March 2024 arXiv papers — page 160

Marc W. Buie, John R. Spencer, Simon B. Porter, Susan D. Benecchi

Following the Pluto fly-by of the New Horizons spacecraft, the mission provided a unique opportunity to explore the Kuiper Belt in-situ. The possibility existed to fly-by a Kuiper Belt object (KBO) as well as to observe additional objects at distances closer than are feasible from earth-orbit facilities. However, at the time of launch no KBOs were known abou

H. C. Rosu, J. de la Cruz

The singular parametric oscillators obtained from the one-parameter Darboux deformation/transformation effected upon the classical harmonic oscillator are introduced and discussed in some detail using sin(omega_0 t) and cos(omega_0 t) as seed solutions. The corresponding Ermakov-Lewis integrability problem of these parametric oscillators is also studied. It

Cheng Peng, Yutao Tang, Yifan Zhou, Nengyu Wang

Recent efforts in using 3D Gaussians for scene reconstruction and novel view synthesis can achieve impressive results on curated benchmarks; however, images captured in real life are often blurry. In this work, we analyze the robustness of Gaussian-Splatting-based methods against various image blur, such as motion blur, defocus blur, downscaling blur, \etc.

Zheng Zhang, Yuanwei Liu, Zhaolin Wang, Jian Chen

A novel near-field transmission framework is proposed for dynamic metasurface antenna (DMA)-enabled non-orthogonal multiple access (NOMA) networks. The base station (BS) exploits the hybrid beamforming to communicate with multiple near users (NUs) and far users (FUs) using the NOMA principle. Based on this framework, two novel beamforming schemes are propose

Xiang Li, Kai Qiu, Jinglu Wang, Xiaohao Xu

Referring perception, which aims at grounding visual objects with multimodal referring guidance, is essential for bridging the gap between humans, who provide instructions, and the environment where intelligent systems perceive. Despite progress in this field, the robustness of referring perception models (RPMs) against disruptive perturbations is not well e

Estelle Raveloaritiana, Thomas Cherico Wanger

Sustainable agriculture in the 21st century requires the production of sufficient food while reducing the environmental impact and safeguarding human livelihoods. Many studies have confirmed agricultural diversification practices such as intercropping, organic farming and soil inoculations as a suitable pathway to achieve these goals, but long-term viability

Obaid Ullah Ahmad, Anwar Said, Mudassir Shabbir, Waseem Abbas

In this paper, we study the problem of unsupervised graph representation learning by harnessing the control properties of dynamical networks defined on graphs. Our approach introduces a novel framework for contrastive learning, a widely prevalent technique for unsupervised representation learning. A crucial step in contrastive learning is the creation of 'au

Pablo Fernández, Miguel A. Martin-Delgado

We apply quantum homomorphic encryption (QHE) schemes suitable for circuits with a polynomial number of $T/T^{\dagger}$-gates to Grover's algorithm, performing a simulation in Qiskit of a Grover circuit that contains 3 qubits. The $T/T^{\dagger}$ gate complexity of Grover's algorithm is also analysed in order to show that any Grover circuit can be evaluated

João Maia

In this thesis, we present results on phase transition for two models: the semi-infinite Ising model with a decaying field, and the long-range Ising model with a random field. We study the semi-infinite Ising model with an external field $h_i = \lambda |i_d|^{-\delta}$, $\lambda$ is the wall influence, and $\delta>0$. This external field decays as it gets fu

Dong Sheng, Siyuan Jing, Xueqing He, Alexandra-Maria Klein

Biodiversity-associated ecosystem services such as pollination and biocontrol may be severely affected by emerging nano/micro-plastics (NMP) pollution. We synthesized the little-explored effects of NMP on pollinators and biocontrol agents on the organismal, farm and landscape scale. For instance ingested NMP trigger organismal changes from gene expression, o

Yizuo Chen, Adnan Darwiche

We study the identification of causal effects, motivated by two improvements to identifiability which can be attained if one knows that some variables in a causal graph are functionally determined by their parents (without needing to know the specific functions). First, an unidentifiable causal effect may become identifiable when certain variables are functi

Canran Wang, Jinwen Wang, Mi Zhou, Vinh Pham

Printer fingerprinting techniques have long played a critical role in forensic applications, including the tracking of counterfeiters and the safeguarding of confidential information. The rise of 3D printing technology introduces significant risks to public safety, enabling individuals with internet access and consumer-grade 3D printers to produce untraceabl

