July 2023 arXiv papers — page 101

Mohamad H. Kazma, Sebastian A. Nugroho, Aleksandar Haber, Ahmad F. Taha

This paper explores the problem of selecting sensor nodes for a general class of nonlinear dynamical networks. In particular, we study the problem by utilizing altered definitions of observability and open-loop lifted observers. The approach is performed by discretizing the system's dynamics using the implicit Runge-Kutta method and by introducing a state-av

Hiroyasu Tsukamoto, Benjamin Rivière, Changrak Choi, Amir Rahmani

The key innovation of our analytical method, CaRT, lies in establishing a new hierarchical, distributed architecture to guarantee the safety and robustness of a given learning-based motion planning policy. First, in a nominal setting, the analytical form of our CaRT safety filter formally ensures safe maneuvers of nonlinear multi-agent systems, optimally wit

Mitchell Black, William Maxwell, Amir Nayyeri

We introduce a new quantum algorithm for computing the Betti numbers of a simplicial complex. In contrast to previous quantum algorithms that work by estimating the eigenvalues of the combinatorial Laplacian, our algorithm is an instance of the generic Incremental Algorithm for computing Betti numbers that incrementally adds simplices to the simplicial compl

Christopher S. Parker, Anna Schroder, Sean C. Epstein, James Cole

Purpose: Previous quantitative MR imaging studies using self-supervised deep learning have reported biased parameter estimates at low SNR. Such systematic errors arise from the choice of Mean Squared Error (MSE) loss function for network training, which is incompatible with Rician-distributed MR magnitude signals. To address this issue, we introduce the nega

Hasan B. Al Ba'ba'a, Mostafa Nouh

Bandgaps, or frequency ranges of forbidden wave propagation, are a hallmark of Phononic Crystals (PnCs). Unlike their lattice counterparts, PnCs taking the form of continuous structures exhibit an infinite number of bandgaps of varying location, bandwidth, and distribution along the frequency spectrum. While these bandgaps are commonly predicted from benchma

Madhuja Layek, In Seok Yang, Zhenghong Dai, Anush Ranka

Using an innovative combination of multi-beam-optical stress-sensor (MOSS) curvature and X-ray diffraction (XRD) techniques, the Young's modulus (E) of polycrystalline MAPbI3 metal-halide perovskite (MHP) thin films attached to Si substrates is estimated to be 10.2 +/- 3.4 GPa. This is comparable to the E of corresponding MAPbI3 single-crystals. This generic

Mason G. MacDougall, Gregory J. Gilbert, Erik A. Petigura

A planet's orbital eccentricity is fundamental to understanding the present dynamical state of a system and is a relic of its formation history. There is high scientific value in measuring eccentricities of Kepler and TESS planets given the sheer size of these samples and the diversity of their planetary systems. However, Kepler and TESS lightcurves typicall

J. -F. Pommaret

According to a quite clever but never acknowledged work of E. Vessiot that won the prize of the Acad\'{e}mie des Sciences in 1904, " Differential Galois Theory " (DGT) has mainly to do with the study of " Principal Homogeneous Spaces " (PHS) for finite groups ( classical Galois theory), algebraic groups (Picard-Vessiot theory) and algebraic pseudogroups (Dra

Will Crichton

This paper explores how design patterns could be revisited in the era of mainstream functional programming languages. I discuss the kinds of knowledge that ought to be represented as functional design patterns: architectural concepts that are relatively self-contained, but whose entirety cannot be represented as a language-level abstraction. I present four c

Indrila Ganguly, Srijan Sengupta, Sujit Ghosh

Residual bootstrap is a classical method for statistical inference in regression settings. With massive data sets becoming increasingly common, there is a demand for computationally efficient alternatives to residual bootstrap. We propose a simple and versatile scalable algorithm called subsampled residual bootstrap (SRB) for generalized linear models (GLMs)

Taehee Ko, Xiantao Li, Chunhao Wang

Density-functional theory (DFT) has revolutionized computer simulations in chemistry and material science. A faithful implementation of the theory requires self-consistent calculations. However, this effort involves repeatedly diagonalizing the Hamiltonian, for which a classical algorithm typically requires a computational complexity that scales cubically wi

Peihao Li, Nadia Dahmani

Large proof of work (PoW) networks allow anyone to earn rewards by running computation-intensive hash puzzles for profit, yet they typically consume electricity comparable to that of medium-sized countries. Repurposing computing resources from hash puzzles to machine learning training can benefit the energy sector as a whole, since this computing power is no

