July 2023 arXiv papers — page 37

Hojin Kim, Varun Shankar, Venkatasubramanian Viswanathan, Romit Maulik

Differentiable physical simulators are proving to be valuable tools for developing data-driven models for computational fluid dynamics (CFD). In particular, these simulators enable end-to-end training of machine learning (ML) models embedded within CFD solvers. This paradigm enables novel algorithms which combine the generalization power and low cost of phys

Roman V. Poberezhnyuk, Horst Stoecker, Volodymyr Vovchenko

We incorporate the empirical low-density properties of isospin symmetric nuclear matter into the excluded-volume model for quarkyonic matter by including attractive mean field in the nucleonic sector and considering variations on the nucleon excluded volume mechanism. This corresponds to the quantum van der Waals equation for nucleons, with the interaction p

Giorgos Anastasiou, Ignacio J. Araya, Avik Chakraborty

We describe a method to generate scalar-tensor theories with Weyl symmetry, starting from arbitrary purely metric higher derivative gravity theories. The method consists in the definition of a conformally-invariant metric $\hat{g}_{\mu \nu}$, that is a rank (0,2)-tensor constructed out of the metric tensor and the scalar field. This new object has zero confo

Richard G. French, Damya Souami

In support of studies of decadal-timescale evolution of outer solar system atmospheres and ring systems, we present detailed Earth-based stellar occultation predictions for Jupiter, Saturn, Uranus, Neptune, Titan, and Triton for 2023-2050, based on the Gaia DR3 star catalog and near-IR K-band photometry from the 2MASS catalog. We tabulate the number of obser

Yichao Cao, Qingfei Tang, Feng Yang, Xiu Su

Human-Object Interaction (HOI) detection is a challenging computer vision task that requires visual models to address the complex interactive relationship between humans and objects and predict HOI triplets. Despite the challenges posed by the numerous interaction combinations, they also offer opportunities for multimodal learning of visual texts. In this pa

I-Chun Chern, Steffi Chern, Shiqi Chen, Weizhe Yuan

The emergence of generative pre-trained models has facilitated the synthesis of high-quality text, but it has also posed challenges in identifying factual errors in the generated text. In particular: (1) A wider range of tasks now face an increasing risk of containing factual errors when handled by generative models. (2) Generated texts tend to be lengthy an

Roberto Leotta, Oliver Giudice, Luca Guarnera, Sebastiano Battiato

Diffusion Models (DM) are highly effective at generating realistic, high-quality images. However, these models lack creativity and merely compose outputs based on their training data, guided by a textual input provided at creation time. Is it acceptable to generate images reminiscent of an artist, employing his name as input? This imply that if the DM is abl

C. A. Downing, O. I. R. Fox

Theories in physics can provide a kind of map of the physical system under investigation, showing all of the possible types of behavior which may occur. Certain points on the map are of greater significance than others, because they describe how the system responds in a useful or interesting manner. For example, the point of resonance is of particular import

Z. W. Lu, S. L. Zhou

In this article, we investigate symmetric 2-designs of prime order admitting a flag-transitive automorphism group G. Recently, the authors proved that the automorphism group G of this type of designs must be point-primitive, and is of affine or almost simple type. Here, we give the complete classification of symmetric 2-designs of prime order, admitting a fl

Lech Wiktor Piotrowski

The vast amounts of data to be collected by the Giant Radio Array for Neutrino Detection (GRAND) and its prototype - GRANDProto300 - require the use of a data format very efficient in terms of i/o speed and compression. At the same time, the data should be easily accessible, without the knowledge of the intricacies of the format, both for bulk processing and

Nooshin M. Estakhri, Ada Warren, Sophia E. Economou, Edwin Barnes

Superconducting microwave resonator couplers will likely become an essential component in modular semiconductor quantum dot (QD) spin qubit processors, as they help alleviate cross-talk and wiring issues as the number of qubits increases. Here, we focus on a three-qubit system composed of two modules: a two-electron triple QD resonator-coupled to a single-el

J. A. Vélez, R. M. Otxoa, U. Atxitia

The experimental discovery of single-pulse ultrafast magnetization switching in ferrimagnetic alloys, such as GdFeCo and MnRuGa, opened the door to a promising route toward faster and more energy efficient data storage. A recent semi-phenomenological theory has proposed that a fast, laser-induced demagnetization below a threshold value puts the system into a

Leo Patrick Mulholland, Yannick Feld, Alexander K. Hartmann

We numerically investigate the dynamics of an SIR model with infection level-based lockdowns on Small-World networks. Using a large-deviation approach, namely the Wang-Landau algorithm, we study the distribution of the cumulative fraction of infected individuals. We are able to resolve the density of states for values as low as $10^{-85}$. Hence, we measure

Aleksander Grochowicz, Koen van Greevenbroek, Hannah C. Bloomfield

In highly renewable power systems the increased weather dependence can result in new resilience challenges, such as renewable energy droughts, or a lack of sufficient renewable generation at times of high demand. The weather conditions responsible for these challenges have been well-studied in the literature. However, in reality multi-day resilience challeng

Liye Guo, Cynthia Kop

Logically constrained term rewriting systems (LCTRSs) are a program analyzing formalism with native support for data types which are not (co)inductively defined. As a first-order formalism, LCTRSs have accommodated only analysis of imperative programs so far. In this paper, we present a higher-order variant of the LCTRS formalism, which can be used to analyz

H. T. Cui, Y. A. Yan, M. Qin, X. X. Yi

The study of phase transitions in dissipative quantum systems based on the Liouvillian is often hindered by the difficulty of constructing a time-local master equation when the system-environment coupling is strong. To address this issