March 2024 arXiv papers — page 15

Evgenios T. A. Kakariadis, Ioannis Apollon Paraskevas

We provide a characterisation of equivariant Fock covariant injective representations for product systems. We show that this characterisation coincides with Nica covariance for compactly aligned product systems over right LCM semigroups of Kwa\'{s}niewski and Larsen, and with the Toeplitz representations of a discrete monoid of Laca and Sehnem. By combining

Tristan Peng, Hongchan Choi, Jonathan Berger

SIREN is a flexible, extensible, and customizable web-based general-purpose interface for auditory data display (sonification). Designed as a digital audio workstation for sonification, synthesizers written in JavaScript using the Web Audio API facilitate intuitive mapping of data to auditory parameters for a wide range of purposes. This paper explores the b

Parisa Mollaei, Danush Sadasivam, Chakradhar Guntuboina, Amir Barati Farimani

Intrinsically Disordered Proteins (IDPs) constitute a large and structure-less class of proteins with significant functions. The existence of IDPs challenges the conventional notion that the biological functions of proteins rely on their three-dimensional structures. Despite lacking well-defined spatial arrangements, they exhibit diverse biological functions

Tristram de Piro

We prove an inversion theorem for the Fourier transform defined for normal functions, in the case when such functions are of moderate decrease, and in dimensions 2 and 3. This improves on Carleson's general almost everywhere convergence result for square integrable functions to everywhere convergence, in the special case of normal functions of moderate decre

Benjamin Kraske, Zakariya Laouar, Zachary Sunberg

As humans come to rely on autonomous systems more, ensuring the transparency of such systems is important to their continued adoption. Explainable Artificial Intelligence (XAI) aims to reduce confusion and foster trust in systems by providing explanations of agent behavior. Partially observable Markov decision processes (POMDPs) provide a flexible framework

Charles G. Durfee, Andy R. Rundquist, Sterling Backus, Catherine Herne

We investigate the case of phase-matched high-harmonic generation in a gas-filled capillary waveguide, comparing in detail theory with experiment. We observe three different regimes of phase matching: one where atomic dispersion balances waveguide dispersion, another corresponding to non-collinear Cerenkov phase-matching, and a third where atomic dispersion

Enzo Vitillaro

The paper addresses the doubly elliptic eigenvalue problem $$\begin{cases} -\Delta u=\lambda u \qquad &\text{in $\Omega$,}\\ u=0 &\text{on $\Gamma_0$,}\\ -\Delta_\Gamma u +\partial_\nu u =\lambda u\qquad &\text{on $\Gamma_1$,} \end{cases} $$ where $\Omega$ is a bounded open subset of $\mathbb{R}^N$ ($N\ge 2$) with $C^1$ boundary $\Gamma=\Gamma_0\cup\Gamma_1$

Dominic Widdows, Willie Aboumrad, Dohun Kim, Sayonee Ray

Language processing is at the heart of current developments in artificial intelligence, and quantum computers are becoming available at the same time. This has led to great interest in quantum natural language processing, and several early proposals and experiments. This paper surveys the state of this area, showing how NLP-related techniques have been used

R. Bartels, S. Backus, E. Zeek, L. Misoguti

High-harmonic generation is one of the most extreme nonlinear-optical processes observed to date. By focusing an intense laser pulse into a gas, the light-atom interaction that occurs during the process of ionising the atoms results in the generation of harmonics of the driving laser frequency, that extend up to order ~300 (corresponding to photon energies f

Rubén Fernández-Casal, Sergio Castillo-Páez, Mario Francisco-Fernández

A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds a certain threshold value is proposed. The method consists of a bootstrap algorithm that combines conditional simulation techniques with nonparametric estimations of the trend and the variability. The nonparametric local linear estimator, con

Sergio Morales-Tejera, Victor E. Ambruş, Maxim N. Chernodub

In this paper, we consider the effect of interactions on the local, average polarization of a quantum plasma of massless fermion particles characterized by vector, axial, and helical quantum numbers. Due to the helical and axial vortical effects, perturbations in the vector charge in a rotating plasma can lead to chiral and helical charge transfer along the

Sergio Morales-Tejera, Victor E. Ambruş, Maxim N. Chernodub

Due to the spin-orbit coupling, Dirac fermions, submerged in a thermal bath with finite macroscopic vorticity, exhibit a spin polarisation along the direction parallel to the vorticity vector $\boldsymbol{\Omega}$. Due to the symmetries of the Lagrangian for free massless Dirac particles, there are three independent and classically conserved currents corresp

