March 2024 arXiv papers — page 121

Michela Mancini, John A. Christian

Orbit determination (OD) from three position vectors is one of the classical problems in astrodynamics. Early contributions to this problem were made by J. Willard Gibbs in the late 1800s and OD of this type is known today as ``Gibbs Problem''. There are a variety of popular solutions to the Gibbs problem. While some authors solve for the orbital elements di

Thea Budde, Marina Krstić Marinković, Joao C. Pinto Barros

The existence of Quantum Many-Body Scars, which prevents thermalization from certain initial states after a long time, has been established across different quantum many-body systems. These include gauge theories corresponding to spin-1/2 quantum link models. Establishing quantum scars in gauge theories with high spin is not accessible with existing numerica

Edwin A. Bergin, Arthur Bosman, Richard Teague, Jenny Calahan

We present the first detection of 13CCH in a protoplanetary disk (TW Hya). Using observations of C2H we measure CCH/13CCH = 65 +/- 20 in gas with a CO isotopic ratio of 12CO/13CO = 21 +/- 5 (Yoshida et al. 2022a). The TW Hya disk exhibits a gas phase C/O that exceeds unity and C2H is the tracer of this excess carbon. We confirm that the TW Hya gaseous disk e

Madeline A. Stricklin, Lauren J. Beesley, Brian P. Weaver, Kelly R. Moran

The Interstellar Boundary Explorer (IBEX) satellite collects data on energetic neutral atoms (ENAs) that provide insight into the heliosphere, the region surrounding our solar system and separating it from interstellar space. IBEX collects information on these particles and on extraneous ``background'' particles. While IBEX records how and when the different

Claire Augusta Bergey, Simon DeDeo

Conversation demands attention. Speakers must call words to mind, listeners must make sense of them, and both together must negotiate this flow of information, all in fractions of a second. We used large language models to study how this works in a large-scale dataset of English-language conversation, the CANDOR corpus. We provide a new estimate of the infor

Masahiro Hori, Ryo Okugawa, K. Tanaka, Takami Tohyama

Weyl superconductivity is a topological phase in three-dimensional crystals in which the Weyl equation describes quasiparticle excitation near band-touching points in momentum space called Weyl nodes. For quasicrystals which lack translational symmetry, a theory of Weyl superconductivity has not been established, in spite of recent extensive studies on quasi

Andrea Conti, Cyril Demarche, Mathieu Florence

Let $\Gamma$ be either i) the absolute Galois group of a local field $F$, or ii) the topological fundamental group of a closed connected orientable surface of genus $g$. In case i), assume that $\mu_{p^2} \subset F$. We give an elementary and unified proof that every representation $\rho_1: \Gamma \to \mathbf{GL}_d(\mathbb{F}_p)$ lifts to a representation $\

Xiao Chen, Shunan Zhang, Eric Z. Chen, Yikang Liu

In artificial intelligence (AI), especially deep learning, data diversity and volume play a pivotal role in model development. However, training a robust deep learning model often faces challenges due to data privacy, regulations, and the difficulty of sharing data between different locations, especially for medical applications. To address this, we develope

Se-eun Yoon, Zhankui He, Jessica Maria Echterhoff, Julian McAuley

Synthetic users are cost-effective proxies for real users in the evaluation of conversational recommender systems. Large language models show promise in simulating human-like behavior, raising the question of their ability to represent a diverse population of users. We introduce a new protocol to measure the degree to which language models can accurately emu

Sebastián Leavy, Gabriela Allegretti, Elen Presotto, Marco Antonio Montoya

Despite its relevance, measuring the contributions of the bioeconomy to national economies remains an arduous task that faces limitations. Part of the difficulty is associated with the lack of a clear and widely accepted concept of the bioeconomy and moves on to the connections between methods, data and indicators. The present study aims to define the concep

Helin Cao, Sven Behnke

We introduce SLCF-Net, a novel approach for the Semantic Scene Completion (SSC) task that sequentially fuses LiDAR and camera data. It jointly estimates missing geometry and semantics in a scene from sequences of RGB images and sparse LiDAR measurements. The images are semantically segmented by a pre-trained 2D U-Net and a dense depth prior is estimated from

Boris Solomyak

The paper is concerned with random $S$-adic systems arising from an i.i.d. sequence of unimodular substitutions. Using equidistribution results of Benoist and Quint, we show in Theorem 3.3 that, under some natural assumptions, if the Lyapunov exponent of the spectral cocycle is strictly less that 1/2 of the Lyapunov exponent of the random walk on $SL(2,\math

Clay Cordova, Diego García-Sepúlveda, Nicholas Holfester

We study non-invertible topological symmetry operators in massive quantum field theories in (1+1) dimensions. In phases where this symmetry is spontaneously broken we show that the particle spectrum often has degeneracies dictated by the non-invertible symmetry and we deduce a procedure to determine the allowed multiplets. These degeneracies are robust predi

Jérémy Perez, Corentin Léger, Marcela Ovando-Tellez, Chris Foulon

Research in cultural evolution aims at providing causal explanations for the change of culture over time. Over the past decades, this field has generated an important body of knowledge, using experimental, historical, and computational methods. While computational models have been very successful at generating testable hypotheses about the effects of several

D. Nevola, N. Aryal, G. D. Gu, P. D. Johnson

We study the non-equilibrium electronic structure of a model Dirac semimetal ZrTe$_5$ by using time-and-angle resolved photoemission spectroscopy and density functional theory-based electron and phonon calculations. By measuring the electronic dispersion near the $\Gamma$ point at time delays up to 10 picoseconds, we discovered that the band spectral weight

Luke Oluwaseye Joel, Wesley Doorsamy, Babu Sena Paul

Missing values or data is one popular characteristic of real-world datasets, especially healthcare data. This could be frustrating when using machine learning algorithms on such datasets, simply because most machine learning models perform poorly in the presence of missing values. The aim of this study is to compare the performance of seven imputation techni

Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lecue

Feature selection is a crucial step in building machine learning models. This process is often achieved with accuracy as an objective, and can be cumbersome and computationally expensive for large-scale datasets. Several additional model performance characteristics such as fairness and robustness are of importance for model development. As regulations are dr

Jing Tan, Ramin Khalili, Holger Karl

The Intelligent Transportation System (ITS) environment is known to be dynamic and distributed, where participants (vehicle users, operators, etc.) have multiple, changing and possibly conflicting objectives. Although Reinforcement Learning (RL) algorithms are commonly applied to optimize ITS applications such as resource management and offloading, most RL a

Bahruz Suleymanli, Kutsal Bozkurt, Elias Khan, Haşim Güven

The influence of finite temperatures and pairing correlations on the ground state properties of multi $\Lambda$- Ca, Sn and Pb hypernuclei is explored using finite temperature Hartree Fock Bogoliubov approach and contact pairing interaction. A critical temperature is predicted and is in agreement with the Bardeen Cooper Schrieffer relationship $k_B T_C^\Lamb

Mukremin Kilic, Pierre Bergeron, Simon Blouin, Gracyn Jewett

Four years after the discovery of a unique DAQ white dwarf with a hydrogen-dominated and carbon-rich atmosphere, we report the discovery of four new DAQ white dwarfs, including two that were not recognized properly in the literature. We find all five DAQs in a relatively narrow mass and temperature range of $M=1.14-1.19~M_{\odot}$ and $T_{\rm eff}=13,000-17,

Coleman Dean, Rodrigo Fernández

We investigate mass ejection from accretion disks formed during the collapse of rapidly-rotating Wolf-Rayet stars. The neutrino-cooled, black hole (BH) accretion disk system that forms at the center of the star -- and the ensuing outflows -- provide the conditions for these systems to be candidate $r$-process element production sites and potential progenitor

Trong-Vu Hoang, Quang-Binh Nguyen, Duy-Nam Ly, Khanh-Duy Le

Drawing is an art that enables people to express their imagination and emotions. However, individuals usually face challenges in drawing, especially when translating conceptual ideas into visually coherent representations and bridging the gap between mental visualization and practical execution. In response, we propose ARtVista - a novel system integrating A

Andrew Urilyon, Stefano Scopa, Giuseppe Del Vecchio Del Vecchio, Jacopo De Nardis

We study the formation and the subsequent dynamics of shock waves in repulsive one-dimensional Bose gases during the free expansion of a density hump. By building coherent Fermi states for interacting Bethe fermions, we define a quantum fluctuating initial state expressed in terms of universal quantities, namely the density and the Luttinger parameter. In th

Xiaohui Liu, Hua Xing Zhu

We introduce a novel category of observables known as the Semi-Inclusive Energy Correlators (SIECs), an extension of the recently proposed nucleon energy correlator to integrate a new element, the fragmenting energy correlation function. These SIECs gauge the correlation between the examined hadron and the surrounding radiations, providing a comprehensive to

Marta L. Bryan, Eve J. Lee

The connection between outer gas giants and inner super-Earths reflects their formation and evolutionary histories. Past work exploring this link has suggested a tentative positive correlation between these two populations, but these studies have been limited by small sample sizes and in some cases sample biases. Here we take a new look at this connection wi

