May 2022 arXiv papers — page 112

Keming Zhang, B. Scott Gaudi

The offset microlensing degeneracy, recently proposed by Zhang et al. (2022), has been shown to generalize the close-wide and inner-outer caustic degeneracies into a unified regime of magnification degeneracy in the interpretation of 2-body planetary microlensing observations. While the inner-outer degeneracy expects the source trajectory to pass equidistant

Rikab Gambhir, Benjamin Nachman, Jesse Thaler

Machine learning offers an exciting opportunity to improve the calibration of nearly all reconstructed objects in high-energy physics detectors. However, machine learning approaches often depend on the spectra of examples used during training, an issue known as prior dependence. This is an undesirable property of a calibration, which needs to be applicable i

Naoya Kitajima, Fumiaki Kozai, Fuminobu Takahashi, Wen Yin

Recently, based on a novel analysis of the Planck satellite data, a hint of a uniform rotation of the polarization of cosmic microwave background photons, called isotropic cosmic birefringence, has been reported. The suggested rotation angle of polarization of about $0.2-0.4$ degrees strongly suggests that it is determined by the fine structure constant, whi

B. Connor McClellan, Shane Davis, Phil Arras

We present two novel additions to the semi-analytic solution of Lyman $\alpha$ (Ly$\alpha$) radiative transfer in spherical geometry: (1) implementation of the correct boundary condition for a steady source, and (2) solution of the time-dependent problem for an impulsive source. For the steady-state problem, the solution can be represented as a sum of two te

Pablo Basteiro, Felix Dusel, Johanna Erdmenger, Dietmar Herdt

We establish how the Breitenlohner-Freedman (BF) bound is realized on tilings of two-dimensional Euclidean Anti-de Sitter space. For the continuum, the BF bound states that on Anti-de Sitter spaces, fluctuation modes remain stable for small negative mass-squared $m^2$. This follows from a real and positive total energy of the gravitational system. For finite

Qiankun Liu, Zhentao Tan, Dongdong Chen, Qi Chu

Transformers have achieved great success in pluralistic image inpainting recently. However, we find existing transformer based solutions regard each pixel as a token, thus suffer from information loss issue from two aspects: 1) They downsample the input image into much lower resolutions for efficiency consideration, incurring information loss and extra misal

Louigi Addario-Berry, Jordan Barrett, Benoît Corsini

We consider a family of local search algorithms for the minimum-weight spanning tree, indexed by a parameter $\rho$. One step of the local search corresponds to replacing a connected induced subgraph of the current candidate graph whose total weight is at most $\rho$ by the minimum spanning tree (MST) on the same vertex set. Fix a non-negative random variabl

Morris Ang, Nina Holden, Xin Sun

We prove that the SLE$_\kappa$ loop measure arises naturally from the conformal welding of two $\gamma$-Liouville quantum gravity (LQG) disks for $\gamma^2 = \kappa \in (0,4)$. The proof relies on our companion work on conformal welding of LQG disks and uses as an essential tool the concept of uniform embedding of LQG surfaces. Combining our result with work

Billy Edwards, Giovanna Tinetti

The ESA Ariel mission has been adopted for launch in 2029 and will conduct a survey of around one thousand exoplanetary atmospheres during its primary mission life. By providing homogeneous datasets, with a high SNR and wide wavelength coverage, Ariel will unveil the atmospheric demographics of these far-away worlds, helping to constrain planet formation and

Tingle Li, Yichen Liu, Andrew Owens, Hang Zhao

From the patter of rain to the crunch of snow, the sounds we hear often convey the visual textures that appear within a scene. In this paper, we present a method for learning visual styles from unlabeled audio-visual data. Our model learns to manipulate the texture of a scene to match a sound, a problem we term audio-driven image stylization. Given a dataset

Daniel Hershcovich, Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler

The climate impact of AI, and NLP research in particular, has become a serious issue given the enormous amount of energy that is increasingly being used for training and running computational models. Consequently, increasing focus is placed on efficient NLP. However, this important initiative lacks simple guidelines that would allow for systematic climate re

Nikita Marin, Elizaveta Makhneva, Maria Lysyuk, Vladimir Chernyy

Conventional collaborative filtering techniques don't take into consideration the effect of discrepancy in users' rating perception. Some users may rarely give 5 stars to items while others almost always assign 5 stars to the chosen item. Even if they had experience with the same items this systematic discrepancy in their evaluation style will lead to the sy

