November 2024 arXiv papers — page 76

Roland Daynauth, Christopher Clarke, Krisztian Flautner, Lingjia Tang

Deciding which large language model (LLM) to use is a complex challenge. Pairwise ranking has emerged as a new method for evaluating human preferences for LLMs. This approach entails humans evaluating pairs of model outputs based on a predefined criterion. By collecting these comparisons, a ranking can be constructed using methods such as Elo. However, apply

G. C. Sloan, K. E. Kraemer, B. Aringer, J. Cami

The Medium-Resolution Spectrometer on the Mid-Infrared Instrument on JWST obtained spectra of three carbon stars in the Large Magellanic Cloud. Two of the spectra differ significantly from spectra obtained ~16-19 years earlier with the Infrared Spectrograph on the Spitzer Space Telescope. The one semi-regular variable among the three has changed little. The

Ahmad Sajedi, Samir Khaki, Lucy Z. Liu, Ehsan Amjadian

Dataset distillation aims to distill the knowledge of a large-scale real dataset into small yet informative synthetic data such that a model trained on it performs as well as a model trained on the full dataset. Despite recent progress, existing dataset distillation methods often struggle with computational efficiency, scalability to complex high-resolution

Leihao Chen, Tobias Fritz, Tomáš Gonda, Andreas Klingler

The Aldous-Hoover Theorem concerns an infinite matrix of random variables whose distribution is invariant under finite permutations of rows and columns. It states that, up to equality in distribution, each random variable in the matrix can be expressed as a function only depending on four key variables: one common to the entire matrix, one that encodes infor

P. Smirnova, E. I. Makarenko, S. D. Clarke, E. Glukhov

About 15%-60% of all supernova remnants are estimated to interact with dense molecular clouds. In these high density environments, radiative losses are significant. The cooling radiation can be observed in forbidden lines at optical wavelengths. We aim to determine whether supernovae at different positions within a molecular cloud can be distinguished based

Canberk Guvendik

Recent introduction of center vortices with 't Hooft flux on two torus compactification leads to a new semiclassical regime where confinement is analytically calculable. In this work, we investigate the stability of the classical minima for gauge fields under quantum corrections. Although the classical $Z_N \times Z_N$ symmetric minima is stable at small-$N$

Md Ridwan Hossain Talukder, Raihan Islam Arnob, Gregory J. Stein

We consider the setting where a robot must complete a sequence of tasks in a persistent large-scale environment, given one at a time. Existing task planners often operate myopically, focusing solely on immediate goals without considering the impact of current actions on future tasks. Anticipatory planning, which reduces the joint objective of the immediate p

V. M. Silkin, D. V. Efremov, M. Yu. Kagan

In this study, we analyze the dielectric function of high-Tc cuprates as a function of doping level, taking into account the full energy band dispersion within the CuO$_2$ monolayer. In addition to the conventional two-dimensional (2D) gapless plasmon mode, our findings reveal the existence of three anomalous branches within the plasmon spectrum. Two of thes

Rachel N. Clark, Sam G. Bishop, Joseph K. Cannon, John P. Hadden

Single-photon detectors are ``blind" after the detection of a photon, and thereafter display a characteristic recovery in efficiency, during which the number of undetected photons depends on the statistics of the incident light. We show how the efficiency-recovery, photon statistics and intensity have an interdependent relationship which suppresses a detecto

Chris M. Harrison, Leah Morabito, Ann Njeri

We report on an international scientific conference, where we brought together African and European academic astronomers. This aimed to bridge the gap between those in position of privilege, with ease of access to international events (i.e., the typical experience of academics in Western institutions), with those historically excluded (affecting the majority

Rishabh Kumar Sharma, Mukund Sharma, Pushkar Sharma, Jeetashree Aparjeeta

While X-ray imaging is indispensable in medical diagnostics, it inherently carries with it those noises and limitations on resolution that mask the details necessary for diagnosis. B/W X-ray images require a careful balance between noise suppression and high-detail preservation to ensure clarity in soft-tissue structures and bone edges. While traditional met

Abdul Basit Anees, Ahmet Canberk Baykal, Muhammed Burak Kizil, Duygu Ceylan

Generative Adversarial Networks (GANs), particularly StyleGAN and its variants, have demonstrated remarkable capabilities in generating highly realistic images. Despite their success, adapting these models to diverse tasks such as domain adaptation, reference-guided synthesis, and text-guided manipulation with limited training data remains challenging. Towar

Paul Janson, Tiberiu Popa, Eugene Belilovsky

Text-conditioned video diffusion models have emerged as a powerful tool in the realm of video generation and editing. But their ability to capture the nuances of human movement remains under-explored. Indeed the ability of these models to faithfully model an array of text prompts can lead to a wide host of applications in human and character animation. In th

