March 2020 arXiv papers

Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf

In order to anticipate rare and impactful events, we propose to quantify the worst-case risk under distributional ambiguity using a recent development in kernel methods -- the kernel mean embedding. Specifically, we formulate the generalized moment problem whose ambiguity set (i.e., the moment constraint) is described by constraints in the associated reprodu

Sven Husmann, Antoniya Shivarova, Rick Steinert

The recent advancements in computational power and machine learning algorithms have led to vast improvements in manifold areas of research. Especially in finance, the application of machine learning enables both researchers and practitioners to gain new insights into financial data and well-studied areas such as company classification. In our paper, we demon

Zhekun Luo, Devin Guillory, Baifeng Shi, Wei Ke

Weakly-supervised action localization requires training a model to localize the action segments in the video given only video level action label. It can be solved under the Multiple Instance Learning (MIL) framework, where a bag (video) contains multiple instances (action segments). Since only the bag's label is known, the main challenge is assigning whi

Roman Stasiński, Julien Berestycki, Bastien Mallein

We consider a branching Brownian motion in $\mathbb{R}^d$. We prove that there exists a random subset $Θ$ of $\mathbb{S}^{d-1}$ such that the limit of the derivative martingale exists simultaneously for all directions $θ\in Θ$ almost surely. This allows us to define a random measure on $\mathbb{S}^{d-1}$ whose density is given by the derivative martingale. T

Chaoran Hu, Mark Elbroch, Thomas Meyer, Vladimir Pozdnyakov

Statistical modeling of animal movement is of critical importance. The continuous trajectory of an animal's movements is only observed at discrete, often irregularly spaced time points. Most existing models cannot handle the unequal sampling interval naturally and/or do not allow inactivity periods such as resting or sleeping. The recently proposed movin

Yu Tang, Li Jin

Modern network systems, such as transportation and communication systems, are prone to cyber-physical disruptions and thus suffer efficiency loss. This paper studies network resiliency, in terms of throughput, and develops resilient control to improve throughput. We consider single-commodity networks that admit congestion propagation. We also apply a Markov

Mohammed Ibrahim, Susan Gauch, Omar Salman, Mohammed Alqahatani

Open-Access and Collaborative Consumer Health Vocabulary (OAC CHV, or CHV for short), is a collection of medical terms written in plain English. It provides a list of simple, easy, and clear terms that laymen prefer to use rather than an equivalent professional medical term. The National Library of Medicine (NLM) has integrated and mapped the CHV terms to th

Luca Fresta

We study discrete random Schrödinger operators via the supersymmetric formalism. We develop a cluster expansion that converges at both strong and weak disorder. We prove the exponential decay of the disorder-averaged Green's function and the smoothness of the local density of states either at weak disorder and at energies in proximity of the unperturbed

Brahim Allal, Genni Fragnelli

In this paper, we analyze the null controllability property for a degenerate parabolic equation involving memory terms with a locally distributed control. We first derive a null controllability result for a nonhomogeneous degenerate heat equation via new Carleman estimates with weighted time functions that do not blow up at t= 0. Then this result is successf

Jongchon Kim

We develop almost-orthogonality principles for maximal functions associated with averages over line segments and directional singular integrals. Using them, we obtain sharp $L^2$-bounds for these maximal functions when the underlying direction set is equidistributed in $\mathbb{S}^{n-1}$.

Zhishen Tong, Zhentao Liu, Jian Wang, Xia Shen

By encoding the high-dimensional light-field imaging information into a detectable two-dimensional speckle plane, ghost imaging camera via sparsity constraints (GISC camera) can directly catch the high-dimensional light-field imaging information with only one snapshot. This makes it worth to revisit the spatial resolution limit of this optical imaging system

Amine Mhedhbi, Pranjal Gupta, Shahid Khaliq, Semih Salihoglu

Graph database management systems (GDBMSs) are highly optimized to perform fast traversals, i.e., joins of vertices with their neighbours, by indexing the neighbourhoods of vertices in adjacency lists. However, existing GDBMSs have system-specific and fixed adjacency list structures, which makes each system efficient on only a fixed set of workloads. We desc

Victoria L. Martin, Andrew Svesko

In this note we compute the 1-loop partition function of spin-$s$ fields on Euclidean de Sitter space $S^{2n+1}$ using the quasinormal mode method. Instead of computing the quasinormal mode frequencies from scratch, we use the analytic continuation prescription $L_{\text{AdS}}\to iL_{\text{dS}}$, appearing in the dS/CFT correspondence, and Wick rotate the no

