October 2020 arXiv papers — page 85

Mohandas Pillai

We consider the 1-equivariant energy critical wave maps problem with two-sphere target. Using a method based on matched asymptotic expansions, we construct infinite time relaxation, blow-up, and intermediate types of solutions that have topological degree one. More precisely, for a symbol class of admissible, time-dependent length scales, we construct soluti

Ashley Armbruster, Grace Barger, Sofya Bykova, Tyler Dvorachek

In this paper, we investigate the existence of Sierpi\'{n}ski numbers and Riesel numbers as binomial coefficients. We show that for any odd positive integer $r$, there exist infinitely many Sierpi\'{n}ski numbers and Riesel numbers of the form $\binom{k}{r}$. Let $S(x)$ be the number of positive integers $r$ satisfying $1\leq r\leq x$ for which $\binom{k}{r}

Sebastian M. Dawid, Adam P. Szczepaniak

We consider a model of relativistic three-body scattering with a bound state in the two-body sub-channel. We show that the naïve K-matrix type parametrization, here referred to as the B-matrix, has nonphysical singularities near the physical region. We show how to eliminate such singularities by using dispersion relations and also show how to reproduce unita

Suman K. Bera, Noujan Pashanasangi, C. Seshadhri

Counting homomorphisms of a constant sized pattern graph $H$ in an input graph $G$ is a fundamental computational problem. There is a rich history of studying the complexity of this problem, under various constraints on the input $G$ and the pattern $H$. Given the significance of this problem and the large sizes of modern inputs, we investigate when near-lin

Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo

We develop a nonparametric extension of the sequential generalized likelihood ratio (GLR) test and corresponding time-uniform confidence sequences for the mean of a univariate distribution. By utilizing a geometric interpretation of the GLR statistic, we derive a simple analytic upper bound on the probability that it exceeds any prespecified boundary; these

D. Martínez-Tibaduiza, L. Pires, C. Farina

In this work, we provide an answer to the question: how sudden or adiabatic is a change in the frequency of a quantum harmonic oscillator (HO)? To do this, we investigate the behavior of a HO, initially in its fundamental state, by making a frequency transition that we can control how fast it occurs. The resulting state of the system is shown to be a vacuum

François Bienvenu, Gabriel Cardona, Celine Scornavacca

Measures of phylogenetic balance, such as the Colless and Sackin indices, play an important role in phylogenetics. Unfortunately, these indices are specifically designed for phylogenetic trees, and do not extend naturally to phylogenetic networks (which are increasingly used to describe reticulate evolution). This led us to consider a lesser-known balance in

A. Grekov, A. Zotov

Using the intertwining matrix of the IRF-Vertex correspondence we propose a determinant representation for the generating function of the commuting Hamiltonians of the double elliptic integrable system. More precisely, it is a ratio of the normally ordered determinants, which turns into a single determinant in the classical case. With its help we reproduce t

Vincent Delecroix, Elise Goujard, Peter Zograf, Anton Zorich

We express the Masur-Veech volume and the area Siegel-Veech constant of the moduli space $\mathcal{Q}_{g,n}$ of genus $g$ meromorphic quadratic differentials with $n$ simple poles as polynomials in the intersection numbers of $ψ$-classes with explicit rational coefficients. The formulae obtained in this article result from lattice point counts involving the

Volodymyr P. Shchedryk

We describe the explicit form of a left greatest common divisor and a least common multiple of solutions of a solvable linear matrix equation over a commutative elementary divisor domain. We prove that these left greatest common divisor and least common multiple are also solutions of the same equation.

Dawie B. Janse van Rensburg, Madelein van Straaten, Frieda Theron, Carsten Trunk

Roots of matrices are well-studied. The conditions for their existence are understood: The block sizes of nilpotent Jordan blocks, arranged in pairs, have to satisfy some simple algebraic property. More interesting are structured roots of structured matrices. Probably the best known example is the existence and uniqueness of positive definite square roots of

Zang Guo, Roghayeh Barmaki

Automatic assessment and evaluation of team performance during collaborative tasks is key to the learning analytics and computer-supported cooperative work research. There is a growing interest in the use of gaze-oriented cues for evaluating the collaboration and cooperativeness of teams. However, collecting gaze data using eye-trackers is not always feasibl

Sagar Dasgupta, Mizanur Rahman, Mhafuzul Islam, Mashrur Chowdhury

Global Navigation Satellite System (GNSS) provides Positioning, Navigation, and Timing (PNT) services for autonomous vehicles (AVs) using satellites and radio communications. Due to the lack of encryption, open-access of the coarse acquisition (C/A) codes, and low strength of the signal, GNSS is vulnerable to spoofing attacks compromising the navigational ca

