arXiv papers from April 2021

Daniel Appelo, Kiera van der Sande, Nathan Albin

Fourier continuation is an approach used to create periodic extensions of non-periodic functions in order to obtain highly-accurate Fourier expansions. These methods have been used in PDE-solvers and have demonstrated high-order convergence and spectrally accurate dispersion relations in numerical experiments. Discontinuous Galerkin (DG) methods are increasi

Ernesto P. Borges, Bruno G. da Costa

Generalized numbers, arithmetic operators and derivative operators, grouped in four classes based on symmetry features, are introduced. Their building element is the pair of $q$-logarithm/$q$-exponential inverse functions. Some of the objects were previously described in the literature, while others are newly defined. Commutativity, associativity and distrib

Cosmin Pohoata, Dmitriy Zakharov

We prove that perfect $3$-hash linear codes in $\mathbb{F}_{3}^{n}$ must have dimension at most $ \left(\frac{1}{4}-\epsilon\right)n$ for some absolute constant $\epsilon > 0$.

Doris Jung-Lin Lee, Dixin Tang, Kunal Agarwal, Thyne Boonmark

Exploratory data science largely happens in computational notebooks with dataframe APIs, such as pandas, that support flexible means to transform, clean, and analyze data. Yet, visually exploring data in dataframes remains tedious, requiring substantial programming effort for visualization and mental effort to determine what analysis to perform next. We prop

S. E. Clark, Chang-Goo Kim, J. Colin Hill, Brandon S. Hensley

Recent measurements of Galactic polarized dust emission have found a nonzero $TB$ signal, a correlation between the total intensity and the $B$-mode polarization component. We present evidence that this parity-odd signal is driven by the relative geometry of the magnetic field and the filamentary interstellar medium in projection. Using neutral hydrogen morp

Nicolas Loizeau, Glennys R. Farrar

We use the galaxy rotation curves in the SPARC database to compare 9 different dark matter and modified gravity models on an equal footing, paying special attention to the stellar mass-to-light ratios. We compare three non-interacting dark matter models, a self interacting DM (SIDM) model, two hadronically interacting DM (HIDM) models, and three modified New

J. A. Mota, D. J. G. Maldonado, J. V. Valério, T. G. Ritto

The present work aims to revisit the simplifications made in the Navier-Stokes equations for the flow between two cylinders with a small thickness of lubricating oil film. Through a dimensionless analysis, the terms of these equations are mapped and ordered by importance for the hydrodynamic bearing application. An effective parameterization of the geometry

Rabin Yu Acharya, Fatemeh Ganji, Domenic Forte

Profiled side-channel analysis (SCA) leverages leakage from cryptographic implementations to extract the secret key. When combined with advanced methods in neural networks (NNs), profiled SCA can successfully attack even those crypto-cores assumed to be protected against SCA. Despite the rise in the number of studies devoted to NN-based SCA, a range of quest

Erik Mainellis

Factor systems are a tool for working on the extension problem of algebraic structures such as groups, Lie algebras, and associative algebras. Their applications are numerous and well-known in these common settings. We construct $\mathscr{P}$ algebra analogues to a series of results from W. R. Scott's $\textit{Group Theory}$, which gives an explicit theory o

James Diffenderfer, Daniel Osei-Kuffuor, Harshitha Menon

Approximate computing techniques have been successful in reducing computation and power costs in several domains. However, error sensitive applications in high-performance computing are unable to benefit from existing approximate computing strategies that are not developed with guaranteed error bounds. While approximate computing techniques can be developed

Jinkyu Lee, Muhyun Back, Sung Soo Hwang, Il Yong Chun

Monocular simultaneous localization and mapping (SLAM) is emerging in advanced driver assistance systems and autonomous driving, because a single camera is cheap and easy to install. Conventional monocular SLAM has two major challenges leading inaccurate localization and mapping. First, it is challenging to estimate scales in localization and mapping. Second

Yisroel Mirsky

Applications such as autonomous vehicles and medical screening use deep learning models to localize and identify hundreds of objects in a single frame. In the past, it has been shown how an attacker can fool these models by placing an adversarial patch within a scene. However, these patches must be placed in the target location and do not explicitly alter th

Anne Rubbens, Zheming Wang, Raphaël M. Jungers

We present a new data-driven method to provide probabilistic stability guarantees for black-box switched linear systems. By sampling a finite number of observations of trajectories, we construct approximate Lyapunov functions and deduce the stability of the underlying system with a user-defined confidence. The number of observations required to attain this c

Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Sai Sandeep

In the scheduling with non-uniform communication delay problem, the input is a set of jobs with precedence constraints. Associated with every precedence constraint between a pair of jobs is a communication delay, the time duration the scheduler has to wait between the two jobs if they are scheduled on different machines. The objective is to assign the jobs t

Paul Burkhardt

Triangle centrality is introduced for finding important vertices in a graph based on the concentration of triangles surrounding each vertex. It has the distinct feature of allowing a vertex to be central if it is in many triangles or none at all. We show experimentally that triangle centrality is broadly applicable to many different types of networks. Our em

Qi Zheng

Automated cooking machine is a goal for the future. The main aim is to make the cooking process easier, safer, and create human welfare. To allow robots to accurately perform the cooking activities, it is important for them to understand the cooking environment and recognize the objects, especially correctly identifying the state of the cooking objects. This

Nicolette Meshkat, Anne Shiu, Angélica Torres

A reaction system exhibits "absolute concentration robustness" (ACR) in some species if the positive steady-state value of that species does not depend on initial conditions. Mathematically, this means that the positive part of the variety of the steady-state ideal lies entirely in a hyperplane of the form $x_i=c$, for some $c>0$. Deciding whether a given re

Hugh Chen, Scott M. Lundberg, Su-In Lee

Local feature attribution methods are increasingly used to explain complex machine learning models. However, current methods are limited because they are extremely expensive to compute or are not capable of explaining a distributed series of models where each model is owned by a separate institution. The latter is particularly important because it often aris

Gianmario Broccia

In orbit, we find a harsh environment able to damage even space-qualified components. The main threats will be listed in the following lines, one by one, also presenting some of the effects on commercial electronics. According to the literature, the most recommended materials and countermeasures will be also introduced under each 'Materials and Countermeasur

Daniela di Serafino, Germana Landi, Marco Viola

We are interested in the restoration of noisy and blurry images where the texture mainly follows a single direction (i.e., directional images). Problems of this type arise, for example, in microscopy or computed tomography for carbon or glass fibres. In order to deal with these problems, the Directional Total Generalized Variation (DTGV) was developed by Kon

Yiming Sun, Yang Guo, Joel A. Tropp, Madeleine Udell

Random projections reduce the dimension of a set of vectors while preserving structural information, such as distances between vectors in the set. This paper proposes a novel use of row-product random matrices in random projection, where we call it Tensor Random Projection (TRP). It requires substantially less memory than existing dimension reduction maps. T

Guangyi Zhang, Ali Etemad

Affective computing with Electroencephalogram (EEG) is a challenging task that requires cumbersome models to effectively learn the information contained in large-scale EEG signals, causing difficulties for real-time smart-device deployment. In this paper, we propose a novel knowledge distillation pipeline to distill EEG representations via capsule-based arch

Liu Yu, Lucas Le Nagard, Solomon Barkley, Lauren Smith

Helical-shaped magnetotactic bacteria provide a rare opportunity to precisely measure both the translational and rotational friction coefficients of micron-sized chiral particles. The possibility to align these cells with a uniform magnetic field allows to clearly separate diffusion along and perpendicular to their longitudinal axis. Meanwhile, their corkscr

Agissilaos Athanassoulis, Odin Gramstad

The Alber equation is a phase-averaged second-moment model for the statistics of a sea state, which recently has been attracting renewed attention. We extend it in two ways: firstly, we derive a generalized Alber system starting from a system of nonlinear Schr\"odinger equations, which contains the classical Alber equation as a special case but can also desc

Yubin Ge, Site Li, Xuyang Li, Fangfang Fan

The widely-used cross-entropy (CE) loss-based deep networks achieved significant progress w.r.t. the classification accuracy. However, the CE loss can essentially ignore the risk of misclassification which is usually measured by the distance between the prediction and label in a semantic hierarchical tree. In this paper, we propose to incorporate the risk-aw

Saraiva Marcus, Forechi Avelino, de Oliveira Neto Jorcy, DelRey Antonio

In the Oil and Gas industry, estimating a subsurface velocity field is an essential step in seismic processing, reservoir characterization, and hydrocarbon volume calculation. Full-waveform inversion (FWI) velocity modeling is an iterative advanced technique that provides an accurate and detailed velocity field model, although at a very high computational co

Steen Ryom-Hansen

We study the representation theory of the braids and ties algebra, or the $bt$-algebra, $ \cal E$. Using the cellular basis $\{m_{{\mathfrak s} {\mathfrak t}} \}$ for $ \cal E$ obtained in previous joint work with J. Espinoza we introduce two kinds of permutation modules $M(\lambda)$ and $ M(\Lambda) $ for $\cal E$. We show that the tensor product module $V^

