August 2022 arXiv papers — page 108

Melody G Whitehead, Andrew Curtis

Expert knowledge is required to interpret data across a range of fields. Experts bridge gaps that often exists in our knowledge about relationships between data and the parameters of interest. This is especially true in geoscientific applications, where knowledge of the Earth is derived from interpretations of observable features and relies on predominantly

Babak Hemmatian, Lav R. Varshney

Recent work demonstrates a bias in the GPT-3 model towards generating violent text completions when prompted about Muslims, compared with Christians and Hindus. Two pre-registered replication attempts, one exact and one approximate, found only the weakest bias in the more recent Instruct Series version of GPT-3, fine-tuned to eliminate biased and toxic outpu

Kaier Liang, Cristian-Ioan Vasile

Mobility-on-demand systems are transforming the way we think about the transportation of people and goods. Most research effort has been placed on scalability issues for systems with a large number of agents and simple pick-up/drop-off demands. In this paper, we consider fair multi-vehicle route planning with streams of complex, temporal logic transportation

Ayush Kumar, Parth Nagarkar, Prabhav Nalhe, Sanjeev Vijayakumar

With the future striving toward data-centric decision-making, seamless access to databases is of utmost importance. There is extensive research on creating an efficient text-to-sql (TEXT2SQL) model to access data from the database. Using a Natural language is one of the best interfaces that can bridge the gap between the data and results by accessing the dat

Montserrat Teixidor i Bigas

We generalize to vector bundles the techniques introduced for line bundles in prior work of the author with Liu, Osserman and Zhang. We then use this method to prove the injectivity of the Petri map for vector bundles and the surjectivity of a map related to deformation theory of Poincar\'e sheaves.

Germana Landi, Giovanni V. Spinelli, Fabiana Zama, Delia Chillura Martino

Fast Field-Cycling Nuclear Magnetic Resonance relaxometry is a non-destructive technique to investigate molecular dynamics and structure of systems having a wide range of applications such as environment, biology, and food. Besides a considerable amount of literature about modeling and application of such technique in specific areas, an algorithmic approach

N. E. Martínez-Pérez, C. Ramírez, V. M. Vázquez Báez

We consider the effective evolution of a phenomenological model from FLRW supersymmetric quantum cosmology with a scalar field. The scalar field acts as a clock and inflaton. We examine a family of simple superpotentials that produce an inflation whose virtual effect on inhomogeneous fluctuations shows very good agreement with PLANCK observational evidence f

Guillermo Angeris

In this note we show how to construct a number of nonconvex quadratic inequalities for a variety of physics equations appearing in physical design problems. These nonconvex quadratic inequalities can then be used to construct bounds on physical design problems where the objective is a quadratic or a ratio of quadratics. We show that the quadratic inequalitie

Majid Farhadi, Jai Moondra, Prasad Tetali, Alejandro Toriello

The cost due to delay in services may be intrinsically different for various applications of vehicle routing such as medical emergencies, logistical operations, and ride-sharing. We study a fundamental generalization of the Traveling Salesman Problem, namely $L_p$ TSP, where the objective is to minimize an aggregated measure of the delay in services, quantif

I. L. Buchbinder, V. A. Krykhtin, T. V. Snegirev

We develop an approach to constructing the manifestly Lorentz covariant cubic interaction vertices for the four-dimensional massless higher spin bosonic fields with two-component dotted and undotted spinor indices. Such fields automatically satisfy the traceless conditions what simplify form of the equations determining the irreducible massless representatio

Uéverton S. Souza

Sparse-dense partitions was introduced by Feder, Hell, Klein, and Motwani [STOC 1999, SIDMA 2003] as a tool to solve partitioning problems. In this paper, the following result concerning independent sets in graphs having sparse-dense partitions is presented: if a $n$-vertex graph $G$ admits a sparse-dense partition concerning classes $\mathcal S$ and $\mathc

Deepthi Gorthi

In the past two decades, a rebirth of interest in low-frequency radio astronomy for 21 cm tomography of the Epoch of Reionization, has given rise to a new class of radio interferometers with $N \gg 100$ antennas. The availability of low-noise receivers that do not require cryogenic cooling has driven down the cost of antennas, making it affordable to build s

V. R. Shaginyan, A. Z. Msezane, G. S. Japaridze, M. V. Zverev

P. W. Phillips, N. E. Hussey, P. Abbamonte (Review Article, 8 July 2022, eabh4273) consider heavy fermion (HF) metals and high-$T_c$ superconductors naming them strange metals. They analyze such features of strange metals as quantum criticality, Planckian dissipation and recently observed fundamental link between the high-$T_c$ superconductivity and strange

