November 2020 arXiv papers — page 3

Alessandra Friedrich Lütz, Marco Antonio Amaral, Lucas Wardil

In a world of hardening borders, nations may deprive themselves of enjoying the benefits of cooperative immigrants. Here, we analyze the effect of efficient cooperative immigrants on a population playing public goods games. We considered a population structured on a square lattice with individuals playing public goods games with their neighbors. The demograp

J. de Curtó, R. Duvall

We introduce a new real-time pipeline for Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO) in the context of planetary rovers. We leverage prior information of the location of the lander to propose an object-level SLAM approach that optimizes pose and shape of the lander together with camera trajectories of the rover. As a furt

Parmida Davarmanesh, Kuanhao Jiang, Tingting Ou, Artem Vysogorets

In spite of advances in gaming hardware and software, gameplay is often tainted with graphics errors, glitches, and screen artifacts. This proof of concept study presents a machine learning approach for automated detection of graphics corruptions in video games. Based on a sample of representative screen corruption examples, the model was able to identify 10

Xuefeng Du, Haochen Zhang, Pengtao Xie

Learning through tests is a broadly used methodology in human learning and shows great effectiveness in improving learning outcome: a sequence of tests are made with increasing levels of difficulty; the learner takes these tests to identify his/her weak points in learning and continuously addresses these weak points to successfully pass these tests. We are i

Yang P. Liu

An important open question in the area of vertex sparsification is whether $(1+\epsilon)$-approximate cut-preserving vertex sparsifiers with size close to the number of terminals exist. The work Chalermsook et al. (SODA 2021) introduced a relaxation called connectivity-$c$ mimicking networks, which asks to construct a vertex sparsifier which preserves connec

Bahman Moraffah, Christ Richmond, Raha Moraffah, Antonia Papandreou-Suppappola

Robust tracking of a target in a clutter environment is an important and challenging task. In recent years, the nearest neighbor methods and probabilistic data association filters were proposed. However, the performance of these methods diminishes as the number of measurements increases. In this paper, we propose a robust generative approach to effectively m

Glebys T. Gonzalez, Upinder Kaur, Masudur Rahma, Vishnunandan Venkatesh

Short response time is critical for future military medical operations in austere settings or remote areas. Such effective patient care at the point of injury can greatly benefit from the integration of semi-autonomous robotic systems. To achieve autonomy, robots would require massive libraries of maneuvers. While this is possible in controlled settings, obt

Roy Adams, Suchi Saria, Michael Rosenblum

The use of observational time series data to assess the impact of multi-time point interventions is becoming increasingly common as more health and activity data are collected and digitized via wearables, social media, and electronic health records. Such time series may involve hundreds or thousands of irregularly sampled observations. One common analysis ap

David Loeffler, Sarah Livia Zerbes

We compute the images of motivic cohomology classes for GSp(4) x GL(2) and GSp(4) x GL(2) x GL(2) under the syntomic regulator, and relate them to non-critical values of p-adic L-functions.

Mikael Beuthe

Isostasy explains why observed gravity anomalies are generally much weaker than what is expected from topography alone, and why planetary crusts can support high topography without breaking up. Classical isostasy, however, neglects internal stresses and geoid contributions to topographical support, and yields ambiguous predictions of geoid anomalies. Isostas

Etienne Richan, Jean Rouat

Searching through vast libraries of sound samples can be a daunting and time-consuming task. Modern audio sample browsers use mappings between acoustic properties and visual attributes to visually differentiate displayed items. There are few studies focused on how well these mappings help users search for a specific sample. We propose new methods for generat

Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu

Supermassive black holes (SMBHs) are ubiquitously found at the centers of most galaxies. Measuring SMBH mass is important for understanding the origin and evolution of SMBHs. However, traditional methods require spectral data which is expensive to gather. To solve this problem, we present an algorithm that weighs SMBHs using quasar light time series, circumv

Thiago Bergamaschi

In this work we study the convergence of a classical algorithm called Simulated Quantum Annealing (SQA) on the Spike Hamiltonian, a specific toy model Hamiltonian for quantum-mechanical tunneling introduced by [FGG02]. This toy model Hamiltonian encodes a simple bit-symmetric cost function f in the computational basis, and is used to emulate local minima in

Seoin Chai, Daniel Rueckert, Ahmed E. Fetit

Despite advances in deep learning, robustness under domain shift remains a major bottleneck in medical imaging settings. Findings on natural images suggest that deep neural models can show a strong textural bias when carrying out image classification tasks. In this thorough empirical study, we draw inspiration from findings on natural images and investigate

Toni Ikonen, Enrico Pasqualetto, Elefterios Soultanis

We construct an isometric embedding from Gigli's abstract tangent module into the concrete tangent module of a space admitting a (weak) Lipschitz differentiable structure, and give two equivalent conditions which characterize when the embedding is an isomorphism. Together with arguments from a recent article by Bate--Kangasniemi--Orponen, this equivalence is

Anirudh Goyal, Yoshua Bengio

A fascinating hypothesis is that human and animal intelligence could be explained by a few principles (rather than an encyclopedic list of heuristics). If that hypothesis was correct, we could more easily both understand our own intelligence and build intelligent machines. Just like in physics, the principles themselves would not be sufficient to predict the

Hugo Duminil-Copin, Ioan Manolescu

This paper studies the critical and near-critical regimes of the planar random-cluster model on $\mathbb Z^2$ with cluster-weight $q\in[1,4]$ using novel coupling techniques. More precisely, we derive the scaling relations between the critical exponents $\beta$, $\gamma$, $\delta$, $\eta$, $\nu$, $\zeta$ as well as $\alpha$ (when $\alpha\ge0$). As a key inpu

Lorenzo Pizzuti, Ippocratis D. Saltas, Luca Amendola

We present an upgraded version of \textsc{MG-MAMPOSSt}, an extension of the \textsc{MAMPOSSt} algorithm that performs Bayesian fits of models of mass and velocity anisotropy profiles to the distribution of tracers in projected phase space, to handle modified gravity models and constrain their parameters. The new version implements two distinct types of gravi

Ilya Gorshkov

The spectrum of a finite group is a set of its element orders. We prove that if $m>5$ then the group $L_{2^m}(2)\times L_{2^m}(2)\times L_{2^m}(2)$ is uniquely determined by its spectrum in the class of finite groups

Jack Holguin, Jeffrey R. Forshaw, Simon Plätzer

The dipole formalism provides a powerful framework from which parton showers can be constructed. In a recent paper, we proposed a dipole shower with improved colour accuracy and in this paper we show how it can be further improved. After an explicit check at $\mathcal{O}(\alpha_{\mathrm{s}}^{2})$ we confirm that our original shower performs as it was designe

Yue Wu

A randomised trapezoidal quadrature rule is proposed for continuous functions which enjoys less regularity than commonly required. Indeed, we consider functions in some fractional Sobolev space. Various error bounds for this randomised rule are established while an error bound for classical trapezoidal quadrature is obtained for comparison. The randomised tr

Bernardo Martin-Iradi, Dario Pacino, Stefan Ropke

We consider a variant of the berth allocation problem-i.e., the multi-port berth allocation problem-aimed at assigning berthing times and positions to vessels in container terminals. This variant involves optimizing vessel travel speeds between multiple ports, thereby exploiting the potentials of a collaboration between carriers (shipping lines) and terminal

Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani

Forecasting complex vehicle and pedestrian multi-modal distributions requires powerful probabilistic approaches. Normalizing flows (NF) have recently emerged as an attractive tool to model such distributions. However, a key drawback is that independent samples drawn from a flow model often do not adequately capture all the modes in the underlying distributio

Ivan Stelmakh, Charvi Rastogi, Nihar B. Shah, Aarti Singh

Peer review is the backbone of academia and humans constitute a cornerstone of this process, being responsible for reviewing papers and making the final acceptance/rejection decisions. Given that human decision making is known to be susceptible to various cognitive biases, it is important to understand which (if any) biases are present in the peer-review pro

Hsin-Po Wang, Iwan Duursma

To multiply astronomic matrices using parallel workers subject to straggling, we recommend interleaving checksums with some fast matrix multiplication algorithms. Nesting the parity-checked algorithms, we weave a product code flavor protection. Two demonstrative configurations are as follows: (A) $9$ workers multiply two $2\times 2$ matrices; each worker mul

Albert Matveev, Ruslan Rakhimov, Alexey Artemov, Gleb Bobrovskikh

We propose Deep Estimators of Features (DEFs), a learning-based framework for predicting sharp geometric features in sampled 3D shapes. Differently from existing data-driven methods, which reduce this problem to feature classification, we propose to regress a scalar field representing the distance from point samples to the closest feature line on local patch

Maciej Kowalski

We give a combinatorial formula for LLT cumulants of unicellular unilevelled shapes in terms of parking functions and Cayley trees. Our formula implies previously conjectured Schur positivity.