F. Pugliese, M. Brodiano, N. Andrés, P. Dmitruk

Direct numerical simulations of 3D compressible MHD turbulence were performed in order to study the relation between waves modes and coherent structures and the consequent energization of test particles. Moreover, the question of which is the main mechanism of this particle energization is rigorously discussed. In particular, using the same initial condition

Kai Chen, Swadeepan Nanda, Pavan Hosur

Response theories in condensed matter typically describe the response of an electron fluid to external electromagnetic fields, while perturbations on neutral particles are often designed to mimic such fields. Here, we study the response of fermions to a space-time-dependent velocity field, thereby sidestepping the issue of gauge charge. First, we use a semic

Yiren Jian, Chongyang Gao, Soroush Vosoughi

We present a novel methodology aimed at optimizing the application of frozen large language models (LLMs) for resource-intensive vision-language (VL) pre-training. The current paradigm uses visual features as prompts to guide language models, with a focus on determining the most relevant visual features for corresponding text. Our approach diverges by concen

Arnaud Joly, Marco Nicolis, Ekaterina Peterova, Alessandro Lombardi

We present a scalable method to produce high quality emphasis for text-to-speech (TTS) that does not require recordings or annotations. Many TTS models include a phoneme duration model. A simple but effective method to achieve emphasized speech consists in increasing the predicted duration of the emphasised word. We show that this is significantly better tha

Anne-Katherine Burns, Tim M. P. Tait, Mauro Valli

In this work we present PRyMordial: A package dedicated to efficient computations of observables in the Early Universe with the focus on the cosmological era of Big Bang Nucleosynthesis (BBN). The code offers fast and precise evaluation of BBN light-element abundances together with the effective number of relativistic degrees of freedom, including non-instan

Yuanhang Zhang, Jundong Liu

Path planning plays a crucial role in various autonomy applications, and RRT* is one of the leading solutions in this field. In this paper, we propose the utilization of vertex-based networks to enhance the sampling process of RRT*, leading to more efficient path planning. Our approach focuses on critical vertices along the optimal paths, which provide essen

Nadine ACeituno-Moya, Fred Torres-Cruz

This article presents a study that uses multiple linear regression analysis to examine the factors influencing the number of people affiliated with different insurance plans within the Comprehensive Health Insurance (SIS) system in Peru.The study highlights the importance of multiple linear regression analysis in understanding the factors that affect SIS Com

Y. Guan, C. Dutreix, H. Gonzales-Herrero, M. M. Ugeda

Fractional charges are one of the wonders of the fractional quantum Hall effect, a liquid of strongly correlated electrons in a large magnetic field. Fractional excitations are also anticipated in two-dimensional crystals of non-interacting electrons under time-reversal symmetry, as bound states of a rotating bond order known as Kekul\'e vortex. However, the

He Huang, Jagadeesh Balam, Boris Ginsburg

We study speech intent classification and slot filling (SICSF) by proposing to use an encoder pretrained on speech recognition (ASR) to initialize an end-to-end (E2E) Conformer-Transformer model, which achieves the new state-of-the-art results on the SLURP dataset, with 90.14% intent accuracy and 82.27% SLURP-F1. We compare our model with encoders pretrained

Hermann Muhammad, Mohamed Mezouar, Gaston Garbarino, Tomasz Poreba

Hexagonal boron nitride (hBN) and black phosphorus (bP) are crystalline materials that can be seen as ordered stackings of two-dimensional layers, which lead to outstanding anisotropic physical properties. The knowledge of the thermal equations of state of hBN and bP is of great interest in the field of 2D materials for a better understanding of the anisotro

Enrico F. Persico

This paper investigates the relationship between mapping style and device roadmap in Resistive Random Access Memory (ReRAM) architectures for neuromorphic computing. The study leverages simulations using DNN+NeuroSim to evaluate the impact of different parameters on chip performance, including latency, energy consumption, and overall system efficiency. The r

Richard Gall, Deniz Kocanaogullari, Murat Akcakaya, Deniz Erdogmus

In a multi-speaker "cocktail party" scenario, a listener can selectively attend to a speaker of interest. Studies into the human auditory attention network demonstrate cortical entrainment to speech envelopes resulting in highly correlated Electroencephalography (EEG) measurements. Current trends in EEG-based auditory attention detection (AAD) using artifici

J. Zak, D. Jones, H. M. J. Boffin, P. G. Beck

The quest for quiet or dormant black holes has been ongoing since several decades. Ellipsoidal variables possibly indicate the existence of a very high-mass invisible companion and are thought to be one of the best ways to find such dormant black holes. This, however, is not a panacea as we show here with one example. We indeed report the discovery of a new

Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen

We explore the methodology and theory of reward-directed generation via conditional diffusion models. Directed generation aims to generate samples with desired properties as measured by a reward function, which has broad applications in generative AI, reinforcement learning, and computational biology. We consider the common learning scenario where the data s

William Cook, Keld Helsgaun, Stefan Hougardy, Rasmus T. Schroeder

Hougardy and Schroeder (WG 2014) proposed a combinatorial technique for pruning the search space in the traveling salesman problem, establishing that, for a given instance, certain edges cannot be present in any optimal tour. We describe an implementation of their technique, employing an exact TSP solver to locate k-opt moves in the elimination process. In o

Maxime Adjigble, Rustam Stolkin, Naresh Marturi

This paper presents an assisted telemanipulation framework for reaching and grasping desired objects from clutter. Specifically, the developed system allows an operator to select an object from a cluttered heap and effortlessly grasp it, with the system assisting in selecting the best grasp and guiding the operator to reach it. To this end, we propose an obj

Theresa Seeholzer, Daniela Tarau, Lea Hollendonner, Andrea Auer

Surface-layer (S-layer) proteins form the outermost envelope in many bacteria and most archaea and arrange in 2D quasi-crystalline structures via self-assembly. We investigated S-layer proteins extracted from the archaeon Pyrobaculum aerophilium with a qPlus sensor-based atomic force microscope (AFM) in both liquid and ambient conditions and compared it to t

Hongyi Zheng, Yixin Zhu, Lavender Yao Jiang, Kyunghyun Cho

Recent advances in large language models have led to renewed interest in natural language processing in healthcare using the free text of clinical notes. One distinguishing characteristic of clinical notes is their long time span over multiple long documents. The unique structure of clinical notes creates a new design choice: when the context length for a la

Samuel Barham, Orion Weller, Michelle Yuan, Kenton Murray

To foster the development of new models for collaborative AI-assisted report generation, we introduce MegaWika, consisting of 13 million Wikipedia articles in 50 diverse languages, along with their 71 million referenced source materials. We process this dataset for a myriad of applications, going beyond the initial Wikipedia citation extraction and web scrap

Willian Righi Assis, Danilo da Silva Borges, Erick de Moraes Franklin

We investigate the behavior of subaqueous barchans reaching dune-size obstacles by carrying out experiments where we varied the obstacle shape and size, the flow strength, and the grains' properties. We found that a subaqueous barchan can pass over or bypass a dune-size obstacle, or even be blocked, with some intermediate situations. In the bypass cases, the

Bo-Ru Lu, Nikita Haduong, Chia-Hsuan Lee, Zeqiu Wu

The capabilities of pretrained language models have opened opportunities to explore new application areas, but applications involving human-human interaction are limited by the fact that most data is protected from public release for privacy reasons. Problem-solving human dialogues in real applications can be much more complex than existing Wizard-of-Oz coll

Jorge Gonzalez-Zapata, Francisco Lopez-Tiro, Elias Villalvazo-Avila, Daniel Flores-Araiza

Several Deep Learning (DL) methods have recently been proposed for an automated identification of kidney stones during an ureteroscopy to enable rapid therapeutic decisions. Even if these DL approaches led to promising results, they are mainly appropriate for kidney stone types for which numerous labelled data are available. However, only few labelled images

Margarita Grushanina, Sylvia Frühwirth-Schnatter

Mixtures of factor analysers (MFA) models represent a popular tool for finding structure in data, particularly high-dimensional data. While in most applications the number of clusters, and especially the number of latent factors within clusters, is mostly fixed in advance, in the recent literature models with automatic inference on both the number of cluster

Neel Dey, S. Mazdak Abulnaga, Benjamin Billot, Esra Abaci Turk

Star-convex shapes arise across bio-microscopy and radiology in the form of nuclei, nodules, metastases, and other units. Existing instance segmentation networks for such structures train on densely labeled instances for each dataset, which requires substantial and often impractical manual annotation effort. Further, significant reengineering or finetuning i

Joe Loughry, David A. Umphress

A previously unknown form of compromising emanations has been discovered. LED status indicators on data communication equipment, under certain conditions, are shown to carry a modulated optical signal that is significantly correlated with information being processed by the device. Physical access is not required; the attacker gains access to all data going t

Ben Allanach

This write-up is intended to form part of the proceedings for Lepton-Photon 2023. We review the decays $b\rightarrow c \ell \bar \nu_\ell$ (where $\ell \in \{e,\mu,\tau\}$) as well as $b\rightarrow s \mu^+ \mu^-$ and $b\rightarrow s e^+ e^-$, giving the current state-of-the-art in terms of measurements. We review fits to such data of new physics weak effecti

Aline Foerster Grande, Guilherme Pumi, Gabriela Bettella Cybis

This work presents a Bayesian approach for the estimation of Beta Autoregressive Moving Average ($\beta$ARMA) models. We discuss standard choice for the prior distributions and employ a Hamiltonian Monte Carlo algorithm to sample from the posterior. We propose a method to approach the problem of unit roots in the model's systematic component. We then present

Óscar Vega-Amaya, Fernando Luque-Vásquez

This note identifies compact and {\sigma}-compact subsets of probability measures on a class of metric spaces with respect to the weak convergence topology. Moreover, it is shown by an example, that the space of probability measures on a {\sigma}-compact metric spaces not need to be {\sigma}-compact space, even though the converse statement holds true for me

Guan Huang, Sergei Kuksin, Andrey Piatnitski

We are concerned with averaging theorems for $\epsilon$-small stochastic perturbations of integrable equations in $\mathbb{R}^d \times \mathbb{T}^n =\{(I,\varphi)\}$ $$ \dot I(t) =0,\quad \dot \varphi(t) = \theta(I), \qquad (1)$$ and in $\mathbb{R}^{2n} = \{v=(\mathbf{v}_1, \dots, \mathbf{v}_n), \; \mathbf{v}_j \in \mathbb{R}^2\}$, $$ \dot{\mathbf{v}}_k(t) =

Eleni Zavrakli, Andrew Parnell, Andrew Dickson, Subhrakanti Dey

Designing efficient closed-loop control algorithms is a key issue in Additive Manufacturing (AM), as various aspects of the AM process require continuous monitoring and regulation, with temperature being a particularly significant factor. Here we study closed-loop control of a state space temperature model with a focus on both model-based and data-driven met

Danny Gasman, Ewine F. van Dishoeck, Sierra L. Grant, Milou Temmink

MIRI/MRS on board the JWST allows us to probe the inner regions of protoplanetary disks. Here we examine the disk around the classical T Tauri star Sz 98, which has an unusually large dust disk in the millimetre with a compact core. We focus on the H$_2$O emission through both its ro-vibrational and pure rotational emission. Furthermore, we compare our chemi

Óscar Vega-Amaya, Fernando Luque-Vásquez

The standard version of the policy iteration (PI) algorithm fails for semicontinuous models, that is, for models with lower semicontinuous one-step costs and weakly continuous transition law. This is due to the lack of continuity properties of the discounted cost for stationary policies, thus appearing a measurability problem in the improvement step. The pre

ATM Omor Faruq

In this paper, we explore the economic, institutional, and political/governmental factors in attracting Foreign Direct Investment (FDI) inflows in the emerging twenty-four Asian economies. To examine the significant determinants of FDI, the study uses panel data for a period of seventeen years (2002-2018). The panel methodology enables us to deal with endoge

Kryštof Kolář, Yiran Zhang, Stevan Nadj-Perge, Felix von Oppen

Twisted $N$-layer graphene (TNG) moir\'e structures have recently been shown to exhibit robust superconductivity similar to twisted bilayer graphene (TBG). In particular for $N=4$ and $N=5$, the phase diagram features a superconducting pocket that extends beyond the nominal full filling of the flat band. These observations are seemingly at odds with the cano

Deressa Wodajo Deressa, Hannes Mareen, Peter Lambert, Solomon Atnafu

Deepfakes have raised significant concerns due to their potential to spread false information and compromise digital media integrity. Current deepfake detection models often struggle to generalize across a diverse range of deepfake generation techniques and video content. In this work, we propose a Generative Convolutional Vision Transformer (GenConViT) for

Dmitri R. Yakovlev, Scott A. Crooker, Marina A. Semina, Janina Rautert

Cesium lead bromide (CsPbBr$_3$) is a representative material of the emerging class of lead halide perovskite semiconductors that possess remarkable optoelectronic properties. Its optical properties in the vicinity of the band gap energy are greatly contributed by excitons, which form exciton-polaritons due to strong light-matter interactions. We examine exc

Elise LePage

We explain how to calculate link homology for a Lie algebra $\mathfrak{g}$ using the Fukaya category associated to a 2d A-model. Links are represented as configurations of particular A-branes and link homology is given by Homs between these A-branes. In the case of $\mathfrak{g}=\mathfrak{su}_2$, we explain how to explicitly construct projective resolutions

Luís H. Carnevale, Piotr Deuar, Zhizhao Che, Panagiotis E. Theodorakis

The breakup of liquid threads into smaller droplets is a fundamental problem in fluid dynamics. In this study, we estimate the characteristic wavelength of the breakup process by means of many-body dissipative particle dynamics. This wavelength shows a power-law dependence on the Ohnesorge number in line with results from stability analysis. We also discover

Vinayak Gupta, Srikanta Bedathur

Human beings always engage in a vast range of activities and tasks that demonstrate their ability to adapt to different scenarios. Any human activity can be represented as a temporal sequence of actions performed to achieve a certain goal. Unlike the time series datasets extracted from electronics or machines, these action sequences are highly disparate in t

Anjith George, Sebastien Marcel

Heterogeneous Face Recognition (HFR) aims to match face images across different domains, such as thermal and visible spectra, expanding the applicability of Face Recognition (FR) systems to challenging scenarios. However, the domain gap and limited availability of large-scale datasets in the target domain make training robust and invariant HFR models from sc

Pablo Sánchez-Peralta

Let $G$ be a countable group and $k$ a positive integer, we show that the $L^2$-Betti numbers of the group $G$ vanish up to degree $k$ provided that there is some infinite index subgroup $H$ with finite $k$th $L^2$-Betti number containing a normal subgroup of $G$ whose $L^2$-Betti numbers are all zero below degree $k$. This generalizes previous criteria of b

Rishabh Dixit, Mert Gurbuzbalaban, Waheed U. Bajwa

This paper considers the problem of understanding the behavior of a general class of accelerated gradient methods on smooth nonconvex functions. Motivated by some recent works that have proposed effective algorithms, based on Polyak's heavy ball method and the Nesterov accelerated gradient method, to achieve convergence to a local minimum of nonconvex functi

Shengminjie Chen, Donglei Du, Wenguo Yang, Dachuan Xu

We investigate the continuous non-monotone DR-submodular maximization problem subject to a down-closed convex solvable constraint. Our first contribution is to construct an example to demonstrate that (first-order) stationary points can have arbitrarily bad approximation ratios, and they are usually on the boundary of the feasible domain. These findings are

Nazanin Hoghooghi, Peter Chang, Scott Egbert Matt Burch, Rizwan Shaik

Molecular diagnostics are a primary tool of modern chemistry, enabling researchers to map chemical reaction pathways and rates to better design and control chemical systems. Many chemical reactions are complex and fast, and existing diagnostic approaches provide incomplete information. For example, mass spectrometry is optimized to gather snapshots of the pr

Valdemar Švábenský, Jan Vykopal, Pavel Čeleda, Lydia Kraus

Cybersecurity professionals need hands-on training to prepare for managing the current advanced cyber threats. To practice cybersecurity skills, training participants use numerous software tools in computer-supported interactive learning environments to perform offensive or defensive actions. The interaction involves typing commands, communicating over the n

Chanwoo Park, Kaiqing Zhang, Asuman Ozdaglar

We study a new class of Markov games, \emph(multi-player) zero-sum Markov Games} with \emph{Networked separable interactions} (zero-sum NMGs), to model the local interaction structure in non-cooperative multi-agent sequential decision-making. We define a zero-sum NMG as a model where {the payoffs of the auxiliary games associated with each state are zero-sum

Ramis Sh. Khasyanov

The concept of the Bohr radius of a pair of Banach spaces is introduced. The lower estimate for the value of the Bohr radius from the Bloch space to the space of bounded functions obtained by I. Kayumov, S. Ponnusamy and N. Shakirov is slightly improved. It is shown that for any weighted Bloch space the Bohr radius is not less than $1/\sqrt{2}$. A criterion

Thea Brüsch, Mikkel N. Schmidt, Tommy S. Alstrøm

Labeling of multivariate biomedical time series data is a laborious and expensive process. Self-supervised contrastive learning alleviates the need for large, labeled datasets through pretraining on unlabeled data. However, for multivariate time series data, the set of input channels often varies between applications, and most existing work does not allow fo

Oliver G. Maupin, Ashlyn D. Burch, Brandon Ruzic, Christopher G. Yale

Current noisy intermediate-scale quantum (NISQ) trapped-ion devices are subject to errors which can significantly impact the accuracy of calculations if left unchecked. A form of error mitigation called zero noise extrapolation (ZNE) can decrease an algorithm's sensitivity to these errors without increasing the number of required qubits. Here, we explore dif

Marc Sabek, Uta Pigorsch

Assortativity, i.e. the tendency of a vertex to bond with another based on their similarity, such as degree, is an important network characteristic that is well-known to be relevant for the network's robustness against attacks. Commonly it is analyzed on the global level, i.e. for the whole network. However, the local structure of assortativity is also of in

Attila Nagy, Dorina Petra Lakatos, Botond Barta, Patrick Nanys

We present a generic framework for data augmentation via dependency subtree swapping that is applicable to machine translation. We extract corresponding subtrees from the dependency parse trees of the source and target sentences and swap these across bisentences to create augmented samples. We perform thorough filtering based on graphbased similarities of th

David Evangelista, Yuri Thamsten

In a fixed time horizon, appropriately executing a large amount of a particular asset -- meaning a considerable portion of the volume traded within this frame -- is challenging. Especially for illiquid or even highly liquid but also highly volatile ones, the role of "market quality" is quite relevant in properly designing execution strategies. Here, we model

Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang

We study the problem of learning general (i.e., not necessarily homogeneous) halfspaces with Random Classification Noise under the Gaussian distribution. We establish nearly-matching algorithmic and Statistical Query (SQ) lower bound results revealing a surprising information-computation gap for this basic problem. Specifically, the sample complexity of this

Ariel Lerman, Marcelo M. Disconzi, Jorge Noronha

We investigate the initial value problem of a very general class of $3+1$ non-Newtonian compressible fluids in which the viscous stress tensor with shear and bulk viscosity relaxes to its Navier-Stokes values. These fluids correspond to the non-relativistic limit of well-known Israel-Stewart-like theories used in the relativistic fluid dynamic simulations of

Vinayak Gupta, Srikanta Bedathur, Abir De

Temporal sequences have become pervasive in various real-world applications. Consequently, the volume of data generated in the form of continuous time-event sequence(s) or CTES(s) has increased exponentially in the past few years. Thus, a significant fraction of the ongoing research on CTES datasets involves designing models to address downstream tasks such

Lucas Layman, William Roden

Organizations use intrusion detection systems (IDSes) to identify harmful activity among millions of computer network events. Cybersecurity analysts review IDS alarms to verify whether malicious activity occurred and to take remedial action. However, IDS systems exhibit high false alarm rates. This study examines the impact of IDS false alarm rate on human a

Valdemar Švábenský, Jan Vykopal, Pavel Čeleda, Kristián Tkáčik

Hands-on cybersecurity training allows students and professionals to practice various tools and improve their technical skills. The training occurs in an interactive learning environment that enables completing sophisticated tasks in full-fledged operating systems, networks, and applications. During the training, the learning environment allows collecting da

C. Ian Short, David J. Lane, Tiffany Fields

We describe the current state of the Burke-Gaffney Observatory (BGO) at Saint Mary's University - a unique fully roboticized remote-access observatory that allows students to carry out imaging, photometry, and spectroscopy projects remotely from anywhere in the world via a web browser or social media. Stellar spectroscopy is available with the ALPY 600 low r

Giorgio Torrieri

We show that volume-preserving diffomorphisms and the chemical shift symmetry defining relativistic lagrangian ideal fluid dynamics can be derived as an emerging symmetry when ergodicity is assumed to apply locally in a way that is invariant under smooth spacetime foliations. This can be used as a way to derive the ideal hydrodynamic limit in a strongly coup

Marcin Michalski, Robert Rałowski, Szymon Żeberski

The motivation of this work are the two classical theorems on inscribing rectangles and squares into large subsets of the plane, namely Eggleston Theorem and Mycielski Theorem. Using Shoenfield Absoluteness Theorem we prove that for every Borel subset of the plane with uncountably many positive (with respect to measure or category) vertical section contains

M. Amélia Bastos, Catarina C. Carvalho, Manuel G. Dias

The local trajectories method establishes invertibility in algebras $\mathcal{B}= \alg(\mathcal{A}, U_G)$, for a unital $C^*$-algebra $\mathcal{A}$ with a non-trivial center, and a unitary group $U_g$, $g\in G$, with $G$ a discrete group, assuming that $G$ is amenable and the action $a\mapsto U_gaU_g^*$ is topologically free. It is applicable in particular t

Shrawan Kumar

We study non-existence of non-constant regular maps from a partial flag variety $X=G/P$ to another partial flag variety $X'=G'/P'$ and prove that there does not exist any non-constant regular map from any partial non-complete flag variety $X$ to any complete flag variety $X'=G'/B'$. We also formulate a general conjecture on the non-existence of non-constant

Hnin Pann Phyu, Diala Naboulsi, Razvan Stanica, Gwenael Poitau

Network slicing is one of the major catalysts to turn future telecommunication networks into versatile service platforms. Along with its benefits, network slicing is introducing new challenges in the development of sustainable network operations. In fact, guaranteeing slices requirements comes at the cost of additional energy consumption, in comparison to no

Carl F. Mela, Jason M. T. Roos, Tulio Sousa

Direct buy advertisers procure advertising inventory at fixed rates from publishers and ad networks. Such advertisers face the complex task of choosing ads amongst myriad new publisher sites. We offer evidence that advertisers do not excel at making these choices. Instead, they try many sites before settling on a favored set, consistent with advertiser learn

Aaman Rebello, Shengpu Tang, Jenna Wiens, Sonali Parbhoo

Off-policy evaluation (OPE) aims to estimate the benefit of following a counterfactual sequence of actions, given data collected from executed sequences. However, existing OPE estimators often exhibit high bias and high variance in problems involving large, combinatorial action spaces. We investigate how to mitigate this issue using factored action spaces i.

Marzia Bordone, Mario Fernández Navarro

Several new physics scenarios that address anomalies in $B$-physics predict an enhancement of $b \rightarrow s \tau \tau$ with respect to its Standard Model prediction. Such scenarios necessarily imply modifications of the lifetime ratio $\tau_{B_{s}}/\tau_{B_{d}}$ and the lifetime difference $\Delta\Gamma_{s}$. In this work, we explore indirect bounds provi

Cheng Chu, Lei Jiang, Fan Chen

Recent advancements in Quantum Neural Networks (QNNs) have demonstrated theoretical and experimental performance superior to their classical counterparts in a wide range of applications. However, existing centralized QNNs cannot solve many real-world problems because collecting large amounts of training data to a common public site is time-consuming and, mor

Bernard J. Giron Castro, Christophe Peucheret, Darko Zibar, Francesco Da Ros

We quantify the impact of thermo-optic and free-carrier effects on time-delay reservoir computing using a silicon microring resonator. We identify pump power and frequency detuning ranges with NMSE less than 0.05 for the NARMA-10 task depending on the time constants of the two considered effects.

Guillermo Alonso Alvarez, Sergey Nadtochiy

In this paper we show how the relaxation techniques can be used to establish the existence of an optimal contract in presence of information asymmetry. The method we illustrate was initially motivated by the problem of designing optimal brokerage fees, but it does apply to other optimal contract problems, in which (i) the agent controls linearly the drift of

Cheng Chu, Fan Chen, Philip Richerme, Lei Jiang

Quantum neural networks (QNNs) succeed in object recognition, natural language processing, and financial analysis. To maximize the accuracy of a QNN on a Noisy Intermediate Scale Quantum (NISQ) computer, approximate synthesis modifies the QNN circuit by reducing error-prone 2-qubit quantum gates. The success of QNNs motivates adversaries to attack QNNs via b

J. R. Barnes, M. R. Standing, C. A. Haswell, D. Staab

We present radial velocity measurements of the very bright ($V\sim5.7$) nearby F star, DMPP-4 (HD 184960). The anomalously low Ca II H&K emission suggests mass loss from planets orbiting a low activity host star. Periodic radial velocity variability with $\sim 10$ ms$^{-1}$ amplitude is found to persist over a $>4$ year timescale. Although the non-simultaneo

Kyle G. Scheuer, Franz B. Romero, Graham J. Hornig, Ray G. DeCorby

We describe a system for interrogating the acoustic properties of sub-nanoliter liquid samples within an open microfluidics platform. Sessile droplets were deposited onto integrated optomechanical sensors, which possess ambient-medium-noise-limited sensitivity and can thus passively sense the thermally driven acoustic spectrum of the droplets. The droplet ac

Mike Verostek, Casey W. Miller, Benjamin M. Zwickl

Joining a research group is one of the most important events on a graduate student's path to earning a PhD, but the ways students go about searching for a group remain largely unstudied. It is therefore crucial to investigate whether departments are equitably supporting students as they look for an advisor, especially as students today enter graduate school

Mateusz Baran, Mateusz Wójcik, Piotr Kolebski, Michał Bernaczyk

The popularity of social media makes politicians use it for political advertisement. Therefore, social media is full of electoral agitation (electioneering), especially during the election campaigns. The election administration cannot track the spread and quantity of messages that count as agitation under the election code. It addresses a crucial problem, wh

Bom Soo Kim

We generalize the Thiele equation with a transverse velocity to the skyrmion motion described by the collective coordinate of magnetization vector. It is applied to investigate significant disparity in the existing data sets of skyrmion and antiskyrmion Hall angles. Our analysis further reveals interesting differences of these Hall angles near the angular mo

Ian Taylor, Andee Kaplan, Brenda Betancourt

Record linkage is the task of combining records from multiple files which refer to overlapping sets of entities when there is no unique identifying field. In streaming record linkage, files arrive sequentially in time and estimates of links are updated after the arrival of each file. This problem arises in settings such as longitudinal surveys, electronic he

Giada Grossi, David Loeffler, Sarah Livia Zerbes

We construct p-adic Asai L-functions for cuspidal automorphic representations of GL2 / F, where F is a real quadratic field in which p splits. Our method relies on higher Hida theory for Hilbert modular surfaces with Iwahori level at one prime above p.

