July 2023 arXiv papers — page 114

B. Babacan, R. Ainsworth, K. J. Hazelwood, D. K Morris

The ionization profile monitors (IPMs) are used to measure the beam size in synchrotrons. Both the Fermilab Recycler and Main Injector (MI) machines have IPMs. However, they were not well understood enough to provide confidence in their measurements. Accurately measuring beam size through the IPMs was crucial to recognize the loss mechanisms for accelerators

Nouf Almousa, Claudia Bucur, Roberta Cornale, Marco Squassina

In the study of concavity properties of positive solutions to nonlinear elliptic partial differential equations the diffusion and the nonlinearity are typically independent of the space variable. In this paper we obtain new results aiming to get almost concavity results for a relevant class of anisotropic semilinear elliptic problems with spatially dependent

Maxime Dupont, Bhuvanesh Sundar

We introduce a relax-and-round approach embedding the quantum approximate optimization algorithm (QAOA) with $p\geq 1$ layers. We show for many problems, including Sherrington-Kirkpatrick spin glasses, that at $p=1$, it is as accurate as its classical counterpart, and maintains the infinite-depth optimal performance guarantee of the QAOA. Employing a differe

K. Monkman, J. Sirker

We discuss some general properties of the symmetry-resolved von-Neumann entanglement entropy in systems with particle number conservation and describe how to obtain the entanglement components from correlation functions for Gaussian systems. We introduce majorization as an important tool to derive entanglement bounds. As an application, we derive lower bound

Pierre-Louis Lions, Benjamin Seeger

We consider linear and nonlinear transport equations with irregular velocity fields, motivated by models coming from mean field games. The velocity fields are assumed to increase in each coordinate, and the divergence therefore fails to be absolutely continuous with respect to the Lebesgue measure in general. For such velocity fields, the well-posedness of f

Guillaume Chevillon, Takamitsu Kurita

This paper tests the feasibility and estimates the cost of climate control through economic policies. It provides a toolbox for a statistical historical assessment of a Stochastic Integrated Model of Climate and the Economy, and its use in (possibly counterfactual) policy analysis. Recognizing that stabilization requires supressing a trend, we use an integra

Brett Leroux

Let $\mu$ be a probability distribution on $\mathbb{R}^d$ which assigns measure zero to every hyperplane and $S$ a set of points sampled independently from $\mu$. What can be said about the expected combinatorial structure of the convex hull of $S$? These polytopes are simplicial with probability one, but not much else is known except when more restrictive a

Marsha J. Berger, Randall J. LeVeque

We present an algorithm to solve the dispersive depth-averaged Serre-Green-Naghdi (SGN) equations using patch-based adaptive mesh refinement. These equations require adding additional higher derivative terms to the nonlinear shallow water equations. This has been implemented as a new component of the open source GeoClaw software that is widely used for model

Dipal Halder

The globalization of semiconductor supply chains has exposed Network-on-Chip (NoC) interconnects in System-on-Chip (SoC) architectures to critical security risks, including reverse engineering and IP theft. To address these threats, this work builds on two methodologies: ObNoCs [11], which obfuscates NoC topologies using programmable multiplexers, and POTENT

Burak Öz, Benjamin Kraner, Nicolò Vallarano, Bingle Stegmann Kruger

This study explores the intricacies of waiting games, a novel dynamic that emerged with Ethereum's transition to a Proof-of-Stake (PoS)-based block proposer selection protocol. Within this PoS framework, validators acquire a distinct monopoly position during their assigned slots, given that block proposal rights are set deterministically, contrasting with Pr

K. McGee, S-H. Kim, P. Ostroumov, G. Eremeev

Upcoming projects requiring high-Q ~650 MHz medium-to-high-${\beta}$ elliptical cavities drive a need to understand magnetic RF loss mechanisms and mitigations in greater detail. High-temperature annealing and fast-cooldowns have proven effective techniques for promoting magnetic flux expulsion in cavities, however the extent of their effectiveness has been

Ognjen Stanojev, Lesia Mitridati, Riccardo de Nardis di Prata, Gabriela Hug

This paper presents a novel safe reinforcement learning algorithm for strategic bidding of Virtual Power Plants (VPPs) in day-ahead electricity markets. The proposed algorithm utilizes the Deep Deterministic Policy Gradient (DDPG) method to learn competitive bidding policies without requiring an accurate market model. Furthermore, to account for the complex