Andrea Weibel, Pascal A. Oesch, Laia Barrufet, Rashmi Gottumukkala

Combining the public JWST/NIRCam imaging programs CEERS, PRIMER and JADES, spanning a total area of $\sim500\,{\rm arcmin}^2$, we obtain a sample of $>$30,000 galaxies at $z_{\rm phot}\sim4-9$ that allows us to perform a complete, rest-optical selected census of the galaxy population at $z>3$. Comparing the stellar mass $M_*$ and the UV-slope $\beta$ distrib

Magdalena Siwek, Luke Zoltan Kelley, Lars Hernquist

We investigate the effect of cutting-edge circumbinary disk (CBD) evolution models on massive black hole binary (MBHB) populations and the gravitational wave background (GWB). We show that CBD-driven evolution leaves a tell-tale signature in MBHB populations, by driving binaries towards an equilibrium eccentricity that depends on binary mass ratio. We find h

Hiba Tu Noor, Jay Farihi, Mark Hollands, Silvia Toonen

The accretion of tidally disrupted planetary bodies is the current consensus model for the presence of photospheric metals commonly detected in white dwarfs. While most dynamical studies have considered a single star and associated planetary instabilities, several investigations have instead considered the influence of widely-bound stellar companions as pote

Luke R. Holden, Clive N. Tadhunter, Anelise Audibert, Tom Oosterloo

The ultra luminous infrared galaxy (ULIRG) F13451+1232 is an excellent example of a galaxy merger in the early stages of active galactic nucleus (AGN) activity, a phase in which AGN-driven outflows are expected to be particularly important. However, previous observations have determined that the mass outflow rates of the warm ionised and neutral gas phases i

Tom O'Leary, Lewis W. Anderson, Dieter Jaksch, Martin Kiffner

We present an iterative generalisation of the quantum subspace expansion algorithm used with a Krylov basis. The iterative construction connects a sequence of subspaces via their lowest energy states. Diagonalising a Hamiltonian in a given Krylov subspace requires the same quantum resources in both the single step and sequential cases. We propose a variance-

Wolfram Brenig, Olesia Krupnitska

We study electric field induced two-dimensional coherent nonlinear optical spectroscopy (2DCS) in a Kitaev magnet at finite temperature. We show that 2DCS is susceptible to both types of fractional quasiparticles of this quantum spin-liquid, i.e., fermions and flux visons. Focusing on the second order response, we find a strong antidiagonal feature in the tw

Yonatan Kahn, Jesús Pérez-Ríos

The Migdal effect is a key inelastic signal channel which could be used to detect low-mass dark matter, but it has never been observed experimentally using Standard Model probes. Here we propose a conceptual design for an experiment which could detect the Migdal effect in diatomic molecules through low-energy neutron scattering, and we provide the requiremen

L. R. Bedin, J. Dietrich, A. J. Burgasser, D. Apai

Located at less than 2pc away, Luhman16AB (WISE.J104915.57-531906.1) is the closest pair of brown dwarfs and third closest `stellar' system to Earth. An exoplanet candidate in the Luhman16 binary system was reported in 2017 based on a weak astrometric signature in the analysis of 12 HST epochs. An additional epoch collected in 2018 and re-analysis of the dat

Nikolas A. Wittek, Adam Pound, Harald P. Pfeiffer, Leor Barack

This is a third installment in a program to develop a method for alleviating the scale disparity in binary black hole simulations with mass ratios in the intermediate astrophysical range, where simulation cost is prohibitive while purely perturbative methods may not be adequate. The method is based on excising a "worldtube" around the smaller object, much la

B. Prinoth, H. J. Hoeijmakers, B. M. Morris, M. Lam

Exoplanets in the ultra-hot Jupiter regime provide an excellent laboratory for testing the impact of stellar irradiation on the dynamics and chemical composition of gas giant atmospheres. In this study, we observed two transits of the ultra-hot Jupiter WASP-189 b with MAROON-X/Gemini-North to probe its high-altitude atmospheric layers, using strong absorptio

Prashant Kocherlakota, Luciano Rezzolla, Rittick Roy, Maciek Wielgus

Future black hole (BH) imaging observations are expected to resolve finer features corresponding to higher-order images of hotspots and of the horizon-scale accretion flow. In spherical spacetimes, the image order is determined by the number of half-loops executed by the photons that form it. Consecutive-order images arrive approximately after a delay time o