Yusuke Sakumoto, Masaki Aida

The spectral graph theory provides an algebraical approach to investigate the characteristics of weighted networks using the eigenvalues and eigenvectors of a matrix (e.g., normalized Laplacian matrix) that represents the structure of the network. However, it is difficult for large-scale and complex networks (e.g., social network) to represent their structur

Carlos Areces, Raul Fervari

In this paper we introduce sound and strongly complete axiomatizations for XPath with data constraints extended with hybrid operators. First, we present HXPath=, a multi-modal version of XPath with data, extended with nominals and the hybrid operator @. Then, we introduce an axiomatic system for HXPath=, and we prove it is strongly complete with respect to t

Ayush Tewari, Mohamed Elgharib, Gaurav Bharaj, Florian Bernard

StyleGAN generates photorealistic portrait images of faces with eyes, teeth, hair and context (neck, shoulders, background), but lacks a rig-like control over semantic face parameters that are interpretable in 3D, such as face pose, expressions, and scene illumination. Three-dimensional morphable face models (3DMMs) on the other hand offer control over the s

L. Aragon-Muñoz, G. Chacon-Acosta, H. Hernandez-Hernandez

We study the quantum tunnel effect through a potential barrier employing a semiclassical formulation of quantum mechanics based on expectation values of configuration variables and quantum dispersions as dynamical variables. The evolution of the system is given in terms of a dynamical system for which we are able to determine effective trajectories for indiv

Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink

Existing autonomous robot navigation systems allow robots to move from one point to another in a collision-free manner. However, when facing new environments, these systems generally require re-tuning by expert roboticists with a good understanding of the inner workings of the navigation system. In contrast, even users who are unversed in the details of robo

Antoine Paris, Hamed Mirghasemi, Ivan Stupia, Luc Vandendorpe

Motivated by applications such as on-device collaborative neural network inference, this work investigates edge-facilitated collaborative fog computing - in which edge-devices collaborate with each other and with the edge of the network to complete a processing task - to augment the computing capabilities of individual edge-devices while optimizing the colla

Rodica Dinu, Christopher Eur, Tim Seynnaeve

We generalize the Tutte polynomial of a matroid to a morphism of matroids via the K-theory of flag varieties. We introduce two different generalizations, and demonstrate that each has its own merits, where the trade-off is between the ease of combinatorics and geometry. One generalization recovers the Las Vergnas Tutte polynomial of a morphism of matroids, w

Hector Sanjuan, Samuli Poyhtari, Pedro Teixeira, Ioannis Psaras

We study Merkle-DAGs as a transport and persistence layer for Conflict-Free Replicated Data Types (CRDTs), coining the term Merkle-CRDTs and providing an overview of the different concepts, properties, advantages and limitations involved. We show how Merkle-DAGs can act as logical clocks giving Merkle-CRDTs the potential to greatly simplify the design and im

Goce Chadzitaskos, Miloslav Havlíček, Jiří Patera

We derive the explicit form of eigenvectors of selfadjoint extension $H_ξ$, parametrized by $ξ\in \langle 0,π),$ of differential expression $ H=-\frac{d^2 }{d x^2} + \frac{x^2 }{4}$ together with the spectrum $σ(H_ξ)$ on the space $L^2(\mathbb{R}^+).$ For each $ξ$ the set of eigenvectors form an orthonormal basis of $L^2(\mathbb{R}^+).$

Oleg Korobkin, Ryan Wollaeger, Christopher Fryer, Aimee L. Hungerford

The detailed observations of GW170817 proved for the first time directly that neutron star mergers are a major production site of heavy elements. The observations could be fit by a number of simulations that qualitatively agree, but can quantitatively differ (e.g. in total r-process mass) by an order of magnitude. We categorize kilonova ejecta into several t

Ricardo A. E. Mendes

Given an orthogonal representation of a compact group, we show that any element of the connected component of the isometry group of the orbit space lifts to an equivariant isometry of the original Euclidean space. Corollaries include a simple formula for this connected component, which applies to ``most'' representations.

