April 2023 arXiv papers — page 58

M. Muñoz Pérez

Putnam and Finkelstein can be read as providing an answer to Kripke's skeptical argument by appealing to the way mathematics is commonly pursued. Nowadays, the debate surrounding pluralism has questioned the postulation of a unique way of developing mathematical activity. In this paper, we wish to reformulate Kripke's argument as a challenge for the conjunct

Beini Gao, Daniel G. Suárez-Forero, Supratik Sarkar, Tsung-Sheng Huang

Understanding the Hubbard model is crucial for investigating various quantum many-body states and its fermionic and bosonic versions have been largely realized separately. Recently, transition metal dichalcogenides heterobilayers have emerged as a promising platform for simulating the rich physics of the Hubbard model. In this work, we explore the interplay

Sertac Kilickaya, Mete Ahishali, Fahad Sohrab, Turker Ince

Hyperspectral image (HSI) classification is an important task in many applications, such as environmental monitoring, medical imaging, and land use/land cover (LULC) classification. Due to the significant amount of spectral information from recent HSI sensors, analyzing the acquired images is challenging using traditional Machine Learning (ML) methods. As th

Yujie Zhang, Justin Chu, Haoyu Cheng, Heng Li

Satellite DNA are long tandemly repeating sequences in a genome and may be organized as high-order repeats (HORs). They are enriched in centromeres and are challenging to assemble. Existing algorithms for identifying satellite repeats either require the complete assembly of satellites or only work for simple repeat structures without HORs. Here we describe S

Songhua Liu, Jingwen Ye, Xinchao Wang

Style transfer aims to render the style of a given image for style reference to another given image for content reference, and has been widely adopted in artistic generation and image editing. Existing approaches either apply the holistic style of the style image in a global manner, or migrate local colors and textures of the style image to the content count

Weifeng Zhu, Meixia Tao, Xiaojun Yuan, Fan Xu

This paper investigates the problem of activity detection and channel estimation in cooperative multi-cell massive access systems with temporally correlated activity, where all access points (APs) are connected to a central unit via fronthaul links. We propose to perform user-centric AP cooperation for computation burden alleviation and introduce a generaliz

Klara Courteaut, Kurt Johansson

We prove an asymptotic formula for the partition function of a 2d Coulomb gas at inverse temperature $\beta>0$ confined to lie on a Jordan curve. This also gives a central limit theorem for a linear statistic of the particles in the gas. We obtain different expressions for the asymptotic mean and variance which involve either the exterior conformal mapping o

Timothy Lycurgus, Amy Kilbourne, Daniel Almirall

Sequential, multiple assignment randomized trials (SMARTs), which assist in the optimization of adaptive interventions, are growing in popularity in education and behavioral sciences. This is unsurprising, as adaptive interventions reflect the sequential, tailored nature of learning in a classroom or school. Nonetheless, as is true elsewhere in education res

Dongmi Luo, Shiyi Li, Jianxian Qiu, Jun Zhu

In this paper, a compact and high order ADER (Arbitrary high order using DERivatives) scheme using the simple HWENO method (ADER-SHWENO) is proposed for hyperbolic conservation laws. The newly-developed method employs the Lax-Wendroff procedure to convert time derivatives to spatial derivatives, which provides the time evolution of the variables at the cell

Paul Chleboun, Simon Gabriel, Stefan Grosskinsky

We consider the inclusion process on the complete graph with vanishing diffusivity, which leads to condensation of particles in the thermodynamic limit. Describing particle configurations in terms of size-biased and appropriately scaled empirical measures of mass distribution, we establish convergence in law of the inclusion process to a measure-valued Marko

Ozer Can Devecioglu, Mete Ahishali, Fahad Sohrab, Turker Ince

As a consequence of global warming and climate change, the risk and extent of wildfires have been increasing in many areas worldwide. Warmer temperatures and drier conditions can cause quickly spreading fires and make them harder to control; therefore, early detection and accurate locating of active fires are crucial in environmental monitoring. Using satell

K. H. M. R. N. Senavirathna, C. K. Walgampaya

This paper brings an in detail Genetic Algorithm (GA) based combinatorial optimization method used for the optimal design of the water distribution network (WDN) of Gurudeniya Service Zone, Sri Lanka. Genetic Algorithm (GA) mimics the survival of the fittest principle of nature to develop a search process. Methodology employs fuzzy combinations of pipe diame

Nicolas Lenner, Matthias Häring, Stephan Eule, Jörg Großhans

Finite time convergence to functionally important target states is a key component of many biological processes. We previously found that the terminal approach phase of such dynamics exhibits universal types of stochastic dynamics that differ qualitatively between noise-dominated and force-dominated regimes of the approach dynamics. While for the noise-domin

Irtaza Khalid, Carrie A. Weidner, Edmond A. Jonckheere, Sophie G. Shermer

We propose a model-based reinforcement learning (RL) approach for noisy time-dependent gate optimization with improved sample complexity over model-free RL. Sample complexity is the number of controller interactions with the physical system. Leveraging an inductive bias, inspired by recent advances in neural ordinary differential equations (ODEs), we use an

Nicolas Berti, Massimiliano Guasoni, Julien Fatome

We report on an extension of the concept of nonlinear self-repolarization process by means of two different architectures based on dual-Omnipolarizers. More specifically, we compare the performance in terms of polarization attraction capabilities provided by two novel arrangements: The first configuration relies on two cascaded Omnipolarizers, whilst the sec

Zhangjian Hu, Jani A. Virtanen

In their previous work, the authors proved the Berger-Coburn phenomenon for compact and Schatten $S_p$ class Hankel operators $H_f$ on generalized Fock spaces when $1<p<\infty$, that is, for a bounded symbol $f$, if $H_f$ is a compact or Schatten class operator, then so is $H_{\bar f}$. More recently J.~Xia has provided a simple example that shows that there

Mathieu Cocheteux, Aaron Low, Marius Bruehlmeier

We introduce a novel architecture, UniCal, for Camera-to-LiDAR (C2L) extrinsic calibration which leverages self-attention mechanisms through a Transformer-based backbone network to infer the 6-degree of freedom (DoF) relative transformation between the sensors. Unlike previous methods, UniCal performs an early fusion of the input camera and LiDAR data by agg

Antonio Capolupo, Aniello Quaranta

We develop a notion of causal order on a generic manifold as independent of the underlying differential and topological structure. We show that sufficiently regular causal orders can be recovered from a distinguished algebra of sets, which plays a role analogous to that of topologies and $\sigma$ algebras. We then discuss how a natural notion of measure can

Steven E. Boggs

When a $\gamma$-ray interacts in a semiconductor detector, the resulting electron-hole charge clouds drift towards their respective electrodes for signal collection. These charge clouds will expand over time due to both thermal diffusion and mutual electrostatic repulsion. Solutions to the resulting charge profiles are well understood for the limiting cases

Joost Jorritsma, Johannes Lengler, Dirk Sudholt

It is an ongoing debate whether and how comma selection in evolutionary algorithms helps to escape local optima. We propose a new benchmark function to investigate the benefits of comma selection: OneMax with randomly planted local optima, generated by frozen noise. We show that comma selection (the $(1,\lambda)$ EA) is faster than plus selection (the $(1+\l

Filippos Christou, Andreas Kirstädter

During the last few years, there have been concentrated efforts toward intent-driven networking. While relying upon Software-Defined Networking (SDN), Intent-Based Networking (IBN) pushes the frontiers of efficient networking by decoupling the intentions of a network operator (i.e., what is desired to be done) from the implementation (i.e., how is it achieve

Zaitang Li, Pin-Yu Chen, Tsung-Yi Ho

Current studies on adversarial robustness mainly focus on aggregating local robustness results from a set of data samples to evaluate and rank different models. However, the local statistics may not well represent the true global robustness of the underlying unknown data distribution. To address this challenge, this paper makes the first attempt to present a

Doan The Hieu

In this paper, we study $\lambda$-submanifolds of arbitrary codimensions in Gauss spaces. These submanifolds can be seen as natural generalizations of self-shrinker and $\lambda$-hypersurfaces. Using a divergence type theorem and some Simons' type identities, we prove some halfspace type theorems and gap theorems for complete proper $\lambda$-submanifolds. T

Yan Zhang

This paper presents a study of the finite axiomatizability of transitive logics of finite depth and finite weak width. We prove the finite axiomatizability of each transitive logic of finite depth and of weak width $1$ that is characterized by rooted transitive frames in which all antichains contain at most $n$ irreflexive points. As a negative result, we sh

