April 2023 arXiv papers — page 89

Simon Badger, Michal Czakon, Heribertus Bayu Hartanto, Ryan Moodie

In this work, we provide a comprehensive set of differential cross-section distributions for photon + di-jet production in proton-proton collisions with next-to-next-to-leading order precision in massless QCD. The event selection corresponds to recent measurements by the ATLAS collaboration. We observe an improved description of data in comparison to lower-o

A. Chalkiadakis, M. Theocharakis, G. D. Barmparis, G. P. Tsironis

We investigate the use of Quantum Neural Networks for discovering and implementing quantum error-correcting codes. Our research showcases the efficacy of Quantum Neural Networks through the successful implementation of the Bit-Flip quantum error-correcting code using a Quantum Autoencoder, effectively correcting bit-flip errors in arbitrary logical qubit sta

Rupa Basu, Debasish Majumdar, Ashadul Halder, Shibaji Banerjee

The self-interacting dark matter can affect various cosmological processes. Such interactions can be number conserving (\emph{e.g.} $2 \rightarrow 2$) or number violating (\emph{e.g.} $3 \rightarrow 2,\,4 \rightarrow 2$ etc.). The latter processes where three (or more) dark matter particles undergo self-annihilation/scattering to produce less number of dark

N. K. Timofeyuk

To describe long-range behaviour of one particle removed from a few- or a many-body system, a hyperspherical cluster model has been developed. It has been applied to the ground and first excited states of helium drops with five, six, eight and ten atoms interacting via a two-body soft gaussian potential. Convergence of the hyperspherical cluster harmonics ex

Andrey Alcala, Mikhail S. Plyushchay

A correspondence is established between the dynamics of the two-vortex system and the non-commutative Landau problem (NCLP) in its sub- (non-chiral), super- (chiral) and critical phases. As a result, a trivial permutation symmetry of the point vortices induces a weak-strong coupling duality in the NCLP. We show that quantum two-vortex systems with non-zero t

Álvaro Samperio

We show that the problem of recovering the topology and admittance of an electrical network from power and voltage data at all vertices is often ill-posed, and sometimes it even has multiple solutions. We reformulate the problem to seek for a sparse network, i.e., with few edges, which fits the data up to a given tolerance. We propose an algorithm to solve t

Sonia Bullah, Terence L. van Zyl

Multi-objective portfolio optimisation is a critical problem researched across various fields of study as it achieves the objective of maximising the expected return while minimising the risk of a given portfolio at the same time. However, many studies fail to include realistic constraints in the model, which limits practical trading strategies. This study i

Agnes Marjorie Nakiganda, Shahab Dehghan, Petros Aristidou

The integration of the frequency dynamics into Micro-Grid (MG) investment and operational planning problems is vital in ensuring the security of the system in the post-contingency states. However, the task of including transient security constraints in MG planning problems is non-trivial. This is due to the highly non-linear and non-convex nature of the anal

Oleg Imanuvilov, Hongyu Liu, Masahiro Yamamoto

We consider solutions satisfying the zero Neumann boundary condition and a linearized mean field game equation in $\Omega \times (0,T)$ whose principal coefficients depend on the time and spatial variables with general Hamiltonian, where $\Omega$ is a bounded domain in $\Bbb R^d$ and $(0,T)$ is the time interval. We first prove the Lipschitz stability in $\O

Deepan Chakravarthi Padmanabhan, Shruthi Gowda, Elahe Arani, Bahram Zonooz

Few-shot learning (FSL) techniques seek to learn the underlying patterns in data using fewer samples, analogous to how humans learn from limited experience. In this limited-data scenario, the challenges associated with deep neural networks, such as shortcut learning and texture bias behaviors, are further exacerbated. Moreover, the significance of addressing

Jaemin Cho, Linjie Li, Zhengyuan Yang, Zhe Gan

Spatial control is a core capability in controllable image generation. Advancements in layout-guided image generation have shown promising results on in-distribution (ID) datasets with similar spatial configurations. However, it is unclear how these models perform when facing out-of-distribution (OOD) samples with arbitrary, unseen layouts. In this paper, we

Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components, we apply a Bayesian picture, based on the functions expressed by a DNN, to supervised learning. The prior over functions is determined by

Nicolás Morales-Durán, Jie Wang, Gabriel R. Schleder, Mattia Angeli

We show that pressure applied to twisted WSe$_2$ can enhance the many-body gap and region of stability of a fractional Chern insulator at filling $\nu = 1/3$. Our results are based on exact diagonalization of a continuum model, whose pressure-dependence is obtained through {\it ab initio} methods. We interpret our results in terms of a {\it magic line} in th