Alan Morningstar, Vedika Khemani, David A. Huse

We study a stochastic lattice gas of particles in one dimension with strictly finite-range interactions that respect the fracton-like conservation laws of total charge and dipole moment. As the charge density is varied, the connectivity of the system's charge configurations under the dynamics changes qualitatively. We find two distinct phases: Near half

Maria N. Potkina, Igor S. Lobanov, Hannes Jónsson, Valery M. Uzdin

Calculations of skyrmions in antiferromagnets (AFMs) are presented, and their properties compared with skyrmions in corresponding ferromagnets (FMs). The rates of skyrmion collapse and escape through the boundary of a track, as well as the binding to and collapse at a non-magnetic impurity, are calculated as a function of applied magnetic field. The activati

Patrik Knopf, Andrea Signori

The Cahn--Hilliard equation is one of the most common models to describe phase segregation processes in binary mixtures. In recent times, various dynamic boundary conditions have been introduced to model interactions of the materials with the boundary more precisely. To take long-range interactions of the materials into account, we propose a new model consis

Robert Dougherty-Bliss, Doron Zeilberger

Inspired by the recent pioneering work, dubbed "The Ramanujan Machine" by Raayoni et al. (arXiv:1907.00205), we (automatically) [rigorously] prove some of their conjectures regarding the exact values of some specific infinite continued fractions, and generalize them to evaluate infinite families (naturally generalizing theirs). Our work complements t

Arie Bodek, Tejin Cai

Precise modeling of neutrino interactions on nuclear targets is essential for neutrino oscillations experiments. The modeling of the energy of final state particles in quasielastic (QE) scattering and resonance production on bound nucleons requires knowledge of both the removal energy of the initial state bound nucleon as well as the average Coulomb and nucl

Peter Cameron, Maciej Dunajski

We show that the causal properties of asymptotically flat spacetimes depend on their dimensionality: while the time-like future of any point in the past conformal infinity $\mathcal{I}^-$ contains the whole of the future conformal infinity $\mathcal{I}^+$ in $(2+1)$ and $(3+1)$ dimensional Schwarzschild spacetimes, this property (which we call the Penrose pr

Ryan M. Shifler, Camron Withrow

We give a formula in terms of Young diagrams to calculate the minimum positive integer $d$ such that $q^d$ appears in the quantum product of two Schubert classes for the submaximal isotropic Grassmannians in Types B and C. We do this by studying curve neighborhoods. We compute curve neighborhoods in several combinatorial models including $k$-strict partition

Jonathan Noky, Johannes Gooth, Yan Sun, Claudia Felser

The quantum Hall effect in a 2D electron system expresses a topological invariant, leading to a quantized conductivity. The thermal Hall and thermoelectric Nernst conductances in two dimensions are also reported to be quantized in specific systems. However, a comprehensive study of these quantities within one formalism for quantum Hall systems is so far elus

Ratnabali Pal, Arif Ahmed Sekh, Samarjit Kar, Dilip K. Prasad

The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applyi

Xiaying Wang, Michael Hersche, Batuhan Tömekce, Burak Kaya

This paper presents an accurate and robust embedded motor-imagery brain-computer interface (MI-BCI). The proposed novel model, based on EEGNet, matches the requirements of memory footprint and computational resources of low-power microcontroller units (MCUs), such as the ARM Cortex-M family. Furthermore, the paper presents a set of methods, including tempora

L. N. Fletcher, G. S. Orton, T. K. Greathouse, J. H. Rogers

We present multi-wavelength measurements of the thermal, chemical, and cloud contrasts associated with the visibly dark formations (also known as 5-$μ$m hot spots) and intervening bright plumes on the boundary between Jupiter's Equatorial Zone (EZ) and North Equatorial Belt (NEB). Observations made by the TEXES 5-20 $μ$m spectrometer at the Gemini North

Nidhi Rastogi, Mohammed J. Zaki

Existing patient data analytics platforms fail to incorporate information that has context, is personal, and topical to patients. For a recommendation system to give a suitable response to a query or to derive meaningful insights from patient data, it should consider personal information about the patient's health history, including but not limited to th

Suresh Thapa, Sydney R. Provence, Devin Jessup, Jason Lapano

Hybrid oxide molecular beam epitaxy (hMBE), a thin-film deposition technique in which transition metal cations are delivered using a metal-organic precursor, has emerged as the state-of-the-art approach to the synthesis of electronic-grade complex oxide films with a stoichiometric growth window. However, numerous questions remain regarding the chemical mecha

Michael Hendriksen, Nils Kapust

The concept of $k$-compatibility measures how many phylogenetic trees it would take to display all splits in a given set. A set of trees that display every single possible split is termed a \textit{universal tree set}. In this note, we find $A(n)$, the minimal size of a universal tree set for $n$ taxa. By normalising the $k$-compatibility using $A(n)$, one c

