April 2023 arXiv papers — page 51

Neel Mishra, Pawan Kumar

In our work, we propose a novel yet simple approach to obtain an adaptive learning rate for gradient-based descent methods on classification tasks. Instead of the traditional approach of selecting adaptive learning rates via the decayed expectation of gradient-based terms, we use the angle between the current gradient and the new gradient: this new gradient

Ola Amara-Omari, Ronit Mansour, Mary Schaps

For a dominant integral weight $\Lambda$ in a Lie algebra of affine type A and rank $e$, and an interval $I_0$ in the residue set $I$, we define the face for the interval $I_0$ to be the subgraph of the block-reduced crystal $\widehat P(\Lambda)$ that is generated by $f_i$ for $i \in I_0$. We show that such a face has an automorphism that preserves defects.

Vinay Pursnani, Yusuf Sermet, Ibrahim Demir

In recent years, advancements in artificial intelligence (AI) have led to the development of large language models like GPT-4, demonstrating potential applications in various fields, including education. This study investigates the feasibility and effectiveness of using ChatGPT, a GPT-4 based model, in achieving satisfactory performance on the Fundamentals o

Anthony N. Consiglio, Yu Ouyang, Matthew J. Powell-Palm, Boris Rubinsky

The propensity of water to remain in a metastable liquid state at temperatures below its equilibrium melting point holds significant potential for cryopreserving biological material such as tissues and organs. The benefits conferred are a direct result of progressively reducing metabolic expenditure due to colder temperatures while simultaneously avoiding th

Yongao Wang, Jie Ren

We calculate the holographic complexity of a family of hyperbolic black holes in an Einstein-Maxwell-dilaton (EMD) system by applying the complexity=action (CA) conjecture. While people previously studied spherical black holes in the same system, we show that hyperbolic black holes have intriguing features. We confirm that the complexity expression mainly de

Zhihong Chen, Feng Jiang, Junying Chen, Tiannan Wang

This paper presents our efforts to democratize ChatGPT across language. We release a large language model "Phoenix", achieving competitive performance among open-source English and Chinese models while excelling in languages with limited resources (covering both Latin and non-Latin languages). We believe this work will be beneficial to make ChatGPT more acce

Sasha Viktorova

We classify combinations of isolated singularities that can occur on complex cubic threefolds generalizing analogous results for cubic surfaces due to Schl\"{a}fli and Bruce--Wall. In addition, we provide concise combinatorial description of the possible configurations of simple singularities: they essentially correspond to subgraphs of a certain graph.

Jinsol Seo

We prove the unique solvability for the Poisson and heat equations in non-smooth domains $\Omega\subset \mathbb{R}^d$ in weighted Sobolev spaces. The zero Dirichlet boundary condition is considered, and domains are merely assumed to admit the Hardy inequality: $$ \int_{\Omega}\Big|\frac{f(x)}{d(x,\partial\Omega)}\Big|^2\,\,\mathrm{d} x\leq N\int_{\Omega}|\na

Jiaxin Wang, Heidi J. Renninger, Qin Ma, Shichao Jin

Automated stomata detection and measuring are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Current methods are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing empirical and theoretical algorithms and convolutiona

F. M. Zimmer, R. Mourao, M. Schmidt, M. A. Tumelero

In this work, we theoretically demonstrate that a strong enhancement of the Magnetocaloric Effect is achieved in geometrically frustrated cluster spin-glass systems just above the freezing temperature. We consider a network of clusters interacting randomly which have triangular structure composed of Ising spins interacting antiferromagnetically. The interclu

Marco Toschi, Riccardo De Matteo, Riccardo Spezialetti, Daniele De Gregorio

In this paper, we focus on the problem of rendering novel views from a Neural Radiance Field (NeRF) under unobserved light conditions. To this end, we introduce a novel dataset, dubbed ReNe (Relighting NeRF), framing real world objects under one-light-at-time (OLAT) conditions, annotated with accurate ground-truth camera and light poses. Our acquisition pipe

Shaoxiong Ji, Tianlin Zhang, Kailai Yang, Sophia Ananiadou

Pretrained language models have been used in various natural language processing applications. In the mental health domain, domain-specific language models are pretrained and released, which facilitates the early detection of mental health conditions. Social posts, e.g., on Reddit, are usually long documents. However, there are no domain-specific pretrained

Soumalya Nandi, Sravanti Addepalli, Harsh Rangwani, R. Venkatesh Babu

Randomized smoothing (RS) is a well known certified defense against adversarial attacks, which creates a smoothed classifier by predicting the most likely class under random noise perturbations of inputs during inference. While initial work focused on robustness to $\ell_2$ norm perturbations using noise sampled from a Gaussian distribution, subsequent works

Kesen Wang, Reinaldo B. Arellano-Valle, Adelchi Azzalini, Marc G. Genton

In this note, we investigate the non-identifiability of the multivariate unified skew-normal distribution under permutation of its latent variables. We show that the non-identifiability issue also holds with other parametrizations and extends to the family of unified skew-elliptical distributions and more generally to selection distibutions. We provide sever

Xander M. de Wit, Michel Fruchart, Tali Khain, Federico Toschi

Fully developed turbulence is a universal and scale-invariant chaotic state characterized by an energy cascade from large to small scales where the cascade is eventually arrested by dissipation. In this article, we show how to harness these seemingly structureless turbulent cascades to generate patterns. Pattern formation entails a process of wavelength sele

Thomas Parmer, Filippo Radicchi

Estimating the influence that individual nodes have on one another in a Boolean network is essential to predict and control the system's dynamical behavior, for example, detecting key therapeutic targets to control pathways in models of biological signaling and regulation. Exact estimation is generally not possible due to the fact that the number of configur

Yakir Gorski, Amir Jevnisek, Shai Avidan

MLaaS Service Providers (SPs) holding a Neural Network would like to keep the Neural Network weights secret. On the other hand, users wish to utilize the SPs' Neural Network for inference without revealing their data. Multi-Party Computation (MPC) offers a solution to achieve this. Computations in MPC involve communication, as the parties send data back and

Michela Egidi, Delio Mugnolo, Albrecht Seelmann

We develop a Logvinenko--Sereda theory for one-dimensional vector-valued self-adjoint operators. We thus deliver upper bounds on $L^2$-norms of eigenfunctions -- and linear combinations thereof -- in terms of their $L^2$- and $W^{1,2}$-norms on small control sets that are merely measurable and suitably distributed along each interval. An essential step consi

Chih-Hsun Lin, Chia-Yi Hsu, Chia-Mu Yu, Yang Cao

Differentially private synthetic data is a promising alternative for sensitive data release. Many differentially private generative models have been proposed in the literature. Unfortunately, they all suffer from the low utility of the synthetic data, particularly for images of high resolutions. Here, we propose DPAF, an effective differentially private gene

Huijie Wang, Tianyu Li, Yang Li, Li Chen

Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments. However, existing benchmarks tend to oversimplify the scene by solely focusing on lane perception tasks. Observing that human drivers rely on both lanes and traffic signals to operate their vehicles safely, we present OpenLane-V2, the fir

Kehinde Ajayi, Muntabir Hasan Choudhury, Sarah Rajtmajer, Jian Wu

Concerns about reproducibility in artificial intelligence (AI) have emerged, as researchers have reported unsuccessful attempts to directly reproduce published findings in the field. Replicability, the ability to affirm a finding using the same procedures on new data, has not been well studied. In this paper, we examine both reproducibility and replicability

Christoph Lehner, Tilo Wettig

We demonstrate that gauge-equivariant pooling and unpooling layers can perform as well as traditional restriction and prolongation layers in multigrid preconditioner models for lattice QCD. These layers introduce a gauge degree of freedom on the coarse grid, allowing for the use of explicitly gauge-equivariant layers on the coarse grid. We investigate the co

Jaclyn B. Champagne, Caitlin M. Casey, Steven L. Finkelstein, Micaela Bagley

The most luminous quasars at $z > 6$ are suspected to be both highly clustered and reside in the most massive dark matter halos in the early Universe, making them prime targets to search for galaxy overdensities and/or protoclusters. We search for Lyman-break dropout-selected galaxies using HST WFC3/ACS broadband imaging in the fields of three $6 < z < 7$ qu

Hao Sun, Zhexin Zhang, Jiawen Deng, Jiale Cheng

With the rapid popularity of large language models such as ChatGPT and GPT-4, a growing amount of attention is paid to their safety concerns. These models may generate insulting and discriminatory content, reflect incorrect social values, and may be used for malicious purposes such as fraud and dissemination of misleading information. Evaluating and enhancin

Shun-Jia Huang, Yi-Ming Hu, Xian Chen, Jian-dong Zhang

The measurement of the Hubble constant $H_0$ plays an important role in the study of cosmology. In this letter, we propose a new method to constrain the Hubble constant using the strongly lensed gravitational wave (GW) signals. By reparameterizing the waveform, we find that the lensed waveform is sensitive to the $H_0$. Assuming the scenario that no electrom

