May 2023 arXiv papers — page 186

Rhett Hull, Ki Myung Brian Lee, Jennifer Wakulicz, Chanyeol Yoo

We consider the coordinated escort problem, where a decentralised team of supporting robots implicitly assist the mission of higher-value principal robots. The defining challenge is how to evaluate the effect of supporting robots' actions on the principal robots' mission. To capture this effect, we define two novel auxiliary reward functions for supp

Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam

Sharding a large machine learning model across multiple devices to balance the costs is important in distributed training. This is challenging because partitioning is NP-hard, and estimating the costs accurately and efficiently is difficult. In this work, we explore a "pre-train, and search" paradigm for efficient sharding. The idea is to pre-train a

Xinlu Xu, Thamine N. Dalichaouch, Jiaxin Liu, Qianyi Ma

The quality of electron beams produced from plasma-based accelerators, i.e., normalized brightness and energy spread, has made transformative progress in the past several decades in both simulation and experiment. Recently, full-scale particle-in-cell (PIC) simulations have shown that electron beams with unprecedented brightness ($10^{20}\sim10^{21}~\mathrm{

Seunghwan Baek, Hayoung Choi, Seonguk Yoo

In this paper we provide a way to construct new moment sequences from a given moment sequence. An operator based on multivariate positive polynomials is applied to get the new moment sequences. A class of new sequences is corresponding to a unique symmetric polynomial; if this polynomial is positive, then the new sequence becomes again a moment sequence. We

Giulia Martos, Jorge Meléndez, Anne Rathsam, Gabriela Carvalho Silva

The lithium present in the photospheres of solar-type stars is transported to the inner parts by convection, reaching regions even somewhat below the convection zone, by non-standard transport mechanisms. In stars with deeper convective zones, this element can reach regions with temperatures sufficient enough to be destroyed, implying in a lower Li content.

Xuanang Chen, Ben He, Zheng Ye, Le Sun

Adversarial attacks have gained traction in order to identify potential vulnerabilities in neural ranking models (NRMs), but current attack methods often introduce grammatical errors, nonsensical expressions, or incoherent text fragments, which can be easily detected. Additionally, current methods rely heavily on the use of a well-imitated surrogate NRM to g

Tsachy Weissman

Inspired by recent work on compression with and for young humans, the success of transform-based approaches to information processing, and the rise of powerful language-based AI, we propose \emph{textual transform coding}. It shares some of its key properties with traditional transform-based coding underlying much of our current multimedia compression techno

Bhawesh Mishra

Let $q$ be an odd prime and $B = \{b_{j}\}_{j=1}^{l}$ be a finite set of nonzero integers that does not contain a perfect $q^{th}$ power. We show that $B$ has a $q^{th}$ power modulo every prime $p \neq q$ and not dividing $\prod_{b\in B} b$ if and only if $B$ corrresponds to a linear hyperplane covering of $\mathbb{F}_{q}^{k}$. Here, $k$ is the number of di

Changrong Xiao, Sean Xin Xu, Kunpeng Zhang

Image captioning, an important vision-language task, often requires a tremendous number of finely labeled image-caption pairs for learning the underlying alignment between images and texts. In this paper, we proposed a multimodal data augmentation method, leveraging a recent text-to-image model called Stable Diffusion, to expand the training set via high-qua

Jun Shi, Long-Cheng Gui, Jian Liang, Guoming Liu

We implement a convolutional neural network to study the $Σ$ hyperons using experimental data of the $K^-p\toπ^0Λ$ reaction. The averaged accuracy of the NN models in resolving resonances on the test data sets is ${\rm 98.5\%}$, ${\rm 94.8\%}$ and ${\rm 82.5\%}$ for one-, two- and three-additional-resonance case. We find that the three most significant reson

Kendra Shrestha, James Van Strien, David F Fletcher, Kiao Inthavong

Spray atomization process involves complex multi-phase phenomena. Abundant literature and validation of spray modelling for industrial applications like fuel injection in internal combustion and turbine jet engines are available. However, only a handful of studies, primarily limited to discrete phase modelling, of low-pressure applications, such as nasal spr

Antony Morales-Cervantes, Oscar Lobato-Nostroza, Gerardo Marx Chávez-Campos, Yvo Marcelo Chiaradia-Masselli

Weather is one of the main problems in implementing forecasts for photovoltaic panel systems. Since it is the main generator of disturbances and interruptions in electrical energy. It is necessary to choose a reliable forecasting model for better energy use. A measurement prototype was constructed in this work, which collects in-situ voltage and current meas

S. I. Krasheninnikov, R. D. Smirnov

It is shown that stationary non-spherical dust grain immersed into stationary non-magnetized plasma can experience a force caused by the grain-plasma interactions.