Yuji Tachikawa, Hao Y. Zhang

We show that the low-energy effective actions of two ten-dimensional supersymmetric heterotic strings are different by a $\mathbb{Z}_3$-valued discrete topological term even after we turn off the $E_8\times E_8$ and $Spin(32)/\mathbb{Z}_2$ gauge fields. This will be demonstrated by considering the inflow of normal bundle anomaly to the respective NS5-branes

Melodie M. Kao, J. Sebastian Pineda

Despite a burgeoning set of ultracool dwarf ($\leq$M7) radio detections, their radio emissions remain enigmatic. Open questions include the plasma source and acceleration mechanisms for the non-auroral "quiescent" component of these objects' radio emissions, which can trace Jovian synchrotron radiation belt analogs. Ultracool dwarf binary systems can provide

Lewis W. Anderson, Martin Kiffner, Tom O'Leary, Jason Crain

Computing vacuum states of lattice gauge theories (LGTs) containing fermionic degrees of freedom can present significant challenges for classical computation using Monte-Carlo methods. Quantum algorithms may offer a pathway towards more scalable computation of groundstate properties of LGTs. However, a comprehensive understanding of the quantum computational

Jesse Osborne, Ian P. McCulloch, Jad C. Halimeh

Quantum many-body scarring (QMBS) has emerged as an intriguing paradigm of weak ergodicity breaking in nonintegrable quantum many-body models, particularly lattice gauge theories (LGTs) in $1+1$ spacetime dimensions. However, an open question is whether QMBS exists in higher-dimensional LGTs with dynamical matter. Given that nonergodic dynamics in $d{=}1$ sp

Minbin Huang, Yanxin Long, Xinchi Deng, Ruihang Chu

Text-to-image (T2I) generation models have significantly advanced in recent years. However, effective interaction with these models is challenging for average users due to the need for specialized prompt engineering knowledge and the inability to perform multi-turn image generation, hindering a dynamic and iterative creation process. Recent attempts have tri

Alex M. Garcia, Paul Torrey, Sara Ellison, Kathryn Grasha

The scatter about the mass-metallicity relation (MZR) has a correlation with the star formation rate (SFR) of galaxies. The lack of evidence of evolution in correlated scatter at $z\lesssim2.5$ leads many to refer to the relationship between mass, metallicity, and SFR as the Fundamental Metallicity Relation (FMR). Yet, recent high-redshift (z>3) JWST observa

Qu Cao, Jin Dong, Song He, Canxin Shi

We propose a new splitting behavior of tree-level string/particle amplitudes for scalars, gluons and gravitons. We identify certain subspaces in the space of Mandelstam variables, where the universal Koba-Nielsen factor splits into two parts (each with an off-shell leg). Both open- and closed-string amplitudes with Parke-Taylor factors naturally factorize in

Rikab Gambhir, Athis Osathapan, Jesse Thaler

Many machine learning applications involve learning a latent representation of data, which is often high-dimensional and difficult to directly interpret. In this work, we propose "Moment Pooling", a natural extension of Deep Sets networks which drastically decrease latent space dimensionality of these networks while maintaining or even improving performance.

Andrew Marszewski, Guochao Sun, Claude-André Faucher-Giguère, Christopher C. Hayward

The unprecedented infrared spectroscopic capabilities of JWST have provided high-quality interstellar medium (ISM) metallicity measurements and enabled characterization of the gas-phase mass-metallicity relation (MZR) for galaxies at $z \gtrsim 5$ for the first time. We analyze the gas-phase MZR and its evolution in a high-redshift suite of FIRE-2 cosmologic

J. Sebastian Pineda, Gregg Hallinan, Jean Michel Desert, Leon K. Harding

Recent observations have demonstrated that very-low mass stars and brown dwarfs are capable of sustaining strong magnetic fields despite their cool and neutral atmospheres. These kG field strengths are inferred based on strong highly circularly polarized GHz radio emission, a consequence of the electron cyclotron maser instability. Crucially, these observati

Siddharth Mishra-Sharma, Yiding Song, Jesse Thaler

We present PAPERCLIP (Proposal Abstracts Provide an Effective Representation for Contrastive Language-Image Pre-training), a method which associates astronomical observations imaged by telescopes with natural language using a neural network model. The model is fine-tuned from a pre-trained Contrastive Language-Image Pre-training (CLIP) model using successful

Xiaoying Pang, Siqi Liao, Jiadong Li, Zhiqiang Yan

This work analyses the present-day mass function (PDMF) of 93~star clusters utilizing Gaia DR3 data, with membership determined by the StarGo machine learning algorithm. The impact of unresolved binary systems on mass estimation is rigorously assessed, adopting three mass ratio profiles for correction. The PDMF is characterized by the power-law index, $\alph

Yifei Zhang, Hao Zhao, Hongyang Li, Siheng Chen

3D correspondence, i.e., a pair of 3D points, is a fundamental concept in computer vision. A set of 3D correspondences, when equipped with compatibility edges, forms a correspondence graph. This graph is a critical component in several state-of-the-art 3D point cloud registration approaches, e.g., the one based on maximal cliques (MAC). However, its properti

Or Guttman, Ben Shenhar, Arnab Sarkar, Eli Waxman

A semi-analytic approximation is derived for the time-dependent fraction $f_\gamma(t)$ of the energy deposited by radioactive decay $\gamma$-rays in a homologously expanding plasma of general structure. An analytic approximation is given for spherically symmetric plasma distributions. Applied to Kilonovae (KNe) associated with neutron stars mergers and Type

Linyi Jin, Nilesh Kulkarni, David Fouhey

This paper introduces 3DFIRES, a novel system for scene-level 3D reconstruction from posed images. Designed to work with as few as one view, 3DFIRES reconstructs the complete geometry of unseen scenes, including hidden surfaces. With multiple view inputs, our method produces full reconstruction within all camera frustums. A key feature of our approach is the

Paolo Amore, Francisco M. Fernández, Javier Garcia

We test the analytical expressions for the first two eigenvalues of the harmonic oscillator with a Gaussian perturbation proposed recently. Our numerical eigenvalues show that those expressions are valid in an interval of the coupling parameter that is greater than the one estimated by the authors. We also calculate critical values of the coupling parameter

Yupeng Zheng, Xiang Li, Pengfei Li, Yuhang Zheng

Monocular Semantic Occupancy Prediction aims to infer the complete 3D geometry and semantic information of scenes from only 2D images. It has garnered significant attention, particularly due to its potential to enhance the 3D perception of autonomous vehicles. However, existing methods rely on a complex cascaded framework with relatively limited information

Ben Shenhar, Or Guttman, Eli Waxman

A simple analytic description is provided of the rate of energy deposition by $\beta$-decay electrons in the homologously expanding radioactive plasma ejected in neutron star mergers, valid for a wide range of ejecta parameters -- initial entropy, electron fraction $\{s_0,Y_e\}$ and density $\rho t^3$. The formulae are derived using detailed numerical calcul

Enric Corona, Andrei Zanfir, Eduard Gabriel Bazavan, Nikos Kolotouros

We propose VLOGGER, a method for audio-driven human video generation from a single input image of a person, which builds on the success of recent generative diffusion models. Our method consists of 1) a stochastic human-to-3d-motion diffusion model, and 2) a novel diffusion-based architecture that augments text-to-image models with both spatial and temporal

Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter

Large language models (LLMs) are routinely pre-trained on billions of tokens, only to start the process over again once new data becomes available. A much more efficient solution is to continually pre-train these models, saving significant compute compared to re-training. However, the distribution shift induced by new data typically results in degraded perfo

K. Stolzenberg, C. Struckmann, S. Bode, R. Li

Atom interferometery is an exquisite measurement technique sensitive to inertial forces. However, it is commonly limited to a single sensitive axis, allowing high-precision multi-dimensional sensing only through subsequent or post-corrected measurements. We report on a novel method for multi-axis inertial sensing based on the correlation of simultaneous ligh

Yun Xin Teoh, Alice Othmani, Siew Li Goh, Juliana Usman

Knee osteoarthritis is a degenerative joint disease that induces chronic pain and disability. Bone morphological analysis is a promising tool to understand the mechanical aspect of this disorder. This study proposes a 2D bone morphological analysis using manually segmented bones to explore morphological features related to distinct pain conditions. Furthermo

Jialv Zou, Bencheng Liao, Qian Zhang, Wenyu Liu

Learning robust and scalable visual representations from massive multi-view video data remains a challenge in computer vision and autonomous driving. Existing pre-training methods either rely on expensive supervised learning with 3D annotations, limiting the scalability, or focus on single-frame or monocular inputs, neglecting the temporal information. We pr

Andre Maeder

Galaxy velocities in clusters, rotation curves of galaxies, and "vertical" oscillations in the Milky Way currently show too high velocities with respect to the masses thought to be involved. While these velocity excesses are currently interpreted as the consequence of dark matter, it can also be naturally explained as a consequence of scale invariant theory,

Shihan Qiu, Shaoyan Pan, Yikang Liu, Lin Zhao

Current deep learning reconstruction for accelerated cardiac cine MRI suffers from spatial and temporal blurring. We aim to improve image sharpness and motion delineation for cine MRI under high undersampling rates. A spatiotemporal diffusion enhancement model conditional on an existing deep learning reconstruction along with a novel paired sampling strategy

