June 2020 arXiv papers — page 18

Jerzy Białkowski

We construct a numeric algorithm for completing the proof of a conjecture asserting that all deformed preprojective algebras of generalized Dynkin type are periodic. In particular, we obtain an algorithmic procedure showing that non-trivial deformed preprojective algebras of Dynkin types $\mathbb{E}_7$ and $\mathbb{E}_8$ exist only in characteristic 2. As a

Klaus Wehmuth, Artur Ziviani, Leonardo Chinelate Costa, Ana Paula Couto da Silva

In complex network analysis, centralities based on shortest paths, such as betweenness and closeness, are widely used. More recently, many complex systems are being represented by time-varying, multilayer, and time-varying multilayer networks, i.e. multidimensional (or high order) networks. Nevertheless, it is well-known that the aggregation process may crea

John R. Doyle, Alex Rice

For $\ell\geq 2$ and $h\in \mathbb{Z}[x_1,\dots,x_{\ell}]$ of degree $k\geq 2$, we show that every set $A\subseteq \{1,2,\dots,N\}$ lacking nonzero differences in $h(\mathbb{Z}^{\ell})$ satisfies $|A|\ll_h Ne^{-c(\log N)^μ}$, where $c=c(h)>0$, $μ=[(k-1)^2+1]^{-1}$ if $\ell=2$, and $μ=1/2$ if $\ell\geq 3$, provided $h(\mathbb{Z}^{\ell})$ contains a multiple o

Yifan Song, David Nakath, Mengkun She, Furkan Elibol

Nowadays underwater vision systems are being widely applied in ocean research. However, the largest portion of the ocean - the deep sea - still remains mostly unexplored. Only relatively few image sets have been taken from the deep sea due to the physical limitations caused by technical challenges and enormous costs. Deep sea images are very different from t

Taylor R. Brown

This paper introduces the {\it particle swarm filter} (not to be confused with particle swarm optimization): a recursive and embarrassingly parallel algorithm that targets an approximation to the sequence of posterior predictive distributions by averaging expectation approximations from many particle filters. A law of large numbers and a central limit theore

Bui Ngoc Muoi, Ngai-Ching Wong

Let $S$ be a right reversible semitopological semigroup, and let $\operatorname{LUC}(S)$ be the space of left uniformly continuous functions on $S$. Suppose that $\operatorname{LUC}(S)$ has a left invariant mean. Let $K$ be a weakly compact convex subset of a Banach space. We show that there always exists a common fixed point for any jointly weakly continuou

Astik Haldar, Parna Roy, Abhik Basu

We study the nonequilibrium steady states of an asymmetric exclusion process (TASEP) coupled to a reservoir of unlimited capacity. We elucidate how the steady states are controlled by the interplay between the reservoir population that dynamically controls both the entry and exit rates of the TASEP, and the total particle number in the system. The TASEP can

Dieter Armbruster, Michael Herty, Giuseppe Visconti

The Ensemble Kalman Filter (EnKF) belongs to the class of iterative particle filtering methods and can be used for solving control--to--observable inverse problems. In this context, the EnKF is known as Ensemble Kalman Inversion (EKI). In recent years several continuous limits in the number of iteration and particles have been performed in order to study pro

F. P. An, A. B. Balantekin, H. R. Band, M. Bishai

Providing a possible connection between neutrino emission and gravitational-wave (GW) bursts is important to our understanding of the physical processes that occur when black holes or neutron stars merge. In the Daya Bay experiment, using data collected from December 2011 to August 2017, a search has been performed for electron-antineutrino signals coincidin

S. Maltezos

After the breakout of the disease caused by the new virus COVID-19, the mitigation stage has been reached in most of the countries in the world. During this stage, a more accurate data analysis of the daily reported cases and other parameters became possible for the European countries and has been performed in this work. Based on a proposed parametrization m

Qing Ke

Interdisciplinary research (IDR) has been considered as an important source for scientific breakthroughs and as a solution to today's complex societal challenges. While ample empirical evidence has suggested its benefits within the academia such as better creativity and higher scientific impact and visibility, its societal benefits -- a key argument orig

Sumit Singh, Ljubisa D. R. Kocinac

A space $X$ is said to have the set star Hurewicz property if for each nonempty subset $A$ of $X$ and each sequence $(\mathcal{U}_n: n \in \mathbb{N})$ of sets open in $X$ such that for each $n\in \mathbb N$, $\overline{A} \subset \cup \mathcal{U}_n$, there is a sequence $(\mathcal{V}_n: n \in \mathbb{N})$ such that for each $n \in \mathbb{N}$, $\mathcal{V}_