Ruby Byrne

One of the principal challenges of 21 cm cosmology experiments is overcoming calibration error. Established calibration approaches in the field require an exquisitely accurate sky model, and low-level sky model errors introduce calibration errors that corrupt the cosmological signal. We present a novel calibration approach called Delay-Weighted Calibration,

Sérgio Machado, Anirudh Sridhar, Paulo Gil, Jorge Henriques

We study the problem of graph structure identification, i.e., of recovering the graph of dependencies among time series. We model these time series data as components of the state of linear stochastic networked dynamical systems. We assume partial observability, where the state evolution of only a subset of nodes comprising the network is observed. We devise

Maegan Tucker, Kejun Li, Yisong Yue, Aaron D. Ames

Parameter tuning for robotic systems is a time-consuming and challenging task that often relies on domain expertise of the human operator. Moreover, existing learning methods are not well suited for parameter tuning for many reasons including: the absence of a clear numerical metric for `good robotic behavior'; limited data due to the reliance on real-world

Eytan Adar, Elsie Lee-Robbins

Due to their pedagogical advantages, large final projects in information visualization courses have become standard practice. Students take on a client--real or simulated--a dataset, and a vague set of goals to create a complete visualization or visual analytics product. Unfortunately, many projects suffer from ambiguous goals, over or under-constrained clie

Diyi Cheng, Thomas Wynn, Bingyu Lu, Maxwell Marple

Lithium phosphorus oxynitride (LiPON) is a well-known amorphous thin film solid electrolyte that has been extensively studied in the last three decades. Despite the promises to pair with Li metal anode and various cathode materials, the presence of rigid substrate and LiPONs unique amorphous, air-sensitive nature set limitations to comprehensively understand

S. A. K. Wijethunga, J. Eldred, C. Y. Tan, E. Pozdeyev

Fermilab Booster synchrotron requires an intensity upgrade from 4.5x1012 to 6.5x1012 protons per pulse as a part of Fermilabs Proton Improvement Plan-II (PIP-II). One of the factors which may limit the high-intensity performance is the fast transverse instabilities caused by electron cloud effects. According to the experience in the Recycler, the electron cl

Hosein Zarini, Narges Gholipoor, Mohamad Robat Mili, Mehdi Rasti

Passive beamforming in reconfigurable intelligent surfaces (RISs) enables a feasible and efficient way of communication when the RIS reflection coefficients are precisely adjusted. In this paper, we present a framework to track the RIS reflection coefficients with the aid of deep learning from a time-series prediction perspective in a terahertz (THz) communi

Thang Pham, Steven Senger, Michael Tait, Vu Thi Huong Thu

In this paper, we provide a general framework for counting geometric structures in pseudo-random graphs. As applications, our theorems recover and improve several results on the finite field analog of questions originally raised in the continuous setting. The results present interactions between discrete geometry, geometric measure theory, and graph theory.

Arindam Bose, Bo Tang, Wenjie Huang, Mojtaba Soltanalian

The mutual interference between similar radar systems can result in reduced radar sensitivity and increased false alarm rates. To address the synchronous and asynchronous interference mitigation problems in similar radar systems, we first propose herein two slow-time coding schemes to modulate the pulses within a coherent processing interval (CPI) for a sing

Lucas R. Rodrigues, J. F. Stilck, W. G. Dantas

Using the transfer matrix technique, we estimate the entropy for a gas of rods of sizes equal to k (named k-mers), which cover completely a square lattice. Our calculations were made considering three different constructions, using periodical and helical boundary conditions. One of those constructions, which we call Profile Method, was based on the calculati

So-Hsiang Chou, Champike Attanayake

We introduce an enriched unfitted finite element method to solve 1D elliptic interface problems with discontinuous solutions, including those having implicit or Robin-type interface jump conditions. We present a novel approach to construct a one-parameter family of discontinuous enrichment functions by finding an optimal order interpolating function to the d

Henry Robert Thackeray

For positive integers $n$ and $k$ such that $k$ is at most $n$, we find an explicit one-to-one correspondence between the following two sets: the set of words consisting of $k$ $R$s, $k$ $U$s, and $n - k$ $D$s, where the first letter of the word is not $D$; and the set of subgraphs $H$ of a cycle of length $2n$ (where that cycle has differently labelled vert

Saipraneeth Devunuri, Shirin Qiam, Lewis Lehe, Ayush Pandey

Transit agencies have been removing a large number of bus stops, but discussions around the bus stop spacings exhibit a lack of clarity and data for comparison. This paper proposes new terminology and concepts for statistical consideration of stop spacings, and introduces a python package and open-source database which uses General Transit Feed Specification

Anand Patel, Eric Riedl, Geoffrey Smith, Dennis Tseng

We study spaces of lines that meet a smooth hypersurface X in P^n to high order. As an application, we give a polynomial upper bound on the number of planes contained in a smooth degree d hypersurface in P^5 and provide a proof of a result of Landsberg without using moving frames.