Allen George Philip, Zhongqiang Ren, Sivakumar Rathinam, Howie Choset

This paper introduces a new formulation that finds the optimum for the Moving-Target Traveling Salesman Problem (MT-TSP), which seeks to find a shortest path for an agent, that starts at a depot, visits a set of moving targets exactly once within their assigned time-windows, and returns to the depot. The formulation relies on the key idea that when the targe

Luigi Brugnano, Gianmarco Gurioli, Felice Iavernaro

In this paper we describe the efficient numerical implementation of Fractional HBVMs, a class of methods recently introduced for solving systems of fractional differential equations. The reported arguments are implemented in the Matlab code fhbvm, which is made available on the web. An extensive experimentation of the code is reported, to give evidence of it

Arkaprava Roy, Anindya Roy, Subhashis Ghosal

Time series data arising in many applications nowadays are high-dimensional. A large number of parameters describe features of these time series. We propose a novel approach to modeling a high-dimensional time series through several independent univariate time series, which are then orthogonally rotated and sparsely linearly transformed. With this approach,

Stylianos Kampakis, Melody Yuan, Oritsebawo Paul Ikpobe, Linas Stankevicius

In the evolving domain of cryptocurrency markets, accurate token valuation remains a critical aspect influencing investment decisions and policy development. Whilst the prevailing equation of exchange pricing model offers a quantitative valuation approach based on the interplay between token price, transaction volume, supply, and either velocity or holding t

Daniel Domínguez-Vázquez, Gustaaf B. Jacobs, Daniel M. Tartakovsky

Langevin (stochastic differential) equations are routinely used to describe particle-laden flows. They predict Gaussian probability density functions (PDFs) of a particle's trajectory and velocity, even though experimentally observed dynamics might be highly non-Gaussian. Our Liouville approach overcomes this dichotomy by replacing the Wiener process in the

Archit Chaturvedi

Photosynthesis is a fundamental process for plants to produce energy and survive. It is a well known fact that the light reactions in photosynthesis are a significant part of the overall process, and are carried out by chlorophyll molecules. This paper outlines the quantum chemical and mathematical description concerning electronic state transitions that tak

David Buch, Miheer Dewaskar, David B. Dunson

Classically, Bayesian clustering interprets each component of a mixture model as a cluster. The inferred clustering posterior is highly sensitive to any inaccuracies in the kernel within each component. As this kernel is made more flexible, problems arise in identifying the underlying clusters in the data. To address this pitfall, this article proposes a fun

Ruhong Jin, Nicolas Perkowski

We investigate fractional stochastic Navier-Stokes equations in $d\ge 3$, driven by the random force $(-\Delta)^{\frac{\theta}{2}}\xi$ which, as we show, corresponds to a fractional version of the Landau-Lifshitz random force in the physics literature. We obtain the existence and uniqueness of martingale solutions on the torus $\mathbb T^d$ for $\theta > \fr

Karan Muvvala, Andrew M. Wells, Morteza Lahijanian, Lydia E. Kavraki

As robots become more prevalent, the complexity of robot-robot, robot-human, and robot-environment interactions increases. In these interactions, a robot needs to consider not only the effects of its own actions, but also the effects of other agents' actions and the possible interactions between agents. Previous works have considered reactive synthesis, wher

Clayton Williams

We derive identities from Hecke operators acting on a family of Eisenstein-eta quotients, yielding congruences for their coefficients modulo powers of primes. As an application we derive systematic congruences for several higher-order smallest parts functions modulo prime powers, resolving a question of Garvan for these cases. We also relate moments of crank

Kaiwen Cai, Zhekai Duan, Gaowen Liu, Charles Fleming

Recent advancements in Vision-Language (VL) models have sparked interest in their deployment on edge devices, yet challenges in handling diverse visual modalities, manual annotation, and computational constraints remain. We introduce EdgeVL, a novel framework that bridges this gap by seamlessly integrating dual-modality knowledge distillation and quantizatio

Davor Dragicevic, Yeor Hafouta

We prove ``effective'' linear response for certain classes of non-uniformly expanding random dynamical systems which are not necessarily composed in an i.i.d manner. In applications, the results are obtained for base maps with a sufficient amount of mixing. The fact that the rates are effective is then applied to obtain the differentiability of the variance

Brent Lawson, Efrain Vidal, Michael M. Haley, Maria Kamenetska

We achieve, at room temperature, conductance enhancements over two orders of magnitude in single molecule circuits formed with polycyclic benzoquinoidal (BQn) diradicals upon increasing molecular length by ~0.5 nm. We find that this extreme and atypical anti-ohmic conductance enhancement at longer molecular lengths is due to the diradical character of the mo

