March 2023 arXiv papers — page 143

Kai Diethelm, Frank Uhlig

For terminal value problems of fractional differential equations of order $\alpha \in (0,1)$ that use Caputo derivatives, shooting methods are a well developed and investigated approach. Based on recently established analytic properties of such problems, we develop a new technique to select the required initial values that solves such shooting problems quick

Shintaro Minagawa, Hayato Arai

With the recent development of quantum information theory, some attempts exist to construct information theory beyond quantum theory. Here we consider hypothesis testing relative entropy and one-shot classical capacity, that is, the optimal rate of classical information transmitted by using a single channel under a constraint of a certain error probability,

Cheng Chi, Zhenjia Xu, Siyuan Feng, Eric Cousineau

This paper introduces Diffusion Policy, a new way of generating robot behavior by representing a robot's visuomotor policy as a conditional denoising diffusion process. We benchmark Diffusion Policy across 12 different tasks from 4 different robot manipulation benchmarks and find that it consistently outperforms existing state-of-the-art robot learning metho

Gabriele Tiboni, Andrea Protopapa, Tatiana Tommasi, Giuseppe Averta

Soft robots are gaining popularity thanks to their intrinsic safety to contacts and adaptability. However, the potentially infinite number of Degrees of Freedom makes their modeling a daunting task, and in many cases only an approximated description is available. This challenge makes reinforcement learning (RL) based approaches inefficient when deployed on a

V. Lopez-Richard, S. Pradhan, R. S. Wengenroth Silva, O. Lipan

Basic multimode impedance analysis grounded in the availability of nonequilibrium charge carriers and their retarded path towards equilibrium is used to access the inadequacy of equivalent circuits in nonlinear systems with inherent memory. On the basic grounds of generation and recombination (or trapping) of nonequilibrium carriers and their relaxation time

Masoud Akbari, Ali Mohades, M. Hassan Shirali-Shahreza

Intent Detection is one of the tasks of the Natural Language Understanding (NLU) unit in task-oriented dialogue systems. Out of Scope (OOS) and Out of Domain (OOD) inputs may run these systems into a problem. On the other side, a labeled dataset is needed to train a model for Intent Detection in task-oriented dialogue systems. The creation of a labeled datas

Nicholas V. Proscia, Michael A. Meeker, Nicholas Sharac, Frank K. Perkins

Metal-Insulator-Metal (MIM) plasmonic structures can confine electromagnetic waves to a deep subwavelength regime, enabling strong light-matter interactions with potential applications in nonlinear optics and on-chip photonic circuitry. In addition, strong coupling of mid-infrared (mid-IR) vibrational transitions to optical cavities provides a way to modify

Martin Josifoski, Marija Sakota, Maxime Peyrard, Robert West

Large language models (LLMs) have great potential for synthetic data generation. This work shows that useful data can be synthetically generated even for tasks that cannot be solved directly by LLMs: for problems with structured outputs, it is possible to prompt an LLM to perform the task in the reverse direction, by generating plausible input text for a tar

W. H. S. Brandão, J. M. De Sousa, A. L. Aguiar, D. S. Galvão

Pentahexoctite (PH) is a pure sp$^2$ hybridized planar carbon allotrope whose structure consists of a symmetric combination of pentagons, hexagons, and octagons. The proposed PH structure was shown to be an intrinsically metallic material exhibiting good mechanical and thermal stability. PH nanotubes (PHNTs) have also been proposed, and their properties were

Sherry Yang, Ofir Nachum, Yilun Du, Jason Wei

Foundation models pretrained on diverse data at scale have demonstrated extraordinary capabilities in a wide range of vision and language tasks. When such models are deployed in real world environments, they inevitably interface with other entities and agents. For example, language models are often used to interact with human beings through dialogue, and vis

Tamara Bottazzi, Alejandro Varela

We define the (convex) joint numerical range for an infinite family of compact operators in a Hilbert space H. We use this set to determine whether a self-adjoint compact operator A with {||A||, -||A||} in its spectrum is minimal respect to the set of diagonals in a fixed basis E of H in the operator norm, that is ||A|| <= ||A+D||, for all diagonal D. We als

Alberto Chiarini, Simone Floreani, Federico Sau

Consider a random walk on $\mathbb{Z}^d$ in a translation-invariant and ergodic random environment and starting from the origin. In this short note, assuming that a quenched invariance principle for the opportunely-rescaled walks holds, we show how to derive an $L^1$-convergence of the corresponding semigroups. We then apply this result to obtain a quenched