Daniel Erkensten, Samuel Brem, Raul Perea-Causin, Joakim Hagel

Transition-metal dichalcogenide bilayers exhibit a rich exciton landscape including layer-hybridized excitons, i.e. excitons which are of partly intra- and interlayer nature. In this work, we study hybrid exciton-exciton interactions in naturally stacked WSe$_2$ homobilayers. In these materials, the exciton landscape is electrically tunable such that the low

Junjie Ye, Jilin Zhao

In this study, we explore the potential of using a straightforward neural network inspired by the retina model to efficiently restore low-light images. The retina model imitates the neurophysiological principles and dynamics of various optical neurons. Our proposed neural network model reduces the computational overhead compared to traditional signal-process

Kenny Chen, Ryan Nemiroff, Brett T. Lopez

This paper presents Direct LiDAR-Inertial Odometry and Mapping (DLIOM), a robust SLAM algorithm with an explicit focus on computational efficiency, operational reliability, and real-world efficacy. DLIOM contains several key algorithmic innovations in both the front-end and back-end subsystems to design a resilient LiDAR-inertial architecture that is percept

Zachary Hafen, Sameer, Cameron Hummels, Jane Charlton

In the Halo21 absorption modeling challenge we generated synthetic absorption spectra of the circumgalactic medium (CGM), and attempted to estimate the metallicity, temperature, and density (Z, T, and nH) of the underlying gas using observational methods. We iteratively generated and analyzed three increasingly-complex data samples: ion column densities of i

Zeng Wang, Lilas Alrahis, Dominik Sisejkovic, Ozgur Sinanoglu

Logic locking protects the integrity of hardware designs throughout the integrated circuit supply chain. However, recent machine learning (ML)-based attacks have challenged its fundamental security, initiating the requirement for the design of learning-resilient locking policies. A promising ML-resilient locking mechanism hides within multiplexer-based locki

Zhen Huang, Bodhisattva Sen

The sign test (Arbuthnott, 1710) and the Wilcoxon signed-rank test (Wilcoxon, 1945) are among the first examples of a nonparametric test. These procedures -- based on signs, (absolute) ranks and signed-ranks -- yield distribution-free tests for symmetry in one-dimension. In this paper we propose a novel and unified framework for distribution-free testing of

Jay Lal, Aditya Mitkari, Mahesh Bhosale, David Doermann

Data extraction from line-chart images is an essential component of the automated document understanding process, as line charts are a ubiquitous data visualization format. However, the amount of visual and structural variations in multi-line graphs makes them particularly challenging for automated parsing. Existing works, however, are not robust to all thes

Shentong Mo, Yapeng Tian

Segment Anything Model (SAM) has recently shown its powerful effectiveness in visual segmentation tasks. However, there is less exploration concerning how SAM works on audio-visual tasks, such as visual sound localization and segmentation. In this work, we propose a simple yet effective audio-visual localization and segmentation framework based on the Segmen

Melissa van Beekveld, Philip Grace, Anders Kvellestad, Adam Leinweber

Searches for beyond-Standard Model physics scenarios, such as supersymmetry (SUSY), at the Large Hadron Collider (LHC) are frequently optimised on simplified models. After assuming particular particle production and decay processes, analyses are optimised by tuning event selections on benchmark models generated in 2D planes of parameters, with all other para

Bishnu Paudel, Chris Pinner

We obtain a complete description of the integer group determinants for the non-abelian groups of order 18.

Suryansh Upadhyay, Swaroop Ghosh

Security and reliability are primary concerns in any computing paradigm including quantum computing. Currently users can access quantum computers through a cloud based platform where they can run their programs on a suite of quantum computers. As the quantum computing ecosystem grows in popularity and utility it is reasonable to expect that more companies in

Mohamed Abdelmeguid, Chunhui Zhao, Esref Yalcinkaya, George Gazetas

The 2023 M7.8 Kahramanmaraş/Pazarcik earthquake was larger and more destructive than what had been expected. Here we analyzed near-field seismic records and developed a dynamic rupture model that reconciles different currently conflicting inversion results and reveals spatially non-uniform propagation speeds in this earthquake, with predominantly supershear

Aaron Szasz, Ed Younis, Wibe de Jong

Near-term quantum computers have significant error rates and short coherence times, so compilation of circuits to be as short as possible is essential. Two types of compilation problems are typically considered: circuits to prepare a given state from a fixed input state, called "state preparation"; and circuits to implement a given unitary operation,