Xin He, Y. Liu, P. Beckett, H. Uddin

A CMY colour camera differs from its RGB counterpart in that it employs a subtractive colour space of cyan, magenta and yellow. CMY cameras tend to performs better than RGB cameras in low light conditions due to their much higher transmittance. However, conventional CMY colour filter technology made of pigments and dyes are limited in performance for the nex

Shudeng Wu, Tao Dai, Shu-Tao Xia

Recently, deep neural networks (DNNs) have been widely and successfully used in Object Detection, e.g. Faster RCNN, YOLO, CenterNet. However, recent studies have shown that DNNs are vulnerable to adversarial attacks. Adversarial attacks against object detection can be divided into two categories, whole-pixel attacks and patch attacks. While these attacks add

Kristoffer Wickstrøm, Karl Øyvind Mikalsen, Michael Kampffmeyer, Arthur Revhaug

Deep learning-based support systems have demonstrated encouraging results in numerous clinical applications involving the processing of time series data. While such systems often are very accurate, they have no inherent mechanism for explaining what influenced the predictions, which is critical for clinical tasks. However, existing explainability techniques

Uğur Mertoğlu, Burkay Genç

With the digitization of media, an immense amount of news data has been generated by online sources, including mainstream media outlets as well as social networks. However, the ease of production and distribution resulted in circulation of fake news as well as credible, authentic news. The pervasive dissemination of fake news has extreme negative impacts on

Christos Liaskos, Shuai Niez, Ageliki Tsioliaridou, Andreas Pitsillides

Intelligent surfaces exert deterministic control over the wireless propagation phenomenon, enabling novel capabilities in performance, security and wireless power transfer. Such surfaces come in the form of rectangular tiles that cascade to cover large surfaces such as walls, ceilings or building facades. Each tile is addressable and can receive software com

Semen Bronza, Valentina Tairova

Riemann surfaces which are set by algebraic, algebroid and inverse functions are considered. A method for describing these Riemann surfaces by graphs is proposed. Each such Riemann surface is assigned to a special type of graph - profile. In terms of graph theory, the necessary and sufficient conditions of profile existence are clarified. The conditions of a

Matthew Rosenzweig

We consider first-order conservative systems of particles with binary Coulomb interactions in the mean-field scaling regime in dimensions $d\geq 3$. We show that if at some time, the associated sequence of empirical measures converges in a suitable sense to a probability measure with bounded density $ω^0$ as the number of particles $N\rightarrow\infty$, then

Matthew Roughan

The polylogarithm function is one of the constellation of important mathematical functions. It has a long history, and many connections to other special functions and series, and many applications, for instance in statistical physics. However, the practical aspects of its numerical evaluation have not received the type of comprehensive treatments lavished on

Marwin Schindler, Hsiang-Yun Wu, Renata Georgia Raidou

Physical visualizations (i.e., data representations by means of physical objects) have been used for many centuries in medical and anatomical education. Recently, 3D printing techniques started also to emerge. Still, other medical physicalizations that rely on affordable and easy-to-find materials are limited, while smart strategies that take advantage of th

Y. Kenedy Meitei, T. Ibungochouba Singh, I. Ablu Meitei

In this paper, the modified Hawking temperature of a static Riemann space-time is studied using the generalized Klein-Gordon equation and the generalized Dirac equation. Applying the Kerner-Mann quantum tunneling method, the modified Hawking temperature for scalar particle and fermions that crosses the event horizon of the black hole have been derived. We ob

F. Pecora, S. Servidio, A. Greco, W. H. Matthaeus

Plasma turbulence can be viewed as a magnetic landscape populated by large and small scale coherent structures. In this complex network, large helical magnetic tubes might be separated by small scale magnetic reconnection events (current sheets). However, the identification of these magnetic structures in a continuous stream of data has always been a challen

Ziqi Liu

In this paper, the author introduces hyperfields and give some facts about the roots and multiplicities of polynomials over hyperfield based on \cite{2} and \cite{3}. Then he tests the sharpness of an inequality in Baker's former work \cite{2} about the behavior of multiplicities under homomorphisms between hyperfields and show that the inequality is not

Manuel E. Rodrigues, Marcos V. de S. Silva, Andrew S. de Siqueira

In this work, new solutions for regular black holes that have multihorizons are proposed. These are formed by the direct product of solutions already published in the literature, which are described through the coupling of gravity with nonlinear electrodynamics. We analyze the regularity of the spacetime, the electric field, and the energy conditions of each

