July 2021 arXiv papers

Sayak Nag, Dripta S. Raychaudhuri, Sujoy Paul, Amit K. Roy-Chowdhury

In many applications, we are constrained to learn classifiers from very limited data (few-shot classification). The task becomes even more challenging if it is also required to identify samples from unknown categories (open-set classification). Learning a good abstraction for a class with very few samples is extremely difficult, especially under open-set set

Anastasiya Tanana

In this paper, we study expected utility maximization under ratchet and drawdown constraints on consumption in a general incomplete semimartingale market using duality methods. The optimization is considered with respect to two parameters: the initial wealth and the essential lower bound on consumption process. In order to state the problem and define the pr

Yue Zheng, Imtiar Niloy, Paolo Celli, Ian Tobasco

Mechanical metamaterials exhibit exotic properties at the system level, that emerge from the interactions of many nearly rigid building blocks. Determining these emergent properties theoretically has remained an open challenge outside of a few select examples. Here, for a large class of periodic and planar kirigami, we provide a coarse-graining rule linking

Kelvin Cheng, Christopher Healey, Tianfu Wu

Stereo matching has recently witnessed remarkable progress using Deep Neural Networks (DNNs). But, how robust are they? Although it has been well-known that DNNs often suffer from adversarial vulnerability with a catastrophic drop in performance, the situation is even worse in stereo matching. This paper first shows that a type of weak white-box attacks can

Shah Zeb, Muhammad Ahmad Rathore, Aamir Mahmood, Syed Ali Hassan

The 6G vision is envisaged to enable agile network expansion and rapid deployment of new on-demand microservices (e.g., visibility services for data traffic management, mobile edge computing services) closer to the network's edge IoT devices. However, providing one of the critical features of network visibility services, i.e., data flow prediction in the

Jinyan Su, Lijie Hu, Di Wang

In this paper, we revisit the problem of Differentially Private Stochastic Convex Optimization (DP-SCO) and provide excess population risks for some special classes of functions that are faster than the previous results of general convex and strongly convex functions. In the first part of the paper, we study the case where the population risk function satisf

B. Dubetsky

A local positional system (LPS) is proposed, in which particles are launched at given velocities, and a sensor system measures the trajectory of particles in the platform frame. These measurements allow us to restore the position and orientation of the platform in the frame of the rotating Earth, without solving navigation equations. If there are also veloci

J. C. del Valle, Alexander V. Turbiner

For one-dimensional power-like potentials $|x|^m, m > 0$ the Bohr-Sommerfeld Energies (BSE) extracted explicitly from the Bohr-Sommerfeld quantization condition are compared with the exact energies. It is shown that for the ground state as well as for all positive parity states the BSE are always above the exact ones contrary to the negative parity states wh

Jennifer Roloff, Viviana Cavaliere, Marc-André Pleier, Lailin Xu

Longitudinal vector boson scattering provides an important probe of electroweak symmetry breaking, bringing sensitivity to physics beyond the Standard Model as well as constraining properties of the Higgs boson. It is a difficult process to study due to the small production cross section and challenging separation of the different polarization states. We stu

Jiaxi Cheng, Zhenhao Cen, Siliu Xu

Plasmon-induced transparency (PIT) displays complex nonlinear dynamics that find critical phenomena in areas such as nonlinear waves. However, such a nonlinear solution depends sensitively on the selection of parameters and different potentials in the Schrödinger equation. Despite this complexity, the machine learning community has developed remarkable effic

Arunkumar C. S

We initiate a study of non-commutative Choquet boundary for spaces of unbounded operators. We define the notion of local boundary representations for local operator systems in locally C$^*$-algebras and prove that local boundary representations provide an intrinsic invariant for a particular class of local operator systems. An appropriate analog of purity of

Yann Damour, Mickaël Véril, Fábris Kossoski, Michel Caffarel

Following our recent work on the benzene molecule [\href{https://doi.org/10.1063/5.0027617}{J.~Chem.~Phys.~\textbf{153}, 176101 (2020)}], itself motivated by the blind challenge of Eriksen \textit{et al.} [\href{https://doi.org/10.1021/acs.jpclett.0c02621}{J.~Phys.~Chem.~Lett.~\textbf{11}, 8922 (2020)}] on the same system, we report accurate full configurati

Damon Pham, Daniel McDonald, Lei Ding, Mary Beth Nebel

Artifacts in functional MRI (fMRI) data cause deviations from common distributional assumptions, introduce spatial and temporal outliers, and reduce the signal-to-noise ratio of the data -- all of which can have negative consequences for downstream statistical analysis. Scrubbing is a technique for excluding fMRI volumes thought to be contaminated by artifac