Mohsen Gholami, Mohammad Akbari, Cindy Hu, Vaden Masrani

Knowledge distillation from LLMs is essential for the efficient deployment of language models. Prior works have proposed data generation using LLMs for preparing distilled models. We argue that generating data with LLMs is prone to sampling mainly from the center of original content distribution. This limitation hinders the distilled model from learning the

Chris Elliott, Owen Gwilliam, Matteo Lotito

We take first steps toward a theory of ``conformal twists'' for superconformal field theories in dimension 3 to 6, extending the well-known analysis of twists for supersymmetric theories. A conformal twist is a square-zero odd element in the superconformal Lie algebra, and we classify all twists and describe their orbits under the adjoint action of the super

Marcos Matabuena, Juan C. Vidal, Rahul Ghosal, Jukka-Pekka Onnela

Complex survey designs are commonly employed in many medical cohorts. In such scenarios, developing case-specific predictive risk score models that reflect the unique characteristics of the study design is essential for minimizing selective biases in the statistical results. The objectives of this paper are to: (i) propose a general predictive framework for

Mario Guevara

Development of a spatial-temporal and data-driven model of soil respiration at the global scale based on soil temperature, yearly soil moisture, and soil organic carbon (C) estimates. Prediction of soil respiration on an annual basis (1991-2018) with relatively high accuracy (NSE 0.69, CCC 0.82). Lower soil respiration trends, higher soil respiration magnitu

Nathan S. Gottesman, Michael A. Slocum, Gary A. Sevison, Michael Wolf

Nitrogen-vacancy (NV) centers have considerable promise as high sensitivity magnetometers, however are commonly limited by inefficient collection and low contrasts. Laser threshold magnetometry (LTM) enables efficient collection and high contrasts, providing a path towards higher sensitivity magnetometry. We demonstrate an infrared LTM using an ensemble of N

Randy A. Bartels, Ariel Paul, Hans Green, Henry C. Kapteyn

We present spatial coherence measurements of extreme-ultraviolet light generated using the process of high-harmonic upconversion of a femtosecond laser. Using a phase-matched hollow-fiber geometry, the generated beam is found to exhibit essentially full spatial coherence. The coherence of this laser-like EUV source is demonstrated by recording Gabor hologram

Gwen Walker, Nick Ekanger, R. Andrew Gustafson, Sean Heston

It has long been accepted that the cosmos determine our personalities, relationships, and even our fate. Unlike our condensed matter colleagues - who regularly use quantum mechanics to determine the healing properties of crystals - astrology techniques have been unchanged since the 19th century. In this paper, we discuss how astrophysical messengers beyond s

Antoine Tilloy

This note derives the stochastic differential equations and partial differential equation of general hybrid quantum--classical dynamics from the theory of continuous measurement and general (non-Markovian) feedback. The advantage of this approach is an explicit parameterization, without additional positivity constraints. The construction also neatly separate

Hewan Shemtaga, Wenxian Shen, Selim Sukhtaiev

Chemotaxis phenomena govern the directed movement of micro-organisms in response to chemical stimuli. In this paper, we investigate two Keller--Segel systems of reaction-advection-diffusion equations modeling chemotaxis on thin networks. The distinction between two systems is driven by the rate of diffusion of the chemo-attractant. The intermediate rate of d

Charles J. Lada, Jan Forbrich, Glen Petitpas, Sebastien Viaene

Deep interferometric observations of CO and dust continuum emission are obtained with the Sub-Millimeter Array (SMA) at 230 GHz to investigate the physical nature of the giant molecular cloud (GMC) population in the Andromeda galaxy (M31). We use J = 2-1 $^{12}$CO and $^{13}$CO emission to derive the masses, sizes and velocity dispersions of 162 spatially re

Emma Yu Jin, Stephanie van Willigenburg

The question of classifying when two skew Schur functions are equal is a substantial open problem, which remains unsolved for over a century. In 2022, Aliniaeifard, Li and van Willigenburg introduced skew Schur functions in noncommuting variables, $s_{(\delta,D)}$, where $D$ is a connected skew diagram with $n$ boxes and $\delta$ is a permutation in the symm

Alexandros Chiotellis, Emmanouil Zapartas, Dominique M. -A. Meyer

Mixed-morphology supernova remnants (MMSNRs) are characterized by a shell-like morphology in the radio and centrally-peaked thermal emission in the X-ray band. The nature of this peculiar class of supernova remnants (SNRs) remains a controversial issue. In this work, by pairing the predictions of stellar evolution theory with two-dimensional hydrodynamic sim

Johannes M. Henn, Antonela Matijašić, Julian Miczajka, Tiziano Peraro

We compute three families of two-loop six-point massless Feynman integrals in dimensional regularization, namely the double-box, the pentagon-triangle, and the hegaxon-bubble family. This constitutes the first analytic computation of two-loop master integrals with eight scales. We use the method of canonical differential equations. We describe the correspond

Aldo G. Sepulveda, Timothy R. Bedding, Simon J. Murphy, Luca Matra

HD 21997 is host to a prototypical "hybrid" debris disk characterized by debris disk-like dust properties and a CO gas mass comparable to a protoplanetary disk. We use Transiting Exoplanet Survey Satellite time series photometry to demonstrate that HD 21997 is a high-frequency delta Scuti pulsator. If the mode identification can be unambiguously determined i

Yun-Ting Cheng, Kailai Wang, Benjamin D. Wandelt, Tzu-Ching Chang

Line intensity mapping (LIM) has emerged as a promising tool for probing the 3D large-scale structure through the aggregate emission of spectral lines. The presence of interloper lines poses a crucial challenge in extracting the signal from the target line in LIM. In this work, we introduce a novel method for LIM analysis that simultaneously extracts line si

Jiansong Gao, Yonit Hochberg, Benjamin V. Lehmann, Sae Woo Nam

Superconducting detectors are a promising technology for probing dark matter at extremely low masses, where dark matter interactions are currently unconstrained. Realizing the potential of such detectors requires new readout technologies to achieve the lowest possible thresholds for deposited energy. Here we perform a prototype search for dark matter--electr

Valentin Crépel, Peize Ding, Nishchhal Verma, Nicolas Regnault

The observation of delicate correlated phases in twisted heterostructures of graphene and transition metal dichalcogenides suggests that moir\'e flat bands are intrinsically resilient against certain types of disorder. Here, we investigate the robustness of moir\'e flat bands in the chiral limit of the Bistrizer-MacDonald model -- applicable to both platform

Bowen Zhang, Yiji Cheng, Jiaolong Yang, Chunyu Wang

We introduce a radiance representation that is both structured and fully explicit and thus greatly facilitates 3D generative modeling. Existing radiance representations either require an implicit feature decoder, which significantly degrades the modeling power of the representation, or are spatially unstructured, making them difficult to integrate with mains

Keyan Chen, Bowen Chen, Chenyang Liu, Wenyuan Li

Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation. The recent advancements of Convolutional Neural Networks (CNNs) and Transformers have markedly enhanced classification accuracy. Nonetheless, remote sensing scene classification remains a significant chal

Katherine Xu, Lingzhi Zhang, Jianbo Shi

Modern text-to-image (T2I) diffusion models can generate images with remarkable realism and creativity. These advancements have sparked research in fake image detection and attribution, yet prior studies have not fully explored the practical and scientific dimensions of this task. In addition to attributing images to 12 state-of-the-art T2I generators, we pr

Sirui Xu, Ziyin Wang, Yu-Xiong Wang, Liang-Yan Gui

Text-conditioned human motion generation has experienced significant advancements with diffusion models trained on extensive motion capture data and corresponding textual annotations. However, extending such success to 3D dynamic human-object interaction (HOI) generation faces notable challenges, primarily due to the lack of large-scale interaction data and

Kai Zhang, Yi Luan, Hexiang Hu, Kenton Lee

Image retrieval, i.e., finding desired images given a reference image, inherently encompasses rich, multi-faceted search intents that are difficult to capture solely using image-based measures. Recent works leverage text instructions to allow users to more freely express their search intents. However, they primarily focus on image pairs that are visually sim

John Ellis, Malcolm Fairbairn, Gert Hütsi, Juan Urrutia

JWST observations have opened a new chapter in studies of supermassive black holes (SMBHs), stimulating discussion of two puzzles: the abundance of SMBHs in the early Universe and the fraction of dual AGNs. In this paper we argue that the answers to these puzzles may be linked to an interpretation of the data on the nHz gravitational wave (GWs) discovered by

Hui Zhang, Sammy Christen, Zicong Fan, Otmar Hilliges

Human hands possess the dexterity to interact with diverse objects such as grasping specific parts of the objects and/or approaching them from desired directions. More importantly, humans can grasp objects of any shape without object-specific skills. Recent works synthesize grasping motions following single objectives such as a desired approach heading direc

Daphne Cornelisse, Eugene Vinitsky

A central challenge for autonomous vehicles is coordinating with humans. Therefore, incorporating realistic human agents is essential for scalable training and evaluation of autonomous driving systems in simulation. Simulation agents are typically developed by imitating large-scale, high-quality datasets of human driving. However, pure imitation learning age

Samuel Marks, Can Rager, Eric J. Michaud, Yonatan Belinkov

We introduce methods for discovering and applying sparse feature circuits. These are causally implicated subnetworks of human-interpretable features for explaining language model behaviors. Circuits identified in prior work consist of polysemantic and difficult-to-interpret units like attention heads or neurons, rendering them unsuitable for many downstream

Chenyang Liu, Keyan Chen, Haotian Zhang, Zipeng Qi

Monitoring changes in the Earth's surface is crucial for understanding natural processes and human impacts, necessitating precise and comprehensive interpretation methodologies. Remote sensing satellite imagery offers a unique perspective for monitoring these changes, leading to the emergence of remote sensing image change interpretation (RSICI) as a signifi

Sofiia Dubova, Kevin Yang, Horng-Tzer Yau, Jun Yin

We consider a constant-size subset of left and right eigenvectors of an $N\times N$ i.i.d. complex non-Hermitian matrix associated with the eigenvalues with pairwise distances at least $N^{-\frac12+\epsilon}$. We show that arbitrary constant rank projections of these eigenvectors are Gaussian and jointly independent.

Hidir Yesiltepe, Kiymet Akdemir, Pinar Yanardag

Diffusion-based text-to-image models have rapidly gained popularity for their ability to generate detailed and realistic images from textual descriptions. However, these models often reflect the biases present in their training data, especially impacting marginalized groups. While prior efforts to debias language models have focused on addressing specific bi

Frederik vom Ende

We prove the statement "The collection of all elements of $\mathcal S$ which have only simple eigenvalues is dense in $\mathcal S$" for different sets $\mathcal S$, including: all quantum channels, the unital channels, the positive trace-preserving maps, all Lindbladians (GKSL-generators), and all time-dependent Markovian channels. Therefore any element from

Vefa Goksel, Giacomo Micheli

Let $q$ be an odd prime power. Let $f\in \mathbb{F}_q[x]$ be a polynomial having degree at least $2$, $a\in \mathbb{F}_q$, and denote by $f^n$ the $n$-th iteration of $f$. Let $\chi$ be the quadratic character of $\mathbb{F}_q$, and $\mathcal{O}_f(a)$ the forward orbit of $a$ under iteration by $f$. Suppose that the sequence $(\chi(f^n(a)))_{n\geq 1}$ is per

Logan Beaver

This extended abstracts presents a method to generate energy-optimal trajectories for multi-agent systems as a strategic-form game. Using recent results in optimal control, we demonstrate that an energy-optimal trajectory can be generated in milliseconds if the sequence of constraint activations is known a priori. Thus, rather than selecting an infinite-dime

Nadya Gurevich, David Kazhdan

Let $G$ be a split simply-connected group of type $D$ or $E$. The minimal automorphic representation $\Pi$ of $G(\mathbb A)$ admits a realization on a space of functions $\mathcal S(X(\mathbb A))$ for a variety $X$. In this paper we write explicitly an automorphic, i.e. $G(F)$-invariant, functional on $\mathcal S(X(\mathbb A)).$

Julian Parsert

Linear programming describes the problem of optimising a linear objective function over a set of constraints on its variables. In this paper we present a solver for linear programs implemented in the proof assistant Isabelle/HOL. This allows formally proving its soundness, termination, and other properties. We base these results on a previous formalisation o

Yan-Bo Lin, Gedas Bertasius

Traditional audio-visual methods rely on independent audio and visual backbones, which is costly and not scalable. In this work, we investigate using an audio-visual siamese network (AVSiam) for efficient and scalable audio-visual pretraining. Our framework uses a single shared vision transformer backbone to process audio and visual inputs, improving its par

Vaibhav Kalvakota, Aayush Verma

The dynamic of holography between anti-de Sitter space holography and de Sitter holography is a very fascinating comparison, which provides many key insights into what we expect from holography in general. In this Essay, we highlight this dynamic with three examples: first, when taking Wheeler-DeWitt states to the asymptotic boundary, the dual interpretation

Samir H. A. Mohammad, Haneen Farah, Arkady Zgonnikov

Understanding human behavior in overtaking scenarios is crucial for enhancing road safety in mixed traffic with automated vehicles (AVs). Computational models of behavior play a pivotal role in advancing this understanding, as they can provide insight into human behavior generalizing beyond empirical studies. However, existing studies and models of human ove

