November 2024 arXiv papers — page 99

Jianhong Tu, Zhuohao Ni, Nicholas Crispino, Zihao Yu

We present a novel visual instruction tuning strategy to improve the zero-shot task generalization of multimodal large language models by building a firm text-only knowledge base. Existing work lacks sufficient experimentation on the importance of each modality in the instruction tuning stage, often using a majority of vision-language data while keeping text

Sudhanva Lalit, Alexandra C. Semposki, Joshua M. Maldonado

We emulate the Tolman-Oppenheimer-Volkoff (TOV) equations, including tidal deformability, for neutron stars using a new method based upon the Dynamic Mode Decomposition (DMD). This method, which we call Star Log-extended eMulation (SLM), utilizes the underlying logarithmic behavior of the differential equations to enable accurate emulation of the nonlinear s

Peter Halmos, Xinhao Liu, Julian Gold, Benjamin J Raphael

Optimal transport (OT) is a general framework for finding a minimum-cost transport plan, or coupling, between probability distributions, and has many applications in machine learning. A key challenge in applying OT to massive datasets is the quadratic scaling of the coupling matrix with the size of the dataset. [Forrow et al. 2019] introduced a factored coup

Yutao Tang, Yuxiang Guo, Deming Li, Cheng Peng

Recent efforts in Gaussian-Splat-based Novel View Synthesis can achieve photorealistic rendering; however, such capability is limited in sparse-view scenarios due to sparse initialization and over-fitting floaters. Recent progress in depth estimation and alignment can provide dense point cloud with few views; however, the resulting pose accuracy is suboptima

Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Estelle Aflalo

Large Multi-Modal Models (LMMs) have demonstrated impressive capabilities as general-purpose chatbots able to engage in conversations about visual inputs. However, their responses are influenced by societal biases present in their training datasets, leading to undesirable differences in how the model responds when presented with images depicting people of di

Jean-Luc Garden

The nonequilibrium work relation, or Jarzynski equality, establishes a statistical relationship between a series of nonequilibrium experiments on a system subjected to thermal fluctuations and a hypothetical experiment at thermodynamic equilibrium. In these experiments, the fluctuating quantity is the work exchanged between the system and its environment, wh

Boris Mityagin, Petr Siegl

We revisit the local form subordination condition on the perturbation of a self-adjoint operators with compact resolvent, which is used to show the Riesz basis property of the eigensystem of the perturbed operator. Our new assumptions and new proof allow for establishing the Riesz basis property also in the case of slow and non-monotone decay in this subordi

Maria C. Babiuc Hamilton, William A. Messman

Gravitational Wave (GW) signals from Binary Neutron Star (BNS) mergers provide critical insights into the properties of matter under extreme conditions. Due to the scarcity of observational data, Numerical Relativity (NR) simulations are indispensable for exploring these phenomena. However, simulating BNS mergers is a formidable challenge, and ensuring the c

Sangeeta Saha, Swadesh Pal, Roderick Melnik

Phenotypic plasticity is a key factor in driving the evolution of species in the predator-prey interaction. The natural environment is replete with phenotypic plasticity, which is the source of inducible defences against predators, including concealment, cave-dwelling, mimicry, evasion, and revenge. In this work, a predator-prey model is proposed where the p

D. Ferraro, M. Campisi, G. M. Andolina, V. Pellegrini

In this short communication we reply to the comment by Xu and Li (arXiv:2411.04132) on our first work on Dicke quantum batteries (Phys. Rev. Lett. 120, 117702 (2018)).

James D. Serna, Alexander Yu. Sokolov

Theoretical simulations of electron detachment processes are vital for understanding chemical redox reactions, semiconductor and electrochemical properties, and high-energy radiation damage. However, accurate calculations of ionized electronic states are very challenging due to their open-shell nature, importance of electron correlation effects, and strong i

Travis Dillon

This paper proves a 2017 conjecture of De Loera, La Haye, Oliveros, and Rold\'an-Pensado that the "prime grid" $\big\{(p,q) \in \mathbb{Z}^2 : \text{$p$ and $q$ are prime}\big\} \subseteq \mathbb{R}^2$ contains empty polygons with arbitrarily many vertices. This implies that no Helly-type theorem is true for the prime grid.

Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves

Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increasingly relies on computational scale, with recent protein language models (pLM) training on hundreds of graphical processing units (GPUs). We introduce the BioNeMo Framework to faci

Edward Kembery, Tom Reed

The downstream use cases, benefits, and risks of AI models depend significantly on what sort of access is provided to the model, and who it is provided to. Though existing safety frameworks and AI developer usage policies recognise that the risk posed by a given model depends on the level of access provided to a given audience, the procedures they use to mak

Yifu Tao, Miguel Ángel Muñoz-Bañón, Lintong Zhang, Jiahao Wang

This paper introduces a large-scale multi-modal dataset captured in and around well-known landmarks in Oxford using a custom-built multi-sensor perception unit as well as a millimetre-accurate map from a Terrestrial LiDAR Scanner (TLS). The perception unit includes three synchronised global shutter colour cameras, an automotive 3D LiDAR scanner, and an inert

Oem Trivedi, Abraham Loeb

Relations between the graviton mass and the cosmological constant $\Lambda$ have led to some interesting implications. We show that in any approach which leads to a direct correlation between the graviton mass and $\Lambda$, either through direct substitution of gravitational coupling in dispersion relations or through the linearization of Einstein equations

Hesam Hosseini, Ghazal Hosseini Mighan, Amirabbas Afzali, Sajjad Amini

Transformers have revolutionized Computer Vision (CV) through self-attention mechanisms. However, their complexity makes latent token representations difficult to interpret. We introduce ULTra, a framework for interpreting Transformer embeddings and uncovering meaningful semantic patterns within them. ULTra enables unsupervised semantic segmentation using pr

Amrit Khera, Rajat Ghosh, Debojyoti Dutta

LLM alignment ensures that large language models behave safely and effectively by aligning their outputs with human values, goals, and intentions. Aligning LLMs employ huge amounts of data, computation, and time. Moreover, curating data with human feedback is expensive and takes time. Recent research depicts the benefit of data engineering in the fine-tuning

Ankita Agarwal, Tanvi Banerjee, William Romine, Mia Cajita

Artificial intelligence based predictive models trained on the clinical notes can be demographically biased. This could lead to adverse healthcare disparities in predicting outcomes like length of stay of the patients. Thus, it is necessary to mitigate the demographic biases within these models. We proposed an implicit in-processing debiasing method to comba

Priyansh Bhatnagar, Linfeng Wen, Mingu Kang

Extensive efforts have been made to boost the performance in the domain of language models by introducing various attention-based transformers. However, the inclusion of linear layers with large dimensions contributes to significant computational and memory overheads. The escalating computational demands of these models necessitate the development of various

Itay M. Bloch, Simon Knapen, Amalia Madden, Giacomo Marocco

We show that axion dark matter in the range meV $\lesssim m_a\lesssim$ 100 meV can incoherently excite phonons in crystal targets with unpolarised nuclear spins. This can occur through its coupling to nuclear spins and/or through its induced time-dependent electric dipole moment in nuclei. Due to the random orientation of the nuclear spins, translation symme

Jia He, Mukund Rungta, David Koleczek, Arshdeep Sekhon

In the realm of Large Language Models (LLMs), prompt optimization is crucial for model performance. Although previous research has explored aspects like rephrasing prompt contexts, using various prompting techniques (like in-context learning and chain-of-thought), and ordering few-shot examples, our understanding of LLM sensitivity to prompt templates remain

Mingshu Zhao

We investigate spatiotemporal chaos in Bose-Einstein condensate (BEC) confined by a 1D harmonic trap using Gross-Pitaevskii equation simulations. The chaos arises from nonlinear mixing of ground and excited states, confirmed by positive Lyapunov exponents. By sampling the density field at intervals matching the center-of-mass oscillation period, we analyze t

Andrew J. Larkoski

We study the binary discrimination problem of identification of boosted $H\to gg$ decays from massive QCD jets in a systematic expansion in the strong coupling. Though this decay mode of the Higgs is unlikely to be discovered at the LHC, we analytically demonstrate several features of the likelihood ratio for this problem through explicit analysis of signal

C. A. Walsh, D. J. Strozzi, A. Povilus, S. T. O'Neill

This paper explores 4 different magnetic field topologies for application to spherical inertial confinement fusion implosions: axial, mirror, cusp and closed field lines. A mirror field is found to enhance the impact of magnetization over an axial field; this is because the mirror field more closely follows the hot-spot surface. A cusp field, while simple to

Ali Ahmad Khostovan, Jeyhan S. Kartaltepe, Malte Brinch, Caitlin Casey

We present a detailed analysis of EELG1002: a $z = 0.8275$ EELG identified within archival Gemini/GMOS spectroscopy as part of the on-going COSMOS Spectroscopic Archive. We find EELG1002 is a low-mass ($\sim10^{8}$ M$_\odot$), compact ($\sim530$ pc), bursty star-forming galaxy with a $\sim15-35$ Myr mass doubling timescale. EELG1002 has record-breaking rest-