J. D. García-Aguilar, Juan Carlos Gómez-Izquierdo

The lepton sector is studied within a flavored non-renormalizable model where the $\mathbf{S}_{3}\otimes \mathbf{Z}_{2}$ flavor symmetry drives the Yukawa couplings. In this framework, the effective neutrino mass, that comes from the type II see-saw mechanism, as well as the charged lepton mass matrices are hierarchical and possessed (under a benchmark in th

Gil Ben Zvi, Eyal Leizerovich, Nimrod Talmon

We investigate an iterative deliberation process for an agent community wishing to make a joint decision. We develop a general model consisting of a community of n agents, each with their initial ideal point in some metric space (X, d), such that in each iteration of the iterative deliberation process, all agents move slightly closer to the current winner, a

Kuntal Patel, Javed Shaikh, Absar Lakdawala, Atul Sharma

Adaptive interface-Mesh un-Refinement (AiMuR) based Sharp-Interface Level-Set-Method (SI-LSM) is proposed for both uniform and non-uniform Cartesian-Grid. The AiMuR involves interface location based dynamic un-refinement (with merging of the four control volumes) of the Cartesian grid away from the interface. The un-refinement is proposed for the interface s

Stefano Di Sabatino, Pierre-François Loos, Pina Romaniello

Using the simple (symmetric) Hubbard dimer, we analyze some important features of the $GW$ approximation. We show that the problem of the existence of multiple quasiparticle solutions in the (perturbative) one-shot $GW$ method and its partially self-consistent version is solved by full self-consistency. We also analyze the neutral excitation spectrum using t

Chao Liu, Sencheng Yu, Mark Yim

Truss robots are highly redundant parallel robotic systems that can be applied in a variety of scenarios. The variable topology truss (VTT) is a class of modular truss robots. As self-reconfigurable modular robots, a VTT is composed of many edge modules that can be rearranged into various structures depending on the task. These robots change their shape by n

Yi Ji, Simon Mak, Derek Soeder, J-F Paquet

With advances in scientific computing and mathematical modeling, complex scientific phenomena such as galaxy formations and rocket propulsion can now be reliably simulated. Such simulations can however be very time-intensive, requiring millions of CPU hours to perform. One solution is multi-fidelity emulation, which uses data of different fidelities to train

Mason C. Marshall, Reza Ebadi, Connor Hart, Matthew J. Turner

Crystal strain variation imposes significant limitations on many quantum sensing and information applications for solid-state defect qubits in diamond. Thus, precision measurement and control of diamond crystal strain is a key challenge. Here, we report diamond strain measurements with a unique set of capabilities, including micron-scale spatial resolution,

Song Zhang, Amritanshu Pandey, Xiaochuan Luo, Maggy Powell

Motivated by The Federal Energy Regulatory Commission's (FERC) recent direction and ever-growing interest in cloud adoption by power utilities, a Task Force was established to assist power system practitioners with secure, reliable and cost-effective adoption of cloud technology to meet various business needs. This paper summarizes the business drivers,

Mario Bravo, Thierry Champion, Roberto Cominetti

We present a self-contained analysis of a particular family of metrics over the set of non-negative integers. We show that these metrics, which are defined through a nested sequence of optimal transport problems, provide tight estimates for general Krasnosel'skii-Mann fixed point iterations for non-expansive maps. We also describe some of their very spec

Mónica Clapp, Mayra Soares

We study the existence and asymptotic behavior of solutions having positive and sign-changing components to the singularly perturbed system of elliptic equations \begin{equation*} \begin{cases} -\varepsilon^2Δu_i+u_i=μ_i|u_i|^{p-2}u_i + \sum\limits_{\substack{j=1 \\ j \not=i}}^\ellλ_{ij}β_{ij}|u_j|^{α_{ij}}|u_i|^{β_{ij} -2}u_i,\\ u_i \in H^1_0(Ω), \quad u_i\

Andrea Cini, Ivan Marisca, Cesare Alippi

Dealing with missing values and incomplete time series is a labor-intensive, tedious, inevitable task when handling data coming from real-world applications. Effective spatio-temporal representations would allow imputation methods to reconstruct missing temporal data by exploiting information coming from sensors at different locations. However, standard meth

Akshita Jha, Bhanukiran Vinzamuri, Chandan K. Reddy

With the growing interest in the machine learning community to solve real-world problems, it has become crucial to uncover the hidden reasoning behind their decisions by focusing on the fairness and auditing the predictions made by these black-box models. In this paper, we propose a novel method to address two key issues: (a) Can we simultaneously learn fair