Christian Diller, Thomas Funkhouser, Angela Dai

We propose the task of forecasting characteristic 3d poses: from a short sequence observation of a person, predict a future 3d pose of that person in a likely action-defining, characteristic pose -- for instance, from observing a person picking up an apple, predict the pose of the person eating the apple. Prior work on human motion prediction estimates futur

B. C. Hiesmayr, D. McNulty, S. Baek, S. Singha Roy

Mutually unbiased bases (MUBs) provide a standard tool in the verification of quantum states, especially when harnessing a complete set for optimal quantum state tomography. In this work, we investigate the detection of entanglement via inequivalent sets of MUBs, with a particular focus on unextendible MUBs. These are bases for which an additional unbiased b

Andreas Ask, Yao-Lung L. Fang, Anton Frisk Kockum

The absorption of photons in a three-level atom can be controlled and manipulated by applying a coherent drive at one of the atomic transitions. The situation where the absorption is fully canceled, and the atom thus has been turned completely transparent, has been coined electromagnetically induced transparency (EIT). The characteristics of EIT is a narrow

Aneesh Heintz, Vesal Razavimaleki, Javier Duarte, Gage DeZoort

We develop and study FPGA implementations of algorithms for charged particle tracking based on graph neural networks. The two complementary FPGA designs are based on OpenCL, a framework for writing programs that execute across heterogeneous platforms, and hls4ml, a high-level-synthesis-based compiler for neural network to firmware conversion. We evaluate and

Filip Rozpędek, Kyungjoo Noh, Qian Xu, Saikat Guha

We propose an architecture of quantum-error-correction-based quantum repeaters that combines techniques used in discrete- and continuous-variable quantum information. Specifically, we propose to encode the transmitted qubits in a concatenated code consisting of two levels. On the first level we use a continuous-variable GKP code encoding the qubit in a singl

Marco Boggi

For $S=S_{g,n}$ a closed orientable differentiable surface of genus $g$ from which $n$ points have been removed, such that $\chi(S)=2-2g-n<0$, let $\mathrm{P}\Gamma(S)$ be the pure mapping class group of $S$ and $\mathrm{P}\widehat\Gamma(S)$ and $\mathrm{P}\check\Gamma(S)$ be, respectively, its profinite and its congruence completions, the latter being ident

Kartikey Kant, Debasish Pattanayak, Partha Sarathi Mandal

Building structures by low capability robots is a very recent research development. A robot (or a mobile agent) is designed as a deterministic finite automaton. The objective is to make a structure from a given distribution of materials (\textit{bricks}) in an infinite grid $Z\times Z$. The grid cells may contain a brick (\textit{full cells}) or it may be em

Mashnoon Islam, Preetom Nag, Md. Mamun Molla

This paper demonstrates a numerical study of heat transfer in a square porous cavity filled with non-Newtonian power-law fluid. A Graphics Processing Unit (GPU) has been used to accelerate the numerical simulation, which uses the Multiple-Relaxation-Time (MRT) Lattice Boltzmann Method. A modified power-law model has been employed to characterize the flow of

Indranil Biswas, Harald Upmeier

We introduce a class of $G$-invariant connections on a homogeneous principal bundle $Q$ over a hermitian symmetric space $M=G/K$. The parameter space carries the structure of normal variety and has a canonical anti-holomorphic involution. The fixed points of the anti-holomorphic involution are precisely the integrable invariant complex structures on $Q.$ Thi

Jeffrey J. Langford

We compare the solutions of two Poisson problems in a spherical shell with Robin boundary conditions, one with given data, and one where the data has been cap symmetrized. When the Robin parameters are nonnegative, we show that the solution to the symmetrized problem has larger (increasing) convex means. We prove similar results on balls. We also prove a com

W. El Hanafy, Emmanuel N. Saridakis

We investigate the complete universe evolution in the framework of $f(T)$ cosmology. We first study the requirements at the kinematic level and we introduce a simple scale factor with the necessary features. Performing a detailed analysis of the phase portrait we show that the universe begins in the infinite past from a phase where the scale factor goes to z

