to $10^{6}~\rm M_{\odot}$), densities ($1200~\rm M_{\odot}~pc^{-3}$ to $10^{5}~\rm M_{\odot}~pc^{-3}$), and metallicities $(Z = 0.01,~0.001,~0.0001)$. Our results reveal that star

D. O. Jones, P. McGill, T. A. Manning, A. Gagliano

Characterizing the host galaxies of astrophysical transients is important to many areas of astrophysics, including constraining the progenitor systems of core-collapse supernovae, correcting Type Ia supernova distances, and probabilistically classifying transients without photometric or spectroscopic data. Given the increasing transient discovery rate in the

Dani Lipman, Cara Battersby, Daniel L. Walker, Mattia C. Sormani

A comprehensive 3-D model of the central 300 pc of the Milky Way, the Central Molecular Zone (CMZ) is of fundamental importance in understanding energy cycles in galactic nuclei, since the 3-D structure influences the location and intensity of star formation, feedback, and black hole accretion. Current observational constraints are insufficient to distinguis

Daniel L. Walker, Cara Battersby, Dani Lipman, Mattia C. Sormani

The Milky Way's Central Molecular Zone (CMZ) is the largest concentration of dense molecular gas in the Galaxy, the structure of which is shaped by the complex interplay between Galactic-scale dynamics and extreme physical conditions. Understanding the 3-D geometry of this gas is crucial as it determines the locations of star formation and subsequent feedbac

Jeonghoon Lim, Jacob B. Simon, Rixin Li, Daniel Carrera

The streaming instability (SI) is a leading mechanism for concentrating solid particles into regions dense enough to form planetesimals. Its efficiency in clumping particles depends primarily on the dimensionless stopping time ($\tau_s$, a proxy for particle size) and dust-to-gas surface density ratio ($Z$). Previous simulations identified a critical $Z$ ($Z

Juan Polo, Wayne Jordan Chetcuti, Tobias Haug, Anna Minguzzi

Persistent currents flowing in spatially closed tracks define one of the most iconic concepts in mesoscopic physics. They have been studied in solid-state platforms such as superfluids, superconductors and metals. Cold atoms trapped in magneto-optical toroidal circuits and driven by suitable artificial gauge fields allow us to study persistent currents with

Fei Yan, Robert Konik, Aditi Mitra

Physical quantities with long lifetimes have both theoretical significance in the study of quantum many-body systems and practical implications for quantum technologies. In this manuscript, we investigate the roles played by topological defects in the construction of quasi-conserved quantities, using as a prototypical example the Kramers-Wannier duality defe

Nava Gaddam, Ashik H

The principle of holography of information states that all information available in the bulk of asymptotically flat spacetime is also available near its boundary at spatial infinity. However, physical observers never have access to spatial infinity. Therefore, we ask the question: ``Is information contained in a ball of finite radius also holographic in natu

Amedeo Romagnolo, Jakub Klencki, Alejandro Vigna-Gomez, Krzysztof Belczynski

The structure of stellar envelopes strongly influences the course and outcome of binary mass transfer, in particular of common envelope (CE) evolution. Convective envelopes can most easily be ejected during CE events, leading to short-period binaries and potentially gravitational wave (GW) sources. Conversely, radiative envelope are thought to lead to CE mer

Gilad Kishony, Ori Grossman, Netanel Lindner, Mark Rudner

We consider two-dimensional periodically driven systems of fermions with particle-hole symmetry. Such systems support non-trivial topological phases, including ones that cannot be realized in equilibrium. We show that a space-time defect in the driving Hamiltonian, dubbed a ``time vortex,'' can bind $\pi$ Majorana modes. A time vortex is a point in space aro

Wolfgang Altmannshofer, Benoît Assi, Joachim Brod, Nick Hamer

We present the first complete two-loop calculation of the electric dipole moment of the electron, as well as the rates of the lepton-flavor violating decays $\mu \to e + \gamma$ and $\tau \to e/\mu + \gamma$, in the unconstrained two-Higgs doublet model. We include the most general Yukawa interactions of the Higgs doublets with the Standard Model fermions up

