March 2020 arXiv papers — page 14

Yanlin Deng, Feng Du, Jing Mao, Yan Zhao

In this paper, sharp bounds for the first nonzero eigenvalues of different type have been obtained. Moreover, when those bounds are achieved, related rigidities can be characterized. More precisely, first, by applying the Bishop-type volume comparison proven in [10,13] and the Escobar-type eigenvalue comparisons for the first nonzero Steklov eigenvalue of th

Xusheng Luo, Luxin Liu, Yonghua Yang, Le Bo

One of the ultimate goals of e-commerce platforms is to satisfy various shopping needs for their customers. Much efforts are devoted to creating taxonomies or ontologies in e-commerce towards this goal. However, user needs in e-commerce are still not well defined, and none of the existing ontologies has the enough depth and breadth for universal user needs u

Keneth Adrian Dagal

This paper introduces a new equation for rewriting two unit fractions to another two unit fractions. This equation is useful for optimizing the elements of an Egyptian Fraction. Parity of the elements of the Egyptian Fractions are also considered. And lastly, the statement that all rational numbers can be represented as Egyptian Fraction is re-established.

Hyunjong Park, Jongyoun Noh, Bumsub Ham

We address the problem of anomaly detection, that is, detecting anomalous events in a video sequence. Anomaly detection methods based on convolutional neural networks (CNNs) typically leverage proxy tasks, such as reconstructing input video frames, to learn models describing normality without seeing anomalous samples at training time, and quantify the extent

Yoshito Ishiki

As a generalization of Hausdorff's extension theorem of metrics, we prove an interpolation theorem of a family of metrics defined on closed subsets of metrizable spaces. As an application, we investigate typicality of subsets of moduli spaces of metrics. We observe that various sets of all metrics with properties appearing in metric geometry are dense inters

Hrushikesh N Mhaskar

Dealing with massive data is a challenging task for machine learning. An important aspect of machine learning is function approximation. In the context of massive data, some of the commonly used tools for this purpose are sparsity, divide-and-conquer, and distributed learning. In this paper, we develop a very general theory of approximation by networks, whic

Mitchell D. Woodbright, Md Anisur Rahman, Md Zahidul Islam

Data are being collected from various aspects of life. These data can often arrive in chunks/batches. Traditional static clustering algorithms are not suitable for dynamic datasets, i.e., when data arrive in streams of chunks/batches. If we apply a conventional clustering technique over the combined dataset, then every time a new batch of data comes, the pro

Ryoma Kobayashi

For any finite type connected surface $S$, we give an infinite presentation of the fundamental group $\pi_1(S,\ast)$ of $S$ based at an interior point $\ast\in{S}$ whose generators are represented by simple loops. When $S$ is non-orientable, we also give an infinite presentation of the subgroup of $\pi_1(S,\ast)$ generated by elements which are represented b

Pavol Quittner

Liouville theorems for scaling invariant nonlinear parabolic equations and systems (saying that the equation or system does not possess positive entire solutions) guarantee optimal universal estimates of solutions of related initial and initial-boundary value problems. In the case of the nonlinear heat equation $$u_t-\Delta u=u^p\quad\hbox{in}\quad {R}^n\tim

Yoon-Soo Jang, Hao Liu, Jinghui Yang, Mingbin Yu

Laser interferometry serves a fundamental role in science and technology, assisting precision metrology and dimensional length measurement. During the past decade, laser frequency combs - a coherent optical-microwave frequency ruler over a broad spectral range with traceability to time-frequency standards - have contributed pivotal roles in laser dimensional

Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach

In this work we demonstrate how to automate parts of the infectious disease-control policy-making process via performing inference in existing epidemiological models. The kind of inference tasks undertaken include computing the posterior distribution over controllable, via direct policy-making choices, simulation model parameters that give rise to acceptable

Nathan Dahlin, Rahul Jain

A market consisting of a generator with thermal and renewable generation capability, a set of non-preemptive loads (i.e., loads which cannot be interrupted once started), and an independent system operator (ISO) is considered. Loads are characterized by durations, power demand rates and utility for receiving service, as well as disutility functions giving pr

Hiroshi Okada, Yutaro Shoji

We propose a radiative seesaw model based on a modular $A_4$ symmetry, which has good predictability in the lepton sector. We execute a numerical analysis to search for parameters that satisfy the experimental constraints such as those from neutrino oscillation data and lepton flavor violations. Then, we present several predictions in our model that originat