Rémy Brossard, Oriel Frigo, David Dehaene

Despite quick progress in the last few years, recent studies have shown that modern graph neural networks can still fail at very simple tasks, like detecting small cycles. This hints at the fact that current networks fail to catch information about the local structure, which is problematic if the downstream task heavily relies on graph substructure analysis,

Xunyi Wang, Reza Mousavi, Yili Hong

The COVID-19 pandemic has posed an unprecedented challenge to individuals around the globe. To mitigate the spread of the virus, many states in the U.S. issued lockdown orders to urge their residents to stay at their homes, avoid get-togethers, and minimize physical interactions. While many offline workers are experiencing significant challenges performing t

Marlene Berke, Mario Belledonne, Julian Jara-Ettinger

Beyond representing the external world, humans also represent their own cognitive processes. In the context of perception, this metacognition helps us identify unreliable percepts, such as when we recognize that we are seeing an illusion. Here we propose MetaGen, a model for the unsupervised learning of metacognition. In MetaGen, metacognition is expressed a

Mikael Beuthe, Bernard Charlier, Olivier Namur, Attilio Rivoldini

Mercury's crust has a complex structure resulting from a billion years of volcanism. The surface variations in chemical composition have been identified from orbit by the spacecraft MESSENGER. Combining these measurements with laboratory experiments on partial melting, we estimate which variations in surface density and degree of mantle melting are required

Olivier Nicole, Matthieu Lemerre, Sébastien Bardin, Xavier Rival

The kernel is the most safety- and security-critical component of many computer systems, as the most severe bugs lead to complete system crash or exploit. It is thus desirable to guarantee that a kernel is free from these bugs using formal methods, but the high cost and expertise required to do so are deterrent to wide applicability. We propose a method that

David Loeffler, Sarah Livia Zerbes

We develop a (largely conjectural) theory of p-adic L-functions interpolating square roots of central L-values for automorphic forms on GSp(4) x GL(2) x GL(2), and a relation between these p-adic L-functions and families of Galois cohomology classes interpolating algebraic cycles. Our theory is a generalisation of the theory of "diagonal cycles" developed by

Lulu Fan, Wen Chen, Tao An, Fu-Guo Xie

WISE J224607.56$-$052634.9 (W2246-0526) is a hyperluminous ($L_{\rm bol}\approx 1.7\times 10^{14}~L_\odot$), dust-obscured and radio-quiet quasar at redshift $z=4.6$. It plays a key role in probing the transition stage between dusty starbursts and unobscured quasars in the co-evolution of galaxies and supermassive black holes (SMBHs). To search for the evide

Peter S. Morfe

This paper analyzes two classes of second order level set PDE in periodic media in the parabolic scaling. First, we study fully nonlinear geometric operators under general assumptions in dimension $d = 2$ and prove that the associated equations homogenize in this case. Next, we treat a class of quasi-linear geometric operators in arbitrary dimensions $d \geq

D. Bosch, P. Acosta Alba, S. Kerdiles, V. Benevent

To take fully advantage of Junctionless transistor (JLT) low-cost and low-temperature features we investigate a 475 degC process to create onto a wafer a thin poly-Si layer on insulator. We fabricated a 13nm doped (Phosphorous, 1E19 at/cm3) poly-silicon film featuring excellent roughness values (Rmax= 1.6nm and RMS=0.2nm). Guidelines for grain size optimizat

Sara Khatibi, Hamzeh Khanpour

In this paper, we study the triple top quark production at the future high-energy proton-proton colliders to probe the four-fermion interactions involving three top quarks. We employ the Standard Model Effective Field Theory (SMEFT) to find the upper limits at $95\%$ CL on the Wilson coefficients of these kinds of four-fermion operators. We consider a detail

C. Carstensen, N. T. Tran

The relaxation in the calculus of variation motivates the numerical analysis of a class of degenerate convex minimization problems with non-strictly convex energy densities with some convexity control and two-sided $p$-growth. The minimizers may be non-unique in the primal variable but lead to a unique stress $\sigma \in H(\operatorname{div},\Omega;\mathbb{M

Nikolaos Michael Ladas, John Christopher Meyer

We present extensions of the comparison and maximum principles available for nonlinear non-local integro-differential operators $P:\mathcal{C}^{2,1}(\Omega \times (0,T])\times L^\infty (\Omega \times (0,T])\to\mathbb{R}$, of the form $P[u] = L[u] -f(\cdot ,\cdot ,u,Ju)$ on $\Omega \times (0,T]$. Here, we consider: unbounded spatial domains $\Omega \subset \m