Daniel Kráľ, Kristýna Pekárková, Kenny Štorgel

Twin-width is a width parameter introduced by Bonnet, Kim, Thomass\'e and Watrigant [FOCS'20, JACM'22], which has many structural and algorithmic applications. We prove that the twin-width of every graph embeddable in a surface of Euler genus $g$ is $18\sqrt{47g}+O(1)$, which is asymptotically best possible as it asymptotically differs from the lower bound b

Kieran Mastel

The n-qubit Pauli group and its normalizer the n-qubit Clifford group have applications in quantum error correction and device characterization. Recent applications have made use of the representation theory of the Clifford group. We apply the tools of (the coincidentally named) Clifford theory to examine the representation theory of the Clifford group using

Weihong Qi, Jinsheng Pan, Hanjia Lyu, Jiebo Luo

As AI systems become increasingly prevalent in various aspects of daily life, gaining a comprehensive understanding of public perception towards these AI systems has become increasingly essential for several reasons such as ethical considerations, user experience, fear, disinformation, regulation, collaboration, and co-creation. In this study, we investigate

Seoyoung Lyla Jung, N. M. McClure-Griffiths, Ruediger Pakmor, Yik Ki Ma

Faraday rotation measure (RM) is arguably the most practical observational tracer of magnetic fields in the diffuse circumgalactic medium (CGM). We sample synthetic Faraday rotation skies of Milky Way-like galaxies in TNG50 of the IllustrisTNG project by placing an observer inside the galaxies at a solar circle-like position. Our synthetic RM grids emulate s

Rubens Copche, Yohan Duarte Pessanha, Vinicius Durelli, Marcelo Medeiros Eler

Tests executed by human testers are still widespread in practice and fill the gap left by limitations of automated approaches. Among the human-centered approaches, exploratory testing is the de facto approach in agile teams. Although it is focused on the expertise and creativity of the tester, the activity of exploratory testing may benefit from support prov

Guadalupe Tovar Mendoza, Robert F. Wilson, Allison Youngblood, Laura D. Vega

As was discovered with other wide field, precise imagers, the stable photometry necessary for the microlensing surveys is well-suited to general stellar astrophysics, including stellar flares, which are important for understanding stellar magnetic activity and even the space weather environments of exoplanets. Large stellar flare surveys have never been perf

Hirak Kansara, Mingchao Liu, Yinfeng He, Wei Tan

Shape-morphing structures possess the ability to change their shapes from one state to another, and therefore, offer great potential for a broad range of applications. A typical paradigm of morphing is transforming from an initial two-dimensional (2D) flat configuration into a three-dimensional (3D) target structure. One popular fabrication method for these

Seung Yeon Shin, Thomas C. Shen, Ronald M. Summers

We propose a method to incorporate the intensity information of a target lesion on CT scans in training segmentation and detection networks. We first build an intensity-based lesion probability (ILP) function from an intensity histogram of the target lesion. It is used to compute the probability of being the lesion for each voxel based on its intensity. Fina

Ondrej Dyck, Andrew R. Lupini, Philip D. Rack, Jason Fowlkes

Focused electron beam induced deposition (FEBID) is a direct write technique for depositing materials on a support substrate akin to 3D printing with an electron beam (e-beam). Opportunities exist for merging this existing technique with aberration-corrected scanning transmission electron microscopy to achieve molecular- or atomic-level spatial precision. Se

L. Ristori, P. Berrutti, M. Narduzzi, J. Delayen

The US will be contributing to the HL-LHC upgrade at CERN with the fabrication and qualification of RFD crabbing cavities in the framework of the HL-LHC Accelerator Upgrade Project (AUP) managed by Fermilab. AUP received Critical Decision 3 (CD-3) approval by DOE in December 2020 launching the project into the production phase. The electro-magnetic design of

Ruiyu Han

The sliced Wasserstein distance as well as its variants have been widely considered in comparing probability measures defined on $\mathbb R^d$. Here we derive the notion of sliced Wasserstein distance for measures on an infinite dimensional separable Hilbert spaces, depict the relation between sliced Wasserstein distance and narrow convergence of measures an

Hyojin Kim, Kyle Champley

Data-driven deep learning has been successfully applied to various computed tomographic reconstruction problems. The deep inference models may outperform existing analytical and iterative algorithms, especially in ill-posed CT reconstruction. However, those methods often predict images that do not agree with the measured projection data. This paper presents

