arXiv papers from August 2021

Keumgang Cha, Junghoon Seo, Yeji Choi

In the training of deep learning models, how the model parameters are initialized greatly affects the model performance, sample efficiency, and convergence speed. Representation learning for model initialization has recently been actively studied in the remote sensing field. In particular, the appearance characteristics of the imagery obtained using the a sy

Lihong Zhou, Xiaoling Cui

Two-body dissipation usually gives rise to a complex interaction. Here, we study the effect of two-body dissipation on few-body physics, including the fundamental two-body effective scattering and the three-body Efimov physics. By employing a two-channel model that incorporates the decay of closed-channel molecules (generating the two-body dissipation), we e

Yi-Peng Wu, Elena Pinetti, Kalliopi Petraki, Joseph Silk

The ultra-slow-roll (USR) inflation represents a class of single-field models with sharp deceleration of the rolling dynamics on small scales, leading to a significantly enhanced power spectrum of the curvature perturbations and primordial black hole (PBH) formation. Such a sharp transition of the inflationary background can trigger the coherent motion of sc

Benjamin Baily, Justine Dell, Irfan Durmić, Henry Fleischmann

Every positive integer may be written uniquely as a base-$\beta$ decomposition--that is a legal sum of powers of $\beta$--where $\beta$ is the dominating root of a non-increasing positive linear recurrence sequence. Guided by earlier work on a two-player game which produces the Zeckendorf Decomposition of an integer (see [Bai+19]), we define a broad class of

Daniele Notarmuzi, Claudio Castellano, Alessandro Flammini, Dario Mazzilli

Information avalanches in social media are typically studied in a similar fashion as avalanches of neuronal activity in the brain. Whereas a large body of literature reveals substantial agreement about the existence of a unique process characterizing neuronal activity across organisms, the dynamics of information in online social media is far less understood

Audrey Xie, Elhoucine Elfatimi, Sambuddha Ghosal, Pratik Shah

Deep learning models (DLMs) can achieve state-of-the-art performance in histopathology image segmentation and classification, but have limited deployment potential in real-world clinical settings. Uncertainty estimates of DLMs can increase trust by identifying predictions and images that need further review. Dice scores and coefficients (Dice) are benchmarks

Yong Shi, Xiaoling Yu, Shude Mao, Qiusheng Gu

In this study we demonstrate that stellar masses of galaxies (Mstar) are universally correlated through a double power law function with the product of the dynamical velocities (Ve) and sizes to one-fourth power (Re^0.25) of galaxies, both measured at the effective radii. The product VeRe^0.25 represents the fourth root of the total binding energies within e

Eric-Tuan Lê, Minhyuk Sung, Duygu Ceylan, Radomir Mech

Representing human-made objects as a collection of base primitives has a long history in computer vision and reverse engineering. In the case of high-resolution point cloud scans, the challenge is to be able to detect both large primitives as well as those explaining the detailed parts. While the classical RANSAC approach requires case-specific parameter tun

Thomas A. Trainor

The ALICE collaboration recently reported high-statistics $\bf p_t$ spectra from 5 TeV and 13 TeV p-p collisions with intent to determine the role of jets in high-multiplicity collisions. In the present study a two-component (soft + hard) model (TCM) of hadron production in p-p collisions is applied to ALICE $\bf p_t$ spectra. As in previous TCM studies of A

Luigi Ferraro, Desiree Martin, W. Frank Moore

Let $\Bbbk$ be a field and let $I$ be a monomial ideal in the polynomial ring $Q=\Bbbk[x_1,\ldots,x_n]$. In her thesis, Taylor introduced a complex which provides a finite free resolution for $Q/I$ as a $Q$-module. Later, Gemeda constructed a differential graded structure on the Taylor resolution. More recently, Avramov showed that this differential graded a

Kunhao Zheng, Jesse Michael Han, Stanislas Polu

We present miniF2F, a dataset of formal Olympiad-level mathematics problems statements intended to provide a unified cross-system benchmark for neural theorem proving. The miniF2F benchmark currently targets Metamath, Lean, Isabelle (partially) and HOL Light (partially) and consists of 488 problem statements drawn from the AIME, AMC, and the International Ma

Ramin Nateghi, Fattaneh Pourakpour

We propose a two-step domain shift-invariant mitosis cell detection method based on Faster RCNN and a convolutional neural network (CNN). We generate various domain-shifted versions of existing histopathology images using a stain augmentation technique, enabling our method to effectively learn various stain domains and achieve better generalization. The perf