Peter Constantin, Mihaela Ignatova, Fizay-Noah Lee

We consider the limit of vanishing Debye length for ionic diffusion in fluids, described by the Nernst-Planck-Navier-Stokes system. In the asymptotically stable cases of blocking (vanishing normal flux) and uniform selective (special Dirichlet) boundary conditions for the ionic concentrations, we prove that the ionic charge density $\rho$ converges in time t

Jakub M. Tomczak

In this paper, we present a new class of invertible transformations with an application to flow-based generative models. We indicate that many well-known invertible transformations in reversible logic and reversible neural networks could be derived from our proposition. Next, we propose two new coupling layers that are important building blocks of flow-based

Slade Gunter, Eyvi Palsson, Ben Rhodes, Steven Senger

We study a family of variants of Erd\H os' unit distance problem, concerning distances and dot products between pairs of points chosen from a large finite point set. Specifically, given a large finite set of $n$ points $E$, we look for bounds on how many subsets of $k$ points satisfy a set of relationships between point pairs based on distances or dot produc

Paolo Antonelli, Giada Cianfarani Carnevale, Corrado Lattanzio, Stefano Spirito

The relaxation-time limit from the Quantum-Navier-Stokes-Poisson system to the quantum drift-diffusion equation is performed in the framework of finite energy weak solutions. No assumptions on the limiting solution are made. The proof exploits the suitably scaled a priori bounds inferred by the energy and BD entropy estimates. Moreover, it is shown how from

Joaquim Gomis, Diego Hidalgo, Patricio Salgado-Rebolledo

We construct the non-relativistic and Carrollian versions of Jackiw-Teitelboim gravity. In the second order formulation, there are no divergences in the non-relativistic and Carrollian limits. Instead, in the first order formalism there are divergences that can be avoided by starting from a relativistic BF theory with (A)dS2$\times\mathbb{R}$ gauge algebra.

Yves Blickenstorfer, Markus Müller, Roland Dreyfus, Andreas Michael Reichmuth

Diffractometric biosensing is a promising technology to overcome critical limitations of refractometric biosensors, the dominant class of label-free optical transducers. These limitations manifest themselves by higher noise and drifts due to insufficient rejection of refractive index fluctuations caused by variation in temperature, solvent concentration, and

Francesco Regazzoni, Matteo Salvador, Pasquale Claudio Africa, Marco Fedele

In the framework of accurate and efficient segregated schemes for 3D cardiac electromechanics and 0D cardiovascular models, we propose here a novel numerical approach to address the coupled 3D-0D problem introduced in Part I of this two-part series of papers. We combine implicit-explicit schemes to solve the different cardiac models in a multiphysics setting

Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé

Conference peer review constitutes a human-computation process whose importance cannot be overstated: not only it identifies the best submissions for acceptance, but, ultimately, it impacts the future of the whole research area by promoting some ideas and restraining others. A surge in the number of submissions received by leading AI conferences has challeng

Vinicius Pavanelli Vianna, Luiz Otavio Murta

Image registration is a key operation in medical image processing, allowing a plethora of applications. Mutual information (MI) is consolidated as a robust similarity metric often used for medical image registration. Although MI provides a robust medical image registration, it usually fails when the needed image transform is too big due to MI local maxima tr

Juan Carlos Garcia-Escartin, Vicent Gimeno, Julio José Moyano-Fernández

Linear optical systems acting on photon number states produce many interesting evolutions, but cannot give all the allowed quantum operations on the input state. Using Toponogov's theorem from differential geometry, we propose an iterative method that, for any arbitrary quantum operator $U$ acting on $n$ photons in $m$ modes, returns an operator $\widetilde{

Stefan Schreieder

We show that there are smooth complex projective varieties with infinite 2-torsion in their third Griffiths groups. It follows that the torsion subgroup of Griffiths groups is in general not finitely generated, thereby solving a problem of Schoen from 1992.

