May 2022 arXiv papers — page 30

Mahmood Roshan, Bahram Mashhoon

Nonlocal gravity (NLG) is a classical nonlocal generalization of Einstein's theory of gravitation developed in close analogy with the nonlocal electrodynamics of media. It appears that the nonlocal aspect of the universal gravitational interaction could simulate dark matter. Within the Newtonian regime of NLG, we investigate the deviation of the gravitationa

Lisa-Marie Kern, Bastian Pfau, Michael Schneider, Kathinka Gerlinger

In ferromagnetic multilayers, a single laser pulse with a fluence above an optical nucleation threshold can create magnetic skyrmions, which are randomly distributed over the area of the laser spot. However, in order to study the dynamics of skyrmions and for their application in future data technology, a controllable localization of the skyrmion nucleation

Josh Abramson, Arun Ahuja, Federico Carnevale, Petko Georgiev

Creating agents that can interact naturally with humans is a common goal in artificial intelligence (AI) research. However, evaluating these interactions is challenging: collecting online human-agent interactions is slow and expensive, yet faster proxy metrics often do not correlate well with interactive evaluation. In this paper, we assess the merits of the

Guilherme Vieira, Marcos Eduardo Valle

This paper features convolutional neural networks defined on hypercomplex algebras applied to classify lymphocytes in blood smear digital microscopic images. Such classification is helpful for the diagnosis of acute lymphoblast leukemia (ALL), a type of blood cancer. We perform the classification task using eight hypercomplex-valued convolutional neural netw

Marrone Silvério Melo Dantas, Iago Richard Rodrigues, Assis Tiago Oliveira Filho, Gibson Barbosa

IoT devices suffer from resource limitations, such as processor, RAM, and disc storage. These limitations become more evident when handling demanding applications, such as deep learning, well-known for their heavy computational requirements. A case in point is robot pose estimation, an application that predicts the critical points of the desired image object

Alexandru Iosup, Fernando Kuipers, Ana Lucia Varbanescu, Paola Grosso

Our modern society and competitive economy depend on a strong digital foundation and, in turn, on sustained research and innovation in computer systems and networks (CompSys). With this manifesto, we draw attention to CompSys as a vital part of ICT. Among ICT technologies, CompSys covers all the hardware and all the operational software layers that enable ap

Bruno Sauvalle, Arnaud de La Fortelle

We introduce a new architecture for unsupervised object-centric representation learning and multi-object detection and segmentation, which uses a translation-equivariant attention mechanism to predict the coordinates of the objects present in the scene and to associate a feature vector to each object. A transformer encoder handles occlusions and redundant de

Michał Dębski, Zbigniew Lonc, Karolina Okrasa, Marta Piecyk

For graphs $G$ and $H$, an $H$-coloring of $G$ is an edge-preserving mapping from $V(G)$ to $V(H)$. In the $H$-Coloring problem the graph $H$ is fixed and we ask whether an instance graph $G$ admits an $H$-coloring. A generalization of this problem is $H$-ColoringExt, where some vertices of $G$ are already mapped to vertices of $H$ and we ask if this partial

Fangyi Guo, Yaquan Fang, Gang Li, Xinchou Lou

This paper presents the prospects of measuring $\sigma(e^{+}e^{-}\to ZH)\times Br(H \to \gamma\gamma)$ in 3 $Z$ decay channels $Z \to q\bar{q} / \mu^{+} \mu^{-} / \nu\bar{\nu}$ using the baseline detector with $\sqrt{s} = 240 GeV$ at the Circular Electron Positron Collider (CEPC) . The simulated Monte Carlo events are generated and scaled to an integrated lu

Christos Koutlis, Manos Schinas, Symeon Papadopoulos

Image memes and specifically their widely-known variation image macros, is a special new media type that combines text with images and is used in social media to playfully or subtly express humour, irony, sarcasm and even hate. It is important to accurately retrieve image memes from social media to better capture the cultural and social aspects of online phe

Zhili Liu, Jianhua Han, Lanqing Hong, Hang Xu

Self-supervised learning (SSL), especially contrastive methods, has raised attraction recently as it learns effective transferable representations without semantic annotations. A common practice for self-supervised pre-training is to use as much data as possible. For a specific downstream task, however, involving irrelevant data in pre-training may degenerat

Onur Unlu, Muhammed O. Sayin

We present new learning dynamics combining (independent) log-linear learning and value iteration for stochastic games within the auxiliary stage game framework. The dynamics presented provably attain the efficient equilibrium (also known as optimal equilibrium) in identical-interest stochastic games, beyond the recent concentration of progress on provable co