George Georgiou, Georgios Linardopoulos, Dimitrios Zoakos

We set up the computation of correlation functions for operators that are dual to semiclassical string states in strongly coupled defect conformal field theories (dCFTs). In the dCFT that is dual to the D3-D5 probe-brane system, we calculate the correlation function of two heavy operators perturbatively, in powers of the conformal ratio. We find that the lea

Samaria Montenegro, Silvain Rideau-Kikuchi

Pseudo algebraically closed, pseudo real closed, and pseudo $p$-adically closed fields are examples of unstable fields that share many similarities, but have mostly been studied separately. In this text, we propose a unified framework for studying them: the class of pseudo $T$-closed fields, where $T$ is an enriched theory of fields. These fields verify a "l

Simone Traverso, Christoph Fleckenstein, Maura Sassetti, Niccolò Traverso Ziani

Clock-spin models are attracting great interest, due to both their rich phase diagram and their connection to parafermions. In this context, we derive an exact local mapping from clock-spin to fermionic partition functions. Such mapping, akin to techniques introduced by Fedotov and Popov for spin $\frac{1}{2}$ chains, grants access to well established numeri

Martin Reinecke, Sebastian Belkner, Julien Carron

Deep cosmic microwave background polarization experiments allow a very precise internal reconstruction of the gravitational lensing signal in pricinple. For this aim, likelihood-based or Bayesian methods are typically necessary, where very large numbers of lensing and delensing remappings on the sphere are sometimes required before satisfactory convergence.

Yan Wang, Sina Sadeghi, Rajesh Paul, Zach Hetzler

Time-resolved techniques have been widely used in time-gated and luminescence lifetime imaging. However, traditional time-resolved systems require expensive lab equipment such as high-speed excitation sources and detectors or complicated mechanical choppers to achieve high repetition rates. Here, we present a cost-effective and miniaturized smartphone lifeti

Nunziante Valoroso

A regularized damage model is considered named "Graded damage" in which the gradient enhancement has the form of an explicit bound for the spatial gradient of damage. The key features of the proposed approach are demonstrated by computing the analytical solution of two problems that are one-parameter dependent. The first one is the classical one-dimensional

Félix Castro, Alexandre Miquel, Krzysztof Worytkiewicz

Implicative algebras, recently discovered by Miquel, are combinatorial structures unifying classical and intuitionistic realizability as well as forcing. In this paper we introduce implicative assemblies as sets valued in the separator of an underlying implicative algebra. Given a fixed implicative algebra A, implicative assemblies over A organise themselves

Shuhe Wang, Xiaofei Sun, Xiaoya Li, Rongbin Ouyang

Despite the fact that large-scale Language Models (LLM) have achieved SOTA performances on a variety of NLP tasks, its performance on NER is still significantly below supervised baselines. This is due to the gap between the two tasks the NER and LLMs: the former is a sequence labeling task in nature while the latter is a text-generation model. In this paper,

Ana-Claudia Sima, Tarcisio Mendes de Farias

In this paper, we present work in progress on the role of artificial intelligence (AI) chatbots, such as ChatGPT, in facilitating data access to federated knowledge graphs. In particular, we provide examples from the field of bioinformatics, to illustrate the potential use of Conversational AI to describe datasets, as well as generate and explain (federated)

Ira M. Gessel, Ishan Kar

The binomial convolution of two sequences $\{a_n\}$ and $\{b_n\}$ is the sequence whose $n$th term is $\sum_{k=0}^{n} \binom{n}{k} a_k b_{n-k}$. If $\{a_n\}$ and $\{b_n\}$ have rational generating functions then so does their binomial convolution. We discuss an efficient method, using resultants, for computing this rational generating function and give sever

Oliver Nash

We discuss the theory of Lie algebras in Lean's Mathlib library. Using nilpotency as the theme, we outline a computer formalisation of Engel's theorem and an application to root space theory. We emphasise that all arguments work with coefficients in any commutative ring.

