November 2020 arXiv papers — page 45

B. S. Ham

Over the last several decades, quantum entanglement has been intensively studied for potential applications in quantum information science. Although intensive studies have progressed for nonlocal correlation, fundamental understanding of entanglement itself is still limited. Here, the quantum feature of anticorrelation, the so-called HOM dip, based on probab

Haizhou Shi, Dongliang Luo, Siliang Tang, Jian Wang

Recently, a newly proposed self-supervised framework Bootstrap Your Own Latent (BYOL) seriously challenges the necessity of negative samples in contrastive learning frameworks. BYOL works like a charm despite the fact that it discards the negative samples completely and there is no measure to prevent collapse in its training objective. In this paper, we sugg

Zhitong Ni, J. Andrew Zhang, Kai Yang, Xiaojing Huang

Joint communication and radar sensing (JCAS) integrates communication and radar/radio sensing into one system, sharing one transmitted signal. In this paper, we investigate JCAS waveform optimization underlying communication signals, where a base station detects radar targets and communicates with mobile users simultaneously. We first develop individual nove

Taishi Chen, Takahiro Tomita, Susumu Minami, Mingxuan Fu

The recent discoveries of strikingly large zero-field Hall and Nernst effects in antiferromagnets Mn$_3$$X$, ($X$ = Sn, Ge) have brought the study of magnetic topological states to the forefront of condensed matter research and technological innovation. These effects are considered fingerprints of Weyl nodes residing near the Fermi energy, promoting Mn$_3$$X

Michail Gkagkos, Charalambos D. Charalambous

This paper focuses on the structural properties of test channels, of Wyner's operational information rate distortion function (RDF), $\overline{R}(\Delta_X)$, of a tuple of multivariate correlated, jointly independent and identically distributed Gaussian random variables (RVs), $\{X_t, Y_t\}_{t=1}^\infty$, $X_t: \Omega \rightarrow {\mathbb R}^{n_x}$, $Y_t: \

Toru Kojo

Neutron stars are cosmic laboratories to study dense matter in Quantum Chromodynamics (QCD). The observable mass-radius relations of neutron stars are determined by QCD equations of state, and can reflect the properties of QCD phase transitions. In the last decade there have been historical discoveries in neutron stars, the discoveries of two-solar mass neut

Hehui Wu, Wentao Zhang

Given a graph $G$, the \textit{independence complex} $I(G)$ is the simplicial complex whose faces are the independent sets of $V(G)$. Let $\tilde{b}_i$ denote the $i$-th reduced Betti number of $I(G)$, and let $b(G)$ denote the sum of $\tilde{b}_i(G)$'s. A graph is ternary if it does not contain induced cycles with length divisible by three. G. Kalai and K.

Songhua Li, Minming Li, Lingjie Duan, Victor C. S. Lee

We study the online maximum coverage problem on a line, in which, given an online sequence of sub-intervals (which may intersect among each other) of a target large interval and an integer $k$, we aim to select at most $k$ of the sub-intervals such that the total covered length of the target interval is maximized. The decision to accept or reject each sub-in

Yudong Luo, Chao Chen, Motohiko Kusakabe, Toshitaka Kajino

We study the photodisintegration process triggered by the nonthermal electromagnetic Hawking radiation from primordial black holes (PBHs) in critical collapse model. We consider the simplest case that all PBHs formed at a single epoch stemming from an inflationary spectrum with a narrow peak, and an extended mass distribution is obtained due to critical phen

Alexandru Ionut, James C. Hateley

This work is an extension of previous work by Alazah et al. [M. Alazah, S. N. Chandler-Wilde, and S. La Porte, Numerische Mathematik, 128(4):635-661, 2014]. We split the computation of the Fresnel Integrals into 3 cases: a truncated Taylor series, modified trapezoid rule and an asymptotic expansion for small, medium and large arguments respectively. These sp

Fei Yang

We construct some explicit formulas of rational maps and transcendental meromorphic functions having Herman rings of period strictly larger than one. This gives an answer to a question raised by Shishikura in the 1980s. Moreover, the formulas of some rational maps with nested Herman rings are also found. To obtain the formulas of transcendental meromorphic f

Yiyuan Pan, Xuecheng Xu, Weijie Li, Yunxiang Cui

Place recognition is indispensable for a drift-free localization system. Due to the variations of the environment, place recognition using single-modality has limitations. In this paper, we propose a bi-modal place recognition method, which can extract a compound global descriptor from the two modalities, vision and LiDAR. Specifically, we first build the el