Syed Imtiaz Ahamed, Vadlamani Ravi

The main aim of Privacy-Preserving Machine Learning (PPML) is to protect the privacy and provide security to the data used in building Machine Learning models. There are various techniques in PPML such as Secure Multi-Party Computation, Differential Privacy, and Homomorphic Encryption (HE). The techniques are combined with various Machine Learning models and

Ahmad Gazar, Majid Khadiv, Sébastien Kleff, Andrea Del Prete

Generation of robust trajectories for legged robots remains a challenging task due to the underlying nonlinear, hybrid and intrinsically unstable dynamics which needs to be stabilized through limited contact forces. Furthermore, disturbances arising from unmodelled contact interactions with the environment and model mismatches can hinder the quality of the p

J. Tian, G. E. Anderson, P. J. Hancock, J. C. A. Miller-Jones

We present a low-frequency (170\textendash200\,MHz) search for prompt radio emission associated with the long GRB 210419A using the rapid-response mode of the Murchison Widefield Array (MWA), triggering observations with the Voltage Capture System (VCS) for the first time. The MWA began observing GRB 210419A within 89\,s of its detection by \textit{Swift}, e

Kazuyuki Yagasaki

We prove that general three- or four-dimensional systems %of differential equations are real-analytically nonintegrable near degenerate equilibria in the Bogoyavlenskij sense under additional weak conditions when the Jacobian matrices have a zero and pair of purely imaginary eigenvalues or two incommensurate pairs of purely imaginary eigenvalues at the equil

Mohsen Fathi, Marco Olivares, J. R. Villanueva

Recently, an analytical study of radial and circular orbits for null and time-like geodesics that propagate in the spacetime produced by a Schwarzschild black hole associated with cloud of strings, in a universe filled by quintessence, has been done in Ref. \cite{Mustafa:2021}. In this paper, we complete the aforementioned study by investigating possible ana

Ciro Ciliberto, Duccio Sacchi

Let $\mathscr{X}\to W$ be a flat family of generically irreducible hypersurfaces of degree $d\geq 2$ in $\PP^n$ with singular locus of dimension $t$, with $W$ unirational of dimension $r$. We prove that if $n$ is large enough with respect to $d$, $r$ and $t$, then $\mathscr{X}$ is unirational. This extends results in \cite {Pre, HMP}.

Jeaheang Bang, Changfeng Gui, Yun Wang, Chunjing Xie

Liouville-type theorems for the steady incompressible Navier-Stokes system are investigated for solutions in a three-dimensional slab with either no-slip boundary conditions or periodic boundary conditions. When the no-slip boundary conditions are prescribed, we prove that any bounded solution is trivial if it is axisymmetric or $ru^r$ is bounded, and that g

Zhuchao Ji, Junyi Xie

The aims of this paper are to answer several conjectures and questions about multiplier spectrum of rational maps and to give new proofs of several rigidity theorems in complex dynamics, by combining tools from complex and non-archimedean dynamics. A remarkable theorem due to McMullen asserts that aside from the flexible Latt\`es family, the multiplier spect

Miguel-Angel Sanchis-Lozano

We interpret the lack of large-angle temperature correlations and the apparent even-odd parity imbalance, observed in the cosmic microwave background by COBE, WMAP and Planck satellite missions, as a possible stringy signal ultimately stemming from a composite inflaton field (e.g. a fermionic condensate). Based on causality arguments and a Fourier analysis o

Lianna Zhao, Pietro Ferraro, Robert Shorten

As Covid-19 remains a cause of concern, especially due to its mutations, wearing masks correctly and efficiently remains a priority in order to limit the spread of the disease. In this paper we present a wearable smart-mask prototype using concepts from Internet of Things, Control Theory and Distributed Ledger Technologies. Its purpose is to encourage people

Vivien Cabannes, Francis Bach, Vianney Perchet, Alessandro Rudi

The workhorse of machine learning is stochastic gradient descent. To access stochastic gradients, it is common to consider iteratively input/output pairs of a training dataset. Interestingly, it appears that one does not need full supervision to access stochastic gradients, which is the main motivation of this paper. After formalizing the "active labeling" p

Ritajit Kundu, H. A. Fertig, Arijit Kundu

We consider interaction-induced broken symmetry states of two Weyl semimetal surfaces with multiple Fermi-arc (FA) states. In the presence of inter- and intra-surface Coulomb interactions, multiple broken symmetries may emerge which coexist and/or compete with one another. Interlayer exciton condensates involving different FA flavors are shown to form, with

Kang Liu, Di Wu, Yiru Wang, Dan Feng

Deep learning techniques have shown promising results in image compression, with competitive bitrate and image reconstruction quality from compressed latent. However, while image compression has progressed towards a higher peak signal-to-noise ratio (PSNR) and fewer bits per pixel (bpp), their robustness to adversarial images has never received deliberation.