Amit Kumar Rana, Sabarinath Mahadevan, Alexander Hermans, Bastian Leibe

Most state-of-the-art instance segmentation methods rely on large amounts of pixel-precise ground-truth annotations for training, which are expensive to create. Interactive segmentation networks help generate such annotations based on an image and the corresponding user interactions such as clicks. Existing methods for this task can only process a single ins

Mohammadreza Doostmohammadian, Alireza Aghasi, Houman Zarrabi

This paper considers distributed optimization algorithms, with application in binary classification via distributed support-vector-machines (D-SVM) over multi-agent networks subject to some link nonlinearities. The agents solve a consensus-constraint distributed optimization cooperatively via continuous-time dynamics, while the links are subject to strongly

Nicolas Vaskou

We compute explicitly the automorphism and outer automorphism group of all large-type free-of-infinity Artin groups. Our strategy involves reconstructing the associated Deligne complexes in a purely algebraic manner, i.e. in a way that is independent from the choice of standard generators for the groups.

Brian Hall, Ching-Wei Ho, Jonas Jalowy, Zakhar Kabluchko

We establish basic properties of the heat flow on entire holomorphic functions that have order at most 2. We then look specifically at the action of the heat flow on the Gaussian analytic function (GAF). We show that applying the heat flow to a GAF and then rescaling and multiplying by an exponential of a quadratic function gives another GAF. It follows that

Noah G. Singer

In this thesis, we explore streaming algorithms for approximating constraint satisfaction problems (CSPs). The setup is roughly the following: A computer has limited memory space, sees a long "stream" of local constraints on a set of variables, and tries to estimate how many of the constraints may be simultaneously satisfied. The past ten years have seen a n

John Ellis, Ken Mimasu, Francesca Zampedri

We analyze the constraints obtainable from present data using the Standard Model Effective Field Theory (SMEFT) on extensions of the Standard Model with additional electroweak singlet or triplet scalar fields. We compare results obtained using only contributions that are linear in dimension-6 operator coefficients with those obtained including terms quadrati

Luyang Luo, Xi Wang, Yi Lin, Xiaoqi Ma

Breast cancer has reached the highest incidence rate worldwide among all malignancies since 2020. Breast imaging plays a significant role in early diagnosis and intervention to improve the outcome of breast cancer patients. In the past decade, deep learning has shown remarkable progress in breast cancer imaging analysis, holding great promise in interpreting

Wajid Ali, Christopher E. Overton, Robert R. Wilkinson, Kieran J. Sharkey

The basic reproduction number, $R_0$, is a well-known quantifier of epidemic spread. However, a class of existing methods for estimating $R_0$ from incidence data early in the epidemic can lead to an over-estimation of this quantity. In particular, when fitting deterministic models to estimate the rate of spread, we do not account for the stochastic nature o

Norbert J. Mauser, Jakob Möller, Changhe Yang

The self-consistent Pauli-Poisswell and Pauli-Darwin equations for 2-spinors are $O(1/c)$ (where $c$ denotes the speed of light) semi-relativistic approximations of the Dirac-Maxwell equation for 4-spinors coupled to the self-consistent electromagnetic fields generated by the charge and current densities of a fast moving electric charge. They consist of a ve

Nicholas P. Herrington, Clare L. Dobbs, Thomas J. R. Bending

We present hydrodynamic and magnetohydrodynamic (MHD) simulations of sub galactic regions including photoionising and supernova feedack. We aim to improve the initial conditions of our region extraction models by including an initial population of stars. We also investigate the reliability of extracting regions in simulations, and show that with a good choic

Yuichi Harikane, Kimihiko Nakajima, Masami Ouchi, Hiroya Umeda

We present pure spectroscopic constraints on the UV luminosity functions and cosmic star formation rate (SFR) densities from 25 galaxies at $z_\mathrm{spec}=8.61-13.20$. By reducing the JWST/NIRSpec spectra taken in multiple programs of ERO, ERS, GO, and DDT with our analysis technique, we independently confirm 16 galaxies at $z_\mathrm{spec}=8.61-11.40$ inc

R. Rodriguez-Guzman, L. M. Robledo, C. A. Jimenez-Hoyos, N. C. Hernandez

The impact of dynamic pairing correlations and their interplay with Coulomb antipairing effects on the systematic of the spontaneous fission half-lives for the nuclei $^{240-250}$Cm and $^{240-250}$Cf is analyzed, using a hierarchy of approximations based on the parametrization D1M of the Gogny energy density functional (EDF). First, the constrained Hartree-