Alessandro Roggero, Jakub Filipek, Shih-Chieh Hsu, Nathan Wiebe

In this work we present the Scaled QUantum IDentifier (SQUID), an open-source framework for exploring hybrid Quantum-Classical algorithms for classification problems. The classical infrastructure is based on PyTorch and we provide a standardized design to implement a variety of quantum models with the capability of back-propagation for efficient training. We

Nikita Araslanov, Stefan Roth

We propose an approach to domain adaptation for semantic segmentation that is both practical and highly accurate. In contrast to previous work, we abandon the use of computationally involved adversarial objectives, network ensembles and style transfer. Instead, we employ standard data augmentation techniques $-$ photometric noise, flipping and scaling $-$ an

Martin Miguel, Pablo Riera, Diego Fernandez Slezak

Measuring human capabilities to synchronize in time, adapt to perturbations to timing sequences or reproduce time intervals often require experimental setups that allow recording response times with millisecond precision. Most setups present auditory stimuli using either MIDI devices or specialized hardware such as Arduino and are often expensive or require

Asma Bashir, Muhammad Abdul Wasay

The classical and quantum dynamics of two particles constrained on $S^1$ is discussed via Dirac's approach. We show that when state is maximally entangled between two subsystems, the product of dispersion in the measurement reduces. We also quantify the upper bound on the external field $\vec{B}$ such that $\vec{B}\geq\vec{B}_{upper}$ implies no reduction in

Robert Slapikas, Ismaila Dabo, Susan B. Sinnott

An investigation to optimize the application of the third-generation charge optimized many-body (COMB3) interatomic potential and associated input parameters was carried out through the study of solid-liquid interactions in classical molecular dynamics (MD) simulations. The rates of these molecular interactions are understood though the wetting rates of wate

Alan P. Marscher, Svetlana G. Jorstad

Time-variable polarization is an extremely valuable observational tool to probe the dynamical physical conditions of blazar jets. Since 2008, we have been monitoring the flux and linear polarization of a sample of gamma-ray bright blazars at optical frequencies. Some of the observations were performed on nightly or intra-night time-scales in four optical ban

Zhiyang Li, Ming Chen, Zhaohui Yang, Jingwen Zhao

Reconfigurable intelligent surface (RIS) has emerged as a promising technology for achieving high spectrum and energy efficiency in future wireless communication networks. In this paper, we investigate an RIS-aided single-cell multi-user mobile edge computing (MEC) system where an RIS is deployed to support the communication between a base station (BS) equip

H. Nakamura, K. Uchibori, S. Kawata, T. Karino

The Code O-SUKI-N 3D is an upgraded version of the 2D Code O-SUKI (Comput. Phys. Commun. 240, 83 (2019)). Code O-SUKI-N 3D is an integrated 3-dimensional (3D) simulation program system for fuel implosion, ignition and burning of a direct-drive nuclear-fusion pellet in heavy ion beam (HIB) inertial confinement fusion (HIF).The Code O-SUKI-N 3D consists of the

J. N. Wandinger, D. M. Roberts, J. S. Bobowski, T. Johnson

We investigated inductive power transfer (IPT) through a rectangular slab of saltwater. Our inductively-coupled transmitters and receivers were made from loop-gap resonators (LGRs) having resonant frequencies near 100 MHz. Electric fields are confined within the narrow gaps of the LGRs making it possible to strongly suppress the power dissipation associated

Rafhael R. Cunha, Jomi Fred Hübner, Maiquel de Brito

In multi-agent systems, the agents may have goals that depend on a social, shared interpretation about the facts occurring in the system. These are the so-called social goals. Artificial institutions provide such a social interpretation by assigning statuses to the concrete elements that compose the system. These statuses are supposed to enable the assignee

Gianmario Broccia

In the last years, the need for automated real-time detection and classification of astronomical transients began to be more impelling. Better technologies involve a higher number of detected candidates and an automated classification will allow dealing with this amount of data, every night. The desired state-of-the-art in detection and classification will b

Gheorghe Craciun, Abhishek Deshpande

Homeostasis is a mechanism by which a feature can remain invariant with change in external parameters. We adopt the definition of homeostasis in the context of singularity theory. We make a connection between homeostasis and the theory of injective reaction networks. In particular, we show that a reaction network cannot exhibit homeostasis if a modified reac

