November 2024 arXiv papers — page 160

Xingran Chen, Zhenke Wu, Xu Shi, Hyunghoon Cho

We conduct a scoping review of existing approaches for synthetic EHR data generation, and benchmark major methods with proposed open-source software to offer recommendations for practitioners. We search three academic databases for our scoping review. Methods are benchmarked on open-source EHR datasets, MIMIC-III/IV. Seven existing methods covering major cat

Mikołaj Słupiński, Piotr Lipiński

In this paper, we propose a novel model called Recurrent Explicit Duration Switching Linear Dynamical Systems (REDSLDS) that incorporates recurrent explicit duration variables into the rSLDS model. We also propose an inference and learning scheme that involves the use of P\'olya-gamma augmentation. We demonstrate the improved segmentation capabilities of our

Ollie Wiltshire, Seyed Amir Tafrishi

This paper presents a novel type of mobile rolling robot designed as a modular platform for non-prehensile manipulation, highlighting the associated control challenges in achieving balancing control of the robotic system. The developed rolling disk modules incorporate an innovative internally actuated magnetic-pendulum coupling mechanism, which introduces a

Mikołaj Słupiński, Piotr Lipiński

The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) is a natural Bayesian nonparametric extension of the classical Hidden Markov Model for learning from (spatio-)temporal data. A sticky HDP-HMM has been proposed to strengthen the self-persistence probability in the HDP-HMM. Then, disentangled sticky HDP-HMM has been proposed to disentangle the s

Mao Lin, Kyungjoo Noh

Determining the quantum capacity of a noisy quantum channel is an important problem in the field of quantum communication theory. In this work, we consider the Gaussian random displacement channel $N_{\sigma}$, a type of bosonic Gaussian channels relevant in various bosonic quantum information processing systems. In particular, we attempt to make progress on

Nasib Ullah, Erik Schultheis, Jinbin Zhang, Rohit Babbar

Extreme multilabel classification (XMLC) problems occur in settings such as related product recommendation, large-scale document tagging, or ad prediction, and are characterized by a label space that can span millions of possible labels. There are two implicit tasks that the classifier performs: \emph{Evaluating} each potential label for its expected worth,

Hamideh Talafian, Tim Stelzer, Morten Lundsgaard, Maggie Mahmood

Although most teachers acknowledge the importance of taking investigative approached in students' science learning experiences, implementing them in high-school classes can be challenging for teachers. In this work, we analyzed data from multiple sources from a teaching Community of Practice (CoP) to investigate (a) barriers to using open-ended labs in physi

Vinay A. Vaishampayan, Thilaharani Antony, Amirthagunaraj Yogarathnam

Wind energy's role in the global electric grid is set to expand significantly. New York State alone anticipates offshore wind farms (WFs) contributing 9GW by 2035. Integration of energy storage emerges as crucial for this advancement. In this study, we focus on a WF paired with a captive battery energy storage system (BESS). We aim to ascertain the capacity

Yuna Hwang, Arissa J. Sato, Pragathi Praveena, Nathan Thomas White

Leveraging generative AI (for example, Large Language Models) for language understanding within robotics opens up possibilities for LLM-driven robot end-user development (EUD). Despite the numerous design opportunities it provides, little is understood about how this technology can be utilized when constructing robot program logic. In this paper, we outline

Michael Grayson

In this paper, I outline the correspondence of vector partitions with the combinatorics of dynamical systems whose states are partitions of multisets. I use the notion of a limiting shape of vector partitions to determine properties of the equilibrium distribution for these systems. I investigate prebiotic systems as ergodic series of chemical reactions as a

Sagar Bharadwaj, Ziyong Ma, Ivan Liang, Michael Farb

Spatial applications, i.e., applications that tie digital information with the physical world, have improved many of our daily activities, such as navigation and ride-sharing. This class of applications also holds significant promise of enabling new industries such as augmented reality and robotics. The development of these applications is enabled by a syste

Allyson Silva, Artur Scherer, Zak Webb, Abdullah Khalid

We propose a novel technique for optimizing a modular fault-tolerant quantum computing architecture, taking into account any desired space-time trade-offs between the number of physical qubits and the fault-tolerant execution time of a quantum algorithm. We consider a concept architecture comprising a dedicated zone as a multi-level magic state factory and a

Piotr Wzorek, Kamil Jeziorek, Tomasz Kryjak, Andrea Pinna

Event cameras are becoming increasingly popular as an alternative to traditional frame-based vision sensors, especially in mobile robotics. Taking full advantage of their high temporal resolution, high dynamic range, low power consumption and sparsity of event data, which only reflects changes in the observed scene, requires both an efficient algorithm and a

