July 2023 arXiv papers — page 44

Soichiro Uemura

In the generalized topological quantum field theory constructed by Andersen and Kashaev, invariants of 3-manifolds are defined given the combinatorial structure of a tetrahedral decomposition. Furthermore, a variant of the volume conjecture has been proposed in which the hyperbolic volume can be extracted from this invariant of the complementary space of the

Matthew Corbett, Brendan David-John, Jiacheng Shang, Y. Charlie Hu

The modern Mixed Reality devices that make the Metaverse viable require vast information about the physical world and can also violate the privacy of unsuspecting or unwilling bystanders in their vicinity. In this article, we provide an introduction to the problem, existing solutions, and avenues for future research.

Constantia Alexandrou, Simone Bacchio, Giannis Koutsou, Theodoros Leontiou

We present an investigation of pion-nucleon elastic scattering in the $I\,(J^P) = \frac{3}{2}\,(\frac{3}{2}^+)$ channel using lattice QCD with degenerate up and down, strange and charm quarks with masses tuned to their physical values. We use an ensemble of twisted mass fermions with box size $L = 5.1\,\mathrm{fm}$ and lattice spacing $a = 0.08\,\mathrm{fm}$

Han Wu, Jiadong Zhang, Yu Fang, Zhentao Liu

Accurately localizing and identifying vertebrae from CT images is crucial for various clinical applications. However, most existing efforts are performed on 3D with cropping patch operation, suffering from the large computation costs and limited global information. In this paper, we propose a multi-view vertebra localization and identification from CT images

Marizol Lizbeth Serrano Quispe, Fred Torres Cruz

CATASTROAGRI is an application developed to load, analyze and interactively visualize relevant data on catastrophic agricultural insurance. It also focuses on the analysis of an ARIMA (0,1,1) (0,1,1) model to identify and estimate patterns in the agricultural data of the Puno Region, it presents a decreasing trend because there is a significant relationship

Gero Junike, Hauke Stier

We provide a unified framework to obtain numerically certain quantities, such as the distribution function, absolute moments and prices of financial options, from the characteristic function of some (unknown) probability density function using the Fourier-cosine expansion (COS) method. The classical COS method is numerically very efficient in one-dimension,

Siyu Wu, Qian Wu, Hongxia Huang, Xurong Chen

We probe the existence of the $^3_{\Lambda_c}$H where the $N\Lambda_c$ potentials are derived from the quark-delocalization color-screening model (QDCSM). The $N\Lambda_c$ system is studied and the $N\Lambda_c$ scattering length so as the effective range are obtained in the QDCSM. We construct effective Gaussian-type $N\Lambda_c$ potentials which reproduce t

O. V. Usatenko, G. M. Pritula

In this study, we continue our exploration of the concept of information temperature as a characteristic of random sequences. We describe methods for introducing the information temperature in the context of binary high-order Markov chain with step-wise memory and investigate the application of the temperature as a parameter of the sequence complexity. We ai

Ilias Diakonikolas, Daniel M. Kane

We study the problem of PAC learning a linear combination of $k$ ReLU activations under the standard Gaussian distribution on $\mathbb{R}^d$ with respect to the square loss. Our main result is an efficient algorithm for this learning task with sample and computational complexity $(dk/\epsilon)^{O(k)}$, where $\epsilon>0$ is the target accuracy. Prior work ha

Cunyuan Jiang, Matteo Baggioli, Jack F. Douglas

The boson peak (BP), a low-energy excess in the vibrational density of states over the phonon Debye contribution, is usually identified as one of the distinguishing features between ordered crystals and amorphous solid materials. Despite decades of efforts, its microscopic origin still remains a mystery and a consensus on its theoretical derivation has not y

Lennon Ó Náraigh, Juan Mairal

We study droplet-impact problems in a three-dimensional cylindrical or equivalent two-dimensional Cartesian geometry. Such structures do have an approximate experimental realization, and they are often simulated a test-bed for computational methods. We focus on droplet impact on a smooth homogeneous surface as well as head-on collision of two droplets. We pe

Amirshayan Nasirimajd, Simone Alberto Peirone, Chiara Plizzari, Barbara Caputo

This report presents the technical details of our approach for the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition. Our approach is based on the idea that the order in which actions are performed is similar between the source and target domains. Based on this, we generate a modified sequence by randomly combining action

