April 2023 arXiv papers — page 117

Dario Cordero-Erausquin, Alexandros Eskenazis

Let $\mathscr{C}_n=\{-1,1\}^n$ be the discrete hypercube equipped with the uniform probability measure $\sigma_n$. We prove that if $(E,\|\cdot\|_E)$ is a Banach space of finite cotype and $p\in[1,\infty)$, then every function $f:\mathscr{C}_n\to E$ satisfies the dimension-free vector-valued $L_p$ logarithmic Sobolev inequality $$\|f-\mathbb{E} f\|_{L_p(\log

Nikolas Michael, Mihai Cucuringu, Sam Howison

We introduce OFTER, a time series forecasting pipeline tailored for mid-sized multivariate time series. OFTER utilizes the non-parametric models of k-nearest neighbors and Generalized Regression Neural Networks, integrated with a dimensionality reduction component. To circumvent the curse of dimensionality, we employ a weighted norm based on a modified versi

Huan Huang

This paper discusses the properties the spaces of fuzzy sets in a metric space equipped with the endograph metric and the sendograph metric, respectively. We first give some relations among the endograph metric, the sendograph metric and the $\Gamma$-convergence, and then investigate the level characterizations of the endograph metric and the $\Gamma$-conver

Stuart E. Harper, Adam Barr, C. Dickinson, M. W. Peel

The Andromeda galaxy (M31) is our closest neighbouring spiral galaxy, making it an ideal target for studying the physics of the interstellar medium in a galaxy very similar to our own. Using new observations of M31 at 4.76GHz by the C-Band All-Sky Survey (C-BASS), and all available radio data at $1^\circ$ resolution, we produce the integrated spectrum and pu

David Dahlbom, Hao Zhang, Zoha Laraib, Daniel M. Pajerowski

We derive a renormalized classical spin (RCS) theory for $S > 1/2$ quantum magnets by constraining a generalized classical theory that includes all multipolar fluctuations to a reduced CP$^1$ phase space of dipolar SU($2$) coherent states. When the spin Hamiltonian $\hat{\cal{H}}^{S}$ is linear in the spin operators $\hat{\boldsymbol{S}}_j$ for each lattice

Gabriel Avanzi Ubiali, Taufik Abrao, Jose Carlos Marinello

The main requirements for 5G and beyond connectivity include a uniform high quality of service, which can be attained in crowded scenarios by extra-large MIMO (XL-MIMO) systems. Another requirement is to support increasing connected users in (over)crowded machine-type communication (mMTC). In such scenarios, pilot assignment (PA) becomes paramount to reduce

Baosheng Zhang

Loop Closure Detection (LCD) is an essential component of visual simultaneous localization and mapping (SLAM) systems. It enables the recognition of previously visited scenes to eliminate pose and map estimate drifts arising from long-term exploration. However, current appearance-based LCD methods face significant challenges, including high computational cos

Cheongho Han, Chung-Uk Lee, Weicheng Zang, Youn Kil Jung

We inspect 4 microlensing events KMT-2021-BLG-1968, KMT-2021-BLG-2010, KMT-2022-BLG-0371, and KMT-2022-BLG-1013, for which the light curves exhibit partially covered short-term central anomalies. We conduct detailed analyses of the events with the aim of revealing the nature of the anomalies. We test various models that can give rise to the anomalies of the

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Arik

Selective prediction aims to learn a reliable model that abstains from making predictions when uncertain. These predictions can then be deferred to humans for further evaluation. As an everlasting challenge for machine learning, in many real-world scenarios, the distribution of test data is different from the training data. This results in more inaccurate pr

Qiucheng Wu, Yujian Liu, Handong Zhao, Trung Bui

Diffusion-based models have achieved state-of-the-art performance on text-to-image synthesis tasks. However, one critical limitation of these models is the low fidelity of generated images with respect to the text description, such as missing objects, mismatched attributes, and mislocated objects. One key reason for such inconsistencies is the inaccurate cro

Liu Liu, Shubham Kumar, Simon Thomann, Yogesh Singh Chauhan

Ternary content addressable memory (TCAM), widely used in network routers and high-associativity caches, is gaining popularity in machine learning and data-analytic applications. Ferroelectric FETs (FeFETs) are a promising candidate for implementing TCAM owing to their high ON/OFF ratio, non-volatility, and CMOS compatibility. However, conventional single-ga

Sridhar Sola, Darshan Gera

Facial expression recognition (FER) algorithms work well in constrained environments with little or no occlusion of the face. However, real-world face occlusion is prevalent, most notably with the need to use a face mask in the current Covid-19 scenario. While there are works on the problem of occlusion in FER, little has been done before on the particular f

Christopher Beckham, Christopher Pal

In this work we theoretically show that conservative objective models (COMs) for offline model-based optimisation (MBO) are a special kind of contrastive divergence-based energy model, one where the energy function represents both the unconditional probability of the input and the conditional probability of the reward variable. While the initial formulation

Li Hua Yu

We present a set of exact system solutions to a model we developed to study wave function collapse in the quantum spin measurement process. Specifically, we calculated the wave function evolution for a simple harmonic oscillator of spin \frac{1}{2}, with its magnetic moment in interaction with a magnetic field, coupled to an environment that is a bath of har

Yiyuan Yang, Rongshang Li, Qiquan Shi, Xijun Li

Data prefetching is important for storage system optimization and access performance improvement. Traditional prefetchers work well for mining access patterns of sequential logical block address (LBA) but cannot handle complex non-sequential patterns that commonly exist in real-world applications. The state-of-the-art (SOTA) learning-based prefetchers cover

Yi-Hao Chen, Sebastian Heinz, Eric Hooper

The propagation of active galactic nucleus jets depends both on the environment into which they propagate and on their internal structure. To test the impact that different magnetic topologies have on the observable properties of radio galaxies on kpc scales, we conducted a series of magneto-hydrodynamic simulations of jets injected with different magnetic f

Wilson de Souza Junior, Taufik Abrao

We investigate the downlink outage performance of double-RIS-aided non-orthogonal multiple access (NOMA), where a near-BS and a near-users RISs setup are deployed. To extend the coverage to 360 degrees, we deploy a simultaneously transmitting and reflecting RIS (STAR-RIS) structure to improve communication reliability for indoor and outdoor users. New channe

Victor Pacheco-Peña, Yasaman Kiasat, Diego M. Solís, Brian Edwards

We introduce a mechanism that can both hold and amplify electromagnetic waves by rapidly changing the permittivity of the medium during the wave travel from a positive to a dispersionless (i.e. non-Foster) negative value and then back again. The underlying physics behind this phenomenon is theoretically explored by considering a plane wave in an unbounded me

Cecilia Aguerrebere, Ishwar Bhati, Mark Hildebrand, Mariano Tepper

Nowadays, data is represented by vectors. Retrieving those vectors, among millions and billions, that are similar to a given query is a ubiquitous problem, known as similarity search, of relevance for a wide range of applications. Graph-based indices are currently the best performing techniques for billion-scale similarity search. However, their random-acces

Nacira Allaoua, Rezki Chemlal

We show that the set of strictly temporally periodic points of cellular automata with almost equicontinuous points is dense in the topological support of the measure. This extends a result of Lena, Margara and Dennunzio about the density of the set of strictly temporally periodic of cellular automata with equicontinuous points.

Songyuan Cui, Yashraj Bhosale, Mattia Gazzola

Viscous streaming is an efficient rectification mechanism to exploit flow inertia at small scales for fluid and particle manipulation. It typically entails a fluid vibrating around an immersed solid feature that, by concentrating stresses, modulates the emergence of steady flows of useful topology. Motivated by its relevance in biological and artificial sett

Casandra Rusti, Anna Leschanowsky, Carolyn Quinlan, Michaela Pnacek

Speaker recognition is a widely used voice-based biometric technology with applications in various industries, including banking, education, recruitment, immigration, law enforcement, healthcare, and well-being. However, while dataset evaluations and audits have improved data practices in face recognition and other computer vision tasks, the data practices i

Zifeng Wang, Cao Xiao, Jimeng Sun

Clinical trials are essential to drug development but time-consuming, costly, and prone to failure. Accurate trial outcome prediction based on historical trial data promises better trial investment decisions and more trial success. Existing trial outcome prediction models were not designed to model the relations among similar trials, capture the progression

El-Mehdi Mehiri

Consider the restricted Hanoi graphs which correspond to the variants of the famous Tower of Hanoi problem with multiple pegs where moves of the discs are restricted throughout the arcs of a movement digraph whose vertices represent the pegs of the puzzle and an arc from vertex $p$ to vertex $q$ exists if and only if moves from peg $p$ to peg $q$ are allowed

Thiago Augusto Bruza Alves, Taufik Abrao

The extra-large multiple-input multiple-output (XL-MIMO) architecture has been recognized as a technology for supporting the massive MTC (mMTC), providing very high-data rates in high-user density scenarios. However, the large dimension of the array increases the Rayleigh distance (dRayl), in addition to obstacles and scatters causing spatial non-stationarit

Bryn Barker, John B. Bell, Alejandro L. Garcia

The Rayleigh-Plateau instability occurs when surface tension makes a fluid column become unstable to small perturbations. At nanometer scales, thermal fluctuations are comparable to surface energy densities. Consequently, at these scales, thermal fluctuations play a significant role in the dynamics of the instability. These microscopic effects have previousl

Kevin Cao, Kevin Leach

Compiled binary executables are often the only available artifact in reverse engineering, malware analysis, and software systems maintenance. Unfortunately, the lack of semantic information like variable types makes comprehending binaries difficult. In efforts to improve the comprehensibility of binaries, researchers have recently used machine learning techn

Sacha Morin, Robin Legault, Félix Laliberté, Zsuzsa Bakk

StepMix is an open-source Python package for the pseudo-likelihood estimation (one-, two- and three-step approaches) of generalized finite mixture models (latent profile and latent class analysis) with external variables (covariates and distal outcomes). In many applications in social sciences, the main objective is not only to cluster individuals into laten

Ryan Yen, Li Feng, Brinda Mehra, Ching Christie Pang

Live streaming platforms and existing viewer participation tools enable users to interact and engage with an online community, but the anonymity and scale of chat usually result in the spread of negative comments. However, only a few existing moderation tools investigate the influence of proactive moderation on viewers' engagement and prosocial behavior. To

Toshiyasu Arai

In the lecture notes it is shown that an ordinal $\psi_{\Omega}(\varepsilon_{\mathbb{S}^{+}+1})$ is an upper bound for the proof-theoretic ordinal of a set theory ${\sf KP}\omega+(M\prec_{\Sigma_{1}}V)$. In this note we show that ${\sf KP}\omega+(M\prec_{\Sigma_{1}}V)$ proves the well-foundedness up to $\psi_{\Omega}(\omega_{n}(\mathbb{S}^{+}+1))$ for each $

Alexander Madurowicz, Sagnick Mukherjee, Natasha Batalha, Bruce Macintosh

We reanalyze near-infrared spectra of the young extrasolar giant planet 51 Eridani b which was originally presented in (Macintosh et al. 2015) and (Rajan et al. 2017) using modern atmospheric models which include a self-consistent treatment of disequilibrium chemistry due to turbulent vertical mixing. In addition, we investigate the possibility that signific

Prithvi Akella, Apurva Badithela, Richard M. Murray, Aaron D. Ames

Control Barrier Functions (CBFs) allow for efficient synthesis of controllers to maintain desired invariant properties of safety-critical systems. However, the problem of identifying a CBF remains an open question. As such, this paper provides a constructive method for control barrier function synthesis around one expert demonstration that realizes a desired

Yu-Min Jeon, Won-Mu Heo, Jong-Min Kim, Kyounggon Kim

The crime of illegally filming and distributing images or videos worldwide is increasing day by day. With the increasing penetration rate of smartphones, there has been a rise in crimes involving secretly taking pictures of people's bodies and distributing them through messengers. However, little research has been done on these related issue. The crime of di

Milad Sikaroudi, Mehdi Afshari, Abubakr Shafique, Shivam Kalra

Chen et al. [Chen2022] recently published the article 'Fast and scalable search of whole-slide images via self-supervised deep learning' in Nature Biomedical Engineering. The authors call their method 'self-supervised image search for histology', short SISH. We express our concerns that SISH is an incremental modification of Yottixel, has used MinMax binariz

Wayne Polyzou

Light-front formulations of quantum field theories have many advantages for computing electroweak matrix elements of strongly interacting systems and other quantities that are used to study hadronic structure. The theory can be formulated in Hamiltonian form so non-perturbative calculations of the strongly interacting initial and final states are in principl

Alonso S. Castellanos, Erik A. R. Mendoza, Guilherme Tizziotti

In this work, we provide a way to completely determine the set of pure gaps $G_0(P_1, P_2)$ at two rational places $P_1, P_2$ in a function field $F$ over a finite field $\mathbb{F}_q$, and its cardinality. Furthermore, we given a bound for the cardinality of the set $G_0(P_1, P_2)$ which is better, in some cases, than the generic bound given by Homma and Ki

GlueX Collaboration, S. Adhikari, F. Afzal, C. S. Akondi

We report the total and differential cross sections for $J/\psi$ photoproduction with the large acceptance GlueX spectrometer for photon beam energies from the threshold at 8.2~GeV up to 11.44~GeV and over the full kinematic range of momentum transfer squared, $t$. Such coverage facilitates the extrapolation of the differential cross sections to the forward

Zhenghang Yuan, Lichao Mou, Xiao Xiang Zhu

Aiming at answering questions based on the content of remotely sensed images, visual question answering for remote sensing data (RSVQA) has attracted much attention nowadays. However, previous works in RSVQA have focused little on the robustness of RSVQA. As we aim to enhance the reliability of RSVQA models, how to learn robust representations against new wo

Ben Prystawski, Michael Y. Li, Noah D. Goodman

Humans have a powerful and mysterious capacity to reason. Working through a set of mental steps enables us to make inferences we would not be capable of making directly even though we get no additional data from the world. Similarly, when large language models generate intermediate steps (a chain of thought) before answering a question, they often produce be

Lorenzo Rovigatti, Francesco Sciortino

Polymer chains decorated with a fraction of monomers capable of forming reversible bonds form transient polymer networks that are important in soft and biological systems. If chains are flexible and the attractive monomers are all of the same species, the network formation occurs continuously as density increases. By contrast, it has been recently shown [L.

Rouzbeh Behnia, Arman Riasi, Reza Ebrahimi, Sherman S. M. Chow

Secure aggregation protocols ensure the privacy of users' data in federated learning by preventing the disclosure of local gradients. Many existing protocols impose significant communication and computational burdens on participants and may not efficiently handle the large update vectors typical of machine learning models. Correspondingly, we present e-SeaFL

Runyu Zhang, Yuyang Zhang, Rohit Konda, Bryce Ferguson

This paper studies the finite-time horizon Markov games where the agents' dynamics are decoupled but the rewards can possibly be coupled across agents. The policy class is restricted to local policies where agents make decisions using their local state. We first introduce the notion of smooth Markov games which extends the smoothness argument for normal form

M. Lampón, M. López-Puertas, J. Sanz-Forcada, S. Czesla

Characterisation of atmospheres undergoing photo-evaporation is key to understanding the formation, evolution, and diversity of planets. However, only a few upper atmospheres that experience this kind of hydrodynamic escape have been characterised. Our aim is to characterise the upper atmospheres of the hot Jupiters HAT-P-32 b and WASP-69 b, the warm sub-Nep

Qi Qi, Shervin Ardeshir

Despite the success of deep-learning models in many tasks, there have been concerns about such models learning shortcuts, and their lack of robustness to irrelevant confounders. When it comes to models directly trained on human faces, a sensitive confounder is that of human identities. Many face-related tasks should ideally be identity-independent, and perfo

Mohammed Ayman Shalaby, Charles Champagne Cossette, Jerome Le Ny, James Richard Forbes

Ultra-wideband (UWB) systems are becoming increasingly popular as a means of inter-robot ranging and communication. A major constraint associated with UWB is that only one pair of UWB transceivers can range at a time to avoid interference, hence hindering the scalability of UWB-based localization. In this paper, a ranging protocol is proposed that allows all

Stephen Roche, Quincy Bayer, Benjamin Carlson, William Ouligian

We present an interpretable implementation of the autoencoding algorithm, used as an anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. Scenarios at the Large Hadron Collider at CERN are considered, for which the autoencoder is trained using known physical processes of the Standard Model. The design is then

András Bátkai

Mathematical modelling and ethics have more touching points than most of us would like to admit. Everyday decisions are often reasoned by mathematical arguments. Mathematics teachers belong to those mathematically literate, who must point out mistakes in public discussions and reflect on them in their teaching to educate students to become critical thinkers.

Enrico Ventura

Ever since the last two decades of the past century pioneering studies in the field of statistical physics had focused their efforts on developing models of neural networks that could display memory storage and retrieval. Though many associative memory models were easy to handle and still quite effective to explain the basic memory retrieval processes in the

Kan Chen, Runzhou Ge, Hang Qiu, Rami AI-Rfou

Widely adopted motion forecasting datasets substitute the observed sensory inputs with higher-level abstractions such as 3D boxes and polylines. These sparse shapes are inferred through annotating the original scenes with perception systems' predictions. Such intermediate representations tie the quality of the motion forecasting models to the performance of

Gautam Salhotra, I-Chun Arthur Liu, Gaurav Sukhatme

Some Learning from Demonstrations (LfD) methods handle small mismatches in the action spaces of the teacher and student. Here we address the case where the teacher's morphology is substantially different from that of the student. Our framework, Morphological Adaptation in Imitation Learning (MAIL), bridges this gap allowing us to train an agent from demonstr

William Gregory, Mitchell Bushuk, Alistair Adcroft, Yongfei Zhang

Data assimilation is often viewed as a framework for correcting short-term error growth in dynamical climate model forecasts. When viewed on the time scales of climate however, these short-term corrections, or analysis increments, can closely mirror the systematic bias patterns of the dynamical model. In this study, we use convolutional neural networks (CNNs

Runyu Zhang, Yang Zheng, Weiyu Li, Na Li

This paper studies the relationship between state feedback policies and disturbance response policies for the standard Linear Quadratic Regulator (LQR). For open-loop stable plants, we establish a simple relationship between the optimal state feedback controller $u_t=K_\star x_t$ and the optimal disturbance response controller $u_t=L^{(H)}_{\star;1}w_{t-1}+\

Aviraj Sinha, Elena R. Henderson, Jessie M. Henderson, Eric C. Larson

Random number generators (RNG) are essential elements in many cryptographic systems. True random number generators (TRNG) rely upon sources of randomness from natural processes such as those arising from quantum mechanics phenomena. We demonstrate that a quantum computer can serve as a high-quality, weakly random source for a generalized user-defined probabi

Jessie M. Henderson, Elena R. Henderson, Aviraj Sinha, Mitchell A. Thornton

Several prominent quantum computing algorithms--including Grover's search algorithm and Shor's algorithm for finding the prime factorization of an integer--employ subcircuits termed 'oracles' that embed a specific instance of a mathematical function into a corresponding bijective function that is then realized as a quantum circuit representation. Designing o

Raphaël Tinarrage, Jean R. Ponciano, Claudio D. G. Linhares, Agma J. M. Traina

Temporal graphs are commonly used to represent complex systems and track the evolution of their constituents over time. Visualizing these graphs is crucial as it allows one to quickly identify anomalies, trends, patterns, and other properties that facilitate better decision-making. In this context, selecting an appropriate temporal resolution is essential fo

Adam Rycerz, Katarzyna Rycerz, Piotr Witkowski

Thermopower and the Lorentz number for an edge-free (Corbino) graphene disk in the quantum Hall regime is calculated within the Landauer-B\"{u}ttiker formalism. We find, by varying the electrochemical potential, that amplitude of the Seebeck coefficient follows a modified Goldsmid-Sharp relation, in which energy gap is identified with the interval between ze

Nicholas S. Conroy, Michi Bauböck, Vedant Dhruv, Daeyoung Lee

The Event Horizon Telescope (EHT) has produced images of M87* and Sagittarius A*, and will soon produce time sequences of images, or movies. In anticipation of this, we describe a technique to measure the rotation rate, or pattern speed $\Omega_p$, from movies using an autocorrelation technique. We validate the technique on Gaussian random field models with

Gabriela Araujo-Pardo, Zhanar Berikkyzy, Linda Lesniak

In this paper, we work with simple and finite graphs. We study a generalization of the \emph{Cage Problem}, which has been widely studied since cages were introduced by Tutte \cite{T47} in 1947 and after Erd\" os and Sachs \cite{ES63} proved their existence in 1963. An \emph{$(r,g)$-graph} is an $r$-regular graph in which the shortest cycle has length equal

Meltem Civas, Murat Kuscu, Oktay Cetinkaya, Beyza E. Ortlek

Internet of Bio-Nano Things (IoBNT) is a transformative communication framework, characterized by heterogeneous networks comprising both biological entities and artificial micro/nano-scale devices, so-called Bio-Nano Things (BNTs), interfaced with conventional communication networks for enabling innovative biomedical and environmental applications. Realizing

Ian May, Dongwook Lee

This paper presents a fully multidimensional kernel-based reconstruction scheme for finite volume methods applied to systems of hyperbolic conservation laws, with a particular emphasis on the compressible Euler equations. Non-oscillatory reconstruction is achieved through an adaptive order weighted essentially non-oscillatory (WENO-AO) method cast into a for

Viktoriia Bilet, Oleksiy Dovgoshey

The group of combinatorial self-similarities of a pseudometric space $(X, d)$ is the maximal subgroup of the symmetric group $\mathbf{Sym} (X)$ whose elements preserve the four-point equality $d(x,y)=d(u,v)$. Let us denote by $\mathcal{IP}$ the class of all pseudometric spaces $(X, d)$ for which every combinatorial self-similarity $\Phi\colon~X~\to~X$ satisf

Bing Huang, Arezou Ghesmati, Yonghong Chen, Ross Baldick

Pumped storage hydro units (PSHU) are great sources of flexibility in power systems. This is especially valuable in modern systems with increasing shares of intermittent renewable resources. However, the flexibility from PSHUs, particularly in the real-time market, has not been thoroughly studied. The storage optimization in a real-time market hasn't been we

Cagin Yunus, William Detmold

Numerical computations in strongly-interacting quantum field theories are often performed using Monte-Carlo sampling methods. A key task in these calculations is to estimate the value of a given physical quantity from the distribution of stochastic samples that are generated using the Monte-Carlo method. Typically, the sample mean and sample variance are use

Erich Bremer, Tammy DiPrima, Joseph Balsamo, Jonas Almeida

Halcyon is a new pathology imaging analysis and feature management system based on W3C linked-data open standards and is designed to scale to support the needs for the voluminous production of features from deep-learning feature pipelines. Halcyon can support multiple users with a web-based UX with access to all user data over a standards-based web API allow

Santanu Das, Arad Nasiri, Yasaman K. Yazdi

We provide a comprehensive discussion of the Everpresent $\Lambda$ cosmological model arising from fundamental principles in causal set theory and unimodular gravity. In this framework the value of the cosmological constant ($\Lambda$) fluctuates, in magnitude and in sign, over cosmic history. At each epoch, $\Lambda$ stays statistically close to the inverse

F. A. Kassan-Ogly, A. V. Zarubin

We study the frustration properties of the Ising model on a decorated triangular lattice with an arbitrary number of decorating spins on all lattice bonds in the framework of an exact analytical approach based on the Kramers--Wannier transfer matrix method. Expressions for the entropy, heat capacity, and spontaneous magnetization of the lattice are obtained,

Z. M. Malkin, V. M. Tissen

Improvement of the prediction accuracy of the Earth's rotation parameters (ERP) is one of the main problems of applied astrometry. In order to solve this problem, various approaches are used and in order to select the best one, comparison of the accuracy of the forecasts obtained by different methods at different analysis centers are often carried out. In su

Sarah Fakhoury, Saikat Chakraborty, Madan Musuvathi, Shuvendu K. Lahiri

Large language models (LLMs), such as OpenAI's Codex, have demonstrated their potential to generate code from natural language descriptions across a wide range of programming tasks. Several benchmarks have recently emerged to evaluate the ability of LLMs to generate functionally correct code from natural language intent with respect to a set of hidden test c

Courtney M. King, Son Tung Do, Juntao Chen

In this work, we study policy poisoning through state manipulation, also known as sensor spoofing, and focus specifically on the case of an agent forming a control policy through batch learning in a linear-quadratic (LQ) system. In this scenario, an attacker aims to trick the learner into implementing a targeted malicious policy by manipulating the batch dat

Zurab Janelidze, Francois van Niekerk

A noetherian form is an abstract self-dual framework suitable for establishing homomorphism theorems (such as the isomorphism theorems and homological diagram lemmas) for group-like structures. In this paper we identify and carry out an axiomatic analysis of a particular class of noetherian forms which exist for both group-like structures and for sheaves. Mo

Annan Yu, Alex Townsend

Large-scale linear, time-invariant (LTI) dynamical systems are widely used to characterize complicated physical phenomena. We propose a two-stage algorithm to reduce the order of a large-scale LTI system given samples of its transfer function for a target degree $k$ of the reduced system. In the first stage, a modified adaptive Antoulas--Anderson (AAA) algor

Yifan Yin, Xu Cheng, Fan Shi, Xiufeng Liu

Accurate and reliable optical remote sensing image-based small-ship detection is crucial for maritime surveillance systems, but existing methods often struggle with balancing detection performance and computational complexity. In this paper, we propose a novel lightweight framework called \textit{HSI-ShipDetectionNet} that is based on high-order spatial inte

Dongxue Du, Laxman Raju Thoutam, Konrad T. Genser, Chenyu Zhang

We examine the effects of Pt vacancies on the magnetotransport properties of Weyl semimetal candidate GdPtSb films, grown by molecular beam epitaxy on c-plane sapphire. Rutherford backscattering spectrometry (RBS) and x-ray diffraction measurements suggest that phase pure GdPt$_{x}$Sb films can accommodate up to $15\%$ Pt vacancies ($x=0.85$), which act as a

Isolde Adler, Noleen Köhler, Pan Peng

We study property testing of properties that are definable in first-order logic (FO) in the bounded-degree graph and relational structure models. We show that any FO property that is defined by a formula with quantifier prefix $\exists^*\forall^*$ is testable (i.e., testable with constant query complexity), while there exists an FO property that is expressib

Akira Horiguchi, Matthew T. Pratola

Shapley effects are a particularly interpretable approach to assessing how a function depends on its various inputs. The existing literature contains various estimators for this class of sensitivity indices in the context of nonparametric regression where the function is observed with noise, but there does not seem to be an estimator that is computationally

Neda Hejazi, Ian Crossfield, Thomas Nordlander, Megan Mansfield

We present the first elemental abundance measurements of the K dwarf (K7V) exoplanet-host star WASP-107 using high-resolution (R = 45,000), near-infrared (H- and K-band) spectra taken from Gemini-S/IGRINS. We use the previously determined physical parameters of the star from the literature and infer the abundances of 15 elements: C, N, O, Na, Mg, Al, Si, K,