Max Taylor-Davies, Gautier Hamon, Timothé Boulet, Clément Moulin-Frier

Kin selection theory has proven to be a popular and widely accepted account of how altruistic behaviour can evolve under natural selection. Hamilton's rule, first published in 1964, has since been experimentally validated across a range of different species and social behaviours. In contrast to this large body of work in natural populations, however, there h

Urvishkumar Bharti, Vikram Shahapur

In autonomous driving, perception systems are piv otal as they interpret sensory data to understand the envi ronment, which is essential for decision-making and planning. Ensuring the safety of these perception systems is fundamental for achieving high-level autonomy, allowing us to confidently delegate driving and monitoring tasks to machines. This re port

Andrew Konya, Aviv Ovadya, Kevin Feng, Quan Ze Chen

We introduce a method to measure the alignment between public will and language model (LM) behavior that can be applied to fine-tuning, online oversight, and pre-release safety checks. Our `chain of alignment' (CoA) approach produces a rule based reward (RBR) by creating model behavior $\textit{rules}$ aligned to normative $\textit{objectives}$ aligned to $\

Eva Portelance, Masoud Jasbi

In mid-20th century, the linguist Noam Chomsky established generative linguistics, and made significant contributions to linguistics, computer science, and cognitive science by developing the computational and philosophical foundations for a theory that defined language as a formal system, instantiated in human minds or artificial machines. These development

Danny Perez, Aidan Thompson, Stan Moore, Tomas Oppelstrup

The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have howeve

Xiuyuan Zhang, Yi Jia, Tracy R. Slatyer

We study the detectability of GeV-band gamma-ray polarization with the AMS-02 experiment and its proposed successor AMS-100, from Galactic and extragalactic sources. Characterizing gamma-ray polarization in this energy range could shed light on gamma-ray emission mechanisms in the sources; physics beyond the Standard Model, such as the presence of axion-like

Ettore Aldrovandi, Milind Gunjal

We study monoidal 2-categories and bicategories in terms of categorical extensions and the cohomological data they determine in appropriate cohomology theories with coefficients in Picard groupoids. In particular, we analyze the hierarchy of possible commutativity conditions in terms of progressive stabilization of these data. We also show that monoidal stru

Kai-Feng Chen, Michael J. Wilensky, Adrian Liu, Joshua S. Dillon

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of

Babak Taheri, Daniel K. Molzahn

Optimal Transmission Switching (OTS) problems minimize operational costs while treating both the transmission line energization statuses and generator setpoints as decision variables. The combination of nonlinearities from an AC power flow model and discrete variables associated with line statuses makes AC-OTS a computationally challenging Mixed-Integer Nonl

Alex May, Sabrina Pasterski, Chris Waddell, Michelle Xu

In the AdS/CFT correspondence, a subregion of the CFT allows for the recovery of a corresponding subregion of the bulk known as its entanglement wedge. In some cases, an entanglement wedge contains a locally but not globally minimal surface homologous to the CFT subregion, in which case it is said to contain a python's lunch. It has been proposed that python

T. Daniel Brennan, Jaipratap Singh Grewal, Eric Y. Yang

We revisit the problem of a charged particle scattering off of an Aharonov-Bohm cosmic string. A classic computation gave an infinite total scattering cross section, leading to a Callan-Rubakov-like enhancement which can have important implications on baryon number asymmetry in the early universe. However, unlike the Callan-Rubakov effect, the Aharonov-Bohm

Dharmender, Ravi Joshi, Michele Fumagalli, Pasquier Noterdaeme

We aim to constrain the average star formation associated with neutral hydrogen gas reservoirs at cosmic noon. Using a unprecedented sample of 1716 high column density Damped Ly-$\alpha$ absorbers (DLAs) from the Sloan Digital Sky Survey with log($N$(HI) / cm$^{-2}$) $\ge$21, we generated the average Ly-$\alpha$ emission spectrum associated to DLAs, free fro

Yasemin Karacora, Adam Umra, Aydin Sezgin

Terahertz (THz) communication offers the necessary bandwidth to meet the high data rate demands of next-generation wireless systems. However, it faces significant challenges, including severe path loss, dynamic blockages, and beam misalignment, which jeopardize communication reliability. Given that many 6G use cases require both high data rates and strong re

Adrián del Río, F. Javier Marañón-González, José Navarro-Salas

We analyze the semiclassical Schwarzschild geometry in the Boulware quantum state in the framework of two-dimensional (2D) dilaton gravity. The classical model is defined by the spherical reduction of Einstein's gravity sourced with conformal scalar fields. The expectation value of the stress-energy tensor in the Boulware state is singular at the classical h

Gregory S. Boebinger, Andrey V. Chubukov, Ian R. Fisher, F. Malte Grosche

The field of hydride superconductivity has recently been mired in a controversy that might divert attention from the question of central importance: do hydrides support genuine superconductivity or not? We examine some key papers from the field, and conclude that hydride superconductivity is real.