Nikolay Martynchuk, San Vũ Ngoc

This paper presents a complete symplectic classification of $A_k$ Hamiltonians on $\mathbb R^2$, in the analytic and smooth categories. Precisely, consider the pair $(H, ω)$ consisting of a Hamiltonian and a symplectic structure on $\mathbb R^2$ such that $H$ has an $A_{k-1}$ singularity at the origin with $k\geq 2$. We classify such pairs near the origin, u

Baike She, Tyler Hanks, James Fairbanks, Matthew Hale

Composing systems is a fundamental concept in modern control systems, yet it remains challenging to formally analyze how controllers designed for individual subsystems can differ from controllers designed for the composition of those subsystems. To address this challenge, we propose a novel approach to composing control systems based on resource sharing mach

Spencer Secord

We present a proof that all straight domains are locally divided$\unicode{x2014}$thereby answering two open problems posed by Dobbs and Picavet, which appeared in the survey "Open Problems in Commutative Ring Theory" written by Cahen, Fontana, Frisch, and Glaz. In fact, we are able to prove a stronger result: a prime ideal of a domain is straight if

Huma Jamil, Yajing Liu, Turgay Caglar, Christina M. Cole

Researchers typically investigate neural network representations by examining activation outputs for one or more layers of a network. Here, we investigate the potential for ReLU activation patterns (encoded as bit vectors) to aid in understanding and interpreting the behavior of neural networks. We utilize Representational Dissimilarity Matrices (RDMs) to in

Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan, Alejandro Ribeiro

Graph convolutional networks (GCN) leverage topology-driven graph convolutional operations to combine information across the graph for inference tasks. In our recent work, we have studied GCNs with covariance matrices as graphs in the form of coVariance neural networks (VNNs) that draw similarities with traditional PCA-driven data analysis approaches while o

Juan Schmidt, Guilherme Gorgen-Lesseux, Raquel A. Ribeiro, Sergey L. Bud'ko

Although SrNi$_2$P$_2$ adopts the common ThCr$_2$Si$_2$ structure for $T\geq 325$ K, being in an uncollapsed tetragonal state, on cooling below 325 K it adopts a one-third collapsed orthorhombic phase where one out of every three P rows bond across the Sr layers. On the other hand, SrCo$_2$P$_2$ only exhibits the uncollapsed ThCr$_2$Si$_2$ structure from roo

Manish Sihag, Ze Shi Li, Amanda Dash, Nowshin Nawar Arony

The increasing importance of videos as a medium for engagement, communication, and content creation makes them critical for organizations to consider for user feedback. However, sifting through vast amounts of video content on social media platforms to extract requirements-relevant feedback is challenging. This study delves into the potential of TikTok and Y

Hakim Atek, Iryna Chemerynska, Bingjie Wang, Lukas Furtak

We present the results of a search for high-redshift ($z>9$) galaxy candidates in the JWST UNCOVER survey, using deep NIRCam and NIRISS imaging in 7 bands over $\sim45$ arcmin$^2$ and ancillary HST observations. The NIRCam observations reach a $5-σ$ limiting magnitude of $\sim 29.2$ AB. The identification of high$-z$ candidates relies on a combination of a d

Natalia Maślany

We extend the existing results on surjective isometries of unit spheres in the Tsirelson space $T\left[\frac{1}{2}, S_1\right]$ to the class $T[θ,S_α]$ for any integer $θ^{-1} \geq 2$ and $1 \leqslant α< ω_1$, where $S_α$ denotes the Schreier family of order $α$. This positively answers Tingley&#39;s problem for these spaces, which asks whether every surject

A. R. Cadore, B. L. T. Rosa, I. Paradisanos, S. Mignuzzi

Layered material heterostructures (LMHs) can be used to fabricate electroluminescent devices operating in the visible spectral region. A major advantage of LMH-light emitting diodes (LEDs) is that electroluminescence (EL) emission can be tuned across that of different exciton complexes (e.g. biexcitons, trions, quintons) by controlling the charge density. Ho

Sunjae Kwon, Rishabh Garodia, Minhwa Lee, Zhichao Yang

Visual Word Sense Disambiguation (VWSD) is a task to find the image that most accurately depicts the correct sense of the target word for the given context. Previously, image-text matching models often suffered from recognizing polysemous words. This paper introduces an unsupervised VWSD approach that uses gloss information of an external lexical knowledge-b

