August 2022 arXiv papers — page 101

Hiranya Kishore Dey, Archita Mondal

For a finite group $G$, let $\psi(G)$ denote the sum of element orders of $G$. This function was introduced by Amiri, Amiri, and Isaacs in 2009 and they proved that for any finite group $G$ of order $n$, $\psi(G)$ is maximum if and only if $G \simeq \mathbb{Z}_n$ where $\mathbb{Z}_n$ denotes the cyclic group of order $n$. Furthermore, Herzog, Longobardi, and

Elad Zohar, Yanay Florshaim, Oded Zilberman, Amir Stern

We report on the implementation of degenerate Raman sideband cooling of $^{40}$K atoms. The scheme incorporates a 3D optical lattice, which confines the atoms and drives the Raman transitions. The optical cooling cycle is closed by two optical pumping beams. The wavelength of the laser beams forming the lattice is close to the D$_2$ atomic transition, while

G. A. Grigorian

A new approach is used to obtain a global solvability criterion for matrix Riccati equations. It is shown that the obtained result is an extension of a result derived from a comparison theorem for matrix Riccati equations. Two corollaries were drawn from the obtained result as well.

Xinglei Yu, Chengjie Zhang

Quantum parameter estimation with Hermitian systems has been applied in various fields, but there are relatively few results concerning non-Hermitian systems. Here, we study the quantum parameter estimation for general non-Hermitian Hamiltonians and derive an intuitive expression of quantum Fisher information (QFI) for pure states. Furthermore, we propose th

G. Adhikari, N. Carlin, J. J. Choi, S. Choi

The DAMA/LIBRA collaboration has reported the observation of an annual modulation in the event rate that has been attributed to dark matter interactions over the last two decades. However, even though tremendous efforts to detect similar dark matter interactions were pursued, no definitive evidence has been observed to corroborate the DAMA/LIBRA signal. Many

Somadutta Bhatta, Vipul Bairathi

Observables in heavy-ion collisions are generally categorized into centralities, which reflect an average over events within a range of impact parameter including a wide variety of initial state configurations. A multiple binning method using spectator neutrons within each centrality has been previously shown to provide access to events with rare initial sta

Rajni Bala, Sooryansh Asthana, V. Ravishankar

There is a wealth of simulation, experimental and analytical studies on propagation of orbital angular momentum (OAM) modes through atmospheric and oceanic turbulence.} Using the data of these studies and generalising the framework proposed in [Bala et al., [arXiv:2208.04555] for error-immune information transfer, we accomplish two tasks. First, we identify

Sai Peng, Peng Yu

In this study, the OpenFOAM platform, based on the finite volume method, is applied to investigate the two-dimensional viscoelastic flow past a circular cylinder. The FENE-P model, which considers the bounded elongation of polymer molecules, is chosen to describe the elastic constitutive relationship of the polymer solution. The maximum molecular chain lengt

Damaz de Jong, Christian G. Prosko, Lin Han, Filip K. Malinowski

Cooper pair splitters hold utility as a platform for investigating the entanglement of electrons in Cooper pairs, but probing splitters with voltage-biased Ohmic contacts prevents the retention of electrons from split pairs since they can escape to the drain reservoirs. We report the ability to controllably split and retain single Cooper pairs in a multi-qua

Hongxin Dong, Peng Sun, Bin Yan

It is well know that the precise measurement of $H\to\gamma\gamma$ can generate two degenerate parameter spaces of $H\gamma\gamma$ anomalous coupling. We propose to utilize the exclusive Higgs rare decays $H\to\Upsilon(ns)+\gamma$ to break above mentioned degeneracy and further to constrain the $H\gamma\gamma$ anomalous coupling at the HL-LHC. We demonstrate

Venktesh Viswanathan, Mukesh Mohania, Vikram Goyal

Online learning systems have multiple data repositories in the form of transcripts, books and questions. To enable ease of access, such systems organize the content according to a well defined taxonomy of hierarchical nature (subject-chapter-topic). The task of categorizing inputs to the hierarchical labels is usually cast as a flat multi-class classificatio

J. B. S. Mendes, R. O. Cunha, S. O. Ferreira, R. D. dos Reis

In this paper we present spin-to-charge current conversion properties in the Weyl semimetal TaP by means of the inverse Rashba-Edelstein effect (IREE) with the integration of this quantum material with the ferromagnetic metal Permalloy $(Py=Ni_{81}Fe_{19})$. The spin currents are generated in the Py layer by the spin pumping effect (SPE) from microwave-drive

