May 2023 arXiv papers — page 134

Jamie Watson, Mohamed Sayed, Zawar Qureshi, Gabriel J. Brostow

For augmented reality (AR), it is important that virtual assets appear to `sit among' real world objects. The virtual element should variously occlude and be occluded by real matter, based on a plausible depth ordering. This occlusion should be consistent over time as the viewer's camera moves. Unfortunately, small mistakes in the estimated scene depth can r

Chaitanya Goswami, Amanda Merkley, Pulkit Grover

Bivariate Partial Information Decomposition (PID) describes how the mutual information between a random variable M and two random variables Y and Z is decomposed into unique, redundant, and synergistic terms. Recently, PID has shown promise as an emerging tool to understand biological systems and biases in machine learning. However, computing PID is a challe

Souvik Kundu, Kedar Damle

We demonstrate that the low temperature ($T$) properties of a class of anisotropic spin $S=1$ kagome (planar pyrochlore) antiferromagnets on a field-induced $\frac{1}{3}$-magnetization ($\frac{1}{2}$-magnetization) plateau are described by a model of fully-packed dimers and loops on the honeycomb (square) lattice, with a temperature-dependent relative fugaci

Dahun Kim, Anelia Angelova, Weicheng Kuo

We present Region-aware Open-vocabulary Vision Transformers (RO-ViT) - a contrastive image-text pretraining recipe to bridge the gap between image-level pretraining and open-vocabulary object detection. At the pretraining phase, we propose to randomly crop and resize regions of positional embeddings instead of using the whole image positional embeddings. Thi

V. Diana Rakotonirina, Marco Bragato, Guido Falk von Rudorff, O. Anatole von Lilienfeld

Data-hungry machine learning methods have become a new standard to efficiently navigate chemical compound space for molecular and materials design and discovery. Due to the severe scarcity and cost of high-quality experimental or synthetic simulated training data, however, data-acquisition costs can be considerable. Relying on reasonably accurate approximate

Cristian L. Cortes, Matthias Loipersberger, Robert M. Parrish, Sam Morley-Short

The efficient computation of observables beyond the total energy is a key challenge and opportunity for fault-tolerant quantum computing approaches in quantum chemistry. Here we consider the symmetry-adapted perturbation theory (SAPT) components of the interaction energy as a prototypical example of such an observable. We provide a guide for calculating this

Eloi Nicolau, Anselmo M. Marques, Jordi Mompart, Ricardo G. Dias

We study the topological properties of interacting and non-interacting bosons loaded in the orbital angular momentum states $l=1$ in a lattice of rings with alternating distances. At the single-particle level, the two circulation states within each site lead to two decoupled Su-Schrieffer-Heeger lattices with correlated topological phases. We characterize th

Sankar Das Sarma, Jay D. Sau, Tudor D. Stanescu

We consider theoretically the physics of bulk topological superconductivity accompanied by boundary non-Abelian Majorana zero modes in semiconductor-superconductor (SM-SC) hybrid systems consisting of finite wires in the presence of correlated disorder arising from random charged impurities. We find the system to manifest a highly complex behavior due to the

Gaurav Verma, Ryan A. Rossi, Christopher Tensmeyer, Jiuxiang Gu

Visual text evokes an image in a person's mind, while non-visual text fails to do so. A method to automatically detect visualness in text will enable text-to-image retrieval and generation models to augment text with relevant images. This is particularly challenging with long-form text as text-to-image generation and retrieval models are often triggered for

Siddhartha Banerjee, Kamesh Munagala, Yiheng Shen, Kangning Wang

A seller is pricing identical copies of a good to a stream of unit-demand buyers. Each buyer has a value on the good as his private information. The seller only knows the empirical value distribution of the buyer population and chooses the revenue-optimal price. We consider a widely studied third-degree price discrimination model where an information interme

Francois Meyer, Jan Buys

Subword segmenters like BPE operate as a preprocessing step in neural machine translation and other (conditional) language models. They are applied to datasets before training, so translation or text generation quality relies on the quality of segmentations. We propose a departure from this paradigm, called subword segmental machine translation (SSMT). SSMT

Haoyang Huang, Tianyi Tang, Dongdong Zhang, Wayne Xin Zhao

Large language models (LLMs) demonstrate impressive multilingual capability, but their performance varies substantially across different languages. In this work, we introduce a simple yet effective method, called cross-lingual-thought prompting (XLT), to systematically improve the multilingual capability of LLMs. Specifically, XLT is a generic template promp

