November 2020 arXiv papers — page 8

Hojun Moon, Jeongbo Shim, Donghyun You

A numerical method is presented to simulate gas-liquid-solid flows with bubble-particle interaction, including particle collision, sliding, and attachment. Gas-liquid flows are simulated in an Eulerian framework using a volume-of-fluid method. Particle motions are predicted in a Lagrangian framework. Algorithms that are used to detect collision and determine

Senta V. Greene, Julia Velkovska, Brandon Blankenship, Michael Z. Reynolds

Gas electron Multipliers (GEM) are a new generation of gaseous avalanche devices in the Micro Patterned Gaseous Detector category. GEMs are widely used in both nuclear and high energy experiments as well as in medical science. Several parameters define the performance of these types of devices under various experimental conditions. This article focuses on th

Yuki Yanagi, Junya Ikeda, Kohei Fujiwara, Kentaro Nomura

Co-based shandite Co$_3$Sn$_2$S$_2$ is a representative example of magnetic Weyl semimetals showing rich transport phenomena. We thoroughly investigate magnetic and transport properties of hole-doped shandites Co$_3$In$_x$Sn$_{2-x}$S$_2$ by first-principles calculations. The calculations reproduce nonlinear reduction of anomalous Hall conductivity with dopin

J. P. Ma, Z. Y. Pang, G. P. Zhang

Through explicit examples we show that twist-4 parton distributions have no parton interpretation in the sense that parton or partons inside a hadron can carry the momentum fraction $x$ of the hadron with $x >1$ or $x<-1$. The studied twist-4 parton distributions of collinear factoization are power-divergent for $\vert x\vert >1$. The corresponding transvers

Zerong Zheng, Tao Yu, Qionghai Dai, Yebin Liu

Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power. However, unlike polygon mesh-based templates, it remains a challenge to reason dense correspondences or other semantic relationships across shapes represented by DIFs, wh

Kim Chol-jun

We show that while the Fourier transform can figure only an "intensity" of a periodic signal, there is an additional information embedded, which is a "coherence" of the signal. Supposing that the periodicity is reflected only on the "coherence," we introduce a time stability as a measure of "coherence" excluding the "intensity," i.e. amplitude of signal. In

Yuan Liu, Lingjie Liu, Cheng Lin, Zhen Dong

Motion coherence is an important clue for distinguishing true correspondences from false ones. Modeling motion coherence on sparse putative correspondences is challenging due to their sparsity and uneven distributions. Existing works on motion coherence are sensitive to parameter settings and have difficulty in dealing with complex motion patterns. In this p

Jie Xu

We introduce an iterative scheme to prove the Yamabe problem $ - a\Delta_{g} u + S u = \lambda u^{p-1} $, firstly on open domain $ (\Omega, g) $ with Dirichlet boundary conditions, and then on closed manifolds $ (M, g) $ by local argument. It is a new proof, which solves the Yamabe problem for $ n \geqslant 3 $ in a uniform argument, beyonds the traditional

Estelle Basor, Torsten Ehrhardt, Roozbeh Gharakhloo, Alexander Its

We prove the analogue of the strong Szeg{\H o} limit theorem for a large class of bordered Toeplitz determinants. In particular, by applying our results to the formula of Au-Yang and Perk \cite{YP} for the next-to-diagonal correlations $\langle \sigma_{0,0}\sigma_{N-1,N} \rangle$ in the anisotropic square lattice Ising model, we rigorously justify that the n

Lijuan Wang, Can Zhang

In this paper, we first prove a uniform upper bound on costs of null controls for semilinear heat equations with globally Lipschitz nonlinearity on a sequence of increasing domains, where the controls are acted on an equidistributed set that spreads out in the whole Euclidean space R^N . As an application, we then show the exactly null controllability for th

Yilei Zeng, Aayush Shah, Jameson Thai, Michael Zyda

The game industry is moving into an era where old-style game engines are being replaced by re-engineered systems with embedded machine learning technologies for the operation, analysis and understanding of game play. In this paper, we describe our machine learning course designed for graduate students interested in applying recent advances of deep learning a

Younggeun Kim, SungWoo Youn, Danho Ahn, Junu Jeong

Analogous to the light-shining-through-wall setup proposed for axion-like particle searches, a pair of resonant cavities have been considered to search for an extra U(1) massive gauge boson, called a hidden photon, which mediates the interactions in the hidden sector. We propose a new cavity configuration, consisting of a cylindrical emitter surrounded by a