Ar Rohim, Apriadi Salim Adam, Kazuhiro Yamamoto

We study the system of a massive fermion field confined between two parallel plates, where the properties of both plates are discussed under chiral MIT boundary conditions. We investigate the effects of the chiral angle on the Casimir energy for a massive fermion field with the general momentum. We find that the Casimir energy as a function of the chiral ang

Kohji Matsumoto, Hirofumi Tsumura

This paper is a continuation of our previous work on double Dirichlet series associated with arithmetic functions such as the von Mangoldt function, the M\"obius function, and so on. We consider the analytic behaviour around the non-positive integer points on singularity sets which are points of indeterminacy. In particular, we show a certain reciprocity law

Ali Khezeli

It is known that the size of the largest common subtree (i.e., the maximum agreement subtree) of two independent random binary trees with $n$ given labeled leaves is of order between $n^{0.366}$ and $n^{1/2}$. We improve the lower bound to order $n^{0.4464}$ by constructing a common subtree recursively and by proving a lower bound for its asymptotic growth.

Christopher Barua, Eric Burkholder, Gabriel Fragoso, Zsuzsanna Szaniszlo

We are investigating who has the winning strategy in a game in which two players take turns drawing arrows trying to complete cycle cells in a graph. A cycle cell is a cycle with no chords. We examine game boards where the winning strategy was previously unknown. Starting with a $C_{5}$ sharing two consecutive edges with a $C_{7}$ we solve multiple classes o

Masanobu Kaneko, Hirofumi Tsumura

We present several formulas for some specific multiple $L$-values of conductor four. This grew out from the study of zeta functions of level four of Arakawa-Kaneko type. Closely related is a new version of multiple poly-Euler numbers and we briefly discuss this too.

Katerina Santicola

Let $\mathscr{P}_\mathbb{Q}=\{ \alpha^n \; : \; \alpha \in \mathbb{Q}, \; n \ge 2\}$ be the set of rational perfect powers, and let $S \subseteq \mathscr{P}_\mathbb{Q}$ be a finite subset. We prove the existence of a polynomial $f_S \in \mathbb{Z}[X]$ such that $f(\mathbb{Q}) \cap \mathscr{P}_\mathbb{Q}=S$. This generalizes a recent theorem of Gajovi\'{c} wh

Weiqing Gu, Bohan Yang, Ryan Chang

This paper addresses both the various EEG applications and the current EEG market ecosystem propelled by machine learning. Increasingly available open medical and health datasets using EEG encourage data-driven research with a promise of improving neurology for patient care through knowledge discovery and machine learning data science algorithm development.

Rebecca Odom

A partition of a positive integer $n$ is defined as a non-increasing sequence $P = [y_0, y_1, ..., y_m]$ of positive integers which sum to $n$, where the $y_i$ are called the $parts$ of the partition. A Young diagram is a visual representation of a partition using rows of boxes, where each row of boxes corresponds to a part. The conjugate partition is simila

David Baraglia, Pedram Hekmati

In this paper we further develop the theory of equivariant Seiberg-Witten-Floer cohomology of the two authors, with an emphasis on Brieskorn homology spheres. We obtain the following applications. First, we show that the knot concordance invariants $\theta^{(c)}$ defined by the first author satisfy $\theta^{(c)}(T_{a,b}) = (a-1)(b-1)/2$ for torus knots, when

Siyu Wang, Xiaocong Chen, Lina Yao, Sally Cripps

Recent advances in recommender systems have proved the potential of Reinforcement Learning (RL) to handle the dynamic evolution processes between users and recommender systems. However, learning to train an optimal RL agent is generally impractical with commonly sparse user feedback data in the context of recommender systems. To circumvent the lack of intera

Graziela Fonseca, Grasiela Martini, Leonardo Silva

In this paper, we characterize suitable partial (co)actions of Taft and Nichols Hopf algebras on algebras, and moreover we get that such partial (co)actions are symmetric. For certain algebras, these partial (co)actions obtained are, indeed, all of them. This work generalizes the results obtained by the authors in \cite{taft_corpo_revista}.

Sangjoon Park, Eun Sun Lee, Kyung Sook Shin, Jeong Eun Lee

Oversight AI is an emerging concept in radiology where the AI forms a symbiosis with radiologists by continuously supporting radiologists in their decision-making. Recent advances in vision-language models sheds a light on the long-standing problems of the oversight AI by the understanding both visual and textual concepts and their semantic correspondences.