Recep Altar Çiçeksiz, Zhihan Jin, Eero Räty, István Tomon

In 1993, Fishburn and Graham established the following qualitative extension of the classical Erd\H{o}s-Szekeres theorem. If $N$ is sufficiently large with respect to $n$, then any $N\times N$ real matrix contains an $n\times n$ submatrix in which every row and every column is monotone. We prove that the smallest such $N$ is at most $2^{n^{4+o(1)}}$, greatly

Xichen Liang, Kseniia M. Karnaukh, Lei Zhao, Serena Seshadri

Fast and programmable transport of liquid droplets on a solid substrate is desirable in microfluidic, thermal, biomedical, and energy devices. Past research has focused on designing substrates with asymmetric structures or gradient wettability where droplet behaviors are passively controlled, or by applying external electric, thermal, magnetic, or acoustic s

Junjie Zhang, Ruobing Xie, Yupeng Hou, Wayne Xin Zhao

In the past decades, recommender systems have attracted much attention in both research and industry communities, and a large number of studies have been devoted to developing effective recommendation models. Basically speaking, these models mainly learn the underlying user preference from historical behavior data, and then estimate the user-item matching re

Etam Benger, Shahab Asoodeh, Jun Chen

The information bottleneck (IB) method aims to find compressed representations of a variable $X$ that retain the most relevant information about a target variable $Y$. We show that for a wide family of distributions -- namely, when $Y$ is generated by $X$ through a Hamming channel, under mild conditions -- the optimal IB representations require an alphabet s

F. E. Garbuzov, Y. M. Beltukov

This paper presents a generalization of Murnaghan elastic material to viscoelastic behavior using the Green-Rivlin multiple-integral approach. In the linear limit, the model coincides with the generalized Maxwell model. To create a nonlinear generalization, all possible second-order corrections were included in the constitutive equations written in the inter

Antonino De Martino, Kamal Diki, Ali Guzmán Adán

The Fueter-Sce theorem provides a procedure to obtain axially monogenic functions, which are in the kernel of generalized Cauchy-Riemann operator in $ \mathbb{R}^{n+1}$. This result is obtained by using two operators. The first one is the slice operator, which extends holomorphic functions of one complex variable to slice monogenic functions in $ \mathbb{R}^

Manuel Hohmann

We study metric teleparallel geometries, which can either be defined through a Lorentzian metric and flat, metric-compatible affine connection, or a tetrad and a flat spin connection, which are invariant under the transitive action of a four-dimensional Lie group on their spatial equal-time hypersurfaces. There are three such group actions, and their corresp

Siddhartha Sarma, Rahul Shrestha, Rohit B. Chaurasiya

Recognising the limitations of various existing channel-estimation schemes for energy beamforming, we propose an energy-preserving indirect feedback-based approach for finding the optimal beamforming vector. Upon elaborating on the key ideas behind the proposed approach -- dynamics of the harvest-then-transmit protocol and the latency associated with the cha

Jens Marklof, Matthew Welsh

In the first paper of this series we established new upper bounds for multi-variable exponential sums associated with a quadratic form. The present study shows that if one adds a linear term in the exponent, the estimates can be further improved for almost all parameter values. Our results extend the bound for one-variable theta sums obtained by Fedotov and

Guilherme Dean Pelegrina, Miguel Couceiro, Leonardo Tomazeli Duarte

The use of machine learning models in decision support systems with high societal impact raised concerns about unfair (disparate) results for different groups of people. When evaluating such unfair decisions, one generally relies on predefined groups that are determined by a set of features that are considered sensitive. However, such an approach is subjecti

Juri Opitz

The Smatch metric is a popular method for evaluating graph distances, as is necessary, for instance, to assess the performance of semantic graph parsing systems. However, we observe some issues in the metric that jeopardize meaningful evaluation. E.g., opaque pre-processing choices can affect results, and current graph-alignment solvers do not provide us wit

Yuxun Guo, Xiangdong Ji, Yizhuang Liu, Jinghong Yang

There has been growing interest in the near-threshold production of heavy quarkonium which can access the gluonic structure in the nucleon. Previously we studied this process with quantum chromodynamics (QCD) and showed that it can be factorized with the gluon generalized parton distributions (GPDs) in the heavy quark limit. We further argued that the hadron

Zhou Feng

Intermediate dimensions were recently introduced by Falconer, Fraser, and Kempton [Math. Z., 296, (2020)] to interpolate between the Hausdorff and box-counting dimensions. In this paper, we show that for every subset $ E $ of the symbolic space, the intermediate dimensions of the projections of $ E $ under typical self-affine coding maps are constant and giv

Theodoros E. Kouloukas

We study vector quadrirational Yang-Baxter maps representing the momentum-energy transformation of two particles after elastic relativistic collisions. The collision maps admit Lax representations compatible with an r-matrix Poisson structure and correspond to integrable systems of quadrilateral lattice equations.