Haydar Taylan Turan, Markus Meuwly

S-nitrosylation, the covalent addition of NO to the thiol side chain of cysteine, is an important post-transitional modification that can alter the function of various proteins. The structural dynamics and vibrational spectroscopy of S-nitrosylation in the condensed phase is investigated for the methyl-capped cysteine model system and for myoglobin. Using co

Dev Yashpal Sheth, Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro

Deep convolutional neural networks (CNNs) for video denoising are typically trained with supervision, assuming the availability of clean videos. However, in many applications, such as microscopy, noiseless videos are not available. To address this, we propose an Unsupervised Deep Video Denoiser (UDVD), a CNN architecture designed to be trained exclusively wi

Ivan Dynnikov, Pascal Hubert, Alexandra Skripchenko

At the beggining of the 80's, H.Masur and W.Veech started the study of generic properties of interval exchange transformations proving that almost every such transformation is uniquely ergodic. About the same time, S.Novikov's school and French mathematicians independently discovered very intriguing phenomena for classes of measured foliations on surfaces an

Yuanqi Wang

When the rank of the bundle is $\geq 2$, in a certain sense, we found an essential obstruction for the gluing construction of $G_{2}-$instantons with $1-$dimensional singularities. It involves the Atiyah classes generated by contracting a vector in $\mathbb{C}^{3}$ with the curvature. Intuitively speaking, the gluing does not work if the tangent connection a

Simone Colucci, Paolo Papale

Explosive eruptions are the surface manifestation of dynamics that involve transfer of magma from the underground regions of magma accumulation. Evidence of the involvement of compositionally different magmas from different reservoirs is continuously increasing to countless cases. Yet, models of eruption dynamics consider only the uppermost portion of the pl

Francesco Regazzoni, Matteo Salvador, Pasquale Claudio Africa, Marco Fedele

We propose an integrated electromechanical model of the human heart, with focus on the left ventricle, wherein biophysically detailed models describe the different physical phenomena concurring to the cardiac function. We model the subcellular generation of active force by means of an Artificial Neural Network, which is trained by a suitable Machine Learning

Runzhong Wang, Tianqi Zhang, Tianshu Yu, Junchi Yan

Graph Edit Distance (GED) is a popular similarity measurement for pairwise graphs and it also refers to the recovery of the edit path from the source graph to the target graph. Traditional A* algorithm suffers scalability issues due to its exhaustive nature, whose search heuristics heavily rely on human prior knowledge. This paper presents a hybrid approach

Rafi Trad, Myra Spiliopoulou

Authorial clustering involves the grouping of documents written by the same author or team of authors without any prior positive examples of an author's writing style or thematic preferences. For authorial clustering on shorter texts (paragraph-length texts that are typically shorter than conventional documents), the document representation is particularly i

Erik van Zwet, Andrew Gelman

If we have an unbiased estimate of some parameter of interest, then its absolute value is positively biased for the absolute value of the parameter. This bias is large when the signal-to-noise ratio (SNR) is small, and it becomes even larger when we condition on statistical significance; the winner's curse. This is a frequentist motivation for regularization

Robert Harper, Philip Tee

The structure of complex networks has long been understood to play a role in transmission and spreading phenomena on a graph. This behavior is difficult to model analytically and is most often modeled numerically. Such networks form an important part of the structure of society, including transportation networks. As society fights to control the COVID-19 pan

Elie Hachem, Hassan Ghraieb, Jonathan Viquerat, Aurélien Larcher

This research gauges the ability of deep reinforcement learning (DRL) techniques to assist the control of conjugate heat transfer systems governed by the coupled Navier--Stokes and heat equations. It uses a novel, "degenerate" version of the proximal policy optimization (PPO) algorithm, intended for situations where the optimal policy to be learnt by a neura

Dorsa Mohammadi Arezooji

A hierarchical logistic regression Bayesian model is proposed and implemented in R to model the probability of patient improvement corresponding to any given dosage of a certain drug. RStan is used to obtain samples from the posterior distributions via Markov Chain Monte-Carlo (MCMC) sampling. The effects of selecting different families of prior distribution

S. Verma, S. Jha

We provide a rigorous study on dimensions of fractal interpolation function defined on a closed and bounded interval of $\mathbb{R}$ which is associated to a continuous function with respect to a base function, scaling functions and a partition of the interval. In particular, we provide an exact estimation of the box dimension of $\alpha$-fractal functions.