Huajie Li

We establish an invariant local trace formula for the tangent space of some symmetric spaces over a non-archimedean local field of characteristic zero. These symmetric spaces are studied in Guo-Jacquet trace formulae and our methods are inspired by works of Waldspurger and Arthur. Some other results are given during the proof including a noninvariant local t

Aitor Garcia-Ruiz, Haiyao Deng, Vladimir V. Enaldiev, Vladimir I. Fal'ko

We use a hybrid k dot p theory - tight binding (HkpTB) model to describe interlayer coupling simultaneously in both Bernal and twisted graphene structures. For Bernal-aligned interfaces, HkpTB is parametrized using the full Slonczewski-Weiss-McClure (SWMcC) Hamiltonian of graphite, which is then used to refine the commonly used minimal model for twisted inte

Daniel Dilley, Alvin Gonzales, Mark Byrd

In open quantum systems, it is known that if the system and environment are in a product state, the evolution of the system is given by a linear completely positive (CP) Hermitian map. CP maps are a subset of general linear Hermitian maps, which also include non completely positive (NCP) maps. NCP maps can arise in evolutions such as non-Markovian evolution,

K. Flora, A. Khosronejad

We present large-eddy simulations (LESs) of riverine flow in a study reach in the Sacramento River, California. The riverbed bathymetry was surveyed in high-resolution using a multibeam echosounder to construct the computational model of the study area, while the topographies were defined using aerial photographs taken by an Unmanned Aircraft System (UAS). I

F. Sutanto, T. M. Classen, S. A. Dazeley, M. J. Duvall

We present a characterization of a small (9-liter) and mobile 0.1% 6Li-doped pulse-shape-sensitive plastic scintillator antineutrino detector called SANDD (Segmented AntiNeutrino Directional Detector), constructed for the purpose of near-field reactor monitoring with sensitivity to antineutrino direction. SANDD comprises three different types of module. A de

Haoyue Ping, Julia Stoyanovich

It remains an open question how to determine the winner of an election when voter preferences are incomplete or uncertain. One option is to assume some probability space over the voting profile and select the Most Probable Winner (MPW) -- the candidate or candidates with the best chance of winning. In this paper, we propose an alternative winner interpretati

S. S. Agaev, K. Azizi, H. Sundu

We explore properties of the doubly charged vector tetraquark $Z_{\mathrm{V} }^{++}=[cu][\overline{s}\overline{d}]$ built of four quarks of different flavors using the QCD sum rule methods. The mass and current coupling of $Z_{ \mathrm{V}}^{++}$ are computed in the framework of the QCD two-point sum rule approach by taking into account quark, gluon and mixed

Murphy Yuezhen Niu, Alexander Zlokapa, Michael Broughton, Sergio Boixo

Generative adversarial networks (GANs) are one of the most widely adopted semisupervised and unsupervised machine learning methods for high-definition image, video, and audio generation. In this work, we propose a new type of architecture for quantum generative adversarial networks (entangling quantum GAN, EQ-GAN) that overcomes some limitations of previousl

Ziming Li, Julia Kiseleva, Maarten de Rijke

Being able to generate informative and coherent dialogue responses is crucial when designing human-like open-domain dialogue systems. Encoder-decoder-based dialogue models tend to produce generic and dull responses during the decoding step because the most predictable response is likely to be a non-informative response instead of the most suitable one. To al

Artur O. Lopes, Victor Vargas

Denote by $X$ a Banach space and by $T : X \to X$ a bounded linear operator with non-trivial kernel satisfying suitable conditions. We consider the concepts of entropy - for $T$-invariant probability measures - and pressure for H\"older continuous potentials. We also prove the existence of ground states (the limit when temperature goes to zero) associated wi

Gabriel Guidarelli, Jason Nordhaus, Jonathan Carroll-Nellenback, Luke Chamandy

A significant fraction of isolated white dwarfs host magnetic fields in excess of a MegaGauss. Observations suggest that these fields originate in interacting binary systems where the companion is destroyed thus leaving a singular, highly-magnetized white dwarf. In post-main-sequence evolution, radial expansion of the parent star may cause orbiting companion

Lucy Lu Wang, Isabel Cachola, Jonathan Bragg, Evie Yu-Yen Cheng

The majority of scientific papers are distributed in PDF, which pose challenges for accessibility, especially for blind and low vision (BLV) readers. We characterize the scope of this problem by assessing the accessibility of 11,397 PDFs published 2010--2019 sampled across various fields of study, finding that only 2.4% of these PDFs satisfy all of our defin