Ruchi Pandey, Manjunath Mulimani, Archontis Politis, Annamaria Mesaros

This paper investigates the feasibility of class-incremental learning (CIL) for Sound Event Localization and Detection (SELD) tasks. The method features an incremental learner that can learn new sound classes independently while preserving knowledge of old classes. The continual learning is achieved through a mean square error-based distillation loss to mini

Claire Bonial, Stephanie M. Lukin, Mitchell Abrams, Anthony Baker

In this paper, we describe the development of symbolic representations annotated on human-robot dialogue data to make dimensions of meaning accessible to autonomous systems participating in collaborative, natural language dialogue, and to enable common ground with human partners. A particular challenge for establishing common ground arises in remote dialogue

Sonny George, Chris Sypherd, Dylan Cashman

Large language model (LLM) agents show promise in an increasing number of domains. In many proposed applications, it is expected that the agent reasons over accumulated experience presented in an input prompt. We propose the OEDD (Operationalize Experience Despite Distraction) corpus, a human-annotator-validated body of scenarios with pre-scripted agent hist

Sergei Efimov

The fundamental quantum Coulomb problem in the momentum space is considered. A differential equation with SO(4) simmetry has been obtained in the momentum space instead of the integral Fock equation. The corresponding equation in the coordinate space is the sum of the squares of the angular momentum and the Runge-Lenz operators.This approach is unknown in th

Debarshi Basu, Himanshu Chourasiya, Ankur Dey, Vinayak Raj

We investigate the reflected entropy for bipartite mixed state configurations in a $T\bar{T}$ deformed boundary conformal field theory in $2$ dimensions (BCFT$_2$). The bulk dual is described by asymptotically AdS$_3$ geometries with the cut off surface pushed deeper into the bulk and truncated by an end of the world brane. We obtain the reflected entropy up

Hung T. Diep

In 1977, G\'erard Toulouse has proposed a new concept termed as "frustration" in spin systems. Using this definition, several frustrated models have been created and studied, among them we can mention the Villain's model, the fully frustrated simple cubic lattice, the antiferromagnetic triangular lattice. The former models are systems with mixed ferromagneti

Hongzhi Guo

Traditional error detection and correction codes focus on bit-level fidelity, which is insufficient for emerging technologies like eXtended Reality (XR) and holographic communications requiring high-data-rate, low-latency systems. Bit-level metrics cannot comprehensively evaluate Quality-of-Service (QoS) in these scenarios. This letter proposes TopoCode whic

Mingzhu Liu, Angela H. Chen, George H. Chen

Time series foundation models are pre-trained on large datasets and are able to achieve state-of-the-art performance in diverse tasks. However, to date, there has been limited work demonstrating how well these models perform in medical applications, where labeled data can be scarce. Further, we observe that currently, the majority of time series foundation m

Soheil Khajavi, Ali Eghrari, Zahra Shaterzadeh-Yazdi, Mohammad Neshat

Scattering scanning near-field optical microscopy (s-SNOM) is a technique to enhance the spatial resolution, and when combined by Fourier transform spectroscopy it can provide spectroscopic information with high spatial resolution. This paper studies two analytical models for the s-SNOM probe using atomic force microscopy (AFM) tip and its interaction with a

Eric Giovannini, Tingting Ding, Max S. New

Gradually typed programming languages, which allow for soundly mixing static and dynamically typed programming styles, present a strong challenge for metatheorists. Even the simplest sound gradually typed languages feature at least recursion and errors, with realistic languages featuring furthermore runtime allocation of memory locations and dynamic type tag

I H Hutchinson

Long-duration one-dimensional PIC simulations are presented of Buneman-unstable, initially Maxwellian, electron and ion distributions shifted with respect to one another, providing detailed phase-space videos of the time-dependence. The final state of high initial ion temperature cases is dominated by fast electron holes, but when initial ion temperature is

Peter Barnett, Lisa Thiergart

As AI systems advance, AI evaluations are becoming an important pillar of regulations for ensuring safety. We argue that such regulation should require developers to explicitly identify and justify key underlying assumptions about evaluations as part of their case for safety. We identify core assumptions in AI evaluations (both for evaluating existing models

George Balla, Daniel Corey, Igor Makhlin, Victoria Schleis

Several known constructions relate initial degenerations of projective toric varieties and Grassmannians to regular subdivisions of appropriate point configurations. We define a general framework which allows for partial generalizations of these constructions to arbitrary projective schemes (as well as their very affine parts). We associate a point configura

Rocco Amorosso, Sergey Syritsyn, Raju Venugopalan

In recent work arxiv:2410.00112 , we computed a novel flux tube entanglement entropy (FTE$^2$) of the color flux tube stretched between a heavy quark-antiquark pair on a Euclidean lattice in (2+1)D Yang-Mills theory. Our numerical results suggested that FTE$^2$ can be partitioned into an internal color entanglement entropy and a vibrational entropy correspon

Logan Frank, Jim Davis

Knowledge distillation (KD) has been a popular and effective method for model compression. One important assumption of KD is that the teacher's original dataset will also be available when training the student. However, in situations such as continual learning and distilling large models trained on company-withheld datasets, having access to the original dat

A. Leviatan

Pronounced structural changes within individual configurations (Type I QPT), superimposed on an abrupt crossing of these configurations (Type II QPT), define the notion of intertwined quantum phase transitions (QPTs). We discuss and present evidence for such a scenario in finite Bose and Bose-Fermi systems. The analysis is based on algebraic models with expl

Savvas Raptis, Martin Lindberg, Terry Z. Liu, Drew L. Turner

Shock-generated transients, such as hot flow anomalies (HFAs), upstream of planetary bow shocks, play a critical role in electron acceleration. Using multi-mission data from NASA's Magnetospheric Multiscale (MMS) and ESA's Cluster missions, we demonstrate the transmission of HFAs through Earth's quasi-parallel bow shock, associated with acceleration of elect

Junlong Cheng, Bin Fu, Jin Ye, Guoan Wang

Interactive Medical Image Segmentation (IMIS) has long been constrained by the limited availability of large-scale, diverse, and densely annotated datasets, which hinders model generalization and consistent evaluation across different models. In this paper, we introduce the IMed-361M benchmark dataset, a significant advancement in general IMIS research. Firs

Avimita Chatterjee, Archisman Ghosh, Swaroop Ghosh

Quantum error correction (QEC) is crucial for ensuring the reliability of quantum computers. However, implementing QEC often requires a significant number of qubits, leading to substantial overhead. One of the major challenges in quantum computing is reducing this overhead, especially since QEC codes depend heavily on ancilla qubits for stabilizer measuremen

Keh-Fei Liu

The recent lattice QCD calculations of the neutron and proton electric dipole moments (EDMs) and the CP-violating $\pi {\rm NN}$ coupling constant due to the $\theta$ term are reviewed. Progress towards nucleon EDM calculations, including the Weinberg three-gluon operator, and the quark chromoelectric dipole moment operator and their renormalization, is also

Adit Gupta, Momin Siddiqui, Glen Smith, Jenn Reddig

This work examines the sociotechnical factors that influence the adoption and usage of intelligent tutoring systems in self-directed learning contexts, focusing specifically on adult learners. The study is divided into two parts. First, we present Apprentice Tutors, a novel intelligent tutoring system designed to address the unique needs of adult learners. T

Hanyu Zeng, Hui Ji, Pengfei Zhou

People with diabetes need insulin delivery to effectively manage their blood glucose levels, especially after meals, because their bodies either do not produce enough insulin or cannot fully utilize it. Accurate insulin delivery starts with estimating the nutrients in meals and is followed by developing a detailed, personalized insulin injection strategy. Th

Ciara Rowles

Diffusion models excel in image generation, but controlling them remains a challenge. We focus on the problem of style-conditioned image generation. Although example images work, they are cumbersome: srefs (style-reference codes) from MidJourney solve this issue by expressing a specific image style in a short numeric code. These have seen widespread adoption

J. P. Peralta, A. M. P. Mendez, D. M. Mitnik, C. C. Montanari

We present a new non-perturbative model to describe the stopping power by ionization of the $d$-electrons of transition metals. These metals are characterized by the filling of the d-subshell and the promotion of part of the electrons to the conduction band. The contribution of d-electrons at low-impact energies has been noted experimentally in the past as a

Minghao Guo, Chang-Goo Kim, James M. Stone

We investigate the evolution of supernova remnants (SNRs) in a two-phase cloudy medium by performing a series of high-resolution (up to $\Delta x\approx0.01\,\mathrm{pc}$), 3D hydrodynamical simulations including radiative cooling and thermal conduction. We aim to reach a resolution that directly captures the shock-cloud interactions for the majority of the

Antoine Lizée, Pierre-Auguste Beaucoté, James Whitbeck, Marion Doumeingts

The shortage of doctors is creating a critical squeeze in access to medical expertise. While conversational Artificial Intelligence (AI) holds promise in addressing this problem, its safe deployment in patient-facing roles remains largely unexplored in real-world medical settings. We present the first large-scale evaluation of a physician-supervised LLM-base

Zurab Jashi, Jaroslav Scheinpflug, Yale Yauk

Motivated by recent work by Arkani-Hamed et al. arXiv:2401.00041, we compute the ''scaffolding'' residue of $2n$-scalar Yang-Mills-Scalar amplitudes to obtain pure $n$-gluon amplitudes \`a la Cachazo-He-Yuan (CHY). In particular, we show how the Pfaffian of $\Psi$, which is a matrix rich in structure, emerges from that of the simple $A$ matrix. The same CHY

Ping Gao, Han Lin, Cheng Peng

We construct a new family of quantum chaotic models by combining multiple copies of integrable commuting SYK models. As each copy of the commuting SYK model does not commute with others, this construction breaks the integrability of each commuting SYK and the family of models demonstrates the emergence of quantum chaos. We study the spectrum of this model an

Mykhailo Bilokur, Sarang Gopalakrishnan, Shayan Majidy

We investigate the thermodynamic limits on scaling fault-tolerant quantum computers due to heating from quantum error correction (QEC). Quantum computers require error correction, which accounts for 99.9% of the qubit demand and generates heat through information-erasing processes. This heating increases the error rate, necessitating more rounds of error cor

F. Ubertosi, Y. Gong, P. Nulsen, J. P. Leahy

We present a detailed analysis of jet activity in the radio galaxy 3C348 at the center of the galaxy cluster Hercules A. We use archival Chandra data to investigate the jet-driven shock front, the radio-faint X-ray cavities, the eastern jet, and the presence of extended Inverse Compton (IC) X-ray emission from the radio lobes. We detect two pairs of shocks:

Malu Sudha, Renee M. Ludlam, Diego Altamirano, Edward M. Cackett

We report the spectro-temporal study of the neutron star low mass X-ray binary Cygnus X-2 using NICER and NuSTAR data while the source was in the normal branch (NB). We detect a normal branch oscillation (NBO) feature at ~ 5.41 Hz that appears in the middle portion of the NB branch. We note that the NBO appeared only in the 0.5-3 keV energy range, with maxim

Zhenghao Zhong

We look at a family of 3d $\mathcal{N}=4$ rank-0 orthosymplectic quiver gauge theories. We define a superconformal field theory (SCFT) to be rank-0 if either the Higgs branch or Coulomb branch is trivial. This family of non-linear orthosymplectic quivers has Coulomb branches that can be factorized into products of known moduli spaces. More importantly, the H

Yun-Ting Cheng, Brandon S. Hensley, Tzu-Ching Chang, Olivier Doré

Neutral hydrogen (HI) emission closely traces the dust column density at high Galactic latitudes and is thus a powerful tool for predicting dust extinction. However, the relation between HI column density $N_{\rm HI}$ and high-latitude dust emission observed by Planck has large-scale residuals at the level of $\lesssim 20\%$ on tens of degree scales. In this

Y. R. Khalil, B. Famaey, G. Monari, M. Bernet

We provide a purely dynamical global map of the non-axisymmetric structure of the Milky Way disk. For this, we exploit the information contained within the in-plane motions of disk stars from Gaia DR3 to adjust a model of the Galactic potential, including a detailed parametric form for the bar and spiral arms. We explore the parameter space of the non-axisym

Ryan W. Pfeifle, Kimberly A. Weaver, Nathan J. Secrest, Barry Rothberg

Galaxy mergers represent the most transformative and dramatic avenue for galaxy and supermassive black hole (SMBH) evolution. Multi-active galactic nuclei (multi-AGNs) are expected to ignite, grow, and evolve alongside the host galaxies, and these represent different evolutionary stages of the SMBHs over the merger sequence. However, no comprehensive census

Mikael Chala, Javier López Miras, José Santiago, Fuensanta Vilches

We propose an efficient method to perform on-shell matching calculations in effective field theories. The standard off-shell approach to matching requires the use of a Green's basis that includes redundant and evanescent operators. The reduction of such a basis to a physical one is often highly non-trivial, difficult to automate and error prone. Our proposal

Jeremy Hartse, Lukasz Fidkowski, Niklas Mueller

Quantum many-body scars are eigenstates in non-integrable isolated quantum systems that defy typical thermalization paradigms, violating the eigenstate thermalization hypothesis and quantum ergodicity. We identify exact analytic scar solutions in a 2+1 dimensional lattice gauge theory in a quasi-1d limit as zero-magic resource stabilizer states.