Haozhe Yang, Maider Ormaza, Zhendong Chi, Eoin Dolan

Graphene is a light material for long-distance spin transport due to its low spin-orbit coupling, which at the same time is the main drawback to exhibit a sizeable spin Hall effect. Decoration by light atoms has been predicted to enhance the spin Hall angle in graphene while retaining a long spin diffusion length. Here, we combine a light metal oxide (oxidiz

Hadi Hosseini, Aghaheybat Mammadov, Tomasz Wąs

We study the fair allocation of mixtures of indivisible goods and chores under lexicographic preferences$\unicode{x2014}$a subdomain of additive preferences. A prominent fairness notion for allocating indivisible items is envy-freeness up to any item (EFX). Yet, its existence and computation has remained a notable open problem. By identifying a class of inst

S. Afach, D. Aybas Tumturk, H. Bekker, B. C. Buchler

Numerous observations suggest that there exist undiscovered beyond-the-Standard-Model particles and fields. Because of their unknown nature, these exotic particles and fields could interact with Standard Model particles in many different ways and assume a variety of possible configurations. Here we present an overview of the Global Network of Optical Magneto

Ohr Kadrawi, Vadim E. Levit

An independent set in a graph is a collection of vertices that are not adjacent to each other. The cardinality of the largest independent set in $G$ is represented by $α(G)$. The independence polynomial of a graph $G = (V, E)$ was introduced by Gutman and Harary in 1983 and is defined as \[ I(G;x) = \sum_{k=0}^{α(G)}{s_k}x^{k}={s_0}+{s_1}x+{s_2}x^{2}+...+{s_

Yukiya Saito, Iris Dillmann, Reiner Kruecken, Matthew R. Mumpower

Developments in the description of the masses of atomic nuclei have led to various nuclear mass models that provide predictions for masses across the whole chart of nuclides. These mass models play an important role in understanding the synthesis of heavy elements in the rapid neutron capture ($r$-) process. However, it is still a challenging task to estimat

Saurabh Pujar, Luca Buratti, Xiaojie Guo, Nicolas Dupuis

The recent improvement in code generation capabilities due to the use of large language models has mainly benefited general purpose programming languages. Domain specific languages, such as the ones used for IT Automation, have received far less attention, despite involving many active developers and being an essential component of modern cloud platforms. Th

Michael Psenka, Druv Pai, Vishal Raman, Shankar Sastry

This work proposes an algorithm for explicitly constructing a pair of neural networks that linearize and reconstruct an embedded submanifold, from finite samples of this manifold. Our such-generated neural networks, called Flattening Networks (FlatNet), are theoretically interpretable, computationally feasible at scale, and generalize well to test data, a ba

Robert Mieth, Juan M. Morales, H. Vincent Poor

With the ongoing investment in data collection and communication technology in power systems, data-driven optimization has been established as a powerful tool for system operators to handle stochastic system states caused by weather- and behavior-dependent resources. However, most methods are ignorant to data quality, which may differ based on measurement an

Sylvie Corteel, Frederick Huang, Christian Krattenthaler

Di Francesco introduced Aztec triangles as combinatorial objects for which their domino tilings are equinumerous with certain sets of configurations of the twenty-vertex model that are the main focus of his article. We generalize Di Francesco&#39;s construction of Aztec triangles. While we do not know whether there is again a correspondence with configuratio

Hossam O. Ahmed

To keep up with today&#39;s dense metropolitan areas and their accompanying traffic problems, a growing number of towns are looking for more advanced and swift urban taxi drones. The safety parameters that must be taken into consideration may be the most important element in the widespread use of such technology. Most recent aviation mishaps have happened du

Hadrien Vignaud, David Perconte, Wenmin Yang, Bilal Kousar

Hybridizing superconductivity with the quantum Hall (QH) effects has major potential for designing novel circuits capable of inducing and manipulating non-Abelian states for topological quantum computation. However, despite recent experimental progress towards this hybridization, concrete evidence for a chiral QH Josephson junction -- the elemental building

Ahmet-Serdar Karakaya, Ioan-Alexandru Stef, Konstantin Köhler, Julian Heinovski

Increasing the modal share of bicycle traffic to reduce carbon emissions, reduce urban car traffic, and to improve the health of citizens, requires a shift away from car-centric city planning. For this, traffic planners often rely on simulation tools such as SUMO which allow them to study the effects of construction changes before implementing them. Similarl