Hiroyasu Nakayama, Bin Xu, Sotaro Iwamoto, Kaoru Yamamoto

Thermal switching provides an effective way for active heat flow control, which has recently attracted increasing attention in terms of nanoscale thermal management technologies. In magnetic and spintronic materials, the thermal conductivity depends on the magnetization configuration: this is the magneto-thermal resistance effect. Here we show that an epitax

Soonchul Choi, Tsuyoshi Miyatsu, Myung-Ki Cheoun, Koichi Saito

Taking into account the terrestrial experiments and the recent astrophysical observations of neutron stars and gravitational-wave signals, we impose restrictions on the equation of state (EoS) for isospin-asymmetric nuclear matter. Using the relativistic mean-field model with SU(3) flavor symmetry, we investigate the impacts of effective nucleon mass, nuclea

Wen Kang, Emilia Fridman

This paper addresses sampled-data control of 2D Kuramoto-Sivashinsky equation over a rectangular domain. We suggest to divide the 2D rectangular into N sub-domains, where sensors provide spatially averaged or point state measurements to be transmitted through communication network to the controller. Note that differently from 2D heat equation, here we manage

Igor Kotelnikov, Qiusun Zeng

It is shown that steepening of the radial plasma pressure profile leads to a decrease in the critical value of beta, above which small-scale balloon-type perturbations in a mirror trap become unstable. This means that small-scale ballooning instability leads to a smoothing of the radial plasma profile. This fact seems to have received little attention in the

Jeong-Hoe Ku, JiHun Oh, YoungYoon Lee, Gaurav Pooniwala

This paper aims to provide a selective survey about knowledge distillation(KD) framework for researchers and practitioners to take advantage of it for developing new optimized models in the deep neural network field. To this end, we give a brief overview of knowledge distillation and some related works including learning using privileged information(LUPI) an

Shuang Wang, Jun Yang

Recent studies found that atmospheric superrotation (i.e., west-to-east winds over the equator) on tidally locked planets can modify the phase of planetary waves. But, a clear relationship between the superrotation and the magnitude of the phase shift was not examined. In this study, we re-investigate this problem using a two-dimensional (2D) linear shallow

Zhenggang He

This paper mainly studies the relative Gorenstein objects in the extriangulated category $\mathcal{C}=(\mathcal{C},\mathbb{E},\mathfrak{s})$ with a proper class $\xi$ and the related properties of these objects. In the first part, we define the notion of the $\xi$-$\mathcal{G}$projective resolution, and study the relation between $\xi$-projective resolution

Jay Shenoy, Edward Kim, Xiangyu Yue, Taesung Park

Safely interacting with humans is a significant challenge for autonomous driving. The performance of this interaction depends on machine learning-based modules of an autopilot, such as perception, behavior prediction, and planning. These modules require training datasets with high-quality labels and a diverse range of realistic dynamic behaviors. Consequentl

Sheng Luo, Yu Zhou, Huaibin Zheng, Jianbin Liu

It is challenging for observing superbunching effect with true chaotic light, here we propose and demonstrate a method to achieve superbunching effect of the degree of second-order coherence is 2.42 with broadband stationary chaotic light based on a cascaded Michelson interferometer (CMI), exceeding the theoretical upper limit of 2 for the two-photon bunchin

Amin Jalali

In the context of regularized loss minimization with polyhedral gauges, we show that for a broad class of loss functions (possibly non-smooth and non-convex) and under a simple geometric condition on the input data it is possible to efficiently identify a subset of features which are guaranteed to have zero coefficients in all optimal solutions in all proble

Junichiro Iwasawa, Daiki Nishiguchi, Masaki Sano

We study the polar collective dynamics of Janus colloidal particles fueled by an AC electric field. When the density is high enough, the polar interactions between the particles induce a polar orientationally ordered state which exhibits features reminiscent of the Vicsek model such as true long-range order and giant number fluctuations. Independent measurem

Adam J. Batten, Alan R. Duffy, Nastasha Wijers, Vivek Gupta

The dispersion measure (DM) of fast radio bursts (FRBs) provides a unique way to probe ionised baryons in the intergalactic medium (IGM). Cosmological models with different parameters lead to different DM-redshift ($\mathrm{DM}-z$) relations. Additionally, the over/under-dense regions in the IGM and the circumgalactic medium of intervening galaxies lead to s

Zhangdong Ye, Dong Pan, Zhen Sun, Chunguang Du

Quantum secure direct communication provides a direct means of conveying secret information via quantum states among legitimate users. The past two decades have witnessed its great strides both theoretically and experimentally. However, the security analysis of it still stays in its infant. Some practical problems in this field to be solved urgently, such as