Joheen Chakraborty, Kevin B. Burdge, Saul A. Rappaport, James Munday

We report the discovery of three ultracompact binary white dwarf systems hosting accretion disks, with orbital periods of 7.95, 8.68, and 13.15 minutes. This significantly augments the population of mass-transferring binaries at the shortest periods, and provides the first evidence that accretors in ultracompacts can be dense enough to host accretion disks e

D. Nardiello, J. M. Akana Murphy, R. Spinelli, M. Baratella

Small-sized exoplanets in tight orbits around young stars (10-1000 Myr) give us the opportunity to investigate the mechanisms that led to their formation, the evolution of their physical and orbital properties and, especially, of their atmospheres. Thanks to the all-sky survey carried out by TESS, many of these exoplanets have been discovered and have subseq

Bryce Kobrin, Thomas Schuster, Maxwell Block, Weijie Wu

We introduce a novel protocol, which enables Heisenberg-limited quantum-enhanced sensing using the dynamics of any interacting many-body Hamiltonian. Our approach - dubbed butterfly metrology - utilizes a single application of forward and reverse time evolution to produce a coherent superposition of a "scrambled" and "unscrambled" quantum state. In this way,

Shang Liu

In this work, we explore an unconventional class of problems in the study of (quantum) critical phenomena, termed ''deep boundary criticality''. Traditionally, critical systems are analyzed with two types of perturbations: those uniformly distributed throughout the bulk, which can significantly alter the bulk criticality by triggering a nontrivial bulk renor

Thomas Becher, Patrick Hager, Giuliano Martinelli, Matthias Neubert

Jet observables at hadron colliders feature ''super-leading'' logarithms, double-logarithmic corrections resulting from a breakdown of color coherence due to complex phases in hard-scattering amplitudes. While these effects only arise in high orders of perturbation theory and are suppressed in the large-$N_c$ limit, they formally constitute leading logarithm

Bolivia Cuevas-Otahola, Cecilia Mateu, Ivan Cabrera-Ziri, Gustavo Bruzual

Recent works have challenged our canonical view of RR Lyrae (RRL) stars as tracers of exclusively old populations ($\gtrsim10$~Gyr) by proposing a fraction of these stars to be of intermediate ages ($\sim$2-5~Gyr). Since it is currently not possible to infer stellar ages directly for individual RRL stars, our goal in this work is to search for these in assoc

Salomé Perez-Rosero, Robert Dyer, Samuel W. Flint, Shane McIntosh

Many software engineering maintenance tasks require linking a commit that induced a bug with the commit that later fixed that bug. Several existing SZZ algorithms provide a way to identify the potential commit that induced a bug when given a fixing commit as input. Prior work introduced the notion of a "work item", a logical grouping of commits that could be

Florian Cougoulic, Piotr Korcyl, Tomasz Stebel

The Balitsky-Kovchegov (BK) evolution equation is an equation derived from perturbative Quantum Chromodynamics that allows one to evolve with collision energy the scattering amplitude of a pair of quark and antiquark off a hadron target, called the dipole amplitude. The initial condition, being a non-perturbative object, usually has to be modeled separately.

Enrique Gomez-Leos, Ryan R. Martin

A perfect $H$-tiling in a graph $G$ is a collection of vertex-disjoint copies of a graph $H$ in $G$ that covers all vertices of $G$. Motivated by papers of Bush and Zhao and of Balogh, Treglown, and Wagner, we determine the threshold for the existence of a perfect $K_{h,h}$-tiling of a randomly perturbed bipartite graph with linear minimum degree.

Marcilei A. Guazzelli, Luis H. Avanzi, Vitor A. P. Aguiar, Alexis C. Vilas-Bôas

Highly Ordered Pyrolytic Graphite (HOPG) has been extensively researched due to its chemical and physical properties that make it suitable for applications in several technologies. Its high thermal conductivity makes HOPG an excellent heat sink, a crucial characteristic for manufacturing targets used in nuclear reactions, such as those proposed by the NUMEN

Salma Kharrat, Fares Fourati, Marco Canini

The effectiveness of Large Language Models (LLMs) in solving tasks depends significantly on the quality of their instructions, which often require substantial human effort to craft. This underscores the need for automated instruction optimization. However, optimizing instructions is particularly challenging when working with black-box LLMs, where model param

Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic, Luca Mariot

Evolving Boolean functions with specific properties is an interesting optimization problem since, depending on the combination of properties and Boolean function size, the problem can range from very simple to (almost) impossible to solve. Moreover, some problems are more interesting as there may be only a few options for generating the required Boolean func

Yunchao Yao, Uksang Yoo, Jean Oh, Christopher G. Atkeson

Dynamic in-hand manipulation remains a challenging task for soft robotic systems that have demonstrated advantages in safe compliant interactions but struggle with high-speed dynamic tasks. In this work, we present SWIFT, a system for learning dynamic tasks using a soft and compliant robotic hand. Unlike previous works that rely on simulation, quasi-static a