Kenta Suzuki

We calculate the asymptotic behavior of the dimension of the fixed vectors of $\pi$ with respect to compact open subgroups $1+ M_n(\mathfrak{p}^N)\subset\mathrm{GL}_n(F)$ for $\pi$ an admissible representation of $\mathrm{GL}_n(F)$, and $F$ a nonarchimedean local field. Such dimensions can be calculated by germs of the character of $\pi$. We also make some o

Yuang Tian, Hong Zhang, Alexandre Bureau, Hagit Hochner

Parental origin effects play an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parental origin effects and is often convenient to collect in practice. Most existing methods for assessing parental origin effects do not incorporate any covariates, which may be required to control for confou

D. S. Gireesh, B. Hemanthkumar

In this article, we provide partition-theoretic interpretations for some new truncated pentagonal number theorem and identities of Gauss. Also, we deduce few inequalities for some partition functions.

Guochun Wu, Lei Yao, Yinghui Zhang

We are concerned with the instability of a generic compressible two-fluid model in the whole space $\mathbb{R}^3$, where the capillary pressure $f(\alpha^-\rho^-)=P^+-P^-\neq 0$ is taken into account. For the case that the capillary pressure is a strictly decreasing function near the equilibrium, namely, $f'(1)<0$, Evje-Wang-Wen established global stability

Guangyuan Shen, Dehong Gao, Duanxiao Song, Libin Yang

Client selection schemes are widely adopted to handle the communication-efficient problems in recent studies of Federated Learning (FL). However, the large variance of the model updates aggregated from the randomly-selected unrepresentative subsets directly slows the FL convergence. We present a novel clustering-based client selection scheme to accelerate th

Doudou Zhou, Molei Liu, Mengyan Li, Tianxi Cai

Due to label scarcity and covariate shift happening frequently in real-world studies, transfer learning has become an essential technique to train models generalizable to some target populations using existing labeled source data. Most existing transfer learning research has been focused on model estimation, while there is a paucity of literature on transfer

Yu-Cheng Chen, Jiong Cheng, Wen-Zhao Zhang, Cheng-Jie Zhang

Quantum coherence is a crucial resource in quantum resource theory. Previous study mainly focused on standard coherence under a complete orthogonal reference basis. The standard coherence has recently been extended to general positive-operator-valued measure (POVM)-based coherence, including block coherence as a special case. Therefore, it is necessary to co

Guo-Dong Lu, Zhou Zhang, Yue Dai, Yu-Li Dong

It is well known that one can extract all the information of an unknown quantum channel by means of quantum process tomography, such as standard quantum-process tomography and ancilla-assisted quantum process tomography (AAQPT). Furthermore, it has been shown that entanglement is not necessary for AAQPT, there exist separable states which are also useful for

Anvay Grover, Ruediger Ehlers, Loris D'Antoni

Automating string transformations has been one of the killer applications of program synthesis. Existing synthesizers that solve this problem produce programs in domain-specific languages (DSL) that are engineered to help the synthesizer, and therefore lack nice formal properties. This limitation prevents the synthesized programs from being used in verificat

Sungjae Lee, Yoonseo Hur, Subin Park, Kyungyong Lee

Training a Convolutional Neural Network (CNN) model typically requires significant computing power, and cloud computing resources are widely used as a training environment. However, it is difficult for CNN algorithm developers to keep up with system updates and apply them to their training environment due to quickly evolving cloud services. Thus, it is impor

Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh

The goal of robust reinforcement learning (RL) is to learn a policy that is robust against the uncertainty in model parameters. Parameter uncertainty commonly occurs in many real-world RL applications due to simulator modeling errors, changes in the real-world system dynamics over time, and adversarial disturbances. Robust RL is typically formulated as a max

Jose Carlos Pelayo, Karol Gietka, Thomas Busch

In distributed quantum sensing the correlations between multiple modes, typically of a photonic system, are utilized to enhance the measurement precision of an unknown parameter. In this work we investigate the metrological potential of a multi-mode, tilted Bose-Hubbard system and show that it can allow for parameter estimation at the Heisenberg limit of $(N

Kamiar Asgari, Michael J. Neely

In this paper, we provide a sub-gradient based algorithm to solve general constrained convex optimization without taking projections onto the domain set. The well studied Frank-Wolfe type algorithms also avoid projections. However, they are only designed to handle smooth objective functions. The proposed algorithm treats both smooth and non-smooth problems a

Bhavya Ghai, Klaus Mueller

With the rise of AI, algorithms have become better at learning underlying patterns from the training data including ingrained social biases based on gender, race, etc. Deployment of such algorithms to domains such as hiring, healthcare, law enforcement, etc. has raised serious concerns about fairness, accountability, trust and interpretability in machine lea

Shimin Tao, Weibin Meng, Yimeng Chen, Yichen Zhu

Logs are one of the most critical data for service management. It contains rich runtime information for both services and users. Since size of logs are often enormous in size and have free handwritten constructions, a typical log-based analysis needs to parse logs into structured format first. However, we observe that most existing log parsing methods cannot

Guangsheng Yu, Xu Wang, Ren Ping Liu

In certain Blockchain systems, multiple Blockchains are required to operate cooperatively for security, performance, and capacity considerations. This invention defines a cross-chain mechanism where a main Blockchain issues the tokens, which can then be transferred and used in multiple side Blockchains to drive their operations. A set of witnesses are create

R. Arun, R. Gopal, V. K. Chandrasekar, M. Lakshmanan

The dynamics of the magnetization of the free layer in a spin-torque nano oscillator (STNO) influenced by a noncollinear alignment between the magnetizations of the free and pinned layers due to an interlayer exchange coupling has been investigated theoretically. The orientations of the magnetization of the free layer with that of the pinned layer have been

Myung Gyoon Lee, Jang Ho Bae, In Sung Jang

We present a survey of globular clusters (GCs) in the massive gravitational lens cluster SMACS J0723.3-7327 at $z=0.39$ based on the early released JWST/NIRCam images. In the color-magnitude diagrams of the point sources we find clearly a rich population of intracluster GCs that spread in a wide area of the cluster. Their ages, considering the cluster redshi

Dmitrii L. Maslov, Abhishek Kumar, Saurabh Maiti

A combination of spin-orbit coupling and electron-electron interaction gives rise to a new type of collective spin modes, which correspond to oscillations of magnetization even in the absence of the external magnetic field. We review recent progress in theoretical understanding and experimental observation of such modes, focusing on three examples of real-li

Kaitao Song, Teng Wan, Bixia Wang, Huiqiang Jiang

Hypernasality is an abnormal resonance in human speech production, especially in patients with craniofacial anomalies such as cleft palate. In clinical application, hypernasality estimation is crucial in cleft palate diagnosis, as its results determine the subsequent surgery and additional speech therapy. Therefore, designing an automatic hypernasality asses

Ryo Okano, Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa

Isotonic regression or monotone function estimation is a problem of estimating function values under monotonicity constraints, which appears naturally in many scientific fields. This paper proposes a new Bayesian method with global-local shrinkage priors for estimating monotone function values. Specifically, we introduce half shrinkage priors for positive va

Zhilin Wang, Qin Hu, Minghui Xu, Honglu Jiang

Although Metaverse has recently been widely studied, its practical application still faces many challenges. One of the severe challenges is the lack of sufficient resources for computing and communication on local devices, resulting in the inability to access the Metaverse services. To address this issue, this paper proposes a practical blockchain-based mobi

Atia Hamidizadeh, Tony Shen, Martin Ester

Molecular Representation Learning is essential to solving many drug discovery and computational chemistry problems. It is a challenging problem due to the complex structure of molecules and the vast chemical space. Graph representations of molecules are more expressive than traditional representations, such as molecular fingerprints. Therefore, they can impr

Yongke Wu, Xiaoping Xie

Mixed finite element methods are considered for a ferrofluid flow model with magnetization paralleled to the magnetic field. The ferrofluid model is a coupled system of the Maxwell equations and the incompressible Navier-Stokes equations. By skillfully introducing some new variables, the model is rewritten as several decoupled subsystems that can be solved i

Taesik Gong, Jongheon Jeong, Taewon Kim, Yewon Kim

Test-time adaptation (TTA) is an emerging paradigm that addresses distributional shifts between training and testing phases without additional data acquisition or labeling cost; only unlabeled test data streams are used for continual model adaptation. Previous TTA schemes assume that the test samples are independent and identically distributed (i.i.d.), even

Fabian Keller, Andreas Heuer

Cholesterol (CHOL) is one of the most important components of plasma membranes of higher cells and one of the main factors for the formation of (nano)domains. In this work, molecular dynamics simulations of mixtures of CHOL with DPPC (saturated lipid) and DLiPC (unsaturated lipid) as standard phospholipids (PLs) are presented in a wide range of CHOL concentr

Ryota Yambe, Satoru Hayami

Topological spin textures, such as a skyrmion crystal, are a source of unusual physical phenomena owing to the interplay between magnetism and topology. Since physical phenomena depend on the topological property and the symmetry of underlying spin structures, the search for new topological spin textures and emergent phenomena is one of the challenges in con

Zhen Liu, Yinglong Wang, Bing Zeng, Shuaicheng Liu

High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images with realistic details. Restricted by the locality of the receptive field, existing CNN-based methods are typically prone to producing ghosting artifacts and intensity distortions in the presence of large motion and severe saturation. In this paper, we propose a novel Contex

Junan Pan, Zhihao Zhao

A recommender system is a system that helps users filter irrelevant information and create user interest models based on their historical records. With the continuous development of Internet information, recommendation systems have received widespread attention in the industry. In this era of ubiquitous data and information, how to obtain and analyze these d

Mario Michael Krell, Nils Wilshusen, Anett Seeland, Su Kyoung Kim

Objective: Classifier transfers usually come with dataset shifts. To overcome them, online strategies have to be applied. For practical applications, limitations in the computational resources for the adaptation of batch learning algorithms, like the SVM, have to be considered. Approach: We review and compare several strategies for online learning with SVMs.

Kingman Cheung, Jui-Lin Kuo, Po-Yan Tseng, Zeren Simon Wang

We consider a muonphilic axion-like-particle (ALP), denoted as $a$, lighter than twice the muon mass. ALPs of this mass range dominantly decay into a pair of photons, induced by a triangular muon loop. Such light muonphilic ALPs are naturally long-lived. At the atmosphere, the ALPs are copiously produced from charged-meson decays in air showers, such as $\pi

Shichao Dong, Ruibo Li, Jiacheng Wei, Fayao Liu

Instance segmentation on 3D point clouds has been attracting increasing attention due to its wide applications, especially in scene understanding areas. However, most existing methods operate on fully annotated data while manually preparing ground-truth labels at point-level is very cumbersome and labor-intensive. To address this issue, we propose a novel we

Guangsheng Yu, Ren Ping Liu, J. Andrew Zhang, Y. Jay Guo

We investigate the tamper-resistant property of Blockchain and its effectiveness for IoT systems. In particular, we implemented an IoT testbed, and built a Blockchain into the testbed. A number of tamper-resistance experiments were conducted and analyzed to corroborate the process of block validation in Blockchain. Our analysis and experimental results demon

Meixiang Huang, Yuanjin Wang, Zhiqiang Shao

In this paper, we solve constructively the piston problem for one-dimensional isentropic Euler equations of modified Chaplygin gas. In solutions, we prove rigorously the global existence and uniqueness of a shock wave separating constant states ahead of the piston when the piston pushed forward into the gas. It is quite different from the results of Chaplygi

Xiwang Cao, Gaojun Luo

Fractional revival, known as a quantum transport phenomenon, is essential for entanglement generation in quantum spin networks. The concept of fractional revival is a generalization of perfect state transfer and periodicity on graphs. In this paper, we propose a sufficient and necessary condition for abelian Cayley graphs having fractional revival between an

T. J. Burns, E. S. Swanson

We present a model for the $J/\psi\Lambda$ spectrum in $B^-\to J/\psi \Lambda \bar{p}$ decays, including the $P_{\psi s}^\Lambda(4338)$ baryon recently observed by the LHCb collaboration. We assume production via triangle diagrams which couple to the final state via non-perturbative interactions which are constrained by heavy-quark and $SU_3$-flavor symmetry

J. A. Martínez-Cadena

We will study two subclasses of the class of feebly compact spaces in the class of (para)topological groups, the compact-bounded and weakly compact-bounded spaces, both introduced by J. Angoa, Y. F. Ortiz-Castillo and A. Tamariz-Mascar\'ua in [4]. Also, we will study the $r$-weakly compact-bounded subsets of a topological space $X$.

Lantian Feng, Ming Zhang, Jianwei Wang, Xiaoqi Zhou

With high integration density and excellent optical properties, silicon photonics is becoming a promising platform for complete integration and large-scale optical quantum information processing. Scalable quantum information applications need photon generation and detection to be integrated on the same chip, and we have seen that various devices on the silic

Mamoon Obiedat, Sandhya Samarasinghe

This study implements a novel Fuzzy Cognitive Map (FCM) framework for addressing large complex socio-ecological problems. These are characterized as qualitative, dominated by uncertainty, human involvement with different and vague perceptions/expectations, and complex systems dynamics due to feedback relations. The FCM framework provides a participatory soft

Matthew K. Tam, Daniel J. Uteda

Variational inequalities provide a framework through which many optimisation problems can be solved, in particular, saddle-point problems. In this paper, we study modifications to the so-called Golden RAtio ALgorithm (GRAAL) for variational inequalities -- a method which uses a fully explicit adaptive step-size, and provides convergence results under local L

Robert Redmond, Nathan W. Weckwerth, Brian S. Xia, Qian Li

We recently proposed a new cluster operating system stack, DBOS, centered on a DBMS. DBOS enables unique support for ML applications by encapsulating ML code within stored procedures, centralizing ancillary ML data, providing security built into the underlying DBMS, co-locating ML code and data, and tracking data and workflow provenance. Here we demonstrate

Li Liu, Xiangeng Fang, Di Wang, Weijing Tang

Neural Network (Deep Learning) is a modern model in Artificial Intelligence and it has been exploited in Survival Analysis. Although several improvements have been shown by previous works, training an excellent deep learning model requires a huge amount of data, which may not hold in practice. To address this challenge, we develop a Kullback-Leibler-based (K

Sam Condon, Marco Viero, James Bock, Howard Hui

Selected as the next NASA Medium Class Explorer mission, SPHEREx, the Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer is planned for launch in early 2025. SPHEREx calibration data products include detector spectral response, non-linearity, persistence, and telescope focus error measurements. To produce these calib

Song Sun, Junsheng Zhang

We discover a "no semistability at infinity" phenomenon for complete Calabi-Yau metrics asymptotic to cones, by eliminating the possible appearance of an intermediate K-semistable cone in the 2-step degeneration theory developed by Donaldson and the first author. It is in sharp contrast to the setting of local singularities of K\"ahler-Einstein metrics. A by

Beibut Sh. Kulpeshov, Sergey V. Sudoplatov

We study semantic and syntactic properties of spherical orders and their elementary theories, including finite and dense orders and their theories. It is shown that theories of dense $n$-spherical orders are countably categorical and decidable. The values for spectra of countable models of unary expansions of $n$-spherical theories are described. The Vaught

Masato Matsuura, Takahiko Sasaki, Makoto Naka, Jens Müller

The low-temperature state of the quantum spin liquid candidate $\kappa$-(BEDT-TTF)$_{2}$Cu$_{2}$(CN)$_{3}$ emerges via an anomaly at $T^{*}\sim6$ K. Although signatures of this anomaly have been revealed in various quantities, its origin has remained unclear. Here we report inelastic neutron scattering measurements on single crystals of $\kappa$-(BEDT-TTF)$_

François Pomerleau

Definition: The terms "robotics in snow and ice" refers to robotic systems being studied, developed, and used in areas where water can be found in its solid state. This specialized branch of field robotics investigates the impact of extreme conditions related to cold environments on autonomous vehicles.

Gui-Qiang G. Chen, Yucong Huang, Shengguo Zhu

We establish the global-in-time existence of solutions of the Cauchy problem for the full Navier-Stokes equations for compressible heat-conducting flow in multidimensions with initial data that are large, discontinuous, spherically symmetric, and away from the vacuum. The solutions obtained here are of global finite total relative-energy including the origin

Fujun Hou

`Rank and Yank' is practiced in many organizations. This paper is concerned with the condtions for none to be whipped by `Rank and Yank' when the evaluation data under each criterion are assumed to be ordinal rankings and the majority rule is used. Two sufficient conditions are set forth of which the first one formulates the alternatives indifference definit

Angela Zavaleta-Bernuy, Qi Yin Zheng, Hammad Shaikh, Jacob Nogas

Adaptive experiments can increase the chance that current students obtain better outcomes from a field experiment of an instructional intervention. In such experiments, the probability of assigning students to conditions changes while more data is being collected, so students can be assigned to interventions that are likely to perform better. Digital educati

Xiuqi Wu, Ying Zhang, Junsong Peng, Sonia Boscolo

Nonlinear systems with two competing frequencies show locking or resonances. In lasers, the two interacting frequencies can be the cavity repetition rate and a frequency externally applied to the system. Conversely, the excitation of breather oscillations in lasers naturally triggers a second characteristic frequency in the system, therefore showing competit

Fernando J. Yanez, Angela Zavaleta-Bernuy, Ziwen Han, Michael Liut

Conducting randomized experiments in education settings raises the question of how we can use machine learning techniques to improve educational interventions. Using Multi-Armed Bandits (MAB) algorithms like Thompson Sampling (TS) in adaptive experiments can increase students' chances of obtaining better outcomes by increasing the probability of assignment t

Yu Shen, Murat Simsek, Burak Kantarci, Hussein T. Mouftah

The number of Internet of Things (IoT) devices being deployed into networks is growing at a phenomenal level, which makes IoT networks more vulnerable in the wireless medium. Advanced Persistent Threat (APT) is malicious to most of the network facilities and the available attack data for training the machine learning-based Intrusion Detection System (IDS) is

Alen Senanian, Logan G. Wright, Peter F. Wade, Hannah K. Doyle

Photonic simulators using synthetic frequency dimensions have enabled flexible experimental analogues of condensed-matter systems, realizing phenomena that are impractical to observe in real-space systems. However, to date such photonic simulators have been limited to small systems suffering from finite-size effects. Here, we present an analog simulator capa

Angela Zavaleta-Bernuy, Ziwen Han, Hammad Shaikh, Qi Yin Zheng

Email communication between instructors and students is ubiquitous, and it could be valuable to explore ways of testing out how to make email messages more impactful. This paper explores the design space of using emails to get students to plan and reflect on starting weekly homework earlier. We deployed a series of email reminders using randomized A/B compar

H. Avakian, T. B. Hayward, A. Kotzinian, W. R. Armstrong

We report the first measurements of deep inelastic scattering spin-dependent azimuthal asymmetries in back-to-back dihadron electroproduction, where two hadrons are produced in opposite hemispheres along the z-axis in the center-of-mass frame, with the first hadron produced in the current-fragmentation region and the second in the target-fragmentation region

Jinxin Liu, Murat Simsek, Burak Kantarci, Mehran Bagheri

Intrusion Detection Systems (IDS) are critical security mechanisms that protect against a wide variety of network threats and malicious behaviors on networks or hosts. As both Network-based IDS (NIDS) or Host-based IDS (HIDS) have been widely investigated, this paper aims to present a Combined Intrusion Detection System (CIDS) that integrates network and hos

Fedor Sukochev, Dmitriy Zanin

We discuss the optimality of Cwikel-Solomyak estimates for the uniform operator norm and establish optimality of M.Z Solomyak's results \cite{Solomyak1995} within the class of Orlicz spaces. Our methods are based on finding the optimal version of the Sobolev embedding theorem.

Pavel Czempin, Adam Gleave

Self-play reinforcement learning has achieved state-of-the-art, and often superhuman, performance in a variety of zero-sum games. Yet prior work has found that policies that are highly capable against regular opponents can fail catastrophically against adversarial policies: an opponent trained explicitly against the victim. Prior defenses using adversarial t

Zhi-Kang Lin, Qiang Wang, Yang Liu, Haoran Xue

There are two prominent applications of the mathematical concept of topology to the physics of materials: band topology, which classifies different topological insulators and semimetals, and topological defects that represent immutable deviations of a solid lattice from its ideal crystalline form. While these two classes of topological phenomena have general

Johnathan A. Adams, Gentry White, Robyn P. Araujo

A model needs to make verifiable predictions to have any scientific value. In opinion dynamics, the study of how individuals exchange opinions with one another, there are many theoretical models which attempt to model opinion exchange, one of which is the Martins model, which differs from other models by using a parameter that is easier to control for in an

Johnathan A. Adams, Gentry White, Robyn P. Araujo

In opinion dynamics, as in general usage, polarisation is subjective. To understand polarisation, we need to develop more precise methods to measure the agreement in society. This paper presents four mathematical measures of polarisation derived from graph and network representations of societies and information theoretic divergences or distance metrics. Two

Satoko Sawada-Satoh, Seiji Kameno, Sascha Trippe

The cold molecular gas in the circumnuclear disk (CND) of radio galaxies provides critical information for understanding the mass accretion onto active galactic nuclei. We present the first detection and maps of HCN J=1-0 and HCO+ J=1-0 emission lines from the circumnuclear region of a nearby radio galaxy, NGC 4261, using the Northern Extended Millimeter Arr

Zexin Pan, Art B. Owen

We study approximate integration of a function $f$ over $[0,1]^s$ based on taking the median of $2r-1$ integral estimates derived from independently randomized $(t,m,s)$-nets in base $2$. The nets are randomized by Matousek's random linear scramble with a digital shift. If $f$ is analytic over $[0,1]^s$, then the probability that any one randomized net's est

Lihan Wang

We consider complete Riemannian manifolds which satisfy a weighted Poincar\`e inequality and have the Ricci curvature bounded below in terms of the weight function. When the weight function has a non-zero limit at infinity, the structure of this class of manifolds at infinity are studied and certain splitting result is obtained. Our result can be viewed as a

Leah Chowenhill, Gaurav Satyanath, Shubhranshu Singh, Madhav Mahendra Wagh

Few-shot learning is a type of classification through which predictions are made based on a limited number of samples for each class. This type of classification is sometimes referred to as a meta-learning problem, in which the model learns how to learn to identify rare cases. We seek to extract information from five exemplar vocalisations of mammals or bird

Sasha Anan'in, Dmitrii Korshunov

We prove a conjecture of Ian Agol: all isometric realizations of a polyhedral surface with boundary sweep out an isotropic subset in the Kapovich-Millson moduli space of polygons isomorphic to the boundary. For a generic polyhedral disk we show that boundaries of its isometric realizations make up a Lagrangian subset. As an application of this result, we obt

Yuanhao Lu, Ajitesh Srivastava

Multi-model prediction efforts in infectious disease modeling and climate modeling involve multiple teams independently producing projections under various scenarios. Often these scenarios are produced by the presence and absence of a decision in the future, e.g., no vaccinations (scenario A) vs vaccinations (scenario B) available in the future. The models s

Jiashu Wu, Hao Dai, Yang Wang, Shigen Shen

With the fast growing quantity of data generated by smart devices and the exponential surge of processing demand in the Internet of Things (IoT) era, the resource-rich cloud centres have been utilised to tackle these challenges. To relieve the burden on cloud centres, edge-cloud computation offloading becomes a promising solution since shortening the proximi

Ahmed Omara, Burak Kantarci

In this paper, we study the expanding attack surface of Adversarial Machine Learning (AML) and the potential attacks against Vehicle-to-Microgrid (V2M) services. We present an anticipatory study of a multi-stage gray-box attack that can achieve a comparable result to a white-box attack. Adversaries aim to deceive the targeted Machine Learning (ML) classifier

Colby Fronk, Linda Petzold

Neural networks have the ability to serve as universal function approximators, but they are not interpretable and don't generalize well outside of their training region. Both of these issues are problematic when trying to apply standard neural ordinary differential equations (neural ODEs) to dynamical systems. We introduce the polynomial neural ODE, which is

Ted Fujimoto, Samrat Chatterjee, Auroop Ganguly

Advances in ad hoc teamwork have the potential to create agents that collaborate robustly in real-world applications. Agents deployed in the real world, however, are vulnerable to adversaries with the intent to subvert them. There has been little research in ad hoc teamwork that assumes the presence of adversaries. We explain the importance of extending ad h

Jan Vrbik

We show how to calculate individual terms of the Edgeworth series to approximate the distribution of the Pearson correlation coefficient with the help of a simple Mathematica program. We also demonstrate how to eliminate the corresponding skewness, thus making the approximation substantially more accurate. This leads, in a rather natural way, to deriving a s

Mohi Reza, Akmar Chowdhury, Aidan Li, Mahathi Gandhamaneni

What if we take a broader view of what it means to run an education experiment? In this paper, we explore opportunities that arise when we think beyond the commonly-held notion that the purpose of an experiment is to either accept or reject a pre-defined hypothesis and instead, reconsider experimentation as a means to explore the complex design space of crea

Ehsan Saboori, Samar Abdi

This paper presents novel techniques of using hybrid prototyping for early power-performance analysis of MPSoC designs with multiple clock domains. The fundamental idea of hybrid prototyping is to simulate a design with multiple cores by creating an emulation kernel in software on top of a single physical instance of the core. However, so far hybrid prototyp

Binbin Xu, Andrew J. Davison, Stefan Leutenegger

In this paper, we propose a novel object-level mapping system that can simultaneously segment, track, and reconstruct objects in dynamic scenes. It can further predict and complete their full geometries by conditioning on reconstructions from depth inputs and a category-level shape prior with the aim that completed object geometry leads to better object reco