Y. Aoki, T. Blum, S. Collins, L. Del Debbio

We review lattice results related to pion, kaon, $D$-meson, $B$-meson, and nucleon physics with the aim of making them easily accessible to the nuclear and particle physics communities. More specifically, we report on the determination of the light-quark masses, the form factor $f_+(0)$ arising in the semileptonic $K \to \pi$ transition at zero momentum tran

Adam M. Lehavi

The Ramsey number $R(s,t)$ is the smallest integer $n$ such that all graphs of size $n$ contain a clique of size $s$ or an independent set of size $t$. $\mathcal{R}(s,t,n)$ is the set of all counterexample graphs without this property for a given $n$. We prove that if a graph $G_{n+1}$ of size $n+1$ has $\max\{s,t\}+1$ subgraphs in $\mathcal{R}(s,t,n)$, then

Nandakishore Santhi, Stephan Eidenbenz, Brian Key, George Tompkins

We study the challenge of predicting the time at which a competitor product, such as a novel high-capacity EV battery or a new car model, will be available to customers; as new information is obtained, this time-to-market estimate is revised. Our scenario is as follows: We assume that the product is under development at a Firm B, which is a competitor to Fir

Mauricio Velasco, Kaiying O'Hare, Bernardo Rychtenberg, Soledad Villar

Graph neural networks (GNNs) provide state-of-the-art results in a wide variety of tasks which typically involve predicting features at the vertices of a graph. They are built from layers of graph convolutions which serve as a powerful inductive bias for describing the flow of information among the vertices. Often, more than one data modality is available. T

Zhiwei Liu, Seyed Amir Tafrishi

Spherical rolling robots have garnered significant attention in the field of mobile robotics for applications such as inspection and space exploration. Designing underactuated rolling robots poses challenges in achieving multi-directional propulsion with high degrees of freedom while utilizing a limited number of actuators. This paper presents the MonoRollBo

Kaushik Ranade, Tanmay Khule, Riddhi More

Human-computer interaction (HCI) has been a widely researched area for many years, with continuous advancements in technology leading to the development of new techniques that change the way we interact with computers. With the recent advent of powerful computers, we recognize human actions and interact accordingly, thus revolutionizing the way we interact w

Guillermo Alonso Alvarez, Erhan Bayraktar, Ibrahim Ekren, Liwei Huang

In this paper we study a principal-agent problem in continuous time with multiple lump-sum payments (contracts) paid at different deterministic times. We reduce the non-zero sum Stackelberg game between the principal and agent to a standard stochastic optimal control problem. We apply our result to a benchmark model for which we investigate how different inp

Martin Charron, Breeana Elliott, Nada Kerrouri, Liqun He

Inspired by its central role in many biological processes, the transport of biopolymers across nanoscale pores is at the heart of a single-molecule sensing technology aimed at nucleic acid and protein sequencing, as well as biomarker detection. When electrophoretically driven through a pore by an electric potential gradient, a translocating polymer hinders t

Pavel Sountsov, Colin Carroll, Matthew D. Hoffman

Today, cheap numerical hardware offers huge amounts of parallel computing power, much of which is used for the task of fitting neural networks to data. Adoption of this hardware to accelerate statistical Markov chain Monte Carlo (MCMC) applications has been much slower. In this chapter, we suggest some patterns for speeding up MCMC workloads using the hardwa

Asef Yelghi, Aref Yelghi, Shirmohammad Tavangari

The development of artificial intelligence has made significant contributions to the financial sector. One of the main interests of investors is price predictions. Technical and fundamental analyses, as well as econometric analyses, are conducted for price predictions; recently, the use of AI-based methods has become more prevalent. This study examines daily

Kyle G. Miller, Jacob R. Pierce, Fei Li, Brandon K. Russell

Extreme ultraviolet (XUV) light sources allow for the probing of bound electron dynamics on attosecond scales, interrogation of high-energy-density matter, and access to novel regimes of strong-field quantum electrodynamics. Despite the importance of these applications, coherent XUV sources remain relatively rare, and those that do exist are limited in their

Arham Khan, Robert Underwood, Carlo Siebenschuh, Yadu Babuji

Contemporary large language model (LLM) training pipelines require the assembly of internet-scale databases full of text data from a variety of sources (e.g., web, academic, and publishers). Preprocessing these datasets via deduplication -- detecting and eliminating additional instances of the same content -- is a major focus for assembling and curating trai