V. Chouhan, F. Furuta, M. Martinello, T. Ring

Cold electropolishing (EP) of a nitrogen-doped (N-doped) niobium (Nb) superconducting RF (SRF) cavity was found to improve its quality factor. In order to understand the effect of EP temperature on N-doped and undoped surfaces, a systematic EP study was conducted with 2/0 N-doped and heat-treated Nb samples in a beaker. The Nb samples were electropolished at

Emmanuel Senft, Michael Hagenow, Pragathi Praveena, Robert Radwin

Drones can provide a minimally-constrained adapting camera view to support robot telemanipulation. Furthermore, the drone view can be automated to reduce the burden on the operator during teleoperation. However, existing approaches do not focus on two important aspects of using a drone as an automated view provider. The first is how the drone should select f

Ming Fan, Dan Lu, Deeksha Rastogi, Eric M. Pierce

Multimodel ensembling has been widely used to improve climate model predictions, and the improvement strongly depends on the ensembling scheme. In this work, we propose a Bayesian neural network (BNN) ensembling method, which combines climate models within a Bayesian model averaging framework, to improve the predictive capability of model ensembles. Our prop

Raida Karim, Edgar Lopez, Katelynn Oleson, Tony Li

Social robots have been used to assist with mental well-being in various ways such as to help children with autism improve on their social skills and executive functioning such as joint attention and bodily awareness. They are also used to help older adults by reducing feelings of isolation and loneliness, as well as supporting mental well-being of teens and

G. Bevilacqua, M. V. Garzelli, A. Kardos, L. Toth

Data on $W + D$-meson and $W + c$-jet hadroproduction have recently started to be included in at least some of the parton distribution function fits, mainly because of their potential to constrain the strange quark content of the proton. In this contribution we present predictions for $W + D$-meson and $W + c$-jet production with NLO QCD accuracy matched to

Fabio Berra, Gladis Pradolini, Pablo Quijano

We obtain weighted mixed inequalities for operators associated to a critical radius function. We consider Schr\"odinger Calder\'on-Zygmund operators of $(s,\delta)$ type, for $1<s\leq \infty$ and $0<\delta \leq 1$. We also give estimates of the same type for the associated maximal operators. As an application, we obtain a wide variety of mixed inequalities f

A. Shemyakin

The PIP2IT accelerator was assembled in multiple stages in 2014 - 2021 to test concepts and components of the future PIP-II linac that is being constructed at Fermilab. In its final configuration, PIP2IT accelerated a 0.55 ms x 20 Hz x 2 mA H- beam to 16 MeV. To determine location of the beam loss in the accelerators low-energy part, where radiation monitors

Alberto Rodriguez Cuevas, Hani J. Kbashi, Dmitrii Stoliarov, Sergey Sergeyev

In this paper, we demonstrate the polarization-multiplexed system capable of generating two stable optical frequency combs with tunable frequency differences and a large extinction ratio. Also, the polarization dynamics of a dual-frequency comb generated from a single mode-locked Er-doped fiber laser are experimentally studied. The obtained results will exte

Léo Berges, Eloi Haltz, Sujit Panigrahy, Sougata Mallick

Magnetic skyrmions are swirling magnetic textures that can be efficiently driven with spin-orbit torques with a deflected trajectory. However, pinning slows skyrmions down and alters their trajectory, which prevents a quantitative comparison to analytical models. Here, we study skyrmions driven by spin-orbit torques at room temperature in ferrimagnetic GdCo

Branislav Cvetković, Danilo Rakonjac

We analyze the near horizon symmetry of the extremal Kerr black hole within the framework of Poincar\'e gauge theory (PG) for two important limiting cases: Riemannian and teleparallel solution. We show that the algebra of canonical generators is realized by Virasoro algebra, with central charge which depends on the black hole horizon radius . The conformal e

