December 2020 arXiv papers — page 148

Xiaoyu Du, Quan Le, Mark Scanlon

Case-hindering, multi-year digital forensic evidence backlogs have become commonplace in law enforcement agencies throughout the world. This is due to an ever-growing number of cases requiring digital forensic investigation coupled with the growing volume of data to be processed per case. Leveraging previously processed digital forensic cases and their compo

Faisal Hussain, Syed Ghazanfar Abbas, Muhammad Husnain, Ubaid Ullah Fayyaz

The network attacks are increasing both in frequency and intensity with the rapid growth of internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of service (DDoS) attacks are reported as the most frequent attacks in IoT networks. The traditional security solutions like firewalls, intrusion detection systems, etc., are un

Adam Hare, Yu Chen, Yinan Liu, Zhenming Liu

Despite the recent successes of deep learning in natural language processing (NLP), there remains widespread usage of and demand for techniques that do not rely on machine learning. The advantage of these techniques is their interpretability and low cost when compared to frequently opaque and expensive machine learning models. Although they may not be be as

Maurício Gruppi, Sibel Adali, Pin-Yu Chen

This paper describes SChME (Semantic Change Detection with Model Ensemble), a method usedin SemEval-2020 Task 1 on unsupervised detection of lexical semantic change. SChME usesa model ensemble combining signals of distributional models (word embeddings) and wordfrequency models where each model casts a vote indicating the probability that a word sufferedsema

Jiechao Guan, Zhiwu Lu, Tao Xiang, Timothy Hospedales

By transferring knowledge learned from seen/previous tasks, meta learning aims to generalize well to unseen/future tasks. Existing meta-learning approaches have shown promising empirical performance on various multiclass classification problems, but few provide theoretical analysis on the classifiers' generalization ability on future tasks. In this paper

Premala Chandra, Piers Coleman, Mucio A. Continentino, Gilbert G. Lonzarich

Experimentally there exist many materials with first-order phase transitions at finite temperature that display quantum criticality. Classically, a strain-energy density coupling is known to drive first-order transitions in compressible systems, and here we generalize this Larkin-Pikin mechanism to the quantum case. We show that if the T=0 system lies above

Anastasios Kakkavas, Mario H. Castañeda García, Gonzalo Seco-Granados, Henk Wymeersch

In the context of positioning a target with a single-anchor, this contribution focuses on the Fisher information about the position, orientation and clock offset of the target provided by single-bounce reflections. The availability of prior knowledge of the target's environment is taken into account via a prior distribution of the position of virtual anc

Michael Franklin Bosu, Stephen G. MacDonell, Peter Whigham

It seems logical to assert that the dynamic nature of software engineering practice would mean that software effort estimation (SEE) modelling should take into account project start and completion dates. That is, we should build models for future projects based only on data from completed projects; and we should prefer data from recent similar projects over

Alexander Hulpke

We survey group-theoretic algorithms for finding (some or all) subgroups of a finite group and discuss the implementation of these algorithms in the computer algebra system GAP

Wei Emma Zhang, Quan Z. Sheng, Adnan Mahmood, Dai Hoang Tran

Since the term first coined in 1999 by Kevin Ashton, the Internet of Things (IoT) has gained significant momentum as a technology to connect physical objects to the Internet and to facilitate machine-to-human and machine-to-machine communications. Over the past two decades, IoT has been an active area of research and development endeavours by many technical

Fernando Quintino

We study the logarithmic capacity of $G_δ$ subsets of the interval $[0,1].$ Let $S$ be of the form \begin{align*} S=\bigcap_m \bigcup_{k\ge m} I_k, \end{align*} where each $I_k$ is an interval in $[0,1]$ with length $l_k$ that decrease to $0$. We provide sufficient conditions for $S$ to have full capacity, i.e. $\mathop{\mathrm{Cap}}(S)=\mathop{\mathrm{Cap}}

Zeyu Ding, Yuxin Wang, Yingtai Xiao, Guanhong Wang

Private selection algorithms, such as the Exponential Mechanism, Noisy Max and Sparse Vector, are used to select items (such as queries with large answers) from a set of candidates, while controlling privacy leakage in the underlying data. Such algorithms serve as building blocks for more complex differentially private algorithms. In this paper we show that

Anastasios Kakkavas, Henk Wymeersch, Gonzalo Seco-Granados, Mario H. Castañeda García