Wan Tong Lou, Halvard Sutterud, Gino Cassella, W. M. C. Foulkes

Understanding superfluidity remains a major goal of condensed matter physics. Here we tackle this challenge utilizing the recently developed Fermionic neural network (FermiNet) wave function Ansatz [D. Pfau et al., Phys. Rev. Res. 2, 033429 (2020).] for variational Monte Carlo calculations. We study the unitary Fermi gas, a system with strong, short-range, t

Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal

Recent studies have shown promising results on utilizing large pre-trained image-language models for video question answering. While these image-language models can efficiently bootstrap the representation learning of video-language models, they typically concatenate uniformly sampled video frames as visual inputs without explicit language-aware, temporal mo

Rasha Alshawi, Atriya Sen, Nathan S. Upham, Beckett Sterner

We describe a novel dataset for the automated recognition of named taxonomic and other entities relevant to the association of viruses with their hosts. We further describe some initial results using pre-trained models on the named-entity recognition (NER) task on this novel dataset. We propose that our dataset of manually annotated abstracts now offers a Go

Geovanny A. Rave-Franco, Celia Escamilla-Rivera

Teleparallel Gravity is a gauge theory where gravity is a manifestation of the torsion of space-time and its success relies on being a possible solution to some problems of General Relativity. In this essay we introduce the construction of the theory by defining its geometrical setup, and how we can build it as a gauge theory of translations locally invarian

Eshaan Nichani, Alex Damian, Jason D. Lee

One of the central questions in the theory of deep learning is to understand how neural networks learn hierarchical features. The ability of deep networks to extract salient features is crucial to both their outstanding generalization ability and the modern deep learning paradigm of pretraining and finetuneing. However, this feature learning process remains

Alexander Fengler, Alejandro Lancho, Krishna Narayanan, Yury Polyanskiy

In this work we demonstrate how a lack of synchronization can in fact be advantageous in the problem of random access. Specifically, we consider a multiple-access problem over a frame-asynchronous 2-user binary-input adder channel in the unsourced setup (2-UBAC). Previous work has shown that under perfect synchronization the per-user rates achievable with li

Ehsan Kamalloo, Nouha Dziri, Charles L. A. Clarke, Davood Rafiei

Lexical matching remains the de facto evaluation method for open-domain question answering (QA). Unfortunately, lexical matching fails completely when a plausible candidate answer does not appear in the list of gold answers, which is increasingly the case as we shift from extractive to generative models. The recent success of large language models (LLMs) for

Zhengbao Jiang, Frank F. Xu, Luyu Gao, Zhiqing Sun

Despite the remarkable ability of large language models (LMs) to comprehend and generate language, they have a tendency to hallucinate and create factually inaccurate output. Augmenting LMs by retrieving information from external knowledge resources is one promising solution. Most existing retrieval augmented LMs employ a retrieve-and-generate setup that onl

Dieter Spreen

Partiality is a natural phenomenon in computability that we cannot get around. So, the question is whether we can give the areas where partiality occurs, that is, where non-termination happens, more structure. In this paper we consider function classes which besides the total functions only contain finite functions whose domain of definition is an initial se

N. M. Chtchelkatchev, R. E. Ryltsev, M. V. Magnitskaya, S. M. Gorbunov

Boron phosphide (BP) is a (super)hard semiconductor constituted of light elements, which is promising for high demand applications at extreme conditions. The behavior of BP at high temperatures and pressures is of special interest but is also poorly understood because both experimental and conventional ab initio methods are restricted to studying refractory

Daniel N. Blaschke, Ta Duong, Michael J. Demkowicz

Transonic defect motion is of interest for high strain-rate plastic deformation as well as for crack propagation. Ever since Eshelby's 1949 prediction in the isotropic limit of a 'radiation-free' transonic velocity $v_\text{RF}=\sqrt{2}c_{\textrm{T}}$, where shock waves are absent, there has been speculation about the significance of radiation-free velocitie

Zilong Wang, Gideon Mohr, Klaus von Gleissenthall, Jan Reineke

Leakage contracts have recently been proposed as a new security abstraction at the Instruction Set Architecture (ISA) level. Such contracts aim to faithfully capture the information processors may leak through side effects of their microarchitectural implementations. However, so far, we lack a verification methodology to check that a processor actually satis