S. Richard, R. Tiedra de Aldecoa

We present a new technique to obtain polynomial decay estimates for the matrix coefficients of unitary operators. Our approach, based on commutator methods, applies to nets of unitary operators, unitary representations of topological groups, and unitary operators given by the evolution group of a self-adjoint operator or by powers of a unitary operator. Our

Stephen R. Doty

We prove that the permutations of $\{1,\dots, n\}$ having an increasing (resp., decreasing) subsequence of length $n-r$ index a subset of the set of all $r$th Kronecker powers of $n \times n$ permutation matrices which is a basis for the linear span of that set. Thanks to a known Schur--Weyl duality, this gives a new basis for the centralizer algebra of the

Rohil Prasad

In the previous work, we introduced a method for constructing invariant probability measures of a large class of non-singular volume-preserving flows on closed, oriented odd-dimensional smooth manifolds with pseudoholomorphic curve techniques from symplectic geometry. The technique requires existence of certain pseudoholomorphic curves satisfying some weak a

R. X. Zhou, Y. G. Zheng, K. R. Zhu, S. J. Kang

In this paper, we have selected a sample of 64 teraelectronvolt blazars, with redshift, from those classified in the fourth Fermi Large Area Telescope source catalog\footnote{\url{https://fermi.gsfc.nasa.gov/ssc/data/access/lat/8yr_catalog/}}. We have obtained the values of the relevant physical parameters by performing a log-parabolic fitting of the average

Edward J. Daw, Ian J. Hollows, Elliot L. Jones, Ross Kennedy

We present a novel adaptive filtering approach to the dynamic characterisation of waves of varying frequency and amplitude embedded in arbitrary noise backgrounds. This method, known as IWAVE, possesses critical advantages over conventional techniques making it a useful new tool in the dynamic characterisation of a wide range of data containing embedded osci

Madhurananda Pahar, Igor Miranda, Andreas Diacon, Thomas Niesler

We present an automatic non-invasive way of detecting cough events based on both accelerometer and audio signals. The acceleration signals are captured by a smartphone firmly attached to the patient's bed, using its integrated accelerometer. The audio signals are captured simultaneously by the same smartphone using an external microphone. We have compiled a

Rohil Prasad

We introduce a method for constructing invariant probability measures of a large class of non-singular volume-preserving flows on closed, oriented odd-dimensional smooth manifolds using pseudoholomorphic curve techniques from symplectic geometry. These flows include any non-singular volume preserving flow in dimension three, and autonomous Hamiltonian flows

Maria Kalantzi, George Karypis

Graph Neural Networks (GNNs) bring the power of deep representation learning to graph and relational data and achieve state-of-the-art performance in many applications. GNNs compute node representations by taking into account the topology of the node's ego-network and the features of the ego-network's nodes. When the nodes do not have high-quality features,

Snehalkumar, S. Gaikwad, Shankar Iyer, Dalton Lunga

Humanitarian challenges, including natural disasters, food insecurity, climate change, racial and gender violence, environmental crises, the COVID-19 coronavirus pandemic, human rights violations, and forced displacements, disproportionately impact vulnerable communities worldwide. According to UN OCHA, 235 million people will require humanitarian assistance

Youssef Elkharaz, Saad Motahhir, Abdelaziz Elghzizal

In the next Vehicle generations, connected and highly developed driving cars will have an important impact on the networking architecture and the interconnection between ECUs(Electronic Control Unit). The automotive industry begins to develop new and efficient strategies to improve the performance of the global system. AUTOSAR organization as part of this in

Kenneth G. Libbrecht

I describe a new approach to the classification of snow crystal morphologies that focuses on the most common growth behaviors that appear in normal air under conditions of constant applied temperature and water-vapor supersaturation. The resulting morphological structures are generally robust with respect to small environmental changes and thus should be esp

Tobias Fischer

My overarching research goal is to provide robots with perceptional abilities that allow interactions with humans in a human-like manner. To develop these perceptional abilities, I believe that it is useful to study the principles of the human visual system. I use these principles to develop new computer vision algorithms and validate their effectiveness in

Eric Bahuaud, Christine Guenther, James Isenberg

We prove that both the Laplacian on functions, and the Lichnerowicz Laplacian on symmetric 2-tensors with respect to asymptotically hyperbolic metrics, are sectorial maps in weighted H\"older spaces. As an application, the machinery of analytic semigroups then applies to yield well-posedness results for parabolic evolution equations in these spaces.