Dorien Herremans, Tom Bergmans

Billions of USD are invested in new artists and songs by the music industry every year. This research provides a new strategy for assessing the hit potential of songs, which can help record companies support their investment decisions. A number of models were developed that use both audio data, and a novel feature based on social media listening behaviour. T

Abraham Woubie, Pablo Pérez Zarazaga, Tom Bäckström

The COVID-19 outbreak disrupted different organizations, employees and students, who turned to teleconference applications to collaborate and socialize even during the quarantine. Thus, the demand of teleconferencing applications surged with mobile application downloads reaching the highest number ever seen. However, some of the teleconference applications r

Noriyuki Tonami, Keisuke Imoto, Ryosuke Yamanishi, Yoichi Yamashita

Sound event detection (SED) and acoustic scene classification (ASC) are important research topics in environmental sound analysis. Many research groups have addressed SED and ASC using neural-network-based methods, such as the convolutional neural network (CNN), recurrent neural network (RNN), and convolutional recurrent neural network (CRNN). The convention

Jiangnan Li, Yingyuan Yang, Jinyuan Stella Sun

Effective detection of energy theft can prevent revenue losses of utility companies and is also important for smart grid security. In recent years, enabled by the massive fine-grained smart meter data, deep learning (DL) approaches are becoming popular in the literature to detect energy theft in the advanced metering infrastructure (AMI). However, as neural

Fintan Costello, Paul Watts

Null Hypothesis Significance Testing (NHST) has long been of central importance to psychology as a science, guiding theory development and underlying the application of evidence-based intervention and decision-making. Recent years, however, have seen growing awareness of serious problems with NHST as it is typically used; this awareness has led to proposals

Yanru Qu, Dinghan Shen, Yelong Shen, Sandra Sajeev

Data augmentation has been demonstrated as an effective strategy for improving model generalization and data efficiency. However, due to the discrete nature of natural language, designing label-preserving transformations for text data tends to be more challenging. In this paper, we propose a novel data augmentation framework dubbed CoDA, which synthesizes di

Jaya Maithil, Jessie C. Runnoe, Michael S. Brotherton, John F. Wardle

Radio core dominance measurements, an indicator of jet orientation, sometimes rely on core flux density measurements from large-area surveys like Faint Images of the Radio Sky at Twenty cm (FIRST) that have an angular resolution of only 5''. Such low-resolution surveys often fail to resolve cores from the extended emission resulting in an erroneous m

Hao Luan, Alan Gatherer

Manycore SoC architectures based on on-chip shared memory are preferred for flexible and programmable solutions in many application domains. However, the development of many ported memory is becoming increasingly challenging as we approach the end of Moore's Law while systems requirements demand larger shared memory and more access ports. Memory can no l

King Lun Ng, Bogdan Opanchuk, Manushan Thenabadu, Margaret Reid

Despite being at the heart of the theory of the "Big Bang" and cosmic inflation, the quantum field theory prediction of false vacuum tunneling has not been tested. To address the exponential complexity of the problem, a table-top quantum simulator in the form of an engineered Bose-Einstein condensate (BEC) has been proposed to give dynamical solution

Shraddha Barke, Hila Peleg, Nadia Polikarpova

A key challenge in program synthesis is the astronomical size of the search space the synthesizer has to explore. In response to this challenge, recent work proposed to guide synthesis using learned probabilistic models. Obtaining such a model, however, might be infeasible for a problem domain where no high-quality training data is available. In this work we

Jeffrey A. Ivie, Nathan D. Bamberger, Keshaba N. Parida, Stuart Shepard

The rational design of single molecule electrical components requires a deep and predictive understanding of structure-function relationships. Here we explore the relationship between chemical substituents and the conductance of metal-single molecule-metal junctions, using functionalized oligophenylenevinylenes as a model system. Using a combination of mecha

Robin Richter, Duy H. Thai, Stephan F. Huckemann

In image processing, classical methods minimize a suitable functional that balances between computational feasibility (convexity of the functional is ideal) and suitable penalties reflecting the desired image decomposition. The fact that algorithms derived from such minimization problems can be used to construct (deep) learning architectures has spurred the

Faisal Nsour, Hiroki Sayama

Under preferential attachment (PA) network growth models late arrivals are at a disadvantage with regard to their final degrees. Previous extensions of PA have addressed this deficiency by either adding the notion of node fitness to PA, usually drawn from some fitness score distributions, or by using fitness alone to control attachment. Here we introduce a n