Javier Cremona, Javier Civera, Ernesto Kofman, Taihú Pire

The accelerating pace in the automation of agricultural tasks demands highly accurate and robust localization systems for field robots. Simultaneous Localization and Mapping (SLAM) methods inevitably accumulate drift on exploratory trajectories and primarily rely on place revisiting and loop closing to keep a bounded global localization error. Loop closure t

Ali Araabi, Vlad Niculae, Christof Monz

Despite the tremendous success of Neural Machine Translation (NMT), its performance on low-resource language pairs still remains subpar, partly due to the limited ability to handle previously unseen inputs, i.e., generalization. In this paper, we propose a method called Joint Dropout, that addresses the challenge of low-resource neural machine translation by

Curt Waltmann, Ahis Shrestha, Monica Olvera de la Cruz

Recent findings suggest that shell protein distribution and morphology of bacterial microcompartments regulate the chemical fluxes facilitating reactions which dictate their biological function. We explore how the morphology and component patterning are coupled through the competition of mean and Gaussian bending energies in multicomponent elastic shells tha

Zachary P. Neal

Collecting network data directly from network members can be challenging. One alternative involves inferring a network from observed groups, for example, inferring a network of scientific collaboration from researchers' observed paper authorships. In this paper, I explore when an unobserved undirected network of interest can accurately be inferred from obser

Nick W. Koning

It is conventionally believed that a permutation test should ideally use all permutations. If this is computationally unaffordable, it is believed one should use the largest affordable Monte Carlo sample or (algebraic) subgroup of permutations. We challenge this belief by showing we can sometimes obtain dramatically more power by using a tiny subgroup. As th

Martin Lebourdais, Théo Mariotte, Marie Tahon, Anthony Larcher

Voice activity and overlapped speech detection (respectively VAD and OSD) are key pre-processing tasks for speaker diarization. The final segmentation performance highly relies on the robustness of these sub-tasks. Recent studies have shown VAD and OSD can be trained jointly using a multi-class classification model. However, these works are often restricted

Emil T. Akhmedov, Tin-Long Chau, Pei-Ming Ho, Hikaru Kawai

We revisit the connection between Hawking radiation and high-frequency dispersions for a Schwarzschild black hole following the work of Brout et al.. After confirming the robustness of Hawking radiation for monotonic dispersion relations, we consider non-monotonic dispersion relations that deviate from the standard relation only in the trans-Planckian domain

Roberto Casadio, Alexander Kamenshchik, Panagiotis Mavrogiannis, Polina Petriakova

We study the effects of a spatially homogenous magnetic field in Bianchi-I cosmological models. The cases of a pure magnetic field and two models with additional dust and a massless scalar field (stiff matter) are also considered. At the beginning of the cosmological evolution,i.e., in the neighborhood of the singularity, the universe is described by one of

Daniele Bartoli, Giovanni Longobardi, Giuseppe Marino, Marco Timpanella

In recent years, several families of scattered polynomials have been investigated in the literature. However, most of them only exist in odd characteristic. In [B. Csajb\'ok, G. Marino and F. Zullo: New maximum scattered linear sets of the projective line, Finite Fields Appl. 54 (2018), 133-150; G. Marino, M. Montanucci and F. Zullo: MRD-codes arising from t

Zachary P. Neal, Jennifer Watling Neal

It is common to use the projection of a bipartite network to measure a unipartite network of interest. For example, scientific collaboration networks are often measured using a co-authorship network, which is the projection of a bipartite author-paper network. Caution is required when interpreting the edge weights that appear in such projections. However, ba

Maryam Alimardani, Steven Kocken, Nikki Leeuwis

A major issue in Motor Imagery Brain-Computer Interfaces (MI-BCIs) is their poor classification accuracy and the large amount of data that is required for subject-specific calibration. This makes BCIs less accessible to general users in out-of-the-lab applications. This study employed deep transfer learning for development of calibration-free subject-indepen

Honggeun Kim, Nicholas S. Kern, Jacqueline N. Hewitt, Bang D. Nhan

One key challenge in detecting 21 cm cosmological signal at z > 6 is to separate the cosmological signal from foreground emission. This can be studied in a power spectrum space where the foreground is confined to low delay modes whereas the cosmological signal can spread out to high delay modes. When there is a calibration error, however, chromaticity of gai

Jianwei Shen, Jiayu Liang, Qixu Zhao, Menghui Jia

For highly efficient ultrathin solar cells, layered indium selenide (InSe), a van der Waals solid, has shown a great promise. In this paper, we study the coherent dynamics of charge carriers generation in {\gamma}-InSe single crystals. We employ ultrafast transient absorption spectroscopy to examine the dynamics of hot electrons after resonant photoexcitatio