Florian Niedermann, Martin S. Sloth

We explore the possibility that exotic forms of dark matter could expose humans on Earth or on prolonged space travel to a significant radiation dose. The radiation exposure from dark matter interacting with nuclei in the human body is generally assumed to be negligible compared to other sources of background radiation. However, as we discuss here, current d

Amanda L. Ash, Marc H. Pinsonneault, Mathieu Vrard, Joel Zinn

Nearly all cool, evolved stars are solar-like oscillators, and fundamental stellar properties can be inferred from these oscillations with asteroseismology. Scaling relations are commonly used to relate global asteroseismic properties, the frequency of maximum power $\nu_{max}$ and the large frequency separation $\Delta \nu$, to stellar properties. Mass, rad

Nima Laal, Stephen R. Taylor, Luke Zoltan Kelley, Joseph Simon

While supermassive black-hole (SMBH)-binaries are not the only viable source for the low-frequency gravitational wave background (GWB) signal evidenced by the most recent pulsar timing array (PTA) data sets, they are expected to be the most likely. Thus, connecting the measured PTA GWB spectrum and the underlying physics governing the demographics and dynami

Joshua Bennett Lovell, Kristina Monsch, Garrett K. Keating, David J. Wilner

We present images of IRAS~08235--4316 with the Dark Energy Camera Plane Survey (DECaPS; spanning 0.398--1.034$\,\mu$m, at ${\sim}1''$ resolution) and the Submillimeter Array (SMA; at 1.38\,mm/217\,GHz, at ${\sim}1.9''\times1.2''$ resolution), a YSO located in the Vela constellation near to the Puppis boundary, detected in a systematic search for new large/ex

Oleh Ryzhov, Michał J. Michałowski, J. Nadolny, J. Hjorth

Quenching of star-formation plays a fundamental role in galaxy evolution. This process occurs due to the removal of the cold interstellar medium (ISM) or stabilization against collapse, so that gas cannot be used in the formation of new stars. In this paper, we study the effect of different mechanisms of ISM removal. In particular, we revised the well-known

Asimina Arvanitaki, Jonathan Engel, Andrew A. Geraci, Alexander Hepburn

We show that piezoelectric materials can be used to source virtual QCD axions, generating a new axion-mediated force. Spontaneous parity violation within the piezoelectric crystal combined with time-reversal violation from aligned spins provide the necessary symmetry breaking to produce an effective in-medium scalar coupling of the axion to nucleons up to 7

Yu-Ping Lin, Vidya Madhavan, Joel E. Moore

We show that ultrafast optical pump pulses provide effective control over charge orders in the kagome metals $A$V$_3$Sb$_5$ with $A=$ K, Rb, and Cs. Starting from the real charge density waves (rCDWs) at the $p$-type Van Hove singularity, we conduct a thorough analysis of the post-pump dynamics by time-dependent Hartree-Fock theory. Our analysis uncovers dis

Daniel Ekpo, Mara Levy, Saksham Suri, Chuong Huynh

Recent progress in vision-language models (VLMs) has opened new possibilities for robot task planning, but these models often produce incorrect action sequences. To address these limitations, we propose VeriGraph, a novel framework that integrates VLMs for robotic planning while verifying action feasibility. VeriGraph uses scene graphs as an intermediate rep

Yang Zhang, Suk Hyun Sung, Colin B. Clement, Sang-Wook Cheong

In many condensed matter systems, long range order emerges at low temperatures as thermal fluctuations subside. In the presence of competing interactions or quenched disorder, however, some systems can show unusual configurations that become more disordered at low temperature, a rare phenomenon known as "inverse melting". Here, we discover an inverse melting

Jake Robbennolt, Meiyi Li, Javad Mohammadi, Stephen D. Boyles

Shared autonomous electric vehicles can provide on-demand transportation for passengers while also interacting extensively with the electric distribution system. This interaction is especially beneficial after a disaster when the large battery capacity of the fleet can be used to restore critical electric loads. We develop a dispatch policy that balances the