Boris Aronov, Mark de Berg, Leonidas Theocharous

Let $d$ be a (well-behaved) shortest-path metric defined on a path-connected subset of $\mathbb{R}^2$ and let $\mathcal{D}=\{D_1,\ldots,D_n\}$ be a set of geodesic disks with respect to the metric $d$. We prove that $\mathcal{G}^{\times}(\mathcal{D})$, the intersection graph of the disks in $\mathcal{D}$, has a clique-based separator consisting of $O(n^{3/4+

Menglin Zhu, Michael Xu, Yu Yun, Liyan Wu

Switchable order parameters in ferroic materials are essential for functional electronic devices, yet disruptions of the ordering can take the form of planar boundaries or defects that exhibit distinct properties. Characterizing the structure of these boundaries is challenging due to their confined size and three-dimensional nature. Here, a chemical anti-pha

Hussein Behzadipour, Henk Koppelaar, Peyman Nasehpour

In this paper, we investigate semirings whose elements are either units or zero-divisors (nilpotents) with many examples. While comparing these semirings with their counterparts in ring theory, we observe that their behavior is different in many cases.

Shengyuan Hu, Saeed Mahloujifar, Virginia Smith, Kamalika Chaudhuri

Data-dependent privacy accounting frameworks such as per-instance differential privacy (pDP) and Fisher information loss (FIL) confer fine-grained privacy guarantees for individuals in a fixed training dataset. These guarantees can be desirable compared to vanilla DP in real world settings as they tightly upper-bound the privacy leakage for a $\textit{specif

Sona Pavlikova, Daniel Sevcovic

In this paper, we investigate the Moore-Penrose inversion of a simple connected graph. We analyze qualitative, statistical, and extreme properties of spectral indices of signable pseudo-invertible graphs. We introduce and analyze a wide class of signable pseudo-invertible simple connected graphs. It is a generalization of the classical concept of positively

Daniel Maschmann, Janice C. Lee, David A. Thilker, Bradley C. Whitmore

We present the largest catalog to-date of star clusters and compact associations in nearby galaxies. We have performed a V-band-selected census of clusters across the 38 spiral galaxies of the PHANGS-HST Treasury Survey, and measured integrated, aperture-corrected NUV-U-B-V-I photometry. This work has resulted in uniform catalogs that contain $\sim$20,000 cl

Jake Welde, Vijay Kumar

In this work, we address the design of tracking controllers that drive a mechanical system's state asymptotically towards a reference trajectory. Motivated by aerospace and robotics applications, we consider fully-actuated systems evolving on the broad class of homogeneous spaces (encompassing all vector spaces, Lie groups, and spheres of any finite dimensio

Rohith Peddi, Saksham Singh, Saurabh, Parag Singla

Spatio-temporal scene graphs represent interactions in a video by decomposing scenes into individual objects and their pair-wise temporal relationships. Long-term anticipation of the fine-grained pair-wise relationships between objects is a challenging problem. To this end, we introduce the task of Scene Graph Anticipation (SGA). We adapt state-of-the-art sc

William Keel, Alexei Moiseev, Roman Uklein, Aleksandrina Smirnova

We present the results of a search for Extended Emission-Line Regions (EELRs) ionized by extant or recently-faded active galactic nuclei (AGN), using [O III] narrowband imaging and spectroscopic followup. The sample includes 198 galaxies in 92 strongly interacting or merging galaxy systems in the range z=0.009-0.0285. Among these, three have EELRs extended b

Madeline C. Casas, Ky Putnam, Adam B. Mantz, Steven W. Allen

The most dynamically relaxed clusters of galaxies play a special role in cosmological studies as well as astrophysical studies of the intracluster medium (ICM) and active galactic nucleus feedback. While high spatial resolution imaging of the morphology of the ICM has long been the gold standard for establishing a cluster's dynamical state, such data are not

Nicolas Gauthier, Romain Sibille, Vladimir Pomjakushin, Øystein S. Fjellvåg

The control of magnetization using electric fields has been extensively studied in magnetoelectric multiferroic insulator materials. Changes in magnetization in bulk metals caused by electric currents have attracted less attention. The recently discovered metallic magnet Ce$_3$TiBi$_5$ has been reported to exhibit current-induced magnetization. Here we deter