Jaehyeon Ryu

In this paper, we study the almost everywhere convergence problem for the Bochner--Riesz means $S_t^\delta f$ for $f\in L^p(\mathbb R^d)$ in the subcritical range \[ 0\le \delta < \delta(d,p):=d\Big(\frac12-\frac1p\Big)-\frac12, \qquad \frac{2d}{d-1}<p<\infty, \] where $d\ge 2$. In this regime, the operator need not be well defined for fixed $t>0$, even as a

Pasquale Cilibrizzi, Muhammad Junaid Arshad, Benedikt Tissot, Nguyen Tien Son

Spin-active quantum emitters have emerged as a leading platform for quantum technologies. However, one of their major limitations is the large spread in optical emission frequencies, which typically extends over tens of GHz. Here, we investigate single V4+ vanadium centres in 4H-SiC, which feature telecom-wavelength emission and a coherent S=1/2 spin state.

Evangelos Kosinas

We revisit once more the problem of designing an oracle for answering connectivity queries in undirected graphs in the presence of vertex failures. Specifically, given an undirected graph $G$ with $n$ vertices and $m$ edges and an integer $d_{\star}\ll n$, the goal is to preprocess the graph in order to construct a data structure $\mathcal{D}$ such that, giv

Markus Bibinger, Michael Sonntag

We develop and investigate a test for jumps based on high-frequency observations of a fractional process with an additive jump component. The Hurst exponent of the fractional process is unknown. The asymptotic theory under infill asymptotics builds upon extreme value theory for weakly dependent, stationary time series and extends techniques for the semimarti

Tianle Li, Xueguang Ma, Alex Zhuang, Yu Gu

Question answering over knowledge bases is considered a difficult problem due to the challenge of generalizing to a wide variety of possible natural language questions. Additionally, the heterogeneity of knowledge base schema items between different knowledge bases often necessitates specialized training for different knowledge base question-answering (KBQA)

Monika Wolfmayr

This work presents the multiharmonic analysis and derivation of functional type a posteriori estimates of a distributed eddy current optimal control problem and its state equation in a time-periodic setting. The existence and uniqueness of the solution of a weak space-time variational formulation for the optimality system and the forward problem are proved b

Moucheng Xu, Yukun Zhou, Chen Jin, Marius de Groot

In this paper, we study pseudo-labelling. Pseudo-labelling employs raw inferences on unlabelled data as pseudo-labels for self-training. We elucidate the empirical successes of pseudo-labelling by establishing a link between this technique and the Expectation Maximisation algorithm. Through this, we realise that the original pseudo-labelling serves as an emp

Zakaria Jouini, Natalia Chepiga, Loic Herviou, Frédéric Mila

The properties of stable Luttinger liquid phases in models with a non-conserved number of particles are investigated. We study the Luttinger liquid phases in one-dimensional models of hard-core boson and spinless fermion chains where particles can be created and annihilated three by three on adjacent sites. We provide an intuitive and systematic method based

Tatjana Petek, Valery G. Romanovski

There are two ways to compute Poincaré-Dulac normal forms of systems of ODEs. Under the original approach used by Poincaré the normalizing transformation is explicitly computed. On each step, the normalizing procedure requires the substitution of a polynomial to a series. Under the other approach, a normal form is computed using Lie transformations. In this

Ariel Nikas, Hasan Ahmed, Veronika I. Zarnitsyna

Understanding waning of vaccine-induced protection is important for both immunology and public health. Population heterogeneities in underlying (pre-vaccination) susceptibility and vaccine response can cause measured vaccine effectiveness (mVE) to change over time even in the absence of pathogen evolution and any actual waning of immune responses. We use a m

Antonio Delgado, Adam Martin, Runqing Wang

Following a recent publication, in this paper we count the number of independent operators at arbitrary mass dimension in $N=1$ supersymmetric gauge theories and derive their field and derivative content. This work uses Hilbert series machinery and extends a technique from our previous work on handling integration by parts redundancies to vector superfields.

Haopeng Zhang, Xiao Liu, Jiawei Zhang

Extractive summarization aims to form a summary by directly extracting sentences from the source document. Existing works mostly formulate it as a sequence labeling problem by making individual sentence label predictions. This paper proposes DiffuSum, a novel paradigm for extractive summarization, by directly generating the desired summary sentence represent

Christian Kunz

Inspired by recent work arXiv:2301.11227 on massive ambitwistor strings this paper examines the spectrum of such models using oscillator expansions. The spectrum depends heavily on the constant related to the normal ordering of the zero mode operator ${L_0}$ of the Virasoro algebra. The supergravity model is investigated in more detail, and two anomaly-free