Debora Amadori, Alberto Bressan, Wen Shen

The paper is concerned with a scalar conservation law with discontinuous gradient-dependent flux. Namely, the flux is described by two different functions $f(u)$ or $g(u)$, when the gradient $u_x$ of the solution is positive or negative, respectively. We study here the stable case where $f(u)<g(u)$ for all $u\in {\mathbb R}$, with $f,g$ smooth but possibly n

Weiyun Wang, Zhe Chen, Wenhai Wang, Yue Cao

Existing open-source multimodal large language models (MLLMs) generally follow a training process involving pre-training and supervised fine-tuning. However, these models suffer from distribution shifts, which limit their multimodal reasoning, particularly in the Chain-of-Thought (CoT) performance. To address this, we introduce a preference optimization (PO)

Sang Kyu Kim, Eduardo Zubizarreta Casalengua, Katarina Boos, Friedrich Sbresny

Single-photon emission from a two-level system offers promising perspectives for the development of quantum technologies, where multiphotons are generally regarded as accidental, undesired and should be suppressed. In quantum mechanics, however, multiphoton emission can turn out to be even more fundamental and interesting than the single-photon emission, sin

Guowei Xu, Peng Jin, Ziang Wu, Hao Li

Large language models have demonstrated substantial advancements in reasoning capabilities. However, current Vision-Language Models (VLMs) often struggle to perform systematic and structured reasoning, especially when handling complex visual question-answering tasks. In this work, we introduce LLaVA-CoT, a large VLM designed to conduct autonomous multistage

Vlassis Mastrantonis

$L^p$-polarity and $L^p$-Mahler volumes were recently introduced by Berndtsson, Rubinstein, and the author as a new approach, inspired by complex geometry, to the Mahler, Bourgain, and Blocki conjectures. This paper serves two purposes. First, it introduces functional analogues of these notions and establishes functional versions of key theorems previously f

Huizhuo Yuan, Yifeng Liu, Shuang Wu, Xun Zhou

Training deep neural networks--and more recently, large models demands efficient and scalable optimizers. Adaptive gradient algorithms like Adam, AdamW, and their variants have been central to this task. Despite the development of numerous variance reduction algorithms in the past decade aimed at accelerating stochastic optimization in both convex and noncon

Reza Kashtiban, Gavin W. Morley, Mark E. Newton, A T M Anishur Rahman

The nitrogen vacancy (NV) center in diamond is a versatile color center used for magnetometry, quantum computing, and quantum communications. In this article, using a single laser beam as a pump and probe, we measure the spin states of the NV center using the Faraday effect and use such measurements to develop a novel magnetic field sensor. Using the spin-st

Yuhan Fu, Ruobing Xie, Xingwu Sun, Zhanhui Kang

Multimodal Large Language Models (MLLMs) are known to hallucinate, which limits their practical applications. Recent works have attempted to apply Direct Preference Optimization (DPO) to enhance the performance of MLLMs, but have shown inconsistent improvements in mitigating hallucinations. To address this issue more effectively, we introduce Hallucination-t

Yandong Li, Francesco Monticone

Similar to algorithms, which consume time and memory to run, hardware requires resources to function. For devices processing physical waves, implementing operations needs sufficient "space," as dictated by wave physics. How much space is needed to perform a certain function is a fundamental question in optics, with recent research addressing it for given mat

Yannan Bai, Kamesh Munagala, Yiheng Shen, Ian Zhang

In this paper, we consider the classic fair division problem of allocating $m$ divisible items to $n$ agents with linear valuations over the items. We define novel notions of fair shares from the perspective of individual agents via the cake-cutting process. These shares generalize the notion of proportionality by taking into account the valuations of other

Sucheng Ren, Yaodong Yu, Nataniel Ruiz, Feng Wang

There exists recent work in computer vision, named VAR, that proposes a new autoregressive paradigm for image generation. Diverging from the vanilla next-token prediction, VAR structurally reformulates the image generation into a coarse to fine next-scale prediction. In this paper, we show that this scale-wise autoregressive framework can be effectively deco

Josef Leutgeb, Jonas Mager, Anton Rebhan

In this paper, we consider hard-wall AdS/QCD models extended by a string-theory inspired Chern-Simons action in terms of a superconnection involving a bi-fundamental scalar field which corresponds to the open-string tachyon of brane-antibrane configurations and which is naturally identified with the holographic dual of the quark condensate in chiral symmetry