Marco Valentino, Mokanarangan Thayaparan, André Freitas

This paper presents a novel framework for reconstructing multi-hop explanations in science Question Answering (QA). While existing approaches for multi-hop reasoning build explanations considering each question in isolation, we propose a method to leverage explanatory patterns emerging in a corpus of scientific explanations. Specifically, the framework ranks

Scott Viteri, Simon DeDeo

Mathematical proofs are both paradigms of certainty and some of the most explicitly-justified arguments that we have in the cultural record. Their very explicitness, however, leads to a paradox, because the probability of error grows exponentially as the argument expands. When a mathematician encounters a proof, how does she come to believe it? Here we show

Congzheng Song, Ananth Raghunathan

Embeddings are functions that map raw input data to low-dimensional vector representations, while preserving important semantic information about the inputs. Pre-training embeddings on a large amount of unlabeled data and fine-tuning them for downstream tasks is now a de facto standard in achieving state of the art learning in many domains. We demonstrate th

Andrea Di Lorenzo, Damiano Fulghesu, Angelo Vistoli

We compute the integral Chow ring of the stack of smooth, non-hyperelliptic curves of genus three. We obtain this result by computing the integral Chow ring of the stack of smooth plane quartics, by means of equivariant intersection theory.

C. Malacaria, P. Jenke, O. J. Roberts, C. A. Wilson-Hodge

We review more than 10 years of continuous monitoring of accreting X-ray pulsars with the all-sky Gamma-ray Burst Monitor (GBM) aboard the Fermi Gamma-ray Space Telescope. Our work includes data from the start of GBM operations in August 2008, through to November 2019. Pulsations from 39 accreting pulsars are observed over an energy range of $10-50\,$keV by

Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan

We propose a novel reinforcement learning-based approach for adaptive and iterative feature selection. Given a masked vector of input features, a reinforcement learning agent iteratively selects certain features to be unmasked, and uses them to predict an outcome when it is sufficiently confident. The algorithm makes use of a novel environment setting, corre

Jiapeng Zhu, Yujun Shen, Deli Zhao, Bolei Zhou

Recent work has shown that a variety of semantics emerge in the latent space of Generative Adversarial Networks (GANs) when being trained to synthesize images. However, it is difficult to use these learned semantics for real image editing. A common practice of feeding a real image to a trained GAN generator is to invert it back to a latent code. However, exi

João P. Abrantes, Arnaldo J. Abrantes, Frans A. Oliehoek

Evolution gave rise to human and animal intelligence here on Earth. We argue that the path to developing artificial human-like-intelligence will pass through mimicking the evolutionary process in a nature-like simulation. In Nature, there are two processes driving the development of the brain: evolution and learning. Evolution acts slowly, across generations

Cesar Manchein, Eduardo L. Brugnago, Rafael M. da Silva, Carlos F. O. Mendes

In this work we analyse the growth of the cumulative number of confirmed infected cases by the COVID-19 until March 27th, 2020, from countries of Asia, Europe, North and South America. Our results show (i) that power-law growth is observed for all countries; (ii) by using the distance correlation, that the power-law curves between countries are statistically

Zhou Fan, Yi Sun, Tianhao Wang, Yihong Wu

We study the non-convex optimization landscape for maximum likelihood estimation in the discrete orbit recovery model with Gaussian noise. This model is motivated by applications in molecular microscopy and image processing, where each measurement of an unknown object is subject to an independent random rotation from a rotational group. Equivalently, it is a

Alexander Zderic, Ann-Marie Madigan

Axisymmetric disks of high eccentricity, low mass bodies on near-Keplerian orbits are unstable to an out-of-plane buckling. This "inclination instability" exponentially grows the orbital inclinations, raises perihelia distances and clusters in argument of perihelion. Here we examine the instability in a massive primordial scattered disk including the

Xiao Lei Zhang, Anish Agarwal

The study of unsupervised learning can be generally divided into two categories: imitation learning and reinforcement learning. In imitation learning the machine learns by mimicking the behavior of an expert system whereas in reinforcement learning the machine learns via direct environment feedback. Traditional deep reinforcement learning takes a significant

Zhi-Qiang You, Xing-Jiang Zhu, Gregory Ashton, Eric Thrane

Gravitational-wave astronomy provides a unique new way to study the expansion history of the Universe. In this work, we investigate the impact future gravitational-wave observatories will have on cosmology. Third-generation observatories like the Einstein Telescope and Cosmic Explorer will be sensitive to essentially all of the binary black hole coalescence