Ido Ben-Yair, Gil Ben Shalom, Moshe Eliasof, Eran Treister

Quantization of Convolutional Neural Networks (CNNs) is a common approach to ease the computational burden involved in the deployment of CNNs, especially on low-resource edge devices. However, fixed-point arithmetic is not natural to the type of computations involved in neural networks. In this work, we explore ways to improve quantized CNNs using PDE-based

Jeffrey Kuan, Tadahiro Oh, Sunčica Čanić

We prove probabilistic well-posedness for a 2D viscous nonlinear wave equation modeling fluid-structure interaction between a 3D incompressible, viscous Stokes flow and nonlinear elastodynamics of a 2D stretched membrane. The focus is on (rough) data, often arising in real-life problems, for which it is known that the deterministic problem is ill-posed. We s

M. J. Grzybowski, C. F. Schippers, O. Gomonay, K. Rubi

Magnetocrystalline anisotropy is essential in the physics of antiferromagnets and commonly treated as a constant, not depending on an external magnetic field. However, we demonstrate that in CoO the anisotropy should necessarily depend on the magnetic field, which is shown by the spin Hall magnetoresistance of the CoO $|$ Pt device. Below the N\'eel temperat

Zhen Zhang, Yeonjong Shin, George Em Karniadakis

We propose the GENERIC formalism informed neural networks (GFINNs) that obey the symmetric degeneracy conditions of the GENERIC formalism. GFINNs comprise two modules, each of which contains two components. We model each component using a neural network whose architecture is designed to satisfy the required conditions. The component-wise architecture design

Guenter Sigl

We investigate toy models for spatial and temporal instabilities in collective neutrino oscillations induced by neutrino self-interactions, with special emphasis on inhomogeneous systems with densities following a profile. Simulations are based on a mathematica program that solves the Liouville equation with or without vacuum terms, refractive terms from a b

Sarouyeh Khoshkholgh, Ivanka Orozova-Bekkevold, Klaus Mosegaard

When hydrocarbon reservoirs are used as a CO2 storage facility, an accurate uncertainty analysis and risk assessment is essential. An integration of information from geological knowledge, geological modelling, well log data, and geophysical data provides the basis for this analysis. Modelling the time development of stress/strain changes in the overburden pr

Ralf Kircheis

The novel coronavirus SARS-CoV-2 has resulted in a global pandemic with worldwide 6-digital infection rates and thousands death tolls daily. Enormeous effords are undertaken to achieve high coverage of immunization in order to reach herd immunity to stop spreading of SARS-CoV-2 infection. Several SARS-CoV-2 vaccines, based either on mRNA, viral vectors, or i

Katie M. Fasbender, David L. Nidever

Despite extensive searches and the relative proximity of solar system objects (SSOS) to Earth, many remain undiscovered and there is still much to learn about their properties and interactions. This work is the first in a series dedicated to detecting and analyzing SSOs in the all-sky NOIRLab Source Catalog (NSC). We search the first data release of the NSC

Tuhin Chakrabarty, Yejin Choi, Vered Shwartz

Figurative language is ubiquitous in English. Yet, the vast majority of NLP research focuses on literal language. Existing text representations by design rely on compositionality, while figurative language is often non-compositional. In this paper, we study the interpretation of two non-compositional figurative languages (idioms and similes). We collected da

Toshiaki Inada, Wonho Jang, Yutaro Iiyama, Koji Terashi

Quantum error correction is a crucial step beyond the current noisy-intermediate-scale quantum device towards fault-tolerant quantum computing. However, most of the error corrections ever demonstrated rely on post-selection of events or post-correction of states, based on measurement results repeatedly recorded during circuit execution. On the other hand, re

Michael Mackey, Pauline Mellon

We show that there are many sets in the boundary of a bounded symmetric domain that determine the values and norm of holomorphic functions on the domain having continuous extensions to the boundary. We provide an analogue of the Bergmann-Shilov boundary for finite rank JB*-triples.