We consider a single-anchor multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system with imperfectly synchronized transmitter (Tx) and receiver (Rx) clocks, where the Rx estimates its position based on the received reference signals. The Tx, having (imperfect) prior knowledge about the Rx location and the surrounding ge

Maria Urlea, Sergey Loyka

The intuitive sphere-packing argument is used to obtain analytically-tractable closed-form approximations for achievable information rates of coded modulation transmission systems, for which only analytically-intractable expressions are available in the literature. These approximations provide a number of insights, possess useful properties and facilitate de

J. L. Gutiérrez Santiago, G. López Castro, P. Roig

We study the $τ^- \to ν_τ π^{-}π^{0}\ell^{+}\ell^{-}$ ($\ell=e,\,μ$) decays, which are $O(α^2)$-suppressed with respect to the dominant di-pion tau decay channel. Both the inner-bremsstrahlung and the structure- (and model-)dependent contributions are considered. In the $\ell=e$ case, structure-dependent effects are $\mathcal{O}(1\%)$ in the decay rate, yiel

MinKeun Chung, Liang Liu, Andreas Johansson, Martin Nilsson

Massive multiple-input multiple-out (MIMO) technology is vital in millimeter-wave (mmWave) bands to obtain large array gains. However, there are practical challenges, such as high hardware cost and power consumption in such systems. A promising solution to these problems is to adopt a hybrid beamforming architecture. This architecture has a much lower number

Jaime Maldonado, Asil Kaan Bozcuoğlu, Christoph Zetzsche

Typical contact detection is based on the monitoring of a threshold value in the force and torque signals. The selection of a threshold is challenging for robots operating in unstructured or highly dynamic environments, such in a household setting, due to the variability of the characteristics of the objects that might be encountered. We propose a multimodal

K. Shiells, P. G. Blunden, W. Melnitchouk

We present a comprehensive analysis of the $γW$ interference radiative correction to the neutron $β$-decay matrix element. Within a dispersion relations approach, we compute the axial-vector part of the $γW$ box amplitude $\Box^{γW}_{A}$ in terms of the isoscalar part of the $F_3^{γW}$ interference structure function. Using the latest available phenomenology

V. Angeles, F. A. Godinez, J. A. Puente-Velazquez, R. Mendez

We conduct experiments with force-free magnetically-driven rigid helical swimmers in Newtonian and viscoelastic (Boger) fluids. By varying the sizes of the swimmer body and its helical tail, we show that the impact of viscoelasticity strongly depends on the swimmer geometry: it can lead to a significant increase of the swimming speed (up to a factor of five)

Venugopal Mani, Ramasubramanian Balasubramanian, Sushant Kumar, Abhinav Mathur

Recommender Systems have become an integral part of online e-Commerce platforms, driving customer engagement and revenue. Most popular recommender systems attempt to learn from users' past engagement data to understand behavioral traits of users and use that to predict future behavior. In this work, we present an approach to use causal inference to learn

Felix Grezes, Zhaoheng Ni, Viet Anh Trinh, Michael Mandel

Recent works have shown that Deep Recurrent Neural Networks using the LSTM architecture can achieve strong single-channel speech enhancement by estimating time-frequency masks. However, these models do not naturally generalize to multi-channel inputs from varying microphone configurations. In contrast, spatial clustering techniques can achieve such generaliz

Piper Wolters, Chris Careaga, Brian Hutchinson, Lauren Phillips

Advances in deep learning have resulted in state-of-the-art performance for many audio classification tasks but, unlike humans, these systems traditionally require large amounts of data to make accurate predictions. Not every person or organization has access to those resources, and the organizations that do, like our field at large, do not reflect the demog

Patrick Lavin, Jeffrey Young, Rich Vuduc, Jonathan Beard

As systems and applications grow more complex, detailed simulation takes an ever increasing amount of time. The prospect of increased simulation time resulting in slower design iteration forces architects to use simpler models, such as spreadsheets, when they want to iterate quickly on a design. However, the task of migrating from a simple simulation to one

S. Castillo, G. Hamilton, N. Soto, C. Lobos

In the manufacturing process of Carbon Fiber Reinforced Polymer (CFRP) mirrors (replicated from a mandrel) the orientation of the unidirectional carbon fiber layers (layup) has a direct influence on different aspects of the final product, like its general (large scale) shape and local deformations. In particular, optical methods used to evaluate the surface&

A. Bayo, P. Mardones, S. Castillo, G. Hamilton

Planet Formation research is blooming in an era where we are moving from speaking about "protoplanetary disks" to "planet forming disks" (Andrews et al., 2018). However, this transition is still motivated by indirect (but convincing) hints. Up to date, the direct detection of planets "in the making" remains elusive with the remarkable