Hannah Lange, Annika Böhler, Christopher Roth, Annabelle Bohrdt

Simulating large, strongly interacting fermionic systems remains a major challenge for existing numerical methods. In this work, we introduce Gutzwiller projected hidden fermion determinant states (G-HFDS) to simulate the strongly interacting limit of the Fermi-Hubbard model, namely the $t$-$J$ model, across the entire doping regime. We demonstrate that the

Shreya Meel, Pasan Dissanayake, Mohamed Nomeir, Sanghamitra Dutta

In a classification task, counterfactual explanations provide the minimum change needed for an input to be classified into a favorable class. We consider the problem of privately retrieving the exact closest counterfactual from a database of accepted samples while enforcing that certain features of the input sample cannot be changed, i.e., they are \emph{imm

Keck Collaboration, P. A. R. Ade, Z. Ahmed, M. Amiri

Millimeter-wave refracting telescopes targeting the degree-scale structure of the cosmic microwave background (CMB) have recently grown to diffraction-limited apertures of over 0.5 meters. These instruments are entirely housed in vacuum cryostats to support their sub-kelvin bolometric detectors and to minimize radiative loading from thermal emission due to a

Jozsef Vinko, Eniko Regos

Supernovae (SNe) discovered in high-redshift (z > 2) galaxies by the James Webb Space Telescope (JWST) provide a unique opportunity to extend the Hubble-diagram beyond z~1.5 and constrain the cosmic Star Formation Rate in the early Universe. SN~2023adsy, a Type Ia supernova discovered by JWST at z=2.9, was found to be a peculiar event, being extremely red an

J. Tauber, J. Asnacios, L. Mahadevan

Self-organized branching structures can emerge spontaneously as interfacial instabilities in both simple and complex fluids, driven by the interplay between bulk material rheology, boundary constraints, and interfacial forcing. In our experiments, injecting dye between a source and a sink in a Hele-Shaw cell filled with a yield-stress fluid reveals an abrupt

Mykola Matviichuk, Brent Pym, Travis Schedler

We construct a large collection of "quantum projective spaces", in the form of Koszul, Calabi-Yau algebras with the Hilbert series of a polynomial ring. We do so by starting with the toric ones (the q-symmetric algebras), and then deforming their relations using a diagrammatic calculus, proving unobstructedness of such deformations under suitable nondegenera

Anna Gamża, Sam Lycett, Aeron Sanchez, Rowland Kao

H5N1 highly pathogenic avian influenza (HPAI) has been recently circulating in previously unseen patterns. As the underlying causes are uncertain, we need a better understanding of the drivers of virus circulation, as they underpin the spread, and inform about the impact of HPAI. We combine infection and bird population data, using Random Forest models to qu

Simone Carnemolla, Salvatore Calcagno, Simone Palazzo, Daniela Giordano

Speech segmentation at both word and phoneme levels is crucial for various speech processing tasks. It significantly aids in extracting meaningful units from an utterance, thus enabling the generation of discrete elements. In this work we propose a model-agnostic framework to perform word boundary detection in a supervised manner also employing a labels augm

Parsa Hejabi, Elnaz Rahmati, Alireza S. Ziabari, Preni Golazizian

Large Language Models (LLMs) have shown impressive capabilities in complex tasks and interactive environments, yet their creativity remains underexplored. This paper introduces a simulation framework utilizing the game Balderdash to evaluate both the creativity and logical reasoning of LLMs. In Balderdash, players generate fictitious definitions for obscure

Katelin E. J Scott, Maria F. Hermosillo Arrieta, Aislinn J. Williams

SCN2A encodes the alpha subunit of the voltage-gated sodium channel Nav1.2, which is involved in action potential initiation and backpropagation in glutamatergic neurons. Mutations in the gene lead to SCN2A-related disorders, which are highly heterogeneous and manifest in a variety of diagnoses, such as self-limited familial and non-familial infantile epilep

Tomás Ortín, Matteo Zatti

We propose a simple algorithm to compute the generalized Komar charge of any exactly gauge- and diffeomorphism-invariant theory.

