November 2022 arXiv papers — page 110

Ron Fulbright, Grover Walters

We will soon be surrounded by artificial systems capable of cognitive performance rivaling or exceeding a human expert in specific domains of discourse. However, these cogs need not be capable of full general artificial intelligence nor able to function in a stand-alone manner. Instead, cogs and humans will work together in collaboration each compensating fo

Ron Fulbright

Computers are quickly gaining on us. Artificial systems are now exceeding the performance of human experts in several domains. However, we do not yet have a deep definition of expertise. This paper examines the nature of expertise and presents an abstract knowledge-level and skill-level description of expertise. A new level lying above the Knowledge Level, c

Ron Fulbright

We are entering an era in which humans will increasingly work in partnership and collaboration with artificially intelligent entities. For millennia, tools have augmented human physical and mental performance but in the coming era of cognitive systems, human cognitive performance will be augmented. We are only just now beginning to define the fundamental con

Beltrán Labrador, Guanlong Zhao, Ignacio López Moreno, Angelo Scorza Scarpati

In this paper, we present a novel approach to adapt a sequence-to-sequence Transformer-Transducer ASR system to the keyword spotting (KWS) task. We achieve this by replacing the keyword in the text transcription with a special token <kw> and training the system to detect the <kw> token in an audio stream. At inference time, we create a decision function insp

Ron Fulbright

We are at the beginning of a new age in which artificial entities will perform significant amounts of high-level cognitive processing rivaling and even surpassing human thinking. The future belongs to those who can best collaborate with artificial cognitive entities achieving a high degree of cognitive augmenta-tion. However, we currently lack theoretically

Adán Cabello

In a recent note, Hance and Hossenfelder (arXiv:2211.01331) recall that "locally causal completions of quantum mechanics are possible, if they violate the assumption [called statistical independence or measurement independence] that the hidden variables do not in any way depend on measurement settings" and that, consequently, the experimental violations of B

Xiangyu Gao, Divya Raghunathan, Ruijie Fang, Tao Wang

Compiling high-level programs to target high-speed packet-processing pipelines is a challenging combinatorial optimization problem. The compiler must configure the pipeline's resources to match the high-level semantics of the program, while packing all of the program's computation into the pipeline's limited resources. State of the art approaches tackle indi

Peng-Jen Chen, Kevin Tran, Yilin Yang, Jingfei Du

We study speech-to-speech translation (S2ST) that translates speech from one language into another language and focuses on building systems to support languages without standard text writing systems. We use English-Taiwanese Hokkien as a case study, and present an end-to-end solution from training data collection, modeling choices to benchmark dataset releas

Marcos Barrios, Gustavo Mata

In this article we prove that, under certain hypotheses, Morita context algebras that have zero bimodule morphisms have finite $\phi$-dimension. We also study the behaviour of the $\phi$-dimension for an algebra and its opposite. In particular we show that the $\phi$-dimension of an Artin algebra is not symmetric, i.e. there exists a finite dimensional algeb

Thomas Byrne

Following the solution to the One-Round Voronoi Game in arXiv:2011.13275, we naturally may want to consider similar games based upon the competitive locating of points and subsequent dividing of territories. In order to appease the tears of White (the first player) after they have potentially been tricked into going first in a game of point-placement, an alt

Hyuk-Yong Kwon, Gregory M. Curtin, Zachary Morrow, C. T. Kelley

Electronic structure calculations on small systems such as H$_2$, H$_2$O, LiH, and BeH$_2$ with chemical accuracy are still a challenge for the current generation of the noisy intermediate-scale quantum (NISQ) devices. One of the reasons is that due to the device limitations, only minimal basis sets are commonly applied in quantum chemical calculations, whic

Yuewei Yang, Jingwei Sun, Ang Li, Hai Li

Discriminative unsupervised learning methods such as contrastive learning have demonstrated the ability to learn generalized visual representations on centralized data. It is nonetheless challenging to adapt such methods to a distributed system with unlabeled, private, and heterogeneous client data due to user styles and preferences. Federated learning enabl

Huan Zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach

The use of neural network parametrizations to represent the ground state in variational Monte Carlo (VMC) calculations has generated intense interest in recent years. However, as we demonstrate in the context of the periodic Heisenberg spin chain, this approach can produce unreliable wave function approximations. One of the most obvious signs of failure is t