Samuel J. Raymond, David B. Camarillo

Physics-Informed Machine Learning (PIML) has gained momentum in the last 5 years with scientists and researchers aiming to utilize the benefits afforded by advances in machine learning, particularly in deep learning. With large scientific data sets with rich spatio-temporal data and high-performance computing providing large amounts of data to be inferred an

Sayantan Chowdhury, Ben Liang, Ali Tizghadam, Ilijc Albanese

Network traffic classification using machine learning techniques has been widely studied. Most existing schemes classify entire traffic flows, but there are major limitations to their practicality. At a network router, the packets need to be processed with minimum delay, so the classifier cannot wait until the end of the flow to make a decision. Furthermore,

Indranil Chowdhury, Olav Ersland, Espen R. Jakobsen

We construct numerical approximations for Mean Field Games with fractional or nonlocal diffusions. The schemes are based on semi-Lagrangian approximations of the underlying control problems/games along with dual approximations of the distributions of agents. The methods are monotone, stable, and consistent, and we prove convergence along subsequences for (i)

A. O. Sorokin

Using the renormalization group approach, we consider the $O(N)\otimes O(M)$ model in four and more dimensions. We find that independently on $N$ and $M$, for $N\geq M\geq 2$, a transition can be of both the first and second order. In $d>4$, we also cannot exclude a pseudo-first-order behavior. As specific physically interesting cases, we consider the lattic

Nouha Dziri, Hannah Rashkin, Tal Linzen, David Reitter

Knowledge-grounded dialogue systems powered by large language models often generate responses that, while fluent, are not attributable to a relevant source of information. Progress towards models that do not exhibit this issue requires evaluation metrics that can quantify its prevalence. To this end, we introduce the Benchmark for Evaluation of Grounded INte

Natalia Emriskova

The CMS Inner Tracker, made of silicon pixel modules, will be entirely replaced prior to the start of the High Luminosity LHC period. One of the crucial components of the new Inner Tracker system is the readout chip, being developed by the RD53 Collaboration, and in particular its analogue front-end, which receives the signal from the sensor and digitizes it

Neil McGlohon, Christopher D. Carothers

In the area of discrete event simulation (DES), event simultaneity occurs when any two events are scheduled to happen at the same point in simulated time. Simulation determinism is the expectation that the same semantically configured simulation will be guaranteed to repeatedly reproduce identical results. Since events in DES are the sole mechanism for state

John Orlowski-Scherer, Luca Di Mascolo, Tanay Bhandarkar, Alex Manduca

Galaxy clusters are an important tool for cosmology, and their detection and characterization are key goals for current and future surveys. Using data from the Wide-field Infrared Survey Explorer (WISE), the Massive and Distant Clusters of WISE Survey (MaDCoWS) located 2,839 significant galaxy overdensities at redshifts $0.7\lesssim z\lesssim 1.5$, which inc

Sirnam Swetha, Hilde Kuehne, Yogesh S Rawat, Mubarak Shah

Action recognition and detection in the context of long untrimmed video sequences has seen an increased attention from the research community. However, annotation of complex activities is usually time consuming and challenging in practice. Therefore, recent works started to tackle the problem of unsupervised learning of sub-actions in complex activities. Thi

Dong-han Yeom

The interior of the black hole can be described by anisotropic cosmology. By quantizing the metric function, we can obtain the Wheeler-DeWitt equation for inside the horizon. In order to interpret the wave function consistently, one needs to impose a boundary condition. In this paper, we introduce a prescription for the Euclidean analytic continuation inside

Michael P. Frank, Karpur Shukla

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible digital paradigm. However, to date, the essential rationale for and analysis of classical reversible computing (RC) has not yet been

Andrew B. Pace, Matthew G. Walker, Sergey E. Koposov, Nelson Caldwell

The Fornax dwarf spheroidal galaxy has an anomalous number of globular clusters, five, for its stellar mass. There is a longstanding debate about a potential sixth globular cluster (Fornax~6) that has recently been `rediscovered' in DECam imaging. We present new Magellan/M2FS spectroscopy of the Fornax~6 cluster and Fornax dSph. Combined with literature data

Tomaz Martincic, Dejan Stepec, Joao Pita Costa, Kristijan Cagran

Automatic Identification System (AIS) data represents a rich source of information about maritime traffic and offers a great potential for data analytics and predictive modeling solutions, which can help optimizing logistic chains and to reduce environmental impacts. In this work, we address the main limitations of the validity of AIS navigational data field