Askery Canabarro, Taysa M. Mendonça, Ranieri Nery, George Moreno

Previously only considered a frontier area of Physics, nowadays quantum computing is one of the fastest growing research field, precisely because of its technological applications in optimization problems, machine learning, information security and simulations. The goal of this article is to introduce the fundamentals of quantum computing, focusing on a prom

Edwin Vargas, Kumar Vijay Mishra, Roman Jacome, Brian M. Sadler

The increasingly crowded spectrum has spurred the design of joint radar-communications systems that share hardware resources and efficiently use the radio frequency spectrum. We study a general spectral coexistence scenario, wherein the channels and transmit signals of both radar and communications systems are unknown at the receiver. In this dual-blind deco

Roman Kolpakov

For $0<\delta <1$ a $\delta$-subrepetition in a word is a factor which exponent is less than~2 but is not less than $1+\delta$ (the exponent of the factor is the ratio of the factor length to its minimal period). The $\delta$-subrepetition is maximal if it cannot be extended to the left or to the right by at least one letter with preserving its minimal perio

Behnam Hedayatnia, Di Jin, Yang Liu, Dilek Hakkani-Tur

Recent progress on neural approaches for language processing has triggered a resurgence of interest on building intelligent open-domain chatbots. However, even the state-of-the-art neural chatbots cannot produce satisfying responses for every turn in a dialog. A practical solution is to generate multiple response candidates for the same context, and then per

Zhaodong Sun, Xiaobai Li

Video-based remote physiological measurement utilizes face videos to measure the blood volume change signal, which is also called remote photoplethysmography (rPPG). Supervised methods for rPPG measurements achieve state-of-the-art performance. However, supervised rPPG methods require face videos and ground truth physiological signals for model training. In

R. Grossi, Lucas L. Brugger, B. F. Rizzuti, C. Duarte

Inspired by the one-hundredth anniversary of the seminal works of Stern and Gerlach, our contribution is a proposal of how to use their famous experiment in a more contemporary perspective. Our main idea is to re-cast the experiment in the modern language of prepare-and-measure scenarios. By doing so, it is possible to connect geometric and algebraic aspects

David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys

The automated machine learning (AutoML) process can require searching through complex configuration spaces of not only machine learning (ML) components and their hyperparameters but also ways of composing them together, i.e. forming ML pipelines. Optimisation efficiency and the model accuracy attainable for a fixed time budget suffer if this pipeline configu

Nirmali Roy, Anuradha Jha

A two-parameter singularly perturbed problem with discontinuous source and convection coefficient is considered in one dimension. Both convection coefficient and source term are discontinuous at a point in the domain. The presence of perturbation parameters results in boundary layers at the boundaries. Also, an interior layer occurs due to the discontinuity

Emory Taylor

In a paper by Alberto Caballero, a methodology is stated for estimating the probability of an exoplanet alien civilization having malicious intentions toward the human civilization after being messaged by it and estimating the number of malicious exoplanet civilizations in the Milky Way. Caballero states his paper attempts to provide these estimates. Caballe

Goutham Rajendran

We study the Sum of Squares (SoS) Hierarchy with a view towards combinatorial optimization. We survey the use of the SoS hierarchy to obtain approximation algorithms on graphs using their spectral properties. We present a simplified proof of the result of Feige and Krauthgamer on the performance of the hierarchy for the Maximum Clique problem on random graph

Dhiman Ray, Narjes Ansari, Valerio Rizzi, Michele Invernizzi

We introduce a novel enhanced sampling approach named OPES flooding for calculating the kinetics of rare events from atomistic molecular dynamics simulation. This method is derived from the On-the-fly-Probability-Enhanced-Sampling (OPES) approach [Invernizzi and Parrinello, JPC Lett. 2020], which has been recently developed for calculating converged free ene

Shumpei Kubosawa, Takashi Onishi, Yoshimasa Tsuruoka

During the operation of a chemical plant, product quality must be consistently maintained, and the production of off-specification products should be minimized. Accordingly, process variables related to the product quality, such as the temperature and composition of materials at various parts of the plant must be measured, and appropriate operations (that is

Artem Strashko, E. Miles Stoudenmire

While overfitting and, more generally, double descent are ubiquitous in machine learning, increasing the number of parameters of the most widely used tensor network, the matrix product state (MPS), has generally lead to monotonic improvement of test performance in previous studies. To better understand the generalization properties of architectures parameter

Saurabh S. Sawant, Zhi Yao, Revathi Jambunathan, Andy Nonaka

Modeling and characterization of electromagnetic wave interactions with microelectronic devices to derive network parameters has been a widely used practice in the electronic industry. However, as these devices become increasingly miniaturized with finer-scale geometric features, computational tools must make use of manycore/GPU architectures to efficiently