Peizheng Li, Han Cui, Aftab Khan, Usman Raza

This paper studies the indoor localisation of WiFi devices based on a commodity chipset and standard channel sounding. First, we present a novel shallow neural network (SNN) in which features are extracted from the channel state information (CSI) corresponding to WiFi subcarriers received on different antennas and used to train the model. The single-layer ar

Hossein A. Kafiabad, Jacques Vanneste, William R. Young

Anticyclonic vortices focus and trap near-inertial waves so that near-inertial energy levels are elevated within the vortex core. Some aspects of this process, including the nonlinear modification of the vortex by the wave, are explained by the existence of trapped near-inertial eigenmodes. These vortex eigenmodes are easily excited by an initial wave with h

A. E. Thelen, M. A. Cordiner, C. A. Nixon, V. Vuitton

Titan harbors a dense, organic-rich atmosphere primarily composed of N$_2$ and CH$_4$, with lesser amounts of hydrocarbons and nitrogen-bearing species. As a result of high sensitivity observations by the Atacama Large Millimeter/submillimeter Array (ALMA) in Band 6 ($\sim$230-272 GHz), we obtained the first spectroscopic detection of CH$_3$C$_3$N (methylcya

Jian Ni, Taesun Moon, Parul Awasthy, Radu Florian

Relation extraction (RE) is one of the most important tasks in information extraction, as it provides essential information for many NLP applications. In this paper, we propose a cross-lingual RE approach that does not require any human annotation in a target language or any cross-lingual resources. Building upon unsupervised cross-lingual representation lea

Tianyu Ma, Hang Zhang, Hanley Ong, Amar Vora

Segmentation of anatomical regions of interest such as vessels or small lesions in medical images is still a difficult problem that is often tackled with manual input by an expert. One of the major challenges for this task is that the appearance of foreground (positive) regions can be similar to background (negative) regions. As a result, many automatic segm

Adriana L. Duncan, Simran Khunger, Holly Swisher, Ryan Tamura

Integer partitions have long been of interest to number theorists, perhaps most notably Ramanujan, and are related to many areas of mathematics including combinatorics, modular forms, representation theory, analysis, and mathematical physics. Here, we focus on partitions with gap conditions and partitions with parts coming from fixed residue classes. Let $Δ_

Xiangwei Shi, Seyran Khademi, Yunqiang Li, Jan van Gemert

Current weakly supervised object localization and segmentation rely on class-discriminative visualization techniques to generate pseudo-labels for pixel-level training. Such visualization methods, including class activation mapping (CAM) and Grad-CAM, use only the deepest, lowest resolution convolutional layer, missing all information in intermediate layers.

E. S. Morchenko

It is argued that not only the blue (at the brightness maximum) but also the red (in the slow decay phase) components of the optical continuum of powerful flares on dMe stars are formed near the photosphere. The possible appearance of HeI lines in the relaxation zones for the plasma to a state of thermal equilibrium (as a result of a rise in electron tempera

Tejas Srinivasan, Ramon Sanabria, Florian Metze, Desmond Elliott

Visual context has been shown to be useful for automatic speech recognition (ASR) systems when the speech signal is noisy or corrupted. Previous work, however, has only demonstrated the utility of visual context in an unrealistic setting, where a fixed set of words are systematically masked in the audio. In this paper, we simulate a more realistic masking sc

Simon Arberet, Xiao Chen, Boris Mailhe, Peter Speier

Magnetic Resonance Fingerprinting (MRF) reconstructs tissue maps based on a sequence of very highly undersampled images. In order to be able to perform MRF reconstruction, state-of-the-art MRF methods rely on priors such as the MR physics (Bloch equations) and might also use some additional low-rank or spatial regularization. However to our knowledge these t

L. Sabin, M. A. Guerrero, S. Zavala, J. A. Toalá

We present a detailed analysis of the new planetary nebula (PN) IPHASX J193718.6+202102 using deep imaging and intermediate- and high resolution spectroscopy that are interpreted through morpho-kinematic and photoionisation modelling. The physical structure of the nebula consists of a fragmented torus and an extremely faint orthogonal bipolar outflow, contra

Andrei Constantinescu, Edith Elkind

We study the complexity of determining a winning committee under the Chamberlin--Courant voting rule when voters' preferences are single-crossing on a line, or, more generally, on a median graph (this class of graphs includes, e.g., trees and grids). For the line, Skowron et al. (2015) describe an $O(n^2mk)$ algorithm (where $n$, $m$, $k$ are the number