Hedieh Ajam, Marzieh Najafi, Vahid Jamali, Bernhard Schmauss

In this paper, we investigate the modeling and design of intelligent reflecting surface (IRS)-assisted optical communication systems which are deployed to relax the line-of-sight (LOS) requirement in multi-link free space optical (FSO) systems. The FSO laser beams incident on the optical IRSs have a Gaussian power intensity profile and a nonlinear phase prof

Shiqi Jia, Jie Peng, Yuqiong Cheng, Shubo Wang

The practical applications of chiral discrimination are usually limited by the weak chiral response of enantiomers and the high complexity of detection methods. Here, we propose to use the C lines (i.e., lines of polarization singularities) emerged in light scattering by a metal sphere to detect small chiral particles. Using full-wave numerical simulations a

Rong An, Xiang Jiang, Li-Gang Cao, Feng-Shou Zhang

A unified theoretical model reproducing charge radii of known atomic nuclei plays an essential role in making extrapolations for unknown nuclei. Recently developed new ansatz which phenomenologically takes into account the neutron-proton short-range correlations ($np$-SRCs) can describe the discontinuity properties and odd-even staggering (OES) effect of cha

Sam Dillavou, Menachem Stern, Andrea J. Liu, Douglas J. Durian

In typical artificial neural networks, neurons adjust according to global calculations of a central processor, but in the brain neurons and synapses self-adjust based on local information. Contrastive learning algorithms have recently been proposed to train physical systems, such as fluidic, mechanical, or electrical networks, to perform machine learning tas

Mingyuan Luo, Xin Yang, Xiaoqiong Huang, Yuhao Huang

3D ultrasound (US) is widely used for its rich diagnostic information. However, it is criticized for its limited field of view. 3D freehand US reconstruction is promising in addressing the problem by providing broad range and freeform scan. The existing deep learning based methods only focus on the basic cases of skill sequences, and the model relies on the

Muhammad Monjurul Karim, Yu Li, Ruwen Qin

Traffic accident anticipation is a vital function of Automated Driving Systems (ADSs) for providing a safety-guaranteed driving experience. An accident anticipation model aims to predict accidents promptly and accurately before they occur. Existing Artificial Intelligence (AI) models of accident anticipation lack a human-interpretable explanation of their de

Krzysztof Zajkowski

The Weibull distribution can be obtained using a power transformation from the standard exponential distribution. In this article, we will consider a symmetrized power transformation of a random variable with the standard normal distribution. We will call its distribution the $α$-{\it normal (Gaussian) distribution}. We examine properties of this distributio

Kishore Tumarada, Yifan Zhang, Fan Yang, Eduard Dragut

Opinion prediction is an emerging research area with diverse real-world applications, such as market research and situational awareness. We identify two lines of approaches to the problem of opinion prediction. One uses topic-based sentiment analysis with time-series modeling, while the other uses static embedding of text. The latter approaches seek user-spe

A. Silantyev

We construct Quantum Representation Theory which describes quantum analogue of representations in frame of "non-commutative linear geometry" developed by Manin. To do it we generalise the internal hom-functor to the case of adjunction with a parameter and construct a general approach to representations of a monoid in a symmetric monoidal category wit

Zahra Davari, Sohrab Rahvar

In this work, we investigate the MOdified Gravity (MOG) theory for dynamics of the universe and compare the results with the $Λ$CDM cosmology. We study the background cosmological properties of the MOG model and structure formation at the linear perturbation level. We compare the two models with the currently available cosmological data by using statistical

H. T. Cui, M. Qin, L. Tang, H. Z. Shen

In this work, the exact dynamics of excitation in the generalized Aubry-André-Harper model coupled with an Ohmic-type environment is discussed by evaluating the survival probability and inverse participation ratio of the state of system. In contrast to the common belief that localization will preserve the information of the initial state in the system agains

Uttaran Bhattacharya, Elizabeth Childs, Nicholas Rewkowski, Dinesh Manocha

We present a generative adversarial network to synthesize 3D pose sequences of co-speech upper-body gestures with appropriate affective expressions. Our network consists of two components: a generator to synthesize gestures from a joint embedding space of features encoded from the input speech and the seed poses, and a discriminator to distinguish between th