Lijian Lin, Xintao Wang, Zhongang Qi, Ying Shan

Despite that convolution neural networks (CNN) have recently demonstrated high-quality reconstruction for video super-resolution (VSR), efficiently training competitive VSR models remains a challenging problem. It usually takes an order of magnitude more time than training their counterpart image models, leading to long research cycles. Existing VSR methods

Onur Günlü, Rafael F. Schaefer, Holger Boche, H. Vincent Poor

The problem of secure source coding with multiple terminals is extended by considering a remote source whose noisy measurements are the correlated random variables used for secure source reconstruction. The main additions to the problem include 1) all terminals noncausally observe a noisy measurement of the remote source; 2) a private key is available to all

Chatipat Lorpaiboon, Jonathan Weare, Aaron R. Dinner

Transition path theory provides a statistical description of the dynamics of a reaction in terms of local spatial quantities. In its original formulation, it is limited to reactions that consist of trajectories flowing from a reactant set A to a product set B. We extend the basic concepts and principles of transition path theory to reactions in which traject

Yiran Cui, Georgios C. Trichopoulos

Traditional imaging systems, such as the eye or cameras, image scenes that lie in the direct line-of-sight (LoS). Most objects are opaque in the optical and infrared regimes and can limit dramatically the field of view (FoV). Current approaches to see around occlusions exploit the multireflection propagation of signals from neighboring surfaces either in the

Chong Mou, Yanze Wu, Xintao Wang, Chao Dong

Interactive image restoration aims to restore images by adjusting several controlling coefficients, which determine the restoration strength. Existing methods are restricted in learning the controllable functions under the supervision of known degradation types and levels. They usually suffer from a severe performance drop when the real degradation is differ

Shahar Hadar, Daniel Kapec, Alexandru Lupsasca, Andrew Strominger

Space-based next-generation interferometers propose to measure the Lyapunov exponents of the nearly bound geodesics that comprise the photon ring surrounding the black hole M87*. We argue that these classical Lyapunov exponents equal the quantum Ruelle resonances describing the late-time approach to thermal equilibrium of the quantum microstate holographical

Tianrui Sun, Lei Hu, Songbo Zhang, Xiaoyan Li

AST3-3 is the third robotic facility of the Antarctic Survey Telescopes (AST3) for transient surveys to be deployed at Dome A, Antarctica. Due to the current pandemic, the telescope has been currently deployed at the Yaoan Observation Station in China, starting the commissioning observation and a transient survey. This paper presents a fully automatic data p

Dmitri Whitmore

We construct a local deformation problem for residual Galois representations $\bar{\rho}$ valued in an arbitrary reductive group $\hat{G}$ which we use to develop a variant of the Taylor-Wiles method. Our generalization allows Taylor-Wiles places for which the image of Frobenius is semisimple, a weakening of the regular semisimple constraint imposed previous

Marco Pleines, Konstantin Ramthun, Yannik Wegener, Hendrik Meyer

Autonomously trained agents that are supposed to play video games reasonably well rely either on fast simulation speeds or heavy parallelization across thousands of machines running concurrently. This work explores a third way that is established in robotics, namely sim-to-real transfer, or if the game is considered a simulation itself, sim-to-sim transfer.

Pedro E. Harunari, Alberto Garilli, Matteo Polettini

The fluctuation relation, a milestone of modern thermodynamics, is only established when a set of fundamental currents can be measured. Here we prove that it also holds for systems with hidden transitions if observations are carried ``at their own beat,'' that is, by stopping the experiment after a fixed number of visible transitions, rather than the elapse

Sining Gong, Johnny Guzmán, Michael Neilan

We prove three-dimensional Worsey-Farin refinements inherit their parent triangulations' shape-regularity.

Jay Cao, Jacky Chen, Soroush Farghadani, John Hull

We show how D4PG can be used in conjunction with quantile regression to develop a hedging strategy for a trader responsible for derivatives that arrive stochastically and depend on a single underlying asset. We assume that the trader makes the portfolio delta neutral at the end of each day by taking a position in the underlying asset. We focus on how trades

Varun Mandalaparthy, W. G. Noid

Recent studies suggest that cosolute mixtures may exert significant non-additive effects upon protein stability. The corresponding liquid-vapor interfaces may provide useful insight into these non-additive effects. Accordingly, in this work we relate the interfacial properties of dilute multicomponent solutions to the interactions between solutes. We first d

Harmanpreet Kaur, Eytan Adar, Eric Gilbert, Cliff Lampe

Understanding how ML models work is a prerequisite for responsibly designing, deploying, and using ML-based systems. With interpretability approaches, ML can now offer explanations for its outputs to aid human understanding. Though these approaches rely on guidelines for how humans explain things to each other, they ultimately solve for improving the artifac