P. Menegasso, J. C. Souza, I. Vinograd, Z. Wang

The transferred hyperfine interaction between nuclear and electron spins in an heavy fermion material depends on the hybridization between the $f$-electron orbitals and those surrounding a distant nucleus. In CeMIn$_5$ (M=Rh, Ir, Co), both the hyperfine coupling to the two indium sites as well as the crystalline electric field at the Ce are strongly dependen

Battulga Munkhbat, Adriana Canales, Betul Kucukoz, Denis G. Baranov

Hybrid light-matter states, polaritons, are one of the central concepts in modern quantum optics and condensed matter physics. Polaritons emerge as a result of strong interaction between an optical mode and a material resonance, which is frequently realized in molecular, van der Waals, or solid-state platforms (1-7). However, this route requires accurate (na

Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan

We propose a simple extension of top-down decision tree learning heuristics such as ID3, C4.5, and CART. Our algorithm achieves provable guarantees for all target functions $f: \{-1,1\}^n \to \{-1,1\}$ with respect to the uniform distribution, circumventing impossibility results showing that existing heuristics fare poorly even for simple target functions. T

Warren B. Kindzierski, S. Stanley Young, Terry G. Meyer, John D. Dunn

False-positive results and bias may be common features of the biomedical literature today, including risk factor-chronic disease research. A study was undertaken to assess the reliability of base studies used in a meta-analysis examining whether carbon monoxide, particulate matter 10 and 2.5 micro molar, sulfur dioxide, nitrogen dioxide and ozone are risk fa

Daniel Chen, Yekun Xu, Betis Baheri, Chuan Bi

This paper presents a sublinear classical algorithm for principal component regression. The algorithm uses quantum-inspired linear algebra, an idea developed by Tang. Using this technique, her algorithm for recommendation systems achieved runtime only polynomially slower than its quantum counterpart. Her work was quickly adapted to solve many other problems

Manfred K. Warmuth, Wojciech Kotłowski, Ehsan Amid

It was conjectured that any neural network of any structure and arbitrary differentiable transfer functions at the nodes cannot learn the following problem sample efficiently when trained with gradient descent: The instances are the rows of a $d$-dimensional Hadamard matrix and the target is one of the features, i.e. very sparse. We essentially prove this co

Yunheng Han, Hanan Samet

Trajectories represent the mobility of moving objects and thus is of great value in data mining applications. However, trajectory data is enormous in volume, so it is expensive to store and process the raw data directly. Trajectories are also redundant so data compression techniques can be applied. In this paper, we propose effective algorithms to simplify t

Jingfan Meng, Long Gong, Jun, Xu

In this work, we first propose a parallel batch switching algorithm called Small-Batch Queue-Proportional Sampling (SB-QPS). Compared to other batch switching algorithms, SB-QPS significantly reduces the batch size without sacrificing the throughput performance and hence has much lower delay when traffic load is light to moderate. It also achieves the lowest

Allison Hegel, Sudha Rao, Asli Celikyilmaz, Bill Dolan

Existing language models excel at writing from scratch, but many real-world scenarios require rewriting an existing document to fit a set of constraints. Although sentence-level rewriting has been fairly well-studied, little work has addressed the challenge of rewriting an entire document coherently. In this work, we introduce the task of document-level targ

Emma K. Dahl, Shawn Brueshaber, Richard Cosentino, Csaba Palotai

This white paper, written in support of NASA's 2023-2032 Planetary Decadal Survey, outlines 10 major questions that focus on the origin, evolution, and current processes that shape the atmospheres of Uranus and Neptune. Prioritizing these questions over the next decade will greatly improve our understanding of this unique class of planets, which have rem

E. I. Khukhro, P. Shumyatsky

A left Engel sink of an element $g$ of a group $G$ is a set ${\mathscr E}(g)$ such that for every $x\in G$ all sufficiently long commutators $[...[[x,g],g],\dots ,g]$ belong to ${\mathscr E}(g)$. (Thus, $g$ is a left Engel element precisely when we can choose ${\mathscr E}(g)=\{ 1\}$.) We prove that if a finite group $G$ admits an automorphism $φ$ of prime o

Zhilong Chen, Hancheng Cao, Fengli Xu, Mengjie Cheng

Social e-commerce, as a new form of social computing based marketing platforms, utilizes existing real-world social relationships for promotions and sales of products. It has been growing rapidly in recent years and attracted tens of millions of users in China. A key group of actors who enable market transactions on these platforms are intermediaries who con