Alexey Svyatkovskiy, Sarah Fakhoury, Negar Ghorbani, Todd Mytkowicz

Collaborative software development is an integral part of the modern software development life cycle, essential to the success of large-scale software projects. When multiple developers make concurrent changes around the same lines of code, a merge conflict may occur. Such conflicts stall pull requests and continuous integration pipelines for hours to severa

Yasir J Noori, Shibin Thomas, Sami Ramadan, Victoria K. Greenacre

The development of scalable techniques to make 2D material heterostructures is a major obstacle that needs to be overcome before these materials can be implemented in device technologies industrially. Electrodeposition is an industrially compatible deposition technique that offers unique advantages in scaling 2D heterostructures. In this work, we demonstrate

Jan Kopanski, Krzysztof Rzadca

The ever-increasing gap between compute and I/O performance in HPC platforms, together with the development of novel NVMe storage devices (NVRAM), led to the emergence of the burst buffer concept - an intermediate persistent storage layer logically positioned between random-access main memory and a parallel file system. Despite the development of real-world

Nathaniel Kell, Kevin Sun

We study a general allocation setting where agent valuations are concave additive. In this model, a collection of items must be uniquely distributed among a set of agents, where each agent-item pair has a specified utility. The objective is to maximize the sum of agent valuations, each of which is an arbitrary non-decreasing concave function of the agent's t

Olga Kostyukova, Tatiana Tchemisova

The paper is devoted to the regularization of linear Copositive Programming problems which consists of transforming a problem to an equivalent form, where the Slater condition is satisfied and the strong duality holds. We describe here two regularization algorithms based on the concept of immobile indices and an understanding of the important role these indi

Jani Kastikainen, Sanjit Shashi

We compute correlation functions, specifically 1-point and 2-point functions, in holographic boundary conformal field theory (BCFT) using geodesic approximation. The holographic model consists of a massive scalar field coupled to a Karch-Randall brane -- a rigid boundary in the bulk AdS space. Geodesic approximation requires the inclusion of paths reflecting

Guang Yang, Vicente Estrada-Carpenter, Casey Papovich, Fabio Vito

The cosmic black hole accretion density (BHAD) is critical for our understanding of the formation and evolution of supermassive black holes (BHs). However, at high redshifts ($z>3$), X-ray observations report BHADs significantly ($\sim 10$ times) lower than those predicted by cosmological simulations. It is therefore paramount to constrain the high-$z$ BHAD

Xingdi Yuan

Interactive machine reading comprehension (iMRC) is machine comprehension tasks where knowledge sources are partially observable. An agent must interact with an environment sequentially to gather necessary knowledge in order to answer a question. We hypothesize that graph representations are good inductive biases, which can serve as an agent's memory mechani

Roland Herzog, Estefanía Loayza-Romero

We consider discretized two-dimensional PDE-constrained shape optimization problems, in which shapes are represented by triangular meshes. Given the connectivity, the space of admissible vertex positions was recently identified to be a smooth manifold, termed the manifold of planar triangular meshes. The latter can be endowed with a complete Riemannian metri

James Trimble

We present exact and heuristic algorithms that find, for a given family of graphs, a graph that contains each member of the family as an induced subgraph. For $0 \leq k \leq 6$, we give the minimum number of vertices $f(k)$ in a graph containing all $k$-vertex graphs as induced subgraphs, and show that $16 \leq f(7) \leq 18$. For $0 \leq k \leq 5$, we also g

Soumyendu Sarkar

Question Answering with NLP has progressed through the evolution of advanced model architectures like BERT and BiDAF and earlier word, character, and context-based embeddings. As BERT has leapfrogged the accuracy of models, an element of the next frontier can be the introduction of deep networks and an effective way to train them. In this context, I explored

Daniel Kapec, Prahar Mitra

We study exponentiated soft exchange in $d+2$ dimensional gauge and gravitational theories using the celestial CFT formalism. These models exhibit spontaneously broken asymptotic symmetries generated by gauge transformations with non-compact support, and the effective dynamics of the associated Goldstone "edge" mode is expected to be $d$-dimensional. The int

Shen Peng, Gianpiero Canessa, David Ek, Anders Forsgren

We investigate quasi-Newton methods for minimizing a strictly convex quadratic function which is subject to errors in the evaluation of the gradients. The methods all give identical behavior in exact arithmetic, generating minimizers of Krylov subspaces of increasing dimensions, thereby having finite termination. A BFGS quasi-Newton method is empirically kno

Nourdine Zibouche, Surani M. Gunasekera, Daniel Wolverson, Marcin Mucha-Kruczynski

