March 2023 arXiv papers — page 65

Ignacio Rocco, Iurii Makarov, Filippos Kokkinos, David Novotny

We present a method for fast 3D reconstruction and real-time rendering of dynamic humans from monocular videos with accompanying parametric body fits. Our method can reconstruct a dynamic human in less than 3h using a single GPU, compared to recent state-of-the-art alternatives that take up to 72h. These speedups are obtained by using a lightweight deformati

Yushi Hu, Benlin Liu, Jungo Kasai, Yizhong Wang

Despite thousands of researchers, engineers, and artists actively working on improving text-to-image generation models, systems often fail to produce images that accurately align with the text inputs. We introduce TIFA (Text-to-Image Faithfulness evaluation with question Answering), an automatic evaluation metric that measures the faithfulness of a generated

Jared Miller, Mario Sznaier

This work quantifies the safety of trajectories of a dynamical system by the perturbation intensity required to render a system unsafe (crash into the unsafe set). Computation of this measure of safety is posed as a peak-minimizing optimal control problem. Convergent lower bounds on the minimal peak value of controller effort are computed using polynomial op

Alessio Di Prisa

By considering a particular type of invariant Seifert surfaces we define a homomorphism $\Phi$ from the (topological) equivariant concordance group of directed strongly invertible knots $\widetilde{\mathcal{C}}$ to a new equivariant algebraic concordance group $\widetilde{\mathcal{G}}^{\mathbb{Z}}$. We prove that $\Phi$ lifts both Miller and Powell's equivar

Xuhui Wang, Boxuan Li, Liqin Zhou, Long Chen

A single material achieving multiple topological phases can provide potential application for topological spintronics, whereas the candidate materials are very limited. Here, we report the structure, physical properties, and possible emergence of multiple topological phases in the newly discovered, air-stable EuCuBi single crystal. EuCuBi crystallizes in a h

Fan Chen, Xiying Yuan

Graph $G$ is $H$-saturated if $H$ is not a subgraph of $G$ and $H$ is a subgraph of $G+e$ for any edge $e$ not in $G$. The saturation number for a graph $H$ is the minimal number of edges in any $H$-saturated graph of order $n$. In this paper, the saturation number for $K_p\cup (t-1)K_q$ ($t\geqslant 3$ and $2\leqslant p<q$) is determined, and the extremal g

Luke Mosley, Tak-Shing T. Chan, Alex Gibberd

The concepts of sparsity, and regularised estimation, have proven useful in many high-dimensional statistical applications. Dynamic factor models (DFMs) provide a parsimonious approach to modelling high-dimensional time series, however, it is often hard to interpret the meaning of the latent factors. This paper formally introduces a class of sparse DFMs wher

Brady Lund, Ting Wang, Nishith Reddy Mannuru, Bing Nie

This paper discusses OpenAIs ChatGPT, a generative pre-trained transformer, which uses natural language processing to fulfill text-based user requests (i.e., a chatbot). The history and principles behind ChatGPT and similar models are discussed. This technology is then discussed in relation to its potential impact on academia and scholarly research and publi

Baraa Shammout, Leon Karpa, Silke Ospelkaus, Eberhard Tiemann

A model for photoassociation of ultracold atoms and molecules is presented, and applied to the case of $^{39}$K and $^{23}$Na$^{39}$K bosonic particles. The model relies on the assumption that photoaossociation is dominated by long-range atom-molecule interactions, well outside the chemical bond region. The frequency of the photoassociation laser is chosen c

A. Banderchuk, D. Coutinho, E. Camponogara

This paper proposes a control strategy consisting of a robust controller and an Echo State Network (ESN) based control law for stabilizing a class of uncertain nonlinear discrete-time systems subject to persistent disturbances. Firstly, the robust controller is designed to ensure that the closed-loop system is Input-to-State Stable (ISS) with a guaranteed st

Qihao Peng, Hong Ren, Mianxiong Dong, Maged Elkashlan

Resource allocation is conceived for cell-free (CF) massive multi-input multi-output (MIMO)-aided ultra-reliable and low latency communication (URLLC) systems. Specifically, to support multiple devices with limited pilot overhead, pilot reuse among the users is considered, where we formulate a joint pilot length and pilot allocation strategy for maximizing t

Hongkuan Zhou, Aifen Sui, Letian Shi, Yinxian Li

In recent times, there has been a growing focus on end-to-end autonomous driving technologies. This technology involves the replacement of the entire driving pipeline with a single neural network, which has a simpler structure and faster inference time. However, while this approach reduces the number of components in the driving pipeline, it also presents ch