Kihong Kwon, Julián Barragán Amado, Bogeun Gwak

We investigate the scattering of a massless scalar field by a charged non-rotating black hole in the presence of gravity's rainbow. Using the connection coefficients of the confluent Heun equation expressed in terms of the semi-classical confluent conformal blocks and the instanton part of the Nekrasov-Shatashvili (NS) free energy, we obtain an asymptotic ex

D. O. Norkin, E. O. Kiktenko, A. K. Fedorov

Quantum tomography is a widely applicable method for reconstructing unknown quantum states and processes. However, its applications in quantum technologies usually also require estimating the difference between prepared and target quantum states with reliable confidence intervals. In this work we suggest a computationally efficient and reliable scheme for de

Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel

Deep neural networks provide excellent performance for inverse problems such as denoising. However, neural networks can be sensitive to adversarial or worst-case perturbations. This raises the question of whether such networks can be trained efficiently to be worst-case robust. In this paper, we investigate whether jittering, a simple regularization techniqu

Tim Krüger, Michael Gref

Large language models such as ChatGPT-3.5 and GPT-4.0 are ubiquitous and dominate the current discourse. Their transformative capabilities have led to a paradigm shift in how we interact with and utilize (text-based) information. Each day, new possibilities to leverage the capabilities of these models emerge. This paper presents findings on the performance o

Anna Geyer, Yue Liu, Dmitry E. Pelinovsky

We consider the propagation of smooth solitary waves in a two-dimensional generalization of the Camassa--Holm equation. We show that transverse perturbations to one-dimensional solitary waves behave similarly to the KP-II theory. This conclusion follows from our two main results: (i) the double eigenvalue of the linearized equations related to the translatio

Mai Qiao, Chen Xia, Yu-Feng Zhou

Halo dark matter (DM) particles could lose energy due to the scattering off nuclei within the Earth before reaching the underground detectors of DM direct detection experiments. This Earth shielding effect can result in diurnal modulation of the DM-induced recoil event rates observed underground due to the self-rotation of the Earth. For electron recoil sign

André Pedroso Kowacs

This article presents an investigation of global properties of a class of differential operators on $\mathbb{T}^1\times\mathbb{R}$. Our approach involves the utilization of a mixed Fourier transform, incorporating both partial Fourier series on the torus and partial Fourier transform in Euclidean space. By examining the behaviour of the mixed Fourier coeffic

Dominik Bell, Martin Campos Pinto, Davor Kumozec, Frederik Schnack

The gyro-kinetic model is an approximation of the Vlasov-Maxwell system in a strongly magnetized magnetic field. We propose a new algorithm for solving it combining the Semi-Lagrangian (SL) method and the Arakawa (AKW) scheme with a time-integrator. Both methods are successfully used in practice for different kinds of applications, in our case, we combine th

E. H. Rodrigues, M. Dutra, O. Lourenço

We perform an improvement in a van der Waals-type model by including it effects of short-range correlations (SRC). Attractive and repulsive parts of the nucleon-nucleon interaction are assumed to be density-dependent functions, more specifically, we adopt the Carnahan-Starling (CS) method for the latter, and a suitable expression for the former in order to r

A Patrón, B. Sánchez-Rey, C. A. Plata, A. Prados

In this perspective paper, we look into memory effects in out-of-equilibrium systems. To be concrete, we exemplify memory effects with the paradigmatic case of granular fluids, although extensions to other contexts such as molecular fluids with non-linear drag are also considered. The focus is put on two archetypal memory effects: the Kovacs and Mpemba effec

Saad Ejaz, Masaki Inoue

A trust-aware safe control system for autonomous navigation in the presence of humans, specifically pedestrians, is presented. The system combines model predictive control (MPC) with control barrier functions (CBFs) and trust estimation to ensure safe and reliable navigation in complex environments. Pedestrian trust values are computed based on features, ext

Roel A. Botter, Yvan Klaver, Randy te Morsche, Bruno L. Segat Frare

Stimulated Brillouin scattering (SBS), a coherent nonlinear effect coupling acoustics and optics, can be used in a wide range of applications such as Brillouin lasers and tunable narrowband RF filtering. Wide adoption of such technologies however, would need a balance of strong Brillouin interaction and low optical loss in a structure compatible with large s