Rodrigo Agerri, Iñaki San Vicente, Jon Ander Campos, Ander Barrena

Word embeddings and pre-trained language models allow to build rich representations of text and have enabled improvements across most NLP tasks. Unfortunately they are very expensive to train, and many small companies and research groups tend to use models that have been pre-trained and made available by third parties, rather than building their own. This is

Camille L. Latune, Ilya Sinayskiy, Francesco Petruccione

The performances of quantum thermometry in thermal equilibrium together with the output power of certain class of quantum engines share a common characteristic: both are determined by the heat capacity of the probe or working medium. After noticing that the heat capacity of spin ensembles can be significantly modified by collective coupling with a thermal ba

Brendan O'Connor, Paz Beniamini, Chryssa Kouveliotou

Observational follow-up of well localized short gamma-ray bursts (SGRBs) has left $20-30\%$ of the population without a coincident host galaxy association to deep optical and NIR limits ($\gtrsim 26$ mag). These SGRBs have been classified as observationally hostless due to their lack of strong host associations. It has been argued that these hostless SGRBs c

David Andriot, Niccolò Cribiori, David Erkinger

We consider the swampland distance and de Sitter conjectures, of respective order one parameters $λ$ and $c$. Inspired by the recent Trans-Planckian Censorship conjecture (TCC), we propose a generalization of the distance conjecture, which bounds $λ$ to be a half of the TCC bound for $c$, i.e. $λ\geq \frac{1}{2}\sqrt{\frac{2}{3}}$ in 4d. In addition, we prop

B. P. Gompertz, R. Cutter, D. Steeghs, D. K. Galloway

We report the results of optical follow-up observations of 29 gravitational-wave triggers during the first half of the LIGO-Virgo Collaboration (LVC) O3 run with the Gravitational-wave Optical Transient Observer (GOTO) in its prototype 4-telescope configuration (GOTO-4). While no viable electromagnetic counterpart candidate was identified, we estimate our 3D

Hui Zhang, Jinfeng Liao, Enke Wang, Qian Wang

Exploring the nature of exotic multiquark candidates such as the $X(3872)$ plays a pivotal role in understanding quantum chromodynamics (QCD). Despite significant efforts, consensus on their internal structures is still lacking. As a prime example, it remains a pressing open question to decipher the $X(3872)$ state between two popular exotic configurations:

Forrest W. Glines, Brian W. O'Shea, G. Mark Voit

In cool-core galaxy clusters with central cooling times much shorter than a Hubble time, condensation of the ambient central gas is regulated by a heating mechanism, probably an active galactic nucleus (AGN). Previous analytical work has suggested that certain radial distributions of heat input may result in convergence to a quasi-steady global state that do

Hila Glanz, Hagai B. Perets

The dynamical evolution of triple stellar systems could induce the formation of compact binaries and binary mergers. Common envelope (CE) evolution, which plays a major role in the evolution of compact binary systems, can similarly play a key role in the evolution of triples. Here we use hydrodynamical simulations coupled with few-body dynamics to provide th

Michael Hanke, Andreas Koch, Zdenek Prudil, Eva K. Grebel

We present chemodynamical links between the present-day Milky Way halo field star population and Galactic globular clusters (GCs) using a dataset that combines information from the $\rm{\it Gaia}$ space mission and the Sloan Digital Sky Survey (SDSS-IV, DR14). Moreover, we incorporated a sample of halo giant stars with a distinct chemical signature (strong C

Mattias Blennow, Monojit Ghosh, Tommy Ohlsson, Arsenii Titov

We review and investigate lepton flavor models, stemming from discrete non-Abelian flavor symmetries, described by one or two free model parameters. First, we confront eleven one- and seven two-parameter models with current results on leptonic mixing angles from global fits to neutrino oscillation data. We find that five of the one- and five of the two-param

Nathan Seiberg, Shu-Heng Shao

We extend our exploration of nonstandard continuum quantum field theories in 2+1 dimensions to 3+1 dimensions. These theories exhibit exotic global symmetries, a peculiar spectrum of charged states, unusual gauge symmetries, and surprising dualities. Many of the systems we study have a known lattice construction. In particular, one of them is a known gapless

Laura Lopez-Honorez, Olga Mena, Sergio Palomares-Ruiz, Pablo Villanueva-Domingo

The observation of space-time variations in fundamental constants would provide strong evidence for the existence of new light degrees of freedom in the theory of Nature. Robustly constraining such scenarios requires exploiting observations that span different scales and probe the state of the Universe at different epochs. In the context of cosmology, both t