Cornelia Ott, Hedongliang Liu, Antonia Wachter-Zeh

The sum-rank metric arises as an algebraic approach for coding in MIMO block-fading channels and multishot network coding. Codes designed in the sum-rank metric have raised interest in applications such as streaming codes, robust coded distributed storage systems and post-quantum secure cryptosystems. The sum-rank metric can be seen as a generalization of th

Otman Benchekroun, Jiayi Eris Zhang, Siddhartha Chaudhuri, Eitan Grinspun

We propose a reduced-space elasto-dynamic solver that is well suited for augmenting rigged character animations with secondary motion. At the core of our method is a novel deformation subspace based on Linear Blend Skinning that overcomes many of the shortcomings prior subspace methods face. Our skinning subspace is parameterized entirely by a set of scalar

Hyat Huang, Jutta Kunz, Jinbo Yang, Cong Zhang

The geodesics of the Ellis-Bronnikov wormhole with two parameters are studied. The asymmetric wormhole has only one light ring and one innermost stable circular orbit located on one side of the wormhole throat. Consequently, certain light rays can be reflected back by the wormhole. Additionally, the same wormhole can have different appearances on both sides

Sukrut Rao, Moritz Böhle, Bernt Schiele

Deep neural networks are very successful on many vision tasks, but hard to interpret due to their black box nature. To overcome this, various post-hoc attribution methods have been proposed to identify image regions most influential to the models' decisions. Evaluating such methods is challenging since no ground truth attributions exist. We thus propose thre

Jaehyeok Lee, Jae-Suk Park

We develop Morita theory of monoids in a closed symmetric monoidal category, in the context of enriched category theory.

Shrabani Kumar, G. C. Dewangan, K. P. Singh, P. Gandhi

$\require{mediawiki-texvc}$ We study accretion disk emission from eight Seyfert $1 - 1.5$ active galactic nuclei (AGN) using far ultra-violet ($1300-1800$ ${\AA}$) slit-less grating spectra acquired with AstroSat/UVIT. We correct for the Galactic and intrinsic extinction, contamination from the host galaxies, narrow and broad-line regions, Fe II emission and

Liang Li, Pengfei Zhao

Adaptive network pruning approach has recently drawn significant attention due to its excellent capability to identify the importance and redundancy of layers and filters and customize a suitable pruning solution. However, it remains unsatisfactory since current adaptive pruning methods rely mostly on an additional monitor to score layer and filter importanc

Qiaoqiao Wei, Hui Zhang, Jun-Hai Yong

Interactive image segmentation aims at obtaining a segmentation mask for an image using simple user annotations. During each round of interaction, the segmentation result from the previous round serves as feedback to guide the user's annotation and provides dense prior information for the segmentation model, effectively acting as a bridge between interaction

Lingzi Zhang, Xin Zhou, Zhiwei Zeng, Zhiqi Shen

Current multimodal sequential recommendation models are often unable to effectively explore and capture correlations among behavior sequences of users and items across different modalities, either neglecting correlations among sequence representations or inadequately capturing associations between multimodal data and sequence data in their representations. T

Alexandra Cote, J. Eddie Slimak, Astha Sethi, Dalmau Reig-i-Plessis

The sesquioxide, Ce$_{2}$O$_{3}$, has been a material of intense interest in recent years due to reports of an anomalous giant magnetodielectric effect and emergent mixed crystal field-phonon (vibronic) excitations below a putative antiferromagnetic transition at T$_{N}$ = 6.2 K. The claim of long-range magnetic order in this material is based on heat capaci

Hendrik Müller, Andrei Lobanov

Recently multiscale imaging approaches such as DoG-HiT were developed to solve the VLBI imaging problem and showed a promising performance: they are fast, accurate, unbiased and automatic. We extend the multiscalar imaging approach to polarimetric imaging, reconstructions of dynamically evolving sources and finally to dynamic polarimetric reconstructions. Th

Michele Boreale, Luisa Collodi, Daniele Gorla

In the context of the stream calculus, we present an Implicit Function Theorem (IFT) for polynomial systems, and discuss its relations with the classical IFT from calculus. In particular, we demonstrate the advantages of the stream IFT from a computational point of view, and provide a few example applications where its use turns out to be valuable.