Melissa A. Huggan, Richard J. Nowakowski

The 'Cheating Robot' version of Cops and Robbers is played on a finite, simple, connected graph. The players move in the same time period. However, before moving, the robot observes to which vertices the cops are moving and it is fast enough to complete its move in the time period. The cops also know that the robot will use this information. More cop

Raphael Forien, Guodong Pang, Etienne Pardoux

We introduce an epidemic model with varying infectivity and general exposed and infectious periods, where the infectivity of each individual is a random function of the elapsed time since infection, those function being i.i.d. for the various individuals in the population. This approach models infection-age dependent infectivity, and extends the classical SI

S. Rammohan, A. K. Chauhan, R. Nath, A. Eisfeld

Experiments have demonstrated that atoms excited to specific Rydberg states within Bose-Einstein condensates cause significant excitation of phonons. If the Rydberg atom is brought into an electronic superposition state, this coupling to phonons leads to decoherence. We provide the theoretical basis for the treatment of the latter. To this end, we evaluate R

Niladri Gomes, Feng Zhang, Noah F. Berthusen, Cai-Zhuang Wang

We develop a resource efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic method features a fixed shallow quantum circuit depth along the state evolution path. We use this algorithm to determine binding energy curves of a set of molecules, including H$_2$

David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna

Recent results in supervised learning suggest that while overparameterized models have the capacity to overfit, they in fact generalize quite well. We ask whether the same phenomenon occurs for offline contextual bandits. Our results are mixed. Value-based algorithms benefit from the same generalization behavior as overparameterized supervised learning, but

Michael P. Lingg, Stephen M. Hughey, Hasan Metin Aktulga, Balasubramaniam Shanker

Evaluation of pair potentials is critical in a number of areas of physics. The classicalN-body problem has its root in evaluating the Laplace potential, and has spawned tree-algorithms, the fast multipole method (FMM), as well as kernel independent approaches. Over the years, FMM for Laplace potential has had a profound impact on a number of disciplines as i

Patrick Ingram

We study the dynamics of a class of endomorphisms of A^N which restricts, when N = 1, to the class of unicritical polynomials. Over the complex numbers, we obtain lower bounds on the sum of Lyapunov exponents, and a statement which generalizes the compactness of the Mandelbrot set. Over the algebraic numbers, we obtain estimates on the critical height, and o

Mohamed Zbiri, Catherine M. Aitchison, Reiner S. Sprick, Andrew I. Cooper

The quest for efficient and economically accessible cleaner methods to develop sustainable carbon-free energy sources induced a keen interest in the production of hydrogen fuel. This can be achieved via the water-splitting process exploiting solar energy but requiring the use of adequate photocatalysts. Covalent triazine-based frameworks (CTFs) are target ph

Byeong Moom Kim, Myung-Hwan KIm, Dayoon Park

In this paper, we will prove that if $d$ is sufficiently large square-free positive rational integer, then there is no integral septenary universal quadratic lattice over $\mathcal{O}_F$ where $F=\mathbb Q(\sqrt{d})$.

P. Reinert, H. Krebs, E. Epelbaum

The pion-nucleon coupling constants determine the strength of the long-range nuclear forces and play a fundamental part in our understanding of nuclear physics. While the charged- and neutral-pion couplings to protons and neutrons are expected to be very similar, owing to the approximate isospin symmetry of the strong interaction, the different masses of the

Guandong Xu, Tri Dung Duong, Qian Li, Shaowu Liu

Recent years have witnessed the rapid growth of machine learning in a wide range of fields such as image recognition, text classification, credit scoring prediction, recommendation system, etc. In spite of their great performance in different sectors, researchers still concern about the mechanism under any machine learning (ML) techniques that are inherently

Nikhil Kalyanapuram, Raghav G. Jha

We show that accordiohedra furnish polytopes which encode amplitudes for all massive scalar field theories with generic interactions. This is done by deriving integral formulae for the Feynman diagrams at tree level and integrands at one loop level in the planar limit using the twisted intersection theory of convex realizations of the accordiohedron polytope

Joel E. Restrepo, Michael Ruzhansky, Durvudkhan Suragan

Explicit solutions of differential equations of complex fractional orders with respect to functions and with continuous variable coefficients are established. The representations of solutions are given in terms of some convergent infinite series of fractional integro-differential operators, which can be widely and efficiently used for analytic and computatio

Tamir Bendory, Ariel Jaffe, William Leeb, Nir Sharon

We study super-resolution multi-reference alignment, the problem of estimating a signal from many circularly shifted, down-sampled, and noisy observations. We focus on the low SNR regime, and show that a signal in $\mathbb{R}^M$ is uniquely determined when the number $L$ of samples per observation is of the order of the square root of the signal's length

Lamei Zhang, Siyu Zhang, Bin Zou, Hongwei Dong

Deep learning and convolutional neural networks (CNNs) have made progress in polarimetric synthetic aperture radar (PolSAR) image classification over the past few years. However, a crucial issue has not been addressed, i.e., the requirement of CNNs for abundant labeled samples versus the insufficient human annotations of PolSAR images. It is well-known that

Jing Zhu, Yanan Xu, Yanmin Zhu

The aim of session-based recommendation is to predict the users' next clicked item, which is a challenging task due to the inherent uncertainty in user behaviors and anonymous implicit feedback information. A powerful session-based recommender can typically explore the users' evolving interests (i.e., a combination of his/her long-term and short-term

K. M. Rotermund, S. C. Chapman, K. A. Phadke, R. Hill

We present Gemini-S and {\it Spitzer}-IRAC optical-through-near-IR observations in the field of the SPT2349-56 proto-cluster at $z=4.3$. We detect optical/IR counterparts for only nine of the 14 submillimetre galaxies (SMGs) previously identified by ALMA in the core of SPT2349-56. In addition, we detect four $z\sim4$ Lyman-break galaxies (LBGs) in the 30 arc

Hanan Hindy, Robert Atkinson, Christos Tachtatzis, Jean-Noël Colin

Machine Learning (ML) and Deep Learning (DL) have been used for building Intrusion Detection Systems (IDS). The increase in both the number and sheer variety of new cyber-attacks poses a tremendous challenge for IDS solutions that rely on a database of historical attack signatures. Therefore, the industrial pull for robust IDSs that are capable of flagging z

Hanan Hindy, Christos Tachtatzis, Robert Atkinson, David Brosset

The use of supervised Machine Learning (ML) to enhance Intrusion Detection Systems has been the subject of significant research. Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to re-train the model for every unseen cyber-attack class. However, retraining the model

Fredrik Arbo Høeg

We study Hölder continuity for solutions of the $p$-Laplace equation. This is established through a method involving an ordinary differential inequality, in contrast to the classical proof of the De Giorgi-Nash-Moser Theorem which uses iteration of an inequality through concentric balls.

Hanan Hindy, Ethan Bayne, Miroslav Bures, Robert Atkinson

The Internet of Things (IoT) is one of the main research fields in the Cybersecurity domain. This is due to (a) the increased dependency on automated device, and (b) the inadequacy of general purpose Intrusion Detection Systems (IDS) to be deployed for special purpose networks usage. Numerous lightweight protocols are being proposed for IoT devices communica

Khaled Elbassioni

Given a partially order set (poset) $P$, and a pair of families of ideals $\mathcal{I}$ and filters $\mathcal{F}$ in $P$ such that each pair $(I,F)\in \mathcal{I}\times\mathcal{F}$ has a non-empty intersection, the dualization problem over $P$ is to check whether there is an ideal $X$ in $P$ which intersects every member of $\mathcal{F}$ and does not contain

Sashikumaar Ganesan, Deepak Subramani

A novel predictive modeling framework for the spread of infectious diseases using high dimensional partial differential equations is developed and implemented. A scalar function representing the infected population is defined on a high-dimensional space and its evolution over all directions is described by a population balance equation (PBE). New infections

Micol Benetti, Salvatore Capozziello, Gaetano Lambiase

We focus on viable $f(T)$ teleparallel cosmological models, namely power law, exponential and square-root exponential, carrying out a detailed study of their evolution at all scales. Indeed, these models were extensively analysed in the light of late time measurements, while it is possible to find only upper limits looking at the very early time behavior, i.

Jiahua Dong, Yang Cong, Gan Sun, Tao Zhang

Online metric learning has been widely exploited for large-scale data classification due to the low computational cost. However, amongst online practical scenarios where the features are evolving (e.g., some features are vanished and some new features are augmented), most metric learning models cannot be successfully applied to these scenarios, although they

Li-Li Li, Fu-Hu Liu, Khusniddin K. Olimov

The transverse momentum spectra of charged pions, kaons, and protons produced at mid-rapidity in central nucleus-nucleus (AA) collisions at high energies are analyzed by considering particles to be created from two participant partons which are assumed to be contributors from the collision system. Each participant (contributor) parton is assumed to contribut