Eugeny Babichev, Christos Charmousis, Mokhtar Hassaine, Nicolas Lecoeur

Starting from a generalised Kaluza-Klein action including arbitrary Horndeski potentials, we establish integrability and compatibility conditions that solve the generic field equations for spherical symmetry. The resulting theories can be identified as general Horndeski theories having no apparent symmetries in four dimensions or as effective string theory a

Wentao Yang

This paper is a contribution to "neo-stability" type of result for abstract elementary classes. Under certain set theoretic assumptions, we propose a definition and a characterization of NIP in AECs. The class of AECs with NIP properly contains the class of stable AECs. We show that for an AEC $K$ and $\lambda\geq LS(K)$, $K_\lambda$ is NIP if and only if th

Filippo Bigi, Sergey N. Pozdnyakov, Michele Ceriotti

Machine-learning models based on a point-cloud representation of a physical object are ubiquitous in scientific applications and particularly well-suited to the atomic-scale description of molecules and materials. Among the many different approaches that have been pursued, the description of local atomic environments in terms of their neighbor densities has

Sajani Vithana, Sennur Ulukus

In federated learning (FL), a machine learning (ML) model is collectively trained by a large number of users, using their private data in their local devices. With top $r$ sparsification in FL, the users only upload the most significant $r$ fraction of updates, and the servers only send the most significant $r'$ fraction of parameters to the users in order t

José L. Cereceda

For integer $k \geq 0$, let $S_k$ denote the sum of the $k$th powers of the first $n$ positive integers $1^k + 2^k + \cdots + n^k$. For any given $k$, the power sum $S_k$ can in principle be determined by differentiating $k$ times (with respect to $x$) the associated exponential generating function $\sum_{k=0}^{\infty}S_k x^k/k!$, and then taking the limit o

Almut E. D. Veraart

This article introduces the class of periodic trawl processes, which are continuous-time, infinitely divisible, stationary stochastic processes, that allow for periodicity and flexible forms of their serial correlation, including both short- and long-memory settings. We derive some of the key probabilistic properties of periodic trawl processes and present r

Mikhail Borovoi, Tasho Kaletha, Vladimir Hinich

We give closed formulas for the abelian Galois cohomology groups H^1_{ab}(F,G) and H^2_{ab}(F,G) of a connected reductive group G over a global field F in terms of the algebraic fundamental group \pi_1(G) introduced earlier by one of us (M.B.). We further give closed formulas for the effects of restriction, corestriction, and localization, in terms of these

R. Avalos, P. Bargueño, E. Contreras

In this work we construct a static and spherically symmetric black hole geometry supported by a family of generic mono-parametric sources thorough the Gravitational Decoupling. The parameter characterizing the matter sector can be interpreted as hair which cannot be associated to any global charge. Although the solution is constructed by demanding the weak e

Nick Bührer, Zhejun Zhang, Alexander Liniger, Fisher Yu

An emerging field of sequential decision problems is safe Reinforcement Learning (RL), where the objective is to maximize the reward while obeying safety constraints. Being able to handle constraints is essential for deploying RL agents in real-world environments, where constraint violations can harm the agent and the environment. To this end, we propose a s

Muhammad Aurangzeb Ahmad, Vijay Chickarmane, Farinaz Sabz Ali Pour, Nima Shariari

Recently there has been a surge of interest in developing Digital Twins of process flows in healthcare to better understand bottlenecks and areas of improvement. A key challenge is in the validation process. We describe a work in progress for a digital twin using an agent based simulation model for determining bed turnaround time for patients in hospitals. W

Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu

Data-driven simulation has become a favorable way to train and test autonomous driving algorithms. The idea of replacing the actual environment with a learned simulator has also been explored in model-based reinforcement learning in the context of world models. In this work, we show data-driven traffic simulation can be formulated as a world model. We presen

Hong Yang, William Gebhardt, Alexander G. Ororbia, Travis Desell

Out-of-distribution (OOD) inputs can compromise the performance and safety of real world machine learning systems. While many methods exist for OOD detection and work well on small scale datasets with lower resolution and few classes, few methods have been developed for large-scale OOD detection. Existing large-scale methods generally depend on maximum class

Ziqiao Ao, Sahel Ashhab, Fumiki Yoshihara, Tomoko Fuse

We report experimental and theoretical results on the extremely large Lamb shift in a multimode circuit quantum electrodynamics (QED) system in the deep-strong coupling (DSC) regime, where the qubit-resonator coupling strength is comparable to or larger than the qubit and resonator frequencies. The system comprises a superconducting flux qubit (FQ) and a qua

Daniel McGinnis

We give a combinatorial formula for the Ehrhart coefficients of a certain class of weighted multi-hypersimplices. In a special case, where these polytopes coincide with the base polytope of the panhandle matroid $\textrm{Pan}_{k,n-2,n}$, we show that the Ehrhart coefficients are positive.