Yihua Zheng, Michael Xapsos, Insoo Jun, T. P. O'Brien

As miniaturized spacecraft (e.g., cubesats and smallsats) and instrumentation become an increasingly indispensable part of space exploration and scientific investigations, it is important to understand their potential susceptibility to space weather impacts resulting from the sometimes volatile space environment. There are multitude of complexities involved

Young-Pil Choi, Byung-Hoon Hwang

This paper is devoted to a rigorous derivation of the isentropic Euler-alignment system with singular communication weights $\phi_\alpha(x) = |x|^{-\alpha}$ for some $\alpha > 0$. We consider a kinetic BGK-alignment model consisting of a kinetic BGK-type equation with a singular Cucker-Smale alignment force. By taking into account a small relaxation paramete

William Merrill, Nikolaos Tsilivis, Aman Shukla

Grokking is a phenomenon where a model trained on an algorithmic task first overfits but, then, after a large amount of additional training, undergoes a phase transition to generalize perfectly. We empirically study the internal structure of networks undergoing grokking on the sparse parity task, and find that the grokking phase transition corresponds to the

Lenny Jones

Let $f(x)\in {\mathbb Z}[x]$ be a monic polynomial of degree $N$ that is irreducible over ${\mathbb Q}$. We say $f(x)$ is \emph{monogenic} if $\Theta=\{1,\theta,\theta^2,\ldots ,\theta^{N-1}\}$ is a basis for the ring of integers ${\mathbb Z}_K$ of $K={\mathbb Q}(\theta)$, where $f(\theta)=0$. If $\Theta$ is not a basis for ${\mathbb Z}_K$, we say that $f(x)

Dimitri Jordan Kenne

The one-dimensional pseudo Leja sequences introduced in \cite{bialas2012pseudo}, as an alternative to Leja sequences, provides us with good interpolation nodes for the approximation of holomorphic functions. We propose a definition of multidimensional pseudo Leja sequences associated to a compact set $K$ of the complex space $\mathbb{C}^p$ which generalises

Jiaozi Wang, Jochen Gemmer

We study the time evolution of a single qubit in contact with a bath, within the framework of projection operator methods. Employing the so-called modified Redfield theory which also treats energy conserving interactions non-perturbatively, we are able to study the regime beyond the scope of the ordinary approach. Reduced equations of motion for the qubit ar

Guru Dutt Gupt, Yousef Kareri, James Hester, Clemens Ulrich

We report the detailed analysis of temperature dependent neutron diffraction pattern of the Cr$_2$CoAl inverse Heusler alloy and unveil the magnetic structure up to the phase transition as well as its fully compensated ferrimagnetic nature. The Rietveld refinement of the diffraction pattern using the space group I$\bar4${\it m}2 confirm the inverse tetragona

Lluis Arola-Fernandez, Lucas Lacasa

Many empirical time series are genuinely symbolic: examples range from link activation patterns in network science, DNA coding or firing patterns in neuroscience to cryptography or combinatorics on words. In some other contexts, the underlying time series is actually real-valued, and symbolization is applied subsequently, as in symbolic dynamics of chaotic s

Young-Pil Choi, Byung-Hoon Hwang

We establish the global-in-time existence of weak solutions to a variant of the BGK model proposed by Bouchut [J. Stat. Phys., 95, (1999), 113--170] which leads to the barotropic Euler equations in the hydrodynamic limit. Our existence theory makes the quantified estimates of hydrodynamic limit from the BGK-type equations to the multi-dimensional barotropic

Zaid Khan, Yun Fu

Contrastive vision-language models (e.g. CLIP) are typically created by updating all the parameters of a vision model and language model through contrastive training. Can such models be created by a small number of parameter updates to an already-trained language model and vision model? The literature describes techniques that can create vision-language mode

Andrea Giusti, Marco Coraggio, Mario di Bernardo

Geometric pattern formation is an important emergent behavior in many applications involving large-scale multi-agent systems, such as sensor networks deployment and collective transportation. Attraction/repulsion virtual forces are the most common control approach to achieve such behavior in a distributed and scalable manner. Nevertheless, for most existing

Walter Bridges, Benjamin Brindle, Kathrin Bringmann, Johann Franke

Recently, Debruyne and Tenenbaum proved asymptotic formulas for the number of partitions with parts in $\mathcal{L}\subset\mathbb{N}$ ($\gcd(\mathcal{L})=1$) and good analytic properties of the corresponding zeta function, generalizing work of Meinardus. In this paper, we extend their work to prove asymptotic formulas if $\mathcal{L}$ is a multiset of intege

Donggyu Lee, Sangwon Jung, Taesup Moon

Most continual learning (CL) algorithms have focused on tackling the stability-plasticity dilemma, that is, the challenge of preventing the forgetting of previous tasks while learning new ones. However, they have overlooked the impact of the knowledge transfer when the dataset in a certain task is biased - namely, when some unintended spurious correlations o