Orenthal J. Tucker, Rosemary M. Killen, Robert E. Johnson, Prabal Saxena

Early in the Moon's history volcanic outgassing may have produced a periodic millibar level atmosphere (Needham and Kring, 2017). We examined the relevant atmospheric escape processes and lifetime of such an atmosphere. Thermal escape rates were calculated as a function of atmospheric mass for a range of temperatures including the effect of the presence of a

Keivan Mahmoud Aghdami, Abdullah Rahnama, Erden Ertorer, Peter R. Herman

Embedding strong photonic stopbands into traditional optical fibre that can directly access and sense the outside environment is challenging, relying on tedious nanoprocessing steps that result in fragile thinned fibre. Ultrashort pulsed laser filaments have recently provided a non contact means of opening high aspect ratio nanoholes inside of bulk transpare

Carmen Chan-Zheng, Pablo Borja, Nima Monshizadeh, Jacquelien M. A. Scherpen

In this paper, we prove the exponential stability property of a class of mechanical systems represented in the port-Hamiltonian framework. To this end, we propose a Lyapunov candidate function different from the Hamiltonian of the system. Moreover, we study how the proposed analysis can be used to determine the exponential stability and the rate of convergen

Jialong Xu, Bo Ai, Wei Chen, Ang Yang

Recent research on joint source channel coding (JSCC) for wireless communications has achieved great success owing to the employment of deep learning (DL). However, the existing work on DL based JSCC usually trains the designed network to operate under a specific signal-to-noise ratio (SNR) regime, without taking into account that the SNR level during the de

Kevin W. Lu

Consider a multivariate L\'evy-driven Ornstein-Uhlenbeck process where the stationary distribution or background driving L\'evy process is from a parametric family. We derive the likelihood function assuming that the innovation term is absolutely continuous. Two examples are studied in detail: the process where the stationary distribution or background drivi

Isobel M. Romero-Shaw, Kyle Kremer, Paul D. Lasky, Eric Thrane

Globular clusters are considered to be likely breeding grounds for compact binary mergers. In this paper, we demonstrate how the gravitational-wave signals produced by compact object mergers can act as tracers of globular cluster formation and evolution. Globular cluster formation is a long-standing mystery in astrophysics, with multiple competing theories d

Shuhao Cui, Xuan Jin, Shuhui Wang, Yuan He

In visual domain adaptation (DA), separating the domain-specific characteristics from the domain-invariant representations is an ill-posed problem. Existing methods apply different kinds of priors or directly minimize the domain discrepancy to address this problem, which lack flexibility in handling real-world situations. Another research pipeline expresses

Pieter Tibboel

We prove that positive elliptic-elliptic rotopulsator solutions of the $n$-body problem in spaces of constant Gaussian curvature that move on Clifford tori of nonconstant size either lie on great circles, or project onto regular polygons. We additionally prove for the case that the configurations project onto regular polygons that all masses are equal and sh

Ulrich Ebling, Ali Alavi, Joachim Brand

We study properties of the lowest energy states at non-zero total momentum (yrast states) of the Hubbard model for spin-1/2 fermions in the quantum ring configuration with attractive on-site interaction at low density. In the one-dimensional (1D) case we solve the Hubbard model using the Bethe ansatz, while for the crossover into the 2D regime we use the Ful

Anthony B. Davis, Linda Forster, David J. Diner, Bernhard Mayer

3D convective cloud images form via two intertwined radiative diffusion processes. Sunlight starts in the anti-solar direction and ends in toward-sensor ones, but repeated forward-peaked scattering smears the well-collimated beams across_direction_ space. This loss of directional memory in the cloud's "outer shell" (OS) is modeled as a random walk (RW) on th

Shailza Pathania, Amit Goyal, Thokala Soloman Raju, C. N. Kumar

We show the existence of nonlinear resonant states in a higher-order nonlinear Schr\"odinger model that appertains to the wave propagation in femtosecond fiber optics, under certain parametric regime. These nonlinear resonant states are analytically illustrated in terms of Gaussian beams, Airy beams, and periodic beams that resulted due to the presence of qu

Sarah Radway, Anthony Luo, Carmine Elvezio, Jenny Cha

As space exploration efforts shift to deep space missions, new challenges emerge regarding astronaut communication and task completion. While the round trip propagation delay for lunar communications is 2.6 seconds, the time delay increases to nearly 22 minutes for Mars missions. This creates a need for astronaut independence from earth-based assistance, and