John Chiang

In this paper, we present a practical solution to implement privacy-preserving CNN training based on mere Homomorphic Encryption (HE) technique. To our best knowledge, this is the first attempt successfully to crack this nut and no work ever before has achieved this goal. Several techniques combine to accomplish the task:: (1) with transfer learning, privacy

Lev-Arcady Sellem, Rémi Robin, Philippe Campagne-Ibarcq, Pierre Rouchon

We analyze an experimentally accessible Lindblad master equation for a quantum harmonic oscillator. It approximately stabilizes finite-energy periodic grid states called Gottesman-Kitaev-Preskill (GKP) states, that can be used to encode and protect a logical qubit. We give explicit upper bounds for the energy of the solutions of the Lindblad master equation.

Pronoma Banerjee, Manasi V Gude, Rajvi J Sampat, Sharvari M Hedaoo

Machine learning models are often misspecified in the likelihood, which leads to a lack of robustness in the predictions. In this paper, we introduce a framework for correcting likelihood misspecifications in several paradigm agnostic noisy prior models and test the model's ability to remove the misspecification. The "ABC-GAN" framework introduced is a novel

Aniket Sharma, Lia Medeiros, Chi-kwan Chan, Goni Halevi

We introduce Mahakala, a Python-based, modular, radiative ray-tracing code for curved space-times. We employ Google's JAX framework for accelerated automatic differentiation, which can efficiently compute Christoffel symbols directly from the metric, allowing the user to easily and quickly simulate photon trajectories through non-Kerr spacetimes. JAX also en

Raj Kumar Das, Aurindam Mondal, Subir Ghosh, Supriya Pan

A well known extension of Einstein General Relativity is the addition of an $R^2$-term, which is free of ghost excitations and in the linearized framework, reduces Einstein General Relativity and an additional higher derivative scalar. According to \cite{Chakraborty:2020ktp}, the above scalar sector can sustain a Time Crystal-like minimum energy state, with

Jennifer Hu, Roger Levy, Judith Degen, Sebastian Schuster

Scalar inferences (SI) are a signature example of how humans interpret language based on unspoken alternatives. While empirical studies have demonstrated that human SI rates are highly variable -- both within instances of a single scale, and across different scales -- there have been few proposals that quantitatively explain both cross- and within-scale vari

Dariusz Kosz, Bartosz Langowski, Mariusz Mirek, Paweł Plewa

The main goal of the paper is to prove convergence in norm and pointwise almost everywhere on $L^p$, $p\in (1,\infty)$, for certain multiparameter polynomial ergodic averages in the spirit of Dunford and Zygmund for continuous flows. We will pay special attention to quantitative aspects of pointwise convergence phenomena from the point of view of uniform osc

Mukund Telukunta, Venkata Sriram Siddhardh Nadendla

Traditional algorithmic fairness notions rely on label feedback, which can only be elicited from expert critics. However, in most practical applications, several non-expert stakeholders also play a major role in the system and can have distinctive opinions about the decision making philosophy. For example, in kidney placement programs, transplant surgeons ar

Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng

Geometric deep learning enables the encoding of physical symmetries in modeling 3D objects. Despite rapid progress in encoding 3D symmetries into Graph Neural Networks (GNNs), a comprehensive evaluation of the expressiveness of these networks through a local-to-global analysis lacks today. In this paper, we propose a local hierarchy of 3D isomorphism to eval

Chien-Yeah Seng, Mikhail Gorchtein

We propose a new theory framework to study the isospin-symmetry breaking correction $\delta_\text{C}$ in superallowed nuclear beta decays, crucial for the precise determination of $|V_{ud}|$. Based on a general assumptions of the isovector dominance in ISB interactions, we construct a set of functions $F_{T_z}$ which involve nuclear matrix elements of isovec

Walter Zibusiso Ncube, Ahmad Adnan Qidan, Taisir El-Gorashi, Jaafar M. H. Elmirghani

Rising data demands are a growing concern globally. The task at hand is to evolve current communication networks to support enhanced data rates while maintaining low latency, energy consumption and costs. To meet the above challenge, Optical Wireless Communication (OWC) technology is proposed as a solution to complement traditional Radio Frequency (RF) based

Augusto Magalhães, Otacílio B. L. Neto, Francesco Corona

In this work, we consider a differential description of the evolution of the state of a reaction-diffusion system under environmental fluctuations. We are interested in estimating the state of the system when only partial observations are available. To describe how observations and states are related, we combine multiplicative noise-driven dynamics with an o