Renato da S. Guimarães, Tiago F. Silva, Cleber L. Rodrigues, Manfredo H. Tabacniks

Rutherford Backscattering Spectrometry (RBS) is an important technique providing elemental information of the near surface region of samples with high accuracy and robustness. However, this technique lacks throughput by the limited rate of data processing and is hardly routinely applied in research with a massive number of samples (i.e. hundreds or even thou

Hao-Kai Zhang, Chengkai Zhu, Geng Liu, Xin Wang

Exploring quantum applications of near-term quantum devices is a rapidly growing field of quantum information science with both theoretical and practical interests. A leading paradigm to establish such near-term quantum applications is variational quantum algorithms (VQAs). These algorithms use a classical optimizer to train a parameterized quantum circuit t

Beatrice Franzolini, Andrea Cremaschi, Willem van den Boom, Maria De Iorio

Several applications involving counts present a large proportion of zeros (excess-of-zeros data). A popular model for such data is the Hurdle model, which explicitly models the probability of a zero count, while assuming a sampling distribution on the positive integers. We consider data from multiple count processes. In this context, it is of interest to stu

T. Hennen, A. Elias, J. F. Nodin, G. Molas

By imitating the synaptic connectivity and plasticity of the brain, emerging electronic nanodevices offer new opportunities as the building blocks of neuromorphic systems. One challenge for largescale simulations of computational architectures based on emerging devices is to accurately capture device response, hysteresis, noise, and the covariance structure

Corrado Monti, Marco Pangallo, Gianmarco De Francisci Morales, Francesco Bonchi

Agent-Based Models (ABMs) are used in several fields to study the evolution of complex systems from micro-level assumptions. However, ABMs typically can not estimate agent-specific (or "micro") variables: this is a major limitation which prevents ABMs from harnessing micro-level data availability and which greatly limits their predictive power. In this paper

Vadym Koval, Patryk Pagacz

The main purpose of this article is to show that the numerical range of a linear pencil $\lambda A + B$ is equal to $\mathbb{C}$ if and only if $0$ belongs to the convex hull of the joint numerical range of $A$ and $B$. We also prove that if the numerical range of a linear pencil $\lambda A + B$ is equal to $\mathbb{C}$ and $A + A^*, B + B^* \geq 0$, then $A

Arshdeep Sekhon, Yangfeng Ji, Matthew B. Dwyer, Yanjun Qi

Recent literature has seen growing interest in using black-box strategies like CheckList for testing the behavior of NLP models. Research on white-box testing has developed a number of methods for evaluating how thoroughly the internal behavior of deep models is tested, but they are not applicable to NLP models. We propose a set of white-box testing methods

Tiago F. Silva, Cleber L. Rodrigues, Manfredo H. Tabacniks, Hugo D. C. Pereira

With a growing demand for accurate ion beam analysis on a large number of samples, it becomes an issue of how to ensure the quality standards and consistency over hundreds or thousands of samples. In this sense, a virtual assistant that checks the data quality, emitting certificates of quality, is highly desired. Even the processing of a massive number of sp

B. Popescu Braileanu, R. Keppens

The chromosphere is a partially ionized layer of the solar atmosphere, the transition between the photosphere where the gas is almost neutral and the fully ionized corona. As the collisional coupling between neutral and charged particles decreases in the upper part of the chromosphere, the hydrodynamical timescales may become comparable to the collisional ti

Shiuli Chatterjee, Raghuveer Garani, Rajeev Kumar Jain, Brijesh Kanodia

Isolated ideal neutron stars (NS) of age $>10^9$ yrs exhaust thermal and rotational energies and cool down to temperatures below $\mathcal{O}(100)$ K. Accretion of particle dark matter (DM) by such NS can heat them up through kinetic and annihilation processes. This increases the NS surface temperature to a maximum of $\sim 2550$ K in the best case scenario.