Mohit Sewak, Sanjay K. Sahay, Hemant Rathore

We designed and developed DOOM (Adversarial-DRL based Opcode level Obfuscator to generate Metamorphic malware), a novel system that uses adversarial deep reinforcement learning to obfuscate malware at the op-code level for the enhancement of IDS. The ultimate goal of DOOM is not to give a potent weapon in the hands of cyber-attackers, but to create defensive

Mohit Sewak, Sanjay K. Sahay, Hemant Rathore

The Intent in Android plays an important role in inter-process and intra-process communications. The implicit Intent that an application could accept are declared in its manifest and are amongst the easiest feature to extract from an apk. Implicit Intents could even be extracted online and in real-time. So far neither the feasibility of developing an Intrusi

Yiding Hao

Interpretability methods for neural networks are difficult to evaluate because we do not understand the black-box models typically used to test them. This paper proposes a framework in which interpretability methods are evaluated using manually constructed networks, which we call white-box networks, whose behavior is understood a priori. We evaluate five met

Kylen Solvik, Anne M. Bartuszevige, Meghan Bogaerts, Maxwell B. Joseph

In the Great Plains, playas are critical wetland habitats for migratory birds and a source of recharge for the agriculturally-important High Plains aquifer. The temporary wetlands exhibit complex hydrology, filling rapidly via local rain storms and then drying through evaporation and groundwater infiltration. Using a long short-term memory (LSTM) neural netw

Feng Zhang, Ruite Guo, Honggao Cao

Information coefficient (IC) is a widely used metric for measuring investment managers' skills in selecting stocks. However, its adequacy and effectiveness for evaluating stock selection models has not been clearly understood, as IC from a realistic stock selection model can hardly be materially different from zero and is often accompanies with high vola

M. Massi, M. Chernyakova, A. Kraus, D. Malyshev

The stellar binary system LS I +61303, composed of a compact object in an eccentric orbit around a B0 Ve star, emits from radio up to gamma-ray energies. The orbital modulation of radio spectral index, X-ray, and GeV gamma-ray data suggests the presence of two peaks. This two-peaked profile is in line with the accretion theory predicting two accretion-ejecti

R. J. Bueno Rogerio, J. M. Hoff da Silva, C. H. Coronado Villalobos

Bearing in mind the Lounesto spinor classification, we connect the expansion coefficients of well behaved fermionic quantum field, i.e., a local field within a full Lorentz covariant theory, with and only with a given subclass of Type-2 spinors according to Lounesto. We comment on theoretical possibilities as well as physical outputs for the other cases.

Nathalie Majcherczyk, Nishan Srishankar, Carlo Pinciroli

In this paper, we show how the Federated Learning (FL) framework enables learning collectively from distributed data in connected robot teams. This framework typically works with clients collecting data locally, updating neural network weights of their model, and sending updates to a server for aggregation into a global model. We explore the design space of

Suraj Kothawade, Jiten Girdhar, Chandrashekhar Lavania, Rishabh Iyer

Deep Models are increasingly becoming prevalent in summarization problems (e.g. document, video and images) due to their ability to learn complex feature interactions and representations. However, they do not model characteristics such as diversity, representation, and coverage, which are also very important for summarization tasks. On the other hand, submod

Jeff Kahn, Bhargav Narayanan, Jinyoung Park

Resolving a conjecture of Kühn and Osthus from 2012, we show that $p= 1/\sqrt{n}$ is the threshold for the random graph $G_{n,p}$ to contain the square of a Hamilton cycle.

Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar

Information representation as tables are compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used, however industry still faces challenge in detecting and extracting tables from OCR documents or images. This paper proposes an algorithm that detects and

Bitao Wang, Michele Cappellari, Yingjie Peng

In the $(λ_{\rm R}, \varepsilon)$ and $(V/σ, \varepsilon)$ diagrams for characterizing dynamical states, the fast-rotator galaxies (both early-type and spirals) are distributed within a well-defined leaf-shaped envelope. This was explained as due to an upper limit to the orbital anisotropy increasing with galaxy intrinsic flattening. However, a physical expl

Neelima, Sani Biswas, Chaman Kumar, Gonçalo dos Reis

We prove the well-posedness of solutions to McKean-Vlasov stochastic differential equations driven by Lévy noise under mild assumptions where, in particular, the Lévy measure is not required to be finite. The drift, diffusion and jump coefficients are allowed to be random, can grow super-linearly in the state variable, and all may depend on the marginal law

Eric K. Tokuda, Henrique F. de Arruda, Cesar H. Comin, Roberto M. Cesar-Jr.