Zahra Tabrizi, Shunsaku Horiuchi

Although Galactic core-collapse supernovae (SNe) only happen a few times per century, every hour a vast number of explosions happen in the whole universe, emitting energy in the form of neutrinos, resulting in the diffuse supernova neutrino background (DSNB). The DSNB has not yet been detected, but Super-Kamiokande doped with gadolinium is expected to yield

Bahar Asgari, Ramyad Hadidi, Joshua Dierberger, Charlotte Steinichen

Sparse matrices are the key ingredients of several application domains, from scientific computation to machine learning. The primary challenge with sparse matrices has been efficiently storing and transferring data, for which many sparse formats have been proposed to significantly eliminate zero entries. Such formats, essentially designed to optimize memory

Feiran Zhao, Keyou You

Risk-aware control, though with promise to tackle unexpected events, requires a known exact dynamical model. In this work, we propose a model-free framework to learn a risk-aware controller with a focus on the linear system. We formulate it as a discrete-time infinite-horizon LQR problem with a state predictive variance constraint. To solve it, we parameteri

Md. Rahat-uz-Zaman, Shadmaan Hye

Handwritten numerals of different languages have various characteristics. Similarities and dissimilarities of the languages can be measured by analyzing the extracted features of the numerals. Handwritten numeral datasets are available and accessible for many renowned languages of different regions. In this paper, several handwritten numeral datasets of diff

Matthew Brigida

Previous research has found that high-frequency traders will vary the bid or offer price rapidly over periods of milliseconds. This is a benefit to fast traders who can time their trades with microsecond precision, however it is a cost to the average market participant due to increased trade execution price uncertainty. In this analysis we attempt to constru

Yuan Zhang, Liang-Yi Huang

We investigate two Lipschitz invariants of metric spaces defined by $\delta$-connected components, called the maximal power law property and the perfectly disconnectedness. The first property has been studied in literature for some self-similar sets and Bedford-McMullen carpets, while the second property seems to be new. For a self-affine Sierpi$\acute{\text

Yair Margalit, Or Dobkowski, Zhifan Zhou, Omer Amit

The Stern-Gerlach effect, discovered a century ago, has become a paradigm of quantum mechanics. Surprisingly there has been little evidence that the original scheme with freely propagating atoms exposed to gradients from macroscopic magnets is a fully coherent quantum process. Specifically, no full-loop Stern-Gerlach interferometer has been realized with the

Aayush J Rana, Yogesh S Rawat

We propose SSA2D, a simple yet effective end-to-end deep network for actor-action detection in videos. The existing methods take a top-down approach based on region-proposals (RPN), where the action is estimated based on the detected proposals followed by post-processing such as non-maximal suppression. While effective in terms of performance, these methods

Baradhwaj Coleppa, Agnivo Sarkar

We discuss the structure of a model with an extended gauge symmetry group $SU(2)\times SU(2)\times U(1)$ with a correspondingly rich Electroweak Symmetry Breaking structure. In spite of the additional scalar degrees of freedom in the model, the presence of the extra gauge group $SU(2)$ and its associated heavy vector bosons ensures that the scalar spectrum o

Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley

This is a tutorial and survey paper for Locally Linear Embedding (LLE) and its variants. The idea of LLE is fitting the local structure of manifold in the embedding space. In this paper, we first cover LLE, kernel LLE, inverse LLE, and feature fusion with LLE. Then, we cover out-of-sample embedding using linear reconstruction, eigenfunctions, and kernel mapp

Dingkang Wang, Hesong Wang, Fanghui Xiao

In this paper, we characterized the relationship between Groebner bases and u-bases: any minimal Groebner basis of the syzygy module for n univariate polynomials with respect to the term-over-position monomial order is its u-basis. Moreover, based on the gcd computation, we construct a free basis of the syzygy module by the recursive way. According to this r

Chengxi Huang, Jingtong Guan, Qiongyu Li, Fang Wu

Electrical control of magnetism in a two-dimensional (2D) semiconductor is of great interest for emerging nanoscale low-dissipation spintronic devices. Here, we propose a general approach of tuning magnetic coupling and anisotropy of a van der Waals (vdW) 2D magnetic semiconductor via a built-in electric field generated by the adsorption of superatomic ions.

Bo Wang, Lu Meng, Shi-Lin Zhu

We study the newly observed charmoniumlike state $Z_{cs}(3985)$ in the framework of chiral effective field theory. The interaction kernel of the $\bar{D}_sD^\ast/\bar{D}^\ast_sD$ system is calculated up to the next-to-leading order with the explicit chiral dynamics. With the fitted parameters extracted from the $Z_c(3900)$ data as inputs, the mass, width and

Michelle E. Chen, Miguel Muñoz Rojo, Feifei Lian, Justin Koeln

Thermal management is an important challenge in modern electronics, avionics, automotive, and energy storage systems. While passive thermal solutions (like heat sinks or heat spreaders) are often used, actively modulating heat flow (e.g. via thermal switches or diodes) would offer additional degrees of control over the management of thermal transients and sy

Sarath Sreedharan, Anagha Kulkarni, Tathagata Chakraborti, David E. Smith

Existing approaches for the design of interpretable agent behavior consider different measures of interpretability in isolation. In this paper we posit that, in the design and deployment of human-aware agents in the real world, notions of interpretability are just some among many considerations; and the techniques developed in isolation lack two key properti

Kazem Jahanbakhsh

Over the last two decades, we have seen extensive industrial research in the area of computational advertising. In this paper, our goal is to study the performance of various online learning algorithms to identify and display the best ads/offers with the highest conversion rates to web users. We formulate our ad-selection problem as a Multi-Armed Bandit prob

Diogo H. Silva, Silvio C. Ferreira

Localization phenomena permeate many branches of physics playing a fundamental role on dynamical processes evolving on heterogeneous networks. These localization analyses are frequently grounded, for example, on eigenvectors of adjacency or non-backtracking matrices which emerge in theories of dynamic processes near to an active to inactive transition. We ad

Guo-Ping Li, Ke-Jian He, Bing-Bing Chen

By dropping particles into black hole, we have employed the recently new assumption [1] that the change of the black hole mass(enthalpy) should be the same amount as the energy of an infalling particle($\omega = dM$), to carefully test the laws of thermodynamics and the weak cosmic censorship conjecture of a conformal anomaly corrected AdS black hole in diff

Avishan Bagherinezhad, Michael Young, Bei Wang, Masood Parvania

The high penetration of transportation electrification and its associated charging requirements magnify the interdependency of the transportation and power distribution systems. The emergent interdependency requires that system operators fully understand the status of both systems. To this end, a visualization tool is presented to illustrate the interdepende

Kunjal Panchal

In vision and linguistics; the main input modalities are facial expressions, speech patterns, and the words uttered. The issue with analysis of any one mode of expression (Visual, Verbal or Vocal) is that lot of contextual information can get lost. This asks researchers to inspect multiple modalities to get a thorough understanding of the cross-modal depende

Zhenyu Shou, Xu Chen, Yongjie Fu, Xuan Di

This paper aims to develop a paradigm that models the learning behavior of intelligent agents (including but not limited to autonomous vehicles, connected and automated vehicles, or human-driven vehicles with intelligent navigation systems where human drivers follow the navigation instructions completely) with a utility-optimizing goal and the system's equil

Yan Liang, Shiying Shen, Baibiao Haung, Ying Dai

2D intercorrelated ferroelectrics, exhibiting a coupled in-plane and out-of-plane ferroelectricity, is a fundamental phenomenon in the field of condensed-mater physics. The current research is based on the paradigm of bi-directional inversion asymmetry in single-layers, which restricts 2D intercorrelated ferroelectrics to extremely few systems. Herein, we pr

Patrick Letendre

We establish an explicit inequality for the number of divisors of an integer $n$. It uses the size of $n$ and its number of distinct prime divisors.

Fuxun Yu, Dimitrios Stamoulis, Di Wang, Dimitrios Lymberopoulos

This paper gives an overview of our ongoing work on the design space exploration of efficient deep neural networks (DNNs). Specifically, we cover two aspects: (1) static architecture design efficiency and (2) dynamic model execution efficiency. For static architecture design, different from existing end-to-end hardware modeling assumptions, we conduct full-s

Meenakshi Syamkumar, Yugali Gullapalli, Wei Tang, Paul Barford

This paper describes BigBen, a network telemetry processing system designed to enable accurate and timely reporting of Internet events (e.g., outages, attacks and configuration changes). BigBen is distinct from other Internet-wide event detection systems in its use of passive measurements of Network Time Protocol (NTP) traffic. We describe the architecture o

Giovanni Faria, Michel Fernandes Peres, Osmar Moreira da Silva Neto, Jefferson Rodrigo Schuertz

Electric motors can be damaged or operate improperly from a possible set of failures. Such failures are related to high or very low voltage and current levels, phase loss or blocked rotor. Therefore, it is important to protect these equipments through appropriate mechanisms. Alternatively, a workbench can simulate detectable failures related to the engines,