Vincent Corlay, Jean-Christophe Sibel

In the context of railway systems, the application performance can be very critical and the radio conditions not advantageous. Hence, the communication problem parameters include both a survival time stemming from the application layer and a channel error probability stemming from the PHY layer. This paper proposes to consider the framework of Markov Decisio

Pranjal Ralegankar

Primordial magnetic fields (PMF) can enhance baryon perturbations on scales below the photon mean free path. However, a magnetically driven baryon fluid becomes turbulent near recombination, thereby damping out baryon perturbations below the turbulence scale. In this Letter, we show that the initial growth in baryon perturbations gravitationally induces grow

Nathan Leroux, Jan Finkbeiner, Emre Neftci

Transformers are state-of-the-art networks for most sequence processing tasks. However, the self-attention mechanism often used in Transformers requires large time windows for each computation step and thus makes them less suitable for online signal processing compared to Recurrent Neural Networks (RNNs). In this paper, instead of the self-attention mechanis

Zhiqiang Dong, Jiale Cao, Rao Muhammad Anwer, Jin Xie

We propose an end-to-end one-step person search approach with learnable proposals, named LEAPS. Given a set of sparse and learnable proposals, LEAPS employs a dynamic person search head to directly perform person detection and corresponding re-id feature generation without non-maximum suppression post-processing. The dynamic person search head comprises a de

Yunjie He, Mojtaba Nayyeri, Bo Xiong, Yuqicheng Zhu

Answering first-order logical (FOL) queries over knowledge graphs (KG) remains a challenging task mainly due to KG incompleteness. Query embedding approaches this problem by computing the low-dimensional vector representations of entities, relations, and logical queries. KGs exhibit relational patterns such as symmetry and composition and modeling the patter

Fuwang Dong, Fan Liu, Shihang Lu, Yifeng Xiong

Wireless sensing has been recognized as a key enabling technology for numerous emerging applications. For decades, the sensing performance was mostly evaluated from a reliability perspective, with the efficiency aspect widely unexplored. Motivated from both backgrounds of rate-distortion theory and optimal sensing waveform design, a novel efficiency metric,

Niklas Hofmann, Leonard Weigl, Johannes Gradl, Neeraj Mishra

Ultrafast charge separation after photoexcitation is a common phenomenon in various van-der-Waals (vdW) heterostructures with great relevance for future applications in light harvesting and detection. Theoretical understanding of this phenomenon converges towards a coherent mechanism through charge transfer states accompanied by energy dissipation into stron

Konrad Habel, Fabian Deuser, Norbert Oswald

Sports analytics benefits from recent advances in machine learning providing a competitive advantage for teams or individuals. One important task in this context is the performance measurement of individual players to provide reports and log files for subsequent analysis. During sport events like basketball, this involves the re-identification of players dur

Yuanyuan Yang, Bowen Xu, Yinjie Li, Sören Schwertfeger

Benchmarking Simultaneous Localization and Mapping (SLAM) algorithms is important to scientists and users of robotic systems alike. But through their many configuration options in hardware and software, SLAM systems feature a vast parameter space that scientists up to now were not able to explore. The proposed SLAM Hive Benchmarking Suite is able to analyze

Donghwi Jung, Jae-Kyung Cho, Younghwa Jung, Soohyun Shin

We propose a deep learning-based LiDAR odometry estimation method called LoRCoN-LO that utilizes the long-term recurrent convolutional network (LRCN) structure. The LRCN layer is a structure that can process spatial and temporal information at once by using both CNN and LSTM layers. This feature is suitable for predicting continuous robot movements as it use

I. L. Buchbinder, A. P. Isaev, M. A. Podoinitsyn, S. A. Fedoruk

We develop a generalization of the Wigner scheme for constructing the relativistic fields corresponding to irreducible representations of the four-dimensional Poincar\'{e} group with infinite spin. The fields are parameterized by a vector and an additional commuting vector or spinor variable. The equations of motion for fields of infinite spin are derived in

Fabian Deuser, Konrad Habel, Norbert Oswald

Cross-View Geo-Localisation is still a challenging task where additional modules, specific pre-processing or zooming strategies are necessary to determine accurate positions of images. Since different views have different geometries, pre-processing like polar transformation helps to merge them. However, this results in distorted images which then have to be

Kathrin Egberts, Constantin Steppa, Karol Pawel Peters

Gamma-ray observations have recently shifted the focus to higher and higher energies, with capable ground-based instruments enabling measurements in the TeV to PeV domain. While a clear prevalence of diffuse emission is observed in the GeV sky, energy-dependent cosmic-ray transport suggests a reversal of this hierarchy at higher energies. Measurements, howev