Vidas Regelskis, Bart Vlaar

Lie algebra involutions and their fixed-point subalgebras give rise to symmetric spaces and real forms of complex Lie algebras, and are well-studied in the context of symmetrizable Kac-Moody algebras. In this paper we study a generalization. Namely, we introduce the concept of a pseudo-involution, an automorphism which is only required to act involutively on

Cameron R. Wolfe, Fangshuo Liao, Qihan Wang, Junhyung Lyle Kim

Neural network pruning is useful for discovering efficient, high-performing subnetworks within pre-trained, dense network architectures. More often than not, it involves a three-step process -- pre-training, pruning, and re-training -- that is computationally expensive, as the dense model must be fully pre-trained. While previous work has revealed through ex

Hai-Xiao Wang, Yige Chen, Guang-Yu Guo, Hae-Young Kee

The simulation of fermionic relativistic physics, e.g., Dirac and Weyl physics, has led to the discovery of many unprecedented phenomena in photonics, of which the optical-frequency realization is, however, still challenging. Here, surprisingly, we discover that the woodpile photonic crystals commonly used for optical frequency applications host exotic fermi

Ngo Phuc Duc Loc

In the first scenario, we revise the upper bound of the cutoff scale of the dimension-six potential Higgs operator required for a successful electroweak baryogenesis in the case of a modified expansion history caused by the existence of a non-interacting scalar field at the time phase transition happens. The upper bound 860 GeV of the cutoff scale in the con

Hira Asif, Ramazan Sahin

Spatio-temporal control of ultrafast plasmon resonances has gained research interest in recent years because of their tremendous implications in nonlinear optics and ultrafast quantum technology. In particular, the lifetime of ultrashort plasmon oscillations has become a debatable subject in recent experimental and theoretical studies to fulfill the future c

Serio Agriesti, Claudio Roncoli, Bat-Hen Nahmias-Biran

Agent based modelling has acquired the spotlight in the transportation domain both in scientific literature and in real life applications, thanks to its capability to deal with the ever-growing complexity of transportation systems, including future disrupting mobility technologies and services such as automated driving, Mobility as a Service, and micromobili

Jean-Philippe Bouchaud

We attempt to reconcile Gabaix and Koijen's (GK) recent Inelastic Market Hypothesis (IMH) with the order-driven view of markets that emerged within the microstructure literature in the past 20 years. We review the most salient empirical facts and arguments that give credence to the idea that market price fluctuations are mostly due to order flow, whether

Fang Zheng, Le Wang, Sanping Zhou, Wei Tang

Understanding complex social interactions among agents is a key challenge for trajectory prediction. Most existing methods consider the interactions between pairwise traffic agents or in a local area, while the nature of interactions is unlimited, involving an uncertain number of agents and non-local areas simultaneously. Besides, they treat heterogeneous tr

Andrea Cristofari, Marianna De Santis, Stefano Lucidi, Francesco Rinaldi

The l1-ball is a nicely structured feasible set that is widely used in many fields (e.g., machine learning, statistics and signal analysis) to enforce some sparsity in the model solutions. In this paper, we devise an active-set strategy for efficiently dealing with minimization problems over the l1-ball and embed it into a tailored algorithmic scheme that ma

Ningyuan Chen, Xuefeng Gao, Yi Xiong

It has been recently shown in the literature that the sample averages from online learning experiments are biased when used to estimate the mean reward. To correct the bias, off-policy evaluation methods, including importance sampling and doubly robust estimators, typically calculate the conditional propensity score, which is ill-defined for non-randomized p

V. N. Potapov, A. A. Taranenko, Yu. V. Tarannikov

A Boolean function $f$ on $n$ variables is said to be a bent function if the absolute value of all its Walsh coefficients is $2^{n/2}$. Our main result is a new asymptotic lower bound on the number of Boolean bent functions. It is based on a modification of the Maiorana--McFarland family of bent functions and recent progress in the estimation of the number o

Valentina Cammarota, Anna Paola Todino

We study the correlation between the total number of critical points of random spherical harmonics and the number of critical points with value in any interval $I \subset \mathbb{R}$. We show that the correlation is asymptotically zero, while the partial correlation, after controlling the random $L^2$-norm on the sphere of the eigenfunctions, is asymptotical

Bertrand Eynard, Danilo Lewański

We advertise elementary symmetric polynomials $e_i$ as the natural basis for generating series $A_{g,n}$ of intersection numbers of genus g and n marked points. Closed formulae for $A_{g,n}$ are known for genera $0$ and $1$ -- this approach provides formulae for $g = 2,3,4$, together with an algorithm to compute the formula for any g. The claimed naturality

Yurii Kostyukov, Dmitry Mordvinov, Grigory Fedyukovich

First-order logic is a natural way of expressing the properties of computation, traditionally used in various program logics for expressing the correctness properties and certificates. Subsequently, modern methods in the automated inference of program invariants progress towards the construction of first-order definable invariants. Although the first-order r

Fatma Almaz, Mihriban Alyamaç Külahcı

In this paper, Clairaut's theorem is expressed on the surfaces of rotation in semi Euclidean 4-space. Moreover, the general equations of time-like geodesic curves are characterized according to the results of Clairaut's theorem on the hyperbolic surfaces of rotation and the elliptic surface of rotation respectively.