Prashanth Vijayaraghavan, Deb Roy

Stories are a very compelling medium to convey ideas, experiences, social and cultural values. Narrative is a specific manifestation of the story that turns it into knowledge for the audience. In this paper, we propose a machine learning approach to capture the narrative elements in movies by bridging the gap between the low-level data representations and se

Costin Bădescu, Ryan O'Donnell

We provide more sample-efficient versions of some basic routines in quantum data analysis, along with simpler proofs. Particularly, we give a quantum "Threshold Search" algorithm that requires only $O((\log^2 m)/\epsilon^2)$ samples of a $d$-dimensional state $\rho$. That is, given observables $0 \le A_1, A_2, ..., A_m \le 1$ such that $\mathrm{tr}(\rho A_i)

Lukasz Matysiak

In this paper we consider the construction of K + M, where K is the domain, M is the maximal ideal of a some ring of polynomials with coefficients from the field L, where K is its subring. In addition to the usual domains, we also consider the Noetherian, Prufer and GCD-domains. In particular, polynomial composites are a case of K + M construction. In this p

Tingting Liu, Chaobiao Zhou, Shuyuan Xiao

Enhanced optical absorption in two-dimensional (2D) materials has recently moved into the focus of nanophotonics research. In this work, we present a gain-assisted method to achieve critical coupling and demonstrate the maximum absorption in undoped monolayer graphene in the near-infrared. In a two-port system composed of photonic crystal slab loaded with gr

Rufus Willett, Guoliang Yu

We introduce controlled $KK$-theory groups associated to a pair $(A,B)$ of separable $C^*$-algebras. Roughly, these consist of elements of the usual $K$-theory group $K_0(B)$ that approximately commute with elements of $A$. Our main results show that these groups are related to Kasparov's $KK$-groups by a Milnor exact sequence, in such a way that R\o{}rdam's

Peter Schindler, Evan R. Antoniuk, Gowoon Cheon, Yanbing Zhu

The work function is the key surface property that determines how much energy is required for an electron to escape the surface of a material. This property is crucial for thermionic energy conversion, band alignment in heterostructures, and electron emission devices. Here, we present a high-throughput workflow using density functional theory (DFT) to calcul

Yuanzheng Ci, Chen Lin, Ming Sun, Boyu Chen

The automation of neural architecture design has been a coveted alternative to human experts. Recent works have small search space, which is easier to optimize but has a limited upper bound of the optimal solution. Extra human design is needed for those methods to propose a more suitable space with respect to the specific task and algorithm capacity. To furt

F. Holik, J. P. Jorge, C. Massri

We discuss a reconstruction of standard quantum mechanics assuming indistinguishability right from the start, by appealing to quasi-set theory. After recalling the fundamental aspects of the construction and introducing some improvements in the original formulation, we extract some conclusions for the interpretation of quantum theory.

Kirill A. Korinsky

We present a system for running auditable and verifiable elections in untrusted environments. Votes are anonymous since the order of candidates on a ballot sheet is random. Tellers see only the position of the candidate. Voters can check their vote. An election is auditable using blockchain log. Threshold-encryption, which is used to implement the quorum, pr

P. V. Pyshkin, A. Gábris, Da-Wei Luo, Jian-Qiang You

We propose and analyze a nonunitary variant of the continuous time Grover search algorithm based on frequent Zeno-type measurements. We show that the algorithm scales similarly to the pure quantum version by deriving tight analytical lower bounds on its efficiency for arbitrary database sizes and measurement parameters. We also study the behavior of the algo

Allen Hao, Stefano Rini, Vamsi Amalladinne, Asit Kumar Pradhan

The unsourced MAC model was originally introduced to study the communication scenario in which a number of devices with low-complexity and low-energy wish to upload their respective messages to a base station. In the original problem formulation, all devices communicate using the same information rate. This may be very inefficient in certain wireless situati

Patrick Charbonneau, Eric I. Corwin, R. Cameron Dennis, Rafael Díaz Hernández Rojas

Jamming criticality defines a universality class that includes systems as diverse as glasses, colloids, foams, amorphous solids, constraint satisfaction problems, neural networks, etc. A particularly interesting feature of this class is that small interparticle forces ($f$) and gaps ($h$) are distributed according to nontrivial power laws. A recently develop

