October 2023 arXiv papers — page 57

Adeel Yousaf, Muzammal Naseer, Salman Khan, Fahad Shahbaz Khan

Vision-language models (VLMs) classify the query video by calculating a similarity score between the visual features and text-based class label representations. Recently, large language models (LLMs) have been used to enrich the text-based class labels by enhancing the descriptiveness of the class names. However, these improvements are restricted to the text

Lāsma Puķina-Slava, Andrejs Tatuļčenkovs, Andrejs Cēbers, Guntars Kitenbergs

Finding solutions for better mixing in microfluidics remains an important challenge, including understanding fundamental aspects of these processes. Here we investigate the magnetic micro-convection on water and miscible magnetic fluid interface in a vertical microfluidic chip to understand what is the role of gravity, as fluids have different densities. Our

E. Emtsova, A. N. Petrov, A. V. Toporensky

We study the energy-momentum characteristics of the plane ``+''-polarised gravitational wave solution of general relativity in the Teleparallel Equivalent of General Relativity (TEGR) and the Symmetric Teleparallel Equivalent of General Relativity (STEGR) using the previously constructed Noether currents. The current components describe locally measured by o

Barbara Sienkiewicz, Gabriela Sejnova, Paul Gajewski, Michal Vavrecka

Spoken language is the most natural way for a human to communicate with a robot. It may seem intuitive that a robot should communicate with users in their native language. However, it is not clear if a user's perception of a robot is affected by the language of interaction. We investigated this question by conducting a study with twenty-three native Czech pa

Kai Sun, Yingjie Hu, Yue Ma, Ryan Zhenqi Zhou

Point of interest (POI) data provide digital representations of places in the real world, and have been increasingly used to understand human-place interactions, support urban management, and build smart cities. Many POI datasets have been developed, which often have different geographic coverages, attribute focuses, and data quality. From time to time, rese

Lingjun Zhao, Khanh Nguyen, Hal Daumé

We investigate the problem of generating instructions to guide humans to navigate in simulated residential environments. A major issue with current models is hallucination: they generate references to actions or objects that are inconsistent with what a human follower would perform or encounter along the described path. We develop a model that detects these

Yihong Ma, Ning Yan, Jiayu Li, Masood Mortazavi

Graphs have emerged as a natural choice to represent and analyze the intricate patterns and rich information of the Web, enabling applications such as online page classification and social recommendation. The prevailing "pre-train, fine-tune" paradigm has been widely adopted in graph machine learning tasks, particularly in scenarios with limited labeled node

Aysa Xuemo Fan, Ranran Haoran Zhang, Luc Paquette, Rui Zhang

In this paper, we explore the application of large language models (LLMs) for generating code-tracing questions in introductory programming courses. We designed targeted prompts for GPT4, guiding it to generate code-tracing questions based on code snippets and descriptions. We established a set of human evaluation metrics to assess the quality of questions p

Barry Wang, Xinya Du, Claire Cardie

The probing classifiers framework has been employed for interpreting deep neural network models for a variety of natural language processing (NLP) applications. Studies, however, have largely focused on sentencelevel NLP tasks. This work is the first to apply the probing paradigm to representations learned for document-level information extraction (IE). We d

Matthew Ball, Raymond Frey, Kara Merfeld

Magnetar vibrational modes are theorized to be associated with energetic X-ray flares. Regular searches for gravitational waves from these modes have been performed by Advanced LIGO and Advanced Virgo, with no detections so far. Presently, search results are given in limits on the root-sum-square of the integrated gravitational-wave strain. However, the incr

Zheyong Fan, Yang Xiao, Yanzhou Wang, Penghua Ying

We propose an efficient approach for simultaneous prediction of thermal and electronic transport properties in complex materials. Firstly, a highly efficient machine-learned neuroevolution potential is trained using reference data from quantum-mechanical density-functional theory calculations. This trained potential is then applied in large-scale molecular d

Nicolas Delfosse, Andres Paz, Alexander Vaschillo, Krysta M. Svore

Achieving practical quantum advantage requires a classical decoding algorithm to identify and correct faults during computation. This classical decoding algorithm must deliver both accuracy and speed, but in what combination? When is a decoder "fast enough" or "accurate enough"? In the case of surface codes, tens of decoding algorithms have been proposed, wi

Ira M. Gessel

We give a short generating function proof of the Almkvist-Meurman theorem: For integers $h$ and $k\ne0$, define the numbers $M_n(h,k)$ by $kx(e^{hx}-1)/(e^{kx}-1)=\sum_{n=0}^\infty M_n(h,k) x^n/n!$. Equivalently, $M_n(h,k) = k^n(B_n(h/k) - B_n)$, where $B_n(u)$ is the Bernoulli polynomial. Then $M_n(h,k)$ is an integer. The proof is related to Postnikov's fu

Michalis Chatzittofi, Jaime Agudo-Canalejo, Ramin Golestanian

The question of characterization of the degree of non-equilibrium activity in active matter systems is studied in the context of a stochastic microswimmer model driven by a chemical cycle. The resulting dynamical properties and entropy production rate unravel a complex interplay between the chemical and the hydrodynamic degrees of freedom beyond linear respo

Michael Sorochan Armstrong, José Carlos Pérez-Girón, José Camacho, Regino Zamora

A simple least-squares optimisation enables the determination of the spectrum for irregularly sampled data that is readily reconstructed using an adjoint transformation of the Non-Uniform Fast Fourier Transform (NFFT). This is an improvement upon previously reported iterative methods for such problems, and is competitive in terms of time complexity with more

Muskan Nabi, Sanika S. Padelkar, Jacek J. Jasieniak, Alexandr N. Simonov

The magnetic spin degrees of freedom in magnetic materials serve as additional capability to tune materials properties, thereby invoking magneto-optical response. Herein, we report the magneto-optoelectronic properties of a family of lead-free magnetic double perovskites Cs_{2}AgTX_{6} (T = Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu; X=Cl, Br, I). This turns out to p

Haoxiang Wang, Pavan Kumar Anasosalu Vasu, Fartash Faghri, Raviteja Vemulapalli

The landscape of publicly available vision foundation models (VFMs), such as CLIP and Segment Anything Model (SAM), is expanding rapidly. VFMs are endowed with distinct capabilities stemming from their pre-training objectives. For instance, CLIP excels in semantic understanding, while SAM specializes in spatial understanding for segmentation. In this work, w

Li Hua Yu, Victor Smaluk, Timur Shaftan, Ganesh Tiwari

We studied the feasibility of a hard x-ray FEL oscillator (XFELO) based on a 3 to 4 GeV storage ring considered for the low-emittance upgrade of NSLS-II. We present a more detailed derivation of a formula for the small-gain gain calculation for 3 GeV XFELO published in the proceedings of IPAC'21 [1]. We modified the small-signal low-gain formula developed by

Jianhui Li, Zane Kun Li, Po-Lam Yung

Strichartz inequalities, originating from Fourier restriction theory, play a central role in the analysis of dispersive partial differential equations. They serve as a cornerstone for many subsequent developments. We survey some of them in memory of Strichartz, highlighting connections to recent developments in Fourier decoupling.

Shengyu Yan, Jasmin Jelovica

Prismatic sandwich panels fabricated from metals offer a compelling alternative to more traditional panels across diverse industries, primarily due to their superior strength-to-weight ratio. Although several core types were proposed in the past, further improvements in performance could be achieved by devising the topology of the core through a topology opt

Son-Hsien Chen

We investigate bipartite entanglement between two distant parties, \textit{A} and \textit{B}, comprising local magnetic impurities (or qudits) induced by the quench through \textit{sd} exchange in a field-effect-transistor geometry. A wave-function-based time-dependent formalism is employed by including non-dissipative responses that allow for the control of

Paul Lathrop, Beth Boardman, Sonia Martínez

In this paper, we present the Parallel Quantum Rapidly-Exploring Random Tree (Pq-RRT) algorithm, a parallel version of the Quantum Rapidly-Exploring Random Trees (q-RRT) algorithm. Parallel Quantum RRT is a parallel quantum algorithm formulation of a sampling-based motion planner that uses Quantum Amplitude Amplification to search databases of reachable stat

Mikael Brunila, Jack LaViolette, Sky CH-Wang, Priyanka Verma

Critical toponymy examines the dynamics of power, capital, and resistance through place names and the sites to which they refer. Studies here have traditionally focused on the semantic content of toponyms and the top-down institutional processes that produce them. However, they have generally ignored the ways in which toponyms are used by ordinary people in

Xiaomin Ouyang, Xian Shuai, Yang Li, Li Pan

Alzheimer's Disease (AD) and related dementia are a growing global health challenge due to the aging population. In this paper, we present ADMarker, the first end-to-end system that integrates multi-modal sensors and new federated learning algorithms for detecting multidimensional AD digital biomarkers in natural living environments. ADMarker features a nove