Clément L. Canonne, Gautam Kamath, Thomas Steinke

A key tool for building differentially private systems is adding Gaussian noise to the output of a function evaluated on a sensitive dataset. Unfortunately, using a continuous distribution presents several practical challenges. First and foremost, finite computers cannot exactly represent samples from continuous distributions, and previous work has demonstra

Alex Berke, Michiel Bakker, Praneeth Vepakomma, Kent Larson

Governments and researchers around the world are implementing digital contact tracing solutions to stem the spread of infectious disease, namely COVID-19. Many of these solutions threaten individual rights and privacy. Our goal is to break past the false dichotomy of effective versus privacy-preserving contact tracing. We offer an alternative approach to ass

Zongjian Fan, Ryan Bunk, Guangying Wang, Jerry M. Woodall

Novel ohmic contacts to n-ZnSe are demonstrated using single crystal Al films deposited on epitaxially grown ZnSe (100) by molecular beam epitaxy (MBE). Electron Backscatter Diffraction (EBSD) confirmed the single crystalline structure of the Al films. The (110)-oriented Al layer was rotated rotated 45$^\circ$ relative to substrate to match the ZnSe (100) la

Zhuoqian Yang, Wentao Zhu, Wayne Wu, Chen Qian

We present a lightweight video motion retargeting approach TransMoMo that is capable of transferring motion of a person in a source video realistically to another video of a target person. Without using any paired data for supervision, the proposed method can be trained in an unsupervised manner by exploiting invariance properties of three orthogonal factors

Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song

We propose a model-free algorithm for learning efficient policies capable of returning table tennis balls by controlling robot joints at a rate of 100Hz. We demonstrate that evolutionary search (ES) methods acting on CNN-based policy architectures for non-visual inputs and convolving across time learn compact controllers leading to smooth motions. Furthermor

Anirudh Vemula, J. Andrew Bagnell

Trajectory optimization is an important tool for control and planning of complex, underactuated robots, and has shown impressive results in real world robotic tasks. However, in applications where the cost function to be optimized is non-smooth, modern trajectory optimization methods have extremely slow convergence. In this work, we present TRON, an iterativ

Dmitry B. Uskov, Paul M. Alsing

We suggest a dynamical vector model of entanglement in a three qubit system based on isomorphism between $su(4)$ and $so(6)$ Lie algebras. Generalizing Plücker-type description of three-qubit local invariants we introduce three pairs of real-valued $3D$ vector (denoted here as $A_{R,I}$ , $B_{R,I}$ and $C_{R,I}$). Magnitudes of these vectors determine two- a

Paul Bryan, Mohammad N. Ivaki, Julian Scheuer

We employ curvature flows without global terms to seek strictly convex, spacelike solutions of a broad class of elliptic prescribed curvature equations in the simply connected Riemannian spaceforms and the Lorentzian de Sitter space, where the prescribed function may depend on the position and the normal vector. In particular, in the Euclidean space we solve

Petra Tomanová, Vladimír Holý

Arrivals in queueing systems are typically assumed to be independent and exponentially distributed. Our analysis of an online bookshop, however, shows that there is an autocorrelation structure present. First, we adjust the inter-arrival times for diurnal and seasonal patterns. Second, we model adjusted inter-arrival times by the generalized autoregressive s

Mihail Bazhba, Jose Blanchet, Chang-Han Rhee, Bert Zwart

We prove a sample path large deviation principle (LDP) with sub-linear speed for unbounded functionals of certain Markov chains induced by the Lindley recursion. The LDP holds in the Skorokhod space $\mathbb{D}[0,T]$ equipped with the $M_1'$ topology. Our technique hinges on a suitable decomposition of the Markov chain in terms of regeneration cycles. Ea

Evelyn Herberg, Michael Hinze

We consider a parabolic optimal control problem with an initial measure control. The cost functional consists of a tracking term corresponding to the observation of the state at final time. Instead of a regularization term in the cost functional, we follow an approach by E. Casas and K. Kunisch and consider a bound on the measure norm of the initial control.