Yan Cui, Bo Xia, Kai Yang

Previously, the existence of ground state solutions of a family of systems of Klein-Gordon equations has been widely studied. In this article, we will study the linearized operator at the ground state and give a complete description of the spectrum for this operator in the radial case: the existence of a unique negative eigenvalue, no resonance at '1'(the bo

Laura O'Mahony, Vincent Andrearczyk, Henning Muller, Mara Graziani

Mechanistic interpretability aims to understand how models store representations by breaking down neural networks into interpretable units. However, the occurrence of polysemantic neurons, or neurons that respond to multiple unrelated features, makes interpreting individual neurons challenging. This has led to the search for meaningful vectors, known as conc

Xiaodong Zhang

A new method for solving small X-ray structures with up to couple of hundreds of atoms in the unit cell has been developed. The method works by locating atoms one-by-one via global minimization of a newly defined single-atom R1 factor in real-space. In total forty test cases (of twenty samples), every resulting model has at least 52% atoms located correctly,

Fabien Baeriswyl, Valérie Chavez-Demoulin, Olivier Wintenberger

We study the tail asymptotics of two functionals (the maximum and the sum of the marks) of a generic cluster in two sub-models of the marked Poisson cluster process, namely the renewal Poisson cluster process and the Hawkes process. Under the hypothesis that the governing components of the processes are regularly varying, we extend results due to [18] and [5

Romain Loiseau, Elliot Vincent, Mathieu Aubry, Loic Landrieu

We propose an unsupervised method for parsing large 3D scans of real-world scenes with easily-interpretable shapes. This work aims to provide a practical tool for analyzing 3D scenes in the context of aerial surveying and mapping, without the need for user annotations. Our approach is based on a probabilistic reconstruction model that decomposes an input 3D

Sandeep Kumar, Hossein Tahmasbi, Kushal Ramakrishna, Mani Lokamani

We present a study on the transport and materials properties of aluminum spanning from ambient to warm dense matter conditions using a machine-learned interatomic potential (ML-IAP). Prior research has utilized ML-IAPs to simulate phenomena in warm dense matter, but these potentials have often been calibrated for a narrow range of temperature and pressures.

Nicholas Pacheco, Yash Garje, Aakash Rohra, Loris Fichera

This paper proposes a method to regulate the tissue temperature during laser surgery by robotically controlling the laser focus. Laser-tissue interactions are generally considered hard to control due to the inherent inhomogeneity of biological tissue, which can create significant variability in its thermal response to laser irradiation. In this study, we use

Valentin Bouquet, François Delbot, Christophe Picouleau, Stéphane Rovedakis

A set $S\subseteq V$ of a graph $G=(V,E)$ is a dominating set if each vertex has a neighbor in $S$ or belongs to $S$. Dominating Set is the problem of deciding, given a graph $G$ and an integer $k\geq 1$, if $G$ has a dominating set of size at most $k$. It is well known that this problem is $\mathsf{NP}$-complete even for claw-free graphs. We give a complexi

Ziqiao Ao, Jinglai Li

Entropy estimation is of practical importance in information theory and statistical science. Many existing entropy estimators suffer from fast growing estimation bias with respect to dimensionality, rendering them unsuitable for high-dimensional problems. In this work we propose a transform-based method for high-dimensional entropy estimation, which consists

Ian H. Stevenson

Whether, when, and how causal interactions between neurons can be meaningfully studied from observations of neural activity alone are vital questions in neural data analysis. Here we aim to better outline the concept of functional connectivity for the specific situation where systems neuroscientists aim to study synapses using spike train recordings. In some

Daniel Harlow

This chapter gives an overview of the quantum aspects of black holes, focusing on the black hole information problem, the counting of black hole entropy in string theory, and the emergence of spacetime in holography. It is aimed at a broad physics audience, and does not presuppose knowledge of string theory or holography.

Barnabás Farkas, Lukas Daniel Klausner, Marc Lischka

We continue investigating variants of the splitting and reaping numbers introduced in arXiv:1808.02442. In particular, answering a question raised there, we prove the consistency of $\mathrm{cof}(\mathcal{M})<\mathfrak{s}_{\frac{1}{2}}$ and of $\mathfrak{r}_{\frac{1}{2}}<\mathrm{add}(\mathcal{M})$. Moreover, we discuss their natural generalisations $\mathfra

Roger Bosman, Birthe van den Berg, Wenhao Tang, Tom Schrijvers

Algebraic effects & handlers have become a standard approach for side-effects in functional programming. Their modular composition with other effects and clean separation of syntax and semantics make them attractive to a wide audience. However, not all effects can be classified as algebraic; some need a more sophisticated handling. In particular, effects tha