The new class of Janus two-dimensional (2D) transition-metal dichalcogenides with two different interfaces are currently gaining increasing attention due to their distinct properties different from the typical 2D materials. Here, we show that in-plane anisotropy of a 2D atomic crystal, like ReS$_{2}$ or ReSe$_{2}$, allows formation of a large number of inequ

Emmanuel Kengne, Boris A. Malomed, Wu-Ming Liu

We consider a cubic Gross-Pitaevskii (GP) equation governing the dynamics of Bose-Einstein condensates (BECs) with time-dependent coefficients in front of the cubic term and inverted parabolic potential. Under a special condition imposed on the coefficients, a combination of phase-imprint and modified lens-type transformations converts the GP equation into t

Ulrich A. Brodowsky, Stefan Hougardy, Xianghui Zhong

The $k$-Opt heuristic is a simple improvement heuristic for the Traveling Salesman Problem. It starts with an arbitrary tour and then repeatedly replaces $k$ edges of the tour by $k$ other edges, as long as this yields a shorter tour. We will prove that for 2-dimensional Euclidean Traveling Salesman Problems with $n$ cities the approximation ratio of the $k$

Chantal Mutimukwe, Jean Damascene Twizeyimana, Olga Viberg

The widespread interest in learning analytics (LA) is associated with increased availability of and access to student data where students' actions are monitored, collected, stored and analysed. The availability and analysis of such data is argued to be crucial for improved learning and teaching. Yet, these data can be exposed to misuse, for example to be use

Olivia Eriksson, Andrei Kramer, Federica Milinanni, Pierre Nyquist

In this paper we develop a new method for numerically approximating sensitivities in parameter-dependent ordinary differential equations (ODEs). Our approach, intended for situations where the standard forward and adjoint sensitivity analyses become too computationally costly for practical purposes, is based on the Peano-Baker series from control theory. Usi

Maxine Major, Brian Souza, Joseph DiVita, Kimberly Ferguson-Walter

The performance of artificial intelligence (AI) algorithms in practice depends on the realism and correctness of the data, models, and feedback (labels or rewards) provided to the algorithm. This paper discusses methods for improving the realism and ecological validity of AI used for autonomous cyber defense by exploring the potential to use Inverse Reinforc

Bruno Balthazar, Amit Giveon, David Kutasov, Emil J. Martinec

We propose a new $AdS_3/CFT_2$ duality, in which the bulk string theory has a target spacetime $AdS_3$ times a squashed three-sphere $S^3_\flat$, and the dual $CFT_2$ is a symmetric product of sigma models on $R_\phi\times S^3_\flat$, deformed by a $\phi$-dependent $Z_2$ twist operator. The duality maps the asymptotic region of $AdS_3$ to the region $\phi\to

Alexander M. G. Cox, Sigrid Källblad, Martin Larsson, Sara Svaluto-Ferro

We consider a class of stochastic control problems where the state process is a probability measure-valued process satisfying an additional martingale condition on its dynamics, called measure-valued martingales (MVMs). We establish the `classical' results of stochastic control for these problems: specifically, we prove that the value function for the proble

Mats Gustafsson, Lukas Jelinek, Kurt Schab, Miloslav Capek

A unification of characteristic mode decomposition for all method-of-moment formulations of field integral equations describing free-space scattering is derived. The work is based on an algebraic link between impedance and transition matrices, the latter of which was used in early definitions of characteristic modes and is uniquely defined for all scattering

Negar Arabzadeh, Alexandra Vtyurina, Xinyi Yan, Charles L. A. Clarke

Recent years have seen enormous gains in core IR tasks, including document and passage ranking. Datasets and leaderboards, and in particular the MS MARCO datasets, illustrate the dramatic improvements achieved by modern neural rankers. When compared with traditional test collections, the MS MARCO datasets employ substantially more queries with substantially

Susama Agarwala, Franklin Kenter

Many real world graphs have edges correlated to the distance between them, but, in an inhomogeneous manner. While the Chung-Lu model and the geometric random graph models both are elegant in their simplicity, they are insufficient to capture the complexity of these networks. In this paper, we develop a generalized geometric random graph model that preserves

Abhishek Singh, Alok Mathur, Alka Asthana, Juliet Maina

In this work we review recent works analyzing mobility data and its application in understanding the epidemic dynamics for the COVID-19 pandemic and more. We also discuss privacy-preserving solutions to analyze the mobility data in order to expand its reach towards a wider population.