Michael Dinitz, Ama Koranteng, Guy Kortsarz, Zeev Nutov

One of the most important and well-studied settings for network design is edge-connectivity requirements. This encompasses uniform demands such as the Minimum $k$-Edge-Connected Spanning Subgraph problem as well as nonuniform demands such as the Survivable Network Design problem (SND). In a recent paper by [Dinitz, Koranteng, Kortsarz APPROX '22] , the autho

Iskra Y. Georgieva, Carina M. Persson, Elisa Goffo, Lorena Acuña

We report the discovery of a hot ($T_{\rm eq}$ $\approx$ 1055 K) planet in the small planet radius valley transiting the Sun-like star TOI-733, as part of the KESPRINT follow-up program of TESS planets carried out with the HARPS spectrograph. TESS photometry from sectors 9 and 36 yields an orbital period of $P_{\rm orb}$ = $4.884765 _{ - 2.4e-5 } ^ { + 1.9e-

Christophe Vanderaa, Laurent Gatto

Missing values are a notable challenge when analysing mass spectrometry-based proteomics data. While the field is still actively debating on the best practices, the challenge increased with the emergence of mass spectrometry-based single-cell proteomics and the dramatic increase in missing values. A popular approach to deal with missing values is to perform

Fahad Sarfraz, Elahe Arani, Bahram Zonooz

Humans excel at continually acquiring, consolidating, and retaining information from an ever-changing environment, whereas artificial neural networks (ANNs) exhibit catastrophic forgetting. There are considerable differences in the complexity of synapses, the processing of information, and the learning mechanisms in biological neural networks and their artif

Leihang Zhang, Jiapeng Liu, Qiang Yan

It has been reported that clustering-based topic models, which cluster high-quality sentence embeddings with an appropriate word selection method, can generate better topics than generative probabilistic topic models. However, these approaches suffer from the inability to select appropriate parameters and incomplete models that overlook the quantitative rela

Rui Yang, Pei Liu, Luping Ji

Due to the limitations of inadequate Whole-Slide Image (WSI) samples with weak labels, pseudo-bag-based multiple instance learning (MIL) appears as a vibrant prospect in WSI classification. However, the pseudo-bag dividing scheme, often crucial for classification performance, is still an open topic worth exploring. Therefore, this paper proposes a novel sche

Guantao Chen, Songling Shan

Let $G$ be a multigraph. A subset $F$ of $E(G)$ is an edge cover of $G$ if every vertex of $G$ is incident to an edge of $F$. The cover index, $\xi(G)$, is the largest number of edge covers into which the edges of $G$ can be partitioned. Clearly $\xi(G) \le \delta(G)$, the minimum degree of $G$. For $U\subseteq V(G)$, denote by $E^+(U)$ the set of edges inci

Sally Giuseppe Arcidiacono, Salvatore Corrente, Salvatore Greco

In multiple criteria decision aiding, very often the alternatives are compared by means of a value function compatible with the preferences expressed by the Decision Maker. The problem is that, in general, there is a plurality of compatible value functions, and providing a final recommendation on the problem at hand considering only one of them could be cons

Enze Xie, Lewei Yao, Han Shi, Zhili Liu

Diffusion models have proven to be highly effective in generating high-quality images. However, adapting large pre-trained diffusion models to new domains remains an open challenge, which is critical for real-world applications. This paper proposes DiffFit, a parameter-efficient strategy to fine-tune large pre-trained diffusion models that enable fast adapta

Łukasz Baran, Dariusz Tarasewicz, Daniel M. Kamiński, Wojciech Rżysko

The endeavor to selectively fabricate a cubic diamond is challenging due to the formation of competing phases such as its hexagonal polymorph or others possessing similar free energy. The necessity to achieve this is of paramount importance since the cubic diamond is the only polymorph exhibiting a complete photonic bandgap, making it a promising candidate i

Balder ten Cate, Raoul Koudijs

We study the existence of finite characterisations for modal formulas. A finite characterisation of a modal formula $\varphi$ is a finite collection of positive and negative examples that distinguishes $\varphi$ from every other, non-equivalent modal formula, where an example is a finite pointed Kripke structure. This definition can be restricted to specific

Ahmad Ahmad, Cristian-Ioan Vasile, Roberto Tron, Calin Belta

Temporal logics (TLs) have been widely used to formalize interpretable tasks for cyber-physical systems. Time Window Temporal Logic (TWTL) has been recently proposed as a specification language for dynamical systems. In particular, it can easily express robotic tasks, and it allows for efficient, automata-based verification and synthesis of control policies