Ziyuan Zhao, Fangcheng Zhou, Zeng Zeng, Cuntai Guan

Domain shift and label scarcity heavily limit deep learning applications to various medical image analysis tasks. Unsupervised domain adaptation (UDA) techniques have recently achieved promising cross-modality medical image segmentation by transferring knowledge from a label-rich source domain to an unlabeled target domain. However, it is also difficult to c

Sagardeep Talukdar, Riki Dutta, Gautam Kumar Saharia, Sudipta Nandy

In this paper, we propose the bilinearization of the Fokas-Lenells equation (FLE) with a vanishing boundary condition. In the proposed bilinearization we make use of an auxiliary function to convert the trilinear equations into a set of bilinear equations. We obtain bright 1-soliton, 2- soliton solutions and present the scheme for obtaining N soliton solutio

Hans Johnson, Silvia Zorzetti, Jafar Saniie

This work explores avenues and target areas for optimizing FPGA-based control hardware for experiments conducted on superconducting quantum computing systems and serves as an introduction to some of the current research at the intersection of classical and quantum computing hardware. With the promise of building larger-scale error-corrected quantum computers

I. Andrade, D. Bazeia, M. A. Marques, R. Menezes

In this work, we investigate a Maxwell-scalar model that couples the scalar and gauge fields through the electric permittivity and another model, in which the scalar field lives in the presence of impurity. By considering a single spatial dimension, we determine the conditions under which the model with impurity can be seen as an effective model for the Maxw

Valentin Bartier, Oscar Defrain, Fionn Mc Inerney

At STOC 2002, Eiter, Gottlob, and Makino presented a technique called ordered generation that yields an $n^{O(d)}$-delay algorithm listing all minimal transversals of an $n$-vertex hypergraph of degeneracy $d$. Recently at IWOCA 2019, Conte, Kant\'e, Marino, and Uno asked whether this XP-delay algorithm parameterized by $d$ could be made FPT-delay for a weak

Zhikai Zhang, Jian Ding, Li Jiang, Dengxin Dai

Instance segmentation of point clouds is a crucial task in 3D field with numerous applications that involve localizing and segmenting objects in a scene. However, achieving satisfactory results requires a large number of manual annotations, which is a time-consuming and expensive process. To alleviate dependency on annotations, we propose a novel framework,

Julian Hazell

Recent progress in artificial intelligence (AI), particularly in the domain of large language models (LLMs), has resulted in powerful and versatile dual-use systems. This intelligence can be put towards a wide variety of beneficial tasks, yet it can also be used to cause harm. This study explores one such harm by examining how LLMs can be used for spear phis

Mohammad H. Taufik, Tariq Alkhalifah

Physics-informed neural networks (PINNs) are promising to replace conventional partial differential equation (PDE) solvers by offering more accurate and flexible PDE solutions. However, they are hampered by the relatively slow convergence and the need to perform additional, potentially expensive, training for different PDE parameters. To solve this limitatio

Luccas Campos, Mykael Cardoso, Luiz Gustavo Farah

In this paper we study the focusing inhomogeneous 3D nonlinear Schr\"odinger equation with inverse-square potential in the mass-supercritical and energy-subcritical regime. We first establish local well-posedness in $\dot{H}_a^{s_c}\cap \dot{H}_a^1$, with $s_c=3/2-(2-b)/2\sigma$. Next, we prove the blow-up of the scaling invariant Lebesgue norm for radial so

Bo Zhang, Chi Zhang, Xiangyu Hu

Scientific computing libraries, either being in-house or open-source, have experienced enormous progress in both engineering and scientific research. It is therefore essential to ensure that the modifications in the source code aroused by bug fixing or new feature development wouldn't compromise the accuracy and functionality that has already been validated

Usman Gohar, Lu Cheng

The widespread adoption of Machine Learning systems, especially in more decision-critical applications such as criminal sentencing and bank loans, has led to increased concerns about fairness implications. Algorithms and metrics have been developed to mitigate and measure these discriminations. More recently, works have identified a more challenging form of

Akash Sengupta, Ignas Budvytis, Roberto Cipolla

Monocular 3D human pose and shape estimation is an ill-posed problem since multiple 3D solutions can explain a 2D image of a subject. Recent approaches predict a probability distribution over plausible 3D pose and shape parameters conditioned on the image. We show that these approaches exhibit a trade-off between three key properties: (i) accuracy - the like

Camilla Quaresmini, Giuseppe Primiero

Artificial Intelligence (AI) systems are not intrinsically neutral and biases trickle in any type of technological tool. In particular when dealing with people, the impact of AI algorithms' technical errors originating with mislabeled data is undeniable. As they feed wrong and discriminatory classifications, these systems are not systematically guarded again