Gabriel Currier, Shahriar Shahriari

Three $k$-dimensional subspaces $A$, $B$, and $C$ of an $n$-dimensional vector space $V$ over a finite field are called a $3$-cluster if $A \cap B \cap C = \{\mathbf{0}_V\}$ and yet $\dim(A+B+C) \leq 2k$. A special kind of $3$-cluster, which we call a covering triple, consists of subspaces $A,B,C$ such that $A = (A \cap B )\oplus (A \cap C)$. We prove that,

Savvas Petridis, Ben Wedin, Ann Yuan, James Wexler

Large language models (LLMs) are highly capable at a variety of tasks given the right prompt, but writing one is still a difficult and tedious process. In this work, we introduce ConstitutionalExperts, a method for learning a prompt consisting of constitutional principles (i.e. rules), given a training dataset. Unlike prior methods that optimize the prompt a

Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami

Independent evaluation and red teaming are critical for identifying the risks posed by generative AI systems. However, the terms of service and enforcement strategies used by prominent AI companies to deter model misuse have disincentives on good faith safety evaluations. This causes some researchers to fear that conducting such research or releasing their f

Shih Yu Chang, Yimin Wei

The original Choi-Davis-Jensen's inequality, with its wide-ranging applications in diverse scientific and engineering fields, has motivated researchers to explore generalizations. In this study, we extend Davis-Choi-Jensen's inequality by considering a nonlinear map instead of a normalized linear map and generalize operator convex function to any continuous

Evan C. Reed, Lu Qi, Kenneth R. Brown

Sideband cooling enables preparation of trapped ion motion near the ground state and is essential for many scientific and technological applications of trapped ion devices. Here, we study the efficiency of continuous and pulsed sideband cooling using both first- and second-order sidebands applied to an ion where the motion starts outside the Lamb-Dicke regim

Tracey Oellerich, Maria Emelianenko

Conservation laws are an inherent feature in many systems modeling real world phenomena, in particular, those modeling biological and chemical systems. If the form of the underlying dynamical system is known, linear algebra and algebraic geometry methods can be used to identify the conservation laws. Our work focuses on using data-driven methods to identify

Yassine Sekhmani, Dhruba Jyoti Gogoi, Ratbay Myrzakulov, Javlon Rayimbaev

This research paper presents a black hole solution with a rational non-linear electrodynamics source in the Rastall gravity framework. The paper analyzes the thermodynamic properties of the solution in normal phase space and explores its critical behavior. The phase structure is examined using the extended first law of thermodynamics, with the cosmological c

Andy Manapany, Sébastien Fumeron, Malte Henkel

The behaviour of the solutions of the time-fractional diffusion equation, based on the Caputo derivative, is studied and its dependence on the fractional exponent is analysed. The time-fractional convection-diffusion equation is also solved and an application to Pennes bioheat model is presented. Generically, a wave-like transport at short times passes over

Alexander E. Black

The existence of a pivot rule for the simplex method that guarantees a strongly polynomial run-time is a longstanding, fundamental open problem in the theory of linear programming. The leading pivot rule in theory is the shadow pivot rule, which solves a linear program by projecting the feasible region onto a polygon. It has been shown to perform in expected

Peter L. Walters, Joachim Tsakanikas, Fei Wang

Many physical and chemical processes in the condensed phase environment exhibit non-Markovian quantum dynamics. As such simulations are challenging on classical computers, we developed a variational quantum algorithm that is capable of simulating non-Markovian dynamics on NISQ devices. We used a quantum system linearly coupled to its harmonic bath as the mod

Guojin Chen, Hongquan He, Peng Xu, Hao Geng

Resolution Enhancement Techniques (RETs) are critical to meet the demands of advanced technology nodes. Among RETs, Source Mask Optimization (SMO) is pivotal, concurrently optimizing both the source and the mask to expand the process window. Traditional SMO methods, however, are limited by sequential and alternating optimizations, leading to extended runtime

Yuli Wu, Julian Wittmann, Peter Walter, Johannes Stegmaier

Implantable retinal prostheses offer a promising solution to restore partial vision by circumventing damaged photoreceptor cells in the retina and directly stimulating the remaining functional retinal cells. However, the information transmission between the camera and retinal cells is often limited by the low resolution of the electrode array and the lack of

Siyuan Xing, Efstathios G. Charalampidis

In this paper, we apply a machine-learning approach to learn traveling solitary waves across various families of partial differential equations (PDEs). Our approach integrates a novel interpretable neural network (NN) architecture, called Separable Gaussian Neural Networks (SGNN) into the framework of Physics-Informed Neural Networks (PINNs). Unlike the trad