Sara Khatibi

In this paper, we extend the Standard Model (SM) scalar sector with scalar leptoquarks (LQ) as a portal to the dark sector to resolve some observational anomalies simultaneously. We introduce LQ coupling to scalar dark matter (DM) to suggest an exotic decay channel for the neutron into scalar DM and an SM anti-neutrino. If the branching ratio of this new neu

Tamás Baranyai

We present the foundations of a projective geometric theory of elasticity, as well as outline a few possible application possibilities. We give the description of the Cauchy stress and infinitesimal strain tensors compatible with coordinate description of projective geometry and derive their transformation rules under projective transformations. We identify

Josua Illian, Li Li

Nakajima&#39;s graded quiver varieties naturally appear in the study of bases of cluster algebras. One particular family of these varieties, namely the bipartite determinantal varieties, can be defined for any bipartite quiver and gives a vast generalization of classical determinantal varieties with broad applications to algebra, geometry, combinatorics, and

Michael Burnham

Stance detection is identifying expressed beliefs in a document. While researchers widely use sentiment analysis for this, recent research demonstrates that sentiment and stance are distinct. This paper advances text analysis methods by precisely defining stance detection and presenting three distinct approaches: supervised classification, natural language i

Thomas Van Riet, Gianluca Zoccarato

These lecture notes provide a pedagogical introduction, with exercises, to the techniques used in attempts to construct vacua with stabilised moduli in string theory. The reader is only assumed to have a basic knowledge of general relativity, geometry and field theory. We emphasize physical arguments and focus on the latest developments involving the Swampla

Ivan Katkov, Damir Gasymov, Alexei Kniazev, Joseph Gelfand

Stellar counter-rotation in disk galaxies directly relates to the complex phenomenon of the disk mass assembly believed to be driven by external processes, such as accretion and mergers. The detailed study of such systems makes it possible to reveal the source of external accretion and establish the details of this process. In this paper, we investigate the

Francisco Arana-Herrera, Aaron Calderon

By work of Jenkins and Strebel, given a Riemann surface X and a simple closed multi-curve $\alpha$ on it, there exists a unique quadratic differential q on X whose horizontal foliation is measure equivalent to $\alpha$. We study the distribution of the critical graphs of these differentials in the moduli space of metric ribbon graphs as the extremal length o

Michał P. Karpowicz, Gilbert Strang

This paper gives three formulas for the pseudoinverse of a matrix product $A = CR$. The first is sometimes correct, the second is always correct, and the third is almost never correct. But that third randomized pseudoinverse $A^+_r$ may be very useful when $A$ is a very large matrix. 1. $A^+ = R^+C^+$ when $A = CR$ and $C$ has independent columns and $R$ has

Yingji Zhang, Danilo S. Carvalho, André Freitas

Disentangled latent spaces usually have better semantic separability and geometrical properties, which leads to better interpretability and more controllable data generation. While this has been well investigated in Computer Vision, in tasks such as image disentanglement, in the NLP domain sentence disentanglement is still comparatively under-investigated. M

Ahmet-Serdar Karakaya, Leonard Thomas, Denis Koljada, David Bermbach

Cities worldwide are trying to increase the modal share of bicycle traffic to address traffic and carbon emission problems. Aside from safety, a key factor for this is the cycling comfort, including the surface quality of cycle paths. In this paper, we propose a novel edge-based crowdsensing method for analyzing the surface quality of bicycle paths using sma

Zhengxiang Shi, Aldo Lipani

Language models (LMs) trained on vast quantities of unlabelled data have greatly advanced the field of natural language processing (NLP). In this study, we re-visit the widely accepted notion in NLP that continued pre-training LMs on task-related texts improves the performance of fine-tuning (FT) in downstream tasks. Through experiments on eight single-sente

Wenchang Li, John P. Lalor, Yixing Chen, Vamsi K. Kanuri

Sentiment analysis is integral to understanding the voice of the customer and informing businesses' strategic decisions. Conventional sentiment analysis involves three separate tasks: aspect-category detection, aspect-category sentiment analysis, and rating prediction. However, independently tackling these tasks can overlook their interdependencies and often

Jianhui Gao, Clara-Lea Bonzel, Chuan Hong, Paul Varghese

$\textbf{Objective:}$ High-throughput phenotyping will accelerate the use of electronic health records (EHRs) for translational research. A critical roadblock is the extensive medical supervision required for phenotyping algorithm (PA) estimation and evaluation. To address this challenge, numerous weakly-supervised learning methods have been proposed. Howeve