Kumail Zaidi, David A. Wake, Danilo Marchesini, Kartheik Iyer

We present a comprehensive analysis of the observed Stellar-to-Halo mass relationship (SHMR) spanning redshifts from 0.2 to 4.5. This was enabled through galaxy clustering and abundance measurements from two large (effective area ~ 1.61 deg^2) and homogeneously prepared photometric catalogs - UltraVISTA ultra-deep stripes DR3 (COSMOS) and FENIKS v1 (UDS). To

Siddharth Seth, Akash Sonth, Anirban Chakraborty

Person re-identification (re-ID) aims to tackle the problem of matching identities across non-overlapping cameras. Supervised approaches require identity information that may be difficult to obtain and are inherently biased towards the dataset they are trained on, making them unscalable across domains. To overcome these challenges, we propose an unsupervised

Chengzhang Sun

The paper studies the $L^2$-torsion of fibrations, focusing on cases that relax acyclicity and the determinant class condition. We prove the sum formula and the product formula for $L^2$-torsion in the extended abelian category. The desired formula for $L^2$-torsion of a simple fibration is obtained under the assumption that the fibers have zero Euler charac

Reinaldo Francener, Victor P. Goncalves, Diego R. Gratieri

The study of neutrino physics at the Large Hadron Collider is already a reality, and a broad neutrino physics program is expected to be developed in forthcoming years at the Forward Physics Facility (FPF). In particular, the neutrino trident scattering process, which is a rare Standard Model process, is expected to be observed for the first time with a stati

B. J. Wargelin, S. H. Saar, Z. A. Irving, J. D. Slavin

Proxima Cen (GJ 551; dM5.5e) is one of only about a dozen fully convective stars known to have a stellar cycle, and the only one to have long-term X-ray monitoring. A previous analysis found that X-ray and mid-UV observations, particularly two epochs of data from Swift, were consistent with a well sampled 7 yr optical cycle seen in ASAS data, but not convinc

Jiuci Xu

We study the time evolution governed by the two-sided chord Hamiltonian in the double-scaled SYK model, which induces a probability distribution over operators in the double-scaled algebra. Through the bulk-to-boundary map, this distribution translates into dynamical profiles of bulk states within the chord Hilbert space. We derive analytic expressions for s

Corentin Le Bars, Jean Lécureux, Jeroen Schillewaert

Let $G$ be a group with a non-elementary action on a (not necessarily discrete) $\tilde{A}_2$-buildings. We prove that, given a random walk on $G$, isometries in $G$ are strongly regular hyperbolic with high probability. As a consequence, we prove a Tits alternative for $G$, as well as a local-to-global fixed point result. We also prove that isometries of (n

Siddharth Seth, Rishabh Dabral, Diogo Luvizon, Marc Habermann

Modeling a human avatar that can plausibly deform to articulations is an active area of research. We present PocoLoco -- the first template-free, point-based, pose-conditioned generative model for 3D humans in loose clothing. We motivate our work by noting that most methods require a parametric model of the human body to ground pose-dependent deformations. C

Ciprian Demeter, Hongki Jung, Donggeun Ryou

We construct maximal $\Lambda(p)$-subsets on a large class of curved manifolds, in an optimal range of Lebesgue exponents $p$. Our arguments combine restriction estimates and decoupling with old and new probabilistic estimates.

Fabio Bagarello, Sergiusz Kuzel

Let $\mathcal{H}$ be a linear space equipped with an indefinite inner product $[\cdot, \cdot]$. Denote by $\mathcal{F}_{++}=\{f\in\mathcal{H} \ : \ [f,f]>0\}$ the nonlinear set of positive vectors in $\mathcal{H}$. We demonstrate that the properties of a linear operator $W$ in $\mathcal{H}$ can be uniquely determined by its restriction to $\mathcal{F}_{++}$.

Yueqian Liu

Autonomous drone racing has gained attention for its potential to push the boundaries of drone navigation technologies. While much of the existing research focuses on racing in obstacle-free environments, few studies have addressed the complexities of obstacle-aware racing, and approaches presented in these studies often suffer from overfitting, with learned

Anowar Shaikh, Shubhalaxmi Rath, Sadhana Dash, Binata Panda

The highly energetic particle medium formed in the ultrarelativistic heavy ion collision displays a notable difference in the temperatures between its central and peripheral regions. This temperature gradient can generate an electric field within the medium, a phenomenon referred to as the Seebeck effect. We have estimated the Seebeck coefficient for a dense