Annet Kyomuhangi, David Ssevviiri

Let $R$ be a commutative unital ring, $a\in R$ and $t$ a positive integer. $a^{t}$-reduced $R$-modules and universally $a^{t}$-reduced $R$-modules are defined and their properties given. Known (resp. new) results about reduced $R$-modules are retrieved (resp. obtained) by taking $t=1$ and results about reduced rings are deduced.

Andrea Barbiero, Jan Huwer, Joanna Skiba-Szymanska, David J. P. Ellis

Semiconductor quantum dots embedded in hybrid circular Bragg gratings are a promising platform for the efficient generation of nonclassical light. The scalable fabrication of multiple devices with similar performance is highly desirable for their practical use as sources of single and entangled photons, while the ability to operate at telecom wavelength is e

Álvaro Pastor-Gutiérrez, Masatoshi Yamada

The $SU(N)$ Yang-Mills theory in $\mathbb R^4\times S^1$ spacetime is studied as a simple toy model of Gauge-Higgs unification. The theory is perturbatively nonrenormalizable but could be formulated as an asymptotically safe theory, namely a nonperturbatively renormalizable theory. We study the fixed point structure of the Yang-Mills theory in $\mathbb R^4\t

Nan Zhang, Jianzong Wang, Zhenhou Hong, Chendong Zhao

Speaker verification (SV) aims to determine whether the speaker's identity of a test utterance is the same as the reference speech. In the past few years, extracting speaker embeddings using deep neural networks for SV systems has gone mainstream. Recently, different attention mechanisms and Transformer networks have been explored widely in SV fields. Howeve

Qingpeng Cai, Ruohan Zhan, Chi Zhang, Jie Zheng

The wide popularity of short videos on social media poses new opportunities and challenges to optimize recommender systems on the video-sharing platforms. Users provide complex and multi-faceted responses towards recommendations, including watch time and various types of interactions with videos. As a result, established recommendation algorithms that concer

Darshan Kumar, Deepak Jain, Shobhit Mahajan, Amitabha Mukherjee

One of the most significant discoveries in modern cosmology is that the universe is currently in a phase of accelerated expansion after a switch from a decelerated expansion. The redshift corresponding to this epoch is referred to as the transition redshift $z_t$. In this work we put constraints on the $z_t$ with both model-independent and model-dependent ap

Andri Sharma, Rajeev Kapri, Abhishek Chaudhuri

We study the translocation of a semiflexible polymer through a conical channel with attractive surface interactions and a driving force which varies spatially inside the channel. Using the results of the translocation dynamics of a flexible polymer through an extended channel as control, we first show that the asymmetric shape of the channel gives rise to no

Wentao Ding, Jianze Li, Shuzhong Zhang

Characterizing simultaneously diagonalizable (SD) matrices has been receiving considerable attention in the recent decades due to its wide applications and its role in matrix analysis. However, the notion of SD matrices is arguably still restrictive for wider applications. In this paper, we consider two error measures related to the simultaneous diagonalizat

Masatoshi Kitajima, Kouichi Hagino, Takayoshi Kohmura, Mitsuki Hayashida

We have been developing the monolithic active pixel detector "XRPIX" onboard the future X-ray astronomical satellite "FORCE". XRPIX is composed of CMOS pixel circuits, SiO2 insulator, and Si sensor by utilizing the silicon-on-insulator (SOI) technology. When the semiconductor detector is operated in orbit, it suffers from radiation damage due to X-rays emitt

David Viedma, Gerard Queraltó, Jordi Mompart, Verònica Ahufinger

Making use of the isospectrality of Supersymmetry transformations, we propose a general and high-fidelity method to prepare gapped topological modes in discrete systems from a single-site excitation. The method consists of adiabatically connecting two superpartner structures, deforming the input state into the desired mode. We demonstrate the method by pumpi

Eduardo Gallo, Antonio Barrientos

This article proposes a method to diminish the pose (position plus attitude) drift experienced by an SVO (Semi-Direct Visual Odometry) based visual navigation system installed onboard a UAV (Unmanned Air Vehicle) by supplementing its pose estimation non linear optimizations with priors based on the outputs of a GNSS (Global Navigation Satellite System) Denie