Eduardo Andreetta Fontana, Fabio Petrillo

Debugging is a relevant task for finding bugs during software development, maintenance, and evolution. During debugging, developers use modern IDE debuggers to analyze variables, step execution, and set breakpoints. Observing IDE debuggers, we find several breakpoint types. However, what are the breakpoint types? The goal of our study is to map the breakpoin

Alec J. Linot, Michael D. Graham

Dissipative partial differential equations that exhibit chaotic dynamics tend to evolve to attractors that exist on finite-dimensional manifolds. We present a data-driven reduced order modeling method that capitalizes on this fact by finding the coordinates of this manifold and finding an ordinary differential equation (ODE) describing the dynamics in this c

N. Casasayas-Barris, J. Orell-Miquel, M. Stangret, L. Nortmann

Ultra-hot Jupiters are highly irradiated gas giants with equilibrium temperatures typically higher than 2000K. Atmospheric studies of these planets have shown that their transmission spectra are rich in metal lines, with some of these metals being ionised due to the extreme temperatures. Here, we use two transit observations of WASP-76b obtained with the CAR

Guangyu Du, Lei Dong, Fabio Duarte, Carlo Ratti

The movements of individuals are fundamental to building and maintaining social connections. This pictorial presents Wanderlust, an experimental three-dimensional data visualization on the universal visitation pattern revealed from large-scale mobile phone tracking data. It explores ways of visualizing recurrent flows and the attractive places they implied.

Fatima Kahil

The irradiance of the Sun is modulated on all time scales. Small-scale solar magnetic elements composed of quiet-Sun network and active region plages contribute to this modulation on solar cycle time scales. The evaluation of their contrast as a function of their magnetic field strength is an important constraint for models of solar irradiance variation. In

Jonathan McCart, Thomas Osburn, Justin Y. J. Burton

We present new developments and comparisons of competing inspiral and waveform models for highly eccentric non-spinning extreme and intermediate mass-ratio inspirals (EMRIs and IMRIs). Starting from our high eccentricity self-force library, we apply the near-identity transform (NIT) technique to rapidly compute highly eccentric self-forced inspirals for the

Ivan Montero, Nikolaos Pappas, Noah A. Smith

Representation learning for text via pretraining a language model on a large corpus has become a standard starting point for building NLP systems. This approach stands in contrast to autoencoders, also trained on raw text, but with the objective of learning to encode each input as a vector that allows full reconstruction. Autoencoders are attractive because

Amin Mahmoodi

We shall develop a notion of amenability for dual Banach algebras, namely weak Connes amenability, which will play the role that weak amenability does for usual Banach algebras

Laurent Joly, Robert H. Meißner, Marcella Iannuzzi, Gabriele Tocci

Osmotic transport in nanoconfined aqueous electrolytes provides new venues for water desalination and "blue energy" harvesting; the osmotic response of nanofluidic systems is controlled by the interfacial structure of water and electrolyte solutions in the so-called electrical double layer (EDL), but a molecular-level picture of the EDL is to a large extent

Arturo Fernández-Pérez, Gilcione Nonato Costa, Rudy Rosas

We define the Milnor number -- as the intersection number of two holomorphic sections -- of a one-dimensional holomorphic foliation $\mathscr{F}$ with respect to a compact connected component $C$ of its singular set. Under certain conditions, we prove that the Milnor number of $\mathscr{F}$ on a three-dimensional manifold with respect to $C$ is invariant by

O. Ruesch, C. Woehler

The efficiency of regolith production is key in understanding the properties of airless surfaces. Debris aprons, of fillets, around rocks are an ubiquitous morphology on many surfaces without atmosphere, which origin and evolution are largely unknown. Here we show that fillet originates from the juxtaposed rock under abrasion and that rocks of different cohe

Vinicius dos Santos, Anderson Yoshiaki Iwazaki, Katia Romero Felizardo, Érica Ferreira de Souza

Background: The software engineering community has increasingly conducted systematic literature reviews (SLR) as a means to summarize evidence from different studies and bring to light the state of the art of a given research topic. While SLR provide many benefits, they also present several problems with punctual solutions for some of them. However, two main

Ashutosh Mani Dixit, Suraj Regmi

Alternative data have a big role, especially during a crisis. The months of stalemate have made us realize their importance for policy responses. In Nepal, the Government has exerted stay put measures, and physical data collection activities are suspended. The confirmed cases of COVID-19 have been increasing steadily and the country is on high alert. In this

Joseph Moscoso, Rafael S. de Souza, Alain Coc, Christian Iliadis

Big bang nucleosynthesis (BBN) is the standard model theory for the production of the light nuclides during the early stages of the universe, taking place for a period of about 20 minutes after the big bang. Deuterium production, in particular, is highly sensitive to the primordial baryon density and the number of neutrino species, and its abundance serves a

Kiran Luecke

This two-page note gives a non-computational derivation of the dual Steenrod algebra as the automorphisms of the formal additive group. Instead of relying on computational tools like spectral sequences and Steenrod operations, the argument uses a few simple universal properties of certain cohomology theories.

