April 2024 arXiv papers — page 134

Marco Carfagnini, Anna Paola Todino

We consider time-dependent space isotropic and time stationary spherical Gaussian random fields. We establish Chung's law of the iterated logarithm and solve the small probabilities problem. Our results depend on the high-frequency behaviour of the angular power spectrum: the speed of decay of the small ball probability is faster as either the memory paramet

Alberto Canonaco, Mattia Ornaghi, Paolo Stellari

We show that, over an arbitrary commutative ring, the localizations of the categories of dg categories, of cohomologically unital, of unital and of strictly unital $A_\infty$ categories with respect to the corresponding classes of quasi-equivalences are all equivalent. The result is proven at the $\infty$-categorical level by considering the natural $\infty$

Mukul Khanna, Ram Ramrakhya, Gunjan Chhablani, Sriram Yenamandra

The Embodied AI community has made significant strides in visual navigation tasks, exploring targets from 3D coordinates, objects, language descriptions, and images. However, these navigation models often handle only a single input modality as the target. With the progress achieved so far, it is time to move towards universal navigation models capable of han

Silvia Heubach, Matthieu Dufour

We introduce the game Slow $A$-Nim which generalizes a number of recently studied games. Slow $A$-Nim is played on $n$ stacks of tokens, and the set $A$ indicates the number of stacks a player can play on. Once a player has decided on the number $a$ of stacks, s/he will select any $a$ stacks and then remove one token from each stack. The last player to move

Nunzia Gavitone, Gianpaolo Piscitelli

In this paper, we study the first eigenvalue of the Laplacian on doubly connected domains when Robin and Dirichlet conditions are imposed on the outer and the inner part of the boundary, respectively. We provide that the spherical shell reaches the maximum of the first eigenvalue of this problem among the domains with fixed measure, outer perimeter and inner

Kostya Druzhkov

A direct reformulation of the Hamiltonian formalism in terms of the intrinsic geometry of infinitely prolonged differential equations is obtained. Concepts of spatial equation and spatial-gauge symmetry of a Lagrangian system of equations are introduced. A non-covariant canonical variational principle is proposed and demonstrated using the Maxwell equations

Tong Zhao, Lei Yang, Yichen Xie, Mingyu Ding

Road surface conditions, especially geometry profiles, enormously affect driving performance of autonomous vehicles. Vision-based online road reconstruction promisingly captures road information in advance. Existing solutions like monocular depth estimation and stereo matching suffer from modest performance. The recent technique of Bird's-Eye-View (BEV) perc

Ibrahim Aboumahmoud, Ekram Hossain, \\Amine Mezghani

Next generation wireless networks require more stringent performance levels. New technologies such as Reconfigurable intelligent surfaces (RISs) and rate-splitting multiple access (RSMA) are candidates for meeting some of the performance requirements, including higher user rates at reduced costs. RSMA provides a new way of mixing the messages of multiple use

Denis O. Demchenko, Mykhailo Vorobiov, Oleksandr Andrieiev, Mikhail A. Reshchikov

The Heyd-Scuseria-Ernzerhof (HSE) hybrid functional has become a widely used tool for theoretical calculations of point defects in semiconductors. It generally offers a satisfactory qualitative description of defect properties, including the donor/acceptor nature of defects, lowest energy charge states, thermodynamic and optical transition levels, Franck-Con

Jaron J. R. Lee, AmirEmad Ghassami, Ilya Shpitser

Causal inference is made challenging by confounding, selection bias, and other complications. A common approach to addressing these difficulties is the inclusion of auxiliary data on the superpopulation of interest. Such data may measure a different set of variables, or be obtained under different experimental conditions than the primary dataset. Analysis ba

Riccardo Argurio, Francesco Benini, Matteo Bertolini, Giovanni Galati

Three-dimensional Yang-Mills-Chern-Simons theory has the peculiar property that its one-form symmetry defects have non-trivial braiding, namely they are charged under the same symmetry they generate, which is then anomalous. This poses a few puzzles in describing the corresponding Symmetry TFT in a four-dimensional bulk. First, the braiding between lines at

Eric Ballouz, Barbara Lopez-Doriga, Scott T. M. Dawson, H. Jane Bae

This work introduces a formulation of resolvent analysis that uses wavelet transforms rather than Fourier transforms in time. Under this formulation, resolvent analysis may extend to turbulent flows with non-stationary mean states; the optimal resolvent modes are augmented with a temporal dimension and are able to encode the time-transient trajectories that