Boris Buchmann, Kevin W. Lu

Consider the strong subordination of a multivariate L\'evy process with a multivariate subordinator. If the subordinate is a stack of independent L\'evy processes and the components of the subordinator are indistinguishable within each stack, then strong subordination produces a L\'evy process, otherwise it may not. Weak subordination was introduced to exten

Thomas G. Wong

The task of finding an entry in an unsorted list of $N$ elements famously takes $O(N)$ queries to an oracle for a classical computer and $O(\sqrt{N})$ queries for a quantum computer using Grover's algorithm. Reformulated as a spatial search problem, this corresponds to searching the complete graph, or all-to-all network, for a marked vertex by querying an or

Konstantin Makarychev, Miklos Z. Racz, Cyrus Rashtchian, Sergey Yekhanin

Large pools of synthetic DNA molecules have been recently used to reliably store significant volumes of digital data. While DNA as a storage medium has enormous potential because of its high storage density, its practical use is currently severely limited because of the high cost and low throughput of available DNA synthesis technologies. We study the role o

Vitaly Bergelson, Andrew Best

The Furstenberg-S\'ark\"ozy theorem asserts that the difference set $E-E$ of a subset $E \subset \mathbb{N}$ with positive upper density intersects the image set of any polynomial $P \in \mathbb{Z}[n]$ for which $P(0)=0$. Furstenberg's approach relies on a correspondence principle and a polynomial version of the Poincar\'e recurrence theorem, which is derive

Ellert van der Velden, Alan R. Duffy, Darren Croton, Simon J. Mutch

We demonstrate the potential of an emulator-based approach to analyzing galaxy formation models in the domain where constraining data is limited. We have applied the open-source Python package PRISM to the galaxy formation model Meraxes. Meraxes is a semi-analytic model, purposefully built to study the growth of galaxies during the Epoch of Reionization (EoR

W Katherine Tan, Patrick J Heagerty

Prediction models for clinical outcomes may be developed using a source dataset and additionally applied to new settings. Towards model external validation and model updating in the new setting, one procedure is model modification learning that involves the dual goals of recalibrating overall predictions as well as revising individual feature effects. Modifi

Koji Momihara

In the past two decades, many researchers have studied {\it index $2$} Gauss sums, where the group generated by the characteristic $p$ of the underling finite field is of index $2$ in the unit group of ${\mathbb Z}/m{\mathbb Z}$ for the order $m$ of the multiplicative character involved. A complete solution to the problem of evaluating index $2$ Gauss sums w

Lei Wu

We study relative and logarithmic characteristic cycles associated to holonomic $\mathscr D$-modules. As applications, we obtain: (1) an alternative proof of Ginsburg's log characteristic cycle formula for lattices of regular holonomic $\mathscr D$-modules following ideas of Sabbah and Briancon-Maisonobe-Merle, and (2) the constructibility of the log de Rham

Liang Yu, Zhen Gao, Shuqi Qin, Meng Zhang

With the increase of connectivity in power grid, a cascading failure may be triggered by the failure of a transmission line, which can lead to substantial economic losses and serious negative social impacts. Therefore, it is very important to identify the critical lines under various types of attacks that may initiate a cascading failure and deploy defense r

Benteng Ma, Jing Zhang, Yong Xia, Dacheng Tao

Differential Neural Architecture Search (NAS) methods represent the network architecture as a repetitive proxy directed acyclic graph (DAG) and optimize the network weights and architecture weights alternatively in a differential manner. However, existing methods model the architecture weights on each edge (i.e., a layer in the network) as statistically inde

Nadir Hajouji

We classify pairs $(S, \gamma)$, consisting of a rational elliptic surface $S$ and a Galois cover $\gamma$ of the base, which satisfy a condition we call $\mathcal{L}$-stability. We explain how to use the theory of Mordell-Weil lattices to compute the kernel of the restriction maps of Weil-Chatelet groups for $\mathcal{L}$-stable pairs. We also prove results

Koji Momihara

Chowla~(1962), McEliece~(1974), Evans~(1977, 1981) and Aoki~(1997, 2004, 2012) studied Gauss sums, some integral powers of which are in the field of rational numbers. Such Gauss sums are called {\it pure}. In particular, Aoki (2004) gave a necessary and sufficient condition for a Gauss sum to be pure in terms of Dirichlet characters modulo the order of the m

Greg Yang, Edward J. Hu

As its width tends to infinity, a deep neural network's behavior under gradient descent can become simplified and predictable (e.g. given by the Neural Tangent Kernel (NTK)), if it is parametrized appropriately (e.g. the NTK parametrization). However, we show that the standard and NTK parametrizations of a neural network do not admit infinite-width limits th