Ivan D. Chipchakov, Boyan Paunov

Let $\mathbb{P}$ be the set of prime numbers, $\overline {\mathbb{P}}$ the union $\mathbb{P} \cup \{0\}$, and for any field $E$, let char$(E)$ be its characteristic, ddim$(E)$ the Diophantine dimension of $E$, $\mathcal{G}_{E}$ the absolute Galois group of $E$, and cd$(\mathcal{G}_{E})$ the Galois cohomological dimension $\mathcal{G}_{E}$. The research prese

Shaoyun Wang, Zhou Hu, Qian Wu, Hui Chen

Topological pumping supplies a robust mechanism to steer waves across a sample without being affected by disorders and defects. For the first time, we demonstrate the pumping of elastic surface waves, achieved by a smart patterning of a surface that creates a synthetic dimension, which is explored by the wave as it is launched perpendicularly to the steering

Christine D. Wilson, Ashley Bemis, Blake Ledger, Osvald Klimi

We investigate the relationship between CN N = 1 - 0 and HCN J = 1 - 0 emission on scales from 30 pc to 400 pc using ALMA archival data, for which CN is often observed simultaneously with the CO J = 1 - 0 line. In a sample of 9 nearby galaxies ranging from ultra-luminous infrared galaxies to normal spiral galaxies, we measure a remarkably constant CN/HCN lin

B. Steltner, M. A. Papa, H. -B. Eggenstein, R. Prix

We present the results of an all-sky search for continuous gravitational waves in the public LIGO O3 data. The search covers signal frequencies $20$ Hz $\leq f \leq 800$ Hz and a spin-down range down to $-2.6\times 10^{-9}$ Hz s$^{-1}$1, motivated by detectability studies on synthetic populations of Galactic neutron stars. This search is the most sensitive a

Jinchen Han, Henry T. Aller, Alan J. H. McGaughey

In this study, we added vacancies adjacent to a Si/Ge interface to create a disordered structure. The structure was then relaxed using various strategies. We applied Procrustes shape analysis for disorder quantification and identifying different local atomic environments.

Burkhard Kleihaus, Jutta Kunz, Tim Utermöhlen, Emanuele Berti

The addition of a Ricci coupling to Einstein-scalar-Gauss-Bonnet theories makes general relativity a cosmological attractor. Previous work considered a quadratic coupling function with two independent coupling constants in such theories and showed that static, spherically symmetric, spontaneously scalarized black holes are radially stable beyond a critical v

Lev Buhovsky, Maksim Stokić

On a closed and connected symplectic manifold, the group of Hamiltonian diffeomorphisms has the structure of an infinite-dimensional Fr\'echet Lie group, where the Lie algebra is naturally identified with the space of smooth and zero-mean normalized functions, and the adjoint action is given by pullbacks. We show that this action is flexible: for every non-z

Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek

We propose InCA, a lightweight method for transfer learning that cross-attends to any activation layer of a pre-trained model. During training, InCA uses a single forward pass to extract multiple activations, which are passed to external cross-attention adapters, trained anew and combined or selected for downstream tasks. We show that, even when selecting a

Dat Ngo, Lam Pham, Huy Phan, Minh Tran

This paper presents a deep learning system applied for detecting anomalies from respiratory sound recordings. Initially, our system begins with audio feature extraction using Gammatone and Continuous Wavelet transformation. This step aims to transform the respiratory sound input into a two-dimensional spectrogram where both spectral and temporal features are

Nikhil Sheoran, Supawit Chockchowwat, Arav Chheda, Suwen Wang

For exploratory data analysis, it is often desirable to know what answers you are likely to get before actually obtaining those answers. This can potentially be achieved by designing systems to offer the estimates of a data operation result -- say op(data) -- earlier in the process based on partial data processing. Those estimates continuously refine as more

Wenjie Hu, Tomás Caraballo

The main purpose of this work is to characterize the almost sure local structure stability of solutions to a class of linear stochastic partial functional differential equations (SPFDEs) by investigating the Lyapunov exponents and invariant manifolds near the stationary point. It is firstly proved that the trajectory field of the stochastic delayed stochasti