Pengzhan Jin, Zhangli Lin, Bo Xiao

We prove that any symplectic matrix can be factored into no more than 5 unit triangular symplectic matrices, moreover, 5 is the optimal number. This result improves the existing triangular factorization of symplectic matrices which gives proof of 9 factors. We also show the corresponding improved conclusions for structured subsets of symplectic matrices. Thi

Shuntaro Aoki, Hyun Min Lee, Adriana G. Menkara

We propose a new construction of the supergravity inflation as an UV completion of the Higgs-$R^2$ inflation. In the dual description of $R^2$-supergravity, we show that there appear dual chiral superfields containing the scalaron or sigma field in the Starobinsky inflation, which unitarizes the supersymmetric Higgs inflation with a large non-minimal couplin

Dongdong Wan, Guangrui Sun, Mengqi Zhang

Axisymmetric viscoelastic pipe flow of Oldroyd-B fluids has been recently found to be linearly unstable by Garg et al. Phys. Rev. Lett., 121.024502 (2018). From a nonlinear point of view, this means that the flow can transition to turbulence supercritically, in contrast to the subcritical Newtonian pipe flows. Experimental evidences of subcritical and superc

Yu Zhou, Xiaoqing Zhang, Juanjuan Shen, Tingting Han

Deep neural networks (DNNs) have shown remarkable performance in a variety of domains such as computer vision, speech recognition, or natural language processing. Recently they also have been applied to various software engineering tasks, typically involving processing source code. DNNs are well-known to be vulnerable to adversarial examples, i.e., fabricate

Dongyang Zhao, Ziyang Song, Zhenghao Ji, Gangming Zhao

Deep features have been proven powerful in building accurate dense semantic correspondences in various previous works. However, the multi-scale and pyramidal hierarchy of convolutional neural networks has not been well studied to learn discriminative pixel-level features for semantic correspondence. In this paper, we propose a multi-scale matching network th

Stefan Ilić, F. Sebastian Bergeret

We calculate the non-reciprocal critical current and quantify the supercurrent diode effect in Rashba superconductors with arbitrary disorder, using the quasiclassical Eilenberger equation. The non-reciprocity is caused by the helical superconducting state, which appears when both inversion and time-reversal symmetries are broken. In the absence of disorder,

Sjoerd Dirksen, Martin Genzel, Laurent Jacques, Alexander Stollenwerk

Neural networks with random weights appear in a variety of machine learning applications, most prominently as the initialization of many deep learning algorithms and as a computationally cheap alternative to fully learned neural networks. In the present article, we enhance the theoretical understanding of random neural networks by addressing the following da

Xin Xing, Xiaoxu Li, Lin Lin

Despite decades of practice, finite-size errors in many widely used electronic structure theories for periodic systems remain poorly understood. For periodic systems using a general Monkhorst-Pack grid, there has been no comprehensive and rigorous analysis of the finite-size error in the Hartree-Fock theory (HF) and the second order Møller-Plesset perturbati

Ziang Cao, Changhong Fu, Junjie Ye, Bowen Li

Most existing Siamese-based tracking methods execute the classification and regression of the target object based on the similarity maps. However, they either employ a single map from the last convolutional layer which degrades the localization accuracy in complex scenarios or separately use multiple maps for decision making, introducing intractable computat

Roberto Mossa, Michela Zedda

We extend the Polydisk Theorem for symmetric bounded domains to Cartan-Hartogs domains, and apply it to prove that a Cartan-Hartogs domain inherits totally geodesic submanifolds from the bounded symmetric domain which is based on, and to give a characterization of Cartan-Hartogs's geodesics with linear support.