Hengyuan Ma, Wenlian Lu, Jianfeng Feng

Combinatorial optimization problems are widespread but inherently challenging due to their discrete nature. The primary limitation of existing methods is that they can only access a small fraction of the solution space at each iteration, resulting in limited efficiency for searching the global optimal. To overcome this challenge, diverging from conventional

Aleksa Milojević, Benny Sudakov, István Tomon

In this paper we study the number of incidences between $m$ points and $n$ varieties in $\mathbb{F}^d$, where $\mathbb{F}$ is an arbitrary field, assuming the incidence graph contains no copy of $K_{s,s}$. We also consider the analogous problem for algebraically defined graphs and unit distance graphs. First, we prove that if $\mathcal{P}$ is a set of $m$ po

Feng Cheng, Ziyang Wang, Yi-Lin Sung, Yan-Bo Lin

We present a parameter-efficient method for continual video question-answering (VidQA) learning. Our method, named DAM, uses the proposed Dynamic Adapter Merging to (i) mitigate catastrophic forgetting, (ii) enable efficient adaptation to continually arriving datasets, (iii) handle inputs from unknown datasets during inference, and (iv) enable knowledge shar

Alexis Anagnostakis, Sara Mazzonetto

We study a class of high-frequency path functionals for one-dimensional diffusions with singular thresholds or boundaries, allowing for skewness, discontinuities in the diffusion coefficient, and stickiness or sticky reflection. These functionals, originally developed for local-time approximation in non-singular diffusions, are constructed from a test functi

Giovanni Angelini, Luca Fanelli, Luca Neri

When in proxy-SVARs the covariance matrix of VAR disturbances is subject to exogenous, permanent breaks that cause IRFs to change across volatility regimes, even strong, exogenous external instruments yield inconsistent estimates of the dynamic causal effects. However, if these volatility shifts are properly incorporated into the analysis through (testable)

B. Anghinoni, M. Partanen, N. G. C. Astrath

We report on the continuity equations for linear momentum and energy associated to a recently introduced electromagnetic formulation based on classical dipolar sources [Eur. Phys. J. Plus 138, 1034 (2023)]. When connected to the mass-polariton quasi-particle dynamics, these equations provide a consistent microscopic description of the local optical energy an

Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna

Characterizing the function spaces defined by neural networks helps understanding the corresponding learning models and their inductive bias. While in some limits neural networks correspond to function spaces that are Hilbert spaces, these regimes do not capture the properties of the networks used in practice. Indeed, several results have shown that shallow

Shihan Qiu, Shaoyan Pan, Yikang Liu, Lin Zhao

The currently limited quality of accelerated cardiac cine reconstruction may potentially be improved by the emerging diffusion models, but the clinically unacceptable long processing time poses a challenge. We aim to develop a clinically feasible diffusion-model-based reconstruction pipeline to improve the image quality of cine MRI. A multi-in multi-out diff

Samuel Sze, Lars Kunze

In autonomous vehicles, understanding the surrounding 3D environment of the ego vehicle in real-time is essential. A compact way to represent scenes while encoding geometric distances and semantic object information is via 3D semantic occupancy maps. State of the art 3D mapping methods leverage transformers with cross-attention mechanisms to elevate 2D visio

Valery V. Ryzhikov

We construct rigid Poisson suspensions without roots. The discrete rational component in spectrum of an ergodic automorphism S prevents some roots from existing. If S is tensorly multiplied by an ergodic automorphism of the space with a sigma-finite measure, discrete spectrum disappears in this product, but like the smile of Cheshire Cat, the memory of it ca

SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros

Building embodied AI systems that can follow arbitrary language instructions in any 3D environment is a key challenge for creating general AI. Accomplishing this goal requires learning to ground language in perception and embodied actions, in order to accomplish complex tasks. The Scalable, Instructable, Multiworld Agent (SIMA) project tackles this by traini

Dinh-Khoi Vo, Duy-Nam Ly, Khanh-Duy Le, Tam V. Nguyen

Creating thematic collections in industries demands innovative designs and cohesive concepts. Designers may face challenges in maintaining thematic consistency when drawing inspiration from existing objects, landscapes, or artifacts. While AI-powered graphic design tools offer help, they often fail to generate cohesive sets based on specific thematic concept

Craig Innes, Subramanian Ramamoorthy

Autonomous Vehicles (AVs) are often tested in simulation to estimate the probability they will violate safety specifications. Two common issues arise when using existing techniques to produce this estimation: If violations occur rarely, simple Monte-Carlo sampling techniques can fail to produce efficient estimates; if simulation horizons are too long, import