Zhanhong Huang, Xiao Zhang, Xinming Huang

Real-time perception and motion planning are two crucial tasks for autonomous driving. While there are many research works focused on improving the performance of perception and motion planning individually, it is still not clear how a perception error may adversely impact the motion planning results. In this work, we propose a joint simulation framework wit

Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung

Computed Tomography (CT) scans provide detailed and accurate information of internal structures in the body. They are constructed by sending x-rays through the body from different directions and combining this information into a three-dimensional volume. Such volumes can then be used to diagnose a wide range of conditions and allow for volumetric measurement

Connor Malin

We show that Koszul duality for operads in $(\mathrm{Top},\times)$ can be expressed via generalized Thom complexes. As an application, we prove the Koszul self duality of the little disk modules $E_M$. We discuss implications for factorization homology, embedding calculus, and confirm an old conjecture of Ching on the relation of Goodwillie calculus to manif

Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung

Whole-Slide Imaging allows for the capturing and digitization of high-resolution images of histological specimen. An automated analysis of such images using deep learning models is therefore of high demand. The transformer architecture has been proposed as a possible candidate for effectively leveraging the high-resolution information. Here, the whole-slide

Qiuqiang Kong, Ke Chen, Haohe Liu, Xingjian Du

Universal source separation (USS) is a fundamental research task for computational auditory scene analysis, which aims to separate mono recordings into individual source tracks. There are three potential challenges awaiting the solution to the audio source separation task. First, previous audio source separation systems mainly focus on separating one or a li

Aline Marguet, Charline Smadi

We consider a cell population subject to a parasite infection. Cells divide at a constant rate and, at division, share the parasites they contain between their two daughter cells. The sharing may be asymmetrical, and its law may depend on the quantity of parasites in the mother. Cells die at a rate which may depend on the quantity of parasites they carry, an

Masood Tadi, Jiří Witzany

This research introduces a novel pairs trading strategy based on copulas for cointegrated pairs of cryptocurrencies. To identify the most suitable pairs, the study employs linear and non-linear cointegration tests along with a correlation coefficient measure and fits different copula families to generate trading signals formulated from a reference asset for

Jad Hamdan

We show how the renormalization group approach can be used to prove quantitative central limit theorems (CLTs) in the setting of free, Boolean, bi-free and bi-Boolean independence under finite third moment assumptions. The proofs rely on the construction of a contraction on a subspace of probability measures over $\mathbb{R}$ (or $\mathbb{R}^2$) equipped wit

Claudianor O. Alves, Nguyen Van Thin

In this paper we study the existence of multiple normalized solutions to the following class of elliptic problems \begin{align*} \left\{ \begin{aligned} &-\epsilon^2\Delta u+V(x)u=\lambda u+f(u), \quad \quad \hbox{in }\mathbb{R}^N, &\int_{\mathbb{R}^{N}}|u|^{2}dx=a^{2}\epsilon^N, \end{aligned} \right. \end{align*} where $a,\epsilon>0$, $\lambda\in \mathbb{R}

Christopher Tatsch, Jonas Amoama Bredu Jnr, Dylan Covell, Ihsan Berk Tulu

There are many benefits for exploring and exploiting underground mines, but there are also significant risks and challenges. One such risk is the potential for accidents caused by the collapse of the pillars, and roofs which can be mitigated through inspections. However, these inspections can be costly and may put the safety of the inspectors at risk. To add

Seidali S. Seidov, Vladislav D. Kochev, Pavel D. Grigoriev

The interplay between superconductivity (SC) and spin/charge density wave (DW) in organic metals shows many similarities to high-$T_c$ superconductors. It also contains many puzzles, for example, the anisotropic SC onset observed and the severalfold increase of the upper critical field $H_{c2}$ in the coexistence region, as well as the microscopic origin of

Thomas F. Allard, Guillaume Weick

A dimerized chain of dipolar emitters strongly coupled to a multimode optical waveguide cavity is studied. By integrating out the photonic degrees of freedom of the cavity, the system is recast in a two-band model with an effective coupling, so that it mimics a variation of the paradigmatic Su-Schrieffer-Heeger model, which features a nontrivial topological

Andreas Ekström, Christian Forssén, G. Hagen, G. R. Jansen

We compute the structure of the exotic even nuclei $^{20-34}$Ne and $^{34-40}$Mg using interactions from chiral effective field theory (EFT). Our results for the ground-state rotational bands in $^{20-32}$Ne and $^{36-40}$Mg agree with data. We predict a well-deformed $^{34}$Ne and find that $^{40}$Mg exhibits an oblate deformed band close to the prolate gro