Heikki Mäntysaari, Farid Salazar, Björn Schenke, Chun Shen

We study diffractive vector meson production in ultra-peripheral collisions (UPCs) of heavy nuclei, utilizing a theoretical framework based on the Color Glass Condensate (CGC) formalism. We focus on Au+Au, U+U, Ru+Ru, Zr+Zr, and Pb+Pb collisions, examining the transverse momentum dependence of vector meson production cross-sections and ${\rm cos(2\Delta\Phi)

Weiming Ding, Haoxiang Huang, Tzu Jung Lee, Yingjie Liu

In recent years, surrogate models based on deep neural networks (DNN) have been widely used to solve partial differential equations, which were traditionally handled by means of numerical simulations. This kind of surrogate models, however, focuses on global interpolation of the training dataset, and thus requires a large network structure. The process is bo

Ankita Bhaumik, Praveen Venkateswaran, Yara Rizk, Vatche Isahagian

The popularity of conversational digital assistants has resulted in the availability of large amounts of conversational data which can be utilized for improved user experience and personalized response generation. Building these assistants using popular large language models like ChatGPT also require additional emphasis on prompt engineering and evaluation m

Zachary M. Geballe, Joseph Lai, Michael J. Walter

Decades of measurements of the thermophysical properties of hot metals show that pulsed Joule heating is an effective method to heat solid and liquid metals that are chemically reactive or difficult to contain. In order to extend such measurements to megabar pressures, pulsed heating methods must be integrated with diamond anvil cells. We report the design a

Weijie Xu, Wenxiang Hu, Fanyou Wu, Srinivasan Sengamedu

In the burgeoning field of natural language processing (NLP), Neural Topic Models (NTMs) , Large Language Models (LLMs) and Diffusion model have emerged as areas of significant research interest. Despite this, NTMs primarily utilize contextual embeddings from LLMs, which are not optimal for clustering or capable for topic based text generation. NTMs have nev

Andriy Haydys, Rafe Mazzeo, Ryosuke Takahashi

We prove an index formula for the Dirac operator acting on two-valued spinors on a $3$-manifold $M$ which branch along a smoothly embedded graph $\Sigma \subset M$, and with respect to a boundary condition along $\Sigma$ inspired by an instance of this setting related to the deformation theory of $\mathbb Z_2$-harmonic spinors. When $\Sigma$ is a smooth embe

Yuanjun Shi, Linzhi Wu, Minglai Shao

Recently slot filling has witnessed great development thanks to deep learning and the availability of large-scale annotated data. However, it poses a critical challenge to handle a novel domain whose samples are never seen during training. The recognition performance might be greatly degraded due to severe domain shifts. Most prior works deal with this probl

Josep Ingla-Aynés, Antonio L. R. Manesco, Talieh S. Ghiasi, Kenji Watanabe

The achievement of valley-polarized electron currents is a cornerstone for the realization of valleytronic devices. Here, we report on ballistic coherent transport experiments where two opposite quantum point contacts (QPCs) are defined by electrostatic gating in a bilayer graphene (BLG) channel. By steering the ballistic currents with an out-of-plane magnet

Keisuke Masuda, Masahiro Sato

We develop a microscopic theory for the spin Seebeck effect (SSE) in N\'eel and canted phases of antiferromagnetic insulators. We calculate the DC spin current tunneling from the antiferromagnet to an attached metal, incorporating the spin-wave theory and the non-equilibrium Green's function approach. Our result shows a sign change of the spin current at the

P. Plattner, E. Wood, L. Al Ayoubi, O. Beliuskina

Collinear laser spectroscopy was performed on the isomer of the aluminium isotope $^{26m}$Al. The measured isotope shift to $^{27}$Al in the $3s^{2}3p\;^{2}\!P^\circ_{3/2} \rightarrow 3s^{2}4s\;^{2}\!S_{1/2}$ atomic transition enabled the first experimental determination of the nuclear charge radius of $^{26m}$Al, resulting in $R_c$=\qty{3.130\pm.015}{\femto

Muhang Tian, Bernie Chen, Allan Guo, Shiyi Jiang

Electronic Health Records (EHRs) are rich sources of patient-level data, offering valuable resources for medical data analysis. However, privacy concerns often restrict access to EHRs, hindering downstream analysis. Current EHR de-identification methods are flawed and can lead to potential privacy leakage. Additionally, existing publicly available EHR databa

Xiaofeng Yong, Ali Arya

Despite the significant growth in virtual reality applications and research, the notion of inclusion in virtual reality is not well studied. Inclusion refers to the active involvement of different groups of people in the adoption, use, design, and development of VR technology and applications. In this review, we provide a scoping analysis of existing virtual