Matt Visser

Over the last 50 years a large number of effective exponential bounds on the first Chebyshev function $\vartheta(x)$ have been obtained. Specifically we shall be interested in effective exponential bounds of the form \[ |\vartheta(x)-x| < a \;x \;(\ln x)^b \; \exp\left(-c\; \sqrt{\ln x}\right); \qquad (x \geq x_0). \] Herein we shall convert these effective

Sahar Satoori, Saeed Mahdavifar, Javad Vahedi

We consider the spin-$1/2$ XY frustrated antiferromagnetic Heisenberg honeycomb model. There is an unclear intermediate region in the ground state phase diagram of the model. The most recognized phases are the quantum spin-liquid (QSL) and the antiferromagnetic Ising ordering. From the viewpoint of the quantum correlations, the QSL phase is expected to be en

Luis Alvarez-Gaume, Miguel A. Vazquez-Mozo

Anomalies are a very powerful tool in constraining theories beyond the standard model. We give a pedagogical overview of some topics illustrating the important role played by spacetime anomalies in string theory. After discussing the general problem of anomaly cancellation in quantum field theory, the focus is set on the cancellation of anomalies in type-I s

Rajat Majumder, Alexander Yu. Sokolov

We present the first implementation of spin-orbit coupling effects in fully internally contracted second-order quasidegenerate N-electron valence perturbation theory (SO-QDNEVPT2). The SO-QDNEVPT2 approach enables the computations of ground- and excited-state energies and oscillator strengths combining the description of static electron correlation with an e

Michał Czakon, Felix Eschment, Tom Schellenberger

We evaluate the one-loop soft current for the emission of two soft gluons or a soft quark-anti-quark pair in massless Quantum Chromodynamics. The results are exact in dimensional regularisation up to a single Feynman integral. Two terms of the Taylor series of the latter integral as a function of $\epsilon \equiv (4-d)/2$ with $d$ the dimension of spacetime

Shahin S. Nudehi, Dominic Groß

In this work, we investigate grid-forming control for power systems containing three-phase and single-phase converters connected to unbalanced distribution and transmission networks, investigate self-balancing between single-phase converters, and propose a novel balancing feedback for grid-forming control that explicitly allows to trade-off unbalances in vol

Gregory P. Davis, Garrett E. Katz, Rodolphe J. Gentili, James A. Reggia

Imitation learning allows social robots to learn new skills from human teachers without substantial manual programming, but it is difficult for robotic imitation learning systems to generalize demonstrated skills as well as human learners do. Contemporary neurocomputational approaches to imitation learning achieve limited generalization at the cost of data-i

Monika I. Jurkovic, Emese Plachy, László Molnár, Martin A. T. Groenewegen

We present the results of the analysis of Type II and anomalous Cepheids using the data from the Kepler K2 mission. The precise light curves of these pulsating variable stars are the key to study the details of their pulsation, such as the period-doubling effect or the presence of additional modes. We applied the Automated Extended Aperture Photometry (autoE

Lorenzo Posti

Correlations between velocity measurements in disk galaxy rotation curves are usually neglected when fitting dynamical models. Here I show how data correlations can be taken into account in rotation curve decompositions using Gaussian Processes. I find that marginalizing over correlation parameters proves critical to obtain unbiased estimates of the luminous

Josh Alman, Kevin Rao

We give algorithms with lower arithmetic operation counts for both the Walsh-Hadamard Transform (WHT) and the Discrete Fourier Transform (DFT) on inputs of power-of-2 size $N$. For the WHT, our new algorithm has an operation count of $\frac{23}{24}N \log N + O(N)$. To our knowledge, this gives the first improvement on the $N \log N$ operation count of the si

Nathan Kallus, James McInerney

Epistemic uncertainty quantification is a crucial part of drawing credible conclusions from predictive models, whether concerned about the prediction at a given point or any downstream evaluation that uses the model as input. When the predictive model is simple and its evaluation differentiable, this task is solved by the delta method, where we propagate the

Llorenç Escolà-Farràs, Jaròn Has, Maris Ozols, Christian Schaffner

Local simultaneous state discrimination (LSSD) is a recently introduced problem in quantum information processing. Its classical version is a non-local game played by non-communicating players against a referee. Based on a known probability distribution, the referee generates one input for each of the players and keeps one secret value. The players have to g