A. A. Kirillov, E. P. Savelova

We present the hypothesis that some of ring galaxies were formed by relic magnetic torus - shaped wormholes. In the primordial plasma before the recombination magnetic fields of wormholes trap baryons whose energy is smaller than a threshold energy. They work as the Maxwell's demons collecting baryons from the nearest (horizon size) region and thus formi

Ya-Fen Hsu, Jung-Jung Su

The Josephson effect can be regarded as a striking manifestation of exciton condensation. It has been suggested to tune the condensate phase of bilayer excitons by applying interlayer tunneling current. A poorly-understood phenomenon observed by Huang {\it et al} [Phys. Rev. Lett. $\bf 109$, 156802 (2012)] demonstrates that the critical values of the interla

Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach

Videos of actions are complex signals containing rich compositional structure in space and time. Current video generation methods lack the ability to condition the generation on multiple coordinated and potentially simultaneous timed actions. To address this challenge, we propose to represent the actions in a graph structure called Action Graph and present t

Tao Shen, Jie Zhang, Xinkang Jia, Fengda Zhang

Federated learning (FL) enables collaboratively training deep learning models on decentralized data. However, there are three types of heterogeneities in FL setting bringing about distinctive challenges to the canonical federated learning algorithm (FedAvg). First, due to the Non-IIDness of data, the global shared model may perform worse than local models th

S. A. Simmons, F. A. Bayocboc,, J. C. Pillay, D. Colas

Shock waves are examples of the far-from-equilibrium behaviour of matter; they are ubiquitous in nature, yet the underlying microscopic mechanisms behind their formation are not well understood. Here, we study the dynamics of dispersive quantum shock waves in a one-dimensional Bose gas, and show that the oscillatory train forming from a local density bump ex

Ralph John de la Cruz, Philip Saltenberger

Let $B$ be some invertible Hermitian or skew-Hermitian matrix. A matrix $A$ is called $B$-normal if $AA^\star = A^\star A$ holds for $A$ and its adjoint matrix $A^\star := B^{-1}A^HB$. In addition, a matrix $Q$ is called $B$-unitary, if $Q^HBQ = B$. We develop sparse canonical forms for nondefective (i.e. diagonalizable) $J_{2n}$-normal matrices and $R_n$-no

Victor Alexandrov

In 1968, N.\,V.~Efimov proved the following remarkable theorem: \textit{Let $f:\mathbb{R}^2\to\mathbb{R}^2\in C^1$ be such that $\det f&#39;(x)<0$ for all $x\in\mathbb{R}^2$ and let there exist a function $a(x)>0$ and constants $C_1\geqslant 0$, $C_2\geqslant 0$ such that the inequalities $|1/a(x)-1/a(y)|\leqslant C_1 |x-y|+C_2$ and $|\det f&#39;(x)|\geqslan

Valentin Allard, Nicolas Chamel

Mutual entrainment effects in hot neutron-proton superfluid mixtures are studied in the framework of the self-consistent nuclear energy-density functional theory. The local mass currents in homogeneous or inhomogeneous nuclear systems, which we derive from the time-dependent Hartree-Fock-Bogoliubov equations at finite temperatures, are shown to have the same

Matteo Basei, Xin Guo, Anran Hu, Yufei Zhang

We study finite-time horizon continuous-time linear-quadratic reinforcement learning problems in an episodic setting, where both the state and control coefficients are unknown to the controller. We first propose a least-squares algorithm based on continuous-time observations and controls, and establish a logarithmic regret bound of order $O((\ln M)(\ln\ln M)

Sanjay K. Nawalkha, Xiaoyang Zhuo

This paper introduces a dynamic change of measure approach for computing the analytical solutions of expected future prices (and therefore, expected returns) of contingent claims over a finite horizon. The new approach constructs hybrid probability measures called the &#34;equivalent expectation measures&#34;(EEMs), which provide the physical expectation of

Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan, Roshan Godaliyadda

Low light image enhancement is an important challenge for the development of robust computer vision algorithms. The machine learning approaches to this have been either unsupervised, supervised based on paired dataset or supervised based on unpaired dataset. This paper presents a novel deep learning pipeline that can learn from both paired and unpaired datas

Milutin Blagojević, James M. Nester

In the literature on $f(T)$ gravity, the status of local Lorentz invariance and the number of physical degrees of freedom have been controversial issues. Relying on a detailed Hamiltonian analysis, we show that there are several scenarios describing how local Lorentz invariance can be broken, but in the generic case, the number of physical degrees of freedom

Xiaodong Yang, Ran Liu, Jun Li, Xinhua Peng

Designing proper time-dependent control fields for slowly varying the system to the ground state that encodes the problem solution is crucial for adiabatic quantum computation. However, inevitable perturbations in real applications demand us to accelerate the evolution so that the adiabatic errors can be prevented from accumulation. Here, by treating this tr