Vadim Liventsev, Anastasiia Grishina, Aki Härmä, Leon Moonen

Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answer (as measured by text similarity metrics or human evaluation), but achieve a low or even zero accuracy as measured by unit tests due to small imperfections, such as the wrong inp

Jiayu Xie, Jie Wang, Bing Tang

We investigate the circular motion and chaos bound of a charged particle near 4D charged AdS black holes in Einstein-Gauss-Bonnet gravity theory. By means of the Jacobian matrix, the analytical form of the Lyapunov exponent of the charged particle is constructed, which satisfies the upper bound when it is on the event horizon. By further expanding the Lyapun

Yongqiang Wang

In distributed optimization or Nash-equilibrium seeking over directed graphs, it is crucial to find a matrix norm under which the disagreement of individual agents' states contracts. In existing results, the matrix norm is usually defined by approximating the spectral radius of the matrix, which is possible when the matrix is real and has zero row-sums. In t

Arghya Maity, Aditi Sen De

We formulate a protocol for a four-stroke quantum Otto engine that is capable of achieving superior performance when operating between two thermal reservoirs: one at a positive spin temperature and the other at an effective negative spin temperature. We adopt a protocol that encompasses a rotating magnetic field in the (x, y)-plane, as well as an additional

K. Decker French, Nicholas Earl, Annemarie B. Novack, Bhavya Pardasani

The role of AGN in quenching galaxies and driving the evolution from star-forming to quiescent remains a key question in galaxy evolution. We present evidence from the Mapping Nearby Galaxies at APO (MaNGA) survey for fading AGN activity in 6/93 post-starburst galaxies. These six galaxies show extended emission line regions (EELRs) consistent with ionization

Andrii Arman, Andriy Bondarenko, Andriy Prymak

We show that there exist convex bodies of constant width in $\mathbb{E}^n$ with illumination number at least $(\cos(\pi/14)+o(1))^{-n}$, answering a question by G. Kalai. Furthermore, we prove the existence of finite sets of diameter $1$ in $\mathbb{E}^n$ which cannot be covered by $(2/\sqrt{3}+o(1))^{n}$ balls of diameter $1$, improving a result by J. Bourg

Nikos Athanasiou, Mathis Petrovich, Michael J. Black, Gül Varol

Our goal is to synthesize 3D human motions given textual inputs describing simultaneous actions, for example 'waving hand' while 'walking' at the same time. We refer to generating such simultaneous movements as performing 'spatial compositions'. In contrast to temporal compositions that seek to transition from one action to another, spatial compositing requi

Weili Lin, Xiaofeng Wang, Lin Yan, Avishay Gal-Yam

Superluminous supernovae are among the most energetic stellar explosions in the Universe, but their energy sources remain an open question. Here we present long-term observations of one of the closest examples of the hydrogen-poor subclass (SLSNe-I), SN~2017egm, revealing the most complicated known luminosity evolution of SLSNe-I. Three distinct post-peak bu

Yingqian Wang, Longguang Wang, Zhengyu Liang, Jungang Yang

In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model

Benjamin Doerr, Arthur Dremaux, Johannes Lutzeyer, Aurélien Stumpf

In recent work, Lissovoi, Oliveto, and Warwicker (Artificial Intelligence (2023)) proved that the Move Acceptance Hyper-Heuristic (MAHH) leaves the local optimum of the multimodal cliff benchmark with remarkable efficiency. With its $O(n^3)$ runtime, for almost all cliff widths $d,$ the MAHH massively outperforms the $\Theta(n^d)$ runtime of simple elitist e

Frances Y. Kuo, Dirk Nuyens, Laurence Wilkes

We show that a very simple randomised algorithm for numerical integration can produce a near optimal rate of convergence for integrals of functions in the $d$-dimensional weighted Korobov space. This algorithm uses a lattice rule with a fixed generating vector and the only random element is the choice of the number of function evaluations. For a given comput

Weike Yu

In this note, we prove an existence result for generalized Kazdan-Warner equations on compact Riemannian manifolds by using the flow approach or the upper and lower solution method. In addition, we give a prior estimate for this type equations.

Yichuan Deng, Zhihang Li, Zhao Song

Large language models (LLMs) have made transformed changes for human society. One of the key computation in LLMs is the softmax unit. This operation is important in LLMs because it allows the model to generate a distribution over possible next words or phrases, given a sequence of input words. This distribution is then used to select the most likely next wor

Shanliang Yao, Runwei Guan, Xiaoyu Huang, Zhuoxiao Li

Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surrounding environment for safe and efficient navigation. To achieve accurate and robust perception capabilities, autonomous vehicles are often equipped with multiple sensors, making sens

Phuong T. Nguyen, Riccardo Rubei, Juri Di Rocco, Claudio Di Sipio

Recommender systems for software engineering (RSSEs) assist software engineers in dealing with a growing information overload when discerning alternative development solutions. While RSSEs are becoming more and more effective in suggesting handy recommendations, they tend to suffer from popularity bias, i.e., favoring items that are relevant mainly because s