Jun Zhai, Cecilia M. Bitz

Arctic sea ice concentration is often coarsely observed and numerically computed despite its importance for polar climate system. In this work we present three machine-learning methods to recover the original high-resolution images from the coarse-grained low-resolution counterparts. The promising results indicate a possibility of extending the application t

Mengying Lei, Aurelie Labbe, Lijun Sun

As a regression technique in spatial statistics, the spatiotemporally varying coefficient model (STVC) is an important tool for discovering nonstationary and interpretable response-covariate associations over both space and time. However, it is difficult to apply STVC for large-scale spatiotemporal analyses due to its high computational cost. To address this

Mohammad Hadi Shekarriz, Seyed Alireza Talebpour Shirazi Fard, Bahman Ahmadi, Mohammad Hassan Shirdareh Haghighi

A vertex coloring of a graph $G$ is distinguishing if non-identity automorphisms do not preserve it. The distinguishing number, $D(G)$, is the minimum number of colors required for such a coloring and the distinguishing threshold, $\theta(G)$, is the minimum number of colors~$k$ such that any arbitrary $k$-coloring is distinguishing. Moreover, $\Phi_k (G)$ i

Joanna Sitnicka, Kyungwha Park, Paweł Skupiński, Krzysztof Grasza

MnBi$_{2}$Te$_{4}/$(Bi$_{2}$Te$_{3}$)$_{n}$ materials system has recently generated strong interest as a natural platform for realization of the quantum anomalous Hall (QAH) state. The system is magnetically much better ordered than substitutionally doped materials, however, the detrimental effects of certain disorders are becoming increasingly acknowledged.

I. M. Burbano, Francisco Calderón

The normalization in the path integral approach to quantum field theory, in contrast with statistical field theory, can contain physical information. The main claim of this paper is that the inner product on the space of field configurations, one of the fundamental pieces of data required to be added to quantize a classical field theory, determines the norma

Mees van de Kerkhof, Irina Kostitsyna, Maarten Löffler

We prove that circle graphs (intersection graphs of circle chords) can be embedded as intersection graphs of rays in the plane with polynomial-size bit complexity. We use this embedding to show that the global curve simplification problem for the directed Hausdorff distance is NP-hard. In this problem, we are given a polygonal curve $P$ and the goal is to fi

Sayak Ghosh, Thomas G. Kiely, Arkady Shekhter, F. Jerzembeck

Recent experiments suggest that the superconducting order parameter of Sr$_2$RuO$_4$ has two components. A two-component order parameter has multiple degrees of freedom in the superconducting state that can result in low-energy collective modes or the formation of domain walls -- a possibility that would explain a number of experimental observations includin

J. Racker

We extend to the highly degenerate case a recent approach for analyzing the sources of CP violation in baryogenesis models with quasi-degenerate neutrinos. In this approach an expansion of the resummed propagator around the poles is plugged into a quantum field theory model of neutrino oscillations and a source term for the time evolution of the lepton asymm

Saurav Das, Anson Hook

In the early universe, evaporating black holes heat up the surrounding plasma and create a temperature profile around the black hole that can be more important than the black hole itself. As an example, we demonstrate how the hot plasma surrounding evaporating black holes can efficiently produce monopoles via the Kibble-Zurek mechanism. In the case where bla

Sofija Markovic, Andjela Rodic, Igor Salom, Ognjen Milicevic

Determinants of COVID-19 clinical severity are commonly assessed by transverse or longitudinal studies of the fatality counts. However, the fatality counts depend both on disease clinical severity and transmissibility, as more infected also lead to more deaths. Moreover, fatality counts (and related measures such as Case Fatality Rate) are dynamic quantities