Daniel Bonilla Licea, Giuseppe Silano, Mounir Ghogho, Martin Saska

The use of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) has seen significant growth in the research community, industry, and society. Many of these agents are equipped with communication systems that are essential for completing certain tasks successfully. This has led to the emergence of a new interdisciplinary field at the intersecti

Minghui Xu, Yihao Guo, Chunchi Liu, Qin Hu

Blockchain has attracted significant attention in recent years due to its potential to revolutionize various industries by providing trustlessness. To comprehensively examine blockchain systems, this article presents both a macro-level overview on the most popular blockchain systems, and a micro-level analysis on a general blockchain framework and its crucia

Sepideh Gherekhloo, Khaled Ardah, Martin Haardt

In this paper, we consider the channel estimation problem in sub-6 GHz uplink wideband MIMO-OFDM communication systems, where a user equipment with a fully-digital beamforming structure is communicating with a base station having a hybrid analog-digital beamforming structure. A novel channel estimation method called Sequential Alternating Least Squares Appro

B. T. Dullo, J. H. Knapen, R. J. Beswick, R. D. Baldi

Multiwavelength studies indicate that nuclear activity and bulge properties are closely related, but the details remain unclear. To study this further, we combine $Hubble~Space~Telescope$ bulge structural and photometric properties with 1.5 GHz, $e$-MERLIN nuclear radio continuum data from the LeMMINGs survey for a large sample of 173 `active' galaxies (LINE

Mushtaq Ahmad, M. Farasat Shamir, G. Mustafa

In recent few years, the Gauss-Bonnet $f(\mathcal{G},\mathrm{\textit{T}})$ theory of gravity has fascinated considerable researchers owing to its coupling of trace of the stress-energy tensor $T$ with the Gauss-Bonnet term $\mathcal{G}$. In this context, we focuss ourselves to study bouncing universe with in $f(\mathcal{G},\mathrm{\textit{T}})$ gravity backg

Giorgio Mentasti, Carlo Contaldi, Marco Peloso

We build an analytical framework to study the observability of anisotropies and a net chiral polarization of the Stochastic Gravitational Wave Background (SGWB) with a generic network of ground-based detectors. We apply this formalism to perform a Fisher forecast of the performance of a network consisting of the current interferometers (LIGO, Virgo and KAGRA

Hauke Sandhaus, Wendy Ju, Qian Yang

Autonomous Vehicles (AVs) can potentially improve urban living by reducing accidents, increasing transportation accessibility and equity, and decreasing emissions. Realizing these promises requires the innovations of AV driving behaviors, city plans and infrastructure, and traffic and transportation policies to join forces. However, the complex interdependen

Sabina Elkins, Ekaterina Kochmar, Jackie C. K. Cheung, Iulian Serban

Controllable text generation (CTG) by large language models has a huge potential to transform education for teachers and students alike. Specifically, high quality and diverse question generation can dramatically reduce the load on teachers and improve the quality of their educational content. Recent work in this domain has made progress with generation, but

Grahame Erskine, Terry Griggs, Robert Lewis, James Tuite

Two Eulerian circuits, both starting and ending at the same vertex, are avoiding if at every other point of the circuits they are at least distance 2 apart. An Eulerian graph which admits two such avoiding circuits starting from any vertex is said to be doubly Eulerian. The motivation for this definition is that the extremal Eulerian graphs, i.e. the complet

Hongjie Yu

Let $X$ be a projective smooth geometrically connected curve defined over a finite field $\mathbb{F}_q$ of cardinality $q$. Let $S$ be a finite set of closed points of $X$. Let $\bar{X}$ and $\bar{S}$ be the base change of $X$, $S$ to an algebraic closure. We consider the set of $\ell$-adic ($\ell\nmid q$) local systems of rank $n$ over $\bar{X}-\bar{S}$ wit

Marylou Gabrié, Surya Ganguli, Carlo Lucibello, Riccardo Zecchina

Artificial networks have been studied through the prism of statistical mechanics as disordered systems since the 80s, starting from the simple models of Hopfield's associative memory and the single-neuron perceptron classifier. Assuming data is generated by a teacher model, asymptotic generalisation predictions were originally derived using the replica metho

Thomas Bornstein, Dietrich Lange, Jannes Münchmeyer, Jack Woollam

Detecting phase arrivals and pinpointing the arrival times of seismic phases in seismograms is crucial for many seismological analysis workflows. For land station data machine learning methods have already found widespread adoption. However, deep learning approaches are not yet commonly applied to ocean bottom data due to a lack of appropriate training data