Alexandr Cocemasov, Vladimir Brinzari, Do-Gyeom Jeong, Ghenadii Korotcenkov

We report on a comprehensive theoretical and experimental investigation of thermal conductivity in indium-tin-oxide (ITO) thin films with various Ga concentrations (0-30 at. %) deposited by spray pyrolysis technique. X-Ray diffraction (XRD) and scanning electron microscopy have shown a structural transformation in the range 15-20 at. % Ga from the nanocrysta

Jay Lawrence

With the example of a Stern-Gerlach measurement on a spin-1/2 atom, we show that a superposition of both paths may be observed compatibly with properties attributed to state collapse - for example, the singleness (or mutual exclusivity) of outcomes. This is done by inserting a quantum two-state system (an ancilla) in each path, capable of responding to the p

Michael Anis Mihdi Afnan, Cynthia Rudin, Vincent Conitzer, Julian Savulescu

AI has the potential to revolutionize many areas of healthcare. Radiology, dermatology, and ophthalmology are some of the areas most likely to be impacted in the near future, and they have received significant attention from the broader research community. But AI techniques are now also starting to be used in in vitro fertilization (IVF), in particular for s

Alexander Sboev, Sanna Sboeva, Ivan Moloshnikov, Artem Gryaznov

We present the full-size Russian complexly NER-labeled corpus of Internet user reviews, along with an evaluation of accuracy levels reached on this corpus by a set of advanced deep learning neural networks to extract the pharmacologically meaningful entities from Russian texts. The corpus annotation includes mentions of the following entities: Medication (33

J. Calcutt, C. Thorpe, K. Mahn, Laura Fields

Geant4Reweight is an open-source C++ framework that allows users to 1) weight tracks produced by the GEANT4 particle transport Monte Carlo simulation according to hadron interaction cross section variations and 2) estimate uncertainties in GEANT4 interaction models by comparing the simulation's hadron interaction cross section predictions to data. The abilit

Kurt Schab, Bradley Shirley, K. C. Kerby-Patel

Harmonic generation in the scattered fields produced by a dielectric sphere coated with a time-varying conductive shell is studied using a Mie theory approach hybridized with conversion matrix methods. Analytic results are derived for plane wave incidence as well as in a more general transition matrix setting. An equivalent transmission line approach is also

Christian Kehl, Erik van Sebille, Angus Gibson

Array-like collection data structures are widely established in Python's scientific computing-ecosystem for high-performance computations. The structure maps well to regular, gridded lattice structures that are common to computational problems in physics and geosciences. High performance is, however, only guaranteed for static computations with a fixed compu

Aolin Xu

An anytime decoding algorithm for tree codes using Monte-Carlo tree search is proposed. The meaning of anytime decoding here is twofold: 1) the decoding algorithm is an anytime algorithm, whose decoding performance improves as more computational resource, measured by decoding time, is allowed, and 2) the proposed decoding algorithm can approximate the maximu

Serena Eley, Andreas Glatz, Roland Willa

In superconductors, the motion of vortices introduces unwanted dissipation that is disruptive to applications. Fortunately, material defects can immobilize vortices, acting as vortex pinning centers, which engenders dramatic improvements in superconductor material properties and device operation. This has motivated decades of research into developing methods

Louis R. Eeckhoudt, Roger J. A. Laeven

Employing a generalized definition of Pratt (1964) and Arrow's (1965, 1971) probability premium, we introduce a new concept of attitude towards probability. We illustrate in a problem of risk sharing that whether attitude towards probability is a first-order or second-order phenomenon has important economic applications. By developing a local approximation t

Gonçalo Raposo, Pedro Tomás, Nuno Roma

Low-precision formats have proven to be an efficient way to reduce not only the memory footprint but also the hardware resources and power consumption of deep learning computations. Under this premise, the posit numerical format appears to be a highly viable substitute for the IEEE floating-point, but its application to neural networks training still require

Wojciech Czerwiński, Adam Jędrych

Despite recent progress which settled the complexity of the reachability problem for Vector Addition Systems with States (VASSes) as being Ackermann-complete we still lack much understanding for that problem. A striking example is the reachability problem for three-dimensional VASSes (3-VASSes): it is only known to be PSpace-hard and not known to be elementa

Falko Baustian, Martin Fencl, Jan Pospíšil, Vladimír Švígler

In this paper we study partial differential equations (PDEs) that can be used to model value adjustments. Different value adjustments denoted generally as xVA are nowadays added to the risk-free financial derivative values and the PDE approach allows their easy incorporation. The aim of this paper is to show how to solve the PDE analytically in the Black-Sch