Madhur Mangalam, Arash Sadri, Junichiro Hayano, Eiichi Watanabe

Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the same individual to result in the minimum possible false-positive and false-negative rates. The application of standard

Laura Abatangelo, Corentin Léna, Paolo Musolino

We provide a full series expansion of a generalization of the so-called $u$-capacity related to the Dirichlet-Laplacian in dimension three and higher, extending previous results of the authors, and of the authors together with Virginie Bonnaillie-No\"el, dealing with the planar case. We apply the result in order to study the asymptotic behavior of perturbed

Laurent Bartholdi

We prove, for every non-virtually free hyperbolic group $G$, that there is no algorithm that, given a finite collection of dominoes, determines whether the Cayley graph of $G$ may be edge-covered by these dominoes so that colours match at vertices. This answers a conjecture by Aubrun, Barbieri and Moutot and goes towards settling a long-standing conjecture o

Viet-Man Le, Cristian Vidal Silva, Alexander Felfernig, David Benavides

Constraint-based applications attempt to identify a solution that meets all defined user requirements. If the requirements are inconsistent with the underlying constraint set, algorithms that compute diagnoses for inconsistent constraints should be implemented to help users resolve the "no solution could be found" dilemma. FastDiag is a typical direct diagno

Ginger Frame, David J. Armstrong, Heather M. Cegla, Jorge Fernández Fernández

We present the discovery and confirmation of a transiting hot, bloated Super-Neptune using photometry from TESS and LCOGT and radial velocity measurements from HARPS. The host star TOI-2498 is a V = 11.2, G-type (T$_{eff}$ = 5905 $\pm$ 12K) solar-like star with a mass of 1.12 $\pm$ 0.02 M$_{\odot}$ and a radius of 1.26 $\pm$ 0.04 R$_{\odot}$. The planet, TOI

Nikolaos Parthenios, Laura Classen

We study possible patterns for spontaneous symmetry breaking in a Dirac fermion model, which is applicable to twisted bilayer graphene at charge neutrality. We show how a chiral SU(4) symmetry emerges and construct the corresponding low-energy model that includes a Fierz-complete set of symmetry-allowed four-fermion interactions. We employ an unbiased renorm

Rui Zhang, Xiaoyuan Huang, Zhi-Hui Xu, Shiping Zhao

The diffuse gamma-ray emission between 10 and 1000 TeV from the Galactic plane was recently measured by the Large High Altitude Air Shower Observatory (LHAASO). These observations will help tremendously in constraining the propagation and interaction of cosmic rays in the Milky Way. Additionally, new measurements of CR spectra reach a very high precision up

Joshua Smailes, Sebastian Köhler, Simon Birnbach, Martin Strohmeier

Due to an increase in the availability of cheap off-the-shelf radio hardware, spoofing and replay attacks on satellite ground systems have become more accessible than ever. This is particularly a problem for legacy systems, many of which do not offer cryptographic security and cannot be patched to support novel security measures. In this paper we explore rad

David Mallasén, Alberto A. Del Barrio, Manuel Prieto-Matias

The accuracy requirements in many scientific computing workloads result in the use of double-precision floating-point arithmetic in the execution kernels. Nevertheless, emerging real-number representations, such as posit arithmetic, show promise in delivering even higher accuracy in such computations. In this work, we explore the native use of 64-bit posits

David Tebbe, Marc Schütte, Baisali Kundu, Bernd Beschoten

Optical micro-spectroscopy is an invaluable tool for studying and characterizing samples ranging from classical semiconductors to low-dimensional materials and heterostructures. To date, most implementations are based on point-scanning techniques, which are flexible and reliable, but slow. Here, we describe a setup for highly parallel acquisition of hyperspe

Gabriele Perfetto, Federico Carollo, Juan P. Garrahan, Igor Lesanovsky

We investigate the quantum reaction-diffusion dynamics of fermionic particles which coherently hop in a one-dimensional lattice and undergo annihilation reactions. The latter are modelled as dissipative processes which involve losses of pairs $2A \to \emptyset$, triplets $3A \to \emptyset$, and quadruplets $4A \to \emptyset$ of neighbouring particles. When c

Natasha María Monserrat Bertaina Lucero

Perception is a process that requires a great deal of mental processing, which provides the means by which one's concept of the environment is created and which helps one learn and interact with it. The compilation of previous studies throughout history has led to the conclusion that auditory performance improves when combined with visual stimuli and vice ve