Andy Rundquist, Charles G. Durfee, Zenghu Chang, Catherine Herne

Phase-matched harmonic conversion of visible laser light into soft x-rays was demonstrated. The recently developed technique of guided-wave frequency conversion was used to upshift light from 800 nanometers to the range from 17 to 32 nanometers. This process increased the coherent x-ray output by factors of 10^2 to 10^3 compared to the non-phase-matched case

Abhijeet Borkar, Romana Grossová, Jiří Svoboda, Emily Moravec

Green Peas (GPs) are young, compact, star-forming dwarf galaxies, and local (z~0.3) analogues of the early galaxies (z>6) considered to be mainly responsible for the reionisation of the Universe. Recent X-ray observations of GPs have detected high excess emission which cannot be accounted for by star formation alone, and implies presence of an active galacti

Jiangdong Ai, Hong Liu, Zixiang Xu, Qiang Zhou

Given a graph $G$, denote by $h(G)$ the smallest size of a subset of $V(G)$ which intersects every maximum independent set of $G$. We prove that any graph $G$ without induced matching of size $t$ satisfies $h(G)\le \omega(G)^{3t-3+o(1)}$. This resolves a conjecture of Hajebi, Li and Spirkl (Hitting all maximum stable sets in $P_{5}$-free graphs, JCTB 2024).

Pierre-Michel Bousquet, Mickael Rouvier

The SdSv challenge Task 2 provided an opportunity to assess efficiency and robustness of modern text-independent speaker verification systems. But it also made it possible to test new approaches, capable of taking into account the main issues of this challenge (duration, language, ...). This paper describes the contributions of our laboratory to the speaker

Sangjae Bae, David Isele, Alireza Nakhaei, Peng Xu

This paper presents an online smooth-path lane-change control framework. We focus on dense traffic where inter-vehicle space gaps are narrow, and cooperation with surrounding drivers is essential to achieve the lane-change maneuver. We propose a two-stage control framework that harmonizes Model Predictive Control (MPC) with Generative Adversarial Networks (G

Chongjie Ye, Yinyu Nie, Jiahao Chang, Yuantao Chen

We present GauStudio, a novel modular framework for modeling 3D Gaussian Splatting (3DGS) to provide standardized, plug-and-play components for users to easily customize and implement a 3DGS pipeline. Supported by our framework, we propose a hybrid Gaussian representation with foreground and skyball background models. Experiments demonstrate this representat

Yucheng Shi, Qiaoyu Tan, Xuansheng Wu, Shaochen Zhong

Large Language Models (LLMs) have shown proficiency in question-answering tasks but often struggle to integrate real-time knowledge, leading to potentially outdated or inaccurate responses. This problem becomes even more challenging when dealing with multi-hop questions, since they require LLMs to update and integrate multiple knowledge pieces relevant to th

Martí Rosselló

The microstates of supersymmetric black holes in asymptotically flat four-dimensional spacetime are expected to be bosonic due to the spherical symmetry of their horizons. This implies that the index counting the difference between bosonic and fermionic black hole microstates must be positive, as conjectured by Sen in arXiv:1008.4209. We show that the conjec

Zhi Wang, Geelon So, Ramya Korlakai Vinayak

We study metric learning from preference comparisons under the ideal point model, in which a user prefers an item over another if it is closer to their latent ideal item. These items are embedded into $\mathbb{R}^d$ equipped with an unknown Mahalanobis distance shared across users. While recent work shows that it is possible to simultaneously recover the met

Noah L. Samuelson, Liam A. Cohen, Will Wang, Simon Blanch

Anyons are particles with fractional exchange statistics that emerge as elementary excitations of fractional quantum Hall phases. Experimentally, their exchange statistics can be measured in the edge-state Fabry-P\'erot interferometer. In these devices, the presence of $N_{qp}$ localized anyons in the bulk contributes a phase $N_{qp}\theta_a$ to the interfer

Huai-Dong Cao, Junming Xie

This is a sequel to our paper [24], in which we investigated the geometry of 4-dimensional gradient shrinking Ricci solitons with half positive (nonnegative) isotropic curvature. In this paper, we mainly focus on 4-dimensional gradient steady Ricci solitons with nonnegative isotropic curvature (WPIC) or half nonnegative isotropic curvature (half WPIC). In pa

Orphée Collin

This article completes [G. Giacomin, R. Greenblatt, ALEA 2022] by identifying explicitly the leading coefficient in the asymptotic development of the free energy density of the centered Random Field Ising Chain as the spin-spin interaction of the chain goes to infinity, under general assumptions on the disorder law.