Hongyu Guo

Label Smoothing (LS) is an effective regularizer to improve the generalization of state-of-the-art deep models. For each training sample the LS strategy smooths the one-hot encoded training signal by distributing its distribution mass over the non ground-truth classes, aiming to penalize the networks from generating overconfident output distributions. This p

T. Karabassov, A. A. Golubov, V. M. Silkin, V. S. Stolyarov

In the following paper we investigate the critical temperature $T_c$ behavior in the two-dimensional S/TI (S denotes superconductor and TI - topological insulator) junction with a proximity induced in-plane helical magnetization in the TI surface. The calculations of $T_c$ are performed using the general self-consistent approach based on the Usadel equations

Sergio Amat, David Levin, Juan Ruiz-Álvarez

Given values of a piecewise smooth function $f$ on a square grid within a domain $Ω$, we look for a piecewise adaptive approximation to $f$. Standard approximation techniques achieve reduced approximation orders near the boundary of the domain and near curves of jump singularities of the function or its derivatives. The idea used here is that the behavior ne

Damian Kwasny, Daria Hemmerling

In this paper we extend the x-vector framework for the task of speaker's age estimation and gender classification. In particular, we replace the baseline multilayer-TDNN architecture with QuartzNet, a convolutional architecture that has gained success in the field of speech recognition. We further propose a two-staged transfer learning scheme, utilizing

Teng Fei, Duong H. Phong, Sebastien Picard, Xiangwen Zhang

A new derivation of the flow of metrics in the Type IIA flow is given. It is adapted to the formulation of the flow as a variant of a Laplacian flow, and it uses the projected Levi-Civita connection of the metrics themselves instead of their conformal rescalings.

Ivona Bezáková, Kimberly Fluet, Edith Hemaspaandra, Hannah Miller

Computing theory analyzes abstract computational models to rigorously study the computational difficulty of various problems. Introductory computing theory can be challenging for undergraduate students, and the main goal of our research is to help students learn these computational models. The most common pedagogical tool for interacting with these models is

Ling-Wei Kong, Hua-Wei Fan, Celso Grebogi, Ying-Cheng Lai

To predict a critical transition due to parameter drift without relying on model is an outstanding problem in nonlinear dynamics and applied fields. A closely related problem is to predict whether the system is already in or if the system will be in a transient state preceding its collapse. We develop a model free, machine learning based solution to both pro

Lucy G. Todd, Joshua W. Hollett

Three new measures of relative electron motion are introduced: equimomentum, antimomentum, and momentum-balance. The equimomentum is the probability that two electrons have the exact same momentum, whereas the antimomentum is the probability their momenta are the exact opposite. Momentum-balance (MB) is the difference between the equimomentum and antimomentu

Sobhan Soleymani, Ali Dabouei, Fariborz Taherkhani, Jeremy Dawson

In this paper, we present a novel differential morph detection framework, utilizing landmark and appearance disentanglement. In our framework, the face image is represented in the embedding domain using two disentangled but complementary representations. The network is trained by triplets of face images, in which the intermediate image inherits the landmarks

Graciela Boente, Matias Salibian-Barrera

In this paper we review existing methods for robust functional principal component analysis (FPCA) and propose a new method for FPCA that can be applied to longitudinal data where only a few observations per trajectory are available. This method is robust against the presence of atypical observations, and can also be used to derive a new non-robust FPCA appr

Ikkei Shimizu

We consider the initial value problem for the Landau-Lifshitz equation with helicity term (chiral interaction term), which arises from the Dzyaloshinskii-Moriya interaction. We prove that it is well-posed locally-in-time in the space $\bar{k} +H^s$ for $s\ge 3$ with $s\in \mathbb{Z}$ and $\bar{k}={}^t(0,0,1)$. We also show that if we further assume that the

Xin He, Yajing Liu, Paul Beckett, MD Hemayet Uddin

Multispectral cameras capture images in multiple wavelengths in narrow spectral bands. They offer advanced sensing well beyond normal cameras and many single sensor based multispectral cameras have been commercialized aimed at a broad range of applications, such as agroforestry research, medical analysis and so on. However, the existing single sensor based m