Rui Ribeiro, Joao P. Carvalho, Luísa Coheur

Recent approaches have attempted to personalize dialogue systems by leveraging profile information into models. However, this knowledge is scarce and difficult to obtain, which makes the extraction/generation of profile information from dialogues a fundamental asset. To surpass this limitation, we introduce the Profile Generation Task (PGTask). We contribute

Sunder Ali Khowaja, Parus Khuwaja, Kapal Dev, Weizheng Wang

ChatGPT is another large language model (LLM) vastly available for the consumers on their devices but due to its performance and ability to converse effectively, it has gained a huge popularity amongst research as well as industrial community. Recently, many studies have been published to show the effectiveness, efficiency, integration, and sentiments of cha

Severin Bunk, C. S. Shahbazi

We study smooth higher symmetry groups and moduli $\infty$-stacks of generic higher geometric structures on manifolds. Symmetries are automorphisms which cover non-trivial diffeomorphisms of the base manifold. We construct the smooth higher symmetry group of any geometric structure on $M$ and show that this completely classifies, via a universal property, eq

Michiel Busschaert, Florence H. Vermeire, Steffen Waldherr

For over two decades, Flux Balance Analysis (FBA) has been successfully used for predicting growth rates and intracellular reaction rates in microbiological metabolism. An aspect that is often omitted from this analysis, is segregation or heterogeneity between different cells. In this work, we propose an extended FBA method to model cell size distributions i

Ziwei Gao

This paper introduces time-based addiction, which refers to excessive engagement in an activity that results in negative outcomes due to the misallocation of time. This type of addiction is often seen in media-related activities such as video games, social media, and television watching. Behavioural design in video games plays a significant role in enabling

Nathan Lindzey

For each integer partition $\lambda \vdash n$ we give a simple combinatorial expression for the sum of the Jack character $\theta^\lambda_\alpha$ over the integer partitions of $n$ with no singleton parts. For $\alpha = 1,2$ this gives closed forms for the eigenvalues of the permutation and perfect matching derangement graphs, resolving an open question in a

Selim Ghazouani, Corinna Ulcigrai

We consider generalized interval exchange transformations (GIETs) of d intervals ($d\geq 2$) which are linearizable, i.e. differentiably conjugated to standard interval exchange maps (IETs) via a diffeomorphism h of [0, 1] and study the regularity of the conjugacy h. Using a renormalisation operator obtained accelerating Rauzy-Veech induction, we show that,

Haozhe Feng, Zhaorui Yang, Hesun Chen, Tianyu Pang

Without access to the source data, source-free domain adaptation (SFDA) transfers knowledge from a source-domain trained model to target domains. Recently, SFDA has gained popularity due to the need to protect the data privacy of the source domain, but it suffers from catastrophic forgetting on the source domain due to the lack of data. To systematically inv

Anders Lansner, Florian Fiebig, Pawel Herman

Theories and models of working memory (WM) were at least since the mid-1990s dominated by the persistent activity hypothesis. The past decade has seen rising concerns about the shortcomings of sustained activity as the mechanism for short-term maintenance of WM information in the light of accumulating experimental evidence for so-called activity-silent WM an

Pralay Chakraborty, Subhankar Roy

Two new neutrino mass matrix textures exhibiting the \emph{mixed $\mu$-$\tau$ symmetry} are proposed. The mass matrices hint for a promising neutrino mixing schemes and find their connections with $\Delta(27)$ and $A_{4}$ discrete symmetry groups respectively.

Natalia Pavlasek, Sarah H. Q. Li, Behçet Açıkmeşe, Meeko Oishi

In many resource-limited optimal control problems, multiple constraints may be enforced that are jointly infeasible due to external factors such as subsystem failures, unexpected disturbances, or fuel limitations. In this manuscript, we introduce the concept of blameless optimality to characterize control actions that a) satisfy the highest prioritized and f

Joshua C. Smith, Dan Ryczanowski, Matteo Bianconi, Denisa Cristescu

We combine the Planck-SZ2 galaxy cluster catalogue with near-infrared photometry of galaxies from the VISTA Hemisphere Survey to identify candidate brightest cluster galaxies (BCGs) in 306 massive clusters in the Southern skies at redshifts of $z>0.1$. We find that 91% of these clusters have at least one candidate BCG within the 95% confidence interval on th