Anqi Mao, Mehryar Mohri, Yutao Zhong

We present a detailed study of top-$k$ classification, the task of predicting the $k$ most probable classes for an input, extending beyond single-class prediction. We demonstrate that several prevalent surrogate loss functions in multi-class classification, such as comp-sum and constrained losses, are supported by $H$-consistency bounds with respect to the t

Daniel Koch, Aneta Koseska

Many natural, living and engineered systems display oscillations that are characterized by multiple timescales. Typically, such systems are described as slow-fast systems, where the slow dynamics result from a hyperbolic slow manifold that guides the movement of the system trajectories. Recently, we have provided an alternative description in which the slow

Niccolò Tonicello, Guido Lodato, Matthias Ihme

The present work focuses on the generalisation of the Spectral Difference (SD) scheme to the reduced Baer-Nunziato system known as five-equation model for the simulation of two immiscible compressible fluids. This five equation model is considered with the additional Allen-Cahn regularisation to avoid both over-diffusion and over-thinning of the phase field

Zeren Chen, Zhelun Shi, Xiaoya Lu, Lehan He

Achieving generalizability in solving out-of-distribution tasks is one of the ultimate goals of learning robotic manipulation. Recent progress of Vision-Language Models (VLMs) has shown that VLM-based task planners can alleviate the difficulty of solving novel tasks, by decomposing the compounded tasks as a plan of sequentially executing primitive-level skil

Serge Cantat, Romain Dujardin

We confirm a conjecture of Friedland and Milnor: if two polynomial automorphisms f and g in Aut(C^2) with dynamical degree >1 are conjugate by some holomorphic diffeomorphism \phi of C^2, then \phi is a polynomial automorphism; thus, f and g are conjugate inside Aut(C^2). We also discuss a number of variations on this result.

Ole Hall, Anil Yaman

Generative Adversarial Networks (GANs) have shown great success in generating high quality images and are thus used as one of the main approaches to generate art images. However, usually the image generation process involves sampling from the latent space of the learned art representations, allowing little control over the output. In this work, we first empl

Mattia Galeotti

In their celebrated paper of 1976, Rothschild and Stein prove a lifting procedure that locally reduces to a free nilpotent Lie algebra any family of smooth vector fields $X_1,\dots,X_q$, over a manifold $M$. Then, a large class of differential operators can be lifted, and fundamental solutions on the lifted space can be re-projected to fundamental solutions

David Damanik, Tal Malinovitch, Giorgio Young

In this article, we review some notions of ballistic transport from the mathematics and physics literature, describe their basic interrelations, and contrast them with other commonly studied notions of wave packet spread.

Fabian Jakubczyk, Armando Consiglio, Domenico Di Sante, Ronny Thomale

The discovery of superconductivity in infinite-layer nickelates has ignited stark interest within the scientific community, particularly regarding its likely unconventional origin. Conflicting magnetotransport measurements report either isotropic or anisotropic suppression of superconductivity in an external magnetic field, with distinct implications for the

Guido Cavraro, Joshua Comden, Andrey Bernstein

Energy prices and net power injection limitations regulate the operations in distribution grids and typically ensure that operational constraints are met. Nevertheless, unexpected or prolonged abnormal events could undermine the grid's functioning. During contingencies, customers could contribute effectively to sustaining the network by providing services. T

Philip D. Mannheim

Through use of the Pauli-Villars regulator procedure we construct a second- plus fourth-order-derivative theory of gravity that serves as an ultraviolet completion of standard second-order-derivative quantum Einstein gravity that is ghost-free, unitary and power counting renormalizable.

Xiaowei Song, Jv Zheng, Shiran Yuan, Huan-ang Gao

In this paper, we present a Scale-adaptive method for Anti-aliasing Gaussian Splatting (SA-GS). While the state-of-the-art method Mip-Splatting needs modifying the training procedure of Gaussian splatting, our method functions at test-time and is training-free. Specifically, SA-GS can be applied to any pretrained Gaussian splatting field as a plugin to signi

A. M. Rebello, L. M. Ruela, G. Moreto, N. Y. Klein

This paper explores methods to enhance the reproducibility of Josephson junctions, crucial elements in superconducting quantum technologies, when employing the Dolan technique in 30 kV e-beam processes. The study explores the influence of dose distribution along the bridge area on reproducibility, addressing challenges related to fabrication sensitivity. Exp