Zhening Yang, Hui Sun, Zi-Kui Liu, Allison M. Beese

In functionally graded materials (FGMs) fabricated using directed energy deposition (DED) additive manufacturing (AM), cracks may form due to interdendritic stress during solidification, the formation of intermetallics, or the buildup of residual stresses. This study builds on our previously proposed concept of three-alloy FGM system feasibility diagrams for

Vasileios Sevetlidis, George Pavlidis, Spyridon Mouroutsos, Antonios Gasteratos

This study proposes a novel approach for solving the PU learning problem based on an anomaly-detection strategy. Latent encodings extracted from positive-labeled data are linearly combined to acquire new samples. These new samples are used as embeddings to increase the density of positive-labeled data and, thus, define a boundary that approximates the positi

Qi-Bin Sun, Sheng-Bang Qian, Li-Ying Zhu, Wen-Ping Liao

Super-orbital signals and negative superhumps are thought to be related to the reverse precession of the nodal line in a tilted disk, but the evidence is lacking. Our results provide new evidence for the precession of the tilted disk. Based on the TESS and K2 photometry, we investigate the super-orbital signals, negative superhumps, positive superhumps, and

Qinyan Zhou, Hongbin Fang, Zhihai Bi, Jian Xu

The development of versatile robots capable of traversing challenging and irregular environments is of increasing interest in the field of robotics, and metameric robots have been identified as a promising solution due to their slender, deformable bodies. Inspired by the effective locomotion of earthworms, earthworm-like robots capable of both rectilinear an

Mizuki Oikawa

Let $G$ be a group. We give a categorical definition of the $G$-equivariant $\alpha$-induction associated with a given $G$-equivariant Frobenius algebra in a $G$-braided multitensor category, which generalizes the $\alpha$-induction for $G$-twisted representations of conformal nets. For a given $G$-equivariant Frobenius algebra in a spherical $G$-braided fus

Lénaïc Chizat

We study a general formulation of regularized Wasserstein barycenters that enjoys favorable regularity, approximation, stability and (grid-free) optimization properties. This barycenter is defined as the unique probability measure that minimizes the sum of entropic optimal transport (EOT) costs with respect to a family of given probability measures, plus an

MohammadHossein Bateni, Hossein Esfandiari, Hendrik Fichtenberger, Monika Henzinger

In fully dynamic clustering problems, a clustering of a given data set in a metric space must be maintained while it is modified through insertions and deletions of individual points. In this paper, we resolve the complexity of fully dynamic $k$-center clustering against both adaptive and oblivious adversaries. Against oblivious adversaries, we present the f

Samir Kabbaj, Rafik Karkri, Zoubeir Hicham

In this paper, we give a characterization and a some properties of a besselian sequences, which allows us to build some examples of a besselian Schauder frames. Also for a reflexive Banach spaces (with a besselian Schauder frames) we give some characterizations.

Cong Meng, Zhibin Guo

We establish a link between vorticity wave interaction and $\mathcal{PT}$-symmetry breaking in shear flow instabilities. The minimal dynamical system for two coupled counter-propagating vorticity waves is shown to be a non-Hermitian system that exhibits a saddle-node exceptional point. The mechanism of phase-locking and mutual growth of vorticity waves is th

Akanksha Khandelwal, Rishikesh Sharma, Abhijit Chakraborty, Priyanka Chaturvedi

We present the discovery of a transiting massive giant planet around TOI-4603, a sub-giant F-type star from NASA's Transiting Exoplanet Survey Satellite (TESS). The newly discovered planet has a radius of $1.042^{+0.038}_{-0.035}$ $R_{J}$, and an orbital period of $7.24599^{+0.00022}_{-0.00021}$ days. Using radial velocity measurements with the PARAS {and TR

Zhenqian Wu, Xiaoyuan Li, Yazhou Ren, Xiaorong Pu

The accuracy of facial expression recognition is typically affected by the following factors: high similarities across different expressions, disturbing factors, and micro-facial movement of rapid and subtle changes. One potentially viable solution for addressing these barriers is to exploit the neutral information concealed in neutral expression images. To

Bo Yang, Ishan Khatri, Michael Happold, Chulong Chen

As autonomous vehicles and advanced driving assistance systems have entered wider deployment, there is an increased interest in building robust perception systems using radars. Radar-based systems are lower cost and more robust to adverse weather conditions than their LiDAR-based counterparts; however the point clouds produced are typically noisy and sparse