Rachel Freedman, Justin Svegliato, Kyle Wray, Stuart Russell

Reward learning techniques enable machine learning systems to learn objectives from human feedback. A core limitation of these systems is their assumption that all feedback comes from a single human teacher, despite gathering feedback from large and heterogeneous populations. We propose the Hidden Utility Bandit (HUB) framework to model differences in teache

Jenna M. Cann, Arturo O. Martinez, Amethyst Barnes, Sara Doan

In line with the Astro2020 Decadal Report State of the Profession findings and the NASA core value of Inclusion, the NASA Science Mission Directorate (SMD) Bridge Program was created to provide financial and programmatic support to efforts that work to increase the representation and inclusion of students from under-represented minorities in the STEM fields.

Wonyoung Kim, Garud Iyengar, Assaf Zeevi

We propose a new regret minimization algorithm for episodic sparse linear Markov decision process (SMDP) where the state-transition distribution is a linear function of observed features. The only previously known algorithm for SMDP requires the knowledge of the sparsity parameter and oracle access to an unknown policy. We overcome these limitations by combi

Hongwei Wang, Hongming Zhang, Dong Yu

Learning sentence embeddings is a fundamental problem in natural language processing. While existing research primarily focuses on enhancing the quality of sentence embeddings, the exploration of sentence embedding dimensions is limited. Here we present a comprehensive and empirical analysis of the dimensionality of sentence embeddings. First, we demonstrate

Luka Vujeva, Charles L. Steinhardt, Christian Kragh Jespersen, Brenda L. Frye

Several large JWST blank field observing programs have not yet discovered the first galaxies expected to form at $15 \leq z \leq 20$. This has motivated the search for more effective survey strategies that will be able to effectively probe this redshift range. Here, we explore the use of gravitationally lensed cluster fields, that have historically been the

David Meyer

We study the $L^2$-gradient flows, $\partial_t u-\mathrm{div}(\mathrm{D}f(x,\mathbb{A}u))=0$, of functionals of the type $\int_{\Omega}f(x,\mathbb{A}u)\,\mathrm{d}x$, where $f$ is a convex function of linear growth and $\mathbb{A}$ is some first-order linear constant-coefficient differential operator. To this end, we identify the relaxation of the functional

Emmanuel A. Tassone, Carlos N. Kozameh

The evolution of global binary black holes variables such as energy or linear momentum are mainly obtained by applying numerical methods near coalescence, post-Newtonian (PN) expansions, or a combination of both. In this paper, we use a fully relativistic formalism presented several years ago that only uses global variables defined at null infinity together

Ilia Azizi

This paper introduces UncertaintyPlayground, a Python library built on PyTorch and GPyTorch for uncertainty estimation in supervised learning tasks. The library offers fast training for Gaussian and multi-modal outcome distributions through Sparse and Variational Gaussian Process Regressions (SVGPRs) for normally distributed outcomes and Mixed Density Networ

Stefano Marcantoni, Marcello Porta, Julien Sabin

We study the dynamics of many-body Fermi systems, for a class of initial data which are close to quasi-free states exhibiting a nonvanishing pairing matrix. We focus on the mean-field scaling, which for fermionic systems is naturally coupled with a semiclassical scaling. Under the assumption that the initial datum enjoys a suitable semiclassical structure, w

Peter J. Dukes, Kate Nimegeers

We study a system of linear equations associated with Sudoku latin squares. The coefficient matrix $M$ of the normal system has various symmetries arising from Sudoku. From this, we find the eigenvalues and eigenvectors of $M$, and compute a generalized inverse. Then, using linear perturbation methods, we obtain a fractional completion guarantee for sufficie

Bradley Dirks

Saito's microlocalization construction has been used to great effect in understanding hypersurface singularities. In this paper, we introduce what we believe to be a suitable analogue of the microlocalization construction for local complete intersection subvarieties. As evidence, we relate our construction to Saito's in the codimension one case. Moreover, we

Alexandra Butoi, Tim Vieira, Ryan Cotterell, David Chiang

The class of tree-adjoining languages can be characterized by various two-level formalisms, consisting of a context-free grammar (CFG) or pushdown automaton (PDA) controlling another CFG or PDA. These four formalisms are equivalent to tree-adjoining grammars (TAG), linear indexed grammars (LIG), pushdown-adjoining automata (PAA), and embedded pushdown automa

Cheng Qian, Lucas Glass, Nikos Sidiropoulos

Forecasting project expenses is a crucial step for businesses to avoid budget overruns and project failures. Traditionally, this has been done by financial analysts or data science techniques such as time-series analysis. However, these approaches can be uncertain and produce results that differ from the planned budget, especially at the start of a project w