Alexios Liakos, Alceste Z. Bonanos, Emmanouil M. Xilouris, Detlef Koschny

We present results of the NELIOTA campaign for lunar impact flashes observed with the 1.2 m Kryoneri telescope. From August 2019 to August 2023, we report 113 validated and 70 suspected flashes. For the validated flashes, we calculate the physical parameters of the corresponding projectiles, the temperatures developed during the impacts, and the expected cra

Dmitrii Zhemchuzhnikov, Sergei Grudinin

Effective recognition of spatial patterns and learning their hierarchy is crucial in modern spatial data analysis. Volumetric data applications seek techniques ensuring invariance not only to shifts but also to pattern rotations. While traditional methods can readily achieve translational invariance, rotational invariance possesses multiple challenges and re

Evan Matthews, Nicolas Prate

Given a set of ordered pixel data in the form of an image, our goal is to perform upsampling on the data such that: the resulting resolution is improved by some factor, the final result passes the human test, having added new, believable, and realistic information and detail to the image, the time complexity for upscaling is relatively close to that of lossy

Yoshitaka Hatta, Feng Yuan

We discuss the angular dependence of the recently proposed transverse momentum dependent quark and gluon diffractive parton distributions at small-$x$. We introduce the difractive versions of the Sivers function and the elliptic gluon Wigner distribution and evaluate them in simple models with gluon saturation and study their geometric scaling properties. We

H. García-Compeán, C. Ramos

A generalized Kerr-Schild ansatz for bigravity, already considered in the literature, which leads to linear interactions between the metrics is used to study the bigravity equations in the context of the double copy. By contracting the resulting spin-2 field bigravity equations of motion using Killing vector fields, as is usually carried out in general relat

Avinash Ummadisingu, Jongkeum Choi, Koki Yamane, Shimpei Masuda

Acquiring accurate depth information of transparent objects using off-the-shelf RGB-D cameras is a well-known challenge in Computer Vision and Robotics. Depth estimation/completion methods are typically employed and trained on datasets with quality depth labels acquired from either simulation, additional sensors or specialized data collection setups and know

Marta Spreafico

In longitudinal observational studies, marginal structural models (MSMs) are a class of causal models used to analyse the effect of an exposure on the (time-to-event) outcome of interest, while accounting for exposure-affected time-dependent confounding. In the applied literature, inverse probability of treatment weighting (IPTW) has been widely adopted to e

Drew T. Nguyen, Reese Pathak, Anastasios N. Angelopoulos, Stephen Bates

Decision-making pipelines are generally characterized by tradeoffs among various risk functions. It is often desirable to manage such tradeoffs in a data-adaptive manner. As we demonstrate, if this is done naively, state-of-the art uncertainty quantification methods can lead to significant violations of putative risk guarantees. To address this issue, we dev

Luis A. Anchordoqui, Ignatios Antoniadis, Dieter Lust

In the last two years the dark dimension scenario has emerged as focal point of many research interests. In particular, it functions as a stepping stone to address the cosmological hierarchy problem and provides a colosseum for dark matter contenders. We reexamine the possibility that primordial black holes (PBHs) perceiving the dark dimension could constitu

Chengzu Li, Chao Zhang, Simone Teufel, Rama Sanand Doddipatla

We are interested in the generation of navigation instructions, either in their own right or as training material for robotic navigation task. In this paper, we propose a new approach to navigation instruction generation by framing the problem as an image captioning task using semantic maps as visual input. Conventional approaches employ a sequence of panora

Mattias Hallen, Matteo Iovino, Shiva Sander-Tavallaey, Christian Smith

In industrial applications Finite State Machines (FSMs) are often used to implement decision making policies for autonomous systems. In recent years, the use of Behavior Trees (BT) as an alternative policy representation has gained considerable attention. The benefits of using BTs over FSMs are modularity and reusability, enabling a system that is easy to ex

Amogh Anakru, Zhen Bi

Systems with dipole moment conservation have been of recent interest, as they realize both novel quantum dynamics and exotic ground state phases. In this work, we study some generic properties of 1-D and 2-D dipole-conserving fermionic models at integer fillings. We find that a dipolar symmetry-breaking phase can result in a mean-field band insulator whose t

Zhicai Wang, Longhui Wei, Tan Wang, Heyu Chen

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. However, the effective integration of T2I models into fundamental image classification tasks remains an open question. A prevalent strategy to bolster image classification performance