Claudia Pérez-D'Arpino, Rebecca P. Khurshid, Julie A. Shah

Remote robot manipulation with human control enables applications where safety and environmental constraints are adverse to humans (e.g. underwater, space robotics and disaster response) or the complexity of the task demands human-level cognition and dexterity (e.g. robotic surgery and manufacturing). These systems typically use direct teleoperation at the m

Hyungjun Park, Daiki Min, Jong-hyun Ryu, Dong Gu Choi

Typical reinforcement learning (RL) methods show limited applicability for real-world industrial control problems because industrial systems involve various constraints and simultaneously require continuous and discrete control. To overcome these challenges, we devise a novel RL algorithm that enables an agent to handle a highly constrained action space. Thi

Michael Riera, Erfan Bank Tavakoli, Masudul Hassan Quraishi, Fengbo Ren

This paper presents HALO 1.0, an open-ended extensible multi-agent software framework that implements a set of proposed hardware-agnostic accelerator orchestration (HALO) principles. HALO implements a novel compute-centric message passing interface (C^2MPI) specification for enabling the performance portable execution of a hardware-agnostic host application

Brandon M. Matthews, Ohad Shemmer, Cooper Dix, Michael S. Brotherton

We present spectroscopic measurements for 226 sources from the Gemini Near Infrared Spectrograph - Distant Quasar Survey (GNIRS-DQS). Being the largest uniform, homogeneous survey of its kind, it represents a flux-limited sample ($m_{i}$ ${\lesssim}$ 19.0 mag, $H$ ${\lesssim}$ 16.5 mag) of Sloan Digital Sky Survey (SDSS) quasars at 1.5 ${\lesssim}$ $z$ ${\le

Jaeyoung Song, Marios Kountouris

We consider distributed machine learning at the wireless edge, where a parameter server builds a global model with the help of multiple wireless edge devices that perform computations on local dataset partitions. Edge devices transmit the result of their computations (updates of current global model) to the server using a fixed rate and orthogonal multiple a

Umut Can Cabuk

This thesis work presents an architectural design of a system to bring non-repudiation concept into the IP based digital voice conversations (VoIP) in LTE and UMTS networks, using electronic signatures, by considering a centralized approach. Moreover, functionalities and technical methods to support such a system are researched. Last but not least, ways to i

Hossein Talebi, Ehsan Amid, Peyman Milanfar, Manfred K. Warmuth

Conducting pairwise comparisons is a widely used approach in curating human perceptual preference data. Typically raters are instructed to make their choices according to a specific set of rules that address certain dimensions of image quality and aesthetics. The outcome of this process is a dataset of sampled image pairs with their associated empirical pref

Umut Can Cabuk, Vahid Khalilpour Akram, Orhan Dagdeviren

Topology control, including topology construction and maintenance phases, is a vital conception for wireless ad-hoc networks of any kind, expressly the wireless sensor networks (WSN). Topology maintenance, the latter phase, concerns several problems, such as optimizing the energy consumption, increasing the data rate, making clusters, and sustaining the conn

N. Safari, S. M. Mazhari, C. Y. Chung, S. B. Ko

Accurate short-term prediction of overhead line (OHL) transmission ampacity can directly affect the efficiency of power system operation and planning. Any overestimation of the dynamic thermal line rating (DTLR) can lead to lifetime degradation and failure of OHLs, safety hazards, etc. This paper presents a secure yet sharp probabilistic prediction model for

Yuki Fujimoto, Kenji Fukushima

We discuss the Hard Dense Loop resummation at finite quark mass and evaluate the equation of state (EoS) of cold and dense QCD matter in $\beta$ equilibrium. The resummation in the quark sector has an effect of lowering the baryon number density and the EoS turns out to have much smaller uncertainty than the perturbative QCD estimate. Our numerical results f

Tianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou

In this paper we present a scalable deep learning framework for finding Markovian Nash Equilibria in multi-agent stochastic games using fictitious play. The motivation is inspired by theoretical analysis of Forward Backward Stochastic Differential Equations (FBSDE) and their implementation in a deep learning setting, which is the source of our algorithm's sa

Karan Sikka, Jihua Huang, Andrew Silberfarb, Prateeth Nayak

We improve zero-shot learning (ZSL) by incorporating common-sense knowledge in DNNs. We propose Common-Sense based Neuro-Symbolic Loss (CSNL) that formulates prior knowledge as novel neuro-symbolic loss functions that regularize visual-semantic embedding. CSNL forces visual features in the VSE to obey common-sense rules relating to hypernyms and attributes.