Shailesh Mishra, Jonathan Granskog

We present a method for transferring the style from a set of images to a 3D object. The texture appearance of an asset is optimized with a differentiable renderer in a pipeline based on losses using pretrained deep neural networks. More specifically, we utilize a nearest-neighbor feature matching loss with CLIP-ResNet50 to extract the style from images. We s

Guangcong Wang, Guangrun Wang, Wenqi Liang, Jianhuang Lai

We present a weight similarity measure method that can quantify the weight similarity of non-convex neural networks. To understand the weight similarity of different trained models, we propose to extract the feature representation from the weights of neural networks. We first normalize the weights of neural networks by introducing a chain normalization rule,

Haleh Akrami, Wenhui Cui, Anand A Joshi, Richard M. Leahy

Segmentation is one of the most important tasks in MRI medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, head segmentation is commonly used for measuring and visualizing the brain's anatomical structures and is also a necessary step for other applications such as current-source reco

Joseph Dominicus Lap, Berndt Müller

We make use of published yields for $D$-mesons and $J/\psi$ in Pb+Pb collisions at ALICE and a schematic description of the expansion of the hadron gas to study $D$-meson collisions during the hadronic break-up phase as a production mechanism for charmonium in relativistic heavy ion collisions at the Large Hadron Collider. Our calculation is based on chemica

Tristan Zaborniak, Juan Giraldo, Hausi Müller, Hosna Jabbari

RNAs self-interact through hydrogen-bond base-pairing between nucleotides and fold into specific, stable structures that substantially govern their biochemical behaviour. Experimental characterization of these structures remains difficult, hence the desire to predict them computationally from sequence information. However, correctly predicting even the base

B. L. S. Prakasa Rao

We investigate the asymptotic properties of the minimum $L_1$-norm estimator of the drift parameter for fractional Ornstein-Uhlenbeck type process driven by a general Gaussian process.

Christian Bauckhage, Helen Schneider, Benjamin Wulff, Rafet Sifa

We explore the merits of training of support vector machines for binary classification by means of solving systems of ordinary differential equations. We thus assume a continuous time perspective on a machine learning problem which may be of interest for implementations on (re)emerging hardware platforms such as analog- or quantum computers.

Jiahao Wen, Bohan Wang, Jernej Barbič

Modeling arbitrarily large deformations of surfaces smoothly embedded in three-dimensional space is challenging. The difficulties come from two aspects: the existing geometry processing or forward simulation methods penalize the difference between the current status and the rest configuration to maintain the initial shape, which will lead to sharp spikes or

Andrea Panizza, Szymon Tomasz Stefanek, Stefano Melacci, Giacomo Veneri

Nondestructive testing (NDT) is widely applied to defect identification of turbine components during manufacturing and operation. Operational efficiency is key for gas turbine OEM (Original Equipment Manufacturers). Automating the inspection process as much as possible, while minimizing the uncertainties involved, is thus crucial. We propose a model based on

Sofia Sevitz, Nicolás Mirkin, Diego A. Wisniacki

Quantum control relies on the driving of quantum states without the loss of coherence, thus the leakage of quantum properties onto the environment over time is a fundamental challenge. One work-around is to implement fast protocols, hence the Minimal Control Time (MCT) is of upmost importance. Here, we employ a machine learning network in order to estimate t

Yunqing Bao, Hang Dai, Abdulmotaleb Elsaddik

Salient Object Detection (SOD) is a popular and important topic aimed at precise detection and segmentation of the interesting regions in the images. We integrate the linguistic information into the vision-based U-Structure networks designed for salient object detection tasks. The experiments are based on the newly created DUTS Cross Modal (DUTS-CM) dataset,

Jingbo Zhou, Xinjiang Lu, Yixiong Xiao, Jiantao Su

The variability of wind power supply can present substantial challenges to incorporating wind power into a grid system. Thus, Wind Power Forecasting (WPF) has been widely recognized as one of the most critical issues in wind power integration and operation. There has been an explosion of studies on wind power forecasting problems in the past decades. Neverth

Nemanja Rakić

Here we investigate the kinematics of the part of the broad line region (BLR) in active galactic nuclei (AGNs) emitting H$\beta$ and H$\alpha$ emission lines. We explore the widths and asymmetries of the broad H$\beta$ and H$\alpha$ emission lines in a sample of high quality (i.e. high signal to noise ratio) spectra of type 1 AGN taken from the Data Release