Kaia R. Atzberger, Sam A. Usman, Alexander P. Ji, Lara R. Cullinane

Chemical abundances of stellar streams can be used to determine the nature of a stream's progenitor. Here we study the progenitor of the recently discovered Leiptr stellar stream, which was previously suggested to be a tidally disrupted halo globular cluster. We obtain high-resolution spectra of five red giant branch stars selected from the Gaia DR2 STREAMFI

Alexander J. Dittmann

Numerical integration methods are central to the study of self-gravitating systems, particularly those comprised of many bodies or otherwise beyond the reach of analytical methods. Predictor-corrector schemes, both multi-step methods and those based on 2-point Hermite interpolation, have found great success in the simulation of star clusters and other collis

Hassan Khalvati, Alessandro Santini, Francisco Duque, Lorenzo Speri

Extreme-Mass-Ratio Inspirals (EMRIs) are one of the key targets for future space-based gravitational wave detectors, such as LISA. The scientific potential of these sources can only be fully realized with fast and accurate waveform models. In this work, we extend the \textsc{FastEMRIWaveform} (\texttt{FEW}) framework by providing fully relativistic waveforms

Haokun Liu, Yangqiaoyu Zhou, Mingxuan Li, Chenfei Yuan

AI holds promise for transforming scientific processes, including hypothesis generation. Prior work on hypothesis generation can be broadly categorized into theory-driven and data-driven approaches. While both have proven effective in generating novel and plausible hypotheses, it remains an open question whether they can complement each other. To address thi

Ryan Linehan, Tanner Trickle, Christopher R. Conner, Sohitri Ghosh

We present a novel application of a qubit-coupled phonon detector to search for new physics, e.g., ultralight dark matter (DM) and high-frequency gravitational waves. The detector, motivated by recent advances in quantum acoustics, is composed of superconducting transmon qubits coupled to high-overtone bulk acoustic resonators ($h$BARs) and operates in the G

Rawan Karam, Kristen C. Dage, Bailey E. Tetarenko, McKinley C. Brumback

The MOOSE (Monitoring Observations of SMC X-1 Excursions) program uses the Neutron Star Interior Composition Explorer Mission (NICER) to monitor the high mass X-ray binary SMC X-1 during its superorbital period excursions. Here we perform X-ray spectral analyses of 26 NICER observations of SMC X-1, taken at the tail-end of the excursion between 2021-04-01 an

Hila Glanz, Hagai B. Perets, Aakash Bhat, Ruediger Pakmor

Hypervelocity white dwarfs (HVWDs) are stellar remnants moving at speeds exceeding the Milky Way's escape velocity. The origins of the fastest HVWDs are enigmatic, with proposed formation scenarios facing challenges explaining both their extreme velocities and observed properties. Here we report a three-dimensional hydrodynamic simulation of a merger between

Mudit Garg, Alessia Franchini, Alessandro Lupi, Matteo Bonetti

We investigate the effect of dynamically coupling gas torques with gravitational wave (GW) emission during the orbital evolution of an equal-mass massive black hole binary (MBHB). We perform hydrodynamical simulations of eccentric MBHBs with total mass $M=10^6~{\rm M}_\odot$ embedded in a prograde locally isothermal circumbinary disk (CBD). We evolve the bin

Hanjue Zhu, Ellen G. Zweibel, Nickolay Y. Gnedin

We investigate the 1D plane-parallel front connecting the warm ($10^4$ K) and hot ($10^6$ K) phases of the circumgalactic medium (CGM), focusing on the influence of cosmic rays (CRs) in shaping these transition layers. We find that cosmic rays dictate the thermal balance while other fluxes (thermal conduction, radiative cooling, and gas flow) adjust to compe

Hu Xu, Po-Yao Huang, Xiaoqing Ellen Tan, Ching-Feng Yeh

This paper focuses on creating synthetic data to improve the quality of image captions. Existing works typically have two shortcomings. First, they caption images from scratch, ignoring existing alt-text metadata, and second, lack transparency if the captioners' training data (e.g. GPT) is unknown. In this paper, we study a principled approach Altogether bas

