July 2023 arXiv papers — page 134

Vladan Stojnić, Zakaria Laskar, Giorgos Tolias

Deep active learning in the presence of outlier examples poses a realistic yet challenging scenario. Acquiring unlabeled data for annotation requires a delicate balance between avoiding outliers to conserve the annotation budget and prioritizing useful inlier examples for effective training. In this work, we present an approach that leverages three highly sy

Trupti Patil, Ruchika, Sukanta Panda

We do a detailed analysis of a well-theoretically motivated interacting dark energy scalar field model with a time-varying interaction term. Using current cosmological datasets from CMB, BAO, Type Ia Supernova, $H(z)$ measurements from cosmic chronometers, angular diameter measurements from Megamasers, growth measurements, and local SH0ES measurements, we fo

Alexander Schnell, Christof Weitenberg, André Eckardt

Floquet engineering is an important tool for realizing topologically nontrivial band structures for charge-neutral atoms in optical lattices. However, the preparation of a topological-band-insulator-type state of fermions, with one nontrivial quasi-energy band filled completely and the others empty, is challenging as a result of both driving induced heating

Tommaso Pegolotti, Elias Frantar, Dan Alistarh, Markus Püschel

We present ongoing work on a new automatic code generation approach for supporting quantized generative inference on LLMs such as LLaMA or OPT on off-the-shelf CPUs. Our approach is informed by the target architecture and a performance model, including both hardware characteristics and method-specific accuracy constraints. Results on CPU-based inference for

N. A. Carella

Let $E$ be a nonsingular elliptic curve over the rational numbers, and let $\tau^n=p^n+1-\#E(\mathbb{F}_{p^n})$. A result in the current literature claims that the normalized traces of Frobenius $\alpha_n=(\tau^n+\overline{\tau}^n)/2p^{n/2}$ are equidistributed on the interval $[-1,1]$ as $n\to \infty$. This short note has two goals: 1. Proposes a correction

Richard Habrovsky

In this work a new expansions of Coulomb potential and interparticle distance, linear term $r_{12}$ are proposed. Except the singularities, the expansions converge to the exact value in the whole coordinate space including the vicinity of the singularities or correlation cusps points. The disadvantage of the expansion is, that it leads to complicated goniome

Souradeep Pal, K Rajesh Nayak

We implement an eccentric search for compact binary mergers based on particle swarm optimization. Orbital eccentricity is an invaluable input for understanding the formation scenarios of the binary mergers and can play a pivotal role in finding their electromagnetic counterparts. Current modelled searches rely on pre-computed template banks that are computat

Roopayan Ghosh, Sougato Bose

Detecting entanglement in many-body quantum systems is crucial but challenging, typically requiring multiple measurements. Here, we establish the class of states where measuring connected correlations in just $\textit{one}$ basis is sufficient and necessary to detect bipartite separability, provided the appropriate basis and observables are chosen. This meth

Krishnapriya Vishnubhotla, Frank Rudzicz, Graeme Hirst, Adam Hammond

Current models for quotation attribution in literary novels assume varying levels of available information in their training and test data, which poses a challenge for in-the-wild inference. Here, we approach quotation attribution as a set of four interconnected sub-tasks: character identification, coreference resolution, quotation identification, and speake

Maria Teresa Parreira, Michael J. Sack, Hifza Javed, Nawid Jamali

Social distance, or perception of the other, is recognized as a dynamic dimension of an interaction, but yet to be widely explored or understood. Through CORAE, a novel web-based open-source tool for COntinuous Retrospective Affect Evaluation, we collected retrospective ratings of interpersonal perceptions between 12 participant dyads. In this work, we explo

Caio Alves, Rodrigo Ribeiro, Rémy Sanchis

In this paper, we investigate the global clustering coefficient (a.k.a transitivity) and clique number of graphs generated by a preferential attachment random graph model with an additional feature of allowing edge connections between existing vertices. Specifically, at each time step $t$, either a new vertex is added with probability $f(t)$, or an edge is a

Xiaodong Guo, Xiaokang Li, Zengwei Zhu, Kamran Behnia

Whenever two irreversible processes occur simultaneously, time-reversal symmetry of microscopic dynamics gives rise, on a macroscopic level, to Onsager's reciprocal relations, which impose constraints on the number of independent components of any transport coefficient tensor. Here, we show that in the antiferromagnetic YbMnBi$_2$, which displays a strong te