Saeed Nasseh, Maiko Ono, Yuji Yoshino

A major part of this paper is devoted to an in-depth study of j-operators and their properties. This study enables us to obtain several results on liftings and weak liftings of DG modules along simple extensions of DG algebras and unify the proofs of the existing results obtained by the authors on these subjects. Finally, we provide a new characterization of

Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta

The backpropagation algorithm is an invaluable tool for training artificial neural networks; however, because of a weight sharing requirement, it does not provide a plausible model of brain function. Here, in the context of a two-layer network, we derive an algorithm for training a neural network which avoids this problem by not requiring explicit error comp

M. Lacy, J. A. Surace, D. Farrah, K. Nyland

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will observe several Deep Drilling Fields (DDFs) to a greater depth and with a more rapid cadence than the main survey. In this paper, we describe the ``DeepDrill'' survey, which used the Spitzer Space Telescope Infrared Array Camera (IRAC) to observe three of the four currently defined DDF

Antonio Martínez, A. L. Martínez-Triviño, J. P. dos Santos

We establish curvature estimates and a convexity result for mean convex properly embedded $[\varphi,\vec{e}_{3}]$-minimal surfaces in $\mathbb{R}^3$, i.e., $\varphi$-minimal surfaces when $\varphi$ depends only on the third coordinate of $\mathbb{R}^3$. Led by the works on curvature estimates for surfaces in 3-manifolds, due to White for minimal surfaces, to

Alexandru Iosup, Ahmed Musaafir, Alexandru Uta, Arnau Prat Pérez

In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective comparison of graph analysis platforms. Due to the diversity of bottlenecks and performance issues such platforms need to address, Graphalytics consists of a set of selected determinist

Stefan Antusch, Christian Hohl, Vasja Susič

While the observation of nucleon decay would be a smoking gun of Grand Unified Theories (GUTs) in general, the ratios between the decay rates of the various channels carry rich information about the specific GUT model realization. To investigate this fingerprint of GUT models in the context of supersymmetric (SUSY) GUTs, we present the software tool \texttt{

Jiří Kovář, Yasufumi Kojima, Petr Slaný, Zdeněk Stuchlík

Charged fluids rotating around compact objects can form unique equilibrium structures when ambient large-scale electromagnetic fields combine with strong gravity. Equatorial as well as off-equatorial toroidal structures are among such figures of equilibrium with a direct relevance for astrophysics. To investigate their geometrical shapes and physical propert

Zhiyuan Yao, Feng Yuan, Jeremiah P. Ostriker

In a previous work, we have proposed a sub-grid model of active galactic nucleus (AGN) feedback by taking into account the state-of-the-art AGN physics, and used that model to study the effect of AGN feedback on the evolution of an isolated elliptical galaxy by performing two dimensional high-resolution (i.e., the Bondi radius is well resolved) simulations.

Siddharth Dalmia, Yuzong Liu, Srikanth Ronanki, Katrin Kirchhoff

We live in a world where 60% of the population can speak two or more languages fluently. Members of these communities constantly switch between languages when having a conversation. As automatic speech recognition (ASR) systems are being deployed to the real-world, there is a need for practical systems that can handle multiple languages both within an uttera

Amar Deep Sarkar

In this note, we use scaling principle to study the boundary behaviour of the span metric and its higher-order curvatures on finitely connected Jordan planar domains. A localization of this metric near boundary points of finitely connected Jordan domains is also obtained. Further, we obtain boundary sharp estimates for this metric on $ C^2 $-smooth bounded d

Daniel Gratzer, G. A. Kavvos, Andreas Nuyts, Lars Birkedal

We introduce MTT, a dependent type theory which supports multiple modalities. MTT is parametrized by a mode theory which specifies a collection of modes, modalities, and transformations between them. We show that different choices of mode theory allow us to use the same type theory to compute and reason in many modal situations, including guarded recursion,

Moonyoung Lee, Youngsun Kwon, Sebin Lee, JongHun Choe

Although bipedal locomotion provides the ability to traverse unstructured environments, it requires careful planning and control to safely walk across without falling. This poses an integrated challenge for the robot to perceive, plan, and control its movements, especially with dynamic motions where the robot may have to adapt its swing-leg trajectory onthe-

Jesús García Díaz, Julio César Pérez Sansalvador, Lil María Xibai Rodríguez Henríquez, José Alejandro Cornejo Acosta

The graph burning problem is an NP-hard combinatorial optimization problem that helps quantify the vulnerability of a graph to contagion. This paper introduces a simple farthest-first traversal-based approximation algorithm for this problem over general graphs. We refer to this proposal as the Burning Farthest-First (BFF) algorithm. BFF runs in $O(n^3)$ step