Yohei Koizumi, Masayuki Kuzuhara, Masashi Omiya, Teruyuki Hirano

We present the optical spectra of 338 nearby M dwarfs, and compute their spectral types, effective temperatures ($T_{\mathrm{eff}}$), and radii. Our spectra have been obtained using several optical spectrometers with spectral resolutions that range from 1200 to 10000. As many as 97% of the observed M-type dwarfs have a spectral type of M3-M6, with a typical

Richard Garner

It is well established that equational algebraic theories, and the monads they generate, can be used to encode computational effects. An important insight of Power and Shkaravska is that comodels of an algebraic theory T -- i.e., models in the opposite category Set^op -- provide a suitable environment for evaluating the computational effects encoded by T. As

Abhinav Prasad, A. K. Srivastava, T. J. Wang

In the present paper, we derive a new dispersion relation for slow magnetoacoustic waves invoking the effect of thermal conductivity, compressive viscosity, radiation and unknown heating term along with the consideration of heating cooling imbalance from linearized MHD equations. We solve the general dispersion relation to understand role of compressive visc

Junjie Liu, Dvira Segal

The thermodynamic uncertainty relation, originally derived for classical Markov-jump processes, provides a trade-off relation between precision and dissipation, deepening our understanding of the performance of quantum thermal machines. Here, we examine the interplay of quantum system coherences and heat current fluctuations on the validity of the thermodyna

Xiang-Kun Dong, Feng-Kun Guo, Bing-Song Zou

Tremendous progress has been made experimentally in the hadron spectrum containing heavy quarks in the last two decades. It is surprising that many resonant structures are around thresholds of a pair of heavy hadrons. There should be a threshold cusp at any $S$-wave threshold. By constructing a nonrelativistic effective field theory with open channels, we di

Na Li, Xun Li, Jing Peng, Zuo Quan Xu

This paper applies a reinforcement learning (RL) method to solve infinite horizon continuous-time stochastic linear quadratic problems, where drift and diffusion terms in the dynamics may depend on both the state and control. Based on Bellman's dynamic programming principle, an online RL algorithm is presented to attain the optimal control with just partial

Vitaly Bergelson, Jake Huryn, Rushil Raghavan

We explore the properties of non-piecewise syndetic sets with positive upper density, which we call "discordant", in countably infinite amenable (semi)groups. Sets of this kind are involved in many questions of Ramsey theory and manifest the difference in complexity between the classical van der Waerden's theorem and Szemer\'{e}di's theorem. We generalize an

Hangsong Yan, Alexei Ashikhmin, Hong Yang

We study internet of things (IoT) systems supported by cell-free (CF) massive MIMO (mMIMO) with optimal linear channel estimation. For the uplink, we consider optimal linear MIMO receiver and obtain an uplink SINR approximation involving only large-scale fading coefficients using random matrix (RM) theory. Using this approximation we design several max-min p

T. J. Christiansen

We study the resonances of Schr\"odinger operators on the infinite product $X=\mathbb{R}^d\times \mathbb{S}^1$, where $d$ is odd, $\mathbb{S}^1$ is the unit circle, and the potential $V\in L^\infty_c(X)$. This paper shows that at high energy, resonances of the Schr\"odinger operator $-\Delta +V$ on $X=\mathbb{R}^d\times \mathbb{S}^1$ which are near the conti

Huangxing Lin, Yihong Zhuang, Yue Huang, Xinghao Ding

The effectiveness of existing denoising algorithms typically relies on accurate pre-defined noise statistics or plenty of paired data, which limits their practicality. In this work, we focus on denoising in the more common case where noise statistics and paired data are unavailable. Considering that denoising CNNs require supervision, we develop a new \textb

Cheng Wang, Jilu Wang, Zeyu Xia, Liwei Xu

In this paper, we propose and analyze a temporally second-order accurate, fully discrete finite element method for the magnetohydrodynamic (MHD) equations. A modified Crank--Nicolson method is used to discretize the model and appropriate semi-implicit treatments are applied to the fluid convection term and two coupling terms. These semi-implicit approximatio

Zhengqian Cheng, Chris A. Marianetti

Here we propose the Variational Discrete Action Theory (VDAT) to study the ground state properties of quantum many-body Hamiltonians. VDAT is a variational theory based on the sequential product density matrix (SPD) ansatz, characterized by an integer $\mathcal{N}$, which monotonically approaches the exact solution with increasing $\mathcal{N}$. To evaluate