A. C. Hayes, G. Kyrala, M. Gooden, J. B. Wilhelmy

We report on the first experiment dedicated to the study of nuclear reactions on dopants in a cryogenic capsule at the National Ignition Facility (NIF). This was accomplished using bromine doping in the inner layers of the CH ablator of a capsule identical to that used in the NIF shot N140520. The capsule was doped with 3$\times$10$^{16}$ bromine atoms. The

Hewei Frederic Jia

Correlation function of twist operators is a natural quantity of interest in two-dimensional conformal field theory (2d CFT) and finds relevance in various physical contexts. For computing twist operator correlators associated with generic branched covers of genus zero and one, we present a generalization of the conventional stress-tensor method to encompass

Mohamed Elhamdadi, Prasad Senesi, Emanuele Zappala

Quandle representations are homomorphisms from a quandle to the group of invertible matrices on some vector space taken with the conjugation operation. We study certain families of quandle representations. More specifically, we introduce the notion of regular representation for quandles, investigating in detail the regular representations of dihedral quandle

Dandan Guan, Yanmei Chen, Jie Qi, Linglong Du

In this paper, a delay compensation design method based on PDE backstepping is developed for a two-dimensional reaction-diffusion partial differential equation (PDE) with bilateral input delays. The PDE is defined in a rectangular domain, and the bilateral control is imposed on a pair of opposite sides of the rectangle. To represent the delayed bilateral inp

Gabriela Morillo, John Cosmas

High data rates are one of the most prevalent requirements in current mobile communications. To cover this and other high standards regarding performance, increasing coverage, capacity, and reliability, numerous works have proposed the development of systems employing the combination of several techniques such as Multiple Input Multiple Output (MIMO) wireles

Yasha Kaushal, Angelos Nersesian, Rachel Bezanson, Arjen van der Wel

We present individual star-formation histories of $\sim3000$ massive galaxies (log($\mathrm{M_*/M_{\odot}}$) > 10.5) from the Large Early Galaxy Astrophysics Census (LEGA-C) spectroscopic survey at a lookback time of $\sim$7 billion years and quantify the population trends leveraging 20hr-deep integrated spectra of these $\sim$ 1800 star-forming and $\sim$ 1

Michael Geller, Subhajit Ghosh, Sida Lu, Yuhsin Tsai

In this paper, we study a possible early universe source for the recent observation of a stochastic gravitational wave background at the NANOGrav pulsar timing array. The source is a tachyonic instability in a dark gauge field induced by an axion-like particle (ALP), a known source for gravitational waves. We find that relative to the previous analysis with

Avijit Saha, Abhishek Y. Deshmukh, Temistocle Grenga, Heinz Pitsch

Flash-boiling injection is one of the most effective ways to accomplish improved atomization compared to the high-pressure injection strategy. The tiny droplets formed via flash-boiling lead to fast fuel-air mixing and can subsequently improve combustion performance in engines. Most of the previous studies related to the topic focused on modeling flash-boili

Nicole Reindl, Ramazan Islami, Klaus Werner, S. O. Kepler

We report on the spectroscopic confirmation of 68 new bright ($G=13.5-17.2$ mag) and blue (pre-)white dwarfs (WDs). This finding has allowed us to almost double the number of the hottest ($T_{\mathrm{eff}} \geq 60$kK) known WDs brighter than $G=16$ mag. We increased the number of known ultra-high excitation (UHE) WDs by 20%, found one unambiguous close binar

Dong Wang, Dong Yao

We consider the Plancherel-Rotach type asymptotics of the biorthogonal polynomials associated to the biorthogonal ensemble with the joint probability density function \begin{equation*} \frac{1}{C} \prod_{1 \leq i < j \leq n} (\lambda_j -\lambda_i)(f(\lambda_j) - f(\lambda_i)) \prod^n_{j = 1} W^{(n)}_{\alpha}(\lambda_j) d\lambda_j, \end{equation*} where \begi

Jonathan Yang, Dorsa Sadigh, Chelsea Finn

Reusing large datasets is crucial to scale vision-based robotic manipulators to everyday scenarios due to the high cost of collecting robotic datasets. However, robotic platforms possess varying control schemes, camera viewpoints, kinematic configurations, and end-effector morphologies, posing significant challenges when transferring manipulation skills from

Ying-Ying Wang, Yu-Xin Wang, Sean van Geldern, Thomas Connolly

The dispersive interaction between a qubit and a cavity is ubiquitous in circuit and cavity quantum electrodynamics. It describes the frequency shift of one quantum mode in response to excitations in the other, and in closed systems is necessarily bidirectional, i.e.~reciprocal. Here, we present an experimental study of a non-reciprocal dispersive-type inter

Mohamed El Hedi Bahri, Siddhartha Sarkar, Daniel Alejandro Matoz-Fernandez, Andrej Košmrlj

Non-equilibrium and active effects in mesoscopic scale systems have heralded a new era of scientific inquiries, whether concerning meta-materials or biological systems such as bacteria and cellular components. At mesoscopic scales, experimental and theoretical treatments of membranes, and other quasi-two-dimensional elastic surfaces cannot generically ignore

Cameron Berg, Vittorio Caggiano, Vikash Kumar

Learning effective continuous control policies in high-dimensional systems, including musculoskeletal agents, remains a significant challenge. Over the course of biological evolution, organisms have developed robust mechanisms for overcoming this complexity to learn highly sophisticated strategies for motor control. What accounts for this robust behavioral f

David Aasen, Jeongwan Haah, Parsa Bonderson, Zhenghan Wang

We develop protocols for Hastings-Haah Floquet codes in the presence of dead qubits.

Felipe Hernández, Daniel Ranard, C. Jess Riedel

Quantum and classical systems evolving under the same formal Hamiltonian $H$ may dramatically differ after the Ehrenfest timescale $t_E \sim \log(\hbar^{-1})$, even as $\hbar \to 0$. Coupling the system to a Markovian environment results in a Lindblad equation for the quantum evolution. Its classical counterpart is given by the Fokker-Planck equation on phas

Samuel E. Begg, Ryo Hanai

We investigate the impact of nonreciprocity on universality and critical phenomena in open quantum interacting many-body systems. Nonreciprocal open quantum systems often have an exotic spectral sensitivity to boundary conditions, known as the Liouvillian skin effect (LSE). By considering an open quantum XXZ spin chain that exhibits LSE, we demonstrate the e

Navketan Batra, D. E. Feldman

Fractional charges of anyons can be extracted from shot noise in two ways. One can use either the auto-correlation noise of the current in one drain or the cross-correlation noise between two drains on the two sides of the device. The former approach typically overestimates the charge. This may happen due to upstream edge modes. We propose a mechanism for th

Lakshmi Nair, Mikhail Bernadskiy, Arulselvan Madhavan, Craig Chan

The recent rise of large language models (LLMs) has resulted in increased efforts towards running LLMs at reduced precision. Running LLMs at lower precision supports resource constraints and furthers their democratization, enabling users to run billion-parameter LLMs on their personal devices. To supplement this ongoing effort, we propose INT-FP-QSim: an ope

Tom Smeding, Matthijs Vákár

We show how the basic Combinatory Homomorphic Automatic Differentiation (CHAD) algorithm can be optimised, using well-known methods, to yield a simple, composable, and generally applicable reverse-mode automatic differentiation (AD) technique that has the correct computational complexity that we would expect of reverse-mode AD. Specifically, we show that the

Ayse Gizem Yasar, Andrew Chong, Evan Dong, Thomas Krendl Gilbert

As AI technology advances rapidly, concerns over the risks of bigness in digital markets are also growing. The EU's Digital Markets Act (DMA) aims to address these risks. Still, the current framework may not adequately cover generative AI systems that could become gateways for AI-based services. This paper argues for integrating certain AI software as core p

Petr Zapletal, Nathan A. McMahon, Michael J. Hartmann

The analysis of noisy quantum states prepared on current quantum computers is getting beyond the capabilities of classical computing. Quantum neural networks based on parametrized quantum circuits, measurements and feed-forward can process large amounts of quantum data to reduce measurement and computational costs of detecting non-local quantum correlations.

António Leitão, Maxime Lucas, Simone Poetto, Taylor A. Hersh

We provide quantitative evidence suggesting social learning in sperm whales across socio-cultural boundaries, using acoustic data from the Pacific and Atlantic Oceans. Traditionally, sperm whale populations are categorized into clans based on their vocal repertoire: the rhythmically patterned click sequences (codas) that they use. Among these codas, identity

Sebastian Blacker, Hristijan Kochankovski, Andreas Bauswein, Angels Ramos

We provide the first comprehensive study of hyperons in neutron star mergers and quantify their specific impact. We discuss the thermal behavior of hyperonic equations of state~(EoSs) as a distinguishing feature from purely nucleonic models in the remnants of binary mergers using a large set of numerical simulations. Finite temperature enhances the productio

Yohann De Castro, Vincent Duval, Romain Petit

This work is concerned with the recovery of piecewise constant images from noisy linear measurements. We study the noise robustness of a variational reconstruction method, which is based on total (gradient) variation regularization. We show that, if the unknown image is the superposition of a few simple shapes, and if a non-degenerate source condition holds,

Weijian Liang, Xuanmin Cao, Hui Liu, Danning Li

The properties of the pion quasiparticle in hot and dense isospin medium, including the temperature and isospin chemical potential dependence of their screening mass, pole mass and thermal width, as well as their relationships with the pion superfluid phase transition, are investigated in the framework of two-flavor ($N_{f}=2$) soft-wall AdS/QCD models. We e

Nicolás García Trillos, Anna Little, Daniel McKenzie, James M. Murphy

We analyze the convergence properties of Fermat distances, a family of density-driven metrics defined on Riemannian manifolds with an associated probability measure. Fermat distances may be defined either on discrete samples from the underlying measure, in which case they are random, or in the continuum setting, in which they are induced by geodesics under a

Gabriele Di Ubaldo, Eric Perlmutter

We introduce a framework for quantifying random matrix behavior of 2d CFTs and AdS$_3$ quantum gravity. We present a 2d CFT trace formula, precisely analogous to the Gutzwiller trace formula for chaotic quantum systems, which originates from the $SL(2,\mathbb{Z})$ spectral decomposition of the Virasoro primary density of states. An analogy to Berry's diagona

Cassio G. Lopes, Vítor H. Nascimento, Luiz F. O. Chamon

Adaptive networks (ANs) are effective real time techniques to process and track events observed by sensor networks and, more recently, to equip Internet of Things (IoT) applications. ANs operate over nodes equipped with collaborative adaptive filters that solve distributively an estimation problem common to the whole network. However, they do not guarantee t

Giulia L. Celora, Ralf Blossey, Andreas Münch, Barbara Wagner

We study phase equilibria in a minimal model of charge-regulated polymer solutions. Our model consists of a single polymer species whose charge state arises from protonation-deprotonation processes in the presence of a dissolved acid, whose anions serve as screening counterions. We explicitly account for variability in the polymers' charge states. Homogeneou

Zhongliang Jiang, Yuan Bi, Mingchuan Zhou, Ying Hu

Ultrasound (US) imaging is widely used for biometric measurement and diagnosis of internal organs due to the advantages of being real-time and radiation-free. However, due to inter-operator variations, resulting images highly depend on the experience of sonographers. This work proposes an intelligent robotic sonographer to autonomously "explore" target anato

Owen Howell, David Klee, Ondrej Biza, Linfeng Zhao

Learning about the three-dimensional world from two-dimensional images is a fundamental problem in computer vision. An ideal neural network architecture for such tasks would leverage the fact that objects can be rotated and translated in three dimensions to make predictions about novel images. However, imposing SO(3)-equivariance on two-dimensional inputs is

Ishfaq Ahmad Rather, Grigoris Panotopoulos, Ilídio Lopes

We investigate the peculiar nature of strange stars through an analysis of different quark models, i.e. vBag model and CFL model equation of states at different parameter sets, and focus on understanding the equation of state governing the intriguing central compact object (CCO) within the supernova remnant HESS J1731-347, with a mass and radius of $M = 0.77

Siting Xu, Yolo Yunlong Tang, Feng Zheng

Launchpad is a musical instrument that allows users to create and perform music by pressing illuminated buttons. To assist and inspire the design of the Launchpad light effect, and provide a more accessible approach for beginners to create music visualization with this instrument, we proposed the LaunchpadGPT model to generate music visualization designs on

Juergen Mimkes

Peace means order, and war brings disorder and chaos to any society. But order and disorder are not only observed in wars, in many systems they are the dominant property. Understanding order and disorder enables us to understand the structure of systems. Order and disorder are also part of the Lagrange Principle, and as statistics is valid in all systems, we

Daniel Jardon Alvarez, Tahel Malka, Johan van Tol, Yishay Feldman

The magnetic interactions between the spin of an unpaired electron and the surrounding nuclear spins can be exploited to gain structural information, to reduce nuclear relaxation times as well as to create nuclear hyperpolarization via dynamic nuclear polarization (DNP). A central aspect that determines how these interactions manifest from the point of view

Gijs van Cuyck, Lars van Arragon, Jan Tretmans

Model-based testing (MBT) promises a scalable solution to testing large systems, if a model is available. Creating these models for large systems, however, has proven to be difficult. Composing larger models from smaller ones could solve this, but our current MBT conformance relation $\textbf{uioco}$ is not compositional, i.e. correctly tested components, wh

João Henrique Andrade, Juncheng Wei, Zikai Ye

This manuscript is devoted to constructing complete metrics with constant higher fractional curvature on punctured spheres with finitely many isolated singularities. Analytically, this problem is reduced to constructing singular solutions for a conformally invariant integro-differential equation that generalizes the critical GJMS problem. Our proof follows t

Chuanbo Hu, Bin Liu, Xin Li, Yanfang Ye

Social media platforms such as Instagram and Twitter have emerged as critical channels for drug marketing and illegal sale. Detecting and labeling online illicit drug trafficking activities becomes important in addressing this issue. However, the effectiveness of conventional supervised learning methods in detecting drug trafficking heavily relies on having

Dianye Huang, Yuan Bi, Nassir Navab, Zhongliang Jiang

Ultrasound (US) imaging is widely used for diagnosing and monitoring arterial diseases, mainly due to the advantages of being non-invasive, radiation-free, and real-time. In order to provide additional information to assist clinicians in diagnosis, the tubular structures are often segmented from US images. To improve the artery segmentation accuracy and stab

Sinem Getir Yaman, Ana Cavalcanti, Radu Calinescu, Colin Paterson

Autonomous agents are increasingly being proposed for use in healthcare, assistive care, education, and other applications governed by complex human-centric norms. To ensure compliance with these norms, the rules they induce need to be unambiguously defined, checked for consistency, and used to verify the agent. In this paper, we introduce a framework for fo

Hiroshi Iritani, Yuki Koto

We construct an I-function of the projective bundle P(V) associated with a not necessarily split vector bundle V\to B as a Fourier transform of the S^1-equivariant J-function of the total space of V and show that it lies on the Givental Lagrangian cone of P(V). Using this result, we show that the quantum cohomology D-module of P(V) splits into the direct sum

Wes Hellwig, Xian Shi, William A. Sirignano

A recent rotational flamelet model is developed and tested with an improved framework of detailed chemistry and transport. The rotational flamelet model incorporates the effects of shear strain and vorticity on local flame behavior and is three-dimensional by nature. A similarity solution reduces the three-dimensional governing equations to ODEs involving a

Martin Bertran, Shuai Tang, Michael Kearns, Jamie Morgenstern

Membership inference attacks are designed to determine, using black box access to trained models, whether a particular example was used in training or not. Membership inference can be formalized as a hypothesis testing problem. The most effective existing attacks estimate the distribution of some test statistic (usually the model's confidence on the true lab

Jiong Liu, M. Dashti Moghaddam, R. A. Serota

We undertake a systematic study of historic market volatility spanning roughly five preceding decades. We focus specifically on the time series of realized volatility (RV) of the S&P500 index and its distribution function. As expected, the largest values of RV coincide with the largest economic upheavals of the period: Savings and Loan Crisis, Tech Bubble, F

Sevda Esen, Arthur Marius Hennequin, Michel De Cian

Starting in 2022, the upgraded LHCb detector will collect data with a pure software trigger. In its first stage, reducing the rate from 30MHz to about 1MHz, GPUs are used to reconstruct and trigger on B and D meson topologies and high-pT objects in the event. In its second stage, a CPU farm is used to reconstruct the full event and perform candidate selectio

Likun Zhang, Mark D. Risser, Michael F. Wehner, Travis A. O'Brien

In late June, 2021, a devastating heatwave affected the US Pacific Northwest and western Canada, breaking numerous all-time temperature records by large margins and directly causing hundreds of fatalities. The observed 2021 daily maximum temperature across much of the U.S. Pacific Northwest exceeded upper bound estimates obtained from single-station temperat

Wangjunting Xue, Jia-Shu Niu, Hui-Fang Xue, Sijing Yin

In this work, the pulsation analysis is performed on 83 high-amplitude $\delta$ Scuti stars, which have been observed by the Transiting Exoplanet Survey Satellite (TESS). The results show that 49 of these HADS show single-mode pulsation, 27 of them show radial double-modes pulsation (in which 22 of them pulsate with the fundamental and first overtone modes a

Varun Shankar, Dibyajyoti Chakraborty, Venkatasubramanian Viswanathan, Romit Maulik

Deep learning is increasingly becoming a promising pathway to improving the accuracy of sub-grid scale (SGS) turbulence closure models for large eddy simulations (LES). We leverage the concept of differentiable turbulence, whereby an end-to-end differentiable solver is used in combination with physics-inspired choices of deep learning architectures to learn

Joe Stubbs, Smruti Padhy, Richard Cardone, Steven Black

Users increasingly create, manage and share digital resources, including sensitive data, via cloud platforms and APIs. Platforms encode the rules governing access to these resources, referred to as \textit{security policies}, using different systems and semantics. As the number of resources and rules grows, the challenge of reasoning about them collectively

David Boyd

SW Sex stars are an informal sub-class of eclipsing nova-like cataclysmic variables. We report 934 new eclipse times measured over the past 17 years for HS 0728+6738 (V482 Cam), SW Sex, DW UMa, HS 0129+2933 (TT Tri), V1315 Aql, PX And, HS 0455+8315, HS 0220+0603, BP Lyn, BH Lyn, LX Ser, UU Aqr, V1776 Cyg, RW Tri, 1RXS J064434.5+334451, AC Cnc, V363 Aur, and

Elliot M. Lynch, Guillaume Laibe

Spherical flows are a classic problem in astrophysics which are typically studied from a global perspective. However, much like with accretion discs, there are likely many instabilities and small scale phenomena which would be easier to study from a local perspective. For this purpose, we develop a local model for a spherically contracting/expanding gas clou

Takahiro Mimori, Michiaki Hamada

Phylogenetic inference, grounded in molecular evolution models, is essential for understanding the evolutionary relationships in biological data. Accounting for the uncertainty of phylogenetic tree variables, which include tree topologies and evolutionary distances on branches, is crucial for accurately inferring species relationships from molecular data and

Silvestro Fassari, Manuel Gadella, Luis-Miguel Nieto, Fabio Rinaldi

The objective of the present paper is the study of a one-dimensional Hamiltonian with the interaction term given by the sum of two nonlocal attractive $\delta'$-interactions of equal strength and symmetrically located with respect to the origin. We use the procedure known as {\it renormalisation of the coupling constant} in order to rigorously achieve a self

Paul Sánchez, Karen E. Daniels, Heinrich Jaeger, Troy Shinbrot

Granular media are soft matter systems that exhibit some of the extreme behavior of complex fluids. Understanding of the natural formation of planetary bodies, landing on and exploring them, future engineering of structures beyond Earth and planetary defense all hinge on the ability to predict the complex mechanical behavior of granular matter. As we underst

Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic

We present simulation-free score and flow matching ([SF]$^2$M), a simulation-free objective for inferring stochastic dynamics given unpaired samples drawn from arbitrary source and target distributions. Our method generalizes both the score-matching loss used in the training of diffusion models and the recently proposed flow matching loss used in the trainin

Farnik Nikakhtar, Nikhil Padmanabhan, Bruno Lévy, Ravi K. Sheth

Recent research has emphasized the benefits of accurately reconstructing the initial Lagrangian positions of biased tracers from their positions at a later time, to gain cosmological information. A weighted semi-discrete optimal transport algorithm can achieve the required accuracy, provided the late-time positions are known, with minimal information about t

Shao-Zhen Lin, Rishita Changede, Michael P. Sheetz, Jacques Prost

Cell adhesion proteins are transmembrane proteins that bind cells to their environment. These proteins typically cluster into disk-shaped or linear structures. Here we show that such clustering patterns spontaneously emerge when the protein sense the membrane deformation gradient, for example by reaching a lower-energy conformation when the membrane is tilte

Simranjeet Singh, Chandan Kumar Jha, Ankit Bende, Phrangboklang Lyngton Thangkhiew

Memristor-based logic-in-memory (LiM) has become popular as a means to overcome the von Neumann bottleneck in traditional data-intensive computing. Recently, the memristor-aided logic (MAGIC) design style has gained immense traction for LiM due to its simplicity. However, understanding the energy distribution during the design of logic operations within the

Min Yu, Jie Zhang, Arndt Joedicke, Tom Reddyhoff

Electrical contact resistance or capacitance as measured between a lubricated contact has been used in tribometers, partially reflecting the lubrication condition. In contrast, the electrical impedance provides rich information of magnitude and phase, which can be interpreted using equivalent circuit models, enabling more comprehensive measurements, includin

Ethan Gotlieb Wilcox, Tiago Pimentel, Clara Meister, Ryan Cotterell

A fundamental result in psycholinguistics is that less predictable words take a longer time to process. One theoretical explanation for this finding is Surprisal Theory (Hale, 2001; Levy, 2008), which quantifies a word's predictability as its surprisal, i.e. its negative log-probability given a context. While evidence supporting the predictions of Surprisal

Alexandre Lecestre

We observe n possibly dependent random variables, the distribution of which is presumed to be stationary even though this might not be true, and we aim at estimating the stationary distribution. We establish a non-asymptotic deviation bound for the Hellinger distance between the target distribution and our estimator. If the dependence within the observations

Shuang Liang, Xi Sisi Shen, Kevin Smith

We prove local Calabi and higher order estimates for solutions to the continuity equation introduced by La Nave-Tian and extended to Hermitian metrics by Sherman-Weinkove. We apply the estimates to show that on a compact complex manifold the Chern scalar curvature of a solution must blow up at a finite-time singularity. Additionally, starting from certain cl

Haihao Lu, Jinwen Yang

We study the convergence behaviors of primal-dual hybrid gradient (PDHG) for solving linear programming (LP). PDHG is the base algorithm of a new general-purpose first-order method LP solver, PDLP, which aims to scale up LP by taking advantage of modern computing architectures. Despite its numerical success, the theoretical understanding of PDHG for LP is st

A Aberfelds, A Bartkiewicz, M Szymczak, J Šteinbergs

{The variability study of 6.7\,GHz methanol masers has become a useful way to improve our understanding of the physical conditions in high-mass star-forming regions.} {Based on the single-dish monitoring using the Irbene telescopes, we selected three sources with close sky positions.} {We imaged them using the European Very Long Baseline Interferometer Netwo

Baoru Huang, Yicheng Hu, Anh Nguyen, Stamatia Giannarou

In surgical oncology, it is challenging for surgeons to identify lymph nodes and completely resect cancer even with pre-operative imaging systems like PET and CT, because of the lack of reliable intraoperative visualization tools. Endoscopic radio-guided cancer detection and resection has recently been evaluated whereby a novel tethered laparoscopic gamma de

H. -H. Wang, J. Takata, L. C. -C. Lin, P. -H. T. Tam

We investigate the high energy emission activities of two bright gamma-ray pulsars, PSR~J2021+4026 and Vela. For PSR~J2021+4026, the state changes in the gamma-ray flux and spin-down rate have been observed. We report that the long-term evolution of the gamma-ray flux and timing behavior of PSR~J2021+4026 suggests a new gamma-ray flux recovery at around MJD~

Zijing Zhao, Junzhe Kang, Ashwin Tunga, Hojoon Ryu

As a promising alternative to the Von Neumann architecture, in-memory computing holds the promise of delivering high computing capacity while consuming low power. Content addressable memory (CAM) can implement pattern matching and distance measurement in memory with massive parallelism, making them highly desirable for data-intensive applications. In this pa

Tomasz Radożycki

In this work, the paraxial approximation of the free Dirac equation is examined. The results are first obtained by constructing superpositions of exact solutions with suitable profiles, which are borrowed from paraxial optics. In this manner, the paraxial Dirac beams are obtained in four cases: as Gaussian, Bessel-Gaussian, modified Bessel-Gaussian and elega

Annie Xie, Lisa Lee, Ted Xiao, Chelsea Finn

What makes generalization hard for imitation learning in visual robotic manipulation? This question is difficult to approach at face value, but the environment from the perspective of a robot can often be decomposed into enumerable factors of variation, such as the lighting conditions or the placement of the camera. Empirically, generalization to some of the

Aitor Calvo-Fernández, María Blanco-Rey, Asier Eiguren

The numerical renormalization group (NRG) has been widely used as a magnetic impurity solver since the pioneering works by Wilson. Over the past decades, a significant attention has been focused on the application of symmetries in order to reduce the computational cost of the calculations and to improve their accuracy. In particular, a notable progress has b

Dianzhen Cui, X. X. Yi

Finding a feasible protocol for probing the quantum nature of gravity has been attracting an increasing amount of attention. In this manuscript, we propose a protocol to enhance the detection of gravitationally induced entanglement by exploiting the two-phonon drive in a hybrid quantum setup. We consider the setup consisting of a test particle in a double-we

Tomasz Radożycki

An explicit formula for a new type of beams, which in this work are called the "special" hyperbolic Bessel-Gaussian (SHBG) beams, has been derived, using the method of the Hankel transform formulated in our previous work. The fundamental properties of these beams are analyzed. The parameters that define the beam shape have been identified and related to thos

Felipe Espreafico, Johannes Walcher

In recent years, a version of enumerative geometry over arbitrary fields has been developed and studied by Kass-Wickelgren, Levine, and others, in which the counts obtained are not integers but quadratic forms. Aiming to understand the relation to other "refined invariants", and especially their possible interpretation in quantum theory, we explain how to ob

Sinuhé Perea-Puente, Francisco J. Rodríguez-Fortuño

Metasurfaces with linear phase gradients can redirect light beams. We propose controlling both phase and amplitude of a metasurface to extend Snell's law to the realm of complex angles, enabling a non-decaying transmission through opaque media with complex refractive indices. This leads to the discovery of non-diffracting and non-decaying solutions to the wa