Giovanni Aricò, Raul E. Angulo, Sergio Contreras, Lurdes Ondaro-Mallea

We present a neural-network emulator for baryonic effects in the non-linear matter power spectrum. We calibrate this emulator using more than 50,000 measurements in a 15-dimensional parameters space, varying cosmology and baryonic physics. Baryonic physics is described through a baryonification algorithm, that has been shown to accurately capture the relevan

D. Slobinsky, L. Pili, G. Baglietto, S. A. Grigera

Ising models on a pyrochlore oxide lattice are usually associated with spin ice materials and "magnetic monopoles". Ever more often effects connecting magnetic and elastic degrees of freedom are reported on these and other related frustrated materials. Here we extend a spin-ice Hamiltonian to include coupling between spins and the O$^{-2}$ ions mediating sup

Thao P. Le, Alexandra Olaya-Castro

Advancing our understanding of non-trivial quantum effects in biomolecular complexes operating in physiological conditions requires the precise characterisation of the non-classicalities that may be present in such systems as well as asserting whether such features are required for robust function. Here we consider an avian-inspired quantum magnetic sensor c

Xiang Ni, Zhen Yang, Jianyu Li

Tough adhesive hydrogels find broad applications in engineering and medicine. Such hydrogels feature high resistance against both cohesion and adhesion failure. The superior fracture properties may, however, deteriorate when the hydrogels swell upon exposure of water. The underlying correlation between the polymer fraction and fracture properties of tough ad

Wanxin Jin, Todd D. Murphey, Zehui Lu, Shaoshuai Mou

This paper proposes a novel approach that enables a robot to learn an objective function incrementally from human directional corrections. Existing methods learn from human magnitude corrections; since a human needs to carefully choose the magnitude of each correction, those methods can easily lead to over-corrections and learning inefficiency. The proposed

Eleni Bila, John Derrick, Simon Doherty, Brijesh Dongol

Non-volatile memory (NVM), also known as persistent memory, is an emerging paradigm for memory that preserves its contents even after power loss. NVM is widely expected to become ubiquitous, and hardware architectures are already providing support for NVM programming. This has stimulated interest in the design of novel concepts ensuring correctness of concur

Abdellatif Ben Makhlouf

In this article, a novel Finite Time Stability (FTS) analysis of Fractional-Order Time Delay Systems (FOTDSs) is proposed. By using the fixed point approach, sufficient conditions for the robust FTS of FOTDSs have been established. Two illustrative examples are provided to prove the validity of the main result.

Peter S. Morfe

We analyze the sharp interface limit for the Allen-Cahn equation with an anisotropic, spatially periodic mobility coefficient and prove that the large-scale behavior of interfaces is determined by mean curvature flow with an effective mobility. Formally, the result follows from the asymptotics developed by Barles and Souganidis for bistable reaction-diffusio

Carlos R. Handy

For low dimension systems admitting a moment equation representation (MER), the development of an effective eigenenergy bounding theory applicable to all discrete states had remained elusive, until now. Whereas Handy et al (1988 Phys. Rev. Lett. 60 253) demonstrated the effectiveness of the {\it Moment Problem} based, Eigenvalue Moment Method (EMM), for gene

Chengcheng Yang

This paper studies a problem of Erd\"{o}s concerning lattice cubes. Given an $N \times N \times N$ lattice cube, we want to find the maximum number of vertices one can select so that no eight corners of a rectangular box are chosen simultaneously. Erd\"{o}s conjectured that it has a sharp upper bound, which is $O(N^{11/4})$, but no example that large has bee

Maxime Gheysens

We study the topological structure and the topological dynamics of groups of homeomorphisms of scattered spaces. For a large class of them (including the homeomorphism group of any ordinal space or of any locally compact scattered space), we establish Roelcke-precompactness and amenability, classify all closed normal subgroups and compute the universal minim

Tao Yu, Chen Wang, Michael A. Sentef, Gerrit E. W. Bauer

The Doppler shift of the quasiparticle dispersion by charge currents is responsible for the critical supercurrents in superconductors and instabilities of the magnetic ground state of metallic ferromagnets. Here we predict an analogous effect in thin films of magnetic insulators in which microwaves emitted by a proximity stripline generate coherent chiral sp

Brady Neal, Chin-Wei Huang, Sunand Raghupathi

There are many different causal effect estimators in causal inference. However, it is unclear how to choose between these estimators because there is no ground-truth for causal effects. A commonly used option is to simulate synthetic data, where the ground-truth is known. However, the best causal estimators on synthetic data are unlikely to be the best causa