Nicholas A. Battista

Computational scientists have investigated swimming performance across a multitude of different systems for decades. Most models depend on numerous model parameters and performance is sensitive to those parameters. In this paper, parameter subspaces are qualitatively identified in which there exists enhanced swimming performance for an idealized, simple swim

Gannon E. Lenhart, Andrew B. Royston, Keaton E. Wright

We present simulations of one magnetic monopole interacting with multiple magnetic singularities. Three-dimensional plots of the energy density are constructed from explicit solutions to the Bogomolny equation obtained by Blair, Cherkis, and Durcan. Animations follow trajectories derived from collective coordinate mechanics on the multi-centered Taub--NUT mo

Gholamreza Ramezan, Cyril Leung, Chunyan Miao

Blockchain systems are being used in a wide range of application domains. They can support trusted transactions in time critical applications. In this paper, we study how miners should pick up transactions from a transaction pool so as to minimize the average waiting time per transaction. We derive an expression for the average transaction waiting time of th

Yuhang Jiang, Lukun Zheng

Video game genre classification based on its cover and textual description would be utterly beneficial to many modern identification, collocation, and retrieval systems. At the same time, it is also an extremely challenging task due to the following reasons: First, there exists a wide variety of video game genres, many of which are not concretely defined. Se

Gourav Wadhwa, Amandeep Kharb, Satyam Mishra, Mohit Kumar

Accurate real-time assessment of power systems voltage stability has been an active area of research in the past few decades. In the past decade, after the development of phasor measurement units (PMU), a lot of discussions has been going on phasor measurement techniques for real-time voltage stability. The fundamental idea behind these methods is to find th

Marco Fasondini, Sheehan Olver, Yuan Xu

Orthogonal polynomials in two variables on cubic curves are considered, including the case of elliptic curves. For an integral with respect to an appropriate weight function defined on a cubic curve, an explicit basis of orthogonal polynomials is constructed in terms of two families of orthogonal polynomials in one variable. We show that these orthogonal pol

Jean-Claude Crivello, Nataliya Sokolovska, Jean-Marc Joubert

Machine learning (ML) methods are becoming integral to scientific inquiry in numerous disciplines, such as material sciences. In this manuscript, we demonstrate how ML can be used to predict several properties in solid-state chemistry, in particular the heat of formation of a given complex crystallographic phase (here the $\sigma-$phase, $tP30$, $D8_{b}$). B

I. García-Bernete, D. Rigopoulou, A. Alonso-Herrero, M. Pereira-Santaella

Polycyclic Aromatic Hydrocarbons (PAHs) are carbon-based molecules resulting from the union of aromatic rings and related species, which are likely responsible for strong infrared emission features (3.3, 6.2, 7.7, 8.6, 11.3 and 12.7 microns). In this work, using a sample of 50 Seyfert galaxies (DL<100 Mpc) we compare the circumnuclear (inner kpc) PAH emissio

Zhiqing Sun, Shengcao Cao, Yiming Yang, Kris Kitani

DETR is a recently proposed Transformer-based method which views object detection as a set prediction problem and achieves state-of-the-art performance but demands extra-long training time to converge. In this paper, we investigate the causes of the optimization difficulty in the training of DETR. Our examinations reveal several factors contributing to the s

Amine Amimour, Karima Belaide, Ouagnina Hili

We consider a purely fractionally deferenced process driven by a periodically time-varying long memory parameter. We will build an estimate for the vector parameters using the minimum Hellinger distance estimation. The results are investigated through simulation studies.

Kevin R. Chen, Daniel Svoboda, Kenric P. Nelson

A Coupled Variational Autoencoder, which incorporates both a generalized loss function and latent layer distribution, shows improvement in the accuracy and robustness of generated replicas of MNIST numerals. The latent layer uses a Student's t-distribution to incorporate heavy-tail decay. The loss function uses a coupled logarithm, which increases the penalt

Bing Zhao, Anamul Md. Hoque, Dmitrii Khokhriakov, Bogdan Karpiak

The efficient generation and control of spin polarization via charge-spin conversion in topological semimetals are desirable for future spintronic and quantum technologies. Here, we report the charge-spin conversion (CSC) signals measured in a Weyl semimetal candidate WTe2 based hybrid graphene device with a geometrical design. Notably, the geometrical angle

Evan S. Gawlik, Yuji Nakatsukasa

In an influential 1877 paper, Zolotarev asked and answered four questions about polynomial and rational approximation. We ask and answer two questions: what are the best rational approximants $r$ and $s$ to $\sqrt{z}$ and $\mbox{sign}(z)$ on the unit circle (excluding certain arcs near the discontinuities), with the property that $|r(z)|=|s(z)|=1$ for $|z|=1