Paul Z. Chen, Aaron J. Clasky, Frank X. Gu

Supersaturation is the fundamental parameter driving crystal formation, yet its dynamics during the growth of colloidal nanocrystals (NCs) are poorly understood. Experimental characterization of supersaturation in colloidal syntheses has been difficult, limiting insight into the phenomena underlying NC growth. Hence, despite significant interest in the topic

Shayan Hundrieser, Marcel Klatt, Axel Munk

For probability measures on countable spaces we derive distributional limits for empirical entropic optimal transport quantities. More precisely, we show that the empirical optimal transport plan weakly converges to a centered Gaussian process and that the empirical entropic optimal transport value is asymptotically normal. The results are valid for a large

Daniel R. Gurevich, Matthew R. Golden, Patrick A. K. Reinbold, Roman O. Grigoriev

We show how a complete mathematical description of a complicated physical phenomenon can be learned from observational data via a hybrid approach combining three simple and general ingredients: physical assumptions of smoothness, locality, and symmetry, a weak formulation of differential equations, and sparse regression. To illustrate this, we extract a syst

Jian Zeng, Ka Man Chung, Sarath Reddy Adapa, Tianshi Feng

In situ thermal transport measurement of flowing fluid could be useful for the characterization and diagnosis of practical thermal systems such as fluid heat exchangers and thermal energy storage systems. Despite abundant reports on the ex-situ thermal conductivity measurement of stagnant fluids, a suitable technique for the thermal conductivity measurement

Gianni Dal Maso, Riccarda Rossi, Giuseppe Savaré, Rodica Toader

Visco-energetic solutions have been recently advanced as a new solution concept for rate-independent systems, alternative to energetic solutions/quasistatic evolutions and balanced viscosity solutions. In the spirit of this novel concept, we revisit the analysis of the variational model proposed by Francfort and Marigo for the quasi-static crack growth in br

Xiaoli Gao

The fused lasso is an important method for signal processing when the hidden signals are sparse and blocky. It is often used in combination with the squared loss function. However, the squared loss is not suitable for heavy tail error distributions nor is robust against outliers which arise often in practice. The least absolute deviations (LAD) loss provides

Hortensia Galeana-Sánchez, Miguel Tecpa-Galván

Let $H$ be a digraph possibly with loops and $D$ a digraph without loops whose arcs are colored with the vertices of $H$ ($D$ is said to be an $H-$colored digraph). If $W=(x_{0},\ldots,x_{n})$ is an open walk in $D$ and $i\in \{1,\ldots,n-1\}$, we say that there is an obstruction on $x_{i}$ if $(color(x_{i-1},x_{i}),color(x_{i},x_{i+1}))\notin A(H)$. If $S\s

Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan, Jeff Bilmes

With the rapid growth of data, it is becoming increasingly difficult to train or improve deep learning models with the right subset of data. We show that this problem can be effectively solved at an additional labeling cost by targeted data subset selection(TSS) where a subset of unlabeled data points similar to an auxiliary set are added to the training dat

Tomas A. James, Serena Viti, Farhad Yusef-Zadeh, Marc Royster

We report sub-arcsecond ALMA observations between 272 - 375 GHz towards Sgr A*'s Circumnuclear disk (CND). Our data comprises 8 individual pointings, with significant SiO (8(7) - 7(6)) and SO (7 - 6) emission detected towards 98 positions within these pointings. Additionally, we identify H2CS (9(1,9) - 8(1,8)), OCS (25 - 24) and CH3OH (2(1,1) - 2(0,2)) towar

Ramy Shahin, Sahar Kokaly, Marsha Chechik

Safety-critical software systems are in many cases designed and implemented as families of products, usually referred to as Software Product Lines (SPLs). Products within an SPL vary from each other in terms of which features they include. Applying existing analysis techniques to SPLs and their safety cases is usually challenging because of the potentially e

Dan Wang, Dazhi Xu

We investigate the dynamic evolution and thermodynamic process of a driven quantum system immersed in a finite-temperature heat bath. A Born-Markovian quantum master equation is formally derived for the time-dependent system with discrete energy levels. This quantum master equation can be applied to situations with a broad range of driving speeds and bath te

Ahmad Hesam, Lukas Breitwieser, Fons Rademakers, Zaid Al-Ars

Researchers in biology are faced with the tough challenge of developing high-performance computer simulations of their increasingly complex agent-based models. BioDynaMo is an open-source agent-based simulation platform that aims to alleviate researchers from the intricacies that go into the development of high-performance computing. Through a high-level int