Chi Xie, Zhao Zhang, Yixuan Wu, Feng Zhu

Detecting objects based on language information is a popular task that includes Open-Vocabulary object Detection (OVD) and Referring Expression Comprehension (REC). In this paper, we advance them to a more practical setting called Described Object Detection (DOD) by expanding category names to flexible language expressions for OVD and overcoming the limitati

Geehyun Yang, Matthias Kizmann, Alfred Leitenstorfer, Andrey S. Moskalenko

Quantum light is considered to be one of the key resources of the coming second quantum revolution expected to give rise to groundbreaking technologies and applications. If the spatio-temporal and polarization structure of modes is known, the properties of quantum light are well understood. This information provides the basis for contemporary quantum optics

Olga Balsalobre-Ruza, Itziar de Gregorio-Monsalvo, Jorge Lillo-Box, Nuria Huélamo

Context: High-spatial resolution Atacama Large Millimeter/submillimeter Array (ALMA) data have revealed a plethora of substructures in protoplanetary disks. Some of those features are thought to trace the formation of embedded planets. One example is the gas and dust that accumulated in the co-orbital Lagrangian regions $L_4$/$L_5$, which were tentatively de

Wei Yuan, Liang Qu, Lizhen Cui, Yongxin Tong

Owing to the nature of privacy protection, federated recommender systems (FedRecs) have garnered increasing interest in the realm of on-device recommender systems. However, most existing FedRecs only allow participating clients to collaboratively train a recommendation model of the same public parameter size. Training a model of the same size for all clients

S. Bellucci, V. Kh. Kotanjyan, A. A. Saharian

We investigate the properties of the fermionic Fulling-Rindler vacuum for a massive Dirac field in a general number of spatial dimensions. As important local characteristics, the fermionic condensate and the expectation value of the energy-momentum tensor are evaluated. The renormalization is reduced to the subtraction of the corresponding expectation values

Carlos De la Cruz Mengual, Tobias Hartnick

We provide a version of Quillen's homological stability criterion for continuous bounded cohomology. This criterion is exploited in the companion paper (arXiv:2201.03879) in order to derive new bounded cohomological stability results for various families of classical groups.

Shuang Wei, Michael J. Mior

Semantic types are a more powerful and detailed way of describing data than atomic types such as strings or integers. They establish connections between columns and concepts from the real world, providing more nuanced and fine-grained information that can be useful for tasks such as automated data cleaning, schema matching, and data discovery. Existing deep

Giovanni Fusco, Monica Motta

We introduce a notion of bounded variation solution for a new class of nonlinear control systems with ordinary and impulsive controls, in which the drift function depends not only on the state, but also on its past history, through a finite number of time delays. After proving the well posedness of such solutions and the continuity of the corresponding input

Ajay Jha, Pan-Pan Zhang, Vandana Tiwari, Lipeng Chen

Photosystem II (PSII) reaction center is a unique protein-chromophore complex that is capable of efficiently separating electronic charges across the membrane after photoexcitation. In the PSII reaction center, the primary energy- and charge-transfer (CT) processes occur on comparable ultrafast timescales, which makes it extremely challenging to understand t

Reza Asrar Ghaderloo, Ali Parsa Sirat, Abbas Shoulaie

In this paper, a highly compact, low power (<10W), high frequency (2 MHz) isolated active clamp forward converter, comprising a coreless Printed Circuit Board-based transformer is proposed. To decrease the size of converter, high switching frequency is considered which lead to decrease in inductor, capacitor and transformer size. Highly switch loss due to ha

Jan Trienes, Paul Youssef, Jörg Schlötterer, Christin Seifert

Automatically summarizing radiology reports into a concise impression can reduce the manual burden of clinicians and improve the consistency of reporting. Previous work aimed to enhance content selection and factuality through guided abstractive summarization. However, two key issues persist. First, current methods heavily rely on domain-specific resources t

Samuel Balula, Efe C. Balta, Dominic Liao-McPherson, Alisa Rupenyan

Learning-based control methods for industrial processes leverage the repetitive nature of the underlying process to learn optimal inputs for the system. While many works focus on linear systems, real-world problems involve nonlinear dynamics. In this work, we propose an algorithm for the nonlinear iterative learning control problem based on sequential quadra

Nathalie Ayi, Nastassia Pouradier Duteil

In this article, we study the large-population limit of interacting particle systems posed on weighted random graphs. In that aim, we introduce a general framework for the construction of weighted random graphs, generalizing the concept of graphons. We prove that as the number of particles tends to infinity, the finite-dimensional particle system converges i