David Ssevviiri

This is the first in a series of papers highlighting the applications of reduced and coreduced modules. Let $R$ be a commutative unital ring and $I$ an ideal of $R$. We show that $I$-reduced $R$-modules and $I$-coreduced $R$-modules provide a setting in which the Matlis-Greenless-May (MGM) Equivalence and the Greenless-May (GM) Duality hold. These two notion

Chris J Budd Kgomotso S. Morupisi

We look at the periodic behaviour of the Earth's glacial cycles and the transitions between different periodic states when either external parameters (such as $\omega$) or internal parameters (such as $d$) are varied. We model this using the PP04 model of climate change. This is a forced discontinuous Filippov (non-smooth) dynamical system. When periodically

Nirman Chakraborty, Swastik Mondal

The key to most surface phenomenon lies with the surface structure. Particularly it is the charge density distribution over surface that primarily controls overall interaction of the material with external environment. It is generally accepted that surface structure cannot be deciphered from conventional bulk X-ray diffraction data. Thus, when we intend to d

Genqian Liu, Xiaoming Tan

We obtain the asymptotic expansions of the traces of the thermoelastic operators with the Dirichlet and Neumann boundary conditions on a Riemannian manifold, and give an effective method to calculate all the coefficients of the asymptotic expansions. These coefficients provide precise geometric information. In particular, we explicitly calculate the first tw

Yukun Feng, Denghui Ning, Shaobo Zhang, Zhengtian Lu

Monopole-dipole interactions involving scalar couplings between a spin and a massive particle violate both P- and T-symmetry, and can be mediated by axions. We use a $^{129}$Xe-$^{131}$Xe-Rb atomic cell comagnetometer to measure the ratio of precession frequencies between the two xenon isotopes, and search for changes of the ratio correlated with the distanc

Jyri Kimari, Ye Wang, Andreas Kyritsakis, Veronika Zadin

Under strong electric fields, an arc of strong current flowing through plasma can link two metal surfaces even in ultra high vacuum. Despite decades of research, the chain of events leading to vacuum arc breakdowns is hitherto unknown. Previously we showed that a tall and sharp Cu nanotip exposed to strong electric fields heats up by field emission currents

Hao Tang, Tian-Yu Wang, Zi-Yu Shi, Zhen Feng

Dynamic localization, which originates from the phenomena of particle evolution suppression under an externally applied AC electric field, has been simulated by suppressed light evolution in periodically-curved photonic arrays. However, experimental studies on their quantitative dynamic transport properties and application for quantum information processing

Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer

We propose the fully explainable Decision Tree Graph Neural Network (DT+GNN) architecture. In contrast to existing black-box GNNs and post-hoc explanation methods, the reasoning of DT+GNN can be inspected at every step. To achieve this, we first construct a differentiable GNN layer, which uses a categorical state space for nodes and messages. This allows us

Zhen Lyu, Jiaqing Kou, Weiwei Zhang

Modal analysis of fluid flows is essential to understand flow physics and fluid-solid interaction mechanisms, and to implement flow control. Unlike unstable flow, the intrinsic attenuation of subcritical flow has led to failures to experimentally extract the subcritical flow modes clearly. To this end, this paper proposes a modal testing method for subcritic

Du Linglong, Zhou Xinyun

We consider the Cucker-Smale system with multiplicative noise in a harmonic potential field and investigate the effect of harmonic potential field. In the presence of external potential force, the system is expected to emerge into almost surely velocity flocking and spatial concentration, due to the alignment mechanism, confining harmonic potential field and

Supatsara Wattanakriengkrai, Dong Wang, Raula Gaikovina Kula, Christoph Treude

Popular adoption of third-party libraries for contemporary software development has led to the creation of large inter-dependency networks, where sustainability issues of a single library can have widespread network effects. Maintainers of these libraries are often overworked, relying on the contributions of volunteers to sustain these libraries. In this wor

Subham Ghosh, Banibrata Mukhopadhyay

We venture for the comparison between growth rates for magnetorotational instability (MRI) and hydrodynamics instability in the presence of an extra force in the local Keplerian accretion flow. The underlying model is described by the Orr-Sommerfeld and Squire equations in the presence of rotation, magnetic field and an extra force, plausibly noise with a no

Isabella Saccardi, Duygu Sezen Islakoglu, Anouk Neerincx, Federica Lucia Vinella

In current youth-care programs, children with needs (mental health, family issues, learning disabilities, and autism) receive support from youth and family experts as one-to-one assistance at schools or hospitals. Occasionally, social robots have featured in such settings as support roles in a one-to-one interaction with the child. In this paper, we suggest