Navid Noroozi, Andrii Mironchenko, Fabian R. Wirth

Motivated by the scalability problem in large networks, we study stability of a network of infinitely many finite-dimensional subsystems. We develop a so-called relaxed small-gain theorem for input-to-state stability (ISS) with respect to a closed set and show that every exponentially input-to-state stable system necessarily satisfies the proposed small-gain

Heng Fan, Halady Akhilesha Miththanthaya, Harshit, Siranjiv Ramana Rajan

Visual tracking has achieved considerable progress in recent years. However, current research in the field mainly focuses on tracking of opaque objects, while little attention is paid to transparent object tracking. In this paper, we make the first attempt in exploring this problem by proposing a Transparent Object Tracking Benchmark (TOTB). Specifically, TO

Tomasz Kociumaka, Saeed Seddighin

We study dynamic algorithms for the longest increasing subsequence (\textsf{LIS}) problem. A dynamic \textsf{LIS} algorithm maintains a sequence subject to operations of the following form arriving one by one: (i) insert an element, (ii) delete an element, or (iii) substitute an element for another. After performing each operation, the algorithm must report

Andreas Buttenschön, Leah Edelstein-Keshet

Mathematical and computational models can assist in gaining an understanding of cell behavior at many levels of organization. Here, we review models in the literature that focus on eukaryotic cell motility at 3 size scales: intracellular signaling that regulates cell shape and movement, single cell motility, and collective cell behavior from a few cells to t

C. W. Walter, S. E. Spielman, R. Ponce, N. D. Gibson

The first direct experimental observation of an electric quadrupole ($\textit{E}$2) transition between bound states of an atomic negative ion has been made. The transition was observed in the negative ion of bismuth by resonant (1+1) photodetachment from Bi$^-$ $^3\textit{P}_2$ via excitation of the Bi$^-$ $^3\textit{P}_0$ fine structure state. The $\textit{

Hal Schenck, Mike Stillman, Beihui Yuan

A projectively normal Calabi-Yau threefold $X \subseteq \mathbb{P}^n$ has an ideal $I_X$ which is arithmetically Gorenstein, of Castelnuovo-Mumford regularity four. Such ideals have been intensively studied when $I_X$ is a complete intersection, as well as in the case where $X$ is codimension three. In the latter case, the Buchsbaum-Eisenbud theorem shows th

Michael Mitzenmacher, Saeed Seddighin

In this note, we present a substantial improvement on the computational complexity of the Erd\"{o}s-Szekeres partitioning problem and review recent works on dynamic \textsf{LIS}.

Eric A. Carlen, Markus Holzmann, Ian Jauslin, Elliott H. Lieb

In 1963, a Simple Approach was developed to study the ground state energy of an interacting Bose gas. It consists in the derivation of an Equation, which is not based on perturbation theory, and which gives the exact expansion of the energy at low densities. This Equation is expressed directly in the thermodynamic limit, and only involves functions of $3$ va

Alexey Ovchinnikov, Anand Pillay, Gleb Pogudin, Thomas Scanlon

Structural identifiability is a property of an ODE model with parameters that allows for the parameters to be determined from continuous noise-free data. This is a natural prerequisite for practical identifiability. Conducting multiple independent experiments could make more parameters or functions of parameters identifiable, which is a desirable property to

Can Bakiskan, Metehan Cekic, Ahmet Dundar Sezer, Upamanyu Madhow

Deep Neural Networks (DNNs) are vulnerable to adversarial attacks: carefully constructed perturbations to an image can seriously impair classification accuracy, while being imperceptible to humans. While there has been a significant amount of research on defending against such attacks, most defenses based on systematic design principles have been defeated by

Miroslav Bures, Vaclav Rechtberger

In testing of software and Internet of Things (IoT) systems, one of necessary type of tests has to verify the consistency of data that are processed and stored in the system. The Data Cycle Test technique can effectively do such tests. The goal of this technique is to verify that the system processes data entities in a system under test in a correct way and

Matej Klima, Vaclav Rechtberger, Miroslav Bures, Xavier Bellekens

Quality and reliability metrics play an important role in the evaluation of the state of a system during the development and testing phases, and serve as tools to optimize the testing process or to define the exit or acceptance criteria of the system. This study provides a consolidated view on the available quality and reliability metrics applicable to Inter