Juliane T. Moraes, Silvio C. Ferreira

It is possible to investigate emergence in many real systems using time-ordered data. However, classical time series analysis is usually conditioned by data accuracy and quantity. A modern method is to map time series onto graphs and study these structures using the toolbox available in complex network analysis. An important practical problem to investigate

Zichao Shen, Neil Howard, Jose Nunez-Yanez

This paper investigates the energy savings that near-subthreshold processors can obtain in edge AI applications and proposes strategies to improve them while maintaining the accuracy of the application. The selected processors deploy adaptive voltage scaling techniques in which the frequency and voltage levels of the processor core are determined at the run-

Yang Yang, Weijie Ma, Hao Chen, Linlin Ou

The combination of LiDAR and camera modalities is proven to be necessary and typical for 3D object detection according to recent studies. Existing fusion strategies tend to overly rely on the LiDAR modal in essence, which exploits the abundant semantics from the camera sensor insufficiently. However, existing methods cannot rely on information from other mod

Pablo Moreno-Spiegelberg, Damià Gomila

We propose a general population dynamics model for two seagrass species growing and interacting in two spatial dimensions. The model includes spatial terms accounting for the clonal growth characteristics of seagrasses, and coupling between species through the net mortality rate. We consider both intraspecies and interspecies facilitative and competitive int

Akshaya Athwale, Arman Afrasiyabi, Justin Lagüe, Ichrak Shili

Wide-angle lenses are commonly used in perception tasks requiring a large field of view. Unfortunately, these lenses produce significant distortions, making conventional models that ignore the distortion effects unable to adapt to wide-angle images. In this paper, we present a novel transformer-based model that automatically adapts to the distortion produced

Muskaan Chopra, Prakash Chandra Chhipa, Gopal Mengi, Varun Gupta

This work presents a novel domain adaption paradigm for studying contrastive self-supervised representation learning and knowledge transfer using remote sensing satellite data. Major state-of-the-art remote sensing visual domain efforts primarily focus on fully supervised learning approaches that rely entirely on human annotations. On the other hand, human a

Johannes Lengler, Andre Opris, Dirk Sudholt

Population diversity is crucial in evolutionary algorithms as it helps with global exploration and facilitates the use of crossover. Despite many runtime analyses showing advantages of population diversity, we have no clear picture of how diversity evolves over time. We study how population diversity of $(\mu+1)$ algorithms, measured by the sum of pairwise H

Haoxuan Shen, Xiaoyi Gu, Yihong Wu

A plethora of wearable devices have been developed or commercialized for continuous non-invasive monitoring of physiological signals that are crucial for preventive care and management of chronic conditions. However, most of these devices are either sensitive to skin conditions or its interface with the skin due to the requirement that the external stimuli s

Balázs Dóra, Miklós Antal Werner, Cătălin Paşcu Moca

We investigate the quantum quench dynamics of the interacting Hatano-Nelson model with open boundary conditions using both abelian bosonization and numerical methods. Specifically, we follow the evolution of the particle density and current profile in real space over time by turning the imaginary vector potential on or off in the presence of weak interaction

D. Mancini, P. Ricci, N. Vianello, G. Van Parys

Simulations of high-density deuterium plasmas in a lower single-null magnetic configuration based on a TCV discharge are presented. We evolve the dynamics of three charged species (electrons, D$^{+}$ and D$_{2}^{+}$), interacting with two neutrals species (D and D$_2$) through ionization, charge-exchange, recombination and molecular dissociation processes. T

Ben Wilks, Fabien Montiel, Sarah Wakes

Wave interaction with graded metamaterials exhibits the phenomenon of rainbow reflection, in which broadband wave signals slow down and separate into their frequency components before being reflected. This phenomenon has been qualitatively understood by describing the wave field in the metamaterial using the local Bloch wave approximation (LBWA), which local

Olga Y. Mazur, Leonid I. Stefanovich, Yuri A. Genenko

A self-consistent stochastic model of domain structure formation in a uniaxial ferroelectric, quenched from a high-temperature paraelectric phase to a low-temperature ferroelectric phase, is developed with an account of the applied electric field and the feedback effect via local depolarization fields. Both polarization and field components are considered as