Aosong Feng, Jialin Chen, Juan Garza, Brooklyn Berry

The high-resolution time series classification problem is essential due to the increasing availability of detailed temporal data in various domains. To tackle this challenge effectively, it is imperative that the state-of-the-art attention model is scalable to accommodate the growing sequence lengths typically encountered in high-resolution time series data,

Viet-Anh Le, Andreas A. Malikopoulos

In this work, we propose a framework for adapting the controller's parameters based on learning optimal solutions from contextual black-box optimization problems. We consider a class of control design problems for dynamical systems operating in different environments or conditions represented by contextual parameters. The overarching goal is to identify the

Aosong Feng, Weikang Qiu, Jinbin Bai, Xiao Zhang

Building on the success of text-to-image diffusion models (DPMs), image editing is an important application to enable human interaction with AI-generated content. Among various editing methods, editing within the prompt space gains more attention due to its capacity and simplicity of controlling semantics. However, since diffusion models are commonly pretrai

Andre Borgato Morelli, Andre Luiz Cunha

This study proposes a new approach to assessing urban accessibility using the competitive equilibrium method, an adaptation of the balancing cost method that incorporates competition among users into dual accessibility metrics. The need for this method arises from verifying the inability of the balancing cost method to measure the competitive dynamics of tra

Martin Raab

A new sequence in the spirit of the Mills primes is presented and its properties are investigated.

Jonathan Davies, Stefan Schacht, Nicola Skidmore, Amarjit Soni

In light of recently found deviations of the experimental data from predictions from QCD factorization for $B_{(s)}\rightarrow D_{(s)}P$ decays, where $P=\{\pi,K\}$, we systematically probe the current status of the SU(3)$_F$ expansion from a fit to experimental branching ratio data without any further theory input. We find that the current data are in agree

Karri I. I. Koljonen, Ioannis Liodakis, Elina Lindfors, Kari Nilsson

Supermassive black holes disrupt passing stars, producing outbursts called tidal disruption events (TDEs). TDEs have recently gained attention due to their unique dynamics and emission processes, which are still not fully understood. Especially, the so-called optical TDEs, are of interest as they often exhibit delayed or obscured X-ray emission from the accr

Paras Singh, Vishal Jaiswal, Subhrajit Roy, Aryan Tyagi

Savonius turbines, prominent in small-scale wind turbine applications operating under low-speed conditions, encounter limitations due to opposing torque on the returning blade, impeding high efficiency. A viable solution involves mitigating this retarding torque by directing incoming airflow through a cylindrical deflector. However, such flow control is high

Aleksandr Petrov, Craig Macdonald

Adaptations of Transformer models, such as BERT4Rec and SASRec, achieve state-of-the-art performance in the sequential recommendation task according to accuracy-based metrics, such as NDCG. These models treat items as tokens and then utilise a score-and-rank approach (Top-K strategy), where the model first computes item scores and then ranks them according t

Pasin Manurangsi

We consider the differentially private (DP) facility location problem in the so called super-set output setting proposed by Gupta et al. [SODA 2010]. The current best known expected approximation ratio for an $\epsilon$-DP algorithm is $O\left(\frac{\log n}{\sqrt{\epsilon}}\right)$ due to Cohen-Addad et al. [AISTATS 2022] where $n$ denote the size of the met

Amy X. Zhang, Parth Naidu

League of Legends (LoL) has been a dominant esport for a decade, yet the inherent complexity of the game has stymied the creation of analytical measures of player skill and performance. Current industry standards are limited to easy-to-procure individual player statistics that are incomplete and lacking context as they do not take into account teamplay or ga

Frances A. Laureano De Leon, Harish Tayyar Madabushi, Mark Lee

Code-switching is a prevalent linguistic phenomenon in which multilingual individuals seamlessly alternate between languages. Despite its widespread use online and recent research trends in this area, research in code-switching presents unique challenges, primarily stemming from the scarcity of labelled data and available resources. In this study we investig

Liana Patel, Peter Kraft, Carlos Guestrin, Matei Zaharia

Applications increasingly leverage mixed-modality data, and must jointly search over vector data, such as embedded images, text and video, as well as structured data, such as attributes and keywords. Proposed methods for this hybrid search setting either suffer from poor performance or support a severely restricted set of search predicates (e.g., only small

Shahrin Rahman

This paper optimizes the Convolutional Neural Network (CNN) algorithm using high-performance computing (HPC) technologies. It uses multi-core processors, GPUs, and parallel computing frameworks like OpenMPI and CUDA to speed up CNN model training. The approach improves performance and training time and is superior to alternative strategies. The study demonst