Robert A. Wilson

The concept of mass was introduced as a mathematical abstraction and unifying principle in physics by Newton in the 17th century, and calibrated on a Solar System scale by Cavendish at the end of the 18th century. In the 19th century, this concept proved adequate to explain a vast range of physical processes on all scales from the microscopic to the Solar Sy

T. Merle, A. S. Hamers, S. Van Eck, A. Jorissen

Binaries have received much attention as possible progenitors of Type Ia supernova (SNIa) explosions, but long-term gravitational effects in tight triple or quadruple systems could also play a key role in producing SNIa. Here we report on the properties of a spectroscopic quadruple (SB4) found within a star cluster: the 2+2 hierarchical system HD 74438. Its

Morteza Hasanvand

Let $G$ be a graph with a spanning subgraph $F$, let $m$ be a positive integer, and let $f$ be a positive integer-valued function on $V(G)$. In this paper, we show that if for all $S\subseteq V(G)$, $$\Omega_m(G\setminus S)\le \sum_{v\in S}\big(f(v)-2m\big)+m+\Omega_m(G[S]),$$ then $G$ has a spanning $m$-tree-connected subgraph $H$ containing $F$ such that f

Yajing Luo, Peng Liang, Mojtaba Shahin, Zengyang Li

In recent years, Continuous Integration (CI) and Continuous Delivery (CD) has been heatedly discussed and widely used in part or all of the software development life cycle as the practices and pipeline to deliver software products in an efficient way. There are many tools, such as Travis CI, that offer various features to support the CI/CD pipeline, but ther

Ferenc Glück

We report a serious kinematics problem in the bremsstrahlung photon part of the order-$\alpha$ outer (model independent) radiative correction calculations for those neutron (and nuclear beta) decay observables (like electron-neutrino correlation parameter measurement) where the proton (recoil particle) is detected. The so-called neutrino-type radiative corre

Rituparna Ghosh, Biswarup Mukhopadhyaya, Utpal Sarkar

The $\rho$-parameter, together with the W-and Z-masses, acts as Occam's razor on extensions of the electroweak symmetry breaking sectors. We apply this to non-doublet Higgs scenarios, by examining the CDF- $II$ claim on the W-boson mass. Suspending any judgement on the CDF claim, we show that in general, if one works at the tree level, theoretical models whi

Mingrui Liu, Zhenxun Zhuang, Yunwei Lei, Chunyang Liao

In distributed training of deep neural networks, people usually run Stochastic Gradient Descent (SGD) or its variants on each machine and communicate with other machines periodically. However, SGD might converge slowly in training some deep neural networks (e.g., RNN, LSTM) because of the exploding gradient issue. Gradient clipping is usually employed to add

Sergey Loyka, Charalambos D. Charalambous

The operational capacity of Gaussian MIMO channels with memory was obtained by Brandenburg and Wyner in [9] under certain mild assumptions on the channel impulse response and its noise covariance matrix, which essentuially require channel memory to be not too strong. This channel was also considered by Tsybakov in [10] and its information capacity was obtain

K. B. Alkalaev, Semyon Mandrygin, Mikhail Pavlov

We consider the conformal block decomposition in arbitrary exchange channels of a two-dimensional conformal field theory on a torus. The channels are described by diagrams built of a closed loop with external legs (a necklace sub-diagram) and trivalent vertices forming trivalent trees attached to the necklace. Then, the $n$-point torus conformal block in any

Mathieu Lizée, Alice Marcotte, Baptiste Coquinot, Nikita Kavokine

The interface between a liquid and a solid is the location of plethora of intrincate mechanisms at the nanoscale, at the root of their specific emerging properties in natural processes or technological applications. However, while the structural properties and chemistry of interfaces have been intensively explored, the effect of the solid-state electronic tr

Xiao Du, Ting Wang, Qiang Feng, Chenhui Ye

The 6G network enables a subnetwork-wide evolution, resulting in a "network of subnetworks". However, due to the dynamic mobility of wireless subnetworks, the data transmission of intra-subnetwork and inter-subnetwork will inevitably interfere with each other, which poses a great challenge to radio resource management. Moreover, most of the existing approach

Caio Henrique Silva de Souza, Josnei Antonio Novacoski, Mark Spivakovsky

In this paper, we study the structure of the graded ring associated to a limit key polynomial $Q_n$ in terms of the key polynomials that define $Q_n$. In order to do that, we use direct limits. In general, we describe the direct limit of a family of graded rings associated to a totally ordered set of valuations. As an example, we describe the graded ring ass

Todd Wareham, Andrew Vardy

Visual and scalar-field (e.g., chemical) sensing are two of the options robot teams can use to perceive their environments when performing tasks. We give the first comparison of the computational characteristic of visual and scalar-field sensing, phrased in terms of the computational complexities of verifying and designing teams of robots to efficiently and

Michał Banacki, Ravishankar Ramanathan, Paweł Horodecki

Motivated by the recent studies on post-quantum steering, we generalize the notion of bipartite channel steering by introducing the concept of multipartite no-signaling channel assemblages. We first show that beyond the bipartite case, the no-signaling and quantum descriptions of channel assemblages do not coincide. Using the Choi-Jamio{\l}kowski isomorphism