Hui Yang, Ya-Hui Zhang

Significant efforts have been dedicated to achieving excitonic insulators. In this paper, we explore a new problem of doping excitons into a Mott insulator instead of a band insulator. Specifically, we start with a Mott insulator on a triangular moiré superlattice in a transition metal dichalcogenides (TMD) layer and inject excitons by either transferring pa

Francisco J. Peña, Clara Hübinger, Amir H. Payberah, Fernando Jaramillo

Deep learning and remote sensing techniques have significantly advanced water monitoring abilities; however, the need for annotated data remains a challenge. This is particularly problematic in wetland detection, where water extent varies over time and space, demanding multiple annotations for the same area. In this paper, we present DeepAqua, a self-supervi

Stefan Sandner, Miguel Escudero, Samuel J. Witte

The cosmic microwave background (CMB) has proven to be an invaluable tool for studying the properties and interactions of neutrinos, providing insight not only into the sum of neutrino masses but also the free streaming nature of neutrinos prior to recombination. The CMB is a particularly powerful probe of new eV-scale bosons interacting with neutrinos, as t

Vikramaditya Mondal, Sumanta Chakraborty

We evaluate the Lorentzian gravitational path integral in the presence of non-vanishing torsion with the application of the Picard-Lefschetz theory for minisuperspaces corresponding to a number of phenomenological bouncing cosmological models as well as for the inflationary paradigm. It turns out that the semi-classical wave function derived from the saddle

Jorge J. Martínez de Lejarza, Michele Grossi, Leandro Cieri, Germán Rodrigo

Monte Carlo integration is a widely used numerical method for approximating integrals, which is often computationally expensive. In recent years, quantum computing has shown promise for speeding up Monte Carlo integration, and several quantum algorithms have been proposed to achieve this goal. In this paper, we present an application of Quantum Machine Learn

Benoît Assi, Michael L. Wagman

We provide a formulation of potential non-relativistic quantum chromodynamics (pNRQCD) suitable for calculating binding energies and matrix elements of generic hadron and multi-hadron states made of heavy quarks in $SU(N_c)$ gauge theory using quantum Monte Carlo techniques. We compute masses of quarkonium and triply-heavy baryons in order to study the pertu

Nick Choksi, Eugene Chiang, Jeffrey Fung, Zhaohuan Zhu

The hunt is on for dozens of protoplanets hypothesised to reside in protoplanetary discs with imaged gaps. How bright these planets are, and what they will grow to become, depend on their accretion rates, which may be in the runaway regime. Using 3D global simulations we calculate maximum gas accretion rates for planet masses $M_{\rm p}$ from 1$\,M_{\oplus}$

Valentin Mauerhofer, Pratika Dayal

Recent observations with the James Webb Space Telescope are yielding tantalizing hints of an early population of massive, bright galaxies at $z > 10$, with Atacama Large Millimeter Array (ALMA) observations indicating significant dust masses as early as $z\sim 7$. To understand the implications of these observations, we use the DELPHI semi-analytic model tha

Salvatore Bottaro, Diego Redigolo

We reexamine the consequences of perturbative unitarity on dark matter freeze-out when both Sommerfeld enhancement and bound state formation affect dark matter annihilations. At leading order (LO) the annihilation cross-section is infrared dominated and the connection between the unitarity bound and the upper bound on the dark matter mass depends only on how

Gabriel-Dominique Marleau, Rolf Kuiper, William Béthune, Christoph Mordasini

Surveys have looked for H alpha emission from accreting gas giants but found very few objects. Analyses of the detections and non-detections have assumed that the entire gas flow feeding the planet is in radial free-fall. However, hydrodynamical simulations suggest that this is far from reality. We calculate the H alpha emission from multidimensional accreti

Arun Debray, Matthew Yu

When $R$ is one of the spectra $\mathit{ku}$, $\mathit{ko}$, $\mathit{tmf}$, $\mathit{MTSpin}^c$, $\mathit{MTSpin}$, or $\mathit{MTString}$, there is a standard approach to computing twisted $R$-homology groups of a space $X$ with the Adams spectral sequence, by using a change-of-rings isomorphism to simplify the $E_2$-page. This approach requires the assump

Ghazal Geshnizjani, Eric Ling, Jerome Quintin

Inflationary spacetimes have been argued to be past geodesically incomplete in many situations. However, whether the geodesic incompleteness implies the existence of an initial spacetime curvature singularity or whether the spacetime may be extended (potentially into another phase of the universe) is generally unknown. Both questions have important physical