Kevin Tan, Ziping Xu

Hybrid Reinforcement Learning (RL), leveraging both online and offline data, has garnered recent interest, yet research on its provable benefits remains sparse. Additionally, many existing hybrid RL algorithms (Song et al., 2023; Nakamoto et al., 2023; Amortila et al., 2024) impose coverage assumptions on the offline dataset, but we show that this is unneces

ATLAS Collaboration

A measurement of the production of $W$ bosons with opposite electric charges in association with two jets is presented based on 140 fb$^{-1}$ of data collected by the ATLAS detector in proton-proton collisions at $\sqrt{s}=13$ TeV. The analysis is sensitive to the scattering of $W$ bosons, which is of particular interest in the ATLAS physics programme as it

Yajnaseni Dutta, Elham Izadi, Ljudmila Kamenova, Lisa Marquand

Lagrangian fibrations of hyperk\"ahler manifolds are induced by semi-ample line bundles which are isotropic with respect to the Beauville-Bogomolov-Fujiki form. For a non-isotrivial family of hyperk\"ahler manifolds over a complex manifold $S$ of positive dimension, we prove that the set of points in $S$, for which there is an isotropic class in the Picard l

Jan Schuchardt, Mihail Stoian, Arthur Kosmala, Stephan Günnemann

Amplification by subsampling is one of the main primitives in machine learning with differential privacy (DP): Training a model on random batches instead of complete datasets results in stronger privacy. This is traditionally formalized via mechanism-agnostic subsampling guarantees that express the privacy parameters of a subsampled mechanism as a function o

Marco D Alessandro, Enrique Calabrés, Mikel Elkano

Multimodal learning is a rapidly growing research field that has revolutionized multitasking and generative modeling in AI. While much of the research has focused on dealing with unstructured data (e.g., language, images, audio, or video), structured data (e.g., tabular data, time series, or signals) has received less attention. However, many industry-releva

Gabriele Campanella, Eugene Fluder, Jennifer Zeng, Chad Vanderbilt

Artificial Intelligence (AI) has great potential to improve health outcomes by training systems on vast digitized clinical datasets. Computational Pathology, with its massive amounts of microscopy image data and impact on diagnostics and biomarkers, is at the forefront of this development. Gigapixel pathology slides pose a unique challenge due to their enorm

Luís Fernando C. Pereira, Edilberto O. Silva

Potential applications of quantum dots in the nanotechnology industry make these systems an important field of study in various areas of physics. In particular, thermodynamics has a significant role in technological innovations. With this in mind, we studied some thermodynamic properties in quantum dots, such as entropy and heat capacity, as a function of th

Igor N. Ignashin, Demyan V. Yarmoshik

The paper presents various modifications of the Frank-Wolfe algorithm in the equilibrium traffic assignment problem. The Beckman model is used as a model for experiments. In this article, first of all, attention is paid to the choice of the direction of the basic step of the Frank-Wolfe algorithm. Algorithms will be presented: Conjugate Frank-Wolfe (CFW), Bi

Andrey Ryabichev, Konstantin Shcherbakov

The main result of the article says that the formal power series equal to the ratio of two neighboring Chebyshev polynomials, after some renormalization, approximates the generating function of the Catalan numbers. We present a proof of this result using continued fractions. Also, for completeness of the presentation, we recall the basic properties of Chebys

Bohan Liu, Zijie Zhang, Peixiong He, Zhensen Wang

The Lottery Ticket Hypothesis (LTH) states that a dense neural network model contains a highly sparse subnetwork (i.e., winning tickets) that can achieve even better performance than the original model when trained in isolation. While LTH has been proved both empirically and theoretically in many works, there still are some open issues, such as efficiency an

Hedy Attouch, Jalal Fadili, Vyacheslav Kungurtsev

In a real Hilbert space domain setting, we study the convergence properties of the stochastic Ravine accelerated gradient method for convex differentiable optimization. We consider the general form of this algorithm where the extrapolation coefficients can vary with each iteration, and where the evaluation of the gradient is subject to random errors. This ge

Akansh Maurya, Hewan Shrestha, Mohammad Munem Shahriar

With the limited availability of labeled data with various atmospheric conditions in remote sensing images, it seems useful to work with self-supervised algorithms. Few pretext-based algorithms, including from rotation, spatial context and jigsaw puzzles are not appropriate for satellite images. Often, satellite images have a higher temporal frequency. So, t