Tanner Fiez, Nihar B. Shah, Lillian Ratliff

A number of applications involve sequential arrival of users, and require showing each user an ordering of items. A prime example (which forms the focus of this paper) is the bidding process in conference peer review where reviewers enter the system sequentially, each reviewer needs to be shown the list of submitted papers, and the reviewer then &#34;bids&#3

Xisen Jin, Arka Sadhu, Junyi Du, Xiang Ren

We explore task-free continual learning (CL), in which a model is trained to avoid catastrophic forgetting in the absence of explicit task boundaries or identities. Among many efforts on task-free CL, a notable family of approaches are memory-based that store and replay a subset of training examples. However, the utility of stored seen examples may diminish

Alex Mariakakis, Sifang Chen, Bichlien Nguyen, Kirsten Bray

Environmental hazards often go unnoticed because they are invisible to the naked eye, posing risks to our health over time. Project Calico aims to raise awareness of these risks by augmenting everyday fashion with color-changing chemical sensors that can be observed at a glance or captured by a smartphone camera. Project Calico leverages existing cosmetic an

Y. K. Hsiao, Qian Yi, Shu-Ting Cai, H. J. Zhao

In the quark-diagram scheme, we study the charmed baryon decays of ${\bf B}_c\to {\bf B}^* M$, where ${\bf B}_c$ is $Λ_c^+$ or $Ξ_c^{+(0)}$, together with ${\bf B}^*$ ($M$) the decuplet baryon (pseudoscalar meson). It is found that only two $W$-exchange processes are allowed to contribute to ${\bf B}_c\to {\bf B}^* M$. Particularly, we predict ${\cal B}(Λ_c^

Levan Chotorlishvili, Chenglong Jia, Diana A. Rata, Liane Brandt

Composite materials consisting of coupled magnetic and ferroelectric layers hold the promise for new emergent properties such as controlling magnetism with electric fields. Obviously, the interfacial coupling mechanism plays a crucial role and its understanding is the key for exploiting this material class for technological applications. This short review is

Supriyo Ghosh, Christopher K. Newman, Marianne M. Francois

We develop a fully-coupled, fully-implicit approach for phase-field modeling of solidification in metals and alloys. Predictive simulation of solidification in pure metals and metal alloys remains a significant challenge in the field of materials science, as microstructure formation during the solidification process plays a critical role in the properties an

Katsuaki Tanabe

The integrated information theory is thought to be a key clue towards the theoretical understanding of consciousness. In this study, we propose a simple numerical model comprising a set of coupled double quantum dots, where the disconnection of the elements is represented by the removal of Coulomb interaction between the quantum dots, for the quantitative in

Damanvir Singh Binner, Amarpreet Rattan

For positive integers $s$ and $L \geq 3$, Berkovich and Uncu (Ann. Comb. $23$ ($2019$) $263$--$284$) conjectured an inequality between the sizes of two closely related sets of partitions whose parts lie in the interval $\{s, \ldots, L+s\}$. Further restrictions are placed on the sets by specifying impermissible parts as well as a minimum part. The authors pr

Pankaj Sheoran, Hemwati Nandan, Eva Hackmann, Ulises Nucamendi

We study the collision of two massive particles with non-zero intrinsic spin moving in the equatorial plane in the background of a Schwarzschild black hole surrounded by quintessential matter field (SBHQ). For the quintessential matter equation of state (EOS) parameter, we assume three different values. It is shown that for collisions outside the event horiz

Carla Farsi, Christopher Seaton

For a finitely presented discrete group $Γ$, we introduce two generalizations of the orbifold Euler characteristic and $Γ$-orbifold Euler characteristic to a class of proper topological groupoids large enough to include all cocompact proper Lie groupoids. The $Γ$-Euler characteristic is defined as an integral with respect to the Euler characteristic over the

Liwei Wang, Yu-Chin Chan, Faez Ahmed, Zhao Liu

Metamaterials are emerging as a new paradigmatic material system to render unprecedented and tailorable properties for a wide variety of engineering applications. However, the inverse design of metamaterial and its multiscale system is challenging due to high-dimensional topological design space, multiple local optima, and high computational cost. To address

Liwei Wang, Siyu Tao, Ping Zhu, Wei Chen

The data-driven approach is emerging as a promising method for the topological design of multiscale structures with greater efficiency. However, existing data-driven methods mostly focus on a single class of microstructures without considering multiple classes to accommodate spatially varying desired properties. The key challenge is the lack of an inherent o