Nívea B. da Silva, Luis Iván O. Valencia, Fábio M. H. S. Filho, Andressa C. S. Ferreira

We collected individualized (unidentifiable) and aggregated openly available data from various sources related to suspected/confirmed SARS-CoV-2 infections, vaccinations, non-pharmaceutical government interventions, human mobility, and levels of population inequality in Brazil. In addition, a data structure allowing real-time data collection, curation, integ

He Gao, Wei-Hua Lei, Zi-Pei Zhu

Recently, a kilonova-associated gamma-ray burst (GRB 211211A), whose light curve consists of a precursor ($\sim$0.2 s), a hard spiky emission ($\sim$10 s), and a soft long extended emission ($\sim$40 s), has attracted great attention. Kilonova association could prove its merger origin, while the detection of the precursor can be used to infer at least one hi

Emmanuelle Dietz, Johannes K. Fichte, Florim Hamiti

Cognitive theories for reasoning are about understanding how humans come to conclusions from a set of premises. Starting from hypothetical thoughts, we are interested which are the implications behind basic everyday language and how do we reason with them. A widely studied topic is whether cognitive theories can account for typical reasoning tasks and be con

Ruikang Zhong, Yuanwei Liu, Xidong Mu, Yue Chen

A simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted multi-user downlink multiple-input single-output (MISO) communication system is investigated. In contrast to the existing ideal STAR-RIS model assuming an independent transmission and reflection phase-shift control, a practical coupled phase-shift model is consi

Kris Oosthoek, Jack Cable, Georgios Smaragdakis

Ransomware attacks are among the most severe cyber threats. They have made headlines in recent years by threatening the operation of governments, critical infrastructure, and corporations. Collecting and analyzing ransomware data is an important step towards understanding the spread of ransomware and designing effective defense and mitigation mechanisms. We

Teodora Mihailescu, Deborah Baker, Lucie M. Green, Lidia van Driel-Gesztelyi

The chemical composition of the solar corona is different from that of the solar photosphere, with the strongest variation being observed in active regions (ARs). Using data from the Extreme Ultraviolet (EUV) Imaging Spectrometer (EIS) on Hinode, we present a survey of coronal elemental composition as expressed in the first ionisation potential (FIP) bias in

Nicolas Lang, David J. Wilson

We present $I=1/2$ $D^\ast\pi$ scattering amplitudes from lattice QCD and determine two low-lying $J^P=1^+$ axial-vector $D_1$ states and a $J^P=2^+$ tensor $D_2^\ast$. Computing finite-volume spectra at a light-quark mass corresponding to $m_\pi=391$ MeV, for the first time, we are able to constrain coupled $J^P=1^+$ $D^\ast\pi$ amplitudes with $^{2S+1}\ell

Kewei Wu, Xuewei Jia, Tao Yang, Mengzhao Li

The low gain avalanche detectors (LGADs) are thin sensors with fast charge collection which in combination with internal gain deliver an outstanding time resolution of about 30 ps. High collision rates and consequent large particle rates crossing the detectors at the upgraded Large Hadron Collider (LHC) in 2028 will lead to radiation damage and deteriorated

Georg Maierhofer, Katharina Schratz

Recent years have seen an increasing amount of research devoted to the development of so-called resonance-based methods for dispersive nonlinear partial differential equations. In many situations, this new class of methods allows for approximations in a much more general setting (e.g. for rough data) than, for instance, classical splitting or exponential int

Gianmarco Caldini, Andrea Marchese, Simone Steinbrüchel

We prove that for the generic boundary, in the sense of Baire categories, there exists a unique minimizer of the associated optimal branched transportation problem.

Goran Senjanović, Michael Zantedeschi

A realistic extension of the minimal $SU(5)$ theory consisting of the addition of an adjoint fermion is known to predict light real fermion and scalar weak triplets, potentially accessible at the LHC. These particles, in addition to playing a key role in gauge coupling unification, have profound phenomenological implications. The fermion triplet, that throug

Stefano Turzi

Continuum models of active nematic gels have proved successful to describe a number of biological systems consisting of a population of rodlike motile subunits in a fluid environment. However, in order to get a thorough understanding of the collective processes underlying the behaviour of active biosystems, the theoretical underpinnings of these models still