Zhengqian Cheng, Chris A. Marianetti

Variational wave functions and Green's functions are two important paradigms for solving quantum Hamiltonians, each having their own advantages. Here we detail the Variational Discrete Action Theory (VDAT), which exploits the advantages of both paradigms in order to approximately solve the ground state of quantum Hamiltonians. VDAT consists of two central co

Piotr Hajłasz

Erd\"os proved in 1946 that if a set $E\subset\mathbb{R}^n$ is closed and non-empty, then the set, called ambiguous locus or medial axis, of points in $\mathbb{R}^n$ with the property that the nearest point in $E$ is not unique, can be covered by countably many surfaces, each of finite $(n-1)$-dimensional measure. We improve the result by obtaining a new reg

Alexander Meill, Jayden Butts, Elijah Sanderson

We provide a simplified characterization of entanglement in physical systems which are symmetric under the action of subgroups of the symmetric group acting on the party labels. Sets of entanglements are inherently equal, lying in the same orbit under the group action, which we demonstrate for cyclic, dihedral, and polyhedral groups. We then introduce new, g

Pei Wang, Yanbo Li

In this paper, we provide a diagrammatic approach to study the branching rules for cell modules on a sequence of walled Brauer algebras. This also allows us to calculate the structure constants of multiplication over the Grothendieck ring of the sequence.

Lin Hu, Bing Huang, Feng Liu

The 7\times7 reconstruction of the Si(111) surface represents arguably the most fascinating surface reconstruction so far observed in nature. Yet, the atomistic mechanism underpinning its formation remains unclear after it was discovered sixty years ago. Experimentally, it is observed post priori so that analysis of its formation mechanism can only be carrie

Jiayi Yang, Lei Deng, Yukuan Yang, Yuan Xie

Semantic segmentation has been a major topic in research and industry in recent years. However, due to the computation complexity of pixel-wise prediction and backpropagation algorithm, semantic segmentation has been demanding in computation resources, resulting in slow training and inference speed and large storage space to store models. Existing schemes th

Yuqing Wang, Zhaoliang Xu, Xinlong Wang, Chunhua Shen

Video instance segmentation (VIS) is the task that requires simultaneously classifying, segmenting and tracking object instances of interest in video. Recent methods typically develop sophisticated pipelines to tackle this task. Here, we propose a new video instance segmentation framework built upon Transformers, termed VisTR, which views the VIS task as a d

Zachary Hoelscher, Eyvindur Ari Palsson

Motivated by the study of integer partitions, we consider partitions of integers into fractions of a particular form, namely with constant denominators and distinct odd or even numerators. When numerators are odd, the numbers of partitions for integers smaller than the denominator form symmetric patterns. If the number of terms is restricted to $h$, then the

Ujjwal Kumar Nandi, Walter Kob, Sarika Maitra Bhattacharyya

We propose a novel model for a glass-forming liquid which allows to switch in a continuous manner from a standard three-dimensional liquid to a fully connected mean-field model. This is achieved by introducing k additional particle-particle interactions which thus augments the effective number of neighbors of each particle. Our computer simulations of this s

Yixin Dai, Wenxue Li, Liu Wang, Chuan Luo

In this study, the combination of a developing data mining technique called statistical decision tree analysis method and Raman spectroscopy was proposed to differentiate human normal leukocytes from malignant tumor cells. Statistical results obtained indicate this method possesses an admirable performance of a mean classification accuracy of 94.43% on the o

Navid Rezazadeh, Solmaz S. Kia

Constrained submodular set function maximization problems often appear in multi-agent decision-making problems with a discrete feasible set. A prominent example is the problem of multi-agent mobile sensor placement over a discrete domain. However, submodular set function optimization problems are known to be NP-hard. In this paper, we consider a class of sub

Abhiroop Bhattacharjee, Priyadarshini Panda

Memristive crossbars can efficiently implement Binarized Neural Networks (BNNs) wherein the weights are stored in high-resistance states (HRS) and low-resistance states (LRS) of the synapses. We propose SwitchX mapping of BNN weights onto ReRAM crossbars such that the impact of crossbar non-idealities, that lead to degradation in computational accuracy, are

Kavisha Vidanapathirana, Peyman Moghadam, Ben Harwood, Muming Zhao

Place Recognition enables the estimation of a globally consistent map and trajectory by providing non-local constraints in Simultaneous Localisation and Mapping (SLAM). This paper presents Locus, a novel place recognition method using 3D LiDAR point clouds in large-scale environments. We propose a method for extracting and encoding topological and temporal i