Abdelrahman Abdallah, Bhawna Piryani, Adam Jatowt

Answering questions related to the legal domain is a complex task, primarily due to the intricate nature and diverse range of legal document systems. Providing an accurate answer to a legal query typically necessitates specialized knowledge in the relevant domain, which makes this task all the more challenging, even for human experts. Question answering (QA)

Tanmay Deshpande, Saniya Wagh

Let $\breve{K}$ be a complete discrete valuation field with an algebraically closed residue field ${k}$ and ring of integers $\breve{{O}}$. Let $T$ be a torus defined over $\breve{K}$. Let $L^+T$ denote the connected commutative pro-algebraic group over ${k}$ obtained by applying the Greenberg functor to the connected N\'eron model of $T$ over $\breve{{O}}$.

Reece N. Oosterbeek, Gabriela Sirbu, Selma Hansal, Kenneth Nai

Additive manufacturing (AM) has enabled the fabrication of extremely complex components such as porous metallic lattices, which have applications in aerospace, automotive, and in particular biomedical devices. The fatigue resistance of these materials is currently an important limitation however, due to manufacturing defects such as semi-fused particles and

Archit Karandikar, Akashnil Dutta

The Queen's Domination problem, studied for over 160 years, poses the following question: What is the least number of queens that can be arranged on a $m \times n$ chessboard so that they either attack or occupy every cell? We propose a novel relaxation of the Queen's Domination problem and show that it is exactly solvable on both square and rectangular ches

Dewant Katare, Diego Perino, Jari Nurmi, Martijn Warnier

Autonomous driving services rely heavily on sensors such as cameras, LiDAR, radar, and communication modules. A common practice of processing the sensed data is using a high-performance computing unit placed inside the vehicle, which deploys AI models and algorithms to act as the brain or administrator of the vehicle. The vehicular data generated from averag

Mathieu Pagé Fortin

This paper investigates the problem of class-incremental object detection for agricultural applications where a model needs to learn new plant species and diseases incrementally without forgetting the previously learned ones. We adapt two public datasets to include new categories over time, simulating a more realistic and dynamic scenario. We then compare th

Jonas Lund, Lucas Bjarke Jensen, Nick Battle, Peter Gorm Larsen

The VDM-PlantUML Plugin enables translations between the text based UML tool PlantUML and VDM++ and has been released as a part of the VDM VSCode extension. This enhances already extensive feature-set of VDM VSCode with support for UML. The link between VDM and UML is thoroughly described with a set of translation rules that serve as the base of the implemen

Mattias T. Johnsson, Lauritz van Luijk, Daniel Burgarth

A fundamental problem in quantum engineering is determining the lowest time required to ensure that all possible unitaries can be generated with the tools available, which is one of a number of possible quantum speed limits. We examine this problem from the perspective of quantum control, where the system of interest is described by a drift Hamiltonian and s

Takeshi Suguro, Toshiaki Yachimura

In this paper, we study the Tsallis entropic regularized optimal transport in the continuous setting and establish fundamental results such as the $\Gamma$-convergence of the Tsallis regularized optimal transport to the Monge--Kantorovich problem as the regularization parameter tends to zero. In addition, using the quantization and shadow arguments developed

Anu Sreedevi, Bibhuti Kumar Jha, Bidya Binay Karak, Dipankar Banerjee

Bipolar Magnetic Regions (BMRs) provide crucial information about solar magnetism. They exhibit varying morphology and magnetic properties throughout their lifetime, and studying these properties can provide valuable insights into the workings of the solar dynamo. The majority of previous studies have counted every detected BMR as a new one and have not been

E. Aydiner

In this study, we consider dark matter and dark energy as grand-canonical systems which are open, non-equilibrium coupled, and interacting systems. For the first time, we propose a new more realistic interaction scheme to explain dynamics between coupled interacting thermodynamic systems. Based on this new interaction schema, we propose new theorems to defin

Massimiliano Stengel

We show that a lattice mode of arbitrary symmetry induces a well-defined macroscopic polarization at first order in the momentum and second order in the amplitude. We identify a symmetric flexoelectric-like contribution, which is sensitive to both the electrical and mechanical boundary conditions, and an antisymmetric Dzialoshinskii-Moriya-like term, which i

Axel Brandenburg, Kohei Kamada, Kyohei Mukaida, Kai Schmitz

We study the evolution of magnetic fields coupled with chiral fermion asymmetry in the framework of chiral magnetohydrodynamics with zero initial total chirality. The initial magnetic field has a turbulent spectrum peaking at a certain characteristic scale and is fully helical with positive helicity. The initial chiral chemical potential is spatially uniform