Despite the great differences among cities, they face similar challenges regarding social inequality, politics and criminality. Urban art express these feelings from the citizen point-of-view. In particular, the drawing and painting of public surfaces may carry rich information about the time and region it was made. Existing studies have explored the spatial

Riccardo Balin, Kenneth E. Jansen

The turbulent boundary layer over a Gaussian shaped bump is computed by direct numerical simulation (DNS) of the incompressible Navier-Stokes equations. The two-dimensional bump causes a series of strong pressure gradients alternating in rapid succession. At the inflow, the momentum thickness Reynolds number is approximately 1,000 and the boundary layer thic

John O'Leary, Guanyang Wang, Pierre E. Jacob

Couplings play a central role in the analysis of Markov chain Monte Carlo algorithms and appear increasingly often in the algorithms themselves, e.g. in convergence diagnostics, parallelization, and variance reduction techniques. Existing couplings of the Metropolis-Hastings algorithm handle the proposal and acceptance steps separately and fall short of the

Rahul Mishra, Dhruv Gupta, Markus Leippold

We present SUMO, a neural attention-based approach that learns to establish the correctness of textual claims based on evidence in the form of text documents (e.g., news articles or Web documents). SUMO further generates an extractive summary by presenting a diversified set of sentences from the documents that explain its decision on the correctness of the t

Paul Y. Wang, Sandalika Sapra, Vivek Kurien George, Gabriel A. Silva

Although a number of studies have explored deep learning in neuroscience, the application of these algorithms to neural systems on a microscopic scale, i.e. parameters relevant to lower scales of organization, remains relatively novel. Motivated by advances in whole-brain imaging, we examined the performance of deep learning models on microscopic neural dyna

Clifford Cheung, Nabha Shah, Mikhail P. Solon

The geodesic equation encodes test-particle dynamics at arbitrary gravitational coupling, hence retaining all orders in the post-Minkowskian (PM) expansion. Here we explore what geodesic motion can tell us about dynamical scattering in the presence of perturbatively small effects such as tidal distortion and higher derivative corrections to general relativit

Mark D. Smith, Martin Bureau, Timothy A. Davis, Michele Cappellari

Empirical correlations between the masses of supermassive black holes (SMBHs) and properties of their host galaxies are well-established. Among these is the correlation with the flat rotation velocity of each galaxy measured either at a large radius in its rotation curve or via a spatially-integrated emission line width. We propose here the use of the de-pro

N. P. Ong, Sihang Liang

We provide a review of recent experimental results on the chiral anomaly in Dirac/Weyl semimetals. After a brief introduction, we trace the steps leading to the prediction of materials that feature protected 3D bulk Dirac nodes. The chiral anomaly is presented in terms of charge pumping between the chiral Landau levels of Weyl fermions in parallel electric a

Chris Karwin, Simona Murgia, Igor Moskalenko, Sean Fillingham

An excess $γ$-ray signal toward the outer halo of M31 has recently been reported. Although other explanations are plausible, the possibility that it arises from dark matter (DM) is valid. In this work we interpret the excess in the framework of DM annihilation, using as our representative case WIMP DM annihilating to bottom quarks, and we perform a detailed

Kun Ting Eddie Chua, Karia Dibert, Mark Vogelsberger, Jesús Zavala

We study the effects of inelastic dark matter self-interactions on the internal structure of a simulated Milky Way (MW)-size halo. Self-interacting dark matter (SIDM) is an alternative to collisionless cold dark matter (CDM) which offers a unique solution to the problems encountered with CDM on sub-galactic scales. Although previous SIDM simulations have mai

Changha Choi, Márk Mezei, Gábor Sárosi

Pole skipping is a recently discovered subtle effect in the thermal energy density retarded two point function at a special point in the complex $(ω,p)$ planes. We propose that pole skipping is determined by the stress tensor contribution to many-body chaos, and the special point is at $(ω,p)_\text{p.s.}= i λ^{(T)}(1,1/u_B^{(T)})$, where $λ^{(T)}=2π/β$ and $

Samuel E. Gralla

No. All theoretical predictions for the observational appearance of an accreting supermassive black hole, as measured interferometrically by a sparse Earth-sized array at current observation frequencies, are sensitive to many untested assumptions about accretion flow and emission physics. There is no way to distinguish a violation of general relativity (GR)