Davi Rodrigues, Riccardo Tomasello, Giulio Siracusano, Mario Carpentieri

We have designed a passive spintronic diode based on a single skyrmion stabilized in a magnetic tunnel junction and studied its dynamics induced by voltage-controlled anisotropy (VCMA) and Dzyaloshinskii-Moriya interaction (VDMI). We have demonstrated that the sensitivity (rectified voltage over input microwave power) with realistic physical parameters and g

Zahra Tabatabaei, Adrian colomer, Kjersti Engan, Javier Oliver

According to GLOBOCAN 2020, prostate cancer is the second most common cancer in men worldwide and the fourth most prevalent cancer overall. For pathologists, grading prostate cancer is challenging, especially when discriminating between Grade 3 (G3) and Grade 4 (G4). This paper proposes a Self-Supervised Learning (SSL) framework to classify prostate histopat

Yuto Hosaka, Ramin Golestanian, Abdallah Daddi-Moussa-Ider

We theoretically and computationally study the low-Reynolds-number hydrodynamics of a linear active microswimmer surfing on a compressible thin fluid layer characterized by an odd viscosity. Since the underlying three-dimensional fluid is assumed to be very thin compared to any lateral size of the fluid layer, the model is effectively two-dimensional. In the

Kunkun Wang, Lei Xiao, Haiqing Lin, Wei Yi

Exceptional points (EPs) of non-Hermitian (NH) systems have recently attracted increasing attention due to their rich phenomenology and intriguing applications. Compared to the predominantly studied second-order EPs, higher-order EPs have been assumed to play a much less prominent role because they generically require the tuning of more parameters. Here we e

Hyunseung Kim, Haeyeon Choi, Dongju Kang, Won Bo Lee

The goal of most materials discovery is to discover materials that are superior to those currently known. Fundamentally, this is close to extrapolation, which is a weak point for most machine learning models that learn the probability distribution of data. Herein, we develop reinforcement learning-guided combinatorial chemistry, which is a rule-based molecul

Sohail Farhangi

We prove a generalization of van der Corput's difference theorem for sequences of vectors in a Hilbert space. This generalization is obtained by establishing a connection between sequences of vectors in the first Hilbert space with a vector in a new Hilbert space whose spectral type with respect to a certain unitary operator is absolutely continuous with res

Michele Pascale, Vivek Muthurangu, Javier Montalt Tordera, Heather E Fitzke

Three-dimensional (3D) imaging is popular in medical applications, however, anisotropic 3D volumes with thick, low-spatial-resolution slices are often acquired to reduce scan times. Deep learning (DL) offers a solution to recover high-resolution features through super-resolution reconstruction (SRR). Unfortunately, paired training data is unavailable in many

Heinrich Freistuhler

This paper shows that in second-order hyperbolic systems of partial differential equations proposed in authors' earlier paper (J. Math. Phys. 59 (2018)) for modelling the relativistic dynamics of barotropic fluids in the presence of viscosity and heat conduction, shock waves of arbitrary strength have smooth, monotone dissipation profiles. The results and ar

Caixia Zhou, Yaping Huang, Mengyang Pu, Qingji Guan

Deep learning-based edge detectors heavily rely on pixel-wise labels which are often provided by multiple annotators. Existing methods fuse multiple annotations using a simple voting process, ignoring the inherent ambiguity of edges and labeling bias of annotators. In this paper, we propose a novel uncertainty-aware edge detector (UAED), which employs uncert

Sebastian Baran, Corina Constantinescu, Zbigniew Palmowski

We find the asymptotics of the value function maximizing the expected utility of discounted dividend payments of an insurance company whose reserves are modeled as a classical Cram\'er risk process, with exponentially distributed claims, when the initial reserves tend to infinity. We focus on the power and logarithmic utility functions. We perform some numer

Rina Anno, Sergey Arkhipov, Timothy Logvinenko

We define $A_{\infty}$-structures -- algebras, coalgebras, modules, and comodules -- in an arbitrary monoidal DG category or bicategory by rewriting their definitions in terms of unbounded twisted complexes. We develop new notions of strong homotopy unitality and bimodule homotopy unitality to work in this level of generality. For a strong homotopy unital $A

Matthew Brehmer, Maxime Cordeil, Christophe Hurter, Takayuki Itoh

We propose a half-day workshop at IEEE VIS 2023 on the topic of communication and collaboration around data. Specifically, we aim to gather researchers interested on multimodal, synchronous, and remote or hybrid forms of communication and collaboration within organizational and educational settings. This topic lies at the intersection of data visualization,