Siddharth Bhandari, Prahladh Harsha, Mrinal Kumar, Madhu Sudan

The multiplicity Schwartz-Zippel lemma bounds the total multiplicity of zeroes of a multivariate polynomial on a product set. This lemma motivates the multiplicity codes of Kopparty, Saraf and Yekhanin [J. ACM, 2014], who showed how to use this lemma to construct high-rate locally-decodable codes. However, the algorithmic results about these codes crucially

F. Schuller, J. S. Urquhart, T. Csengeri, D. Colombo

The SEDIGISM (Structure, Excitation and Dynamics of the Inner Galactic Interstellar Medium) survey used the APEX telescope to map 84 deg^2 of the Galactic plane between l = -60 deg and l = +31 deg in several molecular transitions, including 13CO(2-1) and C18O(2-1), thus probing the moderately dense (~10^3 cm^-3) component of the interstellar medium. With an

Karttikeya Mangalam, Yang An, Harshayu Girase, Jitendra Malik

Human trajectory forecasting is an inherently multi-modal problem. Uncertainty in future trajectories stems from two sources: (a) sources that are known to the agent but unknown to the model, such as long term goals and (b)sources that are unknown to both the agent & the model, such as intent of other agents & irreducible randomness indecisions. We propose t

Colin Vendromin, Marc M. Dignam

Continuous-variable (CV) entanglement is a valuable resource in the field of quantum information. One source of CV entanglement is the correlations between the position and momentum of photons in a two-mode squeezed state of light. In this paper, we theoretically study the generation of squeezed states, via spontaneous parametric downconversion (SPDC), insid

Christian Fuchs, Ada Baeumner, Anja Brueggemann, Christian Berger

This paper discusses the temperature-dependent properties of (GaIn)As/Ga(AsSb)/(GaIn)As W-quantum well heterostructures for laser applications based on theoretical modeling as well as experimental findings. A microscopic theory is applied to discuss band bending effects giving rise to the characteristic blue shift with increasing charge carrier density obser

Ümit Akıncı

The magneticaloric properties of the Ising nanotube constituted by arbitrary core spin values $S_c$ and the shell spin values $S_s$ have been investigated by mean field approximation. During this investigation, several quantities have been calculated, such as isothermal magnetic entropy change, full width at half maximum value and the refrigerant capacity. T

Jeremy M. Myers, Daniel M. Dunlavy, Keita Teranishi, D. S. Hollman

Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP) tensor decomposition model when the tensor has sparse structure and the tensor elements are nonnegative count data. SparTen is a high-performance C++ library which computes a low

Sara Berri, Samson Lasaulce, Mohammed Said Radjef

One formal way of studying cooperation and incentive mechanisms in wireless ad hoc networks is to use game theory. In this respect, simple interaction models such as the forwarder's dilemma have been proposed and used successfully. However, this type of models is not suited to account for possible fluctuations of the wireless links of the network. Additi

Peter Crawford-Kahrl, Bree Cummins, Tomas Gedeon

The study of monotone Boolean functions (MBFs) has a long history. We explore a connection between MBFs and ordinary differential equation (ODE) models of gene regulation, and, in particular, a problem of the realization of an MBF as a function describing the state transition graph of an ODE. We formulate a problem of joint realizability of finite collection

N. Soto, C. Lobos, P. Mardones, A. Bayo

The surface quality of replicated CFRP mirrors is ideally expected to be as good as the mandrel from which they are manufactured. In practice, a number of factors produce surface imperfections in the final mirrors at different scales. To understand where this errors come from, and develop improvements to the manufacturing process accordingly, a wide range of

Alireza Alizadeh, Mai Vu

We study distributed user association in 5G and beyond millimeter-wave enabled heterogeneous networks using matching theory. We propose a novel and efficient distributed matching game, called early acceptance (EA), which allows users to apply for association with their ranked-preference base station in a distributed fashion and get accepted as soon as they a

Vincent Gripon, Carlos Lassance, Ghouthi Boukli Hacene

Learning deep representations to solve complex machine learning tasks has become the prominent trend in the past few years. Indeed, Deep Neural Networks are now the golden standard in domains as various as computer vision, natural language processing or even playing combinatorial games. However, problematic limitations are hidden behind this surprising unive

Nicolas Lanchier, Axel La Salle

The main objective of this paper is to study the size of a typical cluster of bond percolation on each of the five Platonic solids: the tetrahedron, the cube, the octahedron, the dodecahedron and the icosahedron. Looking at the clusters from a dynamical point of view, i.e., comparing the clusters with birth processes, we first prove that the first and second