Dongdong Chen, Mike E. Davies, Mohammad Golbabaee

Consistency of the predictions with respect to the physical forward model is pivotal for reliably solving inverse problems. This consistency is mostly un-controlled in the current end-to-end deep learning methodologies proposed for the Magnetic Resonance Fingerprinting (MRF) problem. To address this, we propose ProxNet, a learned proximal gradient descent fr

Dechao Li, Qingxue Zeng

To strengthen the effectiveness of approximate reasoning in fuzzy modus ponens (FMP) and fuzzy modus tollens (FMT) problems, three approximate reasoning schemes with aggregation functions are developed and their validity is respectively investigated in this paper. We firstly study some properties of fuzzy implication generated by aggregation function. And th

Xiaoqian Liu, Dongdong Yan, Xuchen Deng, Danhua Wang

In this paper, we introduce the notion of a four-angle Hopf module for a Hom-Hopf algebra $(H,β)$ and show that the category $\!^{H}_{H}\mathfrak{M}^{H}_{H}$ of four-angle Hopf modules is a monoidal category with either a Hom-tensor product $\otimes_{H}$ or a Hom-cotensor product $\Box_{H}$ as a monoidal product. We study the category $\mathcal{YD}^{H}_{H}$

Quoc Tran-Dinh, Deyi Liu, Lam M. Nguyen

We develop a novel and single-loop variance-reduced algorithm to solve a class of stochastic nonconvex-convex minimax problems involving a nonconvex-linear objective function, which has various applications in different fields such as machine learning and robust optimization. This problem class has several computational challenges due to its nonsmoothness, n

Hajar Emami, Ming Dong, Carri K. Glide-Hurst

Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown rapidly in radiation therapy. However, developing class solutions for medical images that contain atypical anatomy remains a major limitation. In this paper, we propose a novel spatial attention-guided generative adversarial network (attention-GAN) model to generate accur

Scott W. McIntosh, Sandra C. Chapman, Robert J. Leamon, Ricky Egeland

The Sun exhibits a well-observed modulation in the number of spots on its disk over a period of about 11 years. From the dawn of modern observational astronomy sunspots have presented a challenge to understanding -- their quasi-periodic variation in number, first noted 175 years ago, stimulates community-wide interest to this day. A large number of technique

Boyuan Liu, Volker Bromm

We construct a theoretical framework to study Population III (Pop III) star formation in the post-reionization epoch ($z\lesssim 6$) by combining cosmological simulation data with semi-analytical models. We find that due to radiative feedback (i.e. Lyman-Werner and ionizing radiation) massive haloes ($M_{\rm halo}\gtrsim 10^{9}\ \rm M_{\odot}$) are the major

Ramtin Afshar, Michael T. Goodrich, Pedro Matias, Martha C. Osegueda

In this paper, we study the parallel query complexity of reconstructing biological and digital phylogenetic trees from simple queries involving their nodes. This is motivated from computational biology, data protection, and computer security settings, which can be abstracted in terms of two parties, a responder, Alice, who must correctly answer queries of a

Wei Guo, Qin-He Yang, Shao-Zhou Jiang

The chiral Lagrangians with vector mesons are constructed in different approaches, including the next-to-leading order Lagrangian in the vector-field approach, the next-to-next-to-leading order Lagrangians in the tensor-field and the hidden local symmetry approaches. Some redundant terms are found at the next-to-leading order in the tensor-field and the hidd

Takato Yasuno, Akira Ishii, Junichiro Fujii, Masazumi Amakata

In order to monitor the state of large-scale infrastructures, image acquisition by autonomous flight drones is efficient for stable angle and high-quality images. Supervised learning requires a large data set consisting of images and annotation labels. It takes a long time to accumulate images, including identifying the damaged regions of interest (ROIs). In

Nicholas Rouse

We prove two arithmetic properties of Dehn surgery points on the canonical component of the $\mathrm{SL}_2(\mathbf{C})$-character variety of the knot $7_4$. The first is that the residue characteristics of the ramified places of the Dehn surgery points form an infinite set, providing evidence for a conjecture of Chinburg, Reid, and Stover. The second is that

J. A. Camargo-Martínez, G. I. González-Pedreros, F. Mesa

This work presents an analysis of the functional derivative of the superconducting transition temperature T$_c$ with respect to the electron-phonon coupling function $α^2F(ω)$ [$δT_c/δα^2$F($ω$)] and $α^2F(ω)$ spectrum of H$_3$S ($Im\bar3m$), in the pressure range where the high-T$_c$ was measured (155-225 GPa). The calculations are done in the framework of