Chang Liu, David A. Lowe

The extended-BMS algebra of asymptotically flat spacetime contains an SO(3,1) subgroup that acts by conformal transformations on the celestial sphere. It is of interest to study the representations of this subgroup associated with gravitons. To reduce the equation of motion to a Schrodinger-like equation it is necessary to impose a non-covariant gauge condit

Raphael Keusch, Hans-Andrea Loeliger

Normals with unknown variance (NUV) can represent many useful priors and blend well with Gaussian models and message passing algorithms. NUV representations of sparsifying priors have long been known, and NUV representations of binary (and M-level) priors have been proposed very recently. In this document, we propose NUV representations of half-space constra

Matjaž Krnc, Nevena Pivač

Graph searching is one of the simplest and most widely used tools in graph algorithms. Every graph search method is defined using some particular selection rule, and the analysis of the corresponding vertex orderings can aid greatly in devising algorithms, writing proofs of correctness, or recognition of various graph families. We study graphs where the sets

Muxin Han

We present an improved formulation of 4-dimensional Lorentzian spinfoam quantum gravity with cosmological constant. The construction of spinfoam amplitudes uses the state-integral model of PSL(2,$\mathbb{C}$) Chern-Simons theory and the implementation of simplicity constraint. The formulation has 2 key features: (1) spinfoam amplitudes are all finite, and (2

Roman Shapovalov, David Novotny, Benjamin Graham, Patrick Labatut

We tackle the problem of monocular 3D reconstruction of articulated objects like humans and animals. We contribute DensePose 3D, a method that can learn such reconstructions in a weakly supervised fashion from 2D image annotations only. This is in stark contrast with previous deformable reconstruction methods that use parametric models such as SMPL pre-train

Po Hu, Igor Kriz, Petr Somberg

We explicitly construct and investigate a number of examples of $\mathbb{Z}/p^r$-equivariant formal group laws and complex-oriented spectra, including those coming from elliptic curves and $p$-divisible groups, as well as some other related examples.

Daniella Bar-Lev, Itai Orr, Omer Sabary, Tuvi Etzion

DNA-based storage is an emerging technology that enables digital information to be archived in DNA molecules. This method enjoys major advantages over magnetic and optical storage solutions such as exceptional information density, enhanced data durability, and negligible power consumption to maintain data integrity. To access the data, an information retriev

Kazumasa Fujiwara

In this manuscript, in the $L^1$ scaling critical case, a lifespan estimate of solutions to the Cauchy problem for non-gauge invariant semilinear semirelativistic equations is considered. The lifespan estimate is given by the modified test function method with a fractional Laplace operator. The main obstacle to obtaining the lifespan estimate is the non-loca

Erik Plauschinn

The tadpole conjecture by Bena, Blaback, Grana and Lust effectively states that for string-theory compactifications with a large number of complex-structure moduli, not all of these moduli can be stabilized by fluxes. In this note we study this conjecture in the large complex-structure regime using statistical data obtained by Demirtas, Long, McAllister and

Petra Shih, Timothy C. Berkelbach

We present a vibrational dynamical mean-field theory (VDMFT) of the dynamics of atoms in solids with anharmonic interactions. Like other flavors of DMFT, VDMFT maps the dynamics of a periodic anharmonic lattice of atoms onto those of a self-consistently defined impurity problem with local anharmonicity and coupling to a bath of harmonic oscillators. VDMFT is

David P. Roberts, Fernando Rodriguez Villegas

Survey of hypergeometric motives, with a focus on their source varieties, Hodge numbers, and L-functions.

Dor Gabay, Cheolhee Han, Pedro L. S. Lopes, Ian Affleck

The multichannel Kondo model supports effective anyons on the partially screened impurity, as suggested by its fractional impurity entropy. It was recently demonstrated for the multi-impurity chiral Kondo model, that scattering of an electron through the impurities depends on the anyon's total fusion channel. Here we study the correlation between impurity-sp

Jessica Rodrigues da Silva, Helena de Medeiros Caseli

Sense representations have gone beyond word representations like Word2Vec, GloVe and FastText and achieved innovative performance on a wide range of natural language processing tasks. Although very useful in many applications, the traditional approaches for generating word embeddings have a strict drawback: they produce a single vector representation for a g

Samantha D'Alonzo, Max Tegmark

We present an automated method for measuring media bias. Inferring which newspaper published a given article, based only on the frequencies with which it uses different phrases, leads to a conditional probability distribution whose analysis lets us automatically map newspapers and phrases into a bias space. By analyzing roughly a million articles from roughl