Sara Berri, Samson Lasaulce, Mohammed Said Radjef

In this paper, the well-known forwarder's dilemma is generalized by accounting for the presence of link quality fluctuations; the forwarder's dilemma is a four-node interaction model with two source nodes and two destination nodes. It is known to be very useful to study ad hoc networks. To characterize the long-term utility region when the source nod

J. I. Collar

Experiments looking for a lepton flavor-violating decay $μ^{+}\!\!\rightarrow \!e^{+} X^{0}$ are reviewed in light of present-day germanium detector technology, with an eye on scenarios where a long-lived, slow-moving massive boson $X^{0}$ might have a cosmological impact. A broad swath of interesting, unexplored parameter space very close to the kinematic l

A. Duarte-Cabral, D. Colombo, J. S. Urquhart, A. Ginsburg

We use the 13CO(2-1) emission from the SEDIGISM high-resolution spectral-line survey of the inner Galaxy, to extract the molecular cloud population with a large dynamic range in spatial scales, using the SCIMES algorithm. This work compiles a cloud catalogue with a total of 10663 molecular clouds, 10300 of which we were able to assign distances and compute p

Alexander Vidybida, Olha Shchur

The statistics of the output activity of a neuron during its stimulation by the stream of input impulses that forms the stochastic Poisson process is studied. The leaky integrate-and-fire neuron is considered as a neuron model. A new representation of the probability distribution function of the output interspike interval durations is found. Based on it, the

Claudenir Freire Rodrigues

In this article, we extend some results about algebra $A$ with the group of units $U(A)$ having a special polynomial identity, Laurent polynomial. And we present a new version of B. Hartley Conjecture with these identities.

Sara Berri, Vineeth Varma, Samson Lasaulce, Mohammed Said Radjef

In this paper, we consider the problem of wireless power control in an interference channel where transmitters aim to maximize their own benefit. When the individual payoff or utility function is derived from the transmission efficiency and the spent power, previous works typically study the Nash equilibrium of the resulting power control game. We propose to

Long Yang, Qian Zheng, Gang Pan

The goal of policy-based reinforcement learning (RL) is to search the maximal point of its objective. However, due to the inherent non-concavity of its objective, convergence to a first-order stationary point (FOSP) can not guarantee the policy gradient methods finding a maximal point. A FOSP can be a minimal or even a saddle point, which is undesirable for

S. Hu, X. Chen, W. Ni, E. Hossain

Distributed machine learning (DML) techniques, such as federated learning, partitioned learning, and distributed reinforcement learning, have been increasingly applied to wireless communications. This is due to improved capabilities of terminal devices, explosively growing data volume, congestion in the radio interfaces, and increasing concern of data privac

A. Maria Salomons

During the Corona crisis measures were taken to avoid the spread of the virus, and one of the most important was to 'keep sufficient distance'. In this period cyclists were facilitated in distancing by the widening of cycle paths, or the use of car lanes. The Corona measures also affected intersection control, since one of the principles of signalizi

Dimitrios Tsiotas, Lykourgos Magafas, Panos Argyrakis

This paper proposes a new method for converting a time-series into a weighted graph (complex network), which builds on the electrostatic conceptualization originating from physics. The proposed method conceptualizes a time-series as a series of stationary, electrically charged particles, on which Coulomb-like forces can be computed. This allows generating el

Rathziel Roncancio, Jupyoung Kim, Aly El Gamal, Jay P. Gore

Turbulent premixed flames are important for power generation using gas turbines. Improvements in characterization and understanding of turbulent flames continue particularly for transient events like ignition and extinction. Pockets or islands of unburned material are features of turbulent flames during these events. These features are directly linked to hea

S. A. Bunyaev, B. Budinska, R. Sachser, Q. Wang

Media with engineered magnetization are essential building blocks in superconductivity, magnetism and magnon spintronics. However, the established thin-film and lithographic techniques insufficiently suit the realization of planar components with on-demand-tailored magnetization in the lateral dimension. Here, we demonstrate the engineering of the magnetic p

Yuhang Lu, Kang Zheng, Weijian Li, Yirui Wang

Accurate segmentation of anatomical structures is vital for medical image analysis. The state-of-the-art accuracy is typically achieved by supervised learning methods, where gathering the requisite expert-labeled image annotations in a scalable manner remains a main obstacle. Therefore, annotation-efficient methods that permit to produce accurate anatomical

Sara Berri, Vineeth Varma, Samson Lasaulce, Mohammed Said Radjef

In the paradigm of mobile Ad hoc networks (MANET), forwarding packets originating from other nodes requires cooperation among nodes. However, as each node may not want to waste its energy, cooperative behavior can not be guaranteed. Therefore, it is necessary to implement some mechanism to avoid selfish behavior and to promote cooperation. In this paper, we