Marina Lotti, Giacomo Calesini, Davide Dardari

This paper introduces a new approach to localize user devices located in non-line-of-sight (NLOS) areas using a passive, non-reconfigurable, and frequency-selective metasurface called metaprism. By analyzing the spatial filtering of subcarriers in the orthogonal frequency division multiplexing (OFDM) signal transmitted by each user device, the base station c

Weihao Wang, Zesong Fei, Jing Guo, Salman Durrani

By exploiting the degree of freedom on the altitude, unmanned aerial vehicle (UAV) communication can provide ubiquitous communication for future wireless networks. In the case of concurrent transmission of multiple UAVs, the directional beamforming formed by multiple antennas is an effective way to reduce co-channel interference. However, factors such as air

Andrea Bacciu, Florin Cuconasu, Federico Siciliano, Fabrizio Silvestri

The emergence of large language models (LLMs) has revolutionized machine learning and related fields, showcasing remarkable abilities in comprehending, generating, and manipulating human language. However, their conventional usage through API-based text prompt submissions imposes certain limitations in terms of context constraints and external source availab

Stevan Stanovic, Benoit Gaüzère, Luc Brun

Convolutional Neural Networks (CNNs) have enabled major advances in image classification through convolution and pooling. In particular, image pooling transforms a connected discrete lattice into a reduced lattice with the same connectivity and allows reduction functions to consider all pixels in an image. However, there is no pooling that satisfies these pr

Ludwig Bothmann, Susanne Dandl, Michael Schomaker

A decision can be defined as fair if equal individuals are treated equally and unequals unequally. Adopting this definition, the task of designing machine learning (ML) models that mitigate unfairness in automated decision-making systems must include causal thinking when introducing protected attributes: Following a recent proposal, we define individuals as

Daniel Rosendo, Kate Keahey, Alexandru Costan, Matthieu Simonin

Distributed infrastructures for computation and analytics are now evolving towards an interconnected ecosystem allowing complex scientific workflows to be executed across hybrid systems spanning from IoT Edge devices to Clouds, and sometimes to supercomputers (the Computing Continuum). Understanding the performance trade-offs of large-scale workflows deploye

Jiacheng Yao, Jindan Xu, Wei Xu, Chau Yuen

Reconfigurable intelligent surface (RIS) is regarded as an important enabling technology for the sixth-generation (6G) network. Recently, modulating information in reflection patterns of RIS, referred to as reflection modulation (RM), has been proven in theory to have the potential of achieving higher transmission rate than existing passive beamforming (PBF)

Paris Koloveas, Serafeim Chatzopoulos, Christos Tryfonopoulos, Thanasis Vergoulis

In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datase

Jiacheng Yao, Zhaohui Yang, Wei Xu, Dusit Niyato

Over-the-air computation (AirComp) has recently been identified as a prominent technique to enhance communication efficiency of wireless federated learning (FL). This letter investigates the impact of channel state information (CSI) uncertainty at the transmitter on an AirComp enabled FL (AirFL) system with the truncated channel inversion strategy. To charac

Martin Huber, Sebastien Ourselin, Christos Bergeles, Tom Vercauteren

In this work, we investigate laparoscopic camera motion automation through imitation learning from retrospective videos of laparoscopic interventions. A novel method is introduced that learns to augment a surgeon's behavior in image space through object motion invariant image registration via homographies. Contrary to existing approaches, no geometric assump

Anisha Bahl, Conor C. Horgan, Mirek Janatka, Oscar J. MacCormac

Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially-resolved, spectral information. For calibration purposes, a white reference image of a highly-reflective Lambertian surface should be obtained under the same imaging conditions. Standard white references are not sterilizable, and so are unsuitable for surgical e

Aryan Singh, Pepijn Van de Ven, Ciarán Eising, Patrick Denny

Graph-based neural network models are gaining traction in the field of representation learning due to their ability to uncover latent topological relationships between entities that are otherwise challenging to identify. These models have been employed across a diverse range of domains, encompassing drug discovery, protein interactions, semantic segmentation

I. N. Ashkarin, S. Lepoutre, P. Pillet, I. I. Beterov

Registers of trapped neutral atoms, excited to Rydberg states to induce strong long-distance interactions, are extensively studied for direct applications in quantum computing. Here, we present a novel $CC\Phi$ quantum phase gate protocol based on radio-frequency-induced F\"{o}rster resonant interactions in the array of highly excited $^{87}$Rb atoms. The ex

Adrien Badré, Li Zhang, Wellington Muchero, Justin C. Reynolds

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. In this study, we compared a series of computational models for estimation of breast cancer PRS. A deep neural network (DNN) was found to outperform alternative machine learning techniques and established statis