Salvador Cardona-Barrero, Giuseppina Battaglia, Carlo Nipoti, Arianna Di Cintio

An anti-correlation between the central density of the dark matter halo ($\rho_{150,\ {\rm DM}}$) and the pericentric distances ($r_{p}$) of the Milky Way's (MW's) dwarf spheroidal galaxies (dSphs) has been reported in the literature. The existence and origin of such anti-correlation is however controversial, one possibility being that only the densest dSphs

Lev Birbrair, Rodrigo Mendes

In this paper, we study Multi-$\mathcal{K}$-equivalence of multi-germs of functions on the plane, definable in a polynomially bounded o-minimal structure. We partition the germ of the plane at origin into zones of arcs in such a way that it produces a non-Archimedean space (set of orders and width functions) compatible with a given multigerm, encoding its as

Giulio Caviglia, Alessandro De Stefani, Enrico Sbarra, Francesco Strazzanti

In this survey paper we first present the main properties of sequentially Cohen-Macaulay modules. Some basic examples are provided to help the reader with quickly getting acquainted with this topic. We then discuss two generalizations of the notion of sequential Cohen-Macaulayness which are inspired by a theorem of J\"urgen Herzog and the third author.

Chaofan Gong

The exploitation of spin Berry phases to generate emergent fields for producing miniaturized and high-quality inductors has enjoyed considerable popularity among proponents of quantum technologies [Nature 586, 202 (2020)}]. Inspired by this breakthrough, we extend its mechanism to spin thermoelectrics by probing responses of ferrimagnetic domain walls (DWs)

Jian Liu, Rui Zhang, Sebastian Szyller, Kui Ren

Deep neural network (DNN) models are valuable intellectual property of model owners, constituting a competitive advantage. Therefore, it is crucial to develop techniques to protect against model theft. Model ownership resolution (MOR) is a class of techniques that can deter model theft. A MOR scheme enables an accuser to assert an ownership claim for a suspe

Deepsikha Das, Punyabrata Pradhan, Sakuntala Chatterjee

We study one-dimensional hardcore lattice gases, with nearest-neighbor interactions, in the presence of an external potential barrier, that moves on the periodic lattice with a constant speed. We investigate how the nature of the interaction (attractive or repulsive) affects particle transport and determine, using numerical simulations and mean-field calcula

Haimiao Chen

We give an explicit presentation for the Kauffman bracket skein algebra of the $5$-punctured sphere over any commutative unitary ring.

O. Siebinga, A. Zgonnikov, D. A. Abbink

A major challenge for autonomous vehicles is handling interactive scenarios, such as highway merging, with human-driven vehicles. A better understanding of human interactive behaviour could help address this challenge. Such understanding could be obtained through modelling human behaviour. However, existing modelling approaches predominantly neglect communic

Erick Fredj, Yann Delorme, Sameeh Jubran, Mark Wasserman

With the approach of Exascale computing power for large-scale High Performance Computing (HPC) clusters, the gap between compute capabilities and storage systems is growing larger. This is particularly problematic for the Weather Research and Forecasting Model (WRF), a widely-used HPC application for high-resolution forecasting and research that produces siz

Duc Minh Vo, Quoc-An Luong, Akihiro Sugimoto, Hideki Nakayama

Humans possess the capacity to reason about the future based on a sparse collection of visual cues acquired over time. In order to emulate this ability, we introduce a novel task called Anticipation Captioning, which generates a caption for an unseen oracle image using a sparsely temporally-ordered set of images. To tackle this new task, we propose a model c

Feugeas Jean-Luc, Mathiaud Julien, Mieussens Luc, Vigier Thomas

Moment models with suitable closure can lead to accurate and computationally efficient solvers for particle transport. Hence, we propose a new asymptotic preserving scheme for the M1 model of linear transport that works uniformly for any Knudsen number. Our idea is to apply the M1 closure at the numerical level to an existing asymptotic preserving scheme for

Mohit Sharma, Claudio Fantacci, Yuxiang Zhou, Skanda Koppula

Recent works have shown that large models pretrained on common visual learning tasks can provide useful representations for a wide range of specialized perception problems, as well as a variety of robotic manipulation tasks. While prior work on robotic manipulation has predominantly used frozen pretrained features, we demonstrate that in robotics this approa

Stefanie J. Beale, Joel J. Wallman

Measurements are a vital part of any quantum computation, whether as a final step to retrieve results, as an intermediate step to inform subsequent operations, or as part of the computation itself (as in measurement-based quantum computing). However, measurements, like any aspect of a quantum system, are highly error-prone and difficult to model. In this pap