Romeo Ortega, Alexey Bobtsov, Ramon Costa-Castello, Nikolay Nikolaev

In this paper we address the challenging problem of designing globally convergent estimators for the parameters of nonlinear systems containing a non-separable exponential nonlinearity. This class of terms appears in many practical applications, and none of the existing parameter estimators is able to deal with them in an efficient way. The proposed estimati

Hunter Campbell, Elliott Khilfeh, Kevin R. Covey, Marina Kounkel

Very young (t $\lesssim$ 10 Myrs) stars possess strong magnetic fields that channel ionized gas from the interiors of their circumstellar discs to the surface of the star. Upon impacting the stellar surface, the shocked gas recombines and emits hydrogen spectral lines. To characterize the density and temperature of the gas within these accretion streams, we

Xuanhong An, David Williams

The experiment of separated flow response to a single-burst actuation over a 2-D NACA-0009 airfoil at $12^o$ angle of attack was conducted. The mechanism of the lift and pitching moment reversal following the single-burst actuation was studied. A spatially localized region of high pressure caused by a vortices-induced downwash is responsible for the lift and

Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan

The prevalence of abusive language on different online platforms has been a major concern that raises the need for automated cross-platform abusive language detection. However, prior works focus on concatenating data from multiple platforms, inherently adopting Empirical Risk Minimization (ERM) method. In this work, we address this challenge from the perspec

Athanasios Kalogiratos, Ioanna Kantzavelou

Bluetooth is a communication technology used to wirelessly exchange data between devices. In the last few years there have been found a great number of security vulnerabilities, and adversaries are taking advantage of them causing harm and significant loss. Numerous system security updates have been approved and installed in order to sort out security holes

Robert A. West, Philip Dumont, Renyu Hu, Vijay Natraj

In our solar system, the densely cloud-covered atmosphere of Venus stands out as an example of how polarimetry can be used to gain information on cloud composition and particle mean radius. With current interest running high on discovering and characterizing extrasolar planets in the habitable zone where water exists in the liquid state, making use of spectr

Suryansh Upadhyay, Mahabubul Alam, Swaroop Ghosh

Quantum computing is changing the way we think about computing. Significant strides in research and development for managing and harnessing the power of quantum systems has been made in recent years, demonstrating the potential for transformative quantum technology. Quantum phenomena like superposition, entanglement, and interference can be exploited to solv

Fabio Siringo

A general formal derivation of the screened massive expansion is provided by Schwinger-Dyson equations. Some known issues of the expansion are clarified and a more general framework is established for a natural extension of the method to two-loop or to amplitudes which are not directly defined by a generating functional. For instance, a one-loop screened exp

Clarence Protin

In this essay we examine some aspects of the classical theory of definition as codified in Aristotle's \emph{Topics} and Porphyry's \emph{Eisagog\^e} in the light of the way definition is carried out in modern mathematical practice. Our goal is to contribute to the understanding of the alleged gap existing between ancient and modern logic and science as well

Avital Dery

Recent progress has demonstrated that the $K\to\mu^+\mu^-$ decay carries clean short-distance information, attainable from a measurement of time-dependence sensitive to $K_L-K_S$ interference effects. We review the ingredients that go into this proposed extraction, and discuss the sensitivity to the CKM parameter $\bar\eta$ as well as to various NP scenarios

Collin Cherubim, Ryan Cloutier, David Charbonneau, Bill Wohler

Characterizing the bulk compositions of transiting exoplanets within the M dwarf radius valley offers a unique means to establish whether the radius valley emerges from an atmospheric mass loss process or is imprinted by planet formation itself. We present the confirmation of such a planet orbiting an early M dwarf ($T_{\rm mag} = 11.0294 \pm 0.0074, M_s = 0

Bashirul Azam Biswas, Qiang Ji

The quality of scene graphs generated by the state-of-the-art (SOTA) models is compromised due to the long-tail nature of the relationships and their parent object pairs. Training of the scene graphs is dominated by the majority relationships of the majority pairs and, therefore, the object-conditional distributions of relationship in the minority pairs are

Rajibul Islam, Ghulam Hussain, Rahul Verma, Mohammad Sadegh Talezadehlari

Spin-polarized conducting edge currents counterpropagate in quantum spin Hall (QSH) insulators and are protected against disorder-driven localizations by the time-reversal symmetry. Using these spin-currents for device applications require materials having large band gap and fast switchable QSH states. By means of in-depth first-principles calculations, we d