Ang Li, Fan Liu, Xuewen Liao, Yuanjun Shen

In this paper, we propose an interference exploitation symbol-level precoding (SLP) method for multi-level modulations via an in-block power allocation scheme to greatly reduce the signaling overhead. Existing SLP approaches require the symbol-level broadcast of the rescaling factor to the users for correct demodulation, which hinders the practical implement

D. B. Melrose, M. Z. Rafat, A. Mastrano

We consider critically the three most widely favored pulsar radio emission mechanisms: coherent curvature emission (CCE), beam-driven relativistic plasma emission (RPE) and anomalous Doppler emission (ADE). We assume that the pulsar plasma is one dimensional (1D), streaming outward with a bulk Lorentz factor $γ_{\rm s} \gg \langle γ\rangle -1 \gtrsim 1$, whe

Yang Hu, Vladyslav Turlo, Irene J. Beyerlein, Subhash Mahajan

High-throughput atomistic simulations reveal the unique effect of solute atoms on twin variant selection in Mg-Al alloys. Twin embryos first undergo a stochastic incubation stage when embryos choose which twin variant to adopt, and then a deterministic growth stage when embryos expand without changing the selected twin variant. An increase in Al composition

Keneth Adrian Dagal

This paper attempts to prove the Sylvester&#39;s conjecture using Egyptian Fractions with two key ingredients. First, creating a set of operators that completely generates all possible Egyptian fraction of 1. And second, to detect patterns in every operator that surely will generate a new number which are relatively prime to all that came before.

Jishan Shaikh, Adya Sharma, Ankit Chouhan, Avinash Mahawar

Deep learning network training is usually computationally expensive and intuitively complex. We present a novel network architecture for custom training and weight evaluations. We reformulate the layers as ResNet-similar blocks with certain inputs and outputs of their own, the blocks (called Alpha blocks) on their connection configuration form their own netw

Han Zhang, Jialin Liu, Xin Yao

The reliable facility location problem (RFLP) is an important research topic of operational research and plays a vital role in the decision-making and management of modern supply chain and logistics. Through solving RFLP, the decision-maker can obtain reliable location decisions under the risk of facilities&#39; disruptions or failures. In this paper, we pro

Hykel Hosni, Angelo Vulpiani

Datacentric enthusiasm is growing strong across a variety of domains. Whilst data science asks unquestionably exciting scientific questions, we argue that its contributions should not be extrapolated from the scientific context in which they originate. In particular we suggest that the simple-minded idea to the effect that data can be seen as a replacement f

K. R. Chowdhary

This paper attempts to connects the evolution of computer languages with the evolution of life, where the later has been dictated by \emph{theory of evolution of species}, and tries to give supportive evidence that the new languages are more robust than the previous, carry-over the mixed features of older languages, such that strong features gets added into

Tamas Foldi, Chris von Csefalvay, Nicolas A. Perez

The new barrier mode in Apache Spark allows embedding distributed deep learning training as a Spark stage to simplify the distributed training workflow. In Spark, a task in a stage does not depend on any other tasks in the same stage, and hence it can be scheduled independently. However, several algorithms require more sophisticated inter-task communications

Bui Ngoc Muoi, Ngai-Ching Wong

Let LUC$(S)$ be the space of left uniformly continuous functions on a semitopological semigroup $S$. Suppose that $S$ is right reversible and $\operatorname{LUC}(S)$ has a left invariant mean. Let $(X,d)$ be a Fréchet space. Let $τ$ be a locally convex topology of $X$ weaker than the $d$-topology such that the metric $d$ is $τ$-lower semicontinuous. Let $K$

Amandeep Singh Bhatia, Mandeep Kaur Saggi, Shenggen Zheng, Soumya Ranjan Nayak

Motivated by particle swarm optimization (PSO) and quantum computing theory, we have presented a quantum variant of PSO (QPSO) mutated with Cauchy operator and natural selection mechanism (QPSO-CD) from evolutionary computations. The performance of proposed hybrid quantum-behaved particle swarm optimization with Cauchy distribution (QPSO-CD) is investigated

Wei Wang, Gangqiang Hu, Bo Yuan, Shandong Ye

Type 2 diabetes (T2DM), one of the most prevalent chronic diseases, affects the glucose metabolism of the human body, which decreases the quantity of life and brings a heavy burden on social medical care. Patients with T2DM are more likely to suffer bone fragility fracture as diabetes affects bone mineral density (BMD). However, the discovery of the determin