Martin Hairer, Sam Punshon-Smith, Tommaso Rosati, Jaeyun Yi

We consider the top Lyapunov exponent associated to the advection-diffusion and linearised Navier-Stokes equations on the two-dimensional torus. The velocity field is given by the stochastic Navier-Stokes equations driven by a non-degenerate white-in-time noise with a power-law correlation structure. We show that the top Lyapunov exponent is bounded from bel

Mahsa Khazaei, Azim Ahmadzadeh, Krishna Rukmini Puthucode

Quantifying similarities between time series in a meaningful way remains a challenge in time series analysis, despite many advances in the field. Most real-world solutions still rely on a few popular measures, such as Euclidean Distance (EuD), Longest Common Subsequence (LCSS), and Dynamic Time Warping (DTW). The strengths and weaknesses of these measures ha

Tomás Ortín, Matteo Zatti

The Cano-Ruip\'erez 4-dimensional string effective action is the simplest consistent truncation of the first-order in $\alpha'$ heterotic string effective action compactified on T$^{6}$. This theory contains, on top of the metric, a dilaton and an axion that couple to the Gauss-Bonnet term and to the Pontrjagin density which suggests a very strong relation b

Mehrnoosh Mirtaheri, Nikhil Varghese, Chandra Khatri, Amol Kelkar

Task-oriented dialogue systems rely on predefined conversation schemes (dialogue flows) often represented as directed acyclic graphs. These flows can be manually designed or automatically generated from previously recorded conversations. Due to variations in domain expertise or reliance on different sets of prior conversations, these dialogue flows can manif

Michal Kolesár, Mikkel Plagborg-Møller

Applied macroeconomists frequently use impulse response estimators motivated by linear models. We study whether the estimands of such procedures have a causal interpretation when the true data generating process is in fact nonlinear. We show that vector autoregressions and linear local projections onto observed shocks or proxies identify weighted averages of

Jianfeng Chi, Ujjwal Karn, Hongyuan Zhan, Eric Smith

We introduce Llama Guard 3 Vision, a multimodal LLM-based safeguard for human-AI conversations that involves image understanding: it can be used to safeguard content for both multimodal LLM inputs (prompt classification) and outputs (response classification). Unlike the previous text-only Llama Guard versions (Inan et al., 2023; Llama Team, 2024b,a), it is s

Claudio Emma, Nathan Majernik, Kelly Swanson, Robert Ariniello

In this Letter we report on the experimental generation of high energy (10 GeV), ultra-short (fs-duration), ultra-high current (0.1 MA), petawatt peak power electron beams in a particle accelerator. These extreme beams enable the exploration of a new frontier of high intensity beam-light and beam-matter interactions broadly relevant across fields ranging fro

K. James Sangston

This work examines the problem of extending the one-dimensional analytic signal, which is ubiquitous throughout signal processing, to higher dimensional signals. Bulow et al. and Felsberg et al. have previously used techniques from Clifford algebra and analysis to extend the one-dimensional analytic signal to higher dimensions. However, each author sets fort

Markus Karmann, Onay Urfalioglu

Recent progress in interactive point prompt based Image Segmentation allows to significantly reduce the manual effort to obtain high quality semantic labels. State-of-the-art unsupervised methods use self-supervised pre-trained models to obtain pseudo-labels which are used in training a prompt-based segmentation model. In this paper, we propose a novel unsup

Hunter J. Frost, Ekta Bhatia, Zhihao Xiao, Stephen Olson

The integration of superconducting niobium and tantalum into superconducting quantum devices has been increasingly explored over the past few years. Recent developments have shown that two-level-systems (TLS) in the surface oxides of these superconducting films are a leading source of decoherence in quantum circuits, and understanding the surface oxidation k

Henry Wegener, Sarah Paczkowski, Marie-Sophie Hartig, Martin Hewitson

Tilts of certain elements within a laser interferometer can undesirably couple into measurements as a form of noise, known as tilt-to-length (TTL) coupling. This TTL coupling is anticipated to be one of the primary noise sources in the Laser Interferometer Space Antenna (LISA) mission, after Time Delay Interferometry (TDI) is applied. Despite the careful int

Amadeu Delshams, Mercè Ollé, Juan Ramon Pacha, Óscar Rodríguez

We consider the Rydberg electron in a circularly polarized microwave field, whose dynamics is described by a 2 d.o.f. Hamiltonian, which is a perturbation of size $K>0$ of the standard rotating Kepler problem. In a rotating frame, the largest chaotic region of this system lies around a center-saddle equilibrium point $L_1$ and its associated invariant manifo

Masoud Mohseni, Artur Scherer, K. Grace Johnson, Oded Wertheim

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits. Nevertheless, there are significant outstanding challenges in quantum hardware, fabrication, software arch

Doron Shterman, Guy Bartal

Structured Illumination Microscopy (SIM) overcomes the optical diffraction limit by folding high-frequency components into the baseband of the optical system, where they can be extracted and then repositioned to their original location in the Fourier domain. Although SIM is considered superior to other super-resolution (SR) methods in terms of compatibility