Md Deluair Hossen

The vast literature on exchange rate fluctuations estimates the exchange rate pass-through (ERPT). Most ERPT studies consider annually aggregated data for developed or large developing countries for estimating ERPT. These estimates vary widely depending on the type of country, data coverage, and frequency. However, the ERPT estimation using firm-level high-f

Akshay Agarwal, Minxu Peng, Vivek K. Goyal

Particle beam microscopy (PBM) performs nanoscale imaging by pixelwise capture of scalar values representing noisy measurements of the response from secondary electrons (SEs) integrated over a dwell time. Extended to metrology, goals include estimating SE yield at each pixel and detecting differences in SE yield across pixels; obstacles include shot noise in

Juan Carlos Criado, Peter D. Hatton, Álvaro Lanza, Sebastian Schenk

Chiral magnets with Dzyaloshinskii-Moriya interactions feature a rich phase diagram with a variety of thermodynamical phases. These include helical and conical spin arrangements and topologically charged objects such as (anti)skyrmions. Crucially, due to hysteresis effects, the thermodynamical phases can co-exist at any given temperature and external magneti

Nathan R. Sandford, Daniel R. Weisz, Yuan-Sen Ting

Large-scale surveys will provide spectroscopy for $\sim$50 million resolved stars in the Milky Way and Local Group. However, these data will have a high degree of heterogeneity and most will be low-resolution ($R<10000$), posing challenges to measuring consistent and reliable stellar labels. Here, we introduce a framework for identifying and remedying these

Nikolay Kolomeec, Ivan Sutormin, Denis Bykov, Matvey Panferov

Properties of the additive differential probability $\mathrm{adp}^{\mathrm{XR}}$ of the composition of bitwise XOR and a bit rotation are investigated, where the differences are expressed using addition modulo $2^n$. This composition is widely used in ARX constructions consisting of additions modulo $2^n$, bit rotations and bitwise XORs. Differential cryptan

Wei Xi, Yongxin Zhang, Changnan Xiao, Xuefeng Huang

Deep Reinforcement Learning combined with Fictitious Play shows impressive results on many benchmark games, most of which are, however, single-stage. In contrast, real-world decision making problems may consist of multiple stages, where the observation spaces and the action spaces can be completely different across stages. We study a two-stage strategy card

Maciej P. Polak, Dane Morgan

There has been a growing effort to replace manual extraction of data from research papers with automated data extraction based on natural language processing, language models, and recently, large language models (LLMs). Although these methods enable efficient extraction of data from large sets of research papers, they require a significant amount of up-front

Hang Qi, Ning Jia, Xiaobo Qu, Zhengbing He

To explain day-to-day (DTD) route-choice behaviors and traffic dynamics observed in a series of lab experiments, Part I of this research proposed a discrete choice-based analytical dynamic model (Qi et al., 2023). Although the deterministic model could well reproduce the experimental observations, it converges to a stable equilibrium of route flow while the

Wenjie Hu, Tomás Caraballo

The main objective of this paper is to obtain estimations of Hausdorff dimension as well as fractal dimension of global attractors and pullback attractors for both autonomous and nonautonomous functional differential equations (FDEs) in Banach spaces. New criterions for the finite Hausdorff dimension and fractal dimension of attractors in Banach spaces are f

Jeffrey Kegler

The Marpa parser was intended to make the best results in the academic literature on Earley's algorithm available as a practical general parser. Earley-based parsers have had issues handling nullable symbols. Initially, we dealt with nullable symbols by following the approach in Aycock and Horspool's 2002 paper. This paper reports our experience with the app

Ruochen Zhang, Carsten Eickhoff

Cross-lingual summarization (CLS) has attracted increasing interest in recent years due to the availability of large-scale web-mined datasets and the advancements of multilingual language models. However, given the rareness of naturally occurring CLS resources, the majority of datasets are forced to rely on translation which can contain overly literal artifa

Giacomo Camposampiero, Loic Houmard, Benjamin Estermann, Joël Mathys

While artificial intelligence (AI) models have achieved human or even superhuman performance in many well-defined applications, they still struggle to show signs of broad and flexible intelligence. The Abstraction and Reasoning Corpus (ARC), a visual intelligence benchmark introduced by Fran\c{c}ois Chollet, aims to assess how close AI systems are to human-l

Tuomo Tanttu, Wee Han Lim, Jonathan Y. Huang, Nard Dumoulin Stuyck

Achieving high-fidelity entangling operations between qubits consistently is essential for the performance of multi-qubit systems and is a crucial factor in achieving fault-tolerant quantum processors. Solid-state platforms are particularly exposed to errors due to materials-induced variability between qubits, which leads to performance inconsistencies. Here