Zhengyu Hu

We prove that the moduli b-divisor of an lc-trivial fibration from a log canonical pair is log abundant. The result follows from a theorem on the restriction of the moduli b-divisor, based on a theory of lc-trivial morphisms, which allows us to treat $\mathbb{R}$-divisors and proper morphisms possibly with disconnected fibres. We also prove a theorem on exte

Aalok Ahluwalia, Massimiliano Di Penta, Davide Falessi

To develop and train defect prediction models, researchers rely on datasets in which a defect is attributed to an artifact, e.g., a class of a given release. However, the creation of such datasets is far from being perfect. It can happen that a defect is discovered several releases after its introduction: this phenomenon has been called "dormant defects&

Thomas Bothner

This article is firstly a historic review of the theory of Riemann-Hilbert problems with particular emphasis placed on their original appearance in the context of Hilbert's 21st problem and Plemelj's work associated with it. The secondary purpose of this note is to invite a new generation of mathematicians to the fascinating world of Riemann-Hilbert

Maximilian N. Günther, Tansu Daylan

We present allesfitter, a public and open-source python software for flexible and robust inference of stars and exoplanets given photometric and radial velocity data. Allesfitter offers a rich selection of orbital and transit/eclipse models, accommodating multiple exoplanets, multi-star systems, transit-timing variations, phase curves, stellar variability, s

Xia Chen, Aurélien Deya, Cheng Ouyang, Samy Tindel

The theory of regularity structures enables the definition of the following parabolic Anderson model in a very rough environment: $\partial_{t} u_{t}(x) = \frac12 Δu_{t}(x) + u_{t}(x) \, \dot W_{t}(x)$, for $t\in\mathbb{R}_{+}$ and $x\in \mathbb{R}^{d}$, where $\dot W_{t}(x)$ is a Gaussian noise whose space time covariance function is singular. In this rough

Matias del Hoyo, Daniel López Garcia

We present Hausdorff versions for Lie Integration Theorems 1 and 2 and apply them to study Hausdorff symplectic groupoids arising from Poisson manifolds. To prepare for these results we include a discussion on Lie equivalences and propose an algebraic approach to holonomy. We also include subsidiary results, such as a generalization of the integration of sub

Jon A. Sjogren

The space of complete orthonormal frames in Euclidean space is not path connected. In fact it has exactly two path components, containing respectively the coordinate frame of n standard coordinates and the frame with two coordinates reversed. The matrices corresponding to these frames have determinant one and minus one respectively. We wish to avoid the impl

Giorgio Ferrari, Hanwu Li, Frank Riedel

In this paper, we study an irreversible investment problem under Knightian uncertainty. In a general framework, in which Knightian uncertainty is modeled through a set of multiple priors, we prove existence and uniqueness of the optimal investment plan, and derive necessary and sufficient conditions for optimality. This allows us to construct the optimal pol

Erick Schulz, Ralf Hiptmair

We develop a framework shedding light on common features of coupled variational formulations arising in electromagnetic scattering and acoustics. We show that spurious resonances haunting coupled domain-boundary formulations based on direct boundary integral equations of the first kind originate from the formal structure of their Calderon identities. Using t

Chris J Mitchell

A recently proposed group key distribution scheme known as UMKESS, based on secret sharing, is shown to be insecure. Not only is it insecure, but it does not always work, and the rationale for its design is unsound. UMKESS is the latest in a long line of flawed group key distribution schemes based on secret sharing techniques.

Sudhansu S. Mandal, T. V. Ramakrishnan

Recent experiments on disordered superconductors find that the superfluid density $n_s(T)$ decreases dramatically and characteristically with disorder, differently from what is expected for a mean order parameter field or BCS, amplitude only, picture for the superconductor. We describe here a new microscopic free energy functional which explicitly describes

Dung Van Vu, Minh Hoang Trinh, Hyo-Sung Ahn

This paper studies a leader-follower formation tracking problem where the leaders are moving at the same unknown bounded velocity. A distance-based control law is proposed for follower agents to maintain the desired distances in the formation and move at the leaders' velocity. The control law consists of a component to handle the uncertainty of the leade

J. D. Dantas, J. J. Rodrigues

We study cosmological models involving a single real scalar field that has an equation of state parameter which evolves with cosmic time. We highlight some common parametrizations for the equation of state as a function of redshift in the context of twinlike theories. The procedure is used to introduce different models that have the same acceleration paramet

Nils E. Strand, Rueih-Sheng Fu, Todd R. Gingrich

It is well-known that Brownian ratchets can exhibit current reversals, wherein the sign of the current switches as a function of the driving frequency. We introduce a spatial discretization of such a two-dimensional Brownian ratchet to enable spectral methods that efficiently compute those currents. These discrete-space models provide a convenient way to stu