Zhuxian Guo, Qitong Wang, Henning Müller, Themis Palpanas

In digital histopathology, entire neoplasm segmentation on Whole Slide Image (WSI) of Hepatocellular Carcinoma (HCC) plays an important role, especially as a preprocessing filter to automatically exclude healthy tissue, in histological molecular correlations mining and other downstream histopathological tasks. The segmentation task remains challenging due to

Zeqiu. Yu, Shuo. Han, Ziheng. Song

The high cure rate of cancer is inextricably linked to physicians' accuracy in diagnosis and treatment, therefore a model that can accomplish high-precision tumor segmentation has become a necessity in many applications of the medical industry. It can effectively lower the rate of misdiagnosis while considerably lessening the burden on clinicians. However, f

Grigorii Monakov

We consider a nonstationary random walk on a compact metrizable abelian group. Under a classical strict aperiodicity assumption we establish a weak-* convergence to the Haar measure, Ergodic Theorem and Large Deviation Type Estimate.

Tasfia Rahman, Sumaiya Islam Mouno, Arunangshu Mojumder Raatul, Abul Kalam Al Azad

Submitting fake certificates is a common problem in Southeast Asia, which prevents qualified candidates from getting the jobs they deserve. When applying for a job, students must provide academic credentials as proof of their qualifications, acquired both inside and outside the classroom. Verifying academic documents before hiring is crucial to prevent fraud

Seth Kulick, Neville Ryant, David J. Irwin, Naomi Nevler

This paper addresses the problem of improving POS tagging of transcripts of speech from clinical populations. In contrast to prior work on parsing and POS tagging of transcribed speech, we do not make use of an in domain treebank for training. Instead, we train on an out of domain treebank of newswire using data augmentation techniques to make these structur

Daniel McDuff, Andrew Barakat, Ari Winbush, Allen Jiang

The impact of digital device use on health and well-being is a pressing question to which individuals, families, schools, policy makers, legislators, and digital designers are all demanding answers. However, the scientific literature on this topic to date is marred by small and/or unrepresentative samples, poor measurement of core constructs (e.g., device us

Long Chen, Jian Jiang, Bozheng Dou, Hongsong Feng

Pain is a significant global health issue, and the current treatment options for pain management have limitations in terms of effectiveness, side effects, and potential for addiction. There is a pressing need for improved pain treatments and the development of new drugs. Voltage-gated sodium channels, particularly Nav1.3, Nav1.7, Nav1.8, and Nav1.9, play a c

Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy

Animals and robots navigate through environments by building and refining maps of space. These maps enable functions including navigation back to home, planning, search and foraging. Here, we use observations from neuroscience, specifically the observed fragmentation of grid cell map in compartmentalized spaces, to propose and apply the concept of Fragmentat

Ondrej Dyck, Lizhi Zhang, Mina Yoon, Jacob L. Swett

Atomic-scale fabrication is an outstanding challenge and overarching goal for the nanoscience community. The practical implementation of moving and fixing atoms to a structure is non-trivial considering that one must spatially address the positioning of single atoms, provide a stabilizing scaffold to hold structures in place, and understand the details of th

C. Narug, T. Arkan, S. Cheban, M. Chen

A Buncher or Capture Cavity (BCC) Cryomodule is currently in development at Fermilab for use in a second injector for LCLS-II-HE. The BCC Cryomodule is designed to contain one 1.3 GHz cavity and one solenoid magnet as part of a 100MeV low emittance injector. The design considerations for the Cryomodule are similar to the LCLS-II cryomodule with additional re

W. A. Ahmad, A. Bartolini, F. Beneventi, L. Benini

In this paper we present D.A.V.I.D.E. (Development for an Added Value Infrastructure Designed in Europe), an innovative and energy efficient High Performance Computing cluster designed by E4 Computer Engineering for PRACE (Partnership for Advanced Computing in Europe). D.A.V.I.D.E. is built using best-in-class components (IBM's POWER8-NVLink CPUs, NVIDIA TES

Mihaela Rosca, Marc Peter Deisenroth

Recent years have seen many insights on deep learning optimisation being brought forward by finding implicit regularisation effects of commonly used gradient-based optimisers. Understanding implicit regularisation can not only shed light on optimisation dynamics, but it can also be used to improve performance and stability across problem domains, from superv

Suyash Verma, Muhammad Saif Ullah Khalid, Arman Hemmati

Three-dimensional wake of an oscillating foil with combined heaving and pitching motion is numerically evaluated at a range of chord-based Strouhal number (0.32 \le Stc \le 0.56) and phase offset (90 deg \le \phi \le 70 deg) at Re = 8000. The changes in \phi and Stc reflect a unique route of transition in mechanisms that govern the origin of spanwise instabi

Eder M. Correa

We construct the first explicit non-trivial example of deformed Hermitian Yang-Mills (dHYM) connection on a higher rank slope-unstable holomorphic vector bundle over a Fano threefold. Additionally, we provide a sufficient algebraic condition in terms of central charges for the existence of dHYM connections on Whitney sum of holomorphic line bundles over rati

Daniel Jörgens, Pierre-Marc Jodoin, Maxime Descoteaux, Rodrigo Moreno

One of the main issues of the current tractography methods is their high false-positive rate. Tractogram filtering is an option to remove false-positive streamlines from tractography data in a post-processing step. In this paper, we train a deep neural network for filtering tractography data in which every streamline of a tractogram is classified as {\em pla

Jianlin Xia

The Nystr\"om method is a convenient heuristic method to obtain low-rank approximations to kernel matrices in nearly linear complexity. Existing studies typically use the method to approximate positive semidefinite matrices with low or modest accuracies. In this work, we propose a series of heuristic strategies to make the Nystr\"om method reach high accurac

Matthias De Lange, Hamid Eghbalzadeh, Reuben Tan, Michael Iuzzolino

In egocentric action recognition a single population model is typically trained and subsequently embodied on a head-mounted device, such as an augmented reality headset. While this model remains static for new users and environments, we introduce an adaptive paradigm of two phases, where after pretraining a population model, the model adapts on-device and on

Michael R. Douglas

Artificial intelligence is making spectacular progress, and one of the best examples is the development of large language models (LLMs) such as OpenAI's GPT series. In these lectures, written for readers with a background in mathematics or physics, we give a brief history and survey of the state of the art, and describe the underlying transformer architectur

André Beauducel, Norbert Hilger

Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant method for the investigation of the oblique independent clusters model. It was argued that minimizing single cross-loadings by means of target rotation may lead to large effects of sampling error on the target rotated factor solutions. Method: In order to minimi

Anqi Feng, Dimitri Johnson, Grace R. Reilly, Loka Thangamathesvaran

Importance: Ultra-widefield fundus photography (UWF-FP) has shown utility in sickle cell retinopathy screening; however, image artifact may diminish quality and gradeability of images. Objective: To create an automated algorithm for UWF-FP artifact classification. Design: A neural network based automated artifact detection algorithm was designed to identify

Wayne Yang, Garrett Nicolai

Neural models have revolutionized the field of machine translation, but creating parallel corpora is expensive and time-consuming. We investigate an alternative to manual parallel corpora - hallucinated parallel corpora created by generative language models. Although these models are themselves trained on parallel data, they can leverage a multilingual vecto

J. Helsper, S. Chandrasekaran, J. Holzbauer, N. Solyak

The PIP-II Project will see international shipment of cryomodules from Europe to the United States, and as such, the shocks which can occur during shipment pose a risk to the internal components. Of particular concern is the coupler ceramic window and surrounding brazes, which will see stresses during an excitation event. Since the antenna design is new, and

Ondrej Dyck, Mina Yoon, Lizhi Zhang, Andrew R. Lupini

Chromium atoms in graphene have been proposed to exhibit magnetic moments and spin-selective conducting states depending on the local bonding geometry within the graphene structure, which could lead to interesting applications in spintronics. Despite this interest, there are few direct experimental reports of Cr dopants in graphene even though it is theorize

Le Hu, Andrew N. Jordan

We show that all non-relativistic quantum processes, whether open or closed, are either unitary or probabilistic unitary, i.e., probabilistic combination of unitary evolutions. This means that for open quantum systems, its continuous dynamics can always be described by the Lindblad master equation with all jump operators being unitary. We call this formalism

Arjun Subramonian, Adina Williams, Maximilian Nickel, Yizhou Sun

The expressive power of graph neural networks is usually measured by comparing how many pairs of graphs or nodes an architecture can possibly distinguish as non-isomorphic to those distinguishable by the $k$-dimensional Weisfeiler-Leman ($k$-WL) test. In this paper, we uncover misalignments between graph machine learning practitioners' conceptualizations of

Fábio Natali, Thiago P. de Andrade

In this paper, we investigate the spectral stability of periodic traveling waves for a cubic-quintic and double dispersion equation. Using the quadrature method we find explict periodic waves and we also present a characterization for all positive and periodic solutions for the model using the monotonicity of the period map in terms of the energy levels. The

Konstantinos Kalimeris, Leonidas Mindrinos

We derive the extension of the classical d'Alembert formula for the wave equation, which provides the analytical solution for the direct scattering problem for a medium with constant refractive index; this is achieved by employing results obtained via the Fokas method. This methodology is further extended to a medium with piecewise constant refractive index,

Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar

Machine learning is increasingly deployed in safety-critical domains where erroneous predictions may lead to potentially catastrophic consequences, highlighting the need for learning systems to be aware of how confident they are in their own predictions: in other words, 'to know when they do not know'. In this paper, we propose a novel Random-Set Neural Netw

Chao Min, Yi Zhao, Yi Bu, Ying Ding

Artificial Intelligence (AI), a cornerstone of 21st-century technology, has seen remarkable growth in China. In this paper, we examine China's AI development process, demonstrating that it is characterized by rapid learning and differentiation, surpassing the export-oriented growth propelled by Foreign Direct Investment seen in earlier Asian industrializers.

J. Helsper, S. Wallon, D. Passarelli, D. Longuevergne

Five 325 MHz high-power couplers will be integrated into the pre-production Single Spoke Resonator Type-II (ppSSR2) cryomodule for the PIP-II project at Fermilab. Couplers were procured by both Fermilab and IJCLAB for this effort. The design of the coupler is described, including design optimizations from the previous generation. This paper then describes th

Giulio Caviglia, Alessio Moscariello, Alessio Sammartano

Let G be a numerical semigroup. In this paper, we prove an upper bound for the Betti numbers of the semigroup ring of G which depends only on the width of G, that is, the difference between the largest and the smallest generator of G. In this way, we make progress towards a conjecture of Herzog and Stamate. Moreover, for 4-generated numerical semigroups, the

Koresh Khateri, Giovanni Beltrame

This paper presents a scalable solution with adjustable computation time for the joint problem of scheduling and assigning machines and transporters for missions that must be completed in a fixed order of operations across multiple stages. A battery-operated multi-robot system with a maximum travel range is employed as the transporter between stages and char

Victor Dubach

The study of longest increasing subsequences (LIS) in permutations led to that of Young diagrams via Robinson-Schensted's (RS) correspondence. In a celebrated paper, Vershik and Kerov obtained a limit theorem for such diagrams and found that the LIS of a uniform permutation of size n behaves as $2\sqrt{n}$. Independently and much later, Hoppen et al. introdu

Aytekin Demirci, Dominik Steinberger, Markus Stricker, Nina Merkert

Over the past decades, discrete dislocation dynamics simulations have been shown to reliably predict the evolution of dislocation microstructures for micrometer-sized metallic samples. Such simulations provide insight into the governing deformation mechanisms and the interplay between different physical phenomena such as dislocation reactions or cross-slip.

Hugo Cisneros

In this thesis, we explore the use of complex systems to study learning and adaptation in natural and artificial systems. The goal is to develop autonomous systems that can learn without supervision, develop on their own, and become increasingly complex over time. Complex systems are identified as a suitable framework for understanding these phenomena due to

Chantal Pellegrini, Matthias Keicher, Ege Özsoy, Nassir Navab

Radiology reporting is a crucial part of the communication between radiologists and other medical professionals, but it can be time-consuming and error-prone. One approach to alleviate this is structured reporting, which saves time and enables a more accurate evaluation than free-text reports. However, there is limited research on automating structured repor

Jan Dymara, Tadeusz Januszkiewicz

We discuss the formalism of tautological characteristic classes of flat bundles. Applied to $PSL(2,K)$ it yields the Witt class of Nekovar. Applied to $PGL_+(2n,K)$, the general linear groups with positive determinant over an arbitrary ordered field, it yields (a generalization of) the Euler class.

Ondrej Dyck, Sinchul Yeom, Sarah Dillender, Andrew R. Lupini

Graphene is of great scientific interest due to a variety of unique properties such as ballistic transport, spin selectivity, the quantum hall effect, and other quantum properties. Nanopatterning and atomic scale modifications of graphene are expected to enable further control over its intrinsic properties, providing ways to tune the electronic properties th

Tobias Braun, Tobias Korzyzkowske, Larissa Putzar, Jan Mietzner

Due to technological advances in the field of radio technology and its availability, the number of interference signals in the radio spectrum is continuously increasing. Interference signals must be detected in a timely fashion, in order to maintain standards and keep emergency frequencies open. To this end, specialized (multi-channel) receivers are used for

Jeremy Hansen, Kirill Tuchin

We study electromagnetic radiation by a fast particle carrying electric charge in chiral medium. The medium is homogeneous and isotropic and supports the chiral magnetic current which renders the fermion and photon states unstable. The instability manifests as the chirality-dependent resonances in the bremsstrahlung cross section, which enhance the energy lo

Erick Oliveira Rodrigues, Esteban Clua, Giovani Bernardes Vitor

This work proposes a complete methodology to colorize images of Fakemon, anime-style monster-like creatures. In addition, we propose algorithms to extract the line art from colorized images as well as to extract color hints. Our work is the first in the literature to use automatic color hint extraction, to train the networks specifically with anime-styled cr

K. Jhuria, V. Ivanov, D. Polley, W. Liu

Silicon-based quantum emitters are candidates for large-scale qubit integration due to their single-photon emission properties and potential for spin-photon interfaces with long spin coherence times. Here, we demonstrate local writing and erasing of selected light-emitting defects using fs laser pulses in combination with hydrogen-based defect activation and

Jingda Yang, Ying Wang

Softwarization and virtualization in 5G and beyond require rigorous testing against vulnerabilities and unintended emergent behaviors for critical infrastructure and network security assurance. Formal methods operates efficiently in protocol-level abstract specification models, and fuzz testing offers comprehensive experimental evaluation of system implement

Leandro Roza Livramento, Yakov Shnir

We construct new solutions of a $U(1)$ gauged Skyrme-Maxwell model of topological degrees $Q\leq 5$, which represent Skyrmions coupled to magnetic fluxes. It is found that, generically, in the strong coupling limit, coupling to the magnetic field results in transformation of the configuration to the toroidally shaped Skyrmions bounded to the local magnetic f

Ji-Chong Yang, Xu-Guang Huang

We investigate the finite-temperature quantum chromodynamics (QCD) on a rotating lattice with $N_f=2+1$ staggered fermions and the projective plane boundary condition. We observe a negative rotational rigidity (defined in the main text) and a negative quark spin susceptibility associated with the chiral vortical effect. In contrast to most of the effective m

Zhiyuan Zhang, Zhan Shi, Daniel Ahmed

Shape transformation, a key mechanism for organismal survival and adaptation, has gained importance across fields as diverse as electronics and medicine. However, designing and controlling microscale shape-shifting materials remains a fundamental challenge in various actuation modalities. Here, we introduce SonoTransformer, an acoustically activated micromac

Pengyun Yue, Long Yang, Cong Fang, Zhouchen Lin

Zeroth-order optimization is a fundamental research topic that has been a focus of various learning tasks, such as black-box adversarial attacks, bandits, and reinforcement learning. However, in theory, most complexity results assert a linear dependency on the dimension of optimization variable, which implies paralyzations of zeroth-order algorithms for high

Muteen Munawar, Kyungchun Lee

This study considers a dual-polarized intelligent reflecting surface (DP-IRS)-assisted multiple-input multiple-output (MIMO) single-user wireless communication system. The transmitter and receiver are equipped with DP antennas, and each antenna features a separate phase shifter for each polarization. We attempt to maximize the system's spectral efficiency (S

Jack Kramer, Vakhtang Chulukhadze, Kenny Huynh, Omar Barrera

This work reports a 50.74 GHz lithium niobate (LiNbO3) acoustic resonator with a high quality factor (Q) of 237 and an electromechanical coupling (k2) of 5.17% resulting in a figure of merit (FoM, Q x k2) of 12.2. The LiNbO3 resonator employs a novel bilayer periodically poled piezoelectric film (P3F) 128 Y-cut LiNbO3 on amorphous silicon (a-Si) on sapphire

Adam Fisch, Amal Rannen-Triki, Razvan Pascanu, Jörg Bornschein

As the application space of language models continues to evolve, a natural question to ask is how we can quickly adapt models to new tasks. We approach this classic question from a continual learning perspective, in which we aim to continue fine-tuning models trained on past tasks on new tasks, with the goal of "transferring" relevant knowledge. However, thi

Raghavendra Kanakagiri, Edgar Solomonik

Sparse tensor decomposition and completion are common in numerous applications, ranging from machine learning to computational quantum chemistry. Typically, the main bottleneck in optimization of these models are contractions of a single large sparse tensor with a network of several dense matrices or tensors (SpTTN). Prior works on high-performance tensor de