Vida Saeedzadeh, S. Lyla Jung, Douglas Rennehan, Arif Babul

Using high-resolution {\sc Romulus} simulations, we explore the origin and evolution of the circumgalactic medium (CGM) in the region 0.1 $\leq \mathrm{R}/\mathrm{R}_\mathrm{500} \leq$ 1 around massive central galaxies in group-scale halos. We find that the CGM is multiphase and highly dynamic. Investigating the dynamics, we identify seven patterns of evolut

Julia Mendelsohn, Sayan Ghosh, David Jurgens, Ceren Budak

Social media enables the rapid spread of many kinds of information, from memes to social movements. However, little is known about how information crosses linguistic boundaries. We apply causal inference techniques on the European Twitter network to quantify multilingual users' structural role and communication influence in cross-lingual information exchange

Matthias C. Löbl, Stefano Paesani, Anders S. Sørensen

We develop an architecture for measurement-based quantum computing using photonic quantum emitters. The architecture exploits spin-photon entanglement as resource states and standard Bell measurements of photons for fusing them into a large spin-qubit cluster state. The scheme is tailored to emitters with limited memory capabilities since it only uses an ini

Derek Perera, Liliya L. R. Williams, Claudia Scarlata

In gravitational lensing, central images in quads can serve as a powerful probe of the inner regions of lens galaxies. The presence of an offset central supermassive black hole (SMBH) has the potential to distort the time-delay surface in a way such that 3 central images form: a strongly de-magnified image near the SMBH, and two less de-magnified (and potent

Ulrich K. Beckering Vinckers, Álvaro de la Cruz-Dombriz, Denis Pollney

We construct a numerical relativity code based on the Baumgarte-Shapiro-Shibata-Nakamura (BSSN) formulation for the gravitational quadratic $f(R)$ Starobinsky model. By removing the assumption that the determinant of the conformal 3-metric is unity, we first generalize the BSSN formulation for general $f(R)$ gravity theories in the metric formalism to accomm

Panagiotis Kaklamanos, Andrea Pugliese, Mattia Sensi, Sara Sottile

We propose a compartmental model for a disease with temporary immunity and secondary infections. From our assumptions on the parameters involved in the model, the system naturally evolves in three time scales. We characterize the equilibria of the system and analyze their stability. We find conditions for the existence of two endemic equilibria, for some cas

Yi Qin, Kai Zhang, Linhu Li

The interplay between the non-Hermiticity and dimensionality gives rise to exotic characteristics in higher dimensions, with one representative phenomenon known as the geometry-dependent skin effect (GDSE), which refers to that the localization of extensive eigenstates depends on the system's geometry under open boundary conditions. In this paper, we demonst

K. Hart, B. J. Shappee, D. Hey, C. S. Kochanek

The All-Sky Automated Survey for Supernovae (ASAS-SN) began observing in late-2011 and has been imaging the entire sky with nightly cadence since late 2017. A core goal of ASAS-SN is to release as much useful data as possible to the community. Working towards this goal, in 2017 the first ASAS-SN Sky Patrol was established as a tool for the community to obtai

Alessia Franchini, Alessandro Lupi, Alberto Sesana, Zoltan Haiman

The shrinking of a binary orbit driven by the interaction with a gaseous circumbinary disc, initially advocated as a potential way to catalyze the binary merger, has been recently debated in the case of geometrically thick (i.e. with $H/R\gtrsim 0.1$) discs. However, a clear consensus is still missing mainly owing to numerical limitations, such as fixed orbi

Thomas Bartsch, Mathew Bullimore, Andrea Grigoletto

It is known that local operators in quantum field theory transform in representations of ordinary global symmetry groups. The purpose of this paper is to generalise this statement to extended operators such as line and surface defects. We explain that $(n-1)$-dimensional operators transform in $n$-representations of a finite invertible or group-like symmetry

Ronan Legin, Matthew Ho, Pablo Lemos, Laurence Perreault-Levasseur

Reconstructing the initial conditions of the universe is a key problem in cosmology. Methods based on simulating the forward evolution of the universe have provided a way to infer initial conditions consistent with present-day observations. However, due to the high complexity of the inference problem, these methods either fail to sample a distribution of pos

Nikita A. Nemkov, Evgeniy O. Kiktenko, Aleksey K. Fedorov

The Fourier expansion of the loss function in variational quantum algorithms (VQA) contains a wealth of information, yet is generally hard to access. We focus on the class of variational circuits, where constant gates are Clifford gates and parameterized gates are generated by Pauli operators, which covers most practical cases while allowing much control tha