Giorgio Ottaviani

This is a revised version of the lecture notes prepared for the workshop on "Plane quartics, Scorza map and related topics", held in Catania, January 19-21, 2016. The last section contains eight Macaulay2 scripts on theta characteristics and the Scorza map, with a tutorial. The first sections give an introduction to these scripts. The tutorial contains a lis

Stephen P. Martin

The lightest supersymmetric particles could be higgsinos that have a small mixing with gauginos. If the lightest higgsino-like state makes up some or all of the dark matter with a thermal freezeout density, then its mass must be between about 100 and 1150 GeV, and dark matter searches put bounds on the amount of gaugino contamination that it can have. Motiva

Fábris Kossoski, Martial Boggio-Pasqua, Pierre-François Loos, Denis Jacquemin

In the realm of photochemistry, the significance of double excitations (also known as doubly-excited states), where two electrons are concurrently elevated to higher energy levels, lies in their involvement in key electronic transitions essential in light-induced chemical reactions as well as their challenging nature from the computational theoretical chemis

Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic

Image captioning has been shown as an effective pretraining method similar to contrastive pretraining. However, the incorporation of location-aware information into visual pretraining remains an area with limited research. In this paper, we propose a simple visual pretraining method with location-aware captioners (LocCa). LocCa uses a simple image captioner

Johann Haselberger, Bonifaz Stuhr, Bernhard Schick, Steffen Müller

There is evidence that the driving style of an autonomous vehicle is important to increase the acceptance and trust of the passengers. The driving situation has been found to have a significant influence on human driving behavior. However, current driving style models only partially incorporate driving environment information, limiting the alignment between

Antonia Susnjar, Antonia Kaiser, Dunja Simicic, Gianna Nossa

A recent expert consensus found that non-standard reporting in MRS studies led to poor reproducibility. In order to address this, MRSinMRS guidelines were introduced; however, because of the disparate nomenclature and data formats, adoption has been slow. To get around this problem, REMY, a toolbox that supports major vendor formats, was created. By efficien

Aimon Rahman, Malsha V. Perera, Vishal M. Patel

Building on the momentum of image generation diffusion models, there is an increasing interest in video-based diffusion models. However, video generation poses greater challenges due to its higher-dimensional nature, the scarcity of training data, and the complex spatiotemporal relationships involved. Image generation models, due to their extensive data requ

Seophine Stanislaus

Recent LHCb measurements of the CKM angle $\gamma$ in ADS and GLW-like decays are presented. One measurement considers $B^{0}\to D K^{*0}(892)$ decays with two- and four-body $D$-decay final states and another considers $B^{\pm}\to D h^{\pm}$ decays with $D \to K\pi\pi\pi$ final states. The former supersedes a previous LHCb measurement and was presented for

Pingcheng Dong, Yonghao Tan, Dong Zhang, Tianwei Ni

Non-linear functions are prevalent in Transformers and their lightweight variants, incurring substantial and frequently underestimated hardware costs. Previous state-of-the-art works optimize these operations by piece-wise linear approximation and store the parameters in look-up tables (LUT), but most of them require unfriendly high-precision arithmetics suc

Emanuelly Silva, Ubaldo Zúñiga-Bolaño, Rafael C. Nunes, Eleonora Di Valentino

Understanding the behavior of the matter power spectrum on non-linear scales beyond the $\Lambda$CDM model is crucial for accurately predicting the large-scale structure (LSS) of the Universe in non-standard cosmologies. In this work, we present an analysis of the non-linear matter power spectrum within the framework of interacting dark energy-dark matter co

Bu Jin, Yupeng Zheng, Pengfei Li, Weize Li

3D dense captioning stands as a cornerstone in achieving a comprehensive understanding of 3D scenes through natural language. It has recently witnessed remarkable achievements, particularly in indoor settings. However, the exploration of 3D dense captioning in outdoor scenes is hindered by two major challenges: 1) the domain gap between indoor and outdoor sc

Donghyun Kim, Byeongho Heo, Dongyoon Han

This paper revives Densely Connected Convolutional Networks (DenseNets) and reveals the underrated effectiveness over predominant ResNet-style architectures. We believe DenseNets' potential was overlooked due to untouched training methods and traditional design elements not fully revealing their capabilities. Our pilot study shows dense connections through c

Tim Johnston, Nikolaos Makras, Sotirios Sabanis

Recent advances in stochastic optimization have yielded the interacting particle Langevin algorithm (IPLA), which leverages the notion of interacting particle systems (IPS) to efficiently sample from approximate posterior densities. This becomes particularly crucial in relation to the framework of Expectation-Maximization (EM), where the E-step is computatio