Praveen Nair, Payal Bhandari, Mohammadsajad Abavisani, Sergey Plis

In many causal learning problems, variables of interest are often not all measured over the same observations, but are instead distributed across multiple datasets with overlapping variables. Tillman et al. (2008) presented the first algorithm for enumerating the minimal equivalence class of ground-truth DAGs consistent with all input graphs by exploiting lo

Hala Hawashin, Mehrnoosh Sadrzadeh

While large language models (LLMs) have advanced the field of natural language processing (NLP), their "black box" nature obscures their decision-making processes. To address this, researchers developed structured approaches using higher order tensors. These are able to model linguistic relations, but stall when training on classical computers due to their e

C. F. P. Avalos, M. C. de Oliveira

Trapped ion systems present non-classical characteristics such as squeezed states that show a quantum advantage in quantum sensing, quantum information processing and quantum thermodynamics. We analyze the non-classical characteristics of a system described by a single ion trapped by a periodic potential field. Within the regime of non-adiabatic manipulation

James D. Watson

The quantum stochastic drift protocol, also known as qDRIFT, has become a popular algorithm for implementing time-evolution of quantum systems using randomised compiling. In this work we develop qFLO, a higher order randomised algorithm for time-evolution. To estimate an observable expectation value at time $T$ to precision $\epsilon$, we show it is sufficie

Irene Botosaru, Isaac Loh, Chris Muris

We introduce a new framework for characterizing identified sets of structural and counterfactual parameters in econometric models. By reformulating the identification problem as a set membership question, we leverage the separating hyperplane theorem in the space of observed probability measures to characterize the identified set through the zeros of a discr

Christa Cuchiero, Francesca Primavera, Sara Svaluto-Ferro

We introduce a class of jump-diffusions, called holomorphic, of which the well-known classes of affine and polynomial processes are particular instances. The defining property concerns the extended generator, which is required to map a (subset of) holomorphic functions to themselves. This leads to a representation of the expectation of power series of the pr

Jeremy Seeman, Yajuan Si, Jerome P Reiter

In general, it is challenging to release differentially private versions of survey-weighted statistics with low error for acceptable privacy loss. This is because weighted statistics from complex sample survey data can be more sensitive to individual survey response and weight values than unweighted statistics, resulting in differentially private mechanisms

Edoardo Sebastiano De Duro, Enrique Taietta, Riccardo Improta, Massimo Stella

Machine psychology aims to reconstruct the mindset of Large Language Models (LLMs), i.e. how these artificial intelligences perceive and associate ideas. This work introduces PhDGPT, a prompting framework and synthetic dataset that encapsulates the machine psychology of PhD researchers and professors as perceived by OpenAI's GPT-3.5. The dataset consists of

Raju Biswas, Rajib Mandal

Let $\mathcal{H}$ be the space of all functions that are analytic in $\mathbb{D}$. Let $\mathcal{A}$ denote the family of all functions $f\in\mathcal{H}$ and normalized by the conditions $f(0)=0=f'(0)-1$. Obradovi\'{c} and Ponnusamy have introduced the class $\mathcal{M}(\lambda)$ such that the functions in $\mathcal{M}(\lambda)$ are univalent in $\mathbb{D}

James Bartusek, Dakshita Khurana

We put forth Oblivious State Preparation (OSP) as a cryptographic primitive that unifies techniques developed in the context of a quantum server interacting with a classical client. OSP allows a classical polynomial-time sender to input a choice of one out of two public observables, and a quantum polynomial-time receiver to recover an eigenstate of the corre

Stephon Alexander, Heliudson Bernardo, Yiya Selina Li, Cooper Niu

We investigate cosmological vacuum amplification of gravitational waves in dynamical Chern-Simons gravity. We develop a comprehensive framework to compute graviton production induced by the parity violating Pontryagin coupling and study its imprint on the stochastic gravitational wave background energy power spectrum. We explore gravitational vacuum amplific

Thomas E. Cecil, Patrick J. Ryan

A hypersurface $M^n$ in a real space form ${\bf R}^{n+1}$, $S^{n+1}$, or $H^{n+1}$ is isoparametric if it has constant principal curvatures. This paper is a survey of the fundamental work of Cartan and M\"{u}nzner on the theory of isoparametric hypersurfaces in real space forms, in particular, spheres. This work is contained in four papers of Cartan publishe

Fernando Granha Jeronimo, Nir Magrafta, Joseph Slote, Pei Wu

Understanding the power and limitations of classical and quantum information and how they differ is a fundamental endeavor. In property testing of distributions, a tester is given samples over a typically large domain $\{0,1\}^n$. An important property is the support size both of distributions [Valiant and Valiant, STOC'11], as well, as of quantum states. Cl