Claudio D. G. Linhares, Jean R. Ponciano, Diogenes S. Pedro, Luis E. C. Rocha

Temporal (or time-evolving) networks are commonly used to model complex systems and the evolution of their components throughout time. Although these networks can be analyzed by different means, visual analytics stands out as an effective way for a pre-analysis before doing quantitative/statistical analyses to identify patterns, anomalies, and other behavior

Maximilian Kolter, Sandra D. Eksioglu, Sarah Nurre Pinkley, Ruben A. Proano

The focus of this research is to evaluate the use of drones for the delivery of pediatric vaccines in remote areas of low income and low and middle income countries. Delivering vaccines in these regions is challenging because of the inadequate road networks, and long transportation distances that make it difficult to maintain the cold chain integrity during

Keefe Mitman, Leo C. Stein, Michael Boyle, Nils Deppe

The Bondi-van der Burg-Metzner-Sachs (BMS) group, which uniquely describes the symmetries of asymptotic infinity and therefore of the gravitational waves that propagate there, has become increasingly important for accurate modeling of waveforms. In particular, waveform models, such as post-Newtonian (PN) expressions, numerical relativity (NR), and black hole

Samrat Sen, Rony Keppens

In flare-relevant current sheets, tearing instability may trigger explosive reconnection and plasmoid formation. We explore how the thermal and tearing modes reinforce each other in the fragmentation of a current sheet in the solar corona through an explosive reconnection process, characterized by the formation of plasmoids which interact and trap condensing

Sanjay Amrutiya, Ayush Jaiswal

We develop the theory of d-holomorphic connections on d-holomorphic vector bundles over a Klein surface by constructing the analogous Atiyah exact sequence for d-holomorphic bundles. We also give a criterion for the existence of d-holomorphic connection in d-holomorphic bundle over a Klein surface in the spirit of the Atiyah-Weil criterion for holomorphic co

Francesco Ciccarello

Most literature on quantum collision models (CMs) usually considers periodic weak collisions featuring a fixed waiting time between two next collisions. Some works have yet addressed CMs with random waiting time and strong collisions (stochastic CMs). This short paper discusses how the open dynamics arising from these two types of models can be formally mapp

Bingqi Ma, Guanglu Song, Boxiao Liu, Yu Liu

Learning robust feature representation from large-scale noisy faces stands out as one of the key challenges in high-performance face recognition. Recent attempts have been made to cope with this challenge by alleviating the intra-class conflict and inter-class conflict. However, the unconstrained noise type in each conflict still makes it difficult for these

Moritz Beller, Hongyu Li, Vivek Nair, Vijayaraghavan Murali

Catching and attributing code change-induced performance regressions in production is hard; predicting them beforehand, even harder. A primer on automatically learning to predict performance regressions in software, this article gives an account of the experiences we gained when researching and deploying an ML-based regression prediction pipeline at Meta. In

Seungmin Jin, Hyunwook Lee, Cheonbok Park, Hyeshin Chu

With deep learning (DL) outperforming conventional methods for different tasks, much effort has been devoted to utilizing DL in various domains. Researchers and developers in the traffic domain have also designed and improved DL models for forecasting tasks such as estimation of traffic speed and time of arrival. However, there exist many challenges in analy

Yunseong Cho, Jinseok Choi, Brian L. Evans

A multicell-coordinated beamforming solution for massive multiple-input multiple-output orthogonal frequency-division multiplexing (OFDM) systems is presented when employing low-resolution data converters and per-antenna level constraints. For a more realistic deployment, we aim to find the downlink (DL) beamformer that minimizes the maximum power on transmi

Sean A. Hartnoll

We solve the Wheeler-DeWitt equation for the planar AdS-Schwarzschild interior in a minisuperspace approximation involving the volume and spatial anisotropy of the interior. A Gaussian wavepacket is constructed that is peaked on the classical interior solution. Simple observables are computed using this wavepacket, demonstrating the freedom to a choose a rel

Jason Phang, Yao Zhao, Peter J. Liu

While large pretrained Transformer models have proven highly capable at tackling natural language tasks, handling long sequence inputs continues to be a significant challenge. One such task is long input summarization, where inputs are longer than the maximum input context of most pretrained models. Through an extensive set of experiments, we investigate wha

Vladimir Frants, Sos Agaian, Karen Panetta

Images captured in real-world applications in remote sensing, image or video retrieval, and outdoor surveillance suffer degraded quality introduced by poor weather conditions. Conditions such as rain and mist, introduce artifacts that make visual analysis challenging and limit the performance of high-level computer vision methods. For time-critical applicati