Hans Georg Schaatun, Ben David Normann, Einar Leite Austnes, Simon Ingebrigtsen

Gravitational lensing refers to the deflection of light by the gravity of celestial bodies, often predominantly composed of dark matter. Seen through a gravitational lens, the images of distant galaxies appear distorted. In this paper we discuss simulation of the image distortion by gravitational lensing. The objective is to enhance our understanding of how

Jose Acevedo, Grigoriy Blekherman

For fixed degree and increasing number of variables the dimension of the vector space of $n$-variate real symmetric homogeneous polynomials (forms) of degree $d$ stabilizes. We study the limits of the cones of symmetric nonnegative polynomials and symmetric sums of squares, when expressed in power-mean or monomial-mean basis. These limits correspond to forms

Matilde Lalin, Anwesh Ray

We consider the family of undirected Cayley graphs associated with odd cyclic groups, and study statistics for the eigenvalues in their spectra. Our results are motivated by analogies between arithmetic geometry and graph theory.

Qiao Jiang, Peng Hu, Jun Wang, Dezhuan Han

Polarization singularities including bound states in the continuum (BICs) and circularly polarized states have provided promising opportunities in the manipulation of light waves. Previous studies show that BICs in photonic crystal slabs are protected by $C_{2}T$ symmetry and hence normally exist on the high-symmetry lines of momentum space. Here, we propose

Zien Chen, Kairui Ye, Mengchao Zhang

Motivated by the collisionless cold dark matter small scale structure problem, we propose an asymmetric dark matter model where dark matter particle interact with each other via a massive dark gauge boson. This model easily avoid the strong limits from cosmic microwave background (CMB) observation, and have a large parameter space to be consistent with small

Marc K. Ritter, Yuriel Núñez Fernández, Markus Wallerberger, Jan von Delft

Multivariate functions of continuous variables arise in countless branches of science. Numerical computations with such functions typically involve a compromise between two contrary desiderata: accurate resolution of the functional dependence, versus parsimonious memory usage. Recently, two promising strategies have emerged for satisfying both requirements:

Ivan Panin, Dimitrii Tyurin

let $R$ be a regular local ring of a mixed characteristic $(0,p)$ where $p\neq 2$ is a prime number. Suppose that the quotient ring $R/pR$ is also regular. Fix a non-degenerate Pfister form $Q(T_{1},\ldots,T_{2^{m}})$ over $R$ and an invertible element $c$ in $R$. Then the equation $Q(T_{1},\ldots,T_{2^{m}})=c$ has a solution over $R$ if and only if it has a

Johannes V. Roth, Lorenz von Smekal

We present first calculations of critical spectral functions of the relaxational Models A, B, and C in the Halperin-Hohenberg classification using a real-time formulation of the functional renormalization group (FRG). We revisit the prediction by Son and Stephanov that the linear coupling of a conserved density to the non-conserved order parameter of Model A

Sung-Feng Huang, Chia-ping Chen, Zhi-Sheng Chen, Yu-Pao Tsai

Personalized TTS is an exciting and highly desired application that allows users to train their TTS voice using only a few recordings. However, TTS training typically requires many hours of recording and a large model, making it unsuitable for deployment on mobile devices. To overcome this limitation, related works typically require fine-tuning a pre-trained

Jing-Jing Yang, Wei Hao, Xiaoyu Wang, De-Min Li

Motivated by the recently observed $D_{s0}(2590)$ state by LHCb, we investigate the mass spectrum and the strong decay properties of the charmed-strange mesons within Godfrey-Isgur model considering the coupled-channel effects. Our results support that $D_{s0}^*(2317)$ and $D_{s1}(2460)$ can be interpreted as the $D_{s}(1^3P_0)$ and $D_{s}(1^3P_1)$ states wi

Xuening Cao, Hao Yang, Bei-Bei Li

Nowadays, ultrasound sensors are playing an irreplaceable role in the fields of biomedical imaging and industrial nondestructive inspection. Currently, piezoelectric transducers are the most widely used ultrasound sensors, but their sensitivities drop quickly when the size becomes smaller, leading to a typical sensor size at the millimeter to centimeter scal

Ardita Kilaj, Silvan Käser, Jia Wang, Patrik Straňák

Recent advances in experimental methodology enabled studies of the quantum-state and conformational dependence of chemical reactions under precisely controlled conditions in the gas phase. Here, we generated samples of selected gauche and s-trans 2,3-dibromobutadiene (DBB) by electrostatic deflection in a molecular beam and studied their reaction with Coulom