Junjun Xu

The Haldane phase with local SU(3) adjoint representation constitutes the simplest non-trivial symmetry-protected topological phases in the SU($N>2$) Heisenberg spin chains. In this paper, we propose to realize this phase by a two-species spinor Bose gas, with each species labeling the quark or antiquark states of SU(3) symmetry. In the strong-coupling limit

Paola Inverardi, Patrizio Migliarini, Massimiliano Palmiero

In the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people's decisions when facing with privacy and security trade-offs, the pressing and time consuming disincentives that influence those decisions, and methods to mitigate them. This work aims to present a syst

Tomasz Radożycki

Various superpositions of Bessel-Gaussian beams and modified Bessel Gaussian beams are considered. Two selected parameters characterizing these beams, with respect to which the superpositions are constructed, are the topological index $n$ associated with the orbital angular momentum carried by the beam, and $\chi$ related to the dilation of the beam. It is s

Sina Zare Pakzad, Mohammad Nasr Esfahani, B. Erdem Alaca

Silicon nanowires have attracted considerable interest due to their wide-ranging applications in nanoelectromechanical systems and nanoelectronics. Molecular dynamics simulations are powerful tools for studying the mechanical properties of nanowires. However, these simulations encounter challenges in interpreting the mechanical behavior and brittle to ductil

José Álamos, Thomas Schmidt, Matthias Waehlisch

Long range wireless transmission techniques such as LoRa are preferential candidates for a substantial class of IoT applications, as they avoid the complexity of multi-hop wireless forwarding. The existing network solutions for LoRa, however, are not suitable for peer-to-peer communication, which is a key requirement for many IoT applications. In this work,

Tim Böhnlein, Simone Ciani, Moritz Egert

Given an elliptic operator $L= - \mathrm{div} (A \nabla \cdot)$ subject to mixed boundary conditions on an open subset of $\mathbb{R}^d$, we study the relation between Gaussian pointwise estimates for the kernel of the associated heat semigroup, H\"older continuity of $L$-harmonic functions and the growth of the Dirichlet energy. To this end, we generalize a

Bhan Lam, Julia Chieng, Kenneth Ooi, Zhen-Ting Ong

Despite being neighbouring countries and sharing the language of Bahasa Melayu (ISO 639-3:ZSM), cultural and language education policy differences between Singapore and Malaysia led to differences in the translation of the "annoying" perceived affective quality (PAQ) attribute from English (ISO 639-3:ENG) to ZSM. This study expands upon the translation of th

Hridoy Debnath, Pavel Fileviez Perez

We discuss a class of theories for Majorana neutrinos where the total lepton number is a local gauge symmetry. These theories predict a dark matter candidate from anomaly cancellation. We discuss the properties of the dark matter candidate and using the cosmological bounds, we obtain the upper bound on the lepton number symmetry breaking scale. The dark matt

Tom Liu, Stephen Roberts, Stefan Zohren

We introduce Deep Inception Networks (DINs), a family of Deep Learning models that provide a general framework for end-to-end systematic trading strategies. DINs extract time series (TS) and cross sectional (CS) features directly from daily price returns. This removes the need for handcrafted features, and allows the model to learn from TS and CS information

S. Magalí López Cortez, Cassandra L. Jacobs

Time pressure and topic negotiation may impose constraints on how people leverage discourse relations (DRs) in spontaneous conversational contexts. In this work, we adapt a system of DRs for written language to spontaneous dialogue using crowdsourced annotations from novice annotators. We then test whether discourse relations are used differently across seve

M. E. Ortega, N. C. Martinez, S. Paron, A. Marinelli

We present a comprehensive physical and chemical study of the fragmentation and star formation activity towards the massive clump AGAL G338.9188+0.5494 harbouring the extended green object EGO 338.92+0.55(b). The presence of an EGO embedded in a massive clump, suggests, at clump scale, that high-mass star formation is occurring. The main goal of this work is

J. Bayron Orjuela-Quintana, Savvas Nesseris, Domenico Sapone

The matter power spectrum $P(k)$ is one of the main quantities connecting observational and theoretical cosmology. Although for a fixed redshift this can be numerically computed very efficiently by Boltzmann solvers, an analytical description is always desirable. However, accurate fitting functions for $P(k)$ are only available for the concordance model. Tak

Yi Zhao, Abhirup Datta, Bohao Tang, Vadim Zipunnikov

In this study, a density-on-density regression model is introduced, where the association between densities is elucidated via a warping function. The proposed model has the advantage of a being straightforward demonstration of how one density transforms into another. Using the Riemannian representation of density functions, which is the square-root function