Abhishek Kumar Singh, Davide Venturelli, Kyle Jamieson

The last couple of years have seen an emergence of physics-inspired computing for maximum likelihood MIMO detection. These methods involve transforming the MIMO detection problem into an Ising minimization problem, which can then be solved on an Ising Machine. Recent works have shown promising projections for MIMO wireless detection using Quantum Annealing o

Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev

Recent methods for visual question answering rely on large-scale annotated datasets. Manual annotation of questions and answers for videos, however, is tedious, expensive and prevents scalability. In this work, we propose to avoid manual annotation and generate a large-scale training dataset for video question answering making use of automatic cross-modal su

Ricard Ravell Rodriguez, Borhan Ahmadi, Pawel Mazurek, Shabir Barzanjeh

We propose a novel approach for optimization of charging of harmonic oscillators (quantum batteries) coupled to a harmonic oscillator (charger), driven by laser field. We demonstrate that energy transfer limitations can be significantly mitigated in the presence of catalyst systems, mediating between the charger and quantum batteries. We show that these cata

Alain Blanchard, Jean-Yves Héloret, Stéphane Ilić, Brahim Lamine

The $\Lambda$CDM model faces several tensions with recent cosmological data and their increased accuracy. The mismatch between the values of the Hubble constant $H_0$ obtained from direct distance ladder measurements and from the cosmic microwave background (CMB) is the most statistically significant, but the amplitude of the matter fluctuations is also rega

Ruifeng Gu

Artificial intelligence algorithms have been extensively applied in the field of intelligent transportation, especially for driving behavior analysis and prediction. This study proposes a novel framework by integrating fuzzy trajectory data, unsupervised learning and supervised learning methods to predict lane-changing behaviors taking multi driving styles i

Jasper Goseling, Milan Lopuhaä-Zwakenberg

We consider the setting of publishing data without leaking sensitive information. We do so in the framework of Robust Local Differential Privacy (RLDP). This ensures privacy for all distributions of the data in an uncertainty set. We formulate the problem of finding the optimal data release protocol as a robust optimization problem. By deriving closed-form e

Ilya Yurchenko, Matthew Farwell, Donovan D. Brady, Cristian Staii

The formation of neuron networks is a process of fundamental importance for understanding the development of the nervous system and for creating biomimetic devices for tissue engineering and neural repair. The basic process that controls the network formation is the growth of an axon from the cell body and its extension towards target neurons. Axonal growth

Zexin Sun, John Baillieul

Building on our recent work on {\em neuromimetic control theory}, new results on resilience and neuro-inspired quantization are reported. The term neuromimetic refers to the models having features that are characteristic of the neurobiology of biological motor control. As in previous work, the focus is on what we call {\em overcomplete} linear systems that a

Jim Agler, Zinaida Lykova, N. J. Young

We introduce the notion of a pseudomultiplier of a Hilbert space $\mathcal H$ of functions on a set $\Omega$. Roughly, a pseudomultiplier of $\mathcal H$ is a function which multiplies a finite-codimensional subspace of $\mathcal H$ into $\mathcal H$, where we allow the possibility that a pseudomultiplier is not defined on all of $\Omega$. A pseudomultiplier

Pedram Beigi, Mohaiminul Haque, Mohammad Sadra Rajabi, Samer Hamdar

Due to the wide-ranging travel restrictions and lockdowns applied to limit the diffusion of the SARS-CoV2 virus, the coronavirus disease of 2019 (COVID-19) pandemic has had an immediate and significant effect on human mobility at the global, national, and local levels. At the local level, bike-sharing played a significant role in urban transport during the p

Amos Uderzo

This paper explores some sufficient conditions for the enhanced solvability of strong vector equilibrium problems, which can be established via a variational approach. Enhanced solvability here means existence of solutions, which are strong with respect to the partial ordering, complemented with inequalities estimating the distance from the solution set (nam

Sai Vidyaranya Nuthalapati, Marcela Vizcaychipi, Pallav Shah, Piotr Chudzik

The COVID-19 pandemic has had a considerable impact on day-to-day life. Tackling the disease by providing the necessary resources to the affected is of paramount importance. However, estimation of the required resources is not a trivial task given the number of factors which determine the requirement. This issue can be addressed by predicting the probability

B. P. Gompertz, M. E. Ravasio, M. Nicholl, A. J. Levan

For decades, gamma-ray bursts (GRBs) have been broadly divided into `long'- and `short'-duration bursts, lasting more or less than 2s, respectively. However, this dichotomy does not map perfectly to the two progenitor channels that are known to produce GRBs -- the merger of compact objects (merger-GRBs) or the collapse of massive stars (collapsar-GRBs). In p