T. Watanabe, R. Okada, K. Tomiyasu

Ultrasound velocity measurements of the pseudo-cubic spin-crossover cobaltite LaCoO$_3$ and the lightly Ni-substituted La(Co$_{0.99}$Ni$_{0.01}$)O$_3$ reveal two types of symmetry-resolved elastic anomaly in the insulating paramagnetic state that are commonly observed in these compounds. The temperature dependence of the bulk modulus exhibits Curie-type soft

Mehrdad Mirbabayi, Andrei Gruzinov

Sphaleron heating has been recently proposed as a mechanism to realize warm inflation when inflaton is an axion coupled to pure Yang-Mills. As a result of heating, there is a friction coefficient $\gamma \propto T^3$ in the equation of motion for the inflaton, and a thermal contribution to cosmological fluctuations. Without the knowledge of the inflaton pote

Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento, Gustavo Carneiro

Survival time prediction from medical images is important for treatment planning, where accurate estimations can improve healthcare quality. One issue affecting the training of survival models is censored data. Most of the current survival prediction approaches are based on Cox models that can deal with censored data, but their application scope is limited b

Haeyeon Kim, Minsu Kim, Federico Berto, Joungho Kim

In this paper, we present DevFormer, a novel transformer-based architecture for addressing the complex and computationally demanding problem of hardware design optimization. Despite the demonstrated efficacy of transformers in domains including natural language processing and computer vision, their use in hardware design has been limited by the scarcity of o

Dye SK Sato, Yukitoshi Fukahata

We study the consistency and optimality of the maximum marginal likelihood estimate (MMLE) in the hyperparameter inference for large-degree-of-freedom models. We perform main analyses within the exponential family, where the natural parameters are hyperparameters. First, we prove the consistency of the MMLE for the general linear models when estimating the s

Alexander Marzok, Stehpan Schlegel, Joachim Saur, Lorenz Roth

We analyze Hubble Space Telescope (HST) observations of Ganymede made with the Space Telescope Imaging Spectrograph (STIS) between 1998 and 2017 to generate a brightness map of Ganymede's oxygen emission at 1356 A. Our Mercator projected map demonstrates that the brightness along Ganymede's northern and southern auroral ovals strongly varies with longitude.

Heqiang Wang, Jie Xu

Federated learning (FL) is a new distributed machine learning framework known for its benefits on data privacy and communication efficiency. Since full client participation in many cases is infeasible due to constrained resources, partial participation FL algorithms have been investigated that proactively select/sample a subset of clients, aiming to achieve

Zhenhou Hong, Jianzong Wang, Xiaoyang Qu, Chendong Zhao

Quantum devices with low qubits are common in the Noisy Intermediate-Scale Quantum (NISQ) era. However, Quantum Neural Network (QNN) running on low-qubit quantum devices would be difficult since it is based on Variational Quantum Circuit (VQC), which requires many qubits. Therefore, it is critical to make QNN with VQC run on low-qubit quantum devices. In thi

Baofeng Chang, Sujia Zhu, Qi Jiang, Wang Xia

Dynamic graph visualization attracts researchers' concentration as it represents time-varying relationships between entities in multiple domains (e.g., social media analysis, academic cooperation analysis, team sports analysis). Integrating visual analytic methods is consequential in presenting, comparing, and reviewing dynamic graphs. Even though dynamic gr

Somnath Hazra, Pallab Dasgupta

Obtaining gold standard annotated data for object detection is often costly, involving human-level effort. Semi-supervised object detection algorithms solve the problem with a small amount of gold-standard labels and a large unlabelled dataset used to generate silver-standard labels. But training on the silver standard labels does not produce good results, b

Yukang Jiang, Ting Tian, Huajun Xie, Hailiang Guo

Amidst the COVID-19 pandemic, travel restrictions have emerged as crucial interventions for mitigating the spread of the virus. In this study, we enhance the predictive capabilities of our model, Sequence-to-Sequence Epidemic Attention Network (S2SEA-Net), by incorporating an attention module, allowing us to assess the impact of distinct classes of travel di

Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye, De-Chuan Zhan

Real-world applications require the classification model to adapt to new classes without forgetting old ones. Correspondingly, Class-Incremental Learning (CIL) aims to train a model with limited memory size to meet this requirement. Typical CIL methods tend to save representative exemplars from former classes to resist forgetting, while recent works find tha

Prateek Chawla, Shrikant Utagi, C. M. Chandrashekar

We set the criteria under which superposition of causal order can be incorporated in to quantum walks. In particular, we show that only periodic quantum walks or those with at least one disorder exhibit Superposition of causal order under the action of `quantum switch'. We exemplify our results with a simple example of two-period discrete-time quantum walks.