Robin Fynn Diedrichs, Niklas Becker, Cédric Jockel, Jan-Erik Christian

In this work we investigate the tidal deformability of a neutron star admixed with dark matter, modeled as a massive, self-interacting, complex scalar field. We derive the equations to compute the tidal deformability of the full Einstein-Hilbert-Klein-Gordon system self-consistently, and probe the influence of the scalar field mass and self-interaction stren

Hang Qi, Ning Jia, Xiaobo Qu, Zhengbing He

In the area of urban transportation networks, a growing number of day-to-day (DTD) traffic dynamic theories have been proposed to describe the network flow evolution, and an increasing amount of laboratory experiments have been conducted to observe travelers' behavior regularities. However, the "communication" between theorists and experimentalists has not b

Haimin Luo, Siyuan Zhang, Fuqiang Zhao, Haotian Jing

We have recently seen tremendous progress in neural rendering (NR) advances, i.e., NeRF, for photo-real free-view synthesis. Yet, as a local technique based on a single computer/GPU, even the best-engineered Instant-NGP or i-NGP cannot reach real-time performance when rendering at a high resolution, and often requires huge local computing resources. In this

Dave Witte Morris, Joy Morris

A finite group $G$ is a "non-DCI group" if there exist subsets $S_1$ and $S_2$ of $G$, such that the associated Cayley digraphs $C\overrightarrow{ay}(G;S_1)$ and $C\overrightarrow{ay}(G;S_2)$ are isomorphic, but no automorphism of $G$ carries $S_1$ to $S_2$. Furthermore, $G$ is a "non-CI group" if the subsets $S_1$ and $S_2$ can be chosen to be closed under

Sk Golam Saroar, Maleknaz Nayebi

GitHub introduced "Actions" in 2019 to increase workflow velocity and add customized automation to the repositories. Any individual can develop Actions for automating workflow on GitHub repositories and others can reuse them whenever open source. GitHub introduced its marketplace for commercializing and sharing these automation tools, which currently hosts 1

Theodosis Alexandrou

We show that for any integer $n\geq2$ there is a smooth complex projective variety $X$ of dimension $5$ whose third Griffiths group $\text{Griff}^{3}(X)$ contains infinitely many torsion elements of order $n$. This generalises a recent theorem of Schreieder who proved the result for $n=2$.

Stefan Floerchinger

An exact functional renormalization group flow equation is derived for the divergence functional which is a generalization of the Kullback-Leibler divergence to quantum field theories in the Euclidean domain. It compares distributions with different sources and field expectation values. The renormalization group flow for a regularized version of this functio

Stefan Floerchinger

Information geometry provides differential geometric concepts like a Riemannian metric, connections and covariant derivatives on spaces of probability distributions. We discuss here how these concepts apply to quantum field theories in the Euclidean domain which can also be seen as statistical field theories. The geometry has a dual affine structure correspo

Luciano Baresi, Giovanni Quattrocchi, Nicholas Rasi

Containerization is a virtualization technique that allows one to create and run executables consistently on any infrastructure. Compared to virtual machines, containers are lighter since they do not bundle a (guest) operating system but they share its kernel, and they only include the files, libraries, and dependencies that are required to properly execute

Helena Bergold, Stefan Felsner, Manfred Scheucher

In 1926, Levi showed that, for every pseudoline arrangement $\mathcal{A}$ and two points in the plane, $\mathcal{A}$ can be extended by a pseudoline which contains the two prescribed points. Later extendability was studied for arrangements of pseudohyperplanes in higher dimensions. While the extendability of an arrangement of proper hyperplanes in $\mathbb{R

Aparajithan Nathamuni-Venkatesan, Ram-Venkat Narayanan, Kishore Pula, Sundarakumar Muthukumaran

Reverse engineering of FPGA based designs from the flattened LUT level netlist to high level RTL helps in verification of the design or in understanding legacy designs. We focus on flattened netlists for FPGA devices from Xilinx 7 series and Zynq 7000. We propose a design element grouping algorithm that makes use of the location information of the elements o

Minyoung Hwang, Jaeyeon Jeong, Minsoo Kim, Yoonseon Oh

The main challenge in vision-and-language navigation (VLN) is how to understand natural-language instructions in an unseen environment. The main limitation of conventional VLN algorithms is that if an action is mistaken, the agent fails to follow the instructions or explores unnecessary regions, leading the agent to an irrecoverable path. To tackle this prob