Dominique Geissler, Stefan Feuerriegel

The 2022 Russian invasion of Ukraine was accompanied by a large-scale, pro-Russian propaganda campaign on social media. However, the strategy behind the dissemination of propaganda has remained unclear, particularly how the online discourse was strategically shaped by the propagandists' community. Here, we analyze the strategy of the Twitter community using

Taras Radul

We consider isomorphism between the idempotent measure monad based on the maximum and the addition operations and the idempotent measure monad based on the maximum and the multiplication operations. A one of the consequences of this result is the construction of a fuzzy integral based on the maximum and the addition operation. We also investigate convexities

Jakob Cordes, Andreas Schadschneider, Alexandre Nicolas

In fluid mechanics, dimensionless numbers like the Reynolds number help classify flows. We argue that such a classification is also relevant for crowd flows by putting forward the dimensionless Intrusion and Avoidance numbers.Using an extensive dataset, we show that these delineate regimes that are characterized by distinct structural signatures, best probed

Qianming Wang, Zeyu Huang, Pengchong Hu, Emilio Ciuffoli

An extremely low-background environment is a crucial requirement for any neutrinoless double beta decay experiment. Neutrons are very difficult to stop, because they can pass through the shields and activate nuclei in the detector, even inside the fiducial volume itself. Using Geant4 simulations we have studied the neutron background for N$\nu$DEx-100 and th

Hana Schiff, Alberto Corticelli, Afonso Guerreiro, Judit Romhányi

The spin point groups are finite groups whose elements act on both real space and spin space. Among these groups are the magnetic point groups in the case where the real and spin space operations are locked to one another. The magnetic point groups are central to magnetic crystallography for strong spin-orbit coupled systems and the spin point groups general

Yaguang Li, Fanqi Meng, Qixuan Wu, Dachao Yuan

Herein, NiO nanosheets supported with Ag single atoms are synthesized for photothermal CO2 hydrogenation to achieve 1065 mmol g$^{-1}$ h$^{-1}$ of CO production rate under 1 sun irradiation, revealing the unparalleled weak sunlight driven reverse water-gas shift reaction (RWGS) activity. This performance is attributed to the coupling effect of Ag-O-Ni sites

Kenji Kurosaki, Shu-ichiro Inutsuka

Numerous exoplanets with masses ranging from Earth to Neptune and radii larger than Earth have been found through observations. These planets possess atmospheres that range in mass fractions from 1% to 30%, reflecting the diversity of atmospheric mass fractions. Such diversities are supposed to be caused by differences in the formation processes or evolution

Rishabh Sharma

Loosely bound light nuclei are produced in abundance in heavy-ion collisions. There are two main possible models to explain their production mechanism - the thermal model and the coalescence model. The thermal model suggests that the light nuclei are produced from a thermal source, where they are in equilibrium with other species present in the fireball. How

Krishan Gopal

Quantum Chromodynamics (QCD) predicts that at sufficiently high temperature ($T$) and/or baryon chemical potential ($\mu_B$), the state of matter is in the form of quarks and gluons, which are no longer confined within hadrons. This deconfined state of matter is known as the Quark-Gluon Plasma (QGP). The goal of relativistic heavy-ion collision experiments i

Sue Claret, Jérôme Lemoine, Arnaud Münch

We address the exact boundary controllability of the semilinear wave equation $\partial_{tt}y-\Delta y + f(y)=0$ posed over a bounded domain $\Omega$ of $\mathbb{R}^d$. Assuming that $f$ is continuous and satisfies the condition $\limsup_{\vert r\vert\to \infty} \vert f(r)\vert /(\vert r\vert \ln^p\vert r\vert)\leq \beta$ for some $\beta$ small enough and so

Nan Chen, Evelyn Lunasin, Stephen Wiggins

Determining the optimal locations for placing extra observational measurements has practical significance. However, the exact underlying flow field is never known in practice. Significant uncertainty appears when the flow field is inferred from a limited number of existing observations via data assimilation or statistical forecast. In this paper, a new compu

Marcos L. W. Basso, Jonas Maziero, Lucas C. Céleri

The fluctuation relations, which characterize irreversible processes in Nature, are among the most important results in non-equilibrium physics. In short, these relations say that it is exponentially unlikely for us to observe a time-reversed process and, thus, establish the thermodynamic arrow of time pointing from low to high entropy. On the other hand, fu

Giorgos Papanastasiou, Nikolaos Dikaios, Jiahao Huang, Chengjia Wang

Medical imaging is a key component in clinical diagnosis, treatment planning and clinical trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance gains in medical image analysis (MIA) over the last years. CNNs can efficiently model local pixel interactions and be trained on small-scale MI data. The main disadvantage of typic

Weiyue Zhao, Xin Li, Zhan Peng, Xianrui Luo

Video stabilization refers to the problem of transforming a shaky video into a visually pleasing one. The question of how to strike a good trade-off between visual quality and computational speed has remained one of the open challenges in video stabilization. Inspired by the analogy between wobbly frames and jigsaw puzzles, we propose an iterative optimizati

David Heson, Shannon Starr, Jacob Thornton

We demonstrate a violation of the ``ferromagnetic ordering of energy levels'' conjecture (FOEL) for even length spin rings. The FOEL conjecture was a guess made by Nachtergaele, Spitzer and an author for the Heisenberg model on certain graphs: a family of inequalities, the first of which is the statement that the spectral gap of the Heisenberg model equals t

Badredine Benhellal, Konstantin Pankrashkin, Mahdi Zreik

We study the self-adjointness of the two-dimensional Dirac operator coupled with electrostatic and Lorentz scalar shell interactions of constant strength $\varepsilon$ and $\mu$ supported on a closed Lipschitz curve. Namely, we present several new explicit ranges of $\varepsilon$ and $\mu$ for which there is a unique self-adjoint realization with domain incl

Per Sebastian Skardal, Juan G. Restrepo

Identifying disturbances in network-coupled dynamical systems without knowledge of the disturbances or underlying dynamics is a problem with a wide range of applications. For example, one might want to know which nodes in the network are being disturbed and identify the type of disturbance. Here we present a model-free method based on machine learning to ide

Stefano Ardizzoni, Irene Saccani, Luca Consolini, Marco Locatelli

The pebble motion on trees (PMT) problem consists in finding a feasible sequence of moves that repositions a set of pebbles to assigned target vertices. This problem has been widely studied because, in many cases, the more general Multi-Agent path finding (MAPF) problem on graphs can be reduced to PMT. We propose a simple and easy to implement procedure, whi

Peng-Xiong Ma, Bo-Hao Duan, Xin Xu, Ke-Wen Zhang

The Giant Radio Array for Neutrino Detection (GRAND) is an envisioned observatory of ultra-high-energy neutrinos, cosmic rays, and gamma rays, with energies above 100 PeV. GRAND targets the radio signals emitted by extensive air showers induced by the interaction of ultra-high-energy particles in the atmosphere, using an array of 200,000 radio antennas split

Patrick Gérard

We identify the zero dispersion limit of a solution of the Benjamin--Ono equation on the line corresponding to every initial datum in $L^2(\R)\cap L^\infty(\R )$. We infer a maximum principle and a local smoothing property for this limit. The proof is based on an explicit formula for the Benjamin--Ono equation and on the combination of calculations in the sp

Emiru Tsunoo, Hayato Futami, Yosuke Kashiwagi, Siddhant Arora

Although frame-based models, such as CTC and transducers, have an affinity for streaming automatic speech recognition, their decoding uses no future knowledge, which could lead to incorrect pruning. Conversely, label-based attention encoder-decoder mitigates this issue using soft attention to the input, while it tends to overestimate labels biased towards it

Kristof Dekimpe

In this paper, we study degenerate almost complex surfaces in the semi-Riemannian nearly K\"ahler $\mathrm{SL}_2\mathbb{R}\times \mathrm{SL}_2\mathbb{R}$. The geometry of these surfaces depends on the almost product structure of the ambient space and one can distinguish two distinct cases. The geometry of these surfaces is influenced by the almost product st

Runzhen Xue, Dengke Han, Mingyu Yan, Mo Zou

Heterogeneous graph neural networks (HGNNs) have emerged as powerful algorithms for processing heterogeneous graphs (HetGs), widely used in many critical fields. To capture both structural and semantic information in HetGs, HGNNs first aggregate the neighboring feature vectors for each vertex in each semantic graph and then fuse the aggregated results across

Sebastian Steinhäuser, Timm Treskatis, Stefan Turek, Thomas Voigtmann

We show how residual stresses emerge in a visco-elastic material as a signature of its past flow history, through an interplay between flow-modified microscopic relaxation and macroscopic features of the flow. Long-lasting temporal-history dependence of the microscopic dynamics and nonlinear rheology are incorporated through the mode-coupling theory of the g