Shota Onohara, Atsuyuki Miyai, Yuki Imajuku, Kazuki Egashira

Accelerating research on Large Multimodal Models (LMMs) in non-English languages is crucial for enhancing user experiences across broader populations. In this paper, we introduce JMMMU (Japanese MMMU), the first large-scale Japanese benchmark designed to evaluate LMMs on expert-level tasks based on the Japanese cultural context. To facilitate comprehensive c

Cheng-De Fan, Chen-Wei Chang, Yi-Ruei Liu, Jie-Ying Lee

We present SpectroMotion, a novel approach that combines 3D Gaussian Splatting (3DGS) with physically-based rendering (PBR) and deformation fields to reconstruct dynamic specular scenes. Previous methods extending 3DGS to model dynamic scenes have struggled to represent specular surfaces accurately. Our method addresses this limitation by introducing a resid

Vít Růžička, Andrew Markham

On-board processing of hyperspectral data with machine learning models would enable unprecedented amount of autonomy for a wide range of tasks, for example methane detection or mineral identification. This can enable early warning system and could allow new capabilities such as automated scheduling across constellations of satellites. Classical methods suffe

Long Xing, Qidong Huang, Xiaoyi Dong, Jiajie Lu

In large vision-language models (LVLMs), images serve as inputs that carry a wealth of information. As the idiom "A picture is worth a thousand words" implies, representing a single image in current LVLMs can require hundreds or even thousands of tokens. This results in significant computational costs, which grow quadratically as input image resolution incre

Venkatesh Pattabiraman, Yifeng Cao, Siddhant Haldar, Lerrel Pinto

While visuomotor policy learning has advanced robotic manipulation, precisely executing contact-rich tasks remains challenging due to the limitations of vision in reasoning about physical interactions. To address this, recent work has sought to integrate tactile sensing into policy learning. However, many existing approaches rely on optical tactile sensors t

Itamar Pres, Laura Ruis, Ekdeep Singh Lubana, David Krueger

Representation engineering methods have recently shown promise for enabling efficient steering of model behavior. However, evaluation pipelines for these methods have primarily relied on subjective demonstrations, instead of quantitative, objective metrics. We aim to take a step towards addressing this issue by advocating for four properties missing from cur

Martin Bohnert, Justus Springer

We present algorithms for classifying rational polygons with fixed denominator and number of interior lattice points. Our approach is to first describe maximal polygons and then compute all subpolygons, where we eliminate redundancy by a suitable normal form. Executing our classification, we obtained a dataset of several billions of polygons covering a wide

Zesen Cheng, Hang Zhang, Kehan Li, Sicong Leng

Contrastive loss is a powerful approach for representation learning, where larger batch sizes enhance performance by providing more negative samples to better distinguish between similar and dissimilar data. However, scaling batch sizes is constrained by the quadratic growth in GPU memory consumption, primarily due to the full instantiation of the similarity

Haian Jin, Hanwen Jiang, Hao Tan, Kai Zhang

We propose the Large View Synthesis Model (LVSM), a novel transformer-based approach for scalable and generalizable novel view synthesis from sparse-view inputs. We introduce two architectures: (1) an encoder-decoder LVSM, which encodes input image tokens into a fixed number of 1D latent tokens, functioning as a fully learned scene representation, and decode

Ge-Peng Ji, Jingyi Liu, Peng Xu, Nick Barnes

Colonoscopy is currently one of the most sensitive screening methods for colorectal cancer. This study investigates the frontiers of intelligent colonoscopy techniques and their prospective implications for multimodal medical applications. With this goal, we begin by assessing the current data-centric and model-centric landscapes through four tasks for colon

Y. Sarkango, J. R. Szalay, P. A. Damiano, A. H. Sulaiman

Banded energy distributions of H$^{+}$, O$^{++}$, S$^{+++}$, and O$^+$ or S$^{++}$ ions between 100 eV to ~20 keV are consistently observed in Jupiter's magnetosphere mapping to M-shells between M=10-20. The bands correspond to flux enhancements at similar speeds for different ion species, providing the first evidence of simultaneous bounce-resonant accelera