Tom Peham, Nina Brandl, Richard Kueng, Robert Wille

Circuit synthesis is the task of decomposing a given logical functionality into a sequence of elementary gates. It is (depth-)optimal if it is impossible to achieve the desired functionality with even shorter circuits. Optimal synthesis is a central problem in both quantum and classical hardware design, but also plagued by complexity-theoretic obstacles. Mot

Selim C. Hotinli, Kyungjin Ahn

The motion of an observer in the rest frame of the cosmic 21-cm background induces an anisotropy in the observed background, even when the background is isotropic. The induced anisotropy includes a dipole and a quadrupole, in the order decreasing in amplitude. If observed, these multipole anisotropies can be used as additional probes of the spectral shape of

Reza Haghshenas, Eli Chertkov, Matthew DeCross, Thomas M. Gatterman

Although quantum mechanics underpins the microscopic behavior of all materials, its effects are often obscured at the macroscopic level by thermal fluctuations. A notable exception is a zero-temperature phase transition, where scaling laws emerge entirely due to quantum correlations over a diverging length scale. The accurate description of such transitions

George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros

Dataset Distillation aims to distill an entire dataset&#39;s knowledge into a few synthetic images. The idea is to synthesize a small number of synthetic data points that, when given to a learning algorithm as training data, result in a model approximating one trained on the original data. Despite recent progress in the field, existing dataset distillation m

Huang Huang, Antonio Loquercio, Ashish Kumar, Neerja Thakkar

For locomotion, is an arm on a legged robot a liability or an asset for locomotion? Biological systems evolved additional limbs beyond legs that facilitates postural control. This work shows how a manipulator can be an asset for legged locomotion at high speeds or under external perturbations, where the arm serves beyond manipulation. Since the system has 15

Luigi Castiglioni, Silvia Penati, Marcia Tenser, Diego Trancanelli

We continue our study of renormalization group (RG) flows on Wilson loop defects in ABJM theory, which we have initiated in arXiv:2211.16501. We generalize that analysis by including non-supersymmetric fixed points and RG trajectories. To this end, we first determine the ``ordinary&#34;, non-supersymmetric Wilson loops, which turn out to be two and to includ

Luya Wang

Given two closed contact three-manifolds, one can form their contact connected sum via the Weinstein one-handle attachment. We study how pseudo-holomorphic curves in the symplectization behave under this operation. As a result, we give a connected sum formula for embedded contact homology.

Junmo Kang, Wei Xu, Alan Ritter

Fine-tuning large models is highly effective, however, inference can be expensive and produces carbon emissions. Knowledge distillation has been shown to be a practical solution to reduce inference costs, but the distillation process itself requires significant computational resources. Rather than buying or renting GPUs to fine-tune, then distill a large mod

Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon

Text-to-image models (T2I) offer a new level of flexibility by allowing users to guide the creative process through natural language. However, personalizing these models to align with user-provided visual concepts remains a challenging problem. The task of T2I personalization poses multiple hard challenges, such as maintaining high visual fidelity while allo

Shengyu Huang, Zan Gojcic, Zian Wang, Francis Williams

We present Neural Fields for LiDAR (NFL), a method to optimise a neural field scene representation from LiDAR measurements, with the goal of synthesizing realistic LiDAR scans from novel viewpoints. NFL combines the rendering power of neural fields with a detailed, physically motivated model of the LiDAR sensing process, thus enabling it to accurately reprod

Diego B. Fonseca, Lucas L. A. Pereira, Anderson L. R. Barbosa

We investigate the orbital Hall effect through a mesoscopic device with momentum-space orbital texture that is connected to four semi-infinite terminals embedded in the Landauer-Büttiker configuration for quantum transport. We present analytical and numerical evidence that the orbital Hall current exhibits mesoscopic fluctuations, which can be interpreted in

Tong Wu, Ashwinee Panda, Jiachen T. Wang, Prateek Mittal

In-context learning (ICL) is an important capability of Large Language Models (LLMs), enabling these models to dynamically adapt based on specific, in-context exemplars, thereby improving accuracy and relevance. However, LLM&#39;s responses may leak the sensitive private information contained in in-context exemplars. To address this challenge, we propose Dif

Mathis Petrovich, Michael J. Black, Gül Varol

In this paper, we present TMR, a simple yet effective approach for text to 3D human motion retrieval. While previous work has only treated retrieval as a proxy evaluation metric, we tackle it as a standalone task. Our method extends the state-of-the-art text-to-motion synthesis model TEMOS, and incorporates a contrastive loss to better structure the cross-mo