Dun Zeng, Shiyu Liu, Siqi Liang, Zonghang Li

Federated learning enables isolated clients to train a shared model collaboratively by aggregating the locally-computed gradient updates. However, privacy information could be leaked from uploaded gradients and be exposed to malicious attackers or an honest-but-curious server. Although the additive homomorphic encryption technique guarantees the security of

Tom Markiewicz, Tor Raubenheimer, Natalia Toro, members of the LESA construction team

The Linac to End Station A (LESA) beamline is being constructed at SLAC and will provide a near-CW beam of multi-GeV electrons to the SLAC End Station A for experiments in particle physics. The 1st half of LESA is ready for commissioning at the end of FY22 and the full beamline will be operational Q1 FY24. The low-current multi-GeV electron beam is produced

Mingjie Li, Hao Kong, Zhouchen Lin

Recently, many works have demonstrated that Symmetric Non-negative Matrix Factorization~(SymNMF) enjoys a great superiority for various clustering tasks. Although the state-of-the-art algorithms for SymNMF perform well on synthetic data, they cannot consistently obtain satisfactory results with desirable properties and may fail on real-world tasks like clust

Zizheng Pan, Jianfei Cai, Bohan Zhuang

Vision Transformers (ViTs) have triggered the most recent and significant breakthroughs in computer vision. Their efficient designs are mostly guided by the indirect metric of computational complexity, i.e., FLOPs, which however has a clear gap with the direct metric such as throughput. Thus, we propose to use the direct speed evaluation on the target platfo

Davide Curcio, Klara Volckaert, Dmytro Kutnyakhov, Steinn Ymir Agustsson

X-ray photoelectron diffraction is a powerful tool for determining the structure of clean and adsorbate-covered surfaces. Extending the technique into the ultrafast time domain will open the door to studies as diverse as the direct determination of the electron-phonon coupling strength in solids and the mapping of atomic motion in surface chemical reactions.

Tianshu Cong, Aihua Xia

[B{\l}aszczyszyn, Yogeshwaran and Yukich (2019)] established central limit theorems for geometric statistics of point processes having fast decay dependence. As limit theorems are of limited use unless we understand their errors involved in the approximation, in this paper, we consider the rates of a normal approximation in terms of the Wasserstein distance

Junhui Liu, Jianfeng Wu, Ali Esamdin, Wei-Min Gu

By assembling the largest sample to date of X-ray emitting EW-type binaries (EWXs), we carried out correlation analyses for the X-ray luminosity log$L_{\textrm{X}}$, and X-ray activity level log($L_{\textrm{X}}$/$L_{\textrm{bol}}$) versus the orbital period $P$ and effective temperature $T_{\rm eff}$. We find strong $P$-log$L_{\textrm{X}}$ and $P$-log($L_{\t

Minsu Kim, Junyoung Park, Jinkyoo Park

Deep reinforcement learning (DRL)-based combinatorial optimization (CO) methods (i.e., DRL-NCO) have shown significant merit over the conventional CO solvers as DRL-NCO is capable of learning CO solvers less relying on problem-specific expert domain knowledge (heuristic method) and supervised labeled data (supervised learning method). This paper presents a n

Li-Hua Wang, Meng-Sen Ma

Following Barrow's idea of fractal black hole horizon, we re-derive black hole entropy of static spherically symmetric black holes. When a black hole absorbs matter its horizon area will increase. Given the spherically fractal structure, we conjecture that the minimal increase of the horizon area should be the area of the smallest bubble sphere. From this, w

Martin Herdegen, Gechun Liang, Osian Shelley

Necessary and sufficient conditions for weak and vague convergence of measures are important for a diverse host of applications. This paper aims to give a comprehensive description of the relationship between the two modes of convergence when the measures are signed, which is largely absent from the literature. Furthermore, when the underlying space is $\mat

Franco Niccolucci, Achille Felicetti, Sorin Hermon

The present paper concerns the design of the semantic infrastructure of the digital space for cultural heritage as envisaged by the European Commission in its recent documents. Due to the complexity of the cultural heritage data and of their intrinsic interrelationships, it is necessary to introduce a novel ontology, yet compliant with existing standards and

Tianyu Pang, Shuicheng Yan, Min Lin

Fermionic neural network (FermiNet) is a recently proposed wavefunction Ansatz, which is used in variational Monte Carlo (VMC) methods to solve the many-electron Schr\"{o}dinger equation. FermiNet proposes permutation-equivariant architectures, on which a Slater determinant is applied to induce antisymmetry. FermiNet is proved to have universal approximation

Dmitri Yafaev

The aim of the lecture is to briefly describe the mathematical background of scattering theory for two- and three-particle quantum systems. We discuss basic objects of the theory: wave and scattering operators and the corresponding scattering matrix and illustrate them on the example of the Schr\"odinger equation. Our goal is to present time-dependent and st

An Chen, Xiaobo Hou, Wanshan Lin, Xueting Tian

In present paper we mainly focus on non-recurrent dynamical orbits with empty syndetic center and show that twelve different statistical structures over mixing expanding maps or transitive Anosov diffeomorphisms all have dynamical complexity in the sense of strongly distributional chaos.