Matthew Cavorsi, Orhan Eren Akgün, Michal Yemini, Andrea Goldsmith

We develop a resilient binary hypothesis testing framework for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations between robots to arrive at tractable, resilient decision making at a centralized Fusion Center (FC) even when i) there exist malicious robots in the network and their number may b

Sanjana Ramprasad, Denis Jered McInerney, Iain J. Marshal, Byron C. Wallace

We present TrialsSummarizer, a system that aims to automatically summarize evidence presented in the set of randomized controlled trials most relevant to a given query. Building on prior work, the system retrieves trial publications matching a query specifying a combination of condition, intervention(s), and outcome(s), and ranks these according to sample si

Alexander Hensley, Thomas E. Videbaek, Hunter Seyforth, William M. Jacobs

Photonic crystals -- a class of materials whose optical properties derive from their structure in addition to their composition -- can be created by self-assembling particles whose sizes are comparable to the wavelengths of visible light. Proof-of-principle studies have shown that DNA can be used to guide the self-assembly of micrometer-sized colloidal parti

Qiong Liu, Tianzhu Zhang, Masoud Hemmatpour, Han Qiu

Modern Artificial Intelligence (AI) technologies, led by Machine Learning (ML), have gained unprecedented momentum over the past decade. Following this wave of "AI summer", the network research community has also embraced AI/ML algorithms to address many problems related to network operations and management. However, compared to their counterparts in other d

Steven Pakiela, Brett Bolen, Ben Holder, Monica Rizzo

Gravitational wave astronomy is an emerging observational discipline that expands the astrophysical messengers astronomers can use to probe cosmic phenomena. The gravitational waveform from a source encodes the astrophysical properties and the dynamical motion of mass within the system; this is particularly evident in the case of binaries, where the overall

Łukasz Kosiński, Nikolai Nikolov, Pascal J. Thomas

We prove that in a strongly pseudoconvex domain with smooth boundary, then the length of a geodesic for the Kobayashi-Royden infinitesimal metric between two points is bounded by a constant multiple of the Euclidean distance between the points.

Yiduo Huang, Zuojun Shen

Express companies are deploying more robotic sorting systems, where mobile robots are used to sort incoming parcels by destination. In this study, we propose an integrated assignment and path-finding method for robots in such sorting systems. The method has two parts: offline and online. In the offline part, we represent the system as a traffic flow network,

Céline Bonnet, Hélène Leman

The aim of this article is to study the impact of resistance acquisition on the distribution of neutral mutations in a cell population under therapeutic pressure. The cell population is modeled by a bi-type branching process. Initially, the cells all carry type 0, associated with a negative growth rate. Mutations towards type $1$ are assumed to be rare and r

Eli Sennesh, Tom Xu, Yoshihiro Maruyama

Category theory has been successfully applied in various domains of science, shedding light on universal principles unifying diverse phenomena and thereby enabling knowledge transfer between them. Applications to machine learning have been pursued recently, and yet there is still a gap between abstract mathematical foundations and concrete applications to ma

Wenjie Hu, Tomás Caraballo

The aim of this paper is to propose a new method to construct exponential attractors for infinite dimensional dynamical systems in Banach spaces with explicit fractal dimension. The approach is established by combing the squeezing properties and the covering of finite subspace of Banach spaces, which generalize the method established in Hilbert spaces. The c

Maureen Daum, Enhao Zhang, Dong He, Stephen Mussmann

We introduce VOCALExplore, a system designed to support users in building domain-specific models over video datasets. VOCALExplore supports interactive labeling sessions and trains models using user-supplied labels. VOCALExplore maximizes model quality by automatically deciding how to select samples based on observed skew in the collected labels. It also sel

The GRAVITY Collaboration, O. Straub, M. Bauböck, R. Abuter

In the Milky Way the central massive black hole, SgrA*, coexists with a compact nuclear star cluster that contains a sub-parsec concentration of fast-moving young stars called S-stars. Their location and age are not easily explained by current star formation models, and in several scenarios the presence of an intermediate-mass black hole (IMBH) has been invo

José Damián López, Miguel Alcubierre

We consider again stationary solutions to the spherically symmetric Einstein--Maxwell--Klein--Gordon system, commonly known as ``charged boson stars'', originally studied by Jetzer and Van Der Bij. We construct families of charged boson stars in the ground state, for different values of the charge parameter $q$, and different values of the central scalar fie