Rob Schneiderman

These introductory notes on Whitney towers in 4-manifolds, as developed in collaboration with Jim Conant and Peter Teichner, are an expansion of three expository lectures given at the Winter Braids X conference February 2020 in Pisa, Italy. Topics presented include local manipulations of surfaces in 4-space, fundamental definitions related to Whitney towers

Stefan Vlaski, Elsa Rizk, Ali H. Sayed

Federated learning is a useful framework for centralized learning from distributed data under practical considerations of heterogeneity, asynchrony, and privacy. Federated architectures are frequently deployed in deep learning settings, which generally give rise to non-convex optimization problems. Nevertheless, most existing analysis are either limited to c

Tanvir Mahmud, Md Awsafur Rahman, Shaikh Anowarul Fattah, Sun-Yuan Kung

Automatic lung lesions segmentation of chest CT scans is considered a pivotal stage towards accurate diagnosis and severity measurement of COVID-19. Traditional U-shaped encoder-decoder architecture and its variants suffer from diminutions of contextual information in pooling/upsampling operations with increased semantic gaps among encoded and decoded featur

Ewine F. van Dishoeck, Edwin A. Bergin

This paper provides a brief summary and overview of the astrochemistry associated with the formation of stars and planets. It is aimed at new researchers in the field to enable them to obtain a quick overview of the landscape and key literature in this rapidly evolving area. The journey of molecules from clouds to protostellar envelopes, disks and ultimately

Yuqi Ouyang, Victor Sanchez

Video anomaly detection is a challenging task not only because it involves solving many sub-tasks such as motion representation, object localization and action recognition, but also because it is commonly considered as an unsupervised learning problem that involves detecting outliers. Traditionally, solutions to this task have focused on the mapping between

Xiao Chen, Thomas Navidi, Ram Rajagopal

Personal devices such as mobile phones can produce and store large amounts of data that can enhance machine learning models; however, this data may contain private information specific to the data owner that prevents the release of the data. We want to reduce the correlation between user-specific private information and the data while retaining the useful in

Javier Román, Ignacio Trujillo, Mireia Montes

The presence of Galactic cirri in deep optical observations is one of the most challenging problems that the extragalactic community is already facing, and it is expected to be even tougher in the near future with the increasing depth of optical surveys. To address this problem, we have performed a photometric characterization of Galactic cirri in the IAC St

J. S. Urquhart, C. Figura, J. R. Cross, M. R. A. Wells

By combining two surveys covering a large fraction of the molecular material in the Galactic disk we investigate the role the spiral arms play in the star formation process. We have matched clumps identified by ATLASGAL with their parental GMCs as identified by SEDIGISM, and use these giant molecular cloud (GMC) masses, the bolometric luminosities, and integ

D. R. Wilkins, S. W. Allen, E. D. Miller, M. Bautz

Space-based X-ray detectors are subject to significant fluxes of charged particles in orbit, notably energetic cosmic ray protons, contributing a significant background. We develop novel machine learning algorithms to detect charged particle events in next-generation X-ray CCDs and DEPFET detectors, with initial studies focusing on the Athena Wide Field Imag

B. M. Rose, D. Rubin, L. Strolger, P. M. Garnavich

Type Ia supernovae (SNe Ia) are standardizable candles, but for over a decade, there has been a debate on how to properly account for their correlations with host galaxy properties. Using the Bayesian hierarchical model UNITY, we simultaneously fit for the SN Ia light curve and host galaxy standardization parameters on a set of 103 Sloan Digital Sky Survey I

Qirong Zhu, Yuexing Li, Yiting Li, Moupiya Maji

Supermassive black holes (SMBHs) of $\sim 10^9\, M_\odot$ are generally believed to be the central engines of the luminous quasars observed at $z\gtrsim6$, but their astrophysical origin remains elusive. The $z\gtrsim$ quasars reside in rare density peaks, which poses several challenges to uniform hydrodynamic simulations. To investigate the formation of the

Paul Caucal, Edmond Iancu, Gregory Soyez

In a series of previous papers, we have presented a new approach, based on perturbative QCD, for the evolution of a jet in a dense quark-gluon plasma. In the original formulation, the plasma was assumed to be homogeneous and static. In this work, we extend our description and its Monte Carlo implementation to a plasma obeying Bjorken longitudinal expansion.