Akshat Mudgal

Let $\textrm{Mat}_2(\mathbb{R})$ be the set of $2 \times 2$ matrices with real entries. For any $\varepsilon>0$ and any finitely--supported probability measure $\mu$ on $\textrm{Mat}_2(\mathbb{R})$, we prove that either \[ T(\mu) = \sum_{X, Y \in {\rm supp}(\mu), XY = YX} \mu(X) \mu(Y) < \varepsilon \] or there exists some finite set ${S}$ contained in a $2$

Chi Zhang, Michael Loecher, Cagan Alkan, Mahmut Yurt

In recent years, machine learning (ML) based reconstruction has been widely investigated and employed in cardiac magnetic resonance (CMR) imaging. ML-based reconstructions can deliver clinically acceptable image quality under substantially accelerated scans. ML-based reconstruction, however, also requires substantial data and computational time to train the

M. Brady, J. Bean, G. Stefánsson, N. Brown

A star's spin-orbit angle can give us insight into a system's formation and dynamical history. In this paper, we use MAROON-X observations of the Rossiter-McLaughlin (RM) effect to measure the projected obliquity of the LP 261-75 (also known as TOI-1779) system, focusing on the fully-convective M dwarf LP 261-75A and the transiting brown dwarf LP 261-75C. Th

Sambatra Andrianomena, Sultan Hassan

We present an approach that can be utilized in order to account for the covariate shift between two datasets of the same observable with different distributions. This helps improve the generalizability of a neural network model trained on in-distribution samples (IDs) when inferring cosmology at the field level on out-of-distribution samples (OODs) of {\it u

Alon Gurman, Ulrich P. Steinwandel, Chia-Yu Hu, Amiel Sterberg

Galaxies at redshift $z\sim 1-2$ display high star formation rates (SFRs) with elevated cold gas fractions and column densities. Simulating a self-regulated ISM in a hydrodynamical, self-consistent context, has proven challenging due to strong outflows triggered by supernova (SN) feedback. At sufficiently high gas column densities, if magnetic fields or othe

Suresh Eswarathasan, Allan Greenleaf, Blake Keeler

The study of the asymptotics of the spectral function for self-adjoint, elliptic differential, or more generally pseudodifferential, operators on a compact manifold has a long history. The seminal 1968 paper of H\"ormander, following important prior contributions by G\"arding, Levitan, Avakumovi\'c, and Agmon-Kannai (to name only some), obtained pointwise as

Ryan S. Brill, Abraham J. Wyner

A longstanding question in the judgment and decision making literature is whether experts, even in high-stakes environments, exhibit the same cognitive biases observed in controlled experiments with inexperienced participants. Massey and Thaler (2013) claim to have found an example of bias and irrationality in expert decision making: general managers' behavi

Zhao-Fan Cai, Yu-Chun Wang, Yu-Ran Zhang, Tao Liu

The non-Hermitian skin effect (NHSE) and nonlinearity can both delocalize topological modes (TMs) from the interface. However, the NHSE requires precise parameter tuning, while nonlinearity in Hermitian systems results in partial delocalization with limited mode capacity. To overcome these limitations, we propose a non-Hermitian nonlinear topological interfa

Jeffrey Olmo, Jared Wilson, Max Forsey, Bryce Hepner

Sparse Autoencoders (SAEs) are a promising approach for extracting neural network representations by learning a sparse and overcomplete decomposition of the network's internal activations. However, SAEs are traditionally trained considering only activation values and not the effect those activations have on downstream computations. This limits the informatio

Christian Jünger, Trevor Chistolini, Long B. Nguyen, Hyunseong Kim

Superinductors have become a crucial component in the superconducting circuit toolbox, playing a key role in the development of more robust qubits. Enhancing the performance of these devices can be achieved by suspending the superinductors from the substrate, thereby reducing stray capacitance. Here, we present a fabrication framework for constructing superc

Nicolas Lang, Robert G. Edwards, Michael J. Peardon

Distillation is a quark-smearing method for the construction of a broad class of hadron operators useful in lattice QCD computations and defined via a projection operator into a vector space of smooth gauge-covariant fields. A new orthonormal basis for this space is constructed which builds in locality. This basis is useful for the construction of stochastic

Carlos Améndola, Kamillo Ferry

A polytrope is a tropical polyhedron that is also classically convex. We study the tropical combinatorial types of polytropes associated to weighted directed acyclic graphs (DAGs). This family of polytropes arises in algebraic statistics when describing the model class of max-linear Bayesian networks. We show how the edge weights of a network directly relate