Walter Schirmacher, Giancarlo Ruocco

We show that the Kubelka-Munk equations for the description of the intensity transfer of light in turbid media are equivalent to a one-dimensional diffusion equation, which is obtained by averaging the three-dimensional diffusion equation over the lateral directions. This enables us to identify uniquely the Kubelka-Munk parameters and derive expressions for

Chang Liu

Stock return prediction is fundamental to financial decision-making, yet traditional time series models fail to capture the complex interdependencies between companies in modern markets. We propose the Full-State Graph Convolutional LSTM (FS-GCLSTM), a novel temporal graph neural network that incorporates value-chain relationships to enhance stock return for

David Neumann, Andreas Lutz, Karsten Müller, Wojciech Samek

Recommender systems have become ubiquitous in the past years. They solve the tyranny of choice problem faced by many users, and are utilized by many online businesses to drive engagement and sales. Besides other criticisms, like creating filter bubbles within social networks, recommender systems are often reproved for collecting considerable amounts of perso

Gianfranco Casnati

In this very short note we give an elementary characteristic free proof of the result claimed in the title (see Theorem 1.2 for a more precise formulation), generalizing a recent result proved for Ulrich bundles over the complex field by V. Benedetti, P. Montero, Y. Prieto Monta\~nez, S. Troncoso. Moreover, we also give a similar result about the twists of t

Danyal Rehman, John H. Lienhard

Continuum models for ion transport through polyamide nanopores require solving partial differential equations (PDEs) through complex pore geometries. Resolving spatiotemporal features at this length and time-scale can make solving these equations computationally intractable. In addition, mechanistic models frequently require functional relationships between

Keno Riechers, Georg Gottwald, Niklas Boers

Paleoclimate proxies reveal abrupt transitions of the North Atlantic climate during past glacial intervals known as Dansgaard--Oeschger (DO) events. A central feature of DO events is a sudden warming of about 10$^{\circ}$C in Greenland marking the beginning of relatively mild phases termed interstadials. These exhibit gradual cooling over several hundred to

LHCb collaboration

A search for direct $\it{CP}$ violation in the Cabibbo-suppressed decay $D_{s}^{+}\rightarrow K^{-}K^{+}K^{+}$ and in the doubly Cabibbo-suppressed decay $D^{+}\rightarrow K^{-}K^{+}K^{+}$ is reported. The analysis is performed with data collected by the LHCb experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV corresponding to an inte

Bin Cheng, Xiu-Hao Deng, Xiu Gu, Yu He

Quantum computers have made extraordinary progress over the past decade, and significant milestones have been achieved along the path of pursuing universal fault-tolerant quantum computers. Quantum advantage, the tipping point heralding the quantum era, has been accomplished along with several waves of breakthroughs. Quantum hardware has become more integrat

Eloi Haltz, Kévin J. A. Franke, Christopher H. Marrows

N\'eel magnetic domain walls that are stabilized by achiral energy terms instead of the usual Dzyaloshinskii-Moriya interaction will be bistable, with the two possible chiral forms being degenerate. Here we focus on the theoretical study of the spin-orbit torque driven dynamics of such bistable N\'eel domain walls. We find that, for a given domain wall, two

Yongchao Rao, C. Y. Zhao, Lei Shen, Shenghong Ju

Recent studies demonstrate that novel 2D triphosphides semiconductors possess high carrier mobility and promising thermoelectric performance, while the carrier transport behaviors in 2D semimetal triphosphides have never been elucidated before. Herein, using the first-principles calculations and Boltzmann transport theory, we reveal that the electron-phonon

Haotian Li, Lu Ying, Haidong Zhang, Yingcai Wu

Computational notebooks are widely used for data analysis. Their interleaved displays of code and execution results (e.g., visualizations) are welcomed since they enable iterative analysis and preserve the exploration process. However, the communication of data findings remains challenging in computational notebooks. Users have to carefully identify useful f

Wenjie Hu, Tomás Caraballo

The purpose of this paper is to investigate the existence and estimation of Hausdorff and fractal dimension of global attractors for a delayed reaction-diffusion equation on an unbounded domain. The noncompactness of the domain cause the Laplace operator has a continuous spectrum, the semigroup generated by the linear part and the Sobolev embeddings no longe

Bingyu Cui, Maxim Sukharev, Abraham Nitzan

The rigorous quantum mechanical description of the collective interaction of many molecules with the radiation field is usually considered numerically intractable, and approximation schemes must be employed. Standard spectroscopy usually contains some levels of perturbation theory, but under strong coupling conditions, other approximations are used. A common