Aljaž Božič, Pablo Palafox, Michael Zollhöfer, Justus Thies

We introduce Neural Deformation Graphs for globally-consistent deformation tracking and 3D reconstruction of non-rigid objects. Specifically, we implicitly model a deformation graph via a deep neural network. This neural deformation graph does not rely on any object-specific structure and, thus, can be applied to general non-rigid deformation tracking. Our m

Alexander Duthie, Sthitadhi Roy, David E. Logan

We introduce a self-consistent theory of mobility edges in nearest-neighbour tight-binding chains with quasiperiodic potentials. Demarcating boundaries between localised and extended states in the space of system parameters and energy, mobility edges are generic in quasiperiodic systems which lack the energy-independent self-duality of the commonly studied A

Shahar Hod

The Penrose strong cosmic censorship conjecture asserts that Cauchy horizons inside dynamically formed black holes are unstable to remnant matter fields that fall into the black holes. The physical importance of this conjecture stems from the fact that it provides a necessary condition for general relativity to be a truly deterministic theory of gravity. Det

S. Berta, A. J. Young, P. Cox, R. Neri

(Abridged) Exploiting the sensitivity and broad band width of NOEMA, we have studied the molecular gas and dust in the galaxy HerBS-89a, at z=2.95. High angular resolution images reveal a partial 1.0" diameter Einstein ring in the dust continuum emission and the molecular emission lines of 12CO(9-8) and H2O(2_02-1_11). We report the detection of the thre

Amit Gordon, Aditya Banerjee, Maciej Koch-Janusz, Zohar Ringel

The analysis of complex physical systems hinges on the ability to extract the relevant degrees of freedom from among the many others. Though much hope is placed in machine learning, it also brings challenges, chief of which is interpretability. It is often unclear what relation, if any, the architecture- and training-dependent learned "relevant" feat

Nikhil Raghuram, Washington Taylor, Andrew P. Turner

We observe that in many F-theory models, tuning a specific gauge group $G$ and matter content $M$ under certain circumstances leads to an automatic enhancement to a larger gauge group $G' \supset G$ and matter content $M' \supset M$. We propose that this is true for any theory $G, M$ whenever there exists a containing theory $G', M'$ that can

Sarang Gopalakrishnan, Michael J. Gullans

A quantum system subject to continuous measurement and post-selection evolves according to a non-Hermitian Hamiltonian. We show that, as one increases the rate of post-selection, this non-Hermitian Hamiltonian undergoes a spectral phase transition. On one side of this phase transition (for weak post-selection) an initially mixed density matrix remains mixed

Jeong Min Park, Yuan Cao, Kenji Watanabe, Takashi Taniguchi

Moiré superlattices have recently emerged as a novel platform where correlated physics and superconductivity can be studied with unprecedented tunability. Although correlated effects have been observed in several other moiré systems, magic-angle twisted bilayer graphene (MATBG) remains the only one where robust superconductivity has been reproducibly measure

Christina C. Williams, Justin S. Spilker, Katherine E. Whitaker, Romeel Davé

We present ALMA CO(2-1) spectroscopy of 6 massive (log$_{10}$M$_{\rm{*}}/\rm{M}_\odot>$11.3) quiescent galaxies at $z\sim1.5$. These data represent the largest sample using CO emission to trace molecular gas in quiescent galaxies above $z>1$, achieving an average 3$σ$ sensitivity of M$_{\rm{H_{2}}}\sim10^{10}\rm{M}_\odot$. We detect one galaxy at 4$σ$ signif

C. E. Barbosa, C. Spiniello, M. Arnaboldi, L. Coccato

The stellar initial mass function (IMF) seems to be variable and not universal, as argued in the literature in the last three decades. Several relations among the low-mass end of the IMF slope and other stellar population, photometric or kinematic parameters of massive early-type galaxies (ETGs) have been proposed, but a consolidated agreement on a factual c

Jérémy Leconte

With the major increase in the volume of the spectroscopic line lists needed to perform accurate radiative transfer calculations, disseminating accurate radiative data has become almost as much a challenge as computing it. Considering that many planetary science applications are only looking for heating rates or mid-to-low resolution spectra, any approach en

Benjamin D. Johnson, Joel Leja, Charlie Conroy, Joshua S. Speagle

Inference of the physical properties of stellar populations from observed photometry and spectroscopy is a key goal in the study of galaxy evolution. In recent years the quality and quantity of the available data has increased, and there have been corresponding efforts to increase the realism of the stellar population models used to interpret these observati