Omar Ghannou, Younès Bennani

Multi-source Domain Adaptation (MDA) seeks to adapt models trained on data from multiple labeled source domains to perform effectively on an unlabeled target domain data, assuming access to sources data. To address the challenges of model adaptation and data privacy, we introduce Collaborative MDA Through Optimal Transport (CMDA-OT), a novel framework consis

Philip Dörr

Generalized inversions $X_\mathrm{inv}^{(d)}$ and generalized descents $X_\mathrm{des}^{(d)}$ are an interesting combinatorial extension of the common inversion and descent statistics on permutation groups. By means of the root poset, they can be defined on all classical Weyl groups (i.e., symmetric groups, signed and even-signed permutation groups). In this

Jayadev Athreya, Jean Lagacé, Martin Möller, Martin Raum

Generalizing the well-known construction of Eisenstein series on the modular curves, Siegel-Veech transforms provide a natural construction of square-integrable functions on strata of differentials on Riemannian surfaces. This space carries actions of the foliated Laplacian derived from the SL(2,R)-action as well as various differential operators related to

Rasmus Bentmann, Ralf Meyer

We describe proper correspondences from graph C*-algebras to arbitrary C*-algebras by K-theoretic data. If the target C*-algebra is a graph C*-algebra as well, we may lift an isomorphism on a certain invariant to correspondences back and forth that are inverse to each other up to ideal-preserving homotopy. This implies a classification theorem for purely inf

A. E. Teretenkov

The work is devoted to superoperator master equations. Namely, the superoperator master equations in the case of the twirling hyperprojector with respect to the whole unitary group are derived. To be consistent with such a hyperprojector the free dynamics is assumed to be depolarizing. And it is perturbed by the arbitrary Gorini--Kossakowski--Sudarshan--Lind

Clovis Farley, Edouard Pinsolle, Bertrand Reulet

The statistics of electron transport in a quantum conductor is affected by fluctuations of its voltage bias. Here we show experimentally how a third order correlation in the electromagnetic field arises from the noise of a tunnel junction in the microwave domain being modulated by the vacuum fluctuations generated by a resistor at ultralow temperature. This

Md. Farhadul Islam, Md. Tanzim Reza, Meem Arafat Manab, Mohammad Rakibul Hasan Mahin

Spatial optimization is often overlooked in many computer vision tasks. Filters should be able to recognize the features of an object regardless of where it is in the image. Similarity search is a crucial task where spatial features decide an important output. The capacity of convolution to capture visual patterns across various locations is limited. In cont

Rubén Seoane Souto, Ramón Aguado

In recent years, experimental advances have made it possible to achieve an unprecedented degree of control over the properties of subgap bound states in hybrid nanoscale superconducting structures. This research has been driven by the promise of engineering subgap states for quantum applications, which includes Majorana zero modes predicted to appear at the

Manran Zhu, János Kertész

Data deluge characteristic for our times has led to information overload, posing a significant challenge to effectively finding our way through the digital landscape. Addressing this issue requires an in-depth understanding of how we navigate through the abundance of information. Previous research has discovered multiple patterns in how individuals navigate

Sean J. Gunderson, Kenneth G. Gayley

We present a general procedure for deriving a line profile model for massive star X-ray spectra that captures the dynamics of the wind more directly. The basis of the model is the analytic solution to the problem of variable jets in Herbig-Haro objects given by \citet{Canto2000}. In deriving our model, we generalize this jet solution to include flows with a

Tamir Shor, Chaim Baskin, Alex Bronstein

Breast cancer is a prominent health concern worldwide, currently being the secondmost common and second-deadliest type of cancer in women. While current breast cancer diagnosis mainly relies on mammography imaging, in recent years the use of thermography for breast cancer imaging has been garnering growing popularity. Thermographic imaging relies on infrared

Jack Garbus, Thomas Willkens, Alexander Lalejini, Jordan Pollack

Co-evolution is a powerful problem-solving approach. However, fitness evaluation in co-evolutionary algorithms can be computationally expensive, as the quality of an individual in one population is defined by its interactions with many (or all) members of one or more other populations. To accelerate co-evolutionary systems, we introduce phylogeny-informed in

Kevin Cummiskey, Lucas Villanti, Ira Crofford

In this paper, we investigate the effectiveness of the home team bunting in extra innings of Major League Baseball games when the game is tied in the bottom of the inning. Using methods rooted in causal inference, we show that teams choose not to bunt when the statistical evidence clearly suggests it is in their advantage to do so. The reluctance to bunt in