Rishabh Iyer, Jeff Bilmes

Submodular Functions are a special class of set functions, which generalize several information-theoretic quantities such as entropy and mutual information [1]. Submodular functions have subgradients and subdifferentials [2] and admit polynomial-time algorithms for minimization, both of which are fundamental characteristics of convex functions. Submodular fu

W. Randolph Franklin, Salles Viana Gomes de Magalhães, Wenli Li

This paper presents a system that sites (finds optimal locations for) thousands of radio transmitter towers on terrains of up to two billion elevation posts. Applications include cellphone towers, camera systems, or even mitigating environmental visual nuisances. The transmitters and receivers may be situated above the terrain. The system has been paralleliz

V. S. Koroliuk, D. Koroliouk

This article proposes a new filtering model for stationary Gaussian Markov statistical experiments, given by diffusion-type difference stochastic equations.

Michael Mitzenmacher

Motivated by recent work on scheduling with predicted job sizes, we consider the performance of scheduling algorithms with minimal advice, namely a single bit. Besides demonstrating the power of very limited advice, such schemes are quite natural. In the prediction setting, one bit of advice can be used to model a simple prediction as to whether a job is &#3

Ruohong Li, Maryam Mostamand, Jekabs Romans, Jens Lassen

Using TRIUMF&#39;s off-line laser ion source test stand with a system of tunable titanium sapphire lasers, the polarization dependence of laser resonance ionization has been investigated using beryllium. A significant polarization dependence was observed for the excitation path $^1$S$_0$$\rightarrow$$^1$P$^{\circ}_1$$\rightarrow$$^1$S$_0$, which are typical

Ritobrato Datta, Micky K. Bacchus, Dushyant Kumar, Mark A. Elliott

Purpose: Thalamic nuclei are largely invisible in conventional MRI due to poor contrast. Thalamus Optimized Multi-Atlas Segmentation (THOMAS) provides automatic segmentation of 12 thalamic nuclei using white-matter-nulled (WMn) MPRAGE sequence at 7T. Application of THOMAS to Magnetization Prepared 2 Rapid Gradient Echo (MP2RAGE) sequence acquired at 7T has b

Maximilian Kraus, Seyed Majid Azimi, Emec Ercelik, Reza Bahmanyar

Multi-pedestrian tracking in aerial imagery has several applications such as large-scale event monitoring, disaster management, search-and-rescue missions, and as input into predictive crowd dynamic models. Due to the challenges such as the large number and the tiny size of the pedestrians (e.g., 4 x 4 pixels) with their similar appearances as well as differ

R. E. Mennickent, J. Garcés, G. Djurašević, P. Iwanek

The subtype of hot algol semidetached binaries dubbed Double Periodic Variables (DPVs) are characterized by a photometric cycle longer than the orbital one, whose nature has been related to a magnetic dynamo in the donor component controlling the mass transfer rate. We aim to understand the morphologic changes observed in the light curve of OGLE-BLG-ECL-1575

Bruno Melo, Igor Brandão, B. Pinheiro da Silva, R. B. Rodrigues

The superposition of a Gaussian mode and a Laguerre-Gauss mode with $\ell=0,p\neq0$ generates the so-called bottle beam: a dark focus surrounded by a bright region. In this paper, we theoretically explore the use of bottle beams as an optical trap for dielectric spheres with a refractive index smaller than that of their surrounding medium. The forces acting

Zi-Yi Dou, Sachin Kumar, Yulia Tsvetkov

Cross-lingual text summarization aims at generating a document summary in one language given input in another language. It is a practically important but under-explored task, primarily due to the dearth of available data. Existing methods resort to machine translation to synthesize training data, but such pipeline approaches suffer from error propagation. In

Martin Burger

The aim of this paper is to study the derivation of appropriate meso- and macroscopic models for interactions as appearing in social processes. There are two main characteristics the models take into account, namely a network structure of interactions, which we treat by an appropriate mesoscopic description, and a different role of interacting agents. The la

Pietro Faccioli, Carlos Lourenço, Thomas Madlener

While the prompt J/$ψ$ cross section and polarization have been measured with good precision as a function of transverse momentum, $p_{\rm T}$, those of the directly produced J/$ψ$ are practically unknown, given that the cross sections and polarizations of the $χ_{c1}$ and $χ_{c2}$ mesons, large indirect contributors to J/$ψ$ production, are only known with

Mohamed I. Nouh, Yosry A. Azzam, Emad A. -B. Abdel-Salam

Lane-Emden differential equations describe different physical and astrophysical phenomena that include forms of stellar structure, isothermal gas spheres, gas spherical cloud thermal history, and thermionic currents. This paper presents a computational approach to solve the problems related to fractional Lane-Emden differential equations based on neural netw