Lucas Kohn, Giuseppe E. Santoro

We propose an efficient algorithm to numerically solve Anderson impurity problems using matrix product states. By introducing a modified chain mapping we obtain significantly lower entanglement, as compared to all previous attempts, while keeping the short-range nature of the couplings. Our approach naturally extends to finite temperatures, with applications

R. B. Paris

We examine the four Féjer-type trigonometric sums of the form \[S_n(x)=\sum_{k=1}^n \frac{f(g(kx))}{k}\qquad (0<x<π)\] where $f(x)$, $g(x)$ are chosen to be either $\sin x$ or $\cos x$. The analysis of the sums with $f(x)=g(x)=\cos x$, $f(x)=\cos x$, $g(x)=\sin x$ and $f(x)=\sin x$, $g(x)=\cos x$ is reasonably straightforward. It is shown that these sums exh

J. Javaraiah

We analyzed the sunspot-group daily data that were reported by Greenwich Photoheliogrphic Results (GPR) during the period 1874-1976 and Debrecen Photoheliographic Data (DPD) during the period 1977-2017. We determined the equatorial rotation rate [A] and the latitude gradient [B] components of the solar differential rotation by fitting the data in each of the

Jalal Arabneydi, Aditya Mahajan

We investigate team optimal control of stochastic subsystems that are weakly coupled in dynamics (through the mean-field of the system) and are arbitrary coupled in the cost. The controller of each subsystem observes its local state and the mean-field of the state of all subsystems. The system has a non-classical information structure. Exploiting the symmetr

Revanth Gangi Reddy, Bhavani Iyer, Md Arafat Sultan, Rong Zhang

End-to-end question answering (QA) requires both information retrieval (IR) over a large document collection and machine reading comprehension (MRC) on the retrieved passages. Recent work has successfully trained neural IR systems using only supervised question answering (QA) examples from open-domain datasets. However, despite impressive performance on Wiki

Habiba Kadiri

Let $q\ge 3$ be a non-exceptional modulus $q\ge3$, and let $a$ be a positive integer coprime with $q$. For any $ε>0$, there exists $α>0$ (computable), such that for all $x\ge α(\log q)^2$, the interval $\left[ e^x,e^{x+ε}\right]$ contains a prime $p$ in the arithmetic progression $a \bmod q$. This gives the bound for the least prime in this arithmetic progre

Oguzhan Can, Tarun Tummuru, Ryan P. Day, Ilya Elfimov

A great variety of novel phenomena occur when two-dimensional materials, such as graphene or transition metal dichalcogenides, are assembled into bilayers with a twist between individual layers. As a new application of this paradigm, we consider structures composed of two monolayer-thin $d$-wave superconductors with a twist angle $θ$ that can be realized by

Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale

We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo. With high computation speed and low memory requirement, PatchmatchNet can process higher resolution imagery and is more suited to run on resource limited devices than competitors that employ 3D cost volume regularization. For the first tim

Thomas L. Carroll

It has been demonstrated that cellular automata had the highest computational capacity at the edge of chaos, the parameter at which their behavior transitioned from ordered to chaotic. This same concept has been applied to reservoir computers; a number of researchers have stated that the highest computational capacity for a reservoir computer is at the edge

Arindam Biswas, Jyoti Prakash Saha

Jambor--Liebeck--O&#39;Brien showed that there exist non-proper-power word maps which are not surjective on $\mathrm{PSL}_{2}(\mathbb{F}_{q})$ for infinitely many $q$. This provided the first counterexamples to a conjecture of Shalev which stated that if a two-variable word is not a proper power of a non-trivial word, then the corresponding word map is surje

Abdolali Banihashemi, Nima Khosravi, Arman Shafieloo

We propose a dark energy model based on the physics of critical phenomena which is consistent with both the Planck&#39;s CMB and the Riess et al.&#39;s local Hubble measurements. In this model the dark energy density behaves like the magnetization of the Ising model. This means the dark energy is an emergent phenomenon and we named it critically emergent dar

P. M. King, K. Miller, N. Lemos, J. L. Shaw

The two-temperature relativistic electron spectrum from a low-density ($3\times10^{17}$~cm$^{-3}$) self-modulated laser wakefield accelerator (SM-LWFA) is observed to transition between temperatures of $19\pm0.65$ and $46\pm2.45$ MeV at an electron energy of about 100 MeV. When the electrons are dispersed orthogonally to the laser polarization, their spectru