Milan Pavlovic, Tijana Sukilovic

In this paper, we study the normal geodesic flow associated with a sub-Riemannian structure corresponding to a left-invariant Riemannian metric and a right-invariant distribution (LR structure) on the $(2n+1)$-dimensional Heisenberg group. We investigate the integrability properties of the corresponding LR system and establish a distinction between the low-d

Luc Blanchet, Constantinos Skordis

We propose an extension of General Relativity (GR) based on a space-time foliation by three-dimensional space-like hypersurfaces labeled by the Khronon scalar field $\tau$. We show that this theory (i) leads to modified Newtonian dynamics (MOND) at galactic scales for stationary systems; (ii) recovers GR plus a cosmological constant in the strong field regim

Thomas Cass, Cristopher Salvi

These notes expound the recent use of the signature transform and rough path theory in data science and machine learning. We develop the core theory of the signature from first principles and then survey some recent popular applications of this approach, including signature-based kernel methods and neural rough differential equations. The notes are based on

Konstantinos Papadopoulos, Panagiotis Papadimitriou, Chrysa Papagianni

In-band network telemetry (INT), empowered by programmable dataplanes such as P4, comprises a viable approach to network monitoring and telemetry analysis. However, P4-INT as well as other existing frameworks for INT yield a substantial transmission overhead, which grows linearly with the number of hops and the number of telemetry values. To address this iss

Peter Alvaro, Matthew Adiletta, Adrian Cockroft, Frank Hady

Remote procedure calls are the workhorse of distributed systems. However, as software engineering trends, such as micro-services and serverless computing, push applications towards ever finer-grained decompositions, the overhead of RPC-based communication is becoming too great to bear. In this paper, we argue that point solutions that attempt to optimize one

Serina Hu

This work hopes to be an introduction to Deligne categories for someone familiar with classical representation theory and some category theory. In the first chapter, we motivate and define (symmetric) tensor categories, construct the Deligne categories, and prove their universal properties. In the second chapter, we define ultraproducts and use them to const

Hristo N. Djidjev

Quantum annealers like those from D-Wave Systems implement adiabatic quantum computing to solve optimization problems, but their analog nature and limited control functionalities present challenges to correcting or mitigating errors. As quantum computing advances towards applications, effective error suppression is an important research goal. We propose a ne

Tong Wang, Ninad Kulkarni, Yanjun Qi

Assessing the factual consistency of automatically generated texts in relation to source context is crucial for developing reliable natural language generation applications. Recent literature proposes AlignScore which uses a unified alignment model to evaluate factual consistency and substantially outperforms previous methods across many benchmark tasks. In

Julia Freund, Alexander Pirker, Wolfgang Dür

We consider multi-path routing of entanglement in quantum networks, where a pre-prepared multipartite entangled 2D cluster state serves as a resource to perform different tasks on demand. We show how to achieve parallel connections between multiple, freely chosen groups of parties by performing appropriate local measurements among diagonal paths, which prese

Carolina Arbeláez, A. E. Cárcamo Hernández, Claudio Dib, Patricio Escalona Contreras

In this work, we explore an extension of the Standard Model designed to elucidate the fermion mass hierarchy, account for the dark matter relic abundance, and explain the observed matter-antimatter asymmetry in the universe. Beyond the Standard Model particle content, our model introduces additional scalars and fermions. Notably, the light active neutrinos a

Parijat Dey, Kausik Ghosh

We study a conformal field theory with cubic anisotropic symmetry in presence of a line defect. We compute the correlators of the low lying defect operators using Feynman diagrams and derive explicit expressions for the two, three and four point defect correlators at the cubic fixed point in $4-\epsilon$ dimensions to $O(\epsilon)$. We also compute the defec

B. Hamil, B. C. Lütfüoğlu

In this paper, we present an exact solution for a spherically symmetric Schwarzschild black hole surrounded by perfect fluid dark matter (PFDM) in the presence of a quintessence field. We investigate the impact of dark matter on the black hole's thermodynamic and optical properties, as well as its quasinormal modes. Our analysis reveals a critical radius whe

Steven Walton, Svetlana Tokareva, Gianmarco Manzini

The stochastic finite volume method offers an efficient one-pass approach for assessing uncertainty in hyperbolic conservation laws. Still, it struggles with the curse of dimensionality when dealing with multiple stochastic variables. We introduce the stochastic finite volume method within the tensor-train framework to counteract this limitation. This integr

Samuel Castelo-Mourelle, Enrique Macías-Virgós, David Mosquera-Lois

We introduce two novel complementary notions of the Lefschetz number for a functor from a finite acyclic category to itself and we prove a Lefschetz fixed-object theorem and a Lefschetz fixed-morphism theorem. In order to do so, we use the connection between these type of categories and simplicial structures, such as trisps or delta complexes. Through the us

Shayan Noei, Heng Li, Ying Zou

Refactoring enhances software quality without altering its functional behaviors. Understanding the refactoring activities of developers is crucial to improving software maintainability. With the increasing use of machine learning (ML) libraries and frameworks, maximizing their maintainability is crucial. Due to the data-driven nature of ML projects, they oft

Yunqing Li, Binil Starly

Sourcing and identification of new manufacturing partners is crucial for manufacturing system integrators to enhance agility and reduce risk through supply chain diversification in the global economy. The advent of advanced large language models has captured significant interest, due to their ability to generate comprehensive and articulate responses across

Ruolin Ye, Yifei Hu, Yuhan, Bian

Meal preparation is an important instrumental activity of daily living~(IADL). While existing research has explored robotic assistance in meal preparation tasks such as cutting and cooking, the crucial task of peeling has received less attention. Robot-assisted peeling, conventionally a bimanual task, is challenging to deploy in the homes of care recipients

David H. Wolpert

The simulation hypothesis has recently excited renewed interest in the physics and philosophy communities. However, the hypothesis specifically concerns {\textit{computers}} that simulate physical universes. So to formally investigate the hypothesis, we need to understand it in terms of computer science (CS) theory. In addition we need a formal way to couple

Mengtao Tang, Daniel P. Stark, Richard S. Ellis, Michael W. Topping

JWST observations have recently begun delivering the first samples of Ly$\alpha$ velocity profile measurements at $z>6$, opening a new window on the reionization process. Interpretation of $z\gtrsim6$ line profiles is currently stunted by limitations in our knowledge of the intrinsic Ly$\alpha$ profile (before encountering the IGM) of the galaxies that are c

Zain Iqbal, Kashif Zafar, Aden Iqbal, Ayesha Khan

Software testing is an important and essential part of the software development life cycle and accounts for almost one-third of system development costs. In the software industry, testing costs can account for about 35% to 40% of the total cost of a software project. Therefore, providing efficient ways to test software is critical to reduce cost, time, and e

Kathryn Volk, Renu Malhotra

We present a stability analysis of a large set of simulated planetary systems of three or more planets based on architectures of multiplanet systems discovered by \textit{Kepler} and \textit{K2}. We propagated 21,400 simulated planetary systems up to 5 billion orbits of the innermost planet; approximately 13% of these simulations ended in a planet-planet col

Flavio Del Santo, Nicolas Gisin

We distinguish two different concepts of time that play a role in physics: \textit{geometric time} and \textit{creative time}. The former is the time of deterministic physics and merely parametrizes a given evolution. The latter is instead characterized by real change, i.e. novel information that gets created when a non-necessary event becomes determinate in

Adam Watts, Thomas Thompson, Dustin Harvey

This article describes two Monte Carlo methods for calculating confidence intervals on cumulative density function (CDF) based multivariate normal quantiles that allows for controlling the tail regions of a multivariate distribution where one is most concerned about extreme responses. The CDF based multivariate normal quantiles associated with bivariate dist

Bibek Upadhayay, Vahid Behzadan

Large Language Models (LLMs) are increasingly being developed and applied, but their widespread use faces challenges. These include aligning LLMs' responses with human values to prevent harmful outputs, which is addressed through safety training methods. Even so, bad actors and malicious users have succeeded in attempts to manipulate the LLMs to generate mis

Haoyang He, Yuhu Bai, Jiangning Zhang, Qingdong He

Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches. However, CNNs struggle with long-range dependencies, while transformers are burdened by quadratic computational complexity. Mamba-based models, with their superior long-range modeling and linear efficiency, have garnered substantial attention. This study

Lindsey Linxi Wei, Chung Yik Edward Yeung, Hongjian Yu, Jingchuan Zhou

We demonstrate MaskSearch, a system designed to accelerate queries over databases of image masks generated by machine learning models. MaskSearch formalizes and accelerates a new category of queries for retrieving images and their corresponding masks based on mask properties, which support various applications, from identifying spurious correlations learned

Yifu Zhang, Lei Ma

Nonadiabatic geometric quantum computation (NGQC) provides a means to perform fast and robust quantum gates. To enhance the robustness of NGQC against control errors, numerous solutions have been proposed by predecessors. However, these solutions typically result in extended operation times for quantum gates. In order to maintain the robustness of quantum ga

Rajshree Daulatabad, Serena Nath

Teaching autonomous mobile robots to successfully navigate human crowds is a challenging task. Not only does it require planning, but it requires maintaining social norms which may differ from one context to another. Here we focus on crowd navigation, using a neural network to learn specific strategies in-situ with a robot. This allows us to take into accoun

Eloise Hamilton, Victoria Hoskins, Joshua Jackson

We give an explicit approach to quotienting affine varieties by linear actions of linear algebraic groups with graded unipotent radical, using results from projective Non-Reductive GIT. Our quotients come with explicit projective completions, whose boundaries we interpret in terms of the original action. As an application we construct moduli spaces of semist

Richard E. Neddo, Zander W. Blasingame, Chen Liu

Face morphing attacks pose an increasing threat to face recognition (FR) systems. A morphed photo contains biometric information from two different subjects to take advantage of vulnerabilities in FRs. These systems are particularly susceptible to attacks when the morphs are subjected to print-scanning to mask the artifacts generated during the morphing proc

Bansi Mandalia, Steve Greenwald, Simon Shaw, Gregory Slabaugh

Coronary Artery Disease (CAD) results from plaque deposit in a coronary artery. Early diagnosis is imperative, so a non-invasive detection method is being developed to identify acoustic signals caused by partial occlusions in the artery. The blood flow in the artery is disturbed and imposes oscillatory stresses on the artery wall. The deformations caused by

Mariia Demianenko, Joerg-Uwe Pott, Kai Polsterer

Nowadays, astronomers perform point spread function (PSF) fitting for most types of observational data. Interpolation of the PSF is often an intermediate step in such algorithms. In the case of the Multi-AO Imaging Camera for Deep Observations (MICADO) at the Extremely Large Telescope (ELT), PSF interpolation will play a crucial role in high-precision astrom

C. J. Rodriguez, S. L. Thomson, T. Alderliesten, P. A. N. Bosman

Many real-world problems have expensive-to-compute fitness functions and are multi-objective in nature. Surrogate-assisted evolutionary algorithms are often used to tackle such problems. Despite this, literature about analysing the fitness landscapes induced by surrogate models is limited, and even non-existent for multi-objective problems. This study addres

Anthony M. Bloch, Peter E. Crouch, Tudor S. Ratiu

We analyze discrete optimal control problems and their connection with back propagation and deep learning. We consider in particular the symmetric representation of the discrete rigid body equations developed via optimal control analysis and optimal flows on adjoint orbits

Ye Wang, Yiru Zhu, Han Yan, Yang Li

Inducing chirality in optically and electronically active materials is interesting for applications in sensing and quantum information transmission. Two-dimensional (2D) transition metal chalcogenides (TMDs) possess excellent electronic and optical properties but are achiral. Here we demonstrate chirality induction in atomically thin layers of 2D MoS2 by fun

Fernando Cukierman, César Massri

We develop some basic facts on deformations of exterior differential ideals on a smooth complex algebraic variety. With these tools we study deformations of several types of differential ideals, leading to several irreducible components of the corresponding moduli spaces

Tanner Andrulis, Ruicong Chen, Hae-Seung Lee, Joel S. Emer

Analog Compute-in-Memory (CiM) accelerators use analog-digital converters (ADCs) to read the analog values that they compute. ADCs can consume significant energy and area, so architecture-level ADC decisions such as ADC resolution or number of ADCs can significantly impact overall CiM accelerator energy and area. Therefore, modeling how architecture-level de

Matías Briceño, Cristián Martínez, Jorge Zanelli

The nature of the central singularity of the BTZ geometries -- stationary vacuum solutions of 2+1 gravity with negative cosmological constant $\Lambda=-\ell^{-2}$ and $SO(2)\times \mathbb{R}$ isometry -- is discussed. The essential tool for this analysis is the holonomy operator on a closed path (i.e., Wilson loop) around the central singularity. The study c

Marco Astorino

The Plebanski-Demianski metric is commonly thought to describe the most general Type D black hole in general relativity (possibly coupled with Maxwell electromagnetism), but in the form we know at the moment, it fails to include the elusive accelerating spacetimes with gravitomagnetic mass without angular momentum. We propose a very general type D metric, st

E. Ahrer, J. V. Seidel, L. Doyle, S. Gandhi

We present high spectral resolution observations of the hot Jupiter WASP-94 A b using the HARPS instrument on ESO's 3.6m telescope in La Silla, Chile. We probed for Na absorption in its atmosphere as well as constrained the previously reported misaligned retrograde orbit using the Rossiter-McLaughlin effect. Additionally, we undertook a combined atmospheric

Haotian Chen, Anna Kuzina, Babak Esmaeili, Jakub M Tomczak

Current state-of-the-art optimizers are adaptive gradient-based optimization methods such as Adam. Recently, there has been an increasing interest in formulating gradient-based optimizers in a probabilistic framework for better modeling the uncertainty of the gradients. Here, we propose to combine both approaches, resulting in the Variational Stochastic Grad

Shikhar Asthana, Martin G. Haehnelt, Girish Kulkarni, Dominique Aubert

We present a new suite of late-end reionization simulations performed with ATON-HE, a revised version of the GPU-based radiative transfer code ATON that includes helium. The simulations are able to reproduce the Ly$\alpha$ flux distribution of the E-XQR-30 sample of QSO absorption spectra at $5 \lesssim z \lesssim 6.2$, and show that a large variety of reion

Daniel Frolovsky, Florian Kuhnel, Ioanna Stamou

A novel methodology for analysing the relation between the energy density in gravitational waves and primordial power spectra is developed. Focusing on scalar-induced gravitational radiation, this methodology is applied to a number of scenarios for the primordial black hole formation. Being differed from conventional Bayesian approaches, its advantages inclu

Aditya Chowdhury, Nissim Kanekar, Jayaram N. Chengalur

We present the first estimate, based on direct HI 21 cm observations, of the HI mass function (HIMF) of star-forming galaxies at $z\approx1$, obtained by combining our measurement of the scaling relation between HI mass ($M_{HI}$) and B-band luminosity ($M_B$) of star-forming galaxies with literature estimates of the B-band luminosity function at $z\approx1$

Evan T. Hockings, Andrew C. Doherty, Robin Harper

Characterising the performance of noisy quantum circuits is central to the production of prototype quantum computers and can enable improved quantum error correction that exploits noise biases identified in a quantum device. We develop a scalable noise characterisation protocol suited to characterising the syndrome extraction circuits of quantum error correc

Mudit Rai, Luca Santoni

It is well known that asymptotically flat black holes in general relativity have vanishing tidal Love numbers. In the case of Schwarzschild and Kerr black holes, this property has been shown to be a consequence of a hidden structure of ladder symmetries for the perturbations. In this work, we extend the ladder symmetries to non-rotating charged black holes i

Chamilla Terp, Kasper E. Heintz, Darach Watson, Gabriel Brammer

We present a comprehensive spectro-photometric analysis of the galaxy GS9422 from the JADES GTO survey located at $z=5.943$, anomalously showing a simultaneous strong Ly$\alpha$ emission feature and damped Ly$\alpha$ absorption (DLA), based on JWST NIRSpec and NIRCam observations. The best-fit modelling of the spectral energy distribution (SED) reveals a you

Luca Barsellotti, Roberto Amoroso, Marcella Cornia, Lorenzo Baraldi

Open-vocabulary semantic segmentation aims at segmenting arbitrary categories expressed in textual form. Previous works have trained over large amounts of image-caption pairs to enforce pixel-level multimodal alignments. However, captions provide global information about the semantics of a given image but lack direct localization of individual concepts. Furt

H. Diego Rosales, Roberto E. Troncoso

The effects of disorder on the robustness of topological magnon states of two-dimensional ferromagnetic skyrmions is investigated. It is diagnosed by evaluating a real space topological invariant, the bosonic Bott index (BI). The disorder simultaneously breaks the axially symmetric shape and the crystalline ordering of the skyrmions array. The corresponding

Karina Barboza, Christopher S. Kochanek

A large fraction of massive stars are found in higher order systems where the presence of a tertiary may significantly modify the system's evolution. In particular, it can lead to increased numbers of compact object binaries and accelerate their mergers with important implications for gravitational wave observations. Using Gaia, we constrain the number of Ga

Subhadip Bouri, Priyank Parashari, Mousumi Das, Ranjan Laha

The exact sources of high-energy neutrinos detected by the IceCube neutrino observatory still remain a mystery. For the first time, this work explores the hypothesis that galaxy mergers may serve as sources for these high-energy neutrinos. Galaxy mergers can host very high-energy hadronic and photohadronic processes, which may produce very high-energy neutri

Valentina Cesare

If visible matter alone is present in the Universe, general relativity (GR) and its Newtonian weak field limit (WFL) cannot explain several pieces of evidence, from the largest to the smallest scales. The most investigated solution is the cosmological model $\Lambda$ cold dark matter ($\Lambda$CDM), where GR is valid and two dark components are introduced, d

Pavel E. Mancera Piña, Giulia Golini, Ignacio Trujillo, Mireia Montes

AGC 114905 is a dwarf gas-rich ultra-diffuse galaxy seemingly in tension with the cold dark matter (CDM) model. Specifically, the galaxy appears to have an extremely low-density halo and a high baryon fraction, while CDM predicts dwarfs to have very dense and dominant dark haloes. The alleged tension relies on the galaxy's rotation curve decomposition, which

Tista Banerjee, Sayan Choudhury, K. Sengupta

We demonstrate the existence of exact Floquet flat bands implying strong violation of the eigenstate thermalization hypothesis in a large class of closed quantum many-body systems in the presence of a two-rate drive characterized by frequencies $\Omega_1$ and $\Omega_2=\nu \Omega_1$. We provide the exact analytic condition for this phenomenon to occur for a

Gavin S. Hartnett, Aaron Barbosa, Pranav S. Mundada, Michael Hush

We introduce and experimentally test a machine-learning-based method for ranking logically equivalent quantum circuits based on expected performance estimates derived from a training procedure conducted on real hardware. We apply our method to the problem of layout selection, in which abstracted qubits are assigned to physical qubits on a given device. Circu

Mark R. Hirsbrunner, J. Wayne Mullinax, Yizhi Shen, David B. Williams-Young

Recent research has shown that wavefunction evolution in real- and imaginary-time can generate quantum subspaces with significant utility for obtaining accurate ground state energies. Inspired by these methods, we propose combining quantum subspace techniques with the variational quantum eigensolver (VQE). In our approach, the parameterized quantum circuit i

David Marzocca, Marco Nardecchia, Alfredo Stanzione, Claudio Toni

We study the implications of the observed excess in $B^+ \to K^+ \nu \bar{\nu}$ under the assumption of Rank-One Flavour Violation, i.e. that New Physics couples to a single specific direction in flavour space. By varying this direction we perform analyses at the level of the low-energy EFT, the SMEFT, and with explicit mediators such as leptoquarks and colo

Evyatar Tulipman, Noga Bashan, Jörg Schmalian, Erez Berg

Strange metal behavior is traditionally associated with an underlying putative quantum critical point at zero temperature. However, in many correlated metals, e.g., high-Tc cuprate superconductors, strange metallicity persists at low temperatures over an extended range of microscopic parameters, suggesting the existence of an underlying quantum critical phas

Francesco D'Eugenio, Alex J. Cameron, Jan Scholtz, Stefano Carniani

We present the third data release of JADES, the JWST Advanced Deep Extragalactic Survey, providing both imaging and spectroscopy in the two GOODS fields. Spectroscopy consists of medium-depth and deep NIRSpec/MSA spectra of 4,000 targets, covering the spectral range 0.6-5.3 $\mu$m and observed with both the low-dispersion prism (R=30-300) and all three mediu

Marcos M. Flores, Yuber F. Perez-Gonzalez

We investigate the generation of the baryon asymmetry within the framework of cosmological gra\-vi\-ta\-tional particle production, employing the Bogoliubov approach. We examine two well-known baryogenesis scenarios, namely baryogenesis in Grand Unified Theories (GUT) and leptogenesis, while considering reheating temperatures sufficiently low for thermal pro

Pravesh K. Kothari, Peter Manohar

We give improved lower bounds for binary $3$-query locally correctable codes (3-LCCs) $C \colon \{0,1\}^k \rightarrow \{0,1\}^n$. Specifically, we prove: (1) If $C$ is a linear design 3-LCC, then $n \geq 2^{(1 - o(1))\sqrt{k} }$. A design 3-LCC has the additional property that the correcting sets for every codeword bit form a perfect matching and every pair

Xiaoyi Dong, Pan Zhang, Yuhang Zang, Yuhang Cao

The Large Vision-Language Model (LVLM) field has seen significant advancements, yet its progression has been hindered by challenges in comprehending fine-grained visual content due to limited resolution. Recent efforts have aimed to enhance the high-resolution understanding capabilities of LVLMs, yet they remain capped at approximately 1500 x 1500 pixels and

Juhong Min, Shyamal Buch, Arsha Nagrani, Minsu Cho

This paper addresses the task of video question answering (videoQA) via a decomposed multi-stage, modular reasoning framework. Previous modular methods have shown promise with a single planning stage ungrounded in visual content. However, through a simple and effective baseline, we find that such systems can lead to brittle behavior in practice for challengi

Yuan-Hong Liao, Rafid Mahmood, Sanja Fidler, David Acuna

Enhancing semantic grounding abilities in Vision-Language Models (VLMs) often involves collecting domain-specific training data, refining the network architectures, or modifying the training recipes. In this work, we venture into an orthogonal direction and explore whether VLMs can improve their semantic grounding by "receiving" feedback, without requiring i

Yixuan Ma, Luciano Rezzolla

The Rezzolla-Zhidenko (RZ) and Konoplya-Rezzolla-Zhidenko (KRZ) frameworks provide an efficient approach to characterize agnostically spherically symmetric or stationary black-hole spacetimes in arbitrary metric theories. In their original construction, these metrics were defined only in the spacetime region outside of the event horizon, where they can repro

Anton Schäfer, Thomas Hofmann, Imanol Schlag, Tiago Pimentel

Tokenisation is a core part of language models (LMs). It involves splitting a character sequence into subwords which are assigned arbitrary indices before being served to the LM. While typically lossless, however, this process may lead to less sample efficient LM training: as it removes character-level information, it could make it harder for LMs to generali

Jane Wu, Georgios Pavlakos, Georgia Gkioxari, Jitendra Malik

Objects manipulated by the hand (i.e., manipulanda) are particularly challenging to reconstruct from Internet videos. Not only does the hand occlude much of the object, but also the object is often only visible in a small number of image pixels. At the same time, two strong anchors emerge in this setting: (1) estimated 3D hands help disambiguate the location

Rong-Gen Cai, Yu-Shi Hao, Shao-Jiang Wang

Recently, much attention has been focused on the false vacuum islands that are flooded by an expanding ocean of true-vacuum bubbles slightly later than most of the other parts of the world. These delayed decay regions will accumulate locally larger vacuum energy density by staying in the false vacuum longer than those already transited into the true vacuum.

Yujian Xiong, Yanshuai Tu, Zhong-Lin Lu, Yalin Wang

Human vision has different concentration on visual fields. Cortical magnification factor (CMF) is a popular measurement on visual acuity and cortex concentration. In order to achieve thorough measurement of CMF across the whole visual field, we propose a method to measure planar CMF upon retinotopic maps generated by pRF decoding, with help of our proposed m

Brandon T. Radzom, Jiayin Dong, Malena Rice, Xian-Yu Wang

Despite decades of effort, the mechanisms by which the spin axis of a star and the orbital axes of its planets become misaligned remain elusive. Particularly, it is of great interest whether the large spin-orbit misalignments observed are driven primarily by high-eccentricity migration -- expected to have occurred for short-period, isolated planets -- or ref

Nathan Brake, Thomas Schaaf

Following an interaction with a patient, physicians are responsible for the submission of clinical documentation, often organized as a SOAP note. A clinical note is not simply a summary of the conversation but requires the use of appropriate medical terminology. The relevant information can then be extracted and organized according to the structure of the SO

Adrien Perrel

We consider random walk in Dirichlet random environment in ${\mathbf{Z}^d, d\ge 3}$, which corresponds to the case where the environment is constructed from i.i.d. transition probabilities at each vertex with a Dirichlet distribution with parameters $(\alpha_i)_{1 \le i \le 2d}$. Dirichlet environments are weakly elliptic and the walk can be slowdowned by lo

W. R. F. Dent, G. Harper, A. M. S. Richards, P. Kervella

Emission lines from Rydberg transitions are detected for the first time from a region close to the surface of Betelgeuse. The H30${\alpha}$ line is observed at 231.905 GHz, with a FWHM ~42 km/s and extended wings. A second line at 232.025 GHz (FWHM ~21 km/s), is modeled as a combination of Rydberg transitions of abundant low First Ionization Potential metals

Doruk Aksoy, Jian Luo, Penghui Cao, Timothy J. Rupert

The discovery of complex concentrated alloys has unveiled materials with diverse atomic environments, prompting the exploration of solute segregation beyond dilute alloys. Data-driven methods offer promising for modeling segregation in such chemically complex environments, and are employed in this study to understand segregation behavior of a refractory comp

Ekansh Sharma, Devin Kwok, Tom Denton, Daniel M. Roy

Neural networks typically exhibit permutation symmetries which contribute to the non-convexity of the networks' loss landscapes, since linearly interpolating between two permuted versions of a trained network tends to encounter a high loss barrier. Recent work has argued that permutation symmetries are the only sources of non-convexity, meaning there are ess