Sushant Kumar, Christian Multunas, Ravishankar Sundararaman

Realizing the potential of plasmonic hot carrier harvesting for energy conversion and photodetection requires new materials that resolve the bottleneck of extracting carriers prior to energy relaxation within the metal. Using first-principles calculations of optical response and carrier transport properties, we show that directional conductors with Fermi vel

David Barbalas, Anaëlle Legros, Gaurab Rimal, Seongshik Oh

The observation of hydrodynamic transport in the metallic delafossite PdCoO$_2$ has increased interest in this family of highly conductive oxides, but experimental studies so far have mostly been confined to bulk crystals. In this work, the development of high-quality thin films of PdCoO$_2$ has enabled a thorough study of the conductivity as a function of f

Lukáš Heriban, Matěj Tušek

The one-dimensional Dirac operator with a singular interaction term which is formally given by $A\otimes|\delta_0\rangle\langle\delta_0|$, where $A$ is an arbitrary $2\times 2$ matrix and $\delta_0$ stands for the Dirac distribution, is introduced as a closed not necessarily self-adjoint operator. We study its spectral properties, find its non-relativistic l

Phuc Thai, My T. Thai, Tam Vu, Thang N. Dinh

Quantum annealing (QA) that encodes optimization problems into Hamiltonians remains the only near-term quantum computing paradigm that provides sufficient many qubits for real-world applications. To fit larger optimization instances on existing quantum annealers, reducing Hamiltonians into smaller equivalent Hamiltonians provides a promising approach. Unfort

Shashank Joshi, Falak Joshi

In human contact, emotion is very crucial. Attributes like words, voice intonation, facial expressions, and kinesics can all be used to portray one's feelings. However, brain-computer interface (BCI) devices have not yet reached the level required for emotion interpretation. With the rapid development of machine learning algorithms, dry electrode techniques,

Jingchen Hu, Matthew R. Williams, Terrance D. Savitsky

This paper introduces a new method that embeds any Bayesian model used to generate synthetic data and converts it into a differentially private (DP) mechanism. We propose an alteration of the model synthesizer to utilize a censored likelihood that induces upper and lower bounds of [$\exp(-\epsilon / 2), \exp(\epsilon / 2)$], where $\epsilon$ denotes the leve

Todd Wareham, Marieke Sweers

Component-Based Development (CBD) is a popular approach to mitigating the costs of creating software systems. However, it is not clear to what extent the core component selection and adaptation activities of CBD can be implemented to operate automatically in an efficient and reliable manner or in what situations (if any) CBD is preferable to other approaches

Stefanie Winkelmann, Johannes Zonker, Christof Schütte, Natasa Djurdjevac Conrad

Agent based models (ABMs) are a useful tool for modeling spatio-temporal population dynamics, where many details can be included in the model description. Their computational cost though is very high and for stochastic ABMs a lot of individual simulations are required to sample quantities of interest. Especially, large numbers of agents render the sampling i

Deyu Xu, Junming Zhao, Linhua Liu

Using a pair of p- and n-type semiconductors separated by a nanoscale vacuum gap, we introduce an optoelectronics element prototype, "photonic p-n junction", as an analogue of the electronic p-n junction, which is demonstrated to serve as an ideal near-field heat flux modulator. The high modulation performance relies on the switch among three fundamental pho

Saeid Tizpaz-Niari, Verya Monjezi, Morgan Wagner, Shiva Darian

This paper presents a data-driven framework to improve the trustworthiness of US tax preparation software systems. Given the legal implications of bugs in such software on its users, ensuring compliance and trustworthiness of tax preparation software is of paramount importance. The key barriers in developing debugging aids for tax preparation systems are the

Malte Londschien, Peter Bühlmann, Solt Kovács

We propose a novel multivariate nonparametric multiple change point detection method using classifiers. We construct a classifier log-likelihood ratio that uses class probability predictions to compare different change point configurations. We propose a computationally feasible search method that is particularly well suited for random forests, denoted by cha

Gabriel Menezes

In this work we explore general leading singularities of one-loop amplitudes in higher-derivative Yang-Mills and quadratic gravity. These theories are known to possess propagators which contain quadratic and quartic momentum dependence, which leads to the presence of an unstable ghostlike resonance. However, unitarity cuts are not to be taken through unstabl

Julian Thoenniss, Alessio Lerose, Dmitry A. Abanin

Describing a quantum impurity coupled to one or more non-interacting fermionic reservoirs is a paradigmatic problem in quantum many-body physics. While historically the focus has been on the equilibrium properties of the impurity-reservoir system, recent experiments with mesoscopic and cold-atomic systems enabled studies of highly non-equilibrium impurity mo