Aditya Mittal, Taha Abdullah, Arjun Ashok, Brandon Zarate Estrada

The growing influence of data science in statistics education requires tools that make key concepts accessible through real-world applications. We introduce "Data Science Looks At Discrimination" (dsld), an R package that provides a comprehensive set of analytical and graphical methods for examining issues of discrimination involving attributes such as race,

Vaseem A. Shaik, Jiahao Gong, Gwynn J. Elfring

Organisms often swim through fluids that are spatially inhomogeneous. If the fluids are polymeric, gradients in polymer concentration may lead to gradients in both fluid viscosity and elasticity. In this letter, we present theoretical results for the dynamics of active particles, biological or otherwise, swimming through spatially inhomogeneous viscoelastic

Jung Yeon Park, Sujay Bhatt, Sihan Zeng, Lawson L. S. Wong

Equivariant neural networks have shown great success in reinforcement learning, improving sample efficiency and generalization when there is symmetry in the task. However, in many problems, only approximate symmetry is present, which makes imposing exact symmetry inappropriate. Recently, approximately equivariant networks have been proposed for supervised cl

Julian Strohmayer, Matthias Wödlinger, Martin Kampel

We propose WiFlexFormer, a highly efficient Transformer-based architecture designed for WiFi Channel State Information (CSI)-based person-centric sensing. We benchmark WiFlexFormer against state-of-the-art vision and specialized architectures for processing radio frequency data and demonstrate that it achieves comparable Human Activity Recognition (HAR) perf

Weiliang Zhao, Daniel Ben-Levi, Wei Hao, Junfeng Yang

We have uncovered a powerful jailbreak technique that leverages large language models' ability to diverge from prior context, enabling them to bypass safety constraints and generate harmful outputs. By simply instructing the LLM to deviate and obfuscate previous attacks, our method dramatically outperforms existing approaches, achieving up to a 62.83% higher

Brendan Hassett

Cubic fourfolds of discriminant 24 contain special codimension-two algebraic cycles of degree 6 and self-intersection 20. Such cycles may be represented by singular scrolls or del Pezzo surfaces. A discriminant 24 cubic fourfold gives rise to a twisted surface, consisting of a degree-six K3 surface and a two-torsion element of its Brauer group. We show that

Ludovica Crosato Menegazzi, Sho Fujibayashi, Masaru Shibata, Aurore Betranhandy

We assess the variance of supernova(SN)-like explosions associated with the core collapse of rotating massive stars into a black hole-accretion disc system under changes in the progenitor structure. Our model of the central engine evolves the black hole and the disc through the transfer of matter and angular momentum and includes the contribution of the disc

Ethan Sussman

Recent work by Hintz--Vasy provides a partial asymptotic analysis of the low-energy limit of scattering for Schr\"odinger operators with a short-range potential. Using a slight refinement of Hintz's algorithm, we complete the asymptotic analysis by providing full asymptotic expansions in every possible asymptotic regime. Moreover, the analysis is done in any

Zhao Xu, Haiyang Yu, Montgomery Bohde, Shuiwang Ji

Recent advancements in equivariant deep models have shown promise in accurately predicting atomic potentials and force fields in molecular dynamics simulations. Using spherical harmonics (SH) and tensor products (TP), these equivariant networks gain enhanced physical understanding, like symmetries and many-body interactions. Beyond encoding physical insights

S. I. Ipatov

The motion of bodies ejected from the Earth was studied, and the probabilities of collisions of such bodies with the present terrestrial planets were calculated. The dependences of these probabilities on velocities, angles and points of ejection of bodies were studied. These dependences can be used in the models with different distributions of ejected materi

Ruhan Wang, Ye Wang, Jing Liu, Toshiaki Koike-Akino

Modern quantum machine learning (QML) methods involve the variational optimization of parameterized quantum circuits on training datasets, followed by predictions on testing datasets. Most state-of-the-art QML algorithms currently lack practical advantages due to their limited learning capabilities, especially in few-shot learning tasks. In this work, we pro

Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet

While synthetic data hold great promise for privacy protection, their statistical analysis poses significant challenges that necessitate innovative solutions. The use of deep generative models (DGMs) for synthetic data generation is known to induce considerable bias and imprecision into synthetic data analyses, compromising their inferential utility as oppos

Jan Nöller, Nikolai Miklin, Martin Kliesch, Mariami Gachechiladze

The rapid advancement of quantum hardware calls for the development of reliable methods to certify its correct functioning. However, existing certification tests often fall short: they either rely on flawless state preparation and measurement or lack soundness guarantees, meaning that they do not rule out incorrect implementations of the target operations by

S. V. Rumyantseva, D. S. Shirokov

It is easier to investigate phenomena in particle physics geometrically by exploring a real solution to the Dirac-Hestenes equation instead of a complex solution to the Dirac equation. The current research presents a formulation of the multidimensional Dirac-Hestenes equation. Since the matrix representation of the complexified (Clifford) geometric algebra $

Carl Pomerance

Mersenne primes and Fermat primes may be thought of as primes of the form $\Phi_m(2)$, where $\Phi_m(x)$ is the $m$th cyclotomic polynomial. This paper discusses the more general problem of primes and composites of this form.

M. D. Voisei

This article employs techniques from convex analysis to present characterizations of (maximal) $n-$monotonicity, similar to the well-established characterizations of (maximal) monotonicity found in the existing literature. These characterizations are further illustrated through examples.

Randall Powers, John Eltinge, Wendy Martinez, Darcy Steeg Morris

Linked micromaps were originally developed to display geographically indexed statistics in an intuitive way by connecting them to a sequence of small maps. The approach integrates several visualization design principles, such as small multiples, discrete color indexing, and ordering. Linked micromaps allow for other types of data displays that are connected

Z. Zhang, A. Faus-Golfe, A. Korsun, B. Bai

The FCC-ee offers the potential to measure the electron Yukawa coupling via direct s-channel Higgs production, $e^+ e^- \rightarrow \text{H}$, at a centre-of-mass (CM) energy of ~125 GeV. This measurement is significantly facilitated if the CM energy spread of $e^+ e^-$ collisions can be reduced to a level comparable to the natural width of the Higgs boson,

Kymani T. K. Armstrong-Williams, Edward Hirst, Blake Jackson, Kyu-Hwan Lee

Machine learning (ML) has emerged as a powerful tool in mathematical research in recent years. This paper applies ML techniques to the study of quivers -- a type of directed multigraph with significant relevance in algebra, combinatorics, computer science, and mathematical physics. Specifically, we focus on the challenging problem of determining the mutation

Ulisses M Portugal

We explicitly compute the effective action from Open Superstring Field Theory in the hybrid formalism to quartic order in the $\alpha'\rightarrow 0$ limit, and show that it reproduces ten-dimensional Super Yang-Mills in terms of four-dimensional superfields. We also show that in this limit the gauge transformations coincide with SYM to all orders, which mean

Brian Kent, Tucker Manton, Sanjit Shashi

In this work, we investigate the assumptions regarding spacetime backgrounds underlying the classical double copy. We argue (contrary to the norm) that single-copy fields naturally constructed on the original curved background metric are only interpretable on a flat metric when such a well-defined limit exists, for which Kerr--Schild coordinates offer a natu

Maxim L. Yattselev

Let $\mu_1$ and $\mu_2$ be two complex-valued Borel measures on the real line such that $\operatorname{supp} \mu_1 =[\alpha_1,\beta_1] < \operatorname{supp} \mu_2 =[\alpha_2,\beta_2]$ and ${\rm d}\mu_i(x) = -\rho_i(x){\rm d}x/2\pi {\rm i}$, where $\rho_i(x)$ is the restriction to $[\alpha_i,\beta_i]$ of a function non-vanishing and holomorphic in some neighb

Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar

We provide new lower bounds on the privacy guarantee of the multi-epoch Adaptive Batch Linear Queries (ABLQ) mechanism with shuffled batch sampling, demonstrating substantial gaps when compared to Poisson subsampling; prior analysis was limited to a single epoch. Since the privacy analysis of Differentially Private Stochastic Gradient Descent (DP-SGD) is obt

Jianyi Yang, Pengfei Li, Adam Wierman, Shaolei Ren

Online Budgeted Matching (OBM) is a classic problem with important applications in online advertising, online service matching, revenue management, and beyond. Traditional online algorithms typically assume a small bid setting, where the maximum bid-to-budget ratio (\kappa) is infinitesimally small. While recent algorithms have tried to address scenarios wit

Ivan Chernyshev, Caroline E. P. Robin, Martin J. Savage

We consider the quantum magic in systems of dense neutrinos undergoing coherent flavor transformations, relevant for supernova and neutron-star binary mergers. Mapping the three-flavor-neutrino system to qutrits, the evolution of quantum magic is explored in the single scattering angle limit for a selection of initial tensor-product pure states for $N_\nu \l

Mohamad H. Kazma, Salma M. Elsherif, Ahmad F. Taha

This paper studies the problem of optimal placement of water quality (WQ) sensors in water distribution networks (WDNs), with a focus on chlorine transport, decay, and reaction models. Such models are traditionally used as suitable proxies for WQ. The literature on this topic is inveterate, but has a key limitation: it utilizes simplified single-species deca

Kuntal Sengupta

Quantum theory allows for the superposition of causal orders between operations, i.e., for an indefinite causal order; an implication of the principle of quantum superposition. Since a higher theory might also admit this feature, an understanding of superposition and indefinite causal order in a generalised probabilistic framework is needed. We present a pos

David Pinzon Ulloa, Ammar Metnani, Emma Frejinger

We consider a strategic decision-making problem where a logistics provider (LP) seeks to locate collection and delivery points (CDPs) with the objective to reduce total logistics costs. The customers maximize utility that depends on their perception of home delivery service as well as the characteristics of the CDPs, including their location. At the strategi

Artur Czerwinski, Jakub J. Borkowski

The paper by K. Sengupta et al. (Opt. Express 32, 40150-40164, 2024) explores quantum illumination using polarization-entangled photon pairs for object detection in noisy environments. In this comment, we highlight fundamental flaws in the mathematical model used to describe photon loss. We argue that the treatment of photon loss and its effects on quantum e

Iryna Hartsock, Cyrillo Araujo, Les Folio, Ghulam Rasool

Radiology reports are often lengthy and unstructured, posing challenges for referring physicians to quickly identify critical imaging findings while increasing the risk of missed information. This retrospective study aimed to enhance radiology reports by making them concise and well-structured, with findings organized by relevant organs. To achieve this, we

Federico Castellani

This paper investigates marginal and dipole TsT transformations of a seed type IIB supergravity solution dual to a supersymmetry-preserving deformation of the Klebanov-Witten 4d SCFT. To explore key properties of the deformed theories, we holographically analyze various observables, including Wilson loops, 't Hooft loops, Entanglement Entropy, and holographi

Guillaume Dideron, Suvodip Mukherjee, Luis Lehner

New physics and systematic errors can lead to deviations between the models used to analyze gravitational wave data and the actual signal. Such deviations will generally be correlated between detectors and manifest differently across the gravitational wave source parameter space. The previously introduced \ttt{SCoRe} framework uses these features to distingu

Anirban Majumdar, Dimitrios K. Papoulias, Hemant Prajapati, Rahul Srivastava

Coherent elastic neutrino-nucleus (CE$\nu$NS) and elastic neutrino-electron scattering (E$\nu$ES) data are exploited to constrain ``chiral'' $U(1)_{X}$ gauged models with light vector mediator mass. These models fall under a distinct class of new symmetries called dark hypercharge symmetries. A key feature is the fact that the $Z'$ boson can couple to all St

Kendall Sullivan, Adam L. Kraus, Travis A. Berger, Daniel Huber

Identifying and removing binary stars from stellar samples is a crucial but complicated task. Regardless of how carefully a sample is selected, some binaries will remain and complicate interpretation of results, especially via flux contamination of survey photometry. One such sample is the data from the Gaia spacecraft, which is collecting photometry and ast

Wenjun Niu

Let $G$ be a reductive algebraic group with Lie algebra $\mathfrak{g}$ and $V$ a finite-dimensional representation of $G$. Costello-Gaiotto studied a graded Lie algebra $\mathfrak{d}_{\mathfrak{g}, V}$ and the associated affine Kac-Moody algebra. In this paper, we show that this Lie algebra can be made into a sheaf of Lie algebras over $T^*[V/G]=[\mu^{-1}(0)

Tudor Dimofte, Wenjun Niu

We propose a nonperturbative construction of Hopf algebras that represent categories of line operators in topological quantum field theory, in terms of semi-extended operators (spark algebras) on pairs of transverse topological boundary conditions. The construction is a direct implementation of Tannakian formalism in QFT. Focusing on d=3 dimensional theories

Katherine Elder, Daniel C. Jacobs, Maria Kovaleva

Measurement of the power spectrum of high redshift 21 cm emission from neutral hydrogen probes the formation of the first luminous objects and the ionization of intergalactic medium by the first stars. However, the 21 cm signal at these redshifts is orders of magnitude fainter than astrophysical foregrounds, making it challenging to measure. Power spectrum t

Brendan J. McKee, Benjamin T. Montet, Samuel W. Yee, Joel D. Hartman

TOI-2818 b is a hot Jupiter orbiting a slightly evolved G-type star on a 4.04-day orbit that shows transit timing variations (TTVs) suggestive of a decreasing orbital period. In the most recent year of TESS observations, transits were observed $\sim$8 minutes earlier than expected for a constant period. The implied orbital decay rate is $1.35 \pm 0.25$ s yr$