Kishore Punniyamurthy, Khaled Hamidouche, Bradford M. Beckmann

In order to satisfy their ever increasing capacity and compute requirements, machine learning models are distributed across multiple nodes using numerous parallelism strategies. As a result, collective communications are often on the critical path, and hiding their latency by overlapping kernel-granular communication and computation is difficult due to the a

Melika Payvand, Simone D'Agostino, Filippo Moro, Yigit Demirag

Biological neurons can detect complex spatio-temporal features in spiking patterns via their synapses spread across across their dendritic branches. This is achieved by modulating the efficacy of the individual synapses, and by exploiting the temporal delays of their response to input spikes, depending on their position on the dendrite. Inspired by this mech

Ning Ding, Ce Zhang, Azim Eskandarian

Object detection (OD) is crucial to autonomous driving. On the other hand, unknown objects, which have not been seen in training sample set, are one of the reasons that hinder autonomous vehicles from driving beyond the operational domain. To addresss this issue, we propose a saliency-based OD algorithm (SalienDet) to detect unknown objects. Our SalienDet ut

Chenhang Cui, Yazhou Ren, Jingyu Pu, Xiaorong Pu

Deep multi-view subspace clustering (DMVSC) has recently attracted increasing attention due to its promising performance. However, existing DMVSC methods still have two issues: (1) they mainly focus on using autoencoders to nonlinearly embed the data, while the embedding may be suboptimal for clustering because the clustering objective is rarely considered i

Calin Tataru, Jamie Vicary

The algebraic zigzag construction has recently been introduced as a combinatorial foundation for a higher dimensional notion of string diagram. For use in a proof assistant, a layout algorithm is required to determine the optimal rendering coordinates, across multiple projection schemes including 2D, 3D, and 4D. For construction of these layouts, a key requi

Iqra Altaf, Ryan Bushling, Bobby Wilson

We prove that, for every norm on $\mathbb{R}^d$ and every $E \subseteq \mathbb{R}^d$, the Hausdorff dimension of the distance set of $E$ with respect to that norm is at least $\dim_{\mathrm{H}} E - (d-1)$. An explicit construction follows, demonstrating that this bound is sharp for every polyhedral norm on $\mathbb{R}^d$. The techniques of algorithmic comple

Oleg Shramko, Andrey Svitenkov, Pavel Zun

One-dimensional blood flow model accuracy has been verified in many studies. This work is about introducing gravity into a one-dimensional model. For this purpose, gravitational force was introduced into the existing model. The boundary conditions must also be adjusted to account for gravity. For this purpose, a method for calculating arterial resistance of

N. A. Smirnov

The paper presents results of a comprehensive study from first principles into the properties of Ni, Pd, Rh, and Ir crystals under pressure. We calculated elastic constants, phonon spectra, isotherms, Hugoniots, sound velocities, relative structural stability, and phase diagrams. It is shown that in nickel and palladium under high pressures ($>$0.14 TPa) and

Orlando E. Martínez-Durive, Sachit Mishra, Cezary Ziemlicki, Stefania Rubrichi

Digital sources have been enabling unprecedented data-driven and large-scale investigations across a wide range of domains, including demography, sociology, geography, urbanism, criminology, and engineering. A major barrier to innovation is represented by the limited availability of dependable digital datasets, especially in the context of data gathered by m

Leonid V. Skripnikov, Alexander V. Oleynichenko, Andréi Zaitsevskii, Nikolai S. Mosyagin

Relativistic coupled-cluster calculations of the ionization potential, dissociation energy, and excited electronic states under 35,000 cm$^{-1}$ are presented for the actinium monofluoride (AcF) molecule. The ionization potential is calculated to be IP$_e=48,866$ cm$^{-1}$, and the ground state is confirmed to be a closed-shell singlet and thus strongly sens

A. Maggio, I. Pillitteri, C. Argiroffi, S. Benatti

Atmospheric mass loss plays a major role in the evolution of exoplanets. This process is driven by the stellar high-energy irradiation, especially in the first hundreds of millions of years after dissipation of the proto-planetary disk. A major source of uncertainty in modeling atmospheric photo-evaporation and photo-chemistry is due to the lack of direct me

Xin-Yue Kang, Jin-Yang Li, Si Li

Unconventional topological quasiparticles have recently garnered significant attention in the realm of condensed matter physics. Here, based on first-principles calculations and symmetry analysis, we reveal the coexistence of multiple types of interesting unconventional topological quasiparticles in the phonon spectrum of the chiral crystal CsBe$_2$F$_5$. Sp