Sergey V. Ulyanov, Viktor S. Ulyanov

The difference between classical and quantum algorithms (QA) is following: problem solved by QA is coded in the structure of the quantum operators. Input to QA in this case is always the same. Output of QA says which problem coded. In some sense, give a function to QA to analyze and QA returns its property as an answer without quantitative computing. QA stud

Pavel Sekatski, Jean-Daniel Bancal, Marie Ioannou, Mikael Afzelius

Quantum memories represent one of the main ingredients of future quantum communication networks. Their certification is therefore a key challenge. Here we develop efficient certification methods for quantum memories. Considering a device-independent approach, where no a priori characterisation of sources or measurement devices is required, we develop a robus

Gergely Flamich, Lucas Theis

We consider channel simulation protocols between two communicating parties, Alice and Bob. First, Alice receives a target distribution $Q$, unknown to Bob. Then, she employs a shared coding distribution $P$ to send the minimum amount of information to Bob so that he can simulate a single sample $X \sim Q$. For discrete distributions, Harsha et al. (2009) dev

Tang Tao, Longfei Gao, Guangrun Wang, Yixing Lao

We introduce a new task, novel view synthesis for LiDAR sensors. While traditional model-based LiDAR simulators with style-transfer neural networks can be applied to render novel views, they fall short of producing accurate and realistic LiDAR patterns because the renderers rely on explicit 3D reconstruction and exploit game engines, that ignore important at

Abbas K. Rizi, Leah A. Keating, James P. Gleeson, David J. P. O'Sullivan

Contact tracing, the practice of isolating individuals who have been in contact with infected individuals, is an effective and practical way of containing disease spread. Here, we show that this strategy is particularly effective in the presence of social groups: Once the disease enters a group, contact tracing not only cuts direct infection paths but can al

William Barford, Cameron A Chambers

We develop a theory of singlet fission in carotenoid dimers. Following photoexcitation of the 'bright' state (i.e., a singlet electron-hole pair) in a single carotenoid, the first step in the singlet fission process is ultrafast intramolecular conversion into the highly-correlated 'dark' (or 2Ag) state. This state has both entangled singlet triplet-pair and

Yihao Zhang, Zeming Wei, Xiyue Zhang, Meng Sun

While Feedforward Neural Networks (FNNs) have achieved remarkable success in various tasks, they are vulnerable to adversarial examples. Several techniques have been developed to verify the adversarial robustness of FNNs, but most of them focus on robustness verification against the local perturbation neighborhood of a single data point. There is still a lar

Juliana S. M. Karp, Johannes U. Lange, Risa H. Wechsler

The quenched fraction of satellite galaxies is aligned with the orientation of the halo's central galaxy, such that on average, satellites form stars at a lower rate along the major axis of the central. This effect, called anisotropic satellite galaxy quenching (ASGQ), has been found in observational data and cosmological simulations. Analyzing the Illustris

Vladyslav Babenko, Vira Babenko, Oleg Kovalenko, Nataliia Parfinovych

In this article we prove sharp Landau--Kolmogorov type inequalities on a class of charges defined on Lebesgue measurable subsets of a cone in $\mathbb{R}^d$, $d\geq 1$, that are absolutely continuous with respect to the Lebesgue measure. In addition we solve the Stechkin problem of approximation of the Radon--Nikodym derivative of such charges by bounded ope

Shayan Mirjafari, Subigya Nepal, Weichen Wang, Andrew T. Campbell

Hallucination is an apparent perception in the absence of real external sensory stimuli. An auditory hallucination is a perception of hearing sounds that are not real. A common form of auditory hallucination is hearing voices in the absence of any speakers which is known as Auditory Verbal Hallucination (AVH). AVH is fragments of the mind's creation that mos

Luca Chirolli, Matteo Carrega, Francesco Giazotto

The quasicharge superconducting qubit realizes the dual of the transmon and shows strong robustness to flux and charge fluctuations thanks to a very large inductance closed on a Josephson junction. At the same time, a weak anharmonicity of the spectrum is inherited from the parent transmon, that introduces leakage errors and is prone to frequency crowding in

Clara Magnin, Laurene Quenot, Sylvain Bohic, Dan Mihai Cenda

Phase Contrast Imaging (PCI), Dark-Field (DF) and Directional Dark-Field (DDF) imaging are recent X-ray imaging modalities that have demonstrated their interest by providing access to information and contrasts different from those provided by conventional absorption X-ray imaging. However, access to these two types of images is currently limited because the