Siddhant Midha, Roshni Singh, Kaveh Gharavi, Jonathan Baugh

Investigating the microscopic details of the proximity effect is crucial for both key experimental applications and fundamental inquiries into nanoscale devices featuring superconducting elements. In this work, we develop a framework motivated by experiments to study induced superconducting correlations in hybrid nanoscale devices featuring layered supercond

Florian Grötschla, Jiaqing Xie, Roger Wattenhofer

Positional Encodings (PEs) are essential for injecting structural information into Graph Neural Networks (GNNs), particularly Graph Transformers, yet their empirical impact remains insufficiently understood. We introduce a unified benchmarking framework that decouples PEs from architectural choices, enabling a fair comparison across 8 GNN and Transformer mod

Gleb Fedorovich, Lukas Devos, Jutho Haegeman, Laurens Vanderstraeten

An efficient algorithm is constructed for contracting two-dimensional tensor networks under periodic boundary conditions. The central ingredient is a novel renormalization step that scales linearly with system size, i.e. from $L \to L+1$. The numerical accuracy is comparable to state-of-the-art tensor network methods, while giving access to much more data po

Matthias C. Caro, Preksha Naik, Joseph Slote

Properties of Boolean functions can often be tested much faster than the functions can be learned. However, this advantage usually disappears when testers are limited to random samples of a function $f$--a natural setting for data science--rather than queries. In this work we initiate the study of a quantum version of this "data science scenario": quantum al

Navdeep Singh Dhindsa, Debsubhra Chakraborty, Archana Radhakrishnan, Nilmani Mathur

We present the most precise results for the ground state mass of the triply-charmed spin-$3/2$ baryon using lattice quantum chromodynamics. The calculations are performed on six $N_f=2+1+1$ Highly Improved Staggered Quark (HISQ) lattice ensembles generated by the MILC collaboration. Two different lattice setups are employed: in the first one, a fully dynamic

Doron Sivan, Misha Tsodyks

In Shannon's seminal paper, entropy of printed English, treated as a stationary stochastic process, was estimated to be roughly 1 bit per character. However, considered as a means of communication, language differs considerably from its printed form: (i) the units of information are not characters or even words but clauses, i.e. shortest meaningful parts of

A. Quinn, G. J. Gregory, I. D. Moore, S. Brudney

Today's most advanced ion trap quantum computers have significant overhead due to the need for dual-species operation. Looking ahead, logical qubit register sizes will be limited by the encoding rate needed to correct generic Pauli errors. We address both of these issues by establishing high-fidelity control of metastable qubits, a key component of \textit{o

Lianghao Cao, Joshua Chen, Michael Brennan, Thomas O'Leary-Roseberry

We present LazyDINO, a transport map variational inference method for fast, scalable, and efficiently amortized solutions of high-dimensional nonlinear Bayesian inverse problems with expensive parameter-to-observable (PtO) maps. Our method consists of an offline phase in which we construct a derivative-informed neural surrogate of the PtO map using joint sam

Galit Askenazi-Golan, Domenico Mergoni Cecchelli, Edward Plumb, Clemens Possnig

We explore the behaviour emerging from learning agents repeatedly interacting strategically for a wide range of learning dynamics, including $Q$-learning, projected gradient, replicator and log-barrier dynamics. Going beyond the better understood classes of potential games and zero-sum games, we consider the setting of a general repeated game with finite rec

Huy Thong Nguyen, En-Hung Chu, Lenord Melvix, Jazon Jiao

We introduce Teacher2Task, a novel framework for multi-teacher learning that eliminates the need for manual aggregation heuristics. Existing multi-teacher methods typically rely on such heuristics to combine predictions from multiple teachers, often resulting in sub-optimal aggregated labels and the propagation of aggregation errors. Teacher2Task addresses t

H. L. M. Osborne, L. D. Nielsen, V. Van Eylen, O. Barragán

Empirical exoplanet mass-radius relations have been used to study the demographics and compositions of small exoplanets for many years. However, the heterogeneous nature of these measurements hinders robust statistical analysis of this population, particularly with regard to the masses of planets. For this reason, we perform a homogeneous and consistent re-a

Akriti Singh, Lucia Guaita, Pascale Hibon, Boris Häussler

The aim of this study is to identify quiescent galaxies in the 2-deg$^2$ COSMOS field at $z \sim 3.1$ and analyze their environment. Using data from the ODIN survey and COSMOS2020 catalog, we identify 24 massive quiescent galaxies (MQGs) with stellar masses $\geq 10^{10.6}$ and derive their star formation histories and quenching timescales using SED fitting

Sam Kirkham

Dynamical theories of speech use computational models of articulatory control to generate quantitative predictions and advance understanding of speech dynamics. The addition of a nonlinear restoring force to task dynamic models is a significant improvement over linear models, but nonlinearity introduces challenges with parameterization and interpretability.