Tongquan Zhou, Siyi Cao, Siruo Zhou, Yao Zhang

ChatGPT is a publicly available chatbot that can quickly generate texts on given topics, but it is unknown whether the chatbot is really superior to human writers in all aspects of writing and whether its writing quality can be prominently improved on the basis of updating commands. Consequently, this study compared the writing performance on a narrative top

Samuel Kemmler, Christoph Rettinger, Ulrich Rüde, Pablo Cuéllar

Current supercomputers often have a heterogeneous architecture using both CPUs and GPUs. At the same time, numerical simulation tasks frequently involve multiphysics scenarios whose components run on different hardware due to multiple reasons, e.g., architectural requirements, pragmatism, etc. This leads naturally to a software design where different simulat

Jan-Michael Mol, Luisa Esguerra, Matthias Meister, David Edward Bruschi

Investigating and verifying the connections between the foundations of quantum mechanics and general relativity will require extremely sensitive quantum experiments. To provide ultimate insight into this fascinating area of physics, the realization of dedicated experiments in space will sooner or later become a necessity. Quantum technologies, and among them

Zehui Dong, Wenjing Liu, Siyuan Liu, Xingzhi Chen

Federated Semi-supervised Learning (FSSL) combines techniques from both fields of federated and semi-supervised learning to improve the accuracy and performance of models in a distributed environment by using a small fraction of labeled data and a large amount of unlabeled data. Without the need to centralize all data in one place for training, it collect up

Gareth A. Jones, Martin Mačaj

We classify the dessins $\mathcal D$ for which the automorphism group $G$ acts primitively and faithfully on the points over one of the three critical values (without loss of generality the black vertices in the usual bipartite map representation). We show that they are all generalised Paley dessins, in which the black vertices are the elements of a finite f

Mobasshir Mahbub, Raed M. Shubair

The objective of the work is to improve the capacity of the micro cell, i.e., enabling the micro cell base station of a two-tier network to serve an increased number of devices. Therefore, the work deployed an IRS in a micro cell and achieved significant improvements in the performance with a reduced transmit power of the micro base station.

Andrej Kolar-Požun, Gregor Kosec

One of the most popular methods employed in computational electromagnetics is the Finite Difference Time Domain (FDTD) method. We generalise it to a meshless setting using the Radial Basis Function generated Finite Difference (RBF-FD) method and investigate its properties on a simple test problem.

Victor Augias, Eduardo Perez-Richet

We study how to optimally design selection mechanisms, accounting for agents' investment incentives. A principal wishes to allocate a resource of homogeneous quality to a heterogeneous population of agents. The principal commits to a possibly random selection rule that depends on a one-dimensional characteristic of the agents she intrinsically values. Agents

Maximilian Kronmueller, Andres Fielbaum, Javier Alonso-Mora

We study routing for on-demand last-mile logistics with two crucial novel features: i) Multiple depots, optimizing where to pick-up every order, ii) Allowing vehicles to perform depot returns prior to being empty, thus adapting their routes to include new orders online. Both features result in shorter distances and more agile planning. We propose a scalable

Gauthier Tallec, Edouard Yvinec, Arnaud Dapogny, Kevin Bailly

The rising performance of deep neural networks is often empirically attributed to an increase in the available computational power, which allows complex models to be trained upon large amounts of annotated data. However, increased model complexity leads to costly deployment of modern neural networks, while gathering such amounts of data requires huge costs t

Pierre Romanet

No.

Khaled Nakhleh, Minahil Raza, Mack Tang, Matthew Andrews

We study the training performance of ROS local planners based on Reinforcement Learning (RL), and the trajectories they produce on real-world robots. We show that recent enhancements to the Soft Actor Critic (SAC) algorithm such as RAD and DrQ achieve almost perfect training after only 10000 episodes. We also observe that on real-world robots the resulting S

Paul J Bonczek, Nicola Bezzo

Typical cooperative multi-agent systems (MASs) exchange information to coordinate their motion in proximity-based control consensus schemes to complete a common objective. However, in the event of faults or cyber attacks to on-board positioning sensors of agents, global control performance may be compromised resulting in a hijacking of the entire MAS. For sy

Neeraj Kumari, Arghajit Jana, Sachindra Naik, Prantik Nandi

We performed a detailed broadband spectral and timing analysis of a small flaring event of ~120 ks in a narrow-line Seyfert 1 galaxy NGC 4051 using simultaneous XMM-Newton and NuSTAR observations. The ~300 ks long NuSTAR observation and the overlapping XMM-Newton exposure were segregated into pre-flare, flare, and post-flare segments. During the flare, the N