Davide Venturelli, Andrea Gambassi

The overdamped dynamics of a particle is in general affected by its interaction with the surrounding medium, especially out of equilibrium, and when the latter develops spatial and temporal correlations. Here we consider the case in which the medium is modeled by a scalar Gaussian field with relaxational dynamics, and the particle is dragged at constant velo

Andrei G. Vladimirov

Weak interaction of temporal cavity solitons due to gain saturation and recovery in a delay differential model of a long cavity semiconductor laser is studied numerically and analytically using an asymptotic approach. It is shown that in addition to the usual soliton repulsion leading to a harmonic mode-locking regimes a soliton attraction is also possible i

Taras Hutak, Taras Krokhmalskii, Oleg Derzhko, Johannes Richter

We apply the rotation-invariant Green's function method to study the finite-temperature properties of a $S{=}1/2$ sawtooth-chain (also called $\Delta$-chain) antiferromagnetic Heisenberg model at the fully frustrated point when the exchange couplings along the straight-line and zig-zag paths are equal. We also use 13 terms of high-temperature expansion serie

Bohan Li, Hao Li, Wenbin Yan

We calculate the fusion rules among $\mathbb{Z}_2$-twisted modules $L_{\mathfrak{sl}_2}(\ell,0)$ at admissible levels. We derive a series MLDEs for normalized characters of ordinary twisted modules of quasi-lisse vertex algebras. Examples include affine VOAs of type $A_1^{(1)}$ at boundary admissible level, admissible level $k=-1/2$, $A^{(1)}_{2}$ at boundar

E. Petri, T. Reynaudo, R. Postoyan, D. Astolfi

Effective management and just-in-time maintenance of lithium-ion batteries require the knowledge of unmeasured (internal) variables that need to be estimated. Observers are thus designed for this purpose using a mathematical model of the battery internal dynamics. It appears that it is often difficult to tune the observers to obtain good estimation performan

Oscar Defrain, Jean-Florent Raymond

Graphs of bounded degeneracy are known to contain induced paths of order $\Omega(\log \log n)$ when they contain a path of order $n$, as proved by Ne\v{s}et\v{r}il and Ossona de Mendez (2012). In 2016 Esperet, Lemoine, and Maffray conjectured that this bound could be improved to $\Omega((\log n)^c)$ for some constant $c>0$ depending on the degeneracy. We dis

Anant Mathur, Sarat Moka, Zdravko Botev

We propose a continuous optimization algorithm for the Column Subset Selection Problem (CSSP) and Nystr\"om approximation. The CSSP and Nystr\"om method construct low-rank approximations of matrices based on a predetermined subset of columns. It is well known that choosing the best column subset of size $k$ is a difficult combinatorial problem. In this work,

Ashkan Mirzaei, Tristan Aumentado-Armstrong, Marcus A. Brubaker, Jonathan Kelly

The popularity of Neural Radiance Fields (NeRFs) for view synthesis has led to a desire for NeRF editing tools. Here, we focus on inpainting regions in a view-consistent and controllable manner. In addition to the typical NeRF inputs and masks delineating the unwanted region in each view, we require only a single inpainted view of the scene, i.e., a referenc

Lidia Aceto, Fabio Durastante

This work deals with the numerical solution of systems of oscillatory second-order differential equations which often arise from the semi-discretization in space of partial differential equations. Since these differential equations exhibit (pronounced or highly) oscillatory behavior, standard numerical methods are known to perform poorly. Our approach consis

Zoya Asghar, M. Farasat Shamir, Ammara Usman, Adnan Malik

In this article, we explore some emerging properties of the stellar objects in the frame of the $f(R,T)$ gravity by employing the well-known Karmarkar condition, where $R$ and $T$ represent Ricci scalar and trace of energy momentum tensor respectively. It is worthy to highlight here that we assume the exponential type model of $f(R,T)$ theory of gravity $f(R

Bertrand Teguia Tabuguia

A function is differentially algebraic (or simply D-algebraic) if there is a polynomial relationship between some of its derivatives and the indeterminate variable. Many functions in the sciences, such as Mathieu functions, the Weierstrass elliptic functions, and holonomic or D-finite functions are D-algebraic. These functions form a field, and are closed un

Naba P. Nayak, Surajit Sarkar, Kedar Damle, Soumya Bera

We study the transport properties of a tight-binding model of non-interacting fermions with random hopping on the honeycomb lattice. At the particle-hole symmetric chemical potential, the absence of diagonal disorder (random onsite potentials) places the system in the well-studied chiral orthogonal universality class of disordered fermion problems, which are