Frank den Hollander, Shubhamoy Nandan

We consider a spatial version of the classical Moran model with seed-banks where the constituent populations have finite sizes. Individuals live in colonies labelled by $\mathbb{Z}^d$, $d\geq 1$, playing the role of a geographic space, carry one of the two $types$: $\heartsuit$ or $\spadesuit$, and change type via $resampling$ as long as they are $active$. E

Tobias Fischer

The nature of core-collapse supernova (SN) explosions is yet incompletely understood. The present article revisits the scenario in which the release of latent heat due to a first-order phase transition, from normal nuclear matter to the quark-gluon plasma, liberates the necessary energy to explain observed SN explosions. Here, the role of the metallicity of

Ariel Arza, Elisa Todarello

It was recently shown that a powerful beam of radio/microwave radiation sent out to space can produce detectable back-scattering via the stimulated decay of ambient axion dark matter. This echo is a faint and narrow signal centered at an angular frequency close to half the axion mass. In this article, we provide a detailed analytical and numerical analysis o

Faustino Palmero, Mario I. Molina, Jesús Cuevas-Maraver, Panayotis G. Kevrekidis

For a one-dimensional linear lattice, earlier work has shown how to systematically construct a slowly-decaying linear potential bearing a localized eigenmode embedded in the continuous spectrum. Here, we extend this idea in two directions: The first one is in the realm of the discrete nonlinear Schrodinger equation, where the linear operator of the Schroding

Huiyan Li, Haohong Lin, You Wang, Hengyang Wang

Silent Speech Decoding (SSD), based on articulatory neuromuscular activities, has become a prevalent task of Brain-Computer Interface (BCI) in recent years. Many works have been devoted to decoding surface electromyography (sEMG) from articulatory neuromuscular activities. However, restoring silent speech in tonal languages such as Mandarin Chinese is still

S. S. Agaev, K. Azizi, H. Sundu

In this work, we treat the newly observed doubly charmed four-quark state $ T_{cc}^{+}$ as an axial-vector tetraquark with content $cc\overline{u} \overline{d}$, and calculate its spectroscopic parameters and width. The mass and current coupling of the tetraquark $T_{cc}^{+}$ are found by means of the QCD two-point sum rule method by taking into account quar

Yufeng Wang, Dan Li, Cong Xu, Min Yang

Missing data imputation is a fundamental problem in data analysis, and many studies have been conducted to improve its performance by exploring model structures and learning procedures. However, data augmentation, as a simple yet effective method, has not received enough attention in this area. In this paper, we propose a novel data augmentation method calle

Xiaoxiao Ma, Wei Yao, Jane J. Ye, Jin Zhang

In this paper, we propose a combined approach with second-order optimality conditions of the lower level problem to study constraint qualifications and optimality conditions for bilevel programming problems. The new method is inspired by the combined approach developed by Ye and Zhu in 2010, where the authors combined the classical first-order and the value

Chuanjian Liu, Kai Han, An Xiao, Yiping Deng

Recent studies on deep convolutional neural networks present a simple paradigm of architecture design, i.e., models with more MACs typically achieve better accuracy, such as EfficientNet and RegNet. These works try to enlarge all the stages in the model with one unified rule by sampling and statistical methods. However, we observe that some network architect

Antonio Marinelli, Antonio Ambrosone, Walid Idrissi Ibnsalih, Gennaro Miele

Starburst galaxies (SBGs) and more in general starforming galaxies represent a class of galaxies with a high star formation rate (up to 100 solar masses/year). Despite their low luminosity, they can 19 be considered as guaranteed "factories" of high energy neutrinos, being "reservoirs" of accelerated 20 cosmic rays and hosting a high density

Mehdi Shokri, Mohammad Reza Setare, Salvatore Capozziello, Jafar Sadeghi

Inflationary models derived from $f(R)$ gravity, where the scalaron rolls down with a constant rate from the top to the minimum of the effective potential, are considered. Specifically, we take into account three $f(R)$ models \textit{i.e.}\,Starobinsky $R^{2}$, $R^{2p}$ and the logarithmic corrected models. We compare the inflationary parameters derived fro

Viktor Holubec, Artem Ryabov

At the dawn of thermodynamics, Carnot's constraint on efficiency of heat engines stimulated the formulation of one of the most universal physical principles, the second law of thermodynamics. In recent years, the field of heat engines acquired a new twist due to enormous efforts to develop and describe microscopic machines based on systems as small as si

Jing Liu, Zibo Miao, Libin Fu, Xiaoguang Wang

The Bhatia-Davis theorem provides a useful upper bound for the variance in mathematics, and in quantum mechanics, the variance of a Hamiltonian is naturally connected to the quantum speed limit due to the Mandelstam-Tamm bound. Inspired by this connection, we construct a formula, referred to as the Bhatia-Davis formula, for the characterization of the quantu