Eren Kurshan

Artificial intelligence (AI) faces a trifecta of grand challenges: the Energy Wall, the Alignment Problem and the Leap from Narrow AI to AGI. We present SAGI, a Systematic Approach to AGI that utilizes system design principles to overcome the energy wall and alignment challenges. This paper asserts that AGI can be realized through multiplicity of design spec

Gilles Parez, William Witczak-Krempa

We study the entanglement between disjoint subregions in quantum critical systems through the lens of the logarithmic negativity. We work with systems in arbitrary dimensions, including conformal field theories and their corresponding lattice Hamiltonians, as well as resonating valence-bond states. At small separations, the logarithmic negativity is big and

Gregoire Josse, Francesco Merenda

In this letter we present a scan for new vacua within consistent truncations of eleven/ten-dimensional supergravity down to five dimensions that preserve $N = 2$ supersymmetry, after their complete classification in arXiv:2112.03931. We first make explicit the link between the equations of exceptional Sasaki-Einstein backgrounds in arXiv:1602.02158 and the s

Chushuang Xiang, Anne Rodriguez, Edson Rafael Cardozo de Oliveira, Luc Le Gratiet

Coherent acoustic phonon generation and detection assisted by optical resonances are at the core of efficient optophononic transduction processes. However, when dealing with a single optical resonance, the optimum generation and detection conditions take place at different laser wavelengths, i.e. different detunings from the cavity mode. In this work, we the

Carlos N. Kozameha, Emmanuel A. Tassone

Using a set of field equations in the null surface formulation we obtain the linearized coupling between the gravitational and matter fields. We first derive a formula for the metric of the space time and then we use this formula to study the scattering of incoming gravitational waves when matter is present, obtaining explicit formulae relating the radiation

Mingyang Wang, Heike Adel, Lukas Lange, Jannik Strötgen

Most languages of the world pose low-resource challenges to natural language processing models. With multilingual training, knowledge can be shared among languages. However, not all languages positively influence each other and it is an open research question how to select the most suitable set of languages for multilingual training and avoid negative interf

Emanuele Marsili, Basile F. E. Curchod

Boron-Nitrogen (B-N) Lewis adducts form a versatile family of compounds with numerous applications in functional molecules. Despite the growing interest in this family of compounds for optoelectronic applications, little is currently known about their photophysics and photochemistry. Even the electronic absorption spectrum of ammonia borane, the textbook exa

Huazhi Ge, Cheng Li, Xi Zhang, Chris Moeckel

Storms operated by moist convection and the condensation of $\rm CH_{4}$ or $\rm H_{2}S$ have been observed on Uranus and Neptune. However, the mechanism of cloud formation, thermal structure, and mixing efficiency of ice giant weather layers remains unclear. In this paper, we show that moist convection is limited by heat transport on giant planets, especial

Adam Rohde, Chad Hazlett

In the quest to make defensible causal claims from observational data, it is sometimes possible to leverage information from "placebo treatments" and "placebo outcomes". Existing approaches employing such information focus largely on point identification and assume (i) "perfect placebos", meaning placebo treatments have precisely zero effect on the outcome a

Jonny Imbierski, Charlene Kalle, Reza Mohammadpour

In this article, we calculate the Birkhoff spectrum in terms of the Hausdorff dimension of level sets for Birkhoff averages of continuous potentials for a certain family of diagonally affine IFS's. Also, we study Besicovitch-Eggleston sets for finite GLS number systems with redundancy. The redundancy refers to the fact that each number $x \in [0,1]$ has unco

Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang

Large Language Models (LLMs) have revolutionized the domain of natural language processing (NLP) with remarkable capabilities of generating human-like text responses. However, despite these advancements, several works in the existing literature have raised serious concerns about the potential misuse of LLMs such as spreading misinformation, generating fake n

Chengrui Li, Soon Ho Kim, Chris Rodgers, Hannah Choi

Exposing meaningful and interpretable neural interactions is critical to understanding neural circuits. Inferred neural interactions from neural signals primarily reflect functional interactions. In a long experiment, subject animals may experience different stages defined by the experiment, stimuli, or behavioral states, and hence functional interactions ca

Injy Hamed, Nizar Habash, Ngoc Thang Vu

Code-switching (CSW) text generation has been receiving increasing attention as a solution to address data scarcity. In light of this growing interest, we need more comprehensive studies comparing different augmentation approaches. In this work, we compare three popular approaches: lexical replacements, linguistic theories, and back-translation (BT), in the