Mihail Arabadji, R. Inanc Baykur

We demonstrate the existence of numerous non-spin 4-manifolds for which the smooth Nielsen realization problem fails; namely, there exist finite subgroups of their mapping class groups that cannot be realized by any group of diffeomorphisms. This extends and complements recent results for spin 4-manifolds. Our examples span virtually all possible intersectio

Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla

Graph Neural Networks (GNNs) have shown state-of-the-art improvements in node classification tasks on graphs. While these improvements have been largely demonstrated in a multi-class classification scenario, a more general and realistic scenario in which each node could have multiple labels has so far received little attention. The first challenge in conduct

Noel Chalmers, Jakub Kurzak, Damon McDougall, Paul T. Bauman

We detail the performance optimizations made in rocHPL, AMD's open-source implementation of the High-Performance Linpack (HPL) benchmark targeting accelerated node architectures designed for exascale systems such as the Frontier supercomputer. The implementation leverages the high-throughput GPU accelerators on the node via highly optimized linear algebra li

Vladimir Toussaint, Jorma Louko

(1+1)-dimensional locally de Sitter Friedmann-Robertson-Walker cosmologies with compact spatial sections allow cosh, sinh and exponential evolution laws, each with a freely-specifiable spatial circumference parameter, and the value of this parameter has an invariant geometric meaning for the cosh and sinh evolution laws. We identify geometrically preferred s

Lenart Zadnik, Juan P. Garrahan

With the aim to understand the role of the constraints in the thermalisation of quantum systems, we study the dynamics of a family of kinetically constrained models arising through duality from the XXZ spin chain. We find that integrable and nonintegrable deformations around the stochastic point give rise to ground state phase transitions between localised a

Tianqing Fang, Quyet V. Do, Zihao Zheng, Weiqi Wang

Commonsense Knowledge Bases (CSKB) Population, which aims at automatically expanding knowledge in CSKBs with external resources, is an important yet hard task in NLP. Fang et al. (2021a) proposed a CSKB Population (CKBP) framework with an evaluation set CKBP v1. However, CKBP v1 relies on crowdsourced annotations that suffer from a considerable number of mis

Avital Boruchovsky, Daniella Bar-Lev, Eitan Yaakobi

This paper introduces a new solution to DNA storage that integrates all three steps of retrieval, namely clustering, reconstruction, and error correction. DNA-correcting codes are presented as a unique solution to the problem of ensuring that the output of the storage system is unique for any valid set of input strands. To this end, we introduce a novel dist

Natalia Chepiga

We study critical properties of a Majorana chain in the presence of two competing interactions of the shortest possible range. The obtained phase diagram is very rich and contains nine different phases, including three floating, two Ising, and four gapped phases. In addition we report a wide variety of quantum phase transitions: the supersymmetric tri-critic

Bercel Boldis, Péter Lévay

In this paper we establish a connection between segmented strings propagating in $AdS_{d+1}$ and $CFT_d$ subsystems in Minkowski spacetime characterized by quantum information theoretic quantities calculated for the vacuum state. We show that the area of the world sheet of a string segment on the AdS side can be connected to fidelity susceptibility (the real

Andrzej Derdzinski, Ivo Terek

Pseudo-Riemannian manifolds with nonzero parallel Weyl tensor which are not locally symmetric are known as ECS manifolds. Every ECS manifold carries a distinguished null parallel distribution $\mathcal{D}$, the rank $d \in \{ 1, 2 \}$ of which is referred to as the rank of the manifold itself. Under a natural genericity assumption on the Weyl tensor, we full

Xin Mu, Fu-Der Chen, Ka My Dang, Michael G. K. Brunk

Advances in chip-scale photonic-electronic integration are enabling a new generation of foundry-manufacturable implantable silicon neural probes incorporating nanophotonic waveguides and microelectrodes for optogenetic stimulation and electrophysiological recording in neuroscience research. Further extending neural probe functionalities with integrated micro

Gayathri Girish, Ponnathota Spandana, Badrish Vasu

Objective: This paper proposes a deep learning model for breast cancer detection from reconstructed images of microwave imaging scan data and aims to improve the accuracy and efficiency of breast tumor detection, which could have a significant impact on breast cancer diagnosis and treatment. Methods: Our framework consists of different convolutional neural n

Gabriele Agliardi, Corey O'Meara, Kavitha Yogaraj, Kumar Ghosh

Computing nonlinear functions over multilinear forms is a general problem with applications in risk analysis. For instance in the domain of energy economics, accurate and timely risk management demands for efficient simulation of millions of scenarios, largely benefiting from computational speedups. We develop a novel hybrid quantum-classical algorithm based