Sharon Levy, Tahilin Sanchez Karver, William D. Adler, Michelle R. Kaufman

Chat-based large language models have the opportunity to empower individuals lacking high-quality healthcare access to receive personalized information across a variety of topics. However, users may ask underspecified questions that require additional context for a model to correctly answer. We study how large language model biases are exhibited through thes

S. Abe, J. Abhir, A. Abhishek, F. Acero

Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the G

Marek Bojko, Preston McAfee, Renato Paes Leme, Balasubramanian Sivan

We study revenue variance in the sale of $k$ homogeneous items to risk-neutral, unit-demand bidders with independent private values. Although the Revenue Equivalence Theorem implies that standard auctions generate the same expected revenue, the distribution of revenue differs across mechanisms. Prior work shows that, in single-item environments with ex-post

Suman Halder, Yunho Shin, Yidan Peng, Long Wang

In the past decade, display technology has been reimagined to meet the needs of the virtual world. By mapping information onto a scene through a transparent display, users can simultaneously visualize both the real world and layers of virtual elements. However, advances in augmented reality (AR) technology have primarily focused on wearable gear or personal

V. Christiaens, M. Samland, Th. Henning, B. Portilla-Revelo

Context. Two protoplanets have recently been discovered within the PDS 70 protoplanetary disk. JWST/NIRCam offers a unique opportunity to characterize them and their birth environment at wavelengths difficult to access from the ground. Aims. We aim to image the circumstellar environment of PDS 70 at 1.87 $\mu$m and 4.83 $\mu$m, assess the presence of Pa-$\al

Stanislaw Kurdzialek, Piotr Dulian, Joanna Majsak, Sagnik Chakraborty

We develop an efficient algorithm for determining optimal adaptive quantum estimation protocols with arbitrary quantum control operations between subsequent uses of a probed channel. We introduce a tensor network representation of an estimation strategy, which drastically reduces the time and memory consumption of the algorithm, and allows us to analyze metr

Christoph Dlapa, Gregor Kälin, Zhengwen Liu, Rafael A. Porto

Leveraging scattering information to describe binary systems in generic orbits requires identifying local- and nonlocal-in-time tail effects. We report here the derivation of the universal (non-spinning) local-in-time conservative dynamics at fourth Post-Minkowskian order, i.e. ${\cal O}(G^4)$. This is achieved by computing the nonlocal-in-time contribution

Bing He, Yingchen Ma, Mustaque Ahamad, Srijan Kumar

Online misinformation poses a global risk with harmful implications for society. Ordinary social media users are known to actively reply to misinformation posts with counter-misinformation messages, which is shown to be effective in containing the spread of misinformation. Such a practice is defined as "social correction". Nevertheless, it remains unknown ho

Hans Gløckner Giil, Bjørnulf Brekke, Jacob Linder, Arne Brataas

Conducting altermagnets have recently emerged as intriguing materials supporting strongly spin-polarized currents without magnetic stray fields. We demonstrate that altermagnets enable three key functionalities, merging superconductivity and spintronics. The first prediction is a controllable supercurrent-induced edge magnetization, which acts like a dissipa

H. R. Stacey, D. M. Powell, S. Vegetti, J. P. McKean

The large-scale mass distributions of galaxy-scale strong lenses have long been assumed to be well-described by a singular ellipsoidal power-law density profile with external shear. However, the inflexibility of this model could lead to systematic errors in astrophysical parameters inferred with gravitational lensing observables. Here, we present observation

Heleno S. Cunha, Lucas H. R. de Souza, Sergio A. P. Prado

In this article we study, in their non-Euclidean versions, two important mechanical systems that are very common in numerous devices. More precisely, we study the laws governing the movement of pulley and gear systems in spherical and hyperbolic geometries. And curiously, we were able to see an interesting similarity between the determined laws.

Marcos A. G. Garcia, Aline Pereyra-Flores

The prediction of a nearly scale-invariant spectrum of curvature and tensor fluctuations is among the main features of cosmic inflation. The current measurements of the primordial fluctuations in the cosmic microwave background (CMB) provide tight constraints on the amplitude of the scalar and tensor spectra, and the scalar tilt. However, the precise connect

Peimeng Guan, Naveed Iqbal, Mark A. Davenport, Mudassir Masood

Model-based deep learning methods such as loop unrolling (LU) and deep equilibrium model}(DEQ) extensions offer outstanding performance in solving inverse problems (IP). These methods unroll the optimization iterations into a sequence of neural networks that in effect learn a regularization function from data. While these architectures are currently state-of