Gautam Krishna, Sameer Dharur, Oggi Rudovic, Pranay Dighe

Device-directed speech detection (DDSD) is the binary classification task of distinguishing between queries directed at a voice assistant versus side conversation or background speech. State-of-the-art DDSD systems use verbal cues, e.g acoustic, text and/or automatic speech recognition system (ASR) features, to classify speech as device-directed or otherwise

Byungkyun Kang, Maengsuk Kim, Chul Hong Park, Anderson Janotti

FeSe has been extensively explored as a quantum material, primarily due to the observed highest superconducting transition temperature among Fe-based unconventional superconductors. Nonetheless, the electronic structure and the electron correlations responsible for the remarkable diversity of physical properties in FeSe remain elusive. We undertook a compreh

Baban Gain, Ramakrishna Appicharla, Soumya Chennabasavaraj, Nikesh Garera

Community Question-Answering (CQA) portals serve as a valuable tool for helping users within an organization. However, making them accessible to non-English-speaking users continues to be a challenge. Translating questions can broaden the community's reach, benefiting individuals with similar inquiries in various languages. Translating questions using Neural

Negar Foroutan, Mohammadreza Banaei, Karl Aberer, Antoine Bosselut

In this work, we study whether multilingual language models (MultiLMs) can transfer logical reasoning abilities to other languages when they are fine-tuned for reasoning in a different language. We evaluate the cross-lingual reasoning abilities of MultiLMs in two schemes: (1) where the language of the context and the question remain the same in the new langu

Catherine Manea, Keith Hawkins, Melissa K. Ness, Sven Buder

The observed chemical diversity of Milky Way stars places important constraints on Galactic chemical evolution and the mixing processes that operate within the interstellar medium. Recent works have found that the chemical diversity of disk stars is low. For example, the APOGEE "chemical doppelganger rate," or the rate at which random pairs of field stars ap

Pablo Lemos, Liam Parker, ChangHoon Hahn, Shirley Ho

We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzing summary statistics, such as the power spectrum, $P_\ell$, with analytic models based on perturbation theory. Consequently, they do not fully exploit the non-linear and non-Gauss

Patrick F. Cronin-Coltsmann, Grant M. Kennedy, Quentin Kral, Jean-François Lestrade

Previous surveys in the far-infrared have found very few, if any, M-dwarf debris discs among their samples. It has been questioned whether M-dwarf discs are simply less common than earlier types, or whether the low detection rate derives from the wavelengths and sensitivities available to those studies. The highly sensitive, long wavelength Atacama Large Mil

Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz

The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the core-collapse supernova (CCSN) rate, neutrino emission spectra, and the fraction of failed supernova

Shubhayan Sarkar

Macro-realistic description of systems is based majorly on two basic intuitions about the classical world, namely, macrorealism per se, that is, the system is always in a distinct state, and non-invasive measurements, that is, measurements do not disturb the system. Given the assumption of no-signalling in time, one utilizes Leggett-Garg inequalities to obse

Roya Beheshti, Brian Lehmann, Carl Lian, Eric Riedl

We study the enumerativity of Gromov-Witten invariants where the domain curve is fixed in moduli and required to pass through the maximum possible number of points. We say a Fano manifold satisfies asymptotic enumerativity if such invariants are enumerative whenever the degree of the curve is sufficiently large. Lian and Pandharipande speculate that every Fa

Paweł Matus, Ruben Lier, Piotr Surówka

We consider an active, stochastic microscopic model of particles suspended in a fluid and show that the coarse-grained description of this model renders odd viscoelasticity. The particles are odd dumbbells, each featuring a robotic device as the bead, which exhibits a particular torque response. We show that this model can be macroscopically treated as a vis

Bruno Régaldo-Saint Blancard, ChangHoon Hahn, Shirley Ho, Jiamin Hou

The non-Gaussisan spatial distribution of galaxies traces the large-scale structure of the Universe and therefore constitutes a prime observable to constrain cosmological parameters. We conduct Bayesian inference of the $\Lambda$CDM parameters $\Omega_m$, $\Omega_b$, $h$, $n_s$, and $\sigma_8$ from the BOSS CMASS galaxy sample by combining the wavelet scatte

F. Gobet, P. Barberet, M. -H. Delville, G. Devès

We study the effects of irradiating water with 3 MeV protons at high doses by observing the motion of charged polystyrene beads outside the proton beam. By single-particle tracking, we measure a radial velocity of the order of microns per second. Combining electrokinetic theory with simulations of the beam-generated reaction products and their outward diffus