Ümit V. Çatalyürek, Karen D. Devine, Marcelo Fonseca Faraj, Lars Gottesbüren

In recent years, significant advances have been made in the design and evaluation of balanced (hyper)graph partitioning algorithms. We survey trends of the last decade in practical algorithms for balanced (hyper)graph partitioning together with future research directions. Our work serves as an update to a previous survey on the topic. In particular, the surv

Pavel Zalesskii

We give a characterization of toral relatively hyperbolic virtually special groups in terms of the profinite completion. We also prove a Tits alternative for subgroups of the profinite completion $\hat G$ of a relatively hyperbolic virtually compact special group $G$ and completely describe finitely generated pro-$p$ subgroups of $\hat G$. This applies to th

Yukun Liu, Jing Qin

Propensity score matching (PSM) is a pseudo-experimental method that uses statistical techniques to construct an artificial control group by matching each treated unit with one or more untreated units of similar characteristics. To date, the problem of determining the optimal number of matches per unit, which plays an important role in PSM, has not been adeq

Yao Zhang, Jiawei Yang, Yang Liu, Jiang Tian

Purpose: Automated liver tumor segmentation from Computed Tomography (CT) images is a necessary prerequisite in the interventions of hepatic abnormalities and surgery planning. However, accurate liver tumor segmentation remains challenging due to the large variability of tumor sizes and inhomogeneous texture. Recent advances based on Fully Convolutional Netw

Vivek Chaudhary, J. Harshan

With potential applications to short-packet communication, we address communication of low-latency messages in fast-fading channels under the presence of a reactive jammer. Unlike a traditional jammer, we assume a full-duplex (FD) jammer capable of detecting pre-existing countermeasures and subsequently changing the target frequency band. To facilitate relia

Shi-Zhuo Looi

This second article in a two-part series (following [arXiv:2105.02865], listed here as \cite{L}) proves optimal pointwise decay rates for the quintic defocusing wave equation with large initial data on nonstationary spacetimes, and both the quintic defocusing and quintic focusing wave equations with small initial data on nonstationary spacetimes. We prove a

Kaspar Rosager Ludvigsen, Shishir Nagaraja

Safety is becoming cybersecurity under most circumstances. This should be reflected in the Cybersecurity Resilience Act when it is proposed and agreed upon in the European Union. In this paper, we define a range of principles which this future Act should build upon, a structure and argue why it should be as broad as possible. It is based on what the cybersec

Devvrat Tiwari, K. G. Paulson, Subhashish Banerjee

In this article, we consider single, and two-qubit central spin systems interacting with spin baths and discuss their dynamical properties. We consider the cases of interacting and non-interacting spin baths and investigate the quantum speed limit (QSL) time of evolution. The impact of the size of the spin bath on the quantum speed limit for a single qubit c

Erwan Taillanter, Marc Barthelemy

Most cities in the US and in the world were organized around car traffic. In particular, large structures such as urban freeways or ring roads were built for reducing car traffic congestion. With the evolution of public transportation, working conditions, the future of these structures and the organization of large urban areas is uncertain. Here, we analyze

Ciro Ciliberto, Flaminio Flamini, Andreas Leopold Knutsen

We prove that for any $r \geq 2$ the moduli space of stable Ulrich bundles of rank $r$ and determinant $\mathcal O_X(r)$ on any smooth Fano threefold $X$ of index two is smooth of dimension $r^2+1$ and that the same holds true for even $r$ when the index is four, in which case no odd--rank Ulrich bundles exist. In particular this shows that any such threefol

Thomas Lowe, Joshua Pinskier

Generating accurate digital tree models from scanned environments is invaluable for forestry, agriculture, and other outdoor industries in tasks such as identifying biomass, fall hazards and traversability, as well as digital applications such as animation and gaming. Existing methods for tree reconstruction rely on feature identification (trunk, crown, etc)

Wei Dai, Chuanfeng Ning, Shiyu Pei, Song Zhu

As a randomized learner model, SCNs are remarkable that the random weights and biases are assigned employing a supervisory mechanism to ensure universal approximation and fast learning. However, the randomness makes SCNs more likely to generate approximate linear correlative nodes that are redundant and low quality, thereby resulting in non-compact network s