Ryo Urano, Wataru Shinoda, Noriyuki Yoshii, Susumu Okazaki

In the molecular dynamics calculations for the free energy of ions and ionic molecules, we often encounter wet charged molecular systems where electrical neutrality condition is broken. This causes a problem in the evaluation of electrostatic interaction under periodic boundary condition. A standard remedy for the problem is to consider a hypothetical homoge

Shivam Agarwal, Siddarth Venkatraman

Steganography is the art of hiding a secret message inside a publicly visible carrier message. Ideally, it is done without modifying the carrier, and with minimal loss of information in the secret message. Recently, various deep learning based approaches to steganography have been applied to different message types. We propose a deep learning based technique

Fengchun Qiao, Long Zhao, Xi Peng

We are concerned with a worst-case scenario in model generalization, in the sense that a model aims to perform well on many unseen domains while there is only one single domain available for training. We propose a new method named adversarial domain augmentation to solve this Out-of-Distribution (OOD) generalization problem. The key idea is to leverage adver

Chengshen Xu

Markov matrices have an important role in the filed of stochastic processes. In this paper, we will show and prove a series of conclusions on Markov matrices and transformations rather than pay attention to stochastic processes although these conclusions are useful for studying stochastic processes. These conclusions we come to, which will make us have a dee

Ryohtaroh T. Ishikawa, Yukio Katsukawa, Patrick Antolin, Shin Toriumi

Coronal rain corresponds to cool and dense clumps in the corona accreting towards the solar surface, and is often observed above solar active regions. They are generally thought to be produced by thermal instability in the corona and their lifetime is limited by the time they take to reach the chromosphere. Although the rain usually fragments into smaller cl

Yuan Luo, Ya Xiao, Long Cheng, Guojun Peng

Anomaly detection is crucial to ensure the security of cyber-physical systems (CPS). However, due to the increasing complexity of CPSs and more sophisticated attacks, conventional anomaly detection methods, which face the growing volume of data and need domain-specific knowledge, cannot be directly applied to address these challenges. To this end, deep learn

Shixun Huang, Zhifeng Bao, Guoliang Li, Yanghao Zhou

Network embedding is an effective method to learn low-dimensional representations of nodes, which can be applied to various real-life applications such as visualization, node classification, and link prediction. Although significant progress has been made on this problem in recent years, several important challenges remain, such as how to properly capture te

Shai Shalev-Shwartz, Shaked Shammah, Amnon Shashua

The AI-alignment problem arises when there is a discrepancy between the goals that a human designer specifies to an AI learner and a potential catastrophic outcome that does not reflect what the human designer really wants. We argue that a formalism of AI alignment that does not distinguish between strategic and agnostic misalignments is not useful, as it de

Indranil Biswas, Lisa C. Jeffrey

We show that the character variety for a $n$-punctured oriented surface has a natural Poisson structure.

Huanchen Bao, Xuhua He

In this paper, we develop the theory of flag manifold over a semifield for any Kac-Moody root datum. We show that the flag manifold over a semifield admits a natural action of the monoid over that semifield associated with the Kac-Moody datum and admits a cellular decomposition. This extends the previous work of Lusztig, Postnikov, Rietsch and others on the

Changyu Ren, Zhizhang Wang

The main result of this paper gives a plenary proof on the curvature estimates for $k$ curvature equations with general right hand sides with $n<2k$ based on a concavity inequality. We further give a explicit lower bound of the inequality.

Ilmun Kim, Sivaraman Balakrishnan, Larry Wasserman

Permutation tests are widely used in statistics, providing a finite-sample guarantee on the type I error rate whenever the distribution of the samples under the null hypothesis is invariant to some rearrangement. Despite its increasing popularity and empirical success, theoretical properties of the permutation test, especially its power, have not been fully

Toshiyasu Arai

In this note let us give two remarks on proof-theory of PA. First a derivability relation is introduced to bound witnesses for provable $\Sigma_{1}$-formulas in PA. Second Paris-Harrington's proof for their independence result is reformulated to show a `consistency' proof of PA based on a combinatorial principle.

Carol Hayes, Katherine Seaton

Through the hands-on creation of two sashiko pieces of work - a counted thread kogin bookmark and a single running stitched hitomezashi sampler - participants will explore not only the living cultural history of this traditional Japanese needlework but will also experience the mathematics of sashiko in a tangible form, and will take away with them items of s

Paolo Cascini, Sho Ejiri, János Kollár, Lei Zhang

Over any algebraically closed field of positive characteristic, we construct examples of fibrations violating subadditivity of Kodaira dimension.

Pei Zhang, Xu Zhang, Wei Chen, Jian Yu

Document-level machine translation incorporates inter-sentential dependencies into the translation of a source sentence. In this paper, we propose a new framework to model cross-sentence dependencies by training neural machine translation (NMT) to predict both the target translation and surrounding sentences of a source sentence. By enforcing the NMT model t

Bing He, Lana Garmire

Coronavirus disease (COVID-19) is an infectious disease discovered in 2019 and currently in outbreak across the world. Lung injury with severe respiratory failure is the leading cause of death in COVID-19, brought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there still lacks efficient treatment for COVID-19 induced lung injury a

Vasileios G. Ataloglou, Ayman H. Dorrah, George V. Eleftheriades

Huygens' metasurfaces have demonstrated a remarkable potential to perform wave transformations within a subwavelength region. In particular, omega-bianisotropic Huygens' metasurfaces have allowed for the passive implementation of any wave transformation that conserves real power locally. Previous reports have also shown that Huygens' metasurface pairs are ca

Juening Jin, Chengshan Xiao, Meixia Tao, Wen Chen

We investigate the fading cognitive multiple access wiretap channel (CMAC-WT), in which two secondary-user transmitters (STs) send secure messages to a secondary-user receiver (SR) in the presence of an eavesdropper (ED) and subject to interference threshold constraints at multiple primary-user receivers (PRs). We design linear precoders to maximize the aver

Rika Yamada, Yutaro Enomoto, Atsushi Nishizawa, Koji Nagano

The quantum locking technique, which uses additional short low-loss sub-cavities, is effective in reducing quantum noise in space gravitational wave antenna DECIGO. However, the quantum noise of the main interferometer depends on the control systems in the sub-cavities. Here we demonstrate a new method to optimize the quantum noise independently of the feedb

Fei Song, Jun Li, Ming Ding, Long Shi

The support for aerial users has become the focus of recent 3GPP standardizations of 5G, due to their high maneuverability and flexibility for on-demand deployment. In this paper, probabilistic caching is studied for ultra-dense small-cell networks with terrestrial and aerial users, where a dynamic on-off architecture is adopted under a sophisticated path lo

Neal Bushaw, Daniel Johnston, Puck Rombach

We introduce a notion of rainbow saturation and the corresponding rainbow saturation number. This is the saturation version of the rainbow Tur\'an numbers whose systematic study was initiated by Keevash, Mubayi, Sudakov, and Verstra\"ete. We give examples of graphs for which the rainbow saturation number is bounded away from the ordinary saturation number. T

Frank Nielsen

The informational energy of Onicescu is a positive quantity that measures the amount of uncertainty of a random variable. But contrary to Shannon's entropy, the informational energy increases when randomness decreases. We report closed-form formula for Onicescu's informational energy and its associated correlation coefficient when the probability distributio

Junyang Lin, An Yang, Yichang Zhang, Jie Liu

Multi-modal pretraining for learning high-level multi-modal representation is a further step towards deep learning and artificial intelligence. In this work, we propose a novel model, namely InterBERT (BERT for Interaction), which is the first model of our series of multimodal pretraining methods M6 (MultiModality-to-MultiModality Multitask Mega-transformer)

Kai Li, Curtis Wigington, Chris Tensmeyer, Handong Zhao

Decomposing images of document pages into high-level semantic regions (e.g., figures, tables, paragraphs), document object detection (DOD) is fundamental for downstream tasks like intelligent document editing and understanding. DOD remains a challenging problem as document objects vary significantly in layout, size, aspect ratio, texture, etc. An additional

Javier Pulgar, Alexis Spina, Carlos Ríos

Traditionally, scholars in physics education research pay attention to students solving well-structured learning activities, which provide restricted room for collaboration and idea-generation due to their close-ended nature. In order to encourage the socialization of information among group members, we utilized a real-world problem where students were asked

Chi-Chun Zhou, Yi Liu

In solving the variational problem, the key is to efficiently find the target function that minimizes or maximizes the specified functional. In this paper, by using the Pade approximant, we suggest a methods for the variational problem. By comparing the method with those based on the radial basis function networks (RBF), the multilayer perception networks (M

Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Başar

While the topic of mean-field games (MFGs) has a relatively long history, heretofore there has been limited work concerning algorithms for the computation of equilibrium control policies. In this paper, we develop a computable policy iteration algorithm for approximating the mean-field equilibrium in linear-quadratic MFGs with discounted cost. Given the mean

Suichan Li, Bin Liu, Dongdong Chen, Qi Chu

Semi-supervised learning (SSL) has been extensively studied to improve the generalization ability of deep neural networks for visual recognition. To involve the unlabelled data, most existing SSL methods are based on common density-based cluster assumption: samples lying in the same high-density region are likely to belong to the same class, including the me

Lucas Fraile, Matteo Marchi, Paulo Tabuada

In this paper we propose a methodology for stabilizing single-input single-output feedback linearizable systems when no system model is known and no prior data is available to identify a model. Conceptually, we have been greatly inspired by the work of Fliess and Join on intelligent PID controllers and the results in this paper provide sufficient conditions

Kai Li, Yulun Zhang, Kunpeng Li, Yun Fu

The recent flourish of deep learning in various tasks is largely accredited to the rich and accessible labeled data. Nonetheless, massive supervision remains a luxury for many real applications, boosting great interest in label-scarce techniques such as few-shot learning (FSL), which aims to learn concept of new classes with a few labeled samples. A natural

Haim Kaplan, Micha Sharir, Uri Stemmer

We study the question of how to compute a point in the convex hull of an input set $S$ of $n$ points in ${\mathbb R}^d$ in a differentially private manner. This question, which is trivial non-privately, turns out to be quite deep when imposing differential privacy. In particular, it is known that the input points must reside on a fixed finite subset $G\subse

Jiangpeng He, Runyu Mao, Zeman Shao, Fengqing Zhu

Modern deep learning approaches have achieved great success in many vision applications by training a model using all available task-specific data. However, there are two major obstacles making it challenging to implement for real life applications: (1) Learning new classes makes the trained model quickly forget old classes knowledge, which is referred to as

Nuno Costa Dias, Maurice de Gosson, Joao Nuno Prata

The notion of partial trace of a density operator is essential for the understanding of the entanglement and separability properties of quantum states. In this paper we investigate these notions putting an emphasis on the geometrical properties of the covariance ellipsoids of the reduced states. We thereafter focus on Gaussian states and we give new and easi

Jae Sung Lee, Jong-Min Park, Hyunggyu Park

Microorganisms such as bacteria are active matters which consume chemical energy and generate their unique run-and-tumble motion. A swarm of such microorganisms provide a nonequilibrium active environment whose noise characteristics are different from those of thermal equilibrium reservoirs. One important difference is a finite persistence time, which is con

Byungchul Cha, Heather Chapman, Brittany Gelb, Chooka Weiss

We study an intrinsic Lagrange spectrum of the unit circle $|z|=1$ in the complex plane with respect to the Eisensteinian field $\mathbb{Q}(\sqrt{-3})$. We prove that the minimum of the Lagrange spectrum is $2$ and that its smallest accumulation point is $4/\sqrt{3}$. In addition, we characterize the set of all values in the spectrum between $2$ and $4/\sqrt

Rijad Alisic, Marco Molinari, Philip E. Paré, Henrik Sandberg

Smart building management systems rely on sensors to optimize the operation of buildings. If an unauthorized user gains access to these sensors, a privacy leak may occur. This paper considers such a potential leak of privacy in a smart residential building, and how it may be mitigated through corrupting the measurements with additive Gaussian noise. This cor

Yusuke Mori, Kei-ichi Okazaki, Toshifumi Mori, Kang Kim

We propose a cross-entropy minimization method for finding the reaction coordinate from a large number of collective variables in complex molecular systems. This method is an extension of the likelihood maximization approach describing the committor function with a sigmoid. By design, the reaction coordinate as a function of various collective variables is o

Xiaojian Li, Chaogang Lou, Xin Li, Yujie Zhang

The thermophotovoltaic cells which convert the low temperature radiation into electricity are of significance due to their potential applications in many fields. In this work, Bi2Te3/Si thermophotovoltaic cells which work under the radiation from the blackbody with the temperature of 300 K-480 K are presented. The experimental results show that the cells can

Ya-Jie Wu, Chao-Chen Liu, Junpeng Hou

Photonic crystals have provided a controllable platform to examine excitingly new topological states in open systems. In this work, we reveal photonic topological corner states in a photonic graphene with mirror-symmetrically patterned gain and loss. Such a nontrivial Wannier-type higher-order topological phase is achieved through solely tuning on-site gain/

Shuhao Cui, Shuhui Wang, Junbao Zhuo, Chi Su

In unsupervised domain adaptation, rich domain-specific characteristics bring great challenge to learn domain-invariant representations. However, domain discrepancy is considered to be directly minimized in existing solutions, which is difficult to achieve in practice. Some methods alleviate the difficulty by explicitly modeling domain-invariant and domain-s

Meng Li, Liheng Bian, Guoan Zheng, Andrew Maiden

Complex-field imaging is indispensable for numerous applications at wavelengths from X-ray to THz, with amplitude describing transmittance (or reflectivity) and phase revealing intrinsic structure of the target object. Coherent diffraction imaging (CDI) employs iterative phase retrieval algorithms to process diffraction measurements and is the predominant no

Yang Bai, Andrew J. Long, Sida Lu

Dark matter could take the form of dark massive compact halo objects (dMACHOs); i.e., composite objects that are made up of dark-sector elementary particles, that could have a macroscopic mass from the Planck scale to above the solar mass scale, and that also admit a wide range of energy densities and sizes. Concentrating on the gravitational interaction of

Sayantika Bhowal, S. Satpathy

Carrying information using generation and detection of the orbital current, instead of the spin current, is an emerging field of research, where the orbital Hall effect (OHE) is an important ingredient. Here, we propose a new mechanism of the OHE that occurs in {\it non-}centrosymmetric materials. We show that the broken inversion symmetry in the 2D transiti

Erhan Bayraktar, Suman Chakraborty, Ruoyu Wu

We consider heterogeneously interacting diffusive particle systems and their large population limit. The interaction is of mean field type with weights characterized by an underlying graphon. A law of large numbers result is established as the system size increases and the underlying graphons converge. The limit is given by a graphon mean field system consis

Yuta Ito

This is the second paper of a series of our works on the self-similar orbit-averaged Fokker-Planck (OAFP) equation and details physical properties of isotropic pre-collapse solution. The fundamental core collapse process at the late stage of relaxation evolution of spherical star clusters can be described by the self-similar OAFP equation. The accurate spect

Shuxin Ding, Qi Zhang, Zhiming Yuan

This paper investigates the robust uncertain two-level cooperative set covering problem (RUTLCSCP). Given two types of facilities, which are called y-facility and z-facility. The problem is to decide which facilities of both types to be selected, in order to cover the demand nodes cooperatively with minimal cost. It combines the concepts of robust, probabili

S. Vaitiekėnas, G. W. Winkler, B. van Heck, T. Karzig

We present a novel route to realizing topological superconductivity using magnetic flux applied to a full superconducting shell surrounding a semiconducting nanowire core. In the destructive Little-Parks regime, reentrant regions of superconductivity are associated with integer number of phase windings in the shell. Tunneling into the core reveals a hard ind

Michel Fruchart, Ryo Hanai, Peter B. Littlewood, Vincenzo Vitelli

Out of equilibrium, the lack of reciprocity is the rule rather than the exception. Non-reciprocal interactions occur, for instance, in networks of neurons, directional growth of interfaces, and synthetic active materials. While wave propagation in non-reciprocal media has recently been under intense study, less is known about the consequences of non-reciproc

Y. Kawashima, T. Asaka, H. Ego, M. Hara

In order to dissipate long-lived radioactive waste, not only high ux proton accelerator but also electron linac have been proposed. A proton accelerator directly induces nuclear fission and mutation. On the other hand, electron beam has two processes: production of gamma rays through bremsstrahlung and produced gamma rays are available for the (gamma ; n) re

Pasquale Giampa, Massimiliano Dibitonto

This paper introduces the MIP Platform architecture model, a novel AI-based cognitive computing platform architecture. The goal of the proposed application of MIP is to reduce the implementation burden for the usage of AI algorithms applied to cognitive computing and fluent HMI interactions within the manufacturing process in a cyber-physical production syst

Shigeo S. Kimura, Kenji Toma

We propose a novel interpretation that gamma-rays from nearby radio galaxies are hadronic emission from magnetically arrested disks (MADs) around central black holes (BHs). The magnetic energy in MADs is higher than the thermal energy of the accreting plasma, where the magnetic reconnection or turbulence may efficiently accelerate non-thermal protons. They e

Vincent Maurice, Zachary L. Newman, Susannah Dickerson, Morgan Rivers

Optical frequency standards, lasers stabilized to atomic or molecular transitions, are widely used in length metrology and laser ranging, provide a backbone for optical communications and lie at the heart of next-generation optical atomic clocks. Here we demonstrate a compact, low-power optical frequency standard based on the Doppler-free, two-photon transit

Chang Liu, Golrokh Akhgar, James L. Collins, Jack Hellerstedt

Na3Bi has attracted significant interest in both bulk form as a three-dimensional topological Dirac semimetal and in ultra-thin form as a wide-bandgap two-dimensional topological insulator. Its extreme air sensitivity has limited experimental efforts on thin- and ultra-thin films grown via molecular beam epitaxy to ultra-high vacuum environments. Here we dem

Gregor Semieniuk, Victor M. Yakovenko

Ambitious scenarios of carbon emission redistribution for mitigating climate change in line with the Paris Agreement and reaching the sustainable development goal of eradicating poverty have been proposed recently. They imply a strong reduction in carbon footprint inequality by 2030 that effectively halves the Gini coefficient to about 0.25. This paper exami

A. D. Alhaidari, T. J. Taiwo

Using a formulation of quantum mechanics based on orthogonal polynomials in the energy and physical parameters, we study quantum systems totally confined in space and associated with the discrete Meixner polynomials. We present several examples of such systems, derive their corresponding potential functions, and plot some of their bound states.

Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

We consider the problem of space-time super-resolution (ST-SR): increasing spatial resolution of video frames and simultaneously interpolating frames to increase the frame rate. Modern approaches handle these axes one at a time. In contrast, our proposed model called STARnet super-resolves jointly in space and time. This allows us to leverage mutually inform

Bernardo A. Mello

Minimizing social contact is an important tool to reduce the spread of diseases, but harms people's well-being. This and other, more compelling reasons, urge people to walk outside periodically. The present simulation explores how organizing the traffic of pedestrians affects the number of walking or running people passing by each other. By applying certain

Gavin Ball, Jesse Madnick

We study associative submanifolds of the Berger space SO(5)/SO(3) endowed with its homogeneous nearly-parallel G2-structure. We focus on two geometrically interesting classes: the ruled associatives, and the associatives with special Gauss map. We show that the associative submanifolds ruled by a certain special type of geodesic are in correspondence with ps

Milko Estrada, Reginaldo Prado

We provide a way of decoupling the first law of thermodynamics in two sectors : the standard first law of thermodynamics and the quasi first law of thermodynamics. It is showed that both sectors share the same thermodynamics volume and the same entropy. However, the total thermodynamics pressure, the total temperature and the total local energy correspond to

Takuya Nomoto, Takashi Koretsune, Ryotaro Arita

Using the ab initio local force method, we investigate the formation mechanism of the helical spin structure in GdRu$_2$Si$_2$ and Gd$_2$PdSi$_3$. We calculate the paramagnetic spin susceptibility and find that the Fermi surface nesting is not the origin of the incommensurate modulation, in contrast to the naive scenario based on the Ruderman-Kittel-Kasuya-Y

Aaron Potechin, Hing Yin Tsang

In this paper, we propose the following conjecture which generalizes a theorem proved by Huang [Hua19] in his recent breakthrough proof of the sensitivity conjecture. We conjecture that for any Cayley graph $X = \Gamma(G,S)$ on a group $G$ and any generating set $S$, if $U \subseteq G$ has size $|U| > |G|/2$, then the induced subgraph of $X$ on $U$ has maxim

Fan Yang, Felicitas Hellbach, Felix Rochau, Wolfgang Belzig

We study experimentally and theoretically the phenomenon of persistent response in ultra-strongly driven membrane resonators. This term denotes the development of a vibrating state with nearly constant amplitude over an extreme wide frequency range. We reveal the underlying mechanism of the persistent response state by directly imaging the vibrational state

Balakumar Sundaralingam, Tucker Hermans

Having the ability to estimate an object's properties through interaction will enable robots to manipulate novel objects. Object's dynamics, specifically the friction and inertial parameters have only been estimated in a lab environment with precise and often external sensing. Could we infer an object's dynamics in the wild with only the robot's sensors? In

R C McPhedran

This article contains work associated with a resolution of the Riemann hypothesis, following work by Taylor \cite{prt}, Lagarias and Suzuki \cite{lagandsuz} and Ki \cite{ki}, as well as Pustyl'nikov \cite{pust, pust2} and Keiper \cite{keiper}. Functions $\xi_+(s)$ and $\xi_-(s)$ are considered, for which it is known that all zeros lie on the critical line. T

Sheikh Ariful Islam, Love Kumar Sah, Srinivas Katkoori

Offshoring the proprietary Intellectual property (IP) has recently increased the threat of malicious logic insertion in the form of Hardware Trojan (HT). A potential and stealthy HT is triggered with nets that switch rarely during regular circuit operation. Detection of HT in the host design requires exhaustive simulation to activate the HT during pre- and p

Kyungjoo Noh, Liang Jiang, Bill Fefferman

Understanding the computational power of noisy intermediate-scale quantum (NISQ) devices is of both fundamental and practical importance to quantum information science. Here, we address the question of whether error-uncorrected noisy quantum computers can provide computational advantage over classical computers. Specifically, we study noisy random circuit sa

Andrey A Popov, Adrian Sandu

This paper uses a probabilistic approach to analyze the converge of an ensemble Kalman filter solution to an exact Kalman filter solution in the simplest possible setting, the scalar case, as it allows us to build upon a rich literature of scalar probability distributions and non-elementary functions. To this end we introduce the bare-bones Scalar Pedagogica

Konstantin Shestopaloff, Mei Dong, Fan Gao, Wei Xu

Current advances in next generation sequencing techniques have allowed researchers to conduct comprehensive research on microbiome and human diseases, with recent studies identifying associations between human microbiome and health outcomes for a number of chronic conditions. However, microbiome data structure, characterized by sparsity and skewness, present

Matúš Medo

We study the epidemic spreading on spatial networks where the probability that two nodes are connected decays with their distance as a power law. As the exponent of the distance dependence grows, model networks smoothly transition from the random network limit to the regular lattice limit. We show that despite keeping the average number of contacts constant,

Tanel Tammet

Commonsense reasoning has long been considered as one of the holy grails of artificial intelligence. Most of the recent progress in the field has been achieved by novel machine learning algorithms for natural language processing. However, without incorporating logical reasoning, these algorithms remain arguably shallow. With some notable exceptions, develope

Anna Kukleva, Makarand Tapaswi, Ivan Laptev

Interactions between people are often governed by their relationships. On the flip side, social relationships are built upon several interactions. Two strangers are more likely to greet and introduce themselves while becoming friends over time. We are fascinated by this interplay between interactions and relationships, and believe that it is an important asp

Jialin Song, Ravi Lanka, Yisong Yue, Bistra Dilkina

This paper studies a strategy for data-driven algorithm design for large-scale combinatorial optimization problems that can leverage existing state-of-the-art solvers in general purpose ways. The goal is to arrive at new approaches that can reliably outperform existing solvers in wall-clock time. We focus on solving integer programs, and ground our approach

Andrey Rogachev, Benjamin Sacépé

Finite-size scaling analysis is a well-accepted method for identification and characterization of quantum phase transitions (QPTs) in superconducting, magnetic and insulating systems. We formally apply this analysis in the form suitable for QPTs in 2-dimensional superconducting films to magnetic-field driven superconductor-metal transition in 1-dimensional M

Swagata Acharya, Dimitar Pashov, Francois Jamet, Mark van Schilfgaarde

Recent observations of selective emergence (suppression) of superconductivity in the uncollapsed (collapsed) tetragonal phase of LaFe$_2$As$_2$ has rekindled interest in understanding what features of the band structure control the superconducting T$_c$. We show that the proximity of the narrow Fe-d$_{xy}$ state to the Fermi energy emerges as the primary fac

Ittai Abraham, Kartik Nayak, Ling Ren, Zhuolun Xiang

This paper investigates the problem \textit{good-case latency} of Byzantine agreement, broadcast and state machine replication in the synchronous authenticated setting. The good-case latency measure captures the time it takes to reach agreement when all non-faulty parties have the same input (or in BB/SMR when the sender/leader is non-faulty). Previous resul

Daniel L. Campbell, Yun-Pil Shim, Bharath Kannan, Roni Winik

Resonant transverse driving of a two-level system as viewed in the rotating frame couples two degenerate states at the Rabi frequency, an amazing equivalence that emerges in quantum mechanics. While spectacularly successful at controlling natural and artificial quantum systems, certain limitations may arise (e.g., the achievable gate speed) due to non-ideali

Ji Chen, Xiaodong Li, Zongming Ma

Techniques of matrix completion aim to impute a large portion of missing entries in a data matrix through a small portion of observed ones. In practice including collaborative filtering, prior information and special structures are usually employed in order to improve the accuracy of matrix completion. In this paper, we propose a unified nonconvex optimizati

Rebecca Patrias, Oliver Pechenik

One of the oldest outstanding problems in dynamical algebraic combinatorics is the following conjecture of P. Cameron and D. Fon-Der-Flaass (1995). Consider a plane partition $P$ in an $a \times b \times c$ box ${\sf B}$. Let $\Psi(P)$ denote the smallest plane partition containing the minimal elements of ${\sf B} - P$. Then if $p= a+b+c-1$ is prime, Cameron

Suman K. Bera, C. Seshadhri

We revisit the well-studied problem of triangle count estimation in graph streams. Given a graph represented as a stream of $m$ edges, our aim is to compute a $(1\pm\varepsilon)$-approximation to the triangle count $T$, using a small space algorithm. For arbitrary order and a constant number of passes, the space complexity is known to be essentially $\Theta(

Michael J. Sorocky, Siqi Zhou, Angela P. Schoellig

In the robotics literature, different knowledge transfer approaches have been proposed to leverage the experience from a source task or robot -- real or virtual -- to accelerate the learning process on a new task or robot. A commonly made but infrequently examined assumption is that incorporating experience from a source task or robot will be beneficial. In

Giulio Isacchini, Carlos Olivares, Armita Nourmohammad, Aleksandra M. Walczak

Recent advances in modelling VDJ recombination and subsequent selection of T and B cell receptors provide useful tools to analyze and compare immune repertoires across time, individuals, and tissues. A suite of tools--IGoR [1], OLGA [2] and SONIA [3]--have been publicly released to the community that allow for the inference of generative and selection models

Michael Franklin Mbouopda, Paulin Melatagia Yonta, Guy Stephane B. Fedim Lombo

Named entity recognition is an important task in natural language processing. It is very well studied for rich language, but still under explored for low-resource languages. The main reason is that the existing techniques required a lot of annotated data to reach good performance. Recently, a new distributional representation of words has been proposed to pr

Harishankar Jayakumar, Artur Lozovoi, Damon Daw, Carlos A. Meriles

We articulate confocal microscopy and electron spin resonance to implement spin-to-charge conversion in a small ensemble of nitrogen-vacancy (NV) centers in bulk diamond, and demonstrate charge conversion of neighboring defects conditional on the NV spin state. We build on this observation to show time-resolved NV spin manipulation and ancilla-charge-aided N

Yiming Chen, Xiao-Liang Qi, Pengfei Zhang

Motivated by recent studies of the information paradox in (1+1)-D anti-de Sitter spacetime with a bath described by a (1+1)-D conformal field theory, we study the dynamics of second R\'{e}nyi entropy of the Sachdev-Ye-Kitaev (SYK) model ($\chi$) coupled to a Majorana chain bath ($\psi$). The system is prepared in the thermofield double (TFD) state and then e

David Benisty, Eduardo I. Guendelman, Emil Nissimov, Svetlana Pacheva

The standard $\Lambda$CDM model of cosmology is formulated as a simple modified gravity coupled to a single scalar field ("darkon") possessing a non-trivial hidden nonlinear Noether symmetry. The main ingredient in the construction is the use of the formalism of non-Riemannian spacetime volume-elements. The associated Noether conserved current produces stres

Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar

Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 infection with high accuracy can be crucially helpful to healthcare professionals. The main clinical tool currently in use for the diagnosis