Leandro Galo-Mendoza

In this paper, we prove the null controllability of a one-dimensional fourth-order degenerate parabolic equation with a singular potential. Here, we analyze cases where boundary control conditions are applied at the left endpoint. We utilize a spectral decomposition involving Bessel functions and their zeros in a convenient weighted Sobolev space for a degen

Natalia Mrnjavac, William F. Martin

Life is an exergonic chemical reaction. Many individual reactions in metabolism entail slightly endergonic steps that are coupled to free energy release, typically as ATP hydrolysis, in order to go forward. ATP is almost always supplied by the rotor-stator ATP synthase, which harnesses chemiosmotic ion gradients. Because the ATP synthase is a protein, it aro

Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes

Large language models (LLMs), despite their remarkable capabilities, are susceptible to generating biased and discriminatory responses. As LLMs increasingly influence high-stakes decision-making (e.g., hiring and healthcare), mitigating these biases becomes critical. In this work, we propose a causality-guided debiasing framework to tackle social biases, aim

C. L. Vaillant, M. P. A. Jones, R. M. Potvliege

Newly calculated multichannel quantum defect theory parameters and channel fractions are presented for the singlet and triplet S, P and D series and singlet F series of strontium. These results correct those reported in Vaillant C L, Jones M P A and Potvliege R M 2014 J. Phys. B: At. Mol. Opt. Phys. 47 155001.

Raj Kiriti Velicheti, Melih Bastopcu, S. Rasoul Etesami, Tamer Başar

Strategic information disclosure, in its simplest form, considers a game between an information provider (sender) who has access to some private information that an information receiver is interested in. While the receiver takes an action that affects the utilities of both players, the sender can design information (or modify beliefs) of the receiver through

Alireza Taheritajar, Reza Rahaeimehr

Acoustic side-channel attacks on keyboards can bypass security measures in many systems that use keyboards as one of the input devices. These attacks aim to reveal users' sensitive information by targeting the sounds made by their keyboards as they type. Most existing approaches in this field ignore the negative impacts of typing patterns and environmental n

Carlo Nicolini, Jacopo Staiano, Bruno Lepri, Raffaele Marino

A substantial gap persists in understanding the reasons behind the exceptional performance of the Transformer architecture in NLP. A particularly unexplored area involves the mechanistic description of how the distribution of parameters evolves over time during training. In this work we suggest that looking at the time evolution of the statistic distribution

Amit Meghanani, Thomas Hain

Acoustic word embeddings (AWEs) are vector representations of spoken words. An effective method for obtaining AWEs is the Correspondence Auto-Encoder (CAE). In the past, the CAE method has been associated with traditional MFCC features. Representations obtained from self-supervised learning (SSL)-based speech models such as HuBERT, Wav2vec2, etc., are outper

Sayar Ghosh Roy, Jiawei Han

Existing Machine Learning approaches for local citation recommendation directly map or translate a query, which is typically a claim or an entity mention, to citation-worthy research papers. Within such a formulation, it is challenging to pinpoint why one should cite a specific research paper for a particular query, leading to limited recommendation interpre

Hongguang Wang, Varun Harbola, Yu-Jung Wu, Peter A. van Aken

Epitaxial growth of thin-film heterostructures is generally considered the most successful procedure to obtain interfaces of excellent structural and electronic quality between three-dimensional materials. However, these interfaces can only join material systems with crystal lattices of matching symmetries and lattice constants. We present a novel category o

Michael Atlan

A comprehensive assessment of retinal health demands reliable and precise methods to measure localized blood perfusion. Despite considerable advancements in imaging techniques, such as indocyanine green and fluorescein angiography, along with optical coherence tomography angiography, their capacity to monitor blood flow dynamics across the cardiac cycle face

Sofia Franchini

We give a classification of torsion pairs, t-structures, and co-t-structures in the Paquette-Yildirim completion of the Igusa-Todorov discrete cluster category. We prove that the aisles of t-structures and co-t-structures are in bijection with non-crossing partitions enriched with some additional data. We also observe that recollements exist in the completio

Niklas Ziereis, Kazuaki Takasan, Naoto Tsuji

Superconductors exhibit a nonlinear interaction with an applied light, which can resonantly excite the collective amplitude (Higgs) mode. Here we study light-induced dynamics of layered superconductors, where each layer is coupled to adjacent layers via the Josephson coupling and the first few layers near the surface are driven by an in-plane-polarized light