David G. White

There have been a number of constructions of Lagrangian Floer homology invariants for $3$-manifolds defined in terms of symplectic character varieties arising from Heegaard splittings. With the aim of establishing an Atiyah-Floer counterpart of Kronheimer and Mrowka's singular instanton homology, we generalize one of these, due to H. Horton, to produce a Lag

Roland Memisevic

Gradient based learning using error back-propagation (``backprop'') is a well-known contributor to much of the recent progress in AI. A less obvious, but arguably equally important, ingredient is parameter sharing - most well-known in the context of convolutional networks. In this essay we relate parameter sharing (``weight sharing'') to analogy making and t

Lim C. Siang, Shams Elnawawi, Lee D. Rippon, Daniel L. O'Connor

A significant portion of the effort involved in advanced process control, process analytics, and machine learning involves acquiring and preparing data. Literature often emphasizes increasingly complex modelling techniques with incremental performance improvements. However, when industrial case studies are published they often lack important details on data

Steven Ceron, Kevin O'Keeffe, Kirstin Petersen

We study the emergent behaviors of a population of swarming coupled oscillators, dubbed 'swarmalators'. Previous work considered the simplest, idealized case: identical swarmalators with global coupling. Here we expand this work by adding more realistic features: local coupling, non-identical natural frequencies, and chirality. This more realistic model gene

Jake Song, Niels Holten-Andersen, Gareth H. McKinley

Viscoelastic stress relaxation is a basic characteristic of soft matter systems such as colloids, gels, and biological networks. Although the Maxwell model of linear viscoelasticity provides a classical description of stress relaxation, the Maxwell model is often not sufficient for capturing the complex relaxation dynamics of soft matter. In this Tutorial, w

Federico Cattorini, Giuseppe Gavazzi, Alessandro Boselli, Matteo Fossati

With the aim of providing the complete demography of galaxies in the local Universe, including their nuclear properties, we present SPRING, a complete census of local galaxies limited to the spring quarter of the Northern sky (10h< RA <16h; 0< Dec <65). The SPRING catalogue is a flux- and volume-limited sample (r < 17.7 mag, cz < 10000 km/s) of 30597 galaxie

Kirill Tchernyshyov, Jessica K. Werk, Matthew C. Wilde, J. Xavier Prochaska

This study addresses how the incidence rate of strong O VI absorbers in a galaxy's circumgalactic medium (CGM) depends on galaxy mass and, independently, on the amount of star formation in the galaxy. We use HST/COS absorption spectroscopy of quasars to measure O VI absorption within 400 projected kpc and 300 km s$^{-1}$ of 52 $M_{*}\sim 10^{10}$ $M_\odot$ g

Anarya Ray, Michael Camilo, Jolien Creighton, Shaon Ghosh

Bayesian hierarchical inference of phenomenological parameterized neutron star equations of state (EoS) from multiple gravitational wave observations of binary neutron star mergers is of fundamental importance in improving our understanding of neutron star structure, the general properties of matter at supra nuclear densities and the strong nuclear force. Ho

Drummond B. Fielding, Bart Ripperda, Alexander A. Philippov

The processes controlling the complex clump structure, phase distribution, and magnetic field geometry that develops across a broad range of scales in the turbulent interstellar medium remains unclear. Using unprecedentedly high resolution three-dimensional magnetohydrodynamic simulations of thermally unstable turbulent systems, we show that large current sh

O. Schib, C. Mordasini, R. Helled

Many protoplanetary discs are self-gravitating early in their lives. If they fragment under their own gravity, they form bound gaseous clumps which may evolve to become giant planets. Today, the fraction of discs that undergo fragmentation, and the frequency of conditions that may lead to giant planet formation via gravitational instability, is still unknown

A. Varghese, R. P. Ratnasingam, R. Vanon, P. V. F. Edelmann

Internal gravity waves (IGWs) can cause mixing in the radiative interiors of stars. We study this mixing by introducing tracer particles into two - dimensional (2D) hydrodynamic simulations. Following the work of Rogers & McElwaine (2017), arXiv:1709.04920, we extend our study to different masses (3 M$_{\odot}$, 7 M$_{\odot}$ and 20 M$_{\odot}$) and ages (ZA

Michele Redi, Andrea Tesi

We study the possibility that the axion Peccei-Quinn symmetry is spontaneously broken after the beginning of inflation. This scenario interpolates between pre-inflationary and post-inflationary axion cosmology with significant phenomenological differences from both. Since the axion is not present at the early stages of inflation large inflationary fluctuatio