Jianing Li, Songsong Li, Yi Ouyang

Let $D$ be a negative integer congruent to $0$ or $1\bmod{4}$ and $\mathcal{O}=\mathcal{O}_D$ be the corresponding order of $ K=\mathbb{Q}(\sqrt{D})$. The Hilbert class polynomial $H_D(x)$ is the minimal polynomial of the $j$-invariant $ j_D=j(\mathbb{C}/\mathcal{O})$ of $\mathcal{O}$ over $K$. Let $n_D=(\mathcal{O}_{\mathbb{Q}( j_D)}:\mathbb{Z}[ j_D])$ deno

Fengping Wang, Jie Li, Siqi Zhang, Chun Qi

Micro-expressions are spontaneous, unconscious facial movements that show people's true inner emotions and have great potential in related fields of psychological testing. Since the face is a 3D deformation object, the occurrence of an expression can arouse spatial deformation of the face, but limited by the available databases are 2D videos, lacking the

Javier González-Delgado, Alberto González-Sanz, Juan Cortés, Pierre Neuvial

This work is motivated by the study of local protein structure, which is defined by two variable dihedral angles that take values from probability distributions on the flat torus. Our goal is to provide the space $\mathcal{P}(\mathbb{R}^2/\mathbb{Z}^2)$ with a metric that quantifies local structural modifications due to changes in the protein sequence, and t

Stjepan Marcelja

Rainy years and dry years in SE Australia are known to be correlated with sea surface temperatures in the specific areas of the Indian Ocean. While over the past 100 years the correlation had been both positive and negative, it significantly increased in strength since the beginning of the 21st century. Over this period, Indian Ocean sea surface temperatures

Shintaro Yuki, Kensuke Tanioka, Hiroshi Yadohisa

We consider a randomized controlled trial between two groups. The objective is to identify a population with characteristics such that the test therapy is more effective than the control therapy. Such a population is called a subgroup. This identification can be made by estimating the treatment effect and identifying interactions between treatments and covar

Gaomin Tang, Lei Zhang, Yong Zhang, Jun Chen

We consider the near-field radiative energy transfer between two separated parallel plates: graphene supported by a substrate and a magneto-optic medium. We first study the scenario in which the two plates have the same temperature. An electric current through the graphene gives rise to nonequilibrium fluctuations and induces energy transfer. Both the magnit

Ming Jin, Ieng Tak Leong, Tao Qian, Guangbin Ren

In the slice Hardy space over the unit ball of quaternions, we introduce the slice hyperbolic backward shift operator $\mathcal S_a$ with the decomposition process $$f=e_a\langle f, e_a\rangle+B_{a}*\mathcal S_a f,$$ where $e_a$ denotes the slice normalized Szegö kernel and $ B_a $ the slice Blaschke factor. Iterating the above decomposition process, a corre

Yasuaki Hayafuchi, Ryota Konno, Annisa Noorhidayati, Mohammad H. Fauzi

The even-denominator states have attracted considerable attention owing to their possible applications in future quantum technologies. In this letter, we first report a 3/2 diagonal resistance, indicating the existence of a 3/2 state in a nanometer-sized triple-gated quantum point contact (QPC) fabricated on a high-mobility (not ultra-high-mobility) single-l

Pietro Marabotti, Alberto Milani, Andrea Lucotti, Luigi Brambilla

The vibrational properties of a series of push-pull polyynes have been studied by infrared and Raman spectroscopy. The simultaneous activation of a strong infrared and Raman mode, i.e. the collective vibration of CC bonds of the sp carbon chain, highlights the effectiveness of a polyyne bridge in promoting charge transfer between the electron donor (D) and a

Wenxiao Wang, Lu Yao, Long Chen, Binbin Lin

Transformers have made great progress in dealing with computer vision tasks. However, existing vision transformers do not yet possess the ability of building the interactions among features of different scales, which is perceptually important to visual inputs. The reasons are two-fold: (1) Input embeddings of each layer are equal-scale, so no cross-scale fea

Kihwan Kim

All learning algorithms for recommendations face inevitable and critical trade-off between exploiting partial knowledge of a user's preferences for short-term satisfaction and exploring additional user preferences for long-term coverage. Although exploration is indispensable for long success of a recommender system, the exploration has been considered as

Zhongyun Bao, Chengjiang Long, Gang Fu, Daquan Liu

Integrating a foreground object into a background scene with illumination harmonization is an important but challenging task in computer vision and augmented reality community. Existing methods mainly focus on foreground and background appearance consistency or the foreground object shadow generation, which rarely consider global appearance and illumination