Carolyn Zhang, Etienne Granet

We consider how a maximally mixed state evolves under $(1+1)D$ Floquet non-unitary circuits with an antiunitary symmetry that squares to identity, that serves as a generalized $\mathcal{PT}$ symmetry. Upon tuning a parameter, the effective Hamiltonian of the Floquet operator demonstrates a symmetry breaking transition. We show that this symmetry breaking tra

Mateusz Baran, Joanna Baran, Mateusz Wójcik, Maciej Zięba

State-of-the-art models can perform well in controlled environments, but they often struggle when presented with out-of-distribution (OOD) examples, making OOD detection a critical component of NLP systems. In this paper, we focus on highlighting the limitations of existing approaches to OOD detection in NLP. Specifically, we evaluated eight OOD detection me

Paolo Fragolino, Martine Schut, Marko Toroš, Sougato Bose

Matter-wave interferometry with nanoparticles will enable the development of quantum sensors capable of probing ultraweak fields with unprecedented applications for fundamental physics. The high sensitivity of such devices however makes them susceptible to a number of noise and decoherence sources and as such can only operate when sufficient isolation from t

Nikolay Bogachev, Dmitry Guschin, Andrei Vesnin

We study a more general version of the gluings of hyperbolic orbifolds in the spirit of Gromov and Piatetski-Shapiro, where the gluing pieces, called the building blocks, are no longer assumed to be arithmetic or incommensurable. We prove that if such a general hyperbolic gluing along a common finite-volume totally geodesic hypersurface is quasi-arithmetic (

Piero Rettegno, Geraint Pratten, Lucy Thomas, Patricia Schmidt

Highly accurate models of the gravitational-wave signal from coalescing compact binaries are built by completing analytical computations of the binary dynamics with non-perturbative information from numerical relativity (NR) simulations. In this paper we present four sets of NR simulations of equal-mass black hole binaries that undergo strong-field scatterin

Jonathan Cabrera Garcia, Timothy C. Beers, Yang Huang, Xin-Yi Li

We employ a sample of 135,873 RR Lyrae stars (RRLs) with precise photometric-metallicity and distance estimates from the newly calibrated $P$--$\phi_{31}$--$R_{21}$--[Fe/H] and $Gaia$ $G$-band $P$--$R_{21}$--[Fe/H] absolute magnitude-metallicity relations of Li et al., combined with available proper motions from $Gaia$ EDR3, and 6955 systemic radial velociti

Flavio Del Santo, Jakub Czartowski, Karol Życzkowski, Nicolas Gisin

While entanglement between distant parties has been extensively studied, entangled measurements have received relatively little attention despite their significance in understanding non-locality and their central role in quantum computation and networks. We present a systematic study of entangled measurements, providing a complete classification of all equiv

Qixuan Zhang, Lingyuan Lyu, Sneh Pancholi, Ziying Yan

Moir\'e superlattices in stacked 2D crystals are powerful platforms for engineering correlated and topological quantum phases, with twisted graphene and transition metal dichalcogenides (TMDs) as prominent examples. Their angle-sensitive band structures enable rich tunability; however, conventional tear-and-stack methods fix the angle at assembly, limiting s

Jack Y. Araz

Statistical models serve as the cornerstone for hypothesis testing in empirical studies. This paper introduces a new cross-platform Python-based package designed to utilise different likelihood prescriptions via a flexible plug-in system. This framework empowers users to propose, examine, and publish new likelihood prescriptions without developing software i

Yuxin Dong, Tarraneh Eftekhari, Wen-fai Fong, Adam T. Deller

We present high-resolution 1.5 $-$ 6 GHz Karl G. Jansky Very Large Array (VLA) and Hubble Space Telescope (HST) optical and infrared observations of the extremely active repeating fast radio burst (FRB) FRB 20201124A and its barred spiral host galaxy. We constrain the location and morphology of star formation in the host and search for a persistent radio sou

Kei Ito, Francesco Valentino, Gabriel Brammer, Andreas L. Faisst

We present the results of a systematic study of the rest-frame optical morphology of quiescent galaxies at $z \geq 3$ using the Near-Infrared Camera (NIRCam) onboard $JWST$. Based on a sample selected by $UVJ$ color or $NUVUVJ$ color, we focus on 26 quiescent galaxies with $9.8<\log{(M_\star/M_\odot)}<11.4$ at $2.8<z_{\rm phot}<4.6$ with publicly available $