Dylan Sheldon Rankin, Jeffrey Krupa, Philip Harris, Maria Acosta Flechas

Computing needs for high energy physics are already intensive and are expected to increase drastically in the coming years. In this context, heterogeneous computing, specifically as-a-service computing, has the potential for significant gains over traditional computing models. Although previous studies and packages in the field of heterogeneous computing hav

Sara Frederick, Suvi Gezari, Matthew J. Graham, Jesper Sollerman

The Zwicky Transient Facility (ZTF) has discovered five new events belonging to an emerging class of AGN undergoing smooth flares with large amplitudes and rapid rise times. This sample consists of several transients that were initially classified as supernovae with narrow spectral lines. However, upon closer inspection, all of the host galaxies display reso

Andrei P. Igoshev, Rainer Hollerbach, Toby Wood, Konstantinos N. Gourgouliatos

Magnetars are neutron stars (NSs) with extreme magnetic fields of strength $5 \times 10^{13}$ - $10^{15}$ G. They exhibit transient, highly energetic events, such as short X-ray flashes, bursts and giant flares, all of which are powered by their enormous magnetic energy. Quiescent magnetars have X-ray luminosities between $10^{29}$ and $10^{35}$ erg/s, and a

Florian Loebbert, Julian Miczajka, Dennis Müller, Hagen Münkler

We extend the study of the recently discovered Yangian symmetry of massive Feynman integrals and its relation to massive momentum space conformal symmetry. After proving the symmetry statements in detail at one and two loop orders, we employ the conformal and Yangian constraints to bootstrap various one-loop examples of massive Feynman integrals. In particul

Nikole K. Lewis, Hannah R. Wakeford, Ryan J. MacDonald, Jayesh M. Goyal

For solar-system objects, ultraviolet spectroscopy has been critical in identifying sources for stratospheric heating and measuring the abundances of a variety of hydrocarbon and sulfur-bearing species, produced via photochemical mechanisms, as well as oxygen and ozone. To date, less than 20 exoplanets have been probed in this critical wavelength range (0.2-

Piotr Błaszczyk

In this paper, we provide an interpretation of Book II of the Elements from the perspective of figures which are represented and not represented on the diagrams. We show that Euclid's reliance on figures not represented on the diagram is a proof technique which enables to turn his diagrams II.11--14 into ideograms of a kind. We also discuss interpretatio

Jiarui Li, Robert J. Green, Zhen Zhang, Ronny Sutarto

Oxygen vacancies play a crucial role in the control of the electronic, magnetic, ionic, and transport properties of functional oxide perovskites. Rare earth nickelates (RENiO$_{3-x}$) have emerged over the years as a rich platform to study the interplay between the lattice, the electronic structure, and ordered magnetism. In this study, we investigate the ev

Andrei Tokovinin, Monika Petr-Gotzens, Cesar Briceno

Statistics of low-mass pre-main sequence binaries in the Orion OB1 association with separations ranging from 0.6" to 20" (220 to 7400 au at 370 pc) are studied using images from the VISTA Orion mini-survey and astrometry from Gaia. The input sample based on the CVSO catalog contains 1137 stars of K and M spectral types (masses between 0.3 and 0.9 Msu

Adrian de Wynter

We introduce Mischief, a simple and lightweight method to produce a class of human-readable, realistic adversarial examples for language models. We perform exhaustive experimentations of our algorithm on four transformer-based architectures, across a variety of downstream tasks, as well as under varying concentrations of said examples. Our findings show that

Shigeo Koshitani, Caroline Lassueur, Benjamin Sambale

We classify principal blocks of finite groups with semidihedral defect groups up to splendid Morita equivalence. This completes the classification of all principal $2$-blocks of tame representation type up to splendid Morita equivalence and shows that Puig's Finiteness Conjecture holds for such blocks.

Angie Waller, Kyle Gorman

Student reviews often make reference to professors' physical appearances. Until recently RateMyProfessors.com, the website of this study's focus, used a design feature to encourage a "hot or not" rating of college professors. In the wake of recent #MeToo and #TimesUp movements, social awareness of the inappropriateness of these reviews has gr

Andrew Keyes, Nicky Bayat, Vahid Reza Khazaie, Yalda Mohsenzadeh

Advanced Generative Adversarial Networks (GANs) are remarkable in generating intelligible audio from a random latent vector. In this paper, we examine the task of recovering the latent vector of both synthesized and real audio. Previous works recovered latent vectors of given audio through an auto-encoder inspired technique that trains an encoder network eit