Mi Lei, Rikuto Fukumori, Jake Rochman, Bihui Zhu

Quantum emitters coupled to optical resonators are quintessential systems for exploring fundamental phenomena in cavity quantum electrodynamics (cQED) and are commonly used in quantum devices acting as qubits, memories and transducers. Many previous experimental cQED studies have focused on regimes in which a small number of identical emitters interact with

Marco Benini, Victor Carmona, Alexander Schenkel

It is proven that the homotopy time-slice axiom for many types of algebraic quantum field theories (AQFTs) taking values in chain complexes can be strictified. This includes the cases of Haag-Kastler-type AQFTs on a fixed globally hyperbolic Lorentzian manifold (with or without time-like boundary), locally covariant conformal AQFTs in two spacetime dimension

Aayush Kumar, Jimiama Mafeni Mase, Divish Rengasamy, Benjamin Rothwell

This paper presents an open-source Python toolbox called Ensemble Feature Importance (EFI) to provide machine learning (ML) researchers, domain experts, and decision makers with robust and accurate feature importance quantification and more reliable mechanistic interpretation of feature importance for prediction problems using fuzzy sets. The toolkit was dev

Trygve Buanes, Iñaki Lara, Krzysztof Rolbiecki, Kazuki Sakurai

We revisit LHC searches for heavy invisible particles by exploiting QCD initial state radiation. We recast a dijet signal region in a general multijet plus MET search by ATLAS. We find that non-trivial mass limit can be obtained for various models of the electroweakino sector with the present data in hadronic channels. The winos are bound to be heavier than

Rene Allerstorfer, Harry Buhrman, Florian Speelman, Philip Verduyn Lunel

We study the role of quantum communication in attacks on quantum position verification. In this work, we construct the first known example of a QPV protocol that is provably secure against unentangled attackers restricted to classical communication, but can be perfectly attacked by local operations and a single round of simultaneous quantum communication ind

Franco Severo

For a large family of stationary continuous Gaussian fields $f$ on $\mathbb{R}^d$, including the Bargmann-Fock and Cauchy fields, we prove that there exists at most one unbounded connected component in the level set $\{f=\ell\}$ (as well as in the excursion set $\{f\geq\ell\}$) almost surely for every level $\ell\in \mathbb{R}$, thus proving a conjecture pro

Francisco Arana-Herrera, Aaron Calderon

Cutting a hyperbolic surface X along a simple closed multi-geodesic results in a hyperbolic structure on the complementary subsurface. We study the distribution of the shapes of these subsurfaces in moduli space as boundary lengths go to infinity, showing that they equidistribute to the Kontsevich measure on a corresponding moduli space of metric ribbon grap

Tancredi Salamone, Henning G. Hugdal, Sol H. Jacobsen, Morten Amundsen

When applying an external magnetic field to a superconductor, orbital and Pauli paramagnetic pairbreaking effects govern the limit of the upper critical magnetic field that can be supported before superconductivity breaks down. Experimental studies have shown that many multiband superconductors exhibit values of the upper critical magnetic field that violate

Shelley J. Cheng, Abraham Loeb

Context: Optically luminous quasars are metal rich across all redshifts. Surprisingly, there is no significant trend in the broad-line region (BLR) metallicity with different star formation rates (SFR) and the average N V/ C IV metallicity does not appear to exceed $9.5~Z_\odot$. Combined, these observations may suggest a metallicity ceiling. Aims: Here, we

David J. Wilson, Allison Youngblood, Odette Toloza, Jeremy J. Drake

The 1215.67A HI Lyman alpha emission line dominates the ultraviolet flux of low mass stars, including the majority of known exoplanet hosts. Unfortunately, strong attenuation by the interstellar medium (ISM) obscures the line core at most stars, requiring the intrinsic Lyman alpha flux to be reconstructed based on fits to the line wings. We present a test of

A. Pensabene, P. van der Werf, R. Decarli, E. Bañados

Water vapor (H$_{2}$O) is one of the brightest molecular emitters after carbon monoxide (CO) in galaxies with high infrared (IR) luminosity, and allows us to investigate the warm dense phase of the interstellar medium (ISM) where star formation occurs. However, due to the complexity of its radiative spectrum, H$_{2}$O is not frequently exploited as an ISM tr

D. G. Levkov, V. E. Maslov, E. Ya. Nugaev, A. G. Panin

We consider oscillons - localized, quasiperiodic, and extremely long-living classical solutions in models with real scalar fields. We develop their effective description in the limit of large size at finite field strength. Namely, we note that nonlinear long-range field configurations can be described by an effective complex field $\psi(t, \boldsymbol{x})$ w