Sumesh Kumar, Fahad Saeed

Database algorithms play a crucial part in systems biology studies by identifying proteins from mass spectrometry data. Many of these database search algorithms incur huge computational costs by computing similarity scores for each pair of sparse experimental spectrum and candidate theoretical spectrum vectors. Modern MS instrumentation techniques which are

Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Jiawei Liu

Occluded person re-identification (ReID) aims to match person images with occlusion. It is fundamentally challenging because of the serious occlusion which aggravates the misalignment problem between images. At the cost of incorporating a pose estimator, many works introduce pose information to alleviate the misalignment in both training and testing. To achi

Bibek Poudel, Thomas Watson, Weizi Li

Autonomous micromobility has been attracting the attention of researchers and practitioners in recent years. A key component of many micro-transport vehicles is the DC motor, a complex dynamical system that is continuous and non-linear. Learning to quickly control the DC motor in the presence of disturbances and uncertainties is desired for various applicati

Byoung-moo Ann, Wouter Kessels, Gary A. Steele

In this work, we analytically and numerically study the sideband transition dynamics of the driven quantum Rabi model (QRM). We focus in particular on the conditions when the external transverse drive fields induce first-order sideband transitions. Inducing sideband transitions between two different systems is an essential technique for various physical mode

Haneul Kang, Kwanghee Park, Sunmin Ryu

Understanding charge transfer (CT) between two chemical entities and subsequent change in their charge densities is essential not only for molecular species but also for various low-dimensional materials. Because of their extremely high fraction of surface atoms, two-dimensional (2-D) materials are most susceptible to charge exchange and exhibit drastically

Verónica Vázquez-Aceves, Lorenz Zwick, Elisa Bortolas, Pedro R. Capelo

One of the main targets of the Laser Interferometer Space Antenna (LISA) is the detection of extreme mass-ratio inspirals (EMRIs) and extremely large mass-ratio inspirals (X-MRIs). Their orbits are expected to be highly eccentric and relativistic when entering the LISA band. Under these circumstances, the inspiral time-scale given by Peters' formula lose

Adityanarayanan Radhakrishnan, George Stefanakis, Mikhail Belkin, Caroline Uhler

Matrix completion problems arise in many applications including recommendation systems, computer vision, and genomics. Increasingly larger neural networks have been successful in many of these applications, but at considerable computational costs. Remarkably, taking the width of a neural network to infinity allows for improved computational performance. In t

Julia Bernatska, Yaacov Kopeliovich

A complete solution of Mumford's second problem about representation of theta derivatives with rational characteristics in terms of theta constants with rational characteristics is found. An explicit formula for computing such an expression for theta derivative with an arbitrary rational characteristic is derived, and illustrated with examples. Expressio

Jian-Wen Peng, Jie Ren

We introduce some new proximal quasi-Newton methods for unconstrained multiobjective optimization problems (in short, UMOP), where each objective function is the sum of a twice continuously differentiable strongly convex function and a proper lower semicontinuous convex but not necessarily differentiable function. We propose proximal BFGS method, proximal se

Nuno Barros e Sá, Lourenço Faria, Bernardo Alves, Miguel Cymbron

The Earth's magnetic field can be decomposed into spherical harmonics, and the exact coefficients of the decomposition can be determined through a few measurements of its value at different locations. Using measurements from a magnetometer on board the International Space Station, we computed the multipolar moments of an expansion in spherical harmonics

Yunxin Zhang

With nontrivial entropy production, first passage process is one of the most common nonequilibrium process in stochastic thermodynamics. Using one dimensional birth and death precess as a model framework, approximated expressions of mean first passage time (FPT), mean total number of jumps (TNJ), and their coefficients of variation (CV), are obtained for the

Eitan Tadmor, Changhui Tan

We study the global wellposedness of the Euler-Monge-Ampère (EMA) system. We obtain a sharp, explicit critical threshold in the space of initial configurations which guarantees the global regularity of EMA system with radially symmetric initial data. The result is obtained using two independent approaches -- one using spectral dynamics of Liu & Tadmor [Comm.

Babu R. Pokhrel

At the leading twist, the transversity distribution function, $h^{q}_{1}(x)$, where $x$ is the longitudinal momentum fraction of the proton carried by quark $q$, encodes the transverse spin structure of the nucleon. Extraction of it is difficult because of its chiral-odd nature. In transversely polarized proton-proton collisions ($p^\uparrow p$), $h_{1}^{q}(