Haitao Lin, Junnan Zhu, Lu Xiang, Yu Zhou

Role-oriented dialogue summarization is to generate summaries for different roles in the dialogue, e.g., merchants and consumers. Existing methods handle this task by summarizing each role's content separately and thus are prone to ignore the information from other roles. However, we believe that other roles' content could benefit the quality of summaries, s

Zangir Iklassov, Dmitrii Medvedev, Otabek Nazarov, Shakhboz Razzokov

Geologic cores are rock samples that are extracted from deep under the ground during the well drilling process. They are used for petroleum reservoirs' performance characterization. Traditionally, physical studies of cores are carried out by the means of manual time-consuming experiments. With the development of deep learning, scientists actively started wor

E. Segawa, S. Koyama, N. Konno, M. Stefanak

We provide a detailed analysis of the survival probability of the Grover walk on the ladder graph with an absorbing sink. This model was discussed in Mare\v s et al., Phys. Rev. A 101, 032113 (2020), as an example of counter-intuitive behaviour in quantum transport where it was found that the survival probability decreases with the length of the ladder $L$,

Luca Gemignani, Beatrice Meini

We present some accelerated variants of fixed point iterations for computing the minimal non-negative solution of the unilateral matrix equation associated with an M/G/1-type Markov chain. These variants derive from certain staircase regular splittings of the block Hessenberg M-matrix associated with the Markov chain. By exploiting the staircase profile we i

Michele Fioretti, Alessandro Iaria, Aljoscha Janssen, Clément Mazet-Sonilhac

Contractual relationships between the state and private firms involving large irreversible investments are vulnerable to sovereign hold-up risk: anticipating that the state can unilaterally revise terms once capital is sunk, firms may underinvest. Causal evidence on this mechanism is scarce because sovereign commitment is typically bundled with broader insti

Yotaro Sato, Yuji Tachikawa, Taizan Watari

We argue that having an odd number of Majorana fermion zero modes on a dynamical point-like soliton signifies an inconsistency in a theory with 3+1 and higher dimensions. We check this statement in a couple of examples in field theory and in string/M theory.

Chris Fields, James F. Glazebrook, Antonino Marciano

We introduce novel methods for implementing generic quantum information within a scale-free architecture. For a given observable system, we show how observational outcomes are taken to be finite bit strings induced by measurement operators derived from a holographic screen bounding the system. In this framework, measurements of identified systems with respec

Chao Zhao, Faeze Brahman, Tenghao Huang, Snigdha Chaturvedi

Pre-trained models (PTMs) have lead to great improvements in natural language generation (NLG). However, it is still unclear how much commonsense knowledge they possess. With the goal of evaluating commonsense knowledge of NLG models, recent work has proposed the problem of generative commonsense reasoning, e.g., to compose a logical sentence given a set of

Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang

The impressive success of style-based GANs (StyleGANs) in high-fidelity image synthesis has motivated research to understand the semantic properties of their latent spaces. In this paper, we approach this problem through a geometric analysis of latent spaces as a manifold. In particular, we propose a local dimension estimation algorithm for arbitrary interme

Caihao Qiu, Marco Salvalaglio, David J. Srolovitz, Jian Han

An intrinsic feature of nearly all internal interfaces in crystalline systems (homo- and hetero-phase) is the presence of disconnections (topological line defects constrained to the interface that have both step and dislocation character). Disconnections play a major role in determining interface thermodynamics and kinetics. We demonstrate that elastic inter

Tomoyoshi Ibukiyama, Valentijn Karemaker, Chia-Fu Yu

We study the Siegel modular variety $\mathcal{A}_g \otimes \overline{\mathbb{F}}_p$ of genus $g$ and its supersingular locus $\mathcal{S}_g$. As our main result we determine precisely when $\mathcal{S}_g$ is irreducible, and we list all $x$ in $\mathcal{A}_g \otimes \overline{\mathbb{F}}_p$ for which the corresponding central leaf $\mathcal{C}(x)$ consists o

Rahul Rajan

Let $T_{f}$ denote the Toeplitz operator on the Hardy space $H^{2}(\mathbb{T})$ and let $T_{n}(f)$ be the corresponding $n \times n$ Toeplitz matrix. In this paper, we characterize the compactness of the operators $T_{|f|^{2}}-T_{f}T_{\overline{f}}$ and $T_{|\tilde{f}|^{2}}-T_{\tilde{f}}T_{\overline{\tilde{f}}},$ where $\tilde{f}(z)=f(z^{-1}),$ in terms of t