Araceli Bonifant, Chad Estabrooks, Thomas Sharland

We describe a topological relationship between slices of the parameter space of cubic maps. In the paper \cite{CP1}, Milnor defined the curves $\mathcal{S}_n$ as the set of all cubic polynomials with a marked critical point of period $p$. In this paper, we will describe a relationship between the boundaries of the connectedness loci in the curves $\mathcal{S

Mohammad Sadra Rajabi, Hosein Taghaddos, Mehdi Zahrai

Because of the occurrence of severe and large magnitude earthquakes each year, earthquake-prone countries suffer considerable financial damage and loss of life. Teaching essential safety measures will lead to a generation that can perform basic procedures during an earthquake, which is an important and effective solution in preventing the loss of life in thi

Marko Mihajlovic, Aayush Bansal, Michael Zollhoefer, Siyu Tang

Image-based volumetric humans using pixel-aligned features promise generalization to unseen poses and identities. Prior work leverages global spatial encodings and multi-view geometric consistency to reduce spatial ambiguity. However, global encodings often suffer from overfitting to the distribution of the training data, and it is difficult to learn multi-v

Kim Jihyun, Lee Hanul, Lee Sangyun, Park Sungmin

CeCoIn5 (Co115) thin films have been grown on Al2O3 (000l) substrates through the pulsed laser deposition (PLD). The films are grown mainly along the c-axis, with CeIn3 and In-related alloys. The rock-salt type grains are nucleated, where Co115 grains mixed with excess indium are evenly distributed over the substrate. The electrical resistivity of the films

Huimin Hu, Siqing Gan

In this paper, we consider scalar stochastic differential equations (SDEs) with a superlinearly growing and piecewise continuous drift coefficient. Existence and uniqueness of strong solutions of such SDEs are obtained. Furthermore, the classical $L_p$-error rate 1/2 for all $p\in [1, +\infty)$ is recovered for the tamed Euler scheme. A numerical example is

Paul S. Koh

Empirically, many strategic settings are characterized by stable outcomes in which players' decisions are publicly observed, yet no player takes the opportunity to deviate. To analyze such situations in the presence of incomplete information, we build an empirical framework by introducing a novel solution concept that we call Bayes stable equilibrium. Our fr

Todd Wareham

The key to reconciling the polynomial-time intractability of many machine learning tasks in the worst case with the surprising solvability of these tasks by heuristic algorithms in practice seems to be exploiting restrictions on real-world data sets. One approach to investigating such restrictions is to analyze why heuristics perform well under restrictions.

M. J. Kronenburg

Two algorithms for computing $P(n,m)$, the number of integer partitions of $n$ into exactly $m$ parts, are described, and using a combination of these two algorithms, the resulting algorithm is $O(n^{3/2})$. The second algorithm uses a list of $P(n)$, the number of integer partitions of $n$, which is cached and therefore needs to be computed only once. Compu

Alexej Moskovka, Jan Valdman

A simple MATLAB implementation of hierarchical shape functions on 2D rectangles is explained and available for download. Global shape functions are ordered for a given polynomial degree according to the indices of the nodes, edges, or elements to which they belong. For a uniform p-refinement, the hierarchical structure enables an effective assembly of mass a

Witold Andrzejewski, Jedrzej Potoniec, Maciej Drozdowski, Jerzy Stefanowski

In this paper, we consider energy demand prediction in district heating systems. Effective energy demand prediction is essential in combined heat power systems when offering electrical energy in competitive electricity markets. To address this problem, we propose two sets of algorithms: (1) a novel extension to the algorithm proposed by E. Dotzauer and (2) a

Álvaro Montoro

This thesis project arises from the need to put into operation the spectrograph (COLORES) of the station (BOOTES 2), located in La Mayora and belonging to the network of Burst Observer and Optical Transient Exploring System (BOOTES) telescopes. A robotic telescope such as the one located at BOOTES 2 has, among its many virtues, the ability to perform a multi

Adam Ginsburg, Vlas Sokolov, Miguel de Val-Borro, Erik Rosolowsky

pyspeckit is a toolkit and library for spectroscopic analysis in Python. We describe the pyspeckit package and highlight some of its capabilities, such as interactively fitting a model to data, akin to the historically widely-used splot function in IRAF. pyspeckit employs the Levenberg-Marquardt optimization method via the mpfit and lmfit implementations, an