Luciano Pandolfi

Leonida Tonelli devised an interesting and efficient method to introduce the Lebesgue integral. The details of this method can only be found in the original Tonelli paper and in an old italian course and solely for the case of the functions of one variable. We believe that this method is worth knowing and here we present a complete account for functions of e

Michael Xieyang Liu, Advait Sarkar, Carina Negreanu, Ben Zorn

Code-generating large language models translate natural language into code. However, only a small portion of the infinite space of naturalistic utterances is effective at guiding code generation. For non-expert end-user programmers, learning this is the challenge of abstraction matching. We examine this challenge in the specific context of data analysis in s

Shaojie Tang, Jing Yuan

Machine learning algorithms play an important role in a variety of important decision-making processes, including targeted advertisement displays, home loan approvals, and criminal behavior predictions. Given the far-reaching impact of these algorithms, it is crucial that they operate fairly, free from bias or prejudice towards certain groups in the populati

Ping Dong, Fan Gao, Runze Wang

For square-integrable genuine Iwahori-spherical representations of central covers, we verify the Hiraga--Ichino--Ikeda formula for their formal degrees. We also compute the Whittaker dimensions of these representations, when their associated modules over the genuine Iwahori--Hecke algebra are one-dimensional.

Yichuan Deng, Yeqi Gao, Zhao Song

Large language models have become ubiquitous in modern life, finding applications in various domains such as natural language processing, language translation, and speech recognition. Recently, a breakthrough work [Zhao, Panigrahi, Ge, and Arora Arxiv 2023] explains the attention model from probabilistic context-free grammar (PCFG). One of the central comput

Orlando Luongo, Stefano Mancini, Paolo Pierosara

The Bardeen and Hayward spacetimes are here considered as standard configurations of spherically symmetric regular black holes. Assuming the thermodynamics of such objects to be analogous to standard black holes, we compute the island formula in the regime of small topological charge and large vacuum energy, respectively for Bardeen and Hayward spacetimes. L

Derya Altıntan, Bastian Alt, Heinz Koeppl

Biochemical reaction networks are an amalgamation of reactions where each reaction represents the interaction of different species. Generally, these networks exhibit a multi-scale behavior caused by the high variability in reaction rates and abundances of species. The so-called jump-diffusion approximation is a valuable tool in the modeling of such systems.

Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé

Age is an important variable to describe the expected brain's anatomy status across the normal aging trajectory. The deviation from that normative aging trajectory may provide some insights into neurological diseases. In neuroimaging, predicted brain age is widely used to analyze different diseases. However, using only the brain age gap information (\ie the

Chun-Wang Wu, Man-Chao Zhang, Yan-Li Zhou, Ting Chen

Quantum correlations, both spatial and temporal, are the central pillars of quantum mechanics. Over the last two decades, a big breakthrough in quantum physics is its complex extension to the non-Hermitian realm, and dizzying varieties of novel phenomena and applications beyond the Hermitian framework have been uncovered. However, unique features of non-Herm

Gil Solanes, Juan Andrés Trillo

Given an isometry invariant valuation on a complex space form we compute its value on the tubes of sufficiently small radii around a set of positive reach. This generalizes classical formulas of Weyl, Gray and others about the volume of tubes. We also develop a general framework on tube formulas for valuations in riemannian manifolds.

Petter Törnberg

This paper assesses the accuracy, reliability and bias of the Large Language Model (LLM) ChatGPT-4 on the text analysis task of classifying the political affiliation of a Twitter poster based on the content of a tweet. The LLM is compared to manual annotation by both expert classifiers and crowd workers, generally considered the gold standard for such tasks.

Francois Jamet, Lachlan P. Lindoy, Yannic Rath, Connor Lenihan

Solving the Anderson impurity model typically involves a two-step process, where one first calculates the ground state of the Hamiltonian, and then computes its dynamical properties to obtain the Green's function. Here we propose a hybrid classical/quantum algorithm where the first step is performed using a classical computer to obtain the tensor network gro

Zoé-Lise Deck-Léger, Amir Bahrami, Zhiyu Li, Christophe Caloz

Electromagnetic scattering in moving structures is a fundamental topic in physics and engineering. Yet, no general numerical solution to related problems has been reported to date. We introduce here a generalized FDTD scheme to remedy this deficiency. That scheme is an extension of the FDTD standard Yee cell and stencil that includes not only the usual, phys