Tiago Pimentel, Josef Valvoda, Niklas Stoehr, Ryan Cotterell

In this paper, we seek to measure how much information a component in a neural network could extract from the representations fed into it. Our work stands in contrast to prior probing work, most of which investigates how much information a model's representations contain. This shift in perspective leads us to propose a new principle for probing, the architec

Andrei Alexandru, Paulo Bedaque, Andrea Carosso, Hyunwoo Oh

Monte Carlo calculations of fermionic systems with continuous auxiliary fields frequently suffer from a diverging variance. If a system has the infinite variance problem, one cannot estimate observables reliably even with an infinite number of samples. In this paper, we explore a method to deal with this problem based on sampling according to the distributio

Oren Mangoubi, Nisheeth K. Vishnoi

Given a symmetric matrix $M$ and a vector $\lambda$, we present new bounds on the Frobenius-distance utility of the Gaussian mechanism for approximating $M$ by a matrix whose spectrum is $\lambda$, under $(\varepsilon,\delta)$-differential privacy. Our bounds depend on both $\lambda$ and the gaps in the eigenvalues of $M$, and hold whenever the top $k+1$ eig

Roland Bittleston

The question of whether the holomorphic collinear singularities of graviton amplitudes define a consistent chiral algebra has garnered much recent attention. We analyse a version of this question for infinitesimal perturbations around the self-dual sector of 4d Einstein gravity. The singularities of tree amplitudes in such perturbations do form a consistent

Sarah Allred, Guoli Ding, Bogdan Oporowski

In 1930, Ramsey proved that every infinite graph contains either an infinite clique or an infinite independent set as an induced subgraph. K\"{o}nig proved that every infinite graph contains either a ray or a vertex of infinite degree. In this paper, we establish the 2-connected analog of these results.

Laurent Freidel, Puttarak Jai-akson

The membrane paradigm displays underlying connections between a timelike stretched horizon and a null boundary (such as a black hole horizon) and bridges the gravitational dynamics of the horizon with fluid dynamics. In this work, we revisit the membrane viewpoint of a finite distance null boundary and present a unified geometrical treatment to the stretched

Joshua Forer, Viatcheslav Kokoouline, Thierry Stoecklin

The role of a large dipole moment in rotating neutral molecules interacting with low-energy electrons is studied using an accurate {\it ab initio} approach accounting for electronic and rotational degrees of freedom. It is found that theory can reproduce weakly-bound (dipole-bound) states observed in a recent photodetachment experiment with C$_3$N$^-$ [Phys.

Liyi Li, Mingwei Zhu, Rance Cleaveland, Alexander Nicolellis

Because of the probabilistic/nondeterministic behavior of quantum programs, it is highly advisable to verify them formally to ensure that they correctly implement their specifications. Formal verification, however, also traditionally requires significant effort. To address this challenge, we present Qafny, an automated proof system based on the program verif

Mateus P. Otto, Rafael Izbicki

Kernel methods provide a flexible and theoretically grounded approach to nonlinear and nonparametric learning. While memory and run-time requirements hinder their applicability to large datasets, many low-rank kernel approximations, such as random Fourier features, were recently developed to scale up such kernel methods. However, these scalable approaches ar

Chenyang Yang, Rachel Brower-Sinning, Grace A. Lewis, Christian Kästner

In spite of machine learning's rapid growth, its engineering support is scattered in many forms, and tends to favor certain engineering stages, stakeholders, and evaluation preferences. We envision a capability-based framework, which uses fine-grained specifications for ML model behaviors to unite existing efforts towards better ML engineering. We use concre

Rickie Xian, Dylan Jones

The influence of human activity own the earth's atmospheric composition has never been more pronounced. Anthropogenic pollution is in fact the largest effector of the observed evolving atmospheric composition (Wallace, 2006). PM2.5 is a class of particulate matter pollutants of notable interest due to their significant driving of chemical, atmospheric change

Yang Li, Xin Ma, Raj Sunderraman, Shihao Ji

Neuroimaging-based prediction methods for intelligence and cognitive abilities have seen a rapid development in literature. Among different neuroimaging modalities, prediction based on functional connectivity (FC) has shown great promise. Most literature has focused on prediction using static FC, but there are limited investigations on the merits of such ana