Tobias Mistele, Stacy McGaugh, Federico Lelli, James Schombert

We combine kinematic and gravitational lensing data to construct the Radial Acceleration Relation (RAR) of galaxies over a large dynamic range. We improve on previous weak-lensing studies in two ways. First, we compute stellar masses using the same stellar population model as for the kinematic data. Second, we introduce a new method for converting excess sur

Marco Comunità, Riccardo F. Gramaccioni, Emilian Postolache, Emanuele Rodolà

Sound design involves creatively selecting, recording, and editing sound effects for various media like cinema, video games, and virtual/augmented reality. One of the most time-consuming steps when designing sound is synchronizing audio with video. In some cases, environmental recordings from video shoots are available, which can aid in the process. However,

ChangHoon Hahn, Pablo Lemos, Liam Parker, Bruno Régaldo-Saint Blancard

The 3D distribution of galaxies encodes detailed cosmological information on the expansion and growth history of the Universe. We present the first cosmological constraints that exploit non-Gaussian cosmological information on non-linear scales from galaxy clustering, inaccessible with current standard analyses. We analyze a subset of the BOSS galaxy survey

José Luis V. Cerdeira, Joaquim Gomis, Axel Kleinschmidt

We consider non-Lorentzian expansions, Galilean and Carrollian, of the Lorentz force equation in which both the particle position and the electro-magnetic field are expanded. There are two well-known limits in the case of a constant field, called electric and magnetic, that are studied separately. We show that the resulting equations of motion follow equival

Hector Robinson, James Wadsley

We use high-resolution MHD simulations of isolated disk galaxies to investigate the co-evolution of magnetic fields with a self-regulated, star-forming interstellar medium (ISM). The simulations are conducted using the Ramses AMR code on the standard Agora initial condition, with gas cooling, star formation and feedback. We run galaxies with a variety of ini

ChangHoon Hahn, Michael Eickenberg, Shirley Ho, Jiamin Hou

We present the first cosmological constraints from analyzing higher-order galaxy clustering on non-linear scales. We use ${\rm S{\scriptsize IM}BIG}$, a forward modeling framework for galaxy clustering analyses that employs simulation-based inference to perform highly efficient cosmological inference using normalizing flows. It leverages the predictive power

Stephen R. Kane, Zhexing Li

The origin and evolution of planetary rings and moons remains an active area of study, particularly as they relate to the impact history and volatile inventory of the outer solar system. The Uranian system contains a complex system of rings that are coplanar with the highly inclined planetary equator relative to the orbital plane. Uranus also harbors five pr

Ved G. Shah, Gautham Narayan, Haille M. L. Perkins, Ryan J. Foley

We present a comprehensive, configurable open-source framework for estimating the rate of electromagnetic detection of kilonovae (KNe) associated with gravitational wave detections of binary neutron star (BNS) mergers. We simulate the current LIGO-Virgo-KAGRA (LVK) observing run (O4) using up-to-date sensitivity and up-time values as well as the next observi

Mete Ismayilzada, Debjit Paul, Syrielle Montariol, Mor Geva

Recent efforts in natural language processing (NLP) commonsense reasoning research have yielded a considerable number of new datasets and benchmarks. However, most of these datasets formulate commonsense reasoning challenges in artificial scenarios that are not reflective of the tasks which real-world NLP systems are designed to solve. In this work, we prese

N. A. Owens, J. Wadsley

We present the first implementation of hyperbolic thermal conduction in smoothed particle hydrodynamics (SPH). Hyperbolic conduction is a physically-motivated alternative to traditional, parabolic conduction. It incorporates a relaxation time, which ensures that heat propagates no faster than a physical signal speed. This allows for larger, Courant like, tim

Wolfgang Lerche

We consider the boundary dual of AdS3xS3xK3 for NS5-flux Q5=1, which is described by a sigma model with target space given by the d-fold symmetric product of K3. Building on results in algebraic geometry, we address the problem of deforming it away from the orbifold point from the viewpoint of topological strings. We propose how the 't Hooft expansion can be

Matthew Dodelson, Cristoforo Iossa, Robin Karlsson, Alexandru Lupsasca

Lorentzian correlators of local operators exhibit surprising singularities in theories with gravity duals. These are associated with null geodesics in an emergent bulk geometry. We analyze singularities of the thermal response function dual to propagation of waves on the AdS Schwarzschild black hole background. We derive the analytic form of the leading sing

James W. Wadsley, Bernhard Baumschlager, Sijing Shen

We present TREVR2 (Tree-based REVerse Ray Tracing 2), a fast, general algorithm for computing the radiation field, suitable for both particle and mesh codes. It is designed to self-consistently evolve chemistry for zoomed-in astrophysical simulations, such as cosmological galaxies with both internal sources and prescribed background radiation, rather than la

Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao

It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Santi et al. (2023) developed models that could accurately infer the value of $\Omega_{\rm m}$ from catalogs that

Digvijay Wadekar, Tejaswi Venumadhav, Ajit Kumar Mehta, Javier Roulet

Searches for gravitational wave events use models, or templates, for the signals of interest. The templates used in current searches in the LIGO-Virgo-Kagra (LVK) data model the dominant quadrupole mode $(\ell,|m|)=(2,2)$ of the signals, and omit sub-dominant higher-order modes (HM) such as $(\ell,|m|)=(3,3)$, $(4,4)$, which are predicted by general relativi

Viraj Pandya, Haowen Zhang, Marc Huertas-Company, Kartheik G. Iyer

The 3D geometry of high-redshift galaxies remains poorly understood. We build a differentiable Bayesian model and use Hamiltonian Monte Carlo to efficiently and robustly infer the 3D shapes of star-forming galaxies in JWST-CEERS observations with $\log M_*/M_{\odot}=9.0-10.5$ at $z=0.5-8.0$. We reproduce previous results from HST-CANDELS in a fraction of the

Jingwen Zhang, Michael Bottom, Eugene Serabyn

Space-based direct imaging provides prospects for detection and spectral characterization of exoplanets at optical and near-infrared wavelengths. Integral field spectrographs (IFS) have been historically baselined for these mission concepts. However, multiple studies have revealed that detector noise is a serious obstacle for such instruments when observing

Aris Tritsis, Nikolaos D. Kylafis

Among all the available observational techniques for studying magnetic fields in the dense cold phase of the interstellar medium, linear polarization of spectral lines, referred to in the literature as the Goldreich-Kylafis effect (Goldreich & Kylafis 1981; hereafter "GK effect"), remains one of the most underutilized methods. In this study, we implement the

B. T. Draine

Aligned interstellar grains produce polarized extinction (observed at wavelengths from the far-ultraviolet to the mid-infrared), and polarized thermal emission (observed at far-infrared and submm wavelengths). The grains must be quite nonspherical, but the actual shapes are unknown. The \emph{relative} efficacy for aligned grains to produce polarization at o

Junmo Jeon, SungBin Lee

Most periodic systems are governed by short-range interactions as long-range interactions in these systems diminish uniformly. In this letter, however, we demonstrate that this is not true for a more general class of systems, which possess long-range order without periodicity, known as quasiperiodic systems. Quasiperiodicity alters the well-known characteris

Aurora Singstad Grefsrud, Trygve Buanes, Fotis Koutroulis, Anna Lipniacka

In models with large extra dimensions, "miniature" black holes (BHs) might be produced in high-energy proton-proton collisions at the Large Hadron Collider (LHC). In the semi-classical regime, those BHs thermally decay, giving rise to large-multiplicity final states with jets and leptons. On the other hand, similar final states are also expected in the produ

Alexandra Wells, David Robinson, Camille Avestruz, Nickolay Y. Gnedin

We examine the evolution of the phase diagram of the low-density intergalactic medium during the Epoch of Reionization in simulation boxes with varying reionization histories from the Cosmic Reionization on Computers project. The PDF of gas temperature at fixed density exhibits two clear modes: a warm and cold temperature mode, corresponding to the gas insid

Pavlo Makushko, Sergey Kovalev, Yevhen Zabila, Igor Ilyakov

The nonlinear Hall effect (NLHE) with time-reversal symmetry constitutes the appearance of a transverse voltage quadratic in the applied electric field. It is a second-order electronic transport phenomenon that induces frequency doubling and occurs in non-centrosymmetric crystals with large Berry curvature -- an emergent magnetic field encoding the geometric

Bernanda Telalovic, Mauricio Bustamante

High-energy astrophysical neutrinos, with TeV--PeV energies, offer unique insight into astrophysics and particle physics. Their incoming directions and flavor composition -- i.e., the proportion of electron, muon, and tau neutrinos in their flux -- are, individually, rewarding observables. Combined, they offer new opportunities, hitherto unexplored, that we

Pascale Berner, Alexandre Refregier, Beatrice Moser, Luca Tortorelli

A forward modelling approach provides simple, fast and realistic simulations of galaxy surveys, without a complex underlying model. For this purpose, galaxy clustering needs to be simulated accurately, both for the usage of clustering as its own probe and to control systematics. We present a forward model to simulate galaxy surveys, where we extend the Ultra