Nicolas Chenavier, Norbert Henze, Moritz Otto

Let $X_1,\ldots,X_n$ be a sequence of independent random points in $\mathbb{R}^d$ with common Lebesgue density $f$. Under some conditions on $f$, we obtain a Poisson limit theorem, as $n \to \infty$, for the number of large probability $k$th-nearest neighbor balls of $X_1,\ldots,X_n$. Our result generalizes Theorem 2. of [10], which refers to the special cas

Benjamin R. Roulston, Paul J. Green, Silvia Toonen, J. J. Hermes

Dwarf carbon (dC) stars, main sequence stars showing carbon molecular bands, are enriched by mass transfer from a previous asymptotic-giant-branch (AGB) companion, which has since evolved to a white dwarf. While previous studies have found radial-velocity variations for large samples of dCs, there are still relatively few dC orbital periods in the literature

L. J. Whitehouse, J. Farihi, I. D. Howarth, S. Mancino

Many characteristics of dwarf carbon stars are broadly consistent with a binary origin, including mass transfer from an evolved companion. While the population overall appears to have old-disc or halo kinematics, roughly 2$\,$per cent of these stars exhibit H$\alpha$ emission, which in low-mass main-sequence stars is generally associated with rotation and re

N. S. Kirsanov, N. R. Kenbaev, A. B. Sagingalieva, D. A. Kronberg

Existing quantum cryptography is resistant against secrecy-breaking quantum computers but suffers fast decay of the signal at long distances. The various types of repeaters of propagating quantum states have been developed to meet the challenge, but the problem is far from being solved. We step in the breach and put forth long-distance high secrecy optical c

Billy Quarles, Siegfried Eggl, Marialis Rosario-Franco, Gongjie Li

The presence of a stellar companion can place constraints on occurrence and orbital evolution of satellites orbiting exoplanets, i.e., exomoons. In this work we revise earlier orbital stability limits for retrograde orbits in the case of a three body system consisting of star-planet-satellite. The latter reads $a_{\rm sat}^{\rm crit} \approx 0.668(1-1.236e_{

Matthew Kolosick, Shravan Narayan, Evan Johnson, Conrad Watt

Software sandboxing or software-based fault isolation (SFI) is a lightweight approach to building secure systems out of untrusted components. Mozilla, for example, uses SFI to harden the Firefox browser by sandboxing third-party libraries, and companies like Fastly and Cloudflare use SFI to safely co-locate untrusted tenants on their edge clouds. While there

Nathan M Myers, Jacob McCready, Sebastian Deffner

By harnessing quantum phenomena, quantum devices have the potential to outperform their classical counterparts. Previous work has shown that a bosonic working medium can yield better performance than a fermionic medium. We expand upon this work by incorporating a singular interaction that allows the effective symmetry to be tuned between the bosonic and ferm

Diego C Nascimento, Pedro Luiz Ramos, David Elal-Olivero, Milton Cortes-Araya

Normality is the most often mathematical supposition used in data modeling. Nonetheless, even based on the law of large numbers (LLN), normality is a strong presumption given that the presence of asymmetry and multi-modality in real-world problems is expected. Thus, a flexible modification in the Normal distribution proposed by Elal-Olivero [12] adds a skewn

Sara Lafia, Andrea Thomer, David Bleckley, Dharma Akmon

This paper describes a machine learning approach for annotating and analyzing data curation work logs at ICPSR, a large social sciences data archive. The systems we studied track curation work and coordinate team decision-making at ICPSR. Repository staff use these systems to organize, prioritize, and document curation work done on datasets, making them prom

Mahboubeh Shahrbaf, Sofija Antić, A. Ayriyan, David Blaschke

We provide a systematic study of hybrid neutron star equations of state (EoS) consisting of a relativistic density functional for the hadronic phase and a covariant nonlocal Nambu--Jona-Lasinio (nlNJL) model to describe the color superconducting quark matter phase. Changing the values of the two free parameters, the dimensionless vector and diquark coupling

Margot Fitz Axen, Stella S. S. Offner, Brandt A. L. Gaches, Chris L. Fryer

Recent studies have suggested that low-energy cosmic rays (CRs) may be accelerated inside molecular clouds by the shocks associated with star formation. We use a Monte Carlo transport code to model the propagation of CRs accelerated by protostellar accretion shocks through protostellar cores. We calculate the CR attenuation and energy losses and compute the