Pierluca Carenza, Ramkishor Sharma, M. C. David Marsh, Axel Brandenburg

The interconversion of axionlike particles (ALPs) and photons in magnetised astrophysical environments provides a promising route to search for ALPs. The strongest limits to date on light ALPs use galaxy clusters as ALP-photon converters. However, such studies traditionally rely on simple models of the cluster magnetic fields, with the state-of-the-art being

Alexey Bobrick, Giuliano Iorio, Vasily Belokurov, Joris Vos

RR Lyrae are a well-known class of pulsating horizontal branch stars widely used as tracers of old, metal-poor stellar populations. However, mounting observational evidence shows that a significant fraction of these stars may be young and metal-rich. Here, through detailed binary stellar evolution modelling, we show that all such metal-rich RR Lyrae can be n

Yichul Choi, Ho Tat Lam, Shu-Heng Shao

In gauge theory, it is commonly stated that time-reversal symmetry only exists at $\theta=0$ or $\pi$ for a $2\pi$-periodic $\theta$-angle. In this paper, we point out that in both the free Maxwell theory and massive QED, there is a non-invertible time-reversal symmetry at every rational $\theta$-angle, i.e., $\theta= \pi p/N$. The non-invertible time-revers

Bridget Marchington, Richard J. Parker

Protoplanetary discs are crucial to understanding how planets form and evolve, but these objects are subject to the vagaries of the birth environments of their host stars. In particular, photoionising radiation from massive stars has been shown to be an effective agent in disrupting protoplanetary discs. External photoevaporation leads to the inward evolutio

Ben Forrest, Gillian Wilson, Adam Muzzin, Danilo MArchesini

In this work we publish stellar velocity dispersions, sizes, and dynamical masses for 8 ultra-massive galaxies (UMGs; log($M$/M$_\odot>11$, $z\gtrsim3$) from the Massive Ancient Galaxies At $z>3$ NEar-infrared (MAGAZ3NE) Survey, more than doubling the number of such galaxies with velocity dispersion measurements at this epoch. Using the deep Keck/MOSFIRE and

Zhengyan Darius Shi, Dominic V. Else, Hart Goldman, T. Senthil

We study electrical transport at quantum critical points (QCPs) associated with loop current ordering in a metal, focusing specifically on models of the "Hertz-Millis" type. At the infrared (IR) fixed point and in the absence of disorder, the simplest such models have infinite DC conductivity and zero incoherent conductivity at nonzero frequencies. However,

Jiwon Jesse Han, Charlie Conroy, Benjamin D. Johnson, Joshua S. Speagle

Modern Galactic surveys have revealed an ancient merger that dominates the stellar halo of our Galaxy (\textit{Gaia}-Sausage-Enceladus, GSE). Using chemical abundances and kinematics from the H3 Survey, we identify 5559 halo stars from this merger in the radial range $r_{\text{Gal}}=6-60\text{ kpc}$. We forward model the full selection function of H3 to infe

Pengfei Li, Stacy S. McGaugh, Federico Lelli, James M. Schombert

The condensation of baryons within a dark matter (DM) halo during galaxy formation should result in some contraction of the halo as the combined system settles into equilibrium. We quantify this effect on the cuspy primordial halos predicted by DM-only simulations for the baryon distributions observed in the galaxies of the SPARC database. We find that the D

Zhiyuan Ji, Mauro Giavalisco

We use the SED-fitting code Prospector to reconstruct the nonparametric star formation history (SFH) of massive ($\log M_*>10.3$) star-forming galaxies (SFGs) and quiescent galaxies (QGs) at redshift $z_{\rm{obs}}\sim2$ to investigate the joint evolution of star-formation activity and structural properties. We find significant correlations between the SFH of

Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes, Alexander Gagliano

We present DELIGHT, or Deep Learning Identification of Galaxy Hosts of Transients, a new algorithm designed to automatically and in real-time identify the host galaxies of extragalactic transients. The proposed algorithm receives as input compact, multi-resolution images centered at the position of a transient candidate and outputs two-dimensional offset vec

Jean Lahoud, Jiale Cao, Fahad Shahbaz Khan, Hisham Cholakkal

The success of the transformer architecture in natural language processing has recently triggered attention in the computer vision field. The transformer has been used as a replacement for the widely used convolution operators, due to its ability to learn long-range dependencies. This replacement was proven to be successful in numerous tasks, in which severa