Juan A. Almendral, I. Leyva, Irene Sendiña-Nadal

Ordinal measures provide a valuable collection of tools for analyzing correlated data series. However, using these methods to understand the information interchange in networks of dynamical systems, and uncover the interplay between dynamics and structure during the synchronization process, remains relatively unexplored. Here, we compare the ordinal permutat

B. Popescu Braileanu, R. Keppens

The density decreases exponentially with height in the solar gravitationally stratified atmosphere, therefore the collisional coupling between the ionized plasma and the neutrals also decreases. Here, we investigate the role of collisions between ions and neutrals on the reconnection process occurring at various heights in the atmosphere. We perform simulati

Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki

Scientific Machine Learning (SciML) is a burgeoning field that synergistically combines domain-aware and interpretable models with agnostic machine learning techniques. In this work, we introduce GOKU-UI, an evolution of the SciML generative model GOKU-nets. GOKU-UI not only broadens the original model's spectrum to incorporate other classes of differential

Saugata Basu, Jannis Born, Aritra Bose, Sara Capponi

In recent years, there has been tremendous progress in the development of quantum computing hardware, algorithms and services leading to the expectation that in the near future quantum computers will be capable of performing simulations for natural science applications, operations research, and machine learning at scales mostly inaccessible to classical comp

Vladislav Borisov, Nastaran Salehi, Manuel Pereiro, Anna Delin

Using ab initio density functional theory with static mean-field correlations, we calculate the Heisenberg and Dzyaloshinskii-Moriya interactions (DMI) for an atomistic spin Hamiltonian for the lacunar spinel, GaV$_4$S$_8$. The parameters describing these interactions are used in atomistic spin dynamics and micromagnetic simulations. The magnetic properties

Theodore Anyika, Ikjun Hong, Justus C. Ndukaife

Double Nanohole Plasmonic Tweezers (DNH) have revolutionized particle trapping capabilities, enabling trapping of nanoscale particles well beyond the diffraction limit. This advancement allows for the low-power trapping of extremely small particles, such as 20 nm nanoparticles and individual proteins. However, to mitigate the potentially amplified effects of

Federico Scavia

Let $E$ be the Fermat cubic curve over $\bar{\mathbb{Q}}$. In 2002, Schoen proved that the group $CH^2(E^3)/\ell$ is infinite for all primes $\ell\equiv 1\pmod 3$. We show that $CH^2(E^3)/\ell$ is infinite for all prime numbers $\ell> 5$. This gives the first example of a smooth projective variety $X$ over $\bar{\mathbb{Q}}$ such that $CH^2(X)/\ell$ is infin

James Atwood, Tina Tian, Ben Packer, Meghana Deodhar

Despite the rich literature on machine learning fairness, relatively little attention has been paid to remediating complex systems, where the final prediction is the combination of multiple classifiers and where multiple groups are present. In this paper, we first show that natural baseline approaches for improving equal opportunity fairness scale linearly w

Tiffany J. Callahan, Ignacio J. Tripodi, Adrianne L. Stefanski, Luca Cappelletti

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. Howev

Satarupa Bhattacharjee, Hans-Georg Müller

Mixed effect modeling for longitudinal data is challenging when the observed data are random objects, which are complex data taking values in a general metric space without linear structure. In such settings the classical additive error model and distributional assumptions are unattainable. Due to the rapid advancement of technology, longitudinal data contai

V. N. Obridko, D. D. Sokoloff, M. M. Katsova

Further development of the work of Obridko et al. [1] based on recent data confirms the assumption that the 25th cycle of solar activity is a medium-low cycle. Its height is expected to be $125.2\pm5.6$, and the expected date of the maximum phase is the end of 2023 or the first quarter of 2024.

J. Linek, M. Wyszynski, B. Müller, D. Korinski

We investigate the coupling factor $\phi_\mu$ that quantifies the magnetic flux $\Phi$ per magnetic moment $\mu$ of a point-like magnetic dipole that couples to a superconducting quantum interference device (SQUID). Representing the dipole by a current-carrying loop, the reciprocity of mutual inductances of SQUID and loop provides a way of calculating $\phi_

Johanna Potyka, Kathrin Schulte, Carole Planchette

Head-on collisions of two immiscible liquid droplets lead to a collision complex, which may either remain stable in the form of a single compound drop, or fragment into two main daughter droplets. This paper investigates the liquid distribution developing in the two daughter droplets and which can be of three types. Either two encapsulated droplets (single r