Jean-Baptiste Gramain

In this article, a model, discrete in space and time, is developed to describe the growth and spread of the Scottish populations of red squirrels (Sciurus vulgaris) and grey squirrel (Sciurus carolinensis). The initial state for the model is designed using a large dataset of records of sightings of individuals of both species reported by members of the publi

Diego Figueira, Santiago Figueira, Edwin Pin

We introduce CPDL+, a family of expressive logics rooted in Propositional Dynamic Logic (PDL). In terms of expressive power, CPDL+ strictly contains PDL extended with intersection and converse (a.k.a. ICPDL) as well as Conjunctive Queries (CQ), Conjunctive Regular Path Queries (CRPQ), or some known extensions thereof (Regular Queries and CQPDL). We investiga

Ruba Mutasim, Gabriel Synnaeve, David Pichardie, Baptiste Rozière

We propose a method combining machine learning with a static analysis tool (i.e. Infer) to automatically repair source code. Machine Learning methods perform well for producing idiomatic source code. However, their output is sometimes difficult to trust as language models can output incorrect code with high confidence. Static analysis tools are trustable, bu

Jay S. Chittidi, Georgia Stolle-McAllister, Regina A. Jorgenson, Nicolas Tejos

We used Bands 6 and 7 of the Atacama Large Millimeter/submillimeter Array (ALMA) in Cycles 7 and 8 to search for $\mathrm{CO}\,(3-2)$ emission from a sample of five fast radio burst (FRB) host galaxies discovered by the Commensal Real-time ASKAP Fast Transients (CRAFT) survey and the Fast and Fortunate for FRB Follow-up (F$^4$) team. These galaxies have reds

Xin Jiang, Peng Wang, Houwen Wu, Haitang Yang

In the context of dS$_3$/CFT$_2$, we propose a timelike entanglement entropy defined by the renormalization group flow. This timelike entanglement entropy is calculated in CFT by using the Callan-Symanzik equation. We find an exact match between this entanglement entropy and the length of a timelike geodesic connecting two different spacelike surfaces in dS$

Yoshinari Motokawa, Toshiharu Sugawara

We propose a model-free reinforcement learning architecture, called distributed attentional actor architecture after conditional attention (DA6-X), to provide better interpretability of conditional coordinated behaviors. The underlying principle involves reusing the saliency vector, which represents the conditional states of the environment, such as the glob

Chengqiu Hu, Wenyuan Wang, Kai-Sum Chan, Zhenghan Yuan

Quantum key distribution (QKD) offers information-theoretic security based on the fundamental laws of physics. However, device imperfections, such as those in active modulators, may introduce side-channel leakage, thus compromising practical security. Attempts to remove active modulation, including passive decoy intensities preparation and polarization encod

V. A. Sevestrean, O. Niţescu, S. Ghinescu, S. Stoica

We present a comprehensive investigation of electron capture (EC) ratios spanning a broad range of atomic numbers. The study employs a self-consistent computational method that incorporates electron screening, electron correlations, overlap and exchange corrections, as well as shake-up and shake-off atomic effects. The electronic wave functions are computed

David Bolin, Alexandre Simas, Jonas Wallin

Whittle-Mat\'ern fields are a recently introduced class of Gaussian processes on metric graphs, which are specified as solutions to a fractional-order stochastic differential equation. Unlike earlier covariance-based approaches for specifying Gaussian fields on metric graphs, the Whittle-Mat\'ern fields are well-defined for any compact metric graph and can p

Peter Frankl, Jian Wang

A family $\mathcal{F}\subset \binom{[n]}{k}$ is called an intersecting family if $F\cap F'\neq \emptyset$ for all $F,F'\in \mathcal{F}$. If $\cap \mathcal{F}\neq \emptyset$ then $\mathcal{F}$ is called a star. The diversity of an intersecting family $\mathcal{F}$ is defined as the minimum number of $k$-sets in $\mathcal{F}$, whose deletion results in a star.

Omar Alghamdi, Sarah Clinch, Mohammad Alhamadi, Caroline Jay

Websites are frequently used by programmers to support the development process. This paper investigates programmer-Web interactions when coding, and combines observations of behaviour with assessments of the resulting source code. We report on an online observational study with ten undergraduate student programmers as they engaged in programming tasks of var

Dávid R. Szabó

For every algebraically closed field $k$ and natural number $r$, we construct several algebraic varieties (over $k$) whose birational automorphism group contains every finite nilpotent group of class at most $2$, rank at most $r$ whose order is coprime to the characteristic of $k$. This construction is sharp in characteristic $0$, i.e. up to bounded extensio

Matilde Baroni, Giulia Garcia Lorenzana, Tommaso Rizzo, Marco Tarzia

We study numerically Anderson localization on lattices that are tree-like except for the presence of one loop of varying length $L$. The resulting expressions allow us to compute corrections to the Bethe lattice solution on i) Random-Regular-Graph (RRG) of finite size $N$ and ii) euclidean lattices in finite dimension. In the first case we show that the $1/N

Naoyuki Kanomata, Akifumi Sako

There is a matrix model corresponding to a scalar field theory called Grosse-Wulkenhaar model, which is renormalizable by adding a harmonic oscillator potential to scalar $\Phi^{4}$ theory on Moyal spaces. There are more unknowns in $\Phi^{4}$ matrix model than in $\Phi^{3}$ matrix model, for example, in terms of integrability. We then construct a one-matrix

Zhihao Wang, Juan Cao, Xiaodong Wei, Zhonggui Chen

This paper presents the application of triangle configuration B-splines (TCB-splines) for representing and analyzing the Kirchhoff-Love shell in the context of isogeometric analysis (IGA). The Kirchhoff-Love shell formulation requires global $C^1$-continuous basis functions. The nonuniform rational B-spline (NURBS)-based IGA has been extensively used for dev

Priyanka Choudhary, Praveen C. Srivastava

In the present work, newly developed microscopic effective $sd$-valence shell interactions such as chiral next-to-next-to-next-to-leading order (N3LO), $J$-matrix inverse scattering potential (JISP16), Daejeon16 (DJ16), and monopole-modified DJ16 (DJ16A) are employed to study the nuclear structural properties of sulphur, chlorine, and argon isotopes with $N

Matouš Jelínek, Kerstin Fischer

While trust in human-robot interaction is increasingly recognized as necessary for the implementation of social robots, our understanding of regulating trust in human-robot interaction is yet limited. In the current experiment, we evaluated different approaches to trust calibration in human-robot interaction. The within-subject experimental approach utilized

Yankai Lin, Michelle S. Chong, Carlos Murguia

We consider the problem of ensuring the safety of nonlinear control systems under adversarial signals. Using Lyapunov based reachability analysis, we first give sufficient conditions to assess safety, i.e., to guarantee that the states of the control system, when starting from a given initial set, always remain in a prescribed safe set. We consider polynomia

I. L. Buchbinder, A. A. Reshetnyak

We study the aspects of constructing the interactions for the higher spin fields in the framework of BRST approach. The main object of such an approach is BRST operator acting in the appropriate Fock space and building on the base of constraints that define the irreducible higher spin representations. In its turn, the constrains are divided into differential

Richard E. Turner

The transformer is a neural network component that can be used to learn useful representations of sequences or sets of data-points. The transformer has driven recent advances in natural language processing, computer vision, and spatio-temporal modelling. There are many introductions to transformers, but most do not contain precise mathematical descriptions o

Victor Chéron, Fabien Evrard, Berend van Wachem

This paper derives new correlations to predict the drag, lift and torque coefficients of axi-symmetric non-spherical rod-like particles for several fluid flow regimes and velocity profiles. The fluid velocity profiles considered are locally uniform flow and locally linear shear flow. The novel correlations for the drag, lift and torque coefficients depend on

Housen Li, Frank Werner

We consider statistical linear inverse problems in separable Hilbert spaces and filter-based reconstruction methods of the form $\hat f_\alpha = q_\alpha \left(T^*T\right)T^*Y$, where $Y$ is the available data, $T$ the forward operator, $\left(q_\alpha\right)_{\alpha \in \mathcal A}$ an ordered filter, and $\alpha > 0$ a regularization parameter. Whenever su

Jiezhu Lin, Xuanming Ye

In this paper, we establish a kind of Dolbeault type cohomology groups for the purpose of studying the varying of complex structure invariants in infinitesimal deformations of any order. We give a concrete description of the higher order Kodaria-Spencer maps by using these cohomology groups. We reformulate the obstruction formulas within the framework of the

Chiaming Hsu, Changtong Zan, Liang Ding, Longyue Wang

Relation Extraction (RE) is a crucial task in Information Extraction, which entails predicting relationships between entities within a given sentence. However, extending pre-trained RE models to other languages is challenging, particularly in real-world scenarios where Cross-Lingual Relation Extraction (XRE) is required. Despite recent advancements in Prompt