Philip J. Morrison, Yoshifumi Kimura

The recently proposed low degree-of-freedom model of Moffat and Kimura [1,2] for describing the approach to finite-time singularity of the incompressible Euler fluid equations is investigated. The model assumes an initial finite-energy configuration of two vortex rings placed symmetrically on two tilted planes. The Hamiltonian structure of the inviscid limit

Mengyang Gu, Hanmo Li

We introduce Gaussian orthogonal latent factor processes for modeling and predicting large correlated data. To handle the computational challenge, we first decompose the likelihood function of the Gaussian random field with a multi-dimensional input domain into a product of densities at the orthogonal components with lower-dimensional inputs. The continuous-

Lukáš Vacek, Václav Kučera

In this paper, we describe a numerical technique for the solution of macroscopic traffic flow models on networks of roads. On individual roads, we consider the standard Lighthill-Whitham-Richards model which is discretized using the discontinuous Galerkin method along with suitable limiters. In order to solve traffic flows on networks, we construct suitable

Cheolhei Lee, Jianguo Wu, Wenjia Wang, Xiaowei Yue

Developing machine learning enabled smart manufacturing is promising for composite structures assembly process. To improve production quality and efficiency of the assembly process, accurate predictive analysis on dimensional deviations and residual stress of the composite structures is required. The novel composite structures assembly involves two challenge

Manpreet Singh Jattana, Fengping Jin, Hans De Raedt, Kristel Michielsen

A general method to mitigate the effect of errors in quantum circuits is outlined. The method is developed in sight of characteristics that an ideal method should possess and to ameliorate an existing method which only mitigates state preparation and measurement errors. The method is tested on different IBM Q quantum devices, using randomly generated circuit

Roger Baker, Glyn Harman

Let c > 0.55. Every large n can be written in the form p +ab, where p is prime, a and b are significantly smaller than x^1/2 and ab is less than n^c. This strengthens a result of Heath-Brown, which has the requirement c>3/4. We introduce the idea of 'intersecting two sieves' as a tool in the proof of this result.

Askar Ali

A recently proposed model for nonlinear electrodynamics has been minimally coupled to dimensionally continued gravity and the topological black holes in the presence of conformal scalar field were studied. In this setup, the new magnetized hairy black hole solution has been found and its thermodynamic properties have also been analyzed. The exact expressions

Mahdi Biparva, John Tsotsos

Feature disentanglement of the foreground target objects and the background surrounding context has not been yet fully accomplished. The lack of network interpretability prevents advancing for feature disentanglement and better generalization robustness. We study the role of the context on interfering with a disentangled foreground target object representati

Dallas Albritton, Zachary Bradshaw

We develop a theory of self-similar solutions to the critical surface quasi-geostrophic equations. We construct self-similar solutions for arbitrarily large data in various regularity classes and demonstrate, in the small data regime, uniqueness and global asymptotic stability. These solutions are non-decaying as $|x| \to +\infty$, which leads to ambiguity i

Marjorie K. Drake

Let $L^{m,p}(\mathbb{R}^n)$ be the homogeneous Sobolev space for $p \in (n,\infty)$, $\mu$ be a Borel regular measure on $\mathbb{R}^n$, and $L^{m,p}(\mathbb{R}^n) + L^p(d\mu)$ be the space of Borel measurable functions with finite seminorm $\|f\|_{L^{m,p}(\mathbb{R}^n) + L^p(d\mu)} := \text{inf}_{f_1 +f_2 = f} \{ \|f_1\|_{L^{m,p}(\mathbb{R}^n)}^p + \int_{\m

Conor L. Morrison, Priscilla E. Greenwood, Lawrence M. Ward

Oscillatory phase pattern formation and amplitude control for a linearized stochastic neuron field model was investigated by simulating coupled stochastic processes defined by stochastic differential equations. It was found, for several choices of parameters, that pattern formation in the phases of these processes occurred if and only if the amplitudes were

Raj Dandekar

Impacts of drops on liquids are ubiquitous in nature and in a range of applications in healthcare, agriculture and industry. They can lead to splash and generation of secondary droplets important for a range of coating, dispersal or contaminant problems. The physics of splash, despite being more than a century old problem, still has a number of unanswered qu

Melika Payvand, Mohammed E. Fouda, Fadi Kurdahi, Ahmed M. Eltawil

Recent breakthroughs in neuromorphic computing show that local forms of gradient descent learning are compatible with Spiking Neural Networks (SNNs) and synaptic plasticity. Although SNNs can be scalably implemented using neuromorphic VLSI, an architecture that can learn using gradient-descent in situ is still missing. In this paper, we propose a local, grad