Shahul Hameed K, Ramakrishnan K O, Biju K

A conjugate skew gain graph is a skew gain graph with the labels (also called, the conjugate skew gains) from the field of complex numbes on the oriented edges such that they get conjugated when we reverse the orientation. In this paper we introduce distance matrices for conjugate skew gain graphs and characterize balanced conjugate skew gain graphs using th

Ela Celikbas, Hugh Geller, Tony Se

We consider fiber products of complete, local, noetherian algebras over a fixed residue field. Some of these rings cannot be minimally resolved with a free resolution using the recent work of the second author. We develop techniques to modify Geller's approach in order to recover the Betti numbers and Poincar\'e series for these fiber products.

Tommaso Treu, Anowar J. Shajib

Time delays from strong gravitational lensing provide a one-step absolute distance measurement. Thus, they measure $H_0$ independently of all other probes. We first review the foundations and history of time-delay cosmography. Then, we illustrate the current state of the art by means of two recent case studies that have been real breakthroughs: i) the quadru

Gonzalo Manzano, Gülce Kardeş, Édgar Roldán, David Wolpert

Developing a thermodynamic theory of computation is a challenging task at the interface of non-equilibrium thermodynamics and computer science. In particular, this task requires dealing with difficulties such as stochastic halting times, unidirectional (possibly deterministic) transitions, and restricted initial conditions, features common in real-world comp

Stanley Yao Xiao, Shuntaro Yamagishi

In this paper, we prove that there does not exist $F \in \mathbb{Q}[x,y]$ of degree $4$ such that $F(\mathbb{Z}^2) = \mathbb{Z}_{\geq 0}$. In particular, this answers a question by John S. Lew and Bjorn Poonen for quartic polynomials.

Giuseppe Orlando, Paolo Francesco Barbante, Luca Bonaventura

Many physical situations are characterized by interfaces with a non trivial shape so that relevant geometric features, such as interfacial area, curvature or unit normal vector, can be used as main indicators of the topology of the interface. We analyze the evolution equations for a set of geometrical quantities that characterize the interface in two-phase f

M. P. Ross, J. van Dongen, Y. Huang, P. Zhou

We describe an inertial rotation sensor with a 30-cm cylindrical proof-mass suspended from a pair of 14-${\mu}$m thick BeCu flexures. The angle between the proof-mass and support structure is measured with a pair of homodyne interferometers which achieve a noise level of $\sim 5\ \text{prad}/\sqrt{\text{Hz}}$. The sensor is entirely made of vacuum compatible

Wojciech Marciniak, Mirosław Werwiński

Fe-Co alloys with induced tetragonal strain are promising materials for rare-earth-free permanent magnets. However, as ultrathin-film studies have shown, tetragonal Fe-Co structures tend to a rapid relaxation toward a cubic structure as the thickness of the deposited film increases. One of the main methods of inducing the stable strain in the bulk material i

Rachel L. Binks, Sarah E. Heaps, Mariella Panagiotopoulou, Yujiang Wang

Vector autoregressions (VARs) are a widely used tool for modelling multivariate time-series. It is common to assume a VAR is stationary; this can be enforced by imposing the stationarity condition which restricts the parameter space of the autoregressive coefficients to the stationary region. However, implementing this constraint is difficult due to the comp

Julien Nicolas, Florent Chiaroni, Imtiaz Ziko, Ola Ahmad

Despite the recent progress in incremental learning, addressing catastrophic forgetting under distributional drift is still an open and important problem. Indeed, while state-of-the-art domain incremental learning (DIL) methods perform satisfactorily within known domains, their performance largely degrades in the presence of novel domains. This limitation ha

Kevin A. McKinnon, Melissa K. Ness, Constance M. Rockosi, Puragra Guhathakurta

Data-driven models of stellar spectra are useful tools to study non-stellar information, such as the Diffuse Interstellar Bands (DIBs) caused by intervening interstellar material. Using $\sim 55000$ spectra of $\sim 17000$ red clump stars from the APOGEE DR16 dataset, we create 2nd order polynomial models of the continuum-normalized flux as a function of ste

Shiying Li, Caroline Moosmueller, Yongzhe Wang

This paper studies iterative schemes for measure transfer and approximation problems, which are defined through a slicing-and-matching procedure. Similar to the sliced Wasserstein distance, these schemes benefit from the availability of closed-form solutions for the one-dimensional optimal transport problem and the associated computational advantages. While