Luciano Maiani, Antonio D. Polosa, Veronica Riquer

We study compact hidden charm pentaquarks in the Born-Oppenheimer approximation, previously introduced for tetraquarks, assuming the heavy pair to be in a color octet. We show that Fermi statistics applied to the complex of the three light quarks, also in color octet, requires S-wave pentaquark ground states to consist of three octets of flavour-SU(3)_f, two

Sercan Çıkıntoğlu, Sinem Şaşmaz, M. Hakan Erkut, K. Yavuz Ekşi

Some models of gamma-ray bursts (GRBs) invoke nascent millisecond magnetars as the central engine and address the X-ray afterglows with the interaction of magnetar magnetospheres with fallback discs. We study the evolution of fallback discs interacting with the millisecond magnetars. Initially, the accretion rate in the fallback disc is very high, well above

Constantinos Kalapotharakos, Zorawar Wadiasingh, Alice K. Harding, Demosthenes Kazanas

We develop kinetic plasma models of pulsar magnetospheres with magnetic-field-line-dependent plasma injection that reveal the importance of various magnetosphere regions in regulating the gamma-ray emission. We set different particle injection rates for the so-called open, closed, and separatrix zones. Moderate particle injection rates in open and closed zon

Bill Noble, Nikolai Ilinykh

Human speakers can generate descriptions of perceptual concepts, abstracted from the instance-level. Moreover, such descriptions can be used by other speakers to learn provisional representations of those concepts. Learning and using abstract perceptual concepts is under-investigated in the language-and-vision field. The problem is also highly relevant to th

E. Albentosa-Ruiz, I. Marti-Vidal

Polarization calibration of interferometric observations is a costly procedure and, in some cases (e.g., a limited coverage of parallactic angle for the calibrator), it may not be possible to be performed. To avoid this worst-case scenario and expand the possibilities for the exploitation of polarization interferometric observations, the use of a new set of

Adarsh Sudhakar, Amit Suthar

Generalized BMS (gBMS) is the Lie group of the asymptotic symmetries at null infinity, and is proposed to be a symmetry of the quantum S-matrix. Despite much progress in understanding the symplectic structure at null infinity consistent with the gBMS symmetries, the construction of a radiative phase space where all the physical soft modes and their conjugate

Pallab Basu, Haridev S R, Prasant Samantray

We investigate aspects of spontaneous breakdown of symmetry for $O(N)$ symmetric linear sigma model in the background of Rindler and Anti-de Sitter spacetimes respectively. In the large $N$ limit, by computing the one-loop effective action, we report that in three dimensional Rindler space, there is a phase transition from the disordered phase to an ordered

Douglas Stanford

We review Mirzakhani's recursion for the volumes of moduli spaces of orientable surfaces, using a perspective that generalizes to non-orientable surfaces. The non-orientable version leads to divergences when the recursion is iterated, from regions in moduli space with small crosscaps. However, the integral kernels of the recursion are well-defined and they m

Jiaan Wang, Yunlong Liang, Fandong Meng, Zengkui Sun

Recently, the emergence of ChatGPT has attracted wide attention from the computational linguistics community. Many prior studies have shown that ChatGPT achieves remarkable performance on various NLP tasks in terms of automatic evaluation metrics. However, the ability of ChatGPT to serve as an evaluation metric is still underexplored. Considering assessing t

Jinjun Li, Zhiyi Wu

In this paper, we study the structure of the spectra for the Sierpi\'{n}ski type spectral measure $\mu_{A,\mathcal{D}}$ on $\mathbb{R}^2$. We give a sufficient and necessary condition for the family of exponential functions $\{e^{-2\pi i\langle\lambda, x\rangle}: \lambda\in\Lambda\}$ to be a maximal orthogonal set in $L^2(\mu_{A,\mathcal{D}})$. Based on this

Eric Kleinherbers, Alexander Schünemann, Jürgen König

We study full counting statistics of electron transport through a Majorana single-charge transistor. At low bias voltage, transport is dominated by the so-called Josephson-Majorana cycle, a sequence of normal and anomalous single-charge and Josephson tunneling. Factorial cumulants characterizing the full counting statistics elucidate the correlated nature of

Jan Giesselmann, Martin Gugat, Teresa Kunkel

We consider a state estimation problem for gas pipeline flow modeled by the one-dimensional barotropic Euler equations. In order to reconstruct the system state, we construct an observer system of Luenberger type based on distributed measurements of one state variable. First, we show the existence of Lipschitz-continuous semi-global solutions of the observer