Cédric Zanni

Implicit surfaces are known for their ability to represent smooth objects of arbitrary topology thanks to hierarchical combinations of primitives using a structure called a blobtree. We present a new tile-based rendering pipeline well suited for modeling scenarios, i.e., no preprocessing is required when primitive parameters are updated. When using approxima

Guillaume Dujardin, Ingrid Lacroix-Violet

This paper deals with stability of classical Runge-Kutta collocation methods. When such methods are embedded in linearly implicit methods as developed in [12] and used in [13] for the time integration of nonlinear evolution PDEs, the stability of these methods has to be adapted to this context. For this reason, we develop in this paper several notions of sta

Gary Nash

Modified General Relativity (MGR) is the natural extension of General Relativity (GR). MGR explicitly uses the smooth regular line element vector field $(\bm{X},-\bm{X}) $, which exists in all Lorentzian spacetimes, to construct a connection-independent symmetric tensor that represents the energy-momentum of the gravitational field. It solves the problem of

Dilxat Muhtar, Xueliang Zhang, Pengfeng Xiao, Zhenshi Li

Self-supervised learning (SSL) has gained widespread attention in the remote sensing (RS) and earth observation (EO) communities owing to its ability to learn task-agnostic representations without human-annotated labels. Nevertheless, most existing RS SSL methods are limited to learning either global semantic separable or local spatial perceptible representa

Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama

This work contributes to developing an agent based on deep reinforcement learning capable of acting in a beyond visual range (BVR) air combat simulation environment. The paper presents an overview of building an agent representing a high-performance fighter aircraft that can learn and improve its role in BVR combat over time based on rewards calculated using

Stephen M. Barnett, Fiona C. Speirits, Joerg B. Goette

We show that Skyrmion field lines, constructed from the local Stokes parameters, trace out lines of constant optical polarisation.

Qiao Jin, Yifan Yang, Qingyu Chen, Zhiyong Lu

While large language models (LLMs) have been successfully applied to various tasks, they still face challenges with hallucinations. Augmenting LLMs with domain-specific tools such as database utilities can facilitate easier and more precise access to specialized knowledge. In this paper, we present GeneGPT, a novel method for teaching LLMs to use the Web API

George McArdle, Rose Davies, Igor V. Lerner, Igor V. Yurkevich

We investigate the Coulomb blockade in quantum dots asymmetrically coupled to the leads for an arbitrary voltage bias focusing on the regime where electrons do not thermalise during their dwell time in the dot. By solving the quantum kinetic equation, we show that the current-voltage characteristics are crucially dependent on the ratio of the Fermi energy to

Kévin Perrot, Sylvain Sené, Léah Tapin

When we focus on finite dynamical systems from both the computability/complexity and the modelling standpoints, automata networks seem to be a particularly appropriate mathematical model on which theory shall be developed. In this paper, automata networks are finite collections of entities (the automata), each automaton having its own set of possible states,

Jonah Botvinick-Greenhouse, Yunan Yang, Romit Maulik

Motivated by the computational difficulties incurred by popular deep learning algorithms for the generative modeling of temporal densities, we propose a cheap alternative which requires minimal hyperparameter tuning and scales favorably to high dimensional problems. In particular, we use a projection-based optimal transport solver [Meng et al., 2019] to join

Alessandro Nagar, Piero Rettegno, Rossella Gamba, Simone Albanesi

The success of analytic waveform modeling within the effective-one-body (EOB) approach relies on the precise understanding of the physical importance of each technical element included in the model. The urgency of constructing progressively more sophisticated and complete waveform models (e.g. including spin precession and eccentricity) partly defocused the

Fei Xue, Rongchen Guo, Siyuan Yao, Luxin Wang

Despite the value of VR (Virtual Reality) for educational purposes, the instructional power of VR in Biology Laboratory education remains under-explored. Laboratory lectures can be challenging due to students' low motivation to learn abstract scientific concepts and low retention rate. Therefore, we designed a VR-based lecture on fermentation and compared it

Liang Zhang, Anwen Hu, Jing Zhang, Shuo Hu

Visual contents, such as illustrations and images, play a big role in product manual understanding. Existing Product Manual Question Answering (PMQA) datasets tend to ignore visual contents and only retain textual parts. In this work, to emphasize the importance of multimodal contents, we propose a Multimodal Product Manual Question Answering (MPMQA) task. F

F. Filippi, L. T. Dickson, M. Backhouse, P. Forestier-Colleoni

Laser-driven plasma wakefields can provide hundreds of MeV electron beam in mm-range distances potentially shrinking the dimension of the actual particle accelerators. The plasma density plays a fundamental role in the control and stability of the acceleration process, which is a key development for the future electron injector proposed by EuPRAXIA. A gas ce

Jaap Pedersen, Jann Michael Weinand, Chloi Syranidou, Daniel Rehfeldt

Existing planning approaches for onshore wind farm siting and grid integration often do not meet minimum cost solutions or social and environmental considerations. In this paper, we develop an exact approach for the integrated layout and cable routing problem of onshore wind farm planning using the Quota Steiner tree problem. Applying a novel transformation

Vanessa Suessle, Mimi Arandjelovic, Ammie K. Kalan, Anthony Agbor

The manual processing and analysis of videos from camera traps is time-consuming and includes several steps, ranging from the filtering of falsely triggered footage to identifying and re-identifying individuals. In this study, we developed a pipeline to automatically analyze videos from camera traps to identify individuals without requiring manual interactio

Aleksandar A. Yanev, Galina D. Momcheva, Stoyan P. Pavlov

Currently, analysis of microscopic In Situ Hybridization images is done manually by experts. Precise evaluation and classification of such microscopic images can ease experts' work and reveal further insights about the data. In this work, we propose a deep-learning framework to detect and classify areas of microscopic images with similar levels of gene expre

Gilles Dowek

On the real numbers, the notions of a semi-decidable relation and that of an effectively enumerable relation differ. The second only seems to be adequate to express, in an algorithmic way, non deterministic physical theories, where magnitudes are represented by real numbers.

Raphaël Khoury, Anderson R. Avila, Jacob Brunelle, Baba Mamadou Camara

In recent years, large language models have been responsible for great advances in the field of artificial intelligence (AI). ChatGPT in particular, an AI chatbot developed and recently released by OpenAI, has taken the field to the next level. The conversational model is able not only to process human-like text, but also to translate natural language into c

Daniel Allendorf

Uniform sampling from the set $\mathcal{G}(\mathbf{d})$ of graphs with a given degree-sequence $\mathbf{d} = (d_1, \dots, d_n) \in \mathbb N^n$ is a classical problem in the study of random graphs. We consider an analogue for temporal graphs in which the edges are labeled with integer timestamps. The input to this generation problem is a tuple $\mathbf{D} =

Sitong Wang, Samia Menon, Tao Long, Keren Henderson

Short videos on social media are the dominant way young people consume content. News outlets aim to reach audiences through news reels -- short videos conveying news -- but struggle to translate traditional journalistic formats into short, entertaining videos. To translate news into social media reels, we support journalists in reframing the narrative. In li

Guanheng Chen

A prequantization bundle is a circle bundle over a symplectic surface with negative Euler class. A connection 1-form induces a natural contact form on it. The purpose of this note is to compute the ECH spectrum of the prequantization bundles of the sphere and the torus. Our proof relies on computations of the ECH cobordism maps induced by the associated line

Victor G. Kac

Foundations of the theory of vertex algebras are extended to the non-Archimedean setting.

Luiz Hartmann, Boris Vertman

In this paper we equate the analytic and the intersection Reidemeister torsions on spaces with a specific type of wedge singularities, which arise by turning the disc cross-sections in the tubular neighborhood of an embedded submanifold of even co-dimension into cones. Our result is related to a similar equation, in a setting disjoint from ours, which was pr

Lucas Georges Gabriel Charpentier, Sondre Wold, David Samuel, Egil Rønningstad

Retrieval-based language models are increasingly employed in question-answering tasks. These models search in a corpus of documents for relevant information instead of having all factual knowledge stored in its parameters, thereby enhancing efficiency, transparency, and adaptability. We develop the first Norwegian retrieval-based model by adapting the REALM

Samuel Yen-Chi Chen

This paper introduces the QDQN-DPER framework to enhance the efficiency of quantum reinforcement learning (QRL) in solving sequential decision tasks. The framework incorporates prioritized experience replay and asynchronous training into the training algorithm to reduce the high sampling complexities. Numerical simulations demonstrate that QDQN-DPER outperfo

Sarah Abusaif, Warren Singh, Timothy Sun

For each surface besides the sphere, projective plane, and Klein bottle, we construct a face-simple minimal quadrangulation, i.e., a simple quadrangulation on the fewest number of vertices possible, whose dual is also a simple graph. Our result answers a question of Liu, Ellingham, and Ye while providing a simpler proof of their main result. The inductive co

Yukai Liu, Wen Chen, Kunlun Wang

The cellular network coexisting with device-to-device (D2D) communications has been studied extensively. Reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) are promising technologies for the evolution of 5G, 6G and beyond. Besides, sparse code multiple access (SCMA) is considered suitable for next-generation wireless network i

Margaret Bilu, Tim Browning

The circle method has been successfully used over the last century to study rational points on hypersurfaces. More recently, a version of the method over function fields, combined with spreading out techniques, has led to a range of results about moduli spaces of rational curves on hypersurfaces. In this paper a version of the circle method is implemented in

Mahshid Eshghie, Mojtaba Eshghie

This paper proposes using ChatGPT, an innovative technology with various applications, as an assistant for psychotherapy. ChatGPT can serve as a patient information collector, a companion for patients in between therapy sessions, and an organizer of gathered information for therapists to facilitate treatment processes. The research identifies five research q

David Ellerman

This paper presents a new `partitional' approach to understanding or interpreting standard quantum mechanics (QM). The thesis is that the mathematics (not the physics) of QM is the Hilbert space version of the math of partitions on a set and, conversely, the math of partitions is a skeletonized set level version of the math of QM. Since at the set level, par

Ravishankar Ramanathan

The extraction of randomness from weakly random seeds is a problem of central importance with multiple applications. In the device-independent setting, this problem of quantum randomness amplification has been mainly restricted to specific weak sources of Santha-Vazirani type, while extraction from the general min-entropy sources has required a large number

J. -F. Donati, P. I. Cristofari, B. Finociety, B. Klein

In this paper we present an analysis of near-infrared spectropolarimetric and velocimetric data of the young M dwarf AU Mic, collected with SPIRou at the Canada-France-Hawaii telescope from 2019 to 2022, mostly within the SPIRou Legacy Survey. With these data, we study the large- and small-scale magnetic field of AU Mic, detected through the unpolarized and

Armando Lara-DI, Smita Mathur, Yair Krongold, Sanskriti Das

The study of the elusive hot component ($T \gtrsim 10^7$ K) of the Milky Way circumgalactic medium (CGM) is a novel topic to understand Galactic formation and evolution. In this work, we use the stacking technique through 46 lines of sight with Chandra ACIS-S HETG totaling over 10Ms of exposure time and 9 lines of sight with ACIS-S LETG observations totaling

Linyu Song, Jiasen Jin

We investigate the steady-state phase transitions in an all-to-all transverse-field Ising model subjected to an environment. The considered model is composed of two ingredient Hamiltonians. The orientation of the external field, which is perpendicular to the spin interaction, can be tuned to be along either $x$ direction or $z$ direction in each ingredient H

Alessandro Ronca

We introduce a new family of temporal logics designed to finely balance the trade-off between expressivity and complexity. Their key feature is the possibility of defining operators of a new kind that we call transformation operators. Some of them subsume existing temporal operators, while others are entirely novel. Of particular interest are transformation

Subhankar Dutta, Suchandan Kayal

In this article, we consider statistical inference based on dependent competing risks data from Marshall-Olkin bivariate Weibull distribution. The maximum likelihood estimates of the unknown model parameters have been computed by using the Newton-Raphson method under adaptive Type II progressive hybrid censoring with partially observed failure causes. The ex

Yiqun Liu, Liangjun Zhai, Songsong Yan, Di Wang

MnBi$_2$Te$_4$, the first confirmed intrinsic antiferromagnetic topological insulator, has garnered increasing attention in recent years. Here we investigate the energy correction and lifetime of magnons in MnBi$_2$Te$_4$ caused by magnon-magnon interaction. First, a calculation based on the density functional theory was performed to get the parameters of th

Kuntal Pal, Kunal Pal, Ankit Gill, Tapobrata Sarkar

We relate the probability distribution of the work done on a statistical system under a sudden quench to the Lanczos coefficients corresponding to evolution under the post-quench Hamiltonian. Using the general relation between the moments and the cumulants of the probability distribution, we show that the Lanczos coefficients can be identified with physical