Yikai Wang, Weijian Li

In recent years, natural language processing (NLP) has become one of the most important areas with various applications in human's life. As the most fundamental task, the field of word embedding still requires more attention and research. Currently, existing works about word embedding are focusing on proposing novel embedding algorithms and dimension reducti

Elita A. Lobo, Mohammad Ghavamzadeh, Marek Petrik

In reinforcement learning, robust policies for high-stakes decision-making problems with limited data are usually computed by optimizing the percentile criterion, which minimizes the probability of a catastrophic failure. Unfortunately, such policies are typically overly conservative as the percentile criterion is non-convex, difficult to optimize, and ignor

Z. J. Zhang, K. Yan, C. M. Li, G. Q. Zhang

Fast radio bursts (FRBs) are millisecond-duration radio transients and can be used as a cosmological probe. However, the dispersion measure (DM) contributed by intergalactic medium (IGM) is hard to be distinguished from other components. In this paper, we use the IllustrisTNG simulation to realistically estimate the $DM_{\rm IGM}$ up to $z\sim 9$. We find $D

M. G. Dainotti, S. Livermore, D. A. Kann, L. Li

Gamma-Ray Bursts (GRBs) are fascinating events due to their panchromatic nature. Their afterglow emission is observed from sub-TeV energies to radio wavelengths. We investigate GRBs that present an optical plateau, leveraging on the resemblance with the X-ray plateau shown in many GRB light curves (LCs). We comprehensively analyze all published GRBs with kno

V. Balbekov

Coherent transverse oscillations of a bunch in a ring accelerator are considered. Three different models of the bunch are used: a hollow bunch in a square potential well, a square bunch in a parabolic potential well, and a parabolic bunch in a parabolic well. The bunch space-charge field, wakefield, and chromaticity are taken into account in all the cases. T

David Cruz-Uribe, Scott Rodney

A classical regularity result is that non-negative solutions to the Dirichlet problem $\Delta u =f$ in a bounded domain $\Omega$, where $f\in L^q(\Omega)$, $q>\frac{n}2$, satisfy $\|u\|_{L^\infty(\Omega)} \leq C\|f\|_{L^q(\Omega)}$. We extend this result in three ways: we replace the Laplacian with a degenerate elliptic operator; we show that we can take the

Nello Blaser, Erlend Raa Vågset

Finding a cycle of lowest weight that represents a homology class in a simplicial complex is known as homology localization (HL). Here we address this NP-complete problem using parameterized complexity theory. We show that it is W[1]-hard to approximate the HL problem when it is parameterized by solution size. We have also designed and implemented two algori

Saliha Muradoğlu, Nicholas Evans, Ekaterina Vylomova

Nen verbal morphology is remarkably complex; a transitive verb can take up to 1,740 unique forms. The combined effect of having a large combinatoric space and a low-resource setting amplifies the need for NLP tools. Nen morphology utilises distributed exponence - a non-trivial means of mapping form to meaning. In this paper, we attempt to model Nen verbal mo

Aayush Prakash, Shoubhik Debnath, Jean-Francois Lafleche, Eric Cameracci

Synthetic data is emerging as a promising solution to the scalability issue of supervised deep learning, especially when real data are difficult to acquire or hard to annotate. Synthetic data generation, however, can itself be prohibitively expensive when domain experts have to manually and painstakingly oversee the process. Moreover, neural networks trained

Junfan Lin, Zhongzhan Huang, Keze Wang, Xiaodan Liang

Although deep reinforcement learning (RL) has been successfully applied to a variety of robotic control tasks, it's still challenging to apply it to real-world tasks, due to the poor sample efficiency. Attempting to overcome this shortcoming, several works focus on reusing the collected trajectory data during the training by decomposing them into a set of po

Benoit Steiner, Chris Cummins, Horace He, Hugh Leather

As machine learning techniques become ubiquitous, the efficiency of neural network implementations is becoming correspondingly paramount. Frameworks, such as Halide and TVM, separate out the algorithmic representation of the network from the schedule that determines its implementation. Finding good schedules, however, remains extremely challenging. We model

Masato Kimura, Patrick van Meurs, Zhenxing Yang

We consider the dynamics of point particles which are confined to a bounded, possibly nonconvex domain $\Omega$. Collisions with the boundary are described as purely elastic collisions. This turns the description of the particle dynamics into a coupled system of second order ODEs with discontinuous right-hand side. The main contribution of this paper is to d