Alkesh K. Srivastava, George P. Kontoudis, Donald Sofge, Michael Otte

Effective communication is crucial for deploying robots in mission-specific tasks, but inadequate or unreliable communication can greatly reduce mission efficacy, for example in search and rescue missions where communication-denied conditions may occur. In such missions, robots are deployed to locate targets, such as human survivors, but they might get trapp

Andreas Rückriegel, Jonas Arnold, Rüdiger Krämer, Peter Kopietz

Exact functional renormalization group (FRG) flow equations for quantum systems can be derived directly within an operator formalism without using functional integrals. This simple insight opens new possibilities for applying FRG methods to models for strongly correlated electrons with projected Hilbert spaces, such as quantum spin models, the $t$-$J$ model,

Rachel Ward, Tamara G. Kolda

We consider alternating gradient descent (AGD) with fixed step size applied to the asymmetric matrix factorization objective. We show that, for a rank-$r$ matrix $\mathbf{A} \in \mathbb{R}^{m \times n}$, $T = C (\frac{\sigma_1(\mathbf{A})}{\sigma_r(\mathbf{A})})^2 \log(1/\epsilon)$ iterations of alternating gradient descent suffice to reach an $\epsilon$-opt

Rohit Dilip Holkar, Md Amir Hossain

Let $X$ be a path connected, locally path connected and semilocally simply connected space; let $\tilde{X}$ be its universal cover. We discuss the existence and description of a Haar system on the fundamental groupoid $\Pi_1(X)$ of $X$. The existence of a Haar system on $\Pi_1(X)$ is justified when $X$ is a second countable, locally compact and Hausdorff. We

Souhail Bakkali, Ziheng Ming, Mickael Coustaty, Marçal Rusiñol

In the recent past, complex deep neural networks have received huge interest in various document understanding tasks such as document image classification and document retrieval. As many document types have a distinct visual style, learning only visual features with deep CNNs to classify document images have encountered the problem of low inter-class discrim

Nolan Schock

Let $Y(E_n)$ denote the moduli space of pairs $(S,B)$ where $S$ is a del Pezzo surface of degree $9-n$ and $B$ is the labeled (marked) sum of its finitely many lines. When $n=6$, $Y(E_6)$ is the classical moduli space of marked cubic surfaces dating back to the nineteenth century. We describe the compactifications of $Y(E_5)$ and $Y(E_6)$ by Koll\'ar--Shephe

Vidya A. Chhabria, Wenjing Jiang, Andrew B. Kahng, Sachin S. Sapatnekar

Due to the unavailability of routing information in design stages prior to detailed routing (DR), the tasks of timing prediction and optimization pose major challenges. Inaccurate timing prediction wastes design effort, hurts circuit performance, and may lead to design failure. This work focuses on timing prediction after clock tree synthesis and placement l

Christian Rose, Martin Tautenhahn

We prove quantitative unique continuation estimates for relatively dense sets and spectral subspaces associated to small energies of Schr\"odinger operators on Riemannian manifolds with Ricci curvature bounded below. The upper bound for the energy range and the constant appearing in the estimate are given in terms of the lower bound of the Ricci curvature an

Huo Chen, Niladri Gomes, Siyuan Niu, Wibe Albert de Jong

Emerging quantum hardware provides new possibilities for quantum simulation. While much of the research has focused on simulating closed quantum systems, the real-world quantum systems are mostly open. Therefore, it is essential to develop quantum algorithms that can effectively simulate open quantum systems. Here we present an adaptive variational quantum a

Pankaj Kumar, Judith T. Karpen, Vadim M. Uritsky, Craig E. Deforest

Microstreams are fluctuations in the solar wind speed and density associated with polarity-reversing folds in the magnetic field (also denoted switchbacks). Despite their long heritage, the origin of these microstreams/switchbacks remains poorly understood. For the first time, we investigated periodicities in microstreams during Parker Solar Probe (PSP) Enco

Hugo Oliveira, Pedro H. T. Gama, Isabelle Bloch, Roberto Marcondes Cesar

Most uses of Meta-Learning in visual recognition are very often applied to image classification, with a relative lack of works in other tasks {such} as segmentation and detection. We propose a generic Meta-Learning framework for few-shot weakly-supervised segmentation in medical imaging domains. We conduct a comparative analysis of meta-learners from distinc

Bachana Beradze, Mikheil Tsitsishvili, Emanuele Tirrito, Marcello Dalmonte

We consider a system of interacting spinless fermions on a two-leg triangular ladder with $\pi/2$ magnetic flux per triangular plaquette. Microscopically, the system exhibits a U(1) symmetry corresponding to the conservation of total fermionic charge, and a discrete $\mathbb{Z}_2$ symmetry -- a product of parity transformation and chain permutation. Using bo