Haining Pan, Hassan Shapourian, Chao-Ming Jian

Dynamical quantum systems both driven by unitary evolutions and monitored through measurements have proved to be fertile ground for exploring new dynamical quantum matters. While the entanglement structure and symmetry properties of monitored systems have been intensively studied, the role of topology in monitored dynamics is much less explored. In this work

Arjun Bagchi, Aritra Banerjee, Saikat Mondal, Sayantan Sarkar

We discover a surprising connection between Carrollian symmetries and hydrodynamics in the shallow water approximation. Carrollian symmetries arise in the speed of light going to zero limit of relativistic Poincar\'e symmetries. Using a recent gauge theoretic description of shallow water wave equations we find that the actions corresponding to two different

Mathieu Gross, Essodjolo Kpatcha, Yann Mambrini, Maria Olalla Olea-Romacho

We calculate the gravitational waves (GWs) produced by primordial black holes (PBHs) in the presence of the inflaton condensate in the early Universe. Combining the GW production from the evaporation process, the gravitational scattering of the inflaton itself, and the density fluctuations due to the inhomogeneous distribution of PBHs, we propose for the fir

Michelle Lochner, Lawrence Rudnick

Modern telescopes generate catalogs of millions of objects with the potential for new scientific discoveries, but this is beyond what can be examined visually. Here we introduce Astronomaly: Protege, an extension of the general purpose machine learning-based active anomaly detection framework Astronomaly. Protege is designed to provide well-selected recommen

Ben G. Patterson, Sharon Mary Tomson, Stephen Fairhurst

We show that the gravitational waveform emitted by a binary on an eccentric orbit can be naturally decomposed into a series of harmonics. The frequencies of these harmonics depend upon the radial frequency, $f_{\mathrm{r}}$, determined by the time to return to apoapsis, and the azimuthal frequency, $f_{\phi}$, determined by the time to complete one orbit rel

Filippo Revello, Gonzalo Villa

Cosmic (super)strings offer promising ways to test ideas about the early universe and physics at high energies. While in field theory constructions their tension is usually assumed to be constant (or at most slowly-varying), this is often not the case in the context of String Theory. Indeed, the tensions of both fundamental and field theory strings within a

Mohsin Iqbal, Anasuya Lyons, Chiu Fan Bowen Lo, Nathanan Tantivasadakarn

The development of programmable quantum devices can be measured by the complexity of manybody states that they are able to prepare. Among the most significant are topologically ordered states of matter, which enable robust quantum information storage and processing. While topological orders are more readily accessible with qudits, experimental realisations h

Filippo Camilloni, Luciano Rezzolla

Astronomical observations and numerical simulations are providing increasing evidence that resistive effects in plasmas around black holes play an important role in determining the phenomenology observed from these objects. In this spirit, we present a general approach to the study of a Penrose process driven by plasmoids that are produced at reconnection si

Samuel Leutheusser, Hong Liu

Field theories exhibit dramatic changes in the structure of their operator algebras in the limit where the number of local degrees of freedom ($N$) becomes infinite. An important example of this is that the algebras associated to local subregions may not be additively generated in the limit. We investigate examples and explore the consequences of this ``supe

Donghae Seo, Gil Young Cho, Robert-Jan Slager

We investigate the interplay between self-duality and spatially modulated symmetry of generalized $N$-state clock models, which include the transverse-field Ising model and ordinary $N$-state clock models as special cases. The spatially modulated symmetry of the model becomes trivial when the model's parameters satisfy a specific number-theoretic relation. W

Anasuya Lyons, Chiu Fan Bowen Lo, Nathanan Tantivasadakarn, Ashvin Vishwanath

Creating and manipulating anyons and symmetry defects in topological phases, especially those with a non-Abelian character, constitutes a primitive for topological quantum computation. We provide a physical protocol for implementing the ribbon operators of non-Abelian anyons and symmetry defects. We utilize dualities, in particular the Kramers-Wannier or gau

Raphaela Fernandes de Melo, Linda Lombardo, Arthur Alencastro Puls, Donatella Romano

Context. Carbon, nitrogen, and oxygen are the most abundant elements throughout the universe, after hydrogen and helium. Studying these elements in low-metallicity stars can provide crucial information on the chemical composition in the early Galaxy and possible internal mixing processes that can alter the surface composition of the stars. Aims. This work ai