Jing Wu, Jia-Wang Bian, Xinghui Li, Guangrun Wang

We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS). Our method first renders a collection of images by using the 3DGS and edits them by using a pre-trained 2D diffusion model (ControlNet) based on the input prompt, which is then used to optimise the 3D model. Our key contribution is multi-view cons

L. Roca, J. Song, E. Oset

We analyze theoretically the coupled-channel meson-baryon interaction with global flavor $\bar c c s s n$ and $\bar c c s s s$, where mesons are pseudoscalars or vectors and baryons have $J ^P=1/2^+$ or $3/2^+$. The aim is to explore whether the nonlinear dynamics inherent in the unitarization process within coupled channels can dynamically generate double-

Pauli Kehayias, Matthew A. Delaney, Raymond A. Haltli, Susan M. Clark

As quantum computing hardware becomes more complex with ongoing design innovations and growing capabilities, the quantum computing community needs increasingly powerful techniques for fabrication failure root-cause analysis. This is especially true for trapped-ion quantum computing. As trapped-ion quantum computing aims to scale to thousands of ions, the ele

Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang

Multimodal Large Language Models (MLLMs) excel in generating responses based on visual inputs. However, they often suffer from a bias towards generating responses similar to their pretraining corpus, overshadowing the importance of visual information. We treat this bias as a "preference" for pretraining statistics, which hinders the model's grounding in visu

Jan Lukas Bosse, Andrew M. Childs, Charles Derby, Filippo Maria Gambetta

In this work we propose an approach for implementing time-evolution of a quantum system using product formulas. The quantum algorithms we develop have provably better scaling (in terms of gate complexity and circuit depth) than a naive application of well-known Trotter formulas, for systems where the evolution is determined by a Hamiltonian with different en

Asad Aali, Giannis Daras, Brett Levac, Sidharth Kumar

We provide a framework for solving inverse problems with diffusion models learned from linearly corrupted data. Firstly, we extend the Ambient Diffusion framework to enable training directly from measurements corrupted in the Fourier domain. Subsequently, we train diffusion models for MRI with access only to Fourier subsampled multi-coil measurements at acce

Xue-Bin Liang

For any positive integer $q\geq 2$ and any real number $\delta\in(0,1)$, let $\alpha_q(n,\delta n)$ denote the maximum size of a subset of $\mathbb{Z}_q^n$ with minimum Hamming distance at least $\delta n$, where $\mathbb{Z}_q=\{0,1,\dotsc,q-1\}$ and $n\in\mathbb{N}$. The asymptotic rate function is defined by $ R_q(\delta) = \limsup_{n\rightarrow\infty}\fra

M. S. Cagliari, B. R. Granett, L. Guzzo, M. Bethermin

Multi-object spectroscopic galaxy surveys typically make use of photometric and colour criteria to select targets. Conversely, the Euclid NISP slitless spectrograph will record spectra for every source over its field of view. Slitless spectroscopy has the advantage of avoiding defining a priori a galaxy sample, but at the price of making the selection functi

Vivek Pareek, David R. Bacon, Xing Zhu, Yang-Hao Chan

Inducing novel quantum phases and topologies in materials using intense light fields is a key objective of modern condensed matter physics, but nonetheless faces significant experimental challenges. Alternately, theory predicts that in the dense limit, excitons - collective excitations composed of Coulomb-bound electron-hole pairs - could also drive exotic q

Sergi Masot-Llima, Artur Garcia-Saez

Efficient simulation of quantum computers relies on understanding and exploiting the properties of quantum states. This is the case for methods such as tensor networks, based on entanglement, and the tableau formalism, which represents stabilizer states. In this work, we integrate these two approaches to present a generalization of the tableau formalism used

Adem Limani

We investigate asymptotic polynomial approximation for a class of weighted Bloch functions in the unit disc. Our main result is a structural theorem on asymptotic polynomial approximation in the unit disc, in the flavor of the classical Plessner Theorem on asymptotic values of meromorphic functions. This provides the appropriate set up for studying metric an

Greg A. Kimmel

Water shows anomalous properties that are enhanced upon supercooling. The unusual behavior is observed in both H$_2$O and D$_2$O, however with different temperature dependences for the two isotopes. It is often noted that comparing the properties of the isotopes at two different temperatures (i.e., a temperature shift) approximately accounts for many of the

Syrine Kalleli, Scott Trigg, Ségolène Albouy, Mathieu Husson

Automatically extracting the geometric content from the hundreds of thousands of diagrams drawn in historical manuscripts would enable historians to study the diffusion of astronomical knowledge on a global scale. However, state-of-the-art vectorization methods, often designed to tackle modern data, are not adapted to the complexity and diversity of historic