Sérgio Vinicius M. C. B. Xavier, Pedro V. P. Cunha, Luís C. B. Crispino, Carlos A. R. Herdeiro

Celebrating the centennial of its first experimental test, the theory of General Relativity (GR) has successfully and consistently passed all subsequent tests with flying colours. It is expected, however, that at certain scales new physics, in particular in the form of quantum corrections, will emerge, changing some of the predictions of GR, which is a class

Otis Chodosh, Kyeongsu Choi, Christos Mantoulidis, Felix Schulze

We show that the mean curvature flow of generic closed surfaces in $\mathbb{R}^{3}$ avoids asymptotically conical and non-spherical compact singularities. We also show that the mean curvature flow of generic closed low-entropy hypersurfaces in $\mathbb{R}^{4}$ is smooth until it disappears in a round point. The main technical ingredient is a long-time existe

Jeff Erickson, Gabriel Nivasch, Junyan Xu

Inspired by a mathematical riddle involving fuses, we define the &#34;fusible numbers&#34; as follows: $0$ is fusible, and whenever $x,y$ are fusible with $|y-x|<1$, the number $(x+y+1)/2$ is also fusible. We prove that the set of fusible numbers, ordered by the usual order on $\mathbb R$, is well-ordered, with order type $\varepsilon_0$. Furthermore, we pro

Kenneth R. Davidson, Michael Hartz

We study the multiplier algebras $A(\mathcal{H})$ obtained as the closure of the polynomials on certain reproducing kernel Hilbert spaces $\mathcal{H}$ on the ball $\mathbb{B}_d$ of $\mathbb{C}^d$. Our results apply, in particular, to the Drury-Arveson space, the Dirichlet space and the Hardy space on the ball. We first obtain a complete description of the d

Max Foxley-Marrable, Thomas E. Collett, Chris Frohmaier, Daniel A. Goldstein

We determine the viability of exploiting lensing time delays to observe strongly gravitationally lensed supernovae (gLSNe) from first light. Assuming a plausible discovery strategy, the Legacy Survey of Space and Time (LSST) and the Zwicky Transient Facility (ZTF) will discover $\sim$ 110 and $\sim$ 1 systems per year before the supernova (SN) explosion in t

Gerard Valentí-Rojas, Niclas Westerberg, Patrik Öhberg

Topological field theories emerge at low energy in strongly-correlated condensed matter systems and appear in the context of planar gravity. In particular, the study of Chern-Simons terms gives rise to the concept of flux attachment when the gauge field is coupled to matter, yielding flux-charge composites. Here we investigate the generation of flux attachme

Wenshan Wang, Delong Zhu, Xiangwei Wang, Yaoyu Hu

We present a challenging dataset, the TartanAir, for robot navigation tasks and more. The data is collected in photo-realistic simulation environments with the presence of moving objects, changing light and various weather conditions. By collecting data in simulations, we are able to obtain multi-modal sensor data and precise ground truth labels such as the

Charles R. Cowley, Donald J. Bord, Kutluay Yüce

Bedell et al. (2018) give precision differential abundances for 79 mostly G-dwarf stars. We correct these abundances for Galactic chemical evolution in a manner similar to that used by these authors but with parameters derived from linear fits to plots of [El/H] vs. age in lieu of [El/Fe]. We examine the resulting abundances for correlations with the 50% con

James B. Kennedy, Jonathan Rohleder

We undertake a systematic investigation of the maxima and minima of the eigenfunctions associated with the first nontrivial eigenvalue of the Laplacian on a metric graph equipped with standard (continuity--Kirchhoff) vertex conditions. This is inspired by the famous hot spots conjecture for the Laplacian on a Euclidean domain, and the points on the graph whe

G. D. Barmparis, G. P. Tsironis

The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial, and educational organization. The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees. The infe

Daniel Cibotaru, Vincent Grandjean, Blaine Lawson,

We present a general framework for obtaining currential double transgression formulas on complex manifolds which can be seen as manifestations of Bott-Chern Duality. These results complement on one hand the simple transgression formulas obtained by Harvey -Lawson and on the other hand the double transgression formulas of Bismut-Gillet-Soulé. Among the applic

Hermann Nicolai, Jan Plefka

Quantum correlators of pure supersymmetric Yang-Mills theories in D=3,4,6 and 10 dimensions can be reformulated via the non-linear and non-local transformation (`Nicolai map&#39;) that maps the full functional measure of the interacting theory to that of a free bosonic theory. As a special application we show that for the maximally extended N=4 theory in fou