Yunqi Miao, Alexandros Lattas, Jiankang Deng, Jungong Han

Near infrared (NIR) to Visible (VIS) face matching is challenging due to the significant domain gaps as well as a lack of sufficient data for cross-modality model training. To overcome this problem, we propose a novel method for paired NIR-VIS facial image generation. Specifically, we reconstruct 3D face shape and reflectance from a large 2D facial dataset a

Daniel Lawson, Ahmed H. Qureshi

Learning long-horizon tasks such as navigation has presented difficult challenges for successfully applying reinforcement learning to robotics. From another perspective, under known environments, sampling-based planning can robustly find collision-free paths in environments without learning. In this work, we propose Control Transformer that models return-con

Francesco Armando Di Bello, Etienne Dreyer, Sanmay Ganguly, Eilam Gross

The simulation of particle physics data is a fundamental but computationally intensive ingredient for physics analysis at the Large Hadron Collider, where observational set-valued data is generated conditional on a set of incoming particles. To accelerate this task, we present a novel generative model based on a graph neural network and slot-attention compon

Ryusuke Jinno, Bibhushan Shakya, Jorinde van de Vis

First order phase transitions are well-motivated and extensively studied sources of gravitational waves (GWs) from the early Universe. The vacuum energy released during such transitions is assumed to be transferred primarily either to the expanding bubble walls, whose collisions source GWs, or to the surrounding plasma, producing sound waves and turbulence,

Gabriel Khan, Xuan Hien Nguyen

We consider the Laplace-Beltrami operator with Dirichlet boundary conditions on convex domains in a Riemannian manifold $(M^n,g)$, and prove that the product of the fundamental gap with the square of the diameter can be arbitrarily small whenever $M^n$ has even a single tangent plane of negative sectional curvature. In particular, the fundamental gap conject

Gabriel Khan, Xuan Hien Nguyen, Malik Tuerkoen, Guofang Wei

We study the log-concavity of the first Dirichlet eigenfunction of the Laplacian for convex domains. For positively curved surfaces satisfying a condition involving the curvature and its second derivatives, we show that the first eigenfunction is strongly log-concave. Previously, for general convex domains, the log-concavity of the first eigenfunctions were

Anjana Wijekoon, David Corsar, Nirmalie Wiratunga

This paper presented an XAI system specification and an interactive dialogue model to facilitate the creation of Explanation Experiences (EE). Such specifications combine the knowledge of XAI, domain and system experts of a use case to formalise target user groups and their explanation needs and to implement explanation strategies to address those needs. For

Chengcai Shen, Vanessa Polito, Katharine K. Reeves, Bin Chen

Magnetic reconnection is the key mechanism for energy release in solar eruptions, where the high-temperature emission is the primary diagnostic for investigating the plasma properties during the reconnection process. Non-thermal broadening of high-temperature lines has been observed in both the reconnection current sheet (CS) and flare loop-top regions by UV

Deep Gandhi, Jash Mehta, Nirali Parekh, Karan Waghela

The use of emojis affords a visual modality to, often private, textual communication. The task of predicting emojis however provides a challenge for machine learning as emoji use tends to cluster into the frequently used and the rarely used emojis. Much of the machine learning research on emoji use has focused on high resource languages and has conceptualise

Ahmad Bin Rabiah, Qi Guo

Conventional image signal processing (ISP) frameworks are designed to reconstruct an RGB image from a single raw measurement. As multi-camera systems become increasingly popular these days, it is worth exploring improvements in ISP frameworks by incorporating raw measurements from multiple cameras. This manuscript is an intermediate progress report of a new

Kilean Hwang, Tomofumi Maruta, Alexander Plastun, Kei Fukushima

Bayesian optimization~(BO) is often used for accelerator tuning due to its high sample efficiency. However, the computational scalability of training over large data-set can be problematic and the adoption of historical data in a computationally efficient way is not trivial. Here, we exploit a neural network model trained over historical data as a prior mean

Domingo García-Senz, Robert Wissing, Rubén M. Cabezón, Eda Vurgun

Many astrophysical and terrestrial scenarios involving magnetic fields can be approached in axial geometry. Although the smoothed particle hydrodynamics (SPH) technique has been successfully extended to magneto-hydrodynamics (MHD), a well-verified, axisymmetric MHD scheme based on such technique does not exist yet. In this work we fill that gap in the scient

C. Porowski, M. Bzowski, M. Tokumaru

The solar wind (SW) is a supersonic outflow of plasma from the solar corona, with the latitudinal speed and density profiles varying with the solar activity. The SW protons charge exchange with the inflowing interstellar neutral atoms and create energetic neutral atoms (ENAs), which bring information on the physical state of the plasma within the boundary re

Reza Yeganegi, Saman Haratizadeh

Session-Based Recommenders (SBRs) aim to predict users' next preferences regard to their previous interactions in sessions while there is no historical information about them. Modern SBRs utilize deep neural networks to map users' current interest(s) during an ongoing session to a latent space so that their next preference can be predicted. Although state-of

J. Bayron Orjuela-Quintana, Savvas Nesseris, Wilmar Cardona

The linear matter power spectrum $P(k,z)$ connects theory with large scale structure observations in cosmology. Its scale dependence is entirely encoded in the matter transfer function $T(k)$, which can be computed numerically by Boltzmann solvers, and can also be computed semi-analytically by using fitting functions such as the well-known Bardeen-Bond-Kaise

José M. Espinar, Harold Rosenberg

In this paper, we study complete minimal hypersurfaces in Riemannian $n-$manifolds $\mathcal{M}^n$ for dimensions $4 \leq n \leq 7$, and we obtain some results in the spirit of known work for $n=3$. Key contributions include extending the work of Anderson and Rodr\'{i}guez to higher dimensions. Specifically, we show that in four-dimensional manifolds with no

Benjamin Jarman, Yotam Yaniv, Deanna Needell

Recovering a signal $x^\ast \in \mathbb{R}^n$ from a sequence of linear measurements is an important problem in areas such as computerized tomography and compressed sensing. In this work, we consider an online setting in which measurements are sampled one-by-one from some source distribution. We propose solving this problem with a variant of the Kaczmarz met

Mark Wyse, Daniel Petrisko, Farzam Gilani, Yuan-Mao Chueh

This paper presents BP-BedRock, the open-source cache coherence protocol and system implemented within the BlackParrot 64-bit RISC-V multicore processor. BP-BedRock implements the BedRock directory-based MOESIF cache coherence protocol and includes two different open-source coherence protocol engines, one FSM-based and the other microcode programmable. Both

Jacqueline E. Rudolph, Yongqi Zhong, Priya Duggal, Shruti H. Mehta

Medical and population health science researchers frequently make ambiguous statements about whether they believe their study sample or results are "representative" of some (implicit or explicit) target population. Here, we provide a comprehensive definition of representativeness, with the goal of capturing the different ways in which a study can be represen

Omprakash Atale

In order theory, partially ordered sets are only equipped with one relation which decides the entire structure/Hasse diagram of the set. In this paper, we have presented how partially ordered sets can be studied under simultaneous partially ordered relations which we have called binary posets. The paper is motivated by the problem of operating a set simultan

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós

The problem of learning threshold functions is a fundamental one in machine learning. Classical learning theory implies sample complexity of $O(\xi^{-1} \log(1/\beta))$ (for generalization error $\xi$ with confidence $1-\beta$). The private version of the problem, however, is more challenging and in particular, the sample complexity must depend on the size $

I. S. W. B. Prasetya, Fernando Pastor Ricós, Fitsum Kifetew, Davide Prandi

Computer games are very challenging to handle for traditional automated testing algorithms. In this paper we will look at intelligent agents as a solution. Agents are suitable for testing games, since they are reactive and able to reason about their environment to decide the action they want to take. This paper presents the experience of using an agent-based

Md Vasimuddin, Ramanarayan Mohanty, Sanchit Misra, Sasikanth Avancha

Training Graph Neural Networks, on graphs containing billions of vertices and edges, at scale using minibatch sampling poses a key challenge: strong-scaling graphs and training examples results in lower compute and higher communication volume and potential performance loss. DistGNN-MB employs a novel Historical Embedding Cache combined with compute-communica

Pierpaola Santarsiero

We present an algorithm aimed to recognize if a given tensor is a non-identifiable rank-3 tensor.

Hunter M. Campbell, Lukas R. Stone, Nathan A. Kaib

Within the dynamically cold low inclination portion of the Classical Kuiper Belt, there exists a population of weakly bound binary systems with a number of unusual properties; most notable of which is their extremely wide orbital separations; beyond 7% of their Hill radii. The stability and evolution of these Ultra-Wide Trans-Neptunian Binaries (TNBs) have,

Matthew J. Reagor, Thomas C. Bohdanowicz, David Rodriguez Perez, Eyob A. Sete

Error correcting codes use multi-qubit measurements to realize fault-tolerant quantum logic steps. In fact, the resources needed to scale-up fault-tolerant quantum computing hardware are largely set by this task. Tailoring next-generation processors for joint measurements, therefore, could result in improvements to speed, accuracy, or cost -- accelerating th

Francesco Di Clemente, Alessandro Drago, Giuseppe Pagliara

The analysis of the central compact object within the supernova remnant HESS J1731-347 suggests that it has a small radius and, even more interestingly, a mass of the order or smaller than one solar mass. This raises the question of which astrophysical process could lead to such a small mass, since the analysis of various types of SN explosions indicate that

Alessandro Greco, Nicola Bartolo, Alessandro Gruppuso

Cosmic birefringence is the in-vacuo rotation of the linear polarization plane experienced by photons of the Cosmic Microwave Background (CMB) radiation when theoretically well-motivated parity-violating extensions of Maxwell electromagnetism are considered. If the angle, parametrizing such a rotation is dependent on the photon's direction, then this phenome

Rian Dolphin, Barry Smyth, Ruihai Dong

Industry classification schemes provide a taxonomy for segmenting companies based on their business activities. They are relied upon in industry and academia as an integral component of many types of financial and economic analysis. However, even modern classification schemes have failed to embrace the era of big data and remain a largely subjective undertak

Martin Zimmermann, Minh Nhat Vu, Florian Beck, Anh Nguyen

This paper presents a two-step algorithm for online trajectory planning in indoor environments with unknown obstacles. In the first step, sampling-based path planning techniques such as the optimal Rapidly exploring Random Tree (RRT*) algorithm and the Line-of-Sight (LOS) algorithm are employed to generate a collision-free path consisting of multiple waypoin

Pedro Sequeira, Jesse Hostetler, Melinda Gervasio

In recent years, advances in deep learning have resulted in a plethora of successes in the use of reinforcement learning (RL) to solve complex sequential decision tasks with high-dimensional inputs. However, existing systems lack the necessary mechanisms to provide humans with a holistic view of their competence, presenting an impediment to their adoption, p

Jerry Luo, Cosmin Paduraru, Octavian Voicu, Yuri Chervonyi

This paper is a technical overview of DeepMind and Google's recent work on reinforcement learning for controlling commercial cooling systems. Building on expertise that began with cooling Google's data centers more efficiently, we recently conducted live experiments on two real-world facilities in partnership with Trane Technologies, a building management sy

Christopher J. McDevitt, Eric Fowler, Subrata Roy

High resolution simulations of incompressible flows have become routine across a range of engineering applications. Despite their routine use, due to the high dimensional parameter space present for most practical applications, a comprehensive exploration of the available parameter space is often impractical. In this work, we demonstrate the ability of physi

Gustavo Garrigos

This survey is a slightly extended version of the lecture given by the author at the \emph{VI International Course of Mathematical Analysis in Andaluc\'\i a} (CIDAMA), in September 2014. Most results are contained (in a slightly less general setting) in the earlier paper [3] (Garrig\'os, Hartzstein, Signes, Torrea and Viviani, Pointwise convergence to initia

Kilian D. Stenning, Jack C. Gartside, Luca Manneschi, Christopher T. S. Cheung

Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narro

Yuto Horikawa, Ryuichi Tarumi

This study proposes 'amigami' as a new method of creating a general curved surface. It conducts the shape optimization of weaving paper strips based on the theory of nonlinear elasticity on Riemannian manifolds. The target surface is split into small curved strips by cutting the medium along with its coordinates, and each strip is embedded into a flat paper

Mohammad Shaique Solanki, Ashutosh M Bharadwaj, Jeevan K, Prasanta Kumar Ghosh

Voiced speech signals such as continuous speech are known to have acoustic features such as pitch(F0), and formant frequencies(F1, F2, F3) which can be used for gender classification. However, gender classification studies using non-speech signals such as vocal breath sounds have not been explored as they lack typical gender-specific acoustic features. In th

Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo

To offer accurate and diverse recommendation services, recent methods use auxiliary information to foster the learning process of user and item representations. Many SOTA methods fuse different sources of information (user, item, knowledge graph, tags, etc.) into a graph and use Graph Neural Networks to introduce the auxiliary information through the message