Shahnawaz A. Adil, Upala Mukhopadhyay, Anjan A. Sen, Sunny Vagnozzi

Early data from the James Webb Space Telescope (JWST) has uncovered the existence of a surprisingly abundant population of very massive galaxies at extremely high redshift, which are hard to accommodate within the standard $\Lambda$CDM cosmology. We explore whether the JWST observations may be pointing towards more complex dynamics in the dark energy (DE) se

Yanhui Zhang, Li Liu, Xianhong Xie

Negacyclic BCH codes are an important subclass of negacyclic codes and are the best linear codes in most cases, but their parameters are hard to determine. In this paper, we mainly study two types of negacyclic BCH codes of length $n=\frac{q^{m}-1}{4},\frac{q^{m}+1}{4}$, and give their dimensions and the lower bound on their minimum distance. Furthermore, we

Wolfgang Boettcher, Lukas Hoyer, Ozan Unal, Ke Li

Depth estimation is one of the essential tasks to be addressed when creating mobile autonomous systems. While monocular depth estimation methods have improved in recent times, depth completion provides more accurate and reliable depth maps by additionally using sparse depth information from other sensors such as LiDAR. However, current methods are specifical

Baiping Xiong, Zaichen Zhang, Jiangzhou Wang

Large-scale reconfigurable intelligent surface (RIS) can effectively enhance the performance of millimeter wave (mmWave) unmanned aerial vehicle (UAV) to ground communication link with obstructed line-of-sight (LoS) path by exploiting more reflecting units. However, the non-negligible array dimension of large-scale RIS and the mobile property of the terminal

Muhammad Danyal Khan, Raheem Ali, Arshad Aziz

Call Centers have huge amount of audio data which can be used for achieving valuable business insights and transcription of phone calls is manually tedious task. An effective Automated Speech Recognition system can accurately transcribe these calls for easy search through call history for specific context and content allowing automatic call monitoring, impro

Bayram Tekin

I describe parts of my joint work with S. Deser [March 19, 1931 - April 21, 2023] which started when I was working as a post-doc at Brandeis University in 2001. Our work was mostly, but not exclusively, on conserved charges of higher curvature theories of gravity. I also describe some recent developments, such as expressing the conserved charges in terms of

Lucas Einig, Jérôme Pety, Antoine Roueff, Paul Vandame

Context. The availability of large bandwidth receivers for millimeter radio telescopes allows the acquisition of position-position-frequency data cubes over a wide field of view and a broad frequency coverage. These cubes contain much information on the physical, chemical, and kinematical properties of the emitting gas. However, their large size coupled with

Mohd Shariq, Praveen Mathil, Jitender Kumar

Let $R$ be a commutative ring with unity. The weakly zero-divisor graph $W\Gamma(R)$ of the ring $R$ is the simple undirected graph whose vertices are nonzero zero-divisors of $R$ and two vertices $x$, $y$ are adjacent if and only if there exists $r\in {\rm ann}(x)$ and $s \in {\rm ann}(y)$ such that $rs =0$. The zero-divisor graph of a ring is a spanning su

Yifan Wang, Peijie Sun, Min Zhang, Qinglin Jia

Conversion rate prediction is critical to many online applications such as digital display advertising. To capture dynamic data distribution, industrial systems often require retraining models on recent data daily or weekly. However, the delay of conversion behavior usually leads to incorrect labeling, which is called delayed feedback problem. Existing work

Cosimo Bambi, Askar B. Abdikamalov, Honghui Liu, Shafqat Riaz

The past 10 years have seen tremendous progress in our capability of testing General Relativity in the strong field regime with black hole observations. 10 years ago, the theory of General Relativity was almost completely unexplored in the strong field regime. Today, we have gravitational wave data of the coalescence of stellar-mass black holes, radio images

Rishabh Jain, Andrei Barcovschi, Mariam Yiwere, Peter Corcoran

Automatic Speech Recognition (ASR) systems often struggle with transcribing child speech due to the lack of large child speech datasets required to accurately train child-friendly ASR models. However, there are huge amounts of annotated adult speech datasets which were used to create multilingual ASR models, such as Whisper. Our work aims to explore whether

Bertille Follain, Francis Bach

Representation learning plays a crucial role in automated feature selection, particularly in the context of high-dimensional data, where non-parametric methods often struggle. In this study, we focus on supervised learning scenarios where the pertinent information resides within a lower-dimensional linear subspace of the data, namely the multi-index model. I