Oscar Garcia-Montero, Philip Plaschke, Sören Schlichting

We use QCD kinetic theory to compute dilepton production coming from the pre-equilibrium phase of the Quark-Gluon Plasma created in high-energy heavy-ion collisions. We demonstrate that the dilepton spectrum exhibits a simple scaling in terms of the specific shear viscosity $\eta/s$ and entropy density $dS/d\zeta \sim {\scriptstyle \left(T\tau^{1/3}\right)_\

Jakub Czartowski, A. de Oliveira Junior

What are the fundamental limits and advantages of using a catalyst to aid thermodynamic transformations between quantum systems? In this work, we answer this question by focusing on transformations between energy-incoherent states under the most general energy-conserving interactions among the system, the catalyst, and a thermal environment. The sole constra

Chae-Yeun Park, Minhyeok Kang, Joonsuk Huh

Variational quantum circuits have recently gained much interest due to their relevance in real-world applications, such as combinatorial optimizations, quantum simulations, and modeling a probability distribution. Despite their huge potential, the practical usefulness of those circuits beyond tens of qubits is largely questioned. One of the major problems is

Pablo Sala, Sara Murciano, Yue Liu, Jason Alicea

Entanglement, measurement, and classical communication together enable teleportation of quantum states between distant parties, in principle with perfect fidelity. To what extent do correlations and entanglement of a many-body wavefunction transfer under imperfect teleportation protocols? We address this question for the case of an imperfectly teleported qua

A. de Oliveira Junior, Jeongrak Son, Jakub Czartowski, Nelly H. Y. Ng

We investigate the thermodynamic constraints on the pivotal task of entanglement generation using out-of-equilibrium states through a model-independent framework with minimal assumptions. We establish a necessary and sufficient condition for a thermal process to generate bipartite qubit entanglement, starting from an initially separable state. Consequently,

Harry Buhrman, Jonas Helsen, Jordi Weggemans

We define a general formulation of quantum PCPs, which captures adaptivity and multiple unentangled provers, and give a detailed construction of the quantum reduction to a local Hamiltonian with a constant promise gap. The reduction turns out to be a versatile subroutine to prove properties of quantum PCPs, allowing us to show: (i) Non-adaptive quantum PCPs

Michael K. Plummer, Ji Wang, Étienne Artigau, René Doyon

Planetary-mass objects and brown dwarfs at the transition ($\rm{T}_{eff}\sim1300$\,K) from relatively red L dwarfs to bluer mid-T dwarfs show enhanced spectrophotometric variability. Multi-epoch observations support atmospheric planetary-scale (Kelvin or Rossby) waves as the primary source of this variability; however, large spots associated with the precipi

Niusha Ahvazi, Laura V. Sales, Julio F. Navarro, Andrew Benson

We study the fraction of the intra-cluster light (ICL) formed in-situ in the three most massive clusters of the TNG50 simulation, with virial masses $\sim 10^{14}$ M$_{\odot}$. We find that a significant fraction of ICL stars ($8\%$-$28\%$) are born in-situ. This amounts to a total stellar mass comparable to the central galaxy itself. Contrary to simple expe

Sambit K. Giri, Michele Bianco, Timothée Schaeffer, Ilian T. Iliev

During the epoch of reionization (EoR), the 21-cm signal allows direct observation of the neutral hydrogen (HI) in the intergalactic medium (IGM). In the post-reionization era, this signal instead probes HI in galaxies, which traces the dark matter density distribution. With new numerical simulations, we investigated the end stages of reionization to elucida

Thomas P. Wytock, Adilson E. Motter

Recent developments in synthetic biology, next-generation sequencing, and machine learning provide an unprecedented opportunity to rationally design new disease treatments based on measured responses to gene perturbations and drugs to reprogram cells. The main challenges to seizing this opportunity are the incomplete knowledge of the cellular network and the

Sebastian Steinhaus

Monte Carlo algorithms are barely considered in spin foam quantum gravity. Due to the quantum nature of spin foam amplitudes one cannot readily apply them, and the present sign problem is a threat to convergence and thus efficiency. Yet, ultimately the severity of the sign problem in spin foams is not known. In this article we propose a new probability distr

Christian Copetti, Lucia Cordova, Shota Komatsu

We show that crossing symmetry of S-matrices is modified in certain theories with non-invertible symmetries or anomalies. Focusing on integrable flows to gapped phases in two dimensions, we find that S-matrices derived previously from the bootstrap approach are incompatible with non-invertible symmetries along the flow. We present consistent alternatives, wh