Praveen Srinivasa Varadhan, Amogh Gulati, Ashwin Sankar, Srija Anand

Despite rapid advancements in TTS models, a consistent and robust human evaluation framework is still lacking. For example, MOS tests fail to differentiate between similar models, and CMOS's pairwise comparisons are time-intensive. The MUSHRA test is a promising alternative for evaluating multiple TTS systems simultaneously, but in this work we show that its

Jean-David Benamou, Guillaume Chazareix, Grégoire Loeper

We propose a discrete time formulation of the semi-martingale optimal transport problem based on multi-marginal entropic transport. This approach offers a new way to formulate and solve numerically the calibration problem proposed by [17], using a multi-marginal extension of Sinkhorn algorithm as in [6, 10, 7]. When the time step goes to zero we recover, as

Yiming Ma, Wenjie Zhong, Xiande Zhang

We study the reconstruction problem of permutation sequences from their $k$-minors, which are subsequences of length $k$ with entries renumbered by $1,2,\ldots,k$ preserving order. We prove that the minimum number $k$ such that any permutation of length $n$ can be reconstructed from the multiset of its $k$-minors is between $\exp{(\Omega(\sqrt{\ln n}))}$ and

Armand Riera, Alejandro Rosales-Ortiz

We develop an excursion theory that describes the evolution of a Markov process indexed by a Levy tree away from a regular and instantaneous point $x$ of the state space. The theory builds upon a notion of local time at $x$ that was recently introduced in [37]. Despite the radically different setting, our results exhibit striking similarities to the classica

Facundo Pérez Paolino, Jeff Bary, Lynne Hillenbrand, Madison Markham

An accurate estimation of the continuum excess emission from accretion spots and inner circumstellar disk regions is crucial for a proper derivation of fundamental stellar parameters in accreting systems. However, the presence of starspots can make disentangling the complicated multi-component emission in these systems challenging. Subtraction of a single-te

Jerónimo García-Mejía, Antoine Goldsborough

In this note, we study the notion of random Dehn function and compute an asymptotic upper bound for finitely presented acylindrically hyperbolic groups whose Dehn function is at most polynomial. By showing that in these cases, if the group is not hyperbolic, then the random Dehn function is strictly smaller than the usual Dehn function we confirm Gromov's in

Pasha Andreyanov, Ilia Krasikov, Alex Suzdaltsev

We study buyer-optimal procurement mechanisms when quality is contractible. When some costs are borne by every participant of a procurement auction regardless of winning, the classic analysis should be amended. We show that an optimal symmetric mechanism is a scoring auction with a score function that may be either flatter or steeper than classically. This d

Zhehan Kan, Ce Zhang, Zihan Liao, Yapeng Tian

Large Vision-Language Model (LVLM) systems have demonstrated impressive vision-language reasoning capabilities but suffer from pervasive and severe hallucination issues, posing significant risks in critical domains such as healthcare and autonomous systems. Despite previous efforts to mitigate hallucinations, a persistent issue remains: visual defect from vi

Ahmed Akib Jawad Karim, Muhammad Zawad Mahmud, Samiha Islam, Aznur Azam

In this research, we explored the improvement in terms of multi-class disease classification via pre-trained language models over Medical-Abstracts-TC-Corpus that spans five medical conditions. We excluded non-cancer conditions and examined four specific diseases. We assessed four LLMs, BioBERT, XLNet, and BERT, as well as a novel base model (Last-BERT). Bio

Chunru Lin, Jugang Fan, Yian Wang, Zeyuan Yang

It is desired to equip robots with the capability of interacting with various soft materials as they are ubiquitous in the real world. While physics simulations are one of the predominant methods for data collection and robot training, simulating soft materials presents considerable challenges. Specifically, it is significantly more costly than simulating ri

Yizhi Chen, Wenyao Zhu, Zhonghai Lu

Network-on-Chip (NoC) based architectures are recently proposed to accelerate deep neural networks in specialized hardware. Given that the hardware configuration is fixed post-manufacture, proper task mapping attracts researchers' interest. We propose a travel time-based task mapping method that allocates uneven counts of tasks across different Processing El

P. Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla

There are few principles or guidelines to ensure evaluations of generative AI (GenAI) models and systems are effective. To help address this gap, we propose a set of general dimensions that capture critical choices involved in GenAI evaluation design. These dimensions include the evaluation setting, the task type, the input source, the interaction style, the

Vincent Kofman, Geronimo Villanueva, Thomas Fauchez, Avi Mandell

The atmospheres and surfaces of planets show tremendous amount of spatial variation, which has a direct effect on the spectrum of the object, even if this may not be spatially resolved. Here, we apply hyper realistic radiative simulations of Earth as an exoplanet comprising thousands of simulations and study the unresolved spectrum. The GlobES module on the

Ayush Singla, Shakson Isaac, Chirag J. Patel

Imaging-based deep learning has transformed healthcare research, yet its clinical adoption remains limited due to challenges in comparing imaging models with traditional non-imaging and tabular data. To bridge this gap, we introduce Barttender, an interpretable framework that uses deep learning for the direct comparison of the utility of imaging versus non-i

Erika Palmerio, Christina Kay, Nada Al-Haddad, Benjamin J. Lynch

Understanding and predicting the structure and evolution of coronal mass ejections (CMEs) in the heliosphere remains one of the most sought-after goals in heliophysics and space weather research. A powerful tool for improving current knowledge and capabilities consists of multi-spacecraft observations of the same event, which take place when two or more spac

Carolina Núñez, John W. Appel, Rahul Datta, Charles L. Bennett

We present the in-lab and on-sky performance for the upgraded 90 GHz focal plane of the Cosmology Large Angular Scale Surveyor (CLASS), which had four of its seven detector wafers updated during the austral winter of 2022. The update aimed to improve the transition-edge-sensor (TES) stability and bias range and to realize the high optical efficiency of the s

Kara L. Kniezewski, Emily I. Mason, Vadim M. Uritsky, Seth H. Garland

Thermal changes in coronal loops are well-studied, both in quiescent active regions and in flaring scenarios. However, relatively little attention has been paid to loop emission in the hours before the onset of a solar flare; here, we present the findings of a study of over 50 off-limb flares of GOES class C5.0 and above. We investigated the integrated emiss

Ahmed Akib Jawad Karim, Kazi Hafiz Md Asad, Aznur Azam

The rapid spread of misinformation, particularly through online platforms, underscores the urgent need for reliable detection systems. This study explores the utilization of machine learning and natural language processing, specifically Support Vector Machines (SVM) and BERT, to detect fake news. We employ three distinct text vectorization methods for SVM: T

Yishai Klein, Edward Strizhevsky, Haim Aknin, Moshe Deutsch

The invention of X-ray interferometers has led to advanced phase-sensing devices that are invaluable in various applications. These include the precise measurement of universal constants, e.g. the Avogadro number, of lattice parameters of perfect crystals, and phase-contrast imaging, which resolves details that standard absorption imaging cannot capture. How

Huaizhi Ge, Yiming Li, Qifan Wang, Yongfeng Zhang

Large Language Models (LLMs) are known to be vulnerable to backdoor attacks, where triggers embedded in poisoned samples can maliciously alter LLMs' behaviors. In this paper, we move beyond attacking LLMs and instead examine backdoor attacks through the novel lens of natural language explanations. Specifically, we leverage LLMs' generative capabilities to pr

Fan Chen, Nicholas Martin, Po-Yu Chen, Xiaozhen Wang

Deciding bank interest rates has been a long-standing challenge in finance. It is crucial to ensure that the selected rates balance market share and profitability. However, traditional approaches typically focus on the interest rate changes of individual banks, often neglecting the interactions with other banks in the market. This work proposes a novel frame

Arnab Bhattacharyya, Davin Choo, Philips George John, Themis Gouleakis

We revisit the problem of distribution learning within the framework of learning-augmented algorithms. In this setting, we explore the scenario where a probability distribution is provided as potentially inaccurate advice on the true, unknown distribution. Our objective is to develop learning algorithms whose sample complexity decreases as the quality of the

Haipeng An, Qi Chen, Yuhang Li, Yuan Yin

In this study, we explore the back reaction of phase transitions in the spectator sector on the inflaton field during slow-roll inflation. Due to the significant excursion of the inflaton field, these phase transitions are likely to occur and can induce substantial non-Gaussian correlations in the curvature perturbation. Our results suggest that these correl

Mario Raeth, Klaus Hallatschek

This paper investigates the energy fluxes for the 6D kinetic Vlasov system. We introduce a novel method for calculating particle and energy flows within this framework which allows for the determination of energy and particle fluxes, as well as the Poynting flux, directly from the system's moments such as kinetic energy density, momentum transfer tensor. The