S. J. Walters, L. K. Forbes, A. M. Reading

This paper presents two approaches to mathematical modelling of a synthetic seismic pulse, and a comparison between them. First, a new analytical model is developed in two-dimensional Cartesian coordinates. Combined with an initial condition of sufficient symmetry, this provides a valuable check for the validity of the numerical method that follows. A partic

Min Fang, Jinyoung Serena Kim, Ilaria Pascucci, Dániel Apai

In this paper, we present a study of the Trapezium cluster in Orion. We analyze flux-calibrated VLT/MUSE spectra of 361 stars to simultaneously measure the spectral types, reddening, and the optical veiling due to accretion. We find that the extinction law from Cardelli et al. (1989) with a total-to-selective extinction value of $R_{\rm V}=$5.5 is more suita

Jibran Iqbal Shah

Using a summation identity obtained for the Fourier coefficients of $x^{2k}$, we derive a closed form expression for the zeta function at even positive integers, using a technique similar to one in an existing proof by Aladdi and Defant[1], but in a simpler and shorter way.

Francois Roewer-Despres, Janelle Berscheid

Despite its utopian promises as a disruptive equalizer, AI - like most tools deployed under the guise of neutrality - has tended to simply reinforce existing social structures. To counter this trend, radical AI calls for centering on the marginalized. We argue that gaps in key infrastructure are preventing the widespread adoption of radical AI, and propose a

Bas Ketsman, Dan Suciu, Yufei Tao

We present a constant-round algorithm in the massively parallel computation (MPC) model for evaluating a natural join where every input relation has two attributes. Our algorithm achieves a load of $\tilde{O}(m/p^{1/\rho})$ where $m$ is the total size of the input relations, $p$ is the number of machines, $\rho$ is the join's fractional edge covering number,

Toyokazu Sekiguchi, Tomo Takahashi

Although cosmic microwave background (CMB) is the most powerful cosmological probe of neutrino masses, it is in trouble with local direct measurements of $H_0$, which is called the $H_0$ tension. Since neutrino masses are correlated with $H_0$ in CMB, one can expect the cosmological bound on neutrino masses would be much affected by the $H_0$ tension. We inv

Yong-Pan Gao, Chuan Wang

The properties of open quantum system in quantum information science is now extensively investigated more generally by the research community as a fundamental issue for a variety of applications. Usually, the states of the open quantum system might be disturbed by the decoherence which will reduce the fidelity in the quantum information processing. So it is

Haoxing Chen, Huaxiong Li, Yaohui Li, Chunlin Chen

The goal of few-shot learning is to classify unseen categories with few labeled samples. Recently, the low-level information metric-learning based methods have achieved satisfying performance, since local representations (LRs) are more consistent between seen and unseen classes. However, most of these methods deal with each category in the support set indepe

Yixiong Zou, Shanghang Zhang, Guangyao Chen, Yonghong Tian

Deep learning has achieved great success in recognizing video actions, but the collection and annotation of training data are still quite laborious, which mainly lies in two aspects: (1) the amount of required annotated data is large; (2) temporally annotating the location of each action is time-consuming. Works such as few-shot learning or untrimmed video r

Hubert Lin, Mitchell van Zuijlen, Sylvia C. Pont, Maarten W. A. Wijntjes

A common strategy for improving model robustness is through data augmentations. Data augmentations encourage models to learn desired invariances, such as invariance to horizontal flipping or small changes in color. Recent work has shown that arbitrary style transfer can be used as a form of data augmentation to encourage invariance to textures by creating pa

Mario Alvarez-Picallo, C. -H. Luke Ong

Cartesian difference categories are a recent generalisation of Cartesian differential categories which introduce a notion of "infinitesimal" arrows satisfying an analogue of the Kock-Lawvere axiom, with the axioms of a Cartesian differential category being satisfied only "up to an infinitesimal perturbation". In this work, we construct a simply-typed calculu

Eduardo C. Garrido-Merchán, Martin Molina, Francisco M. Mendoza

This work seeks to study the beneficial properties that an autonomous agent can obtain by implementing a cognitive architecture similar to the one of conscious beings. Along this document, a conscious model of autonomous agent based in a global workspace architecture is presented. We describe how this agent is viewed from different perspectives of philosophy

Gregorio Landi, Giovanni E. Landi

The center of gravity is one of the most frequently used algorithm for position reconstruction with different analytical forms for the noise optimization. The error distributions of the different forms are essential instruments to improve the track fitting in particle physics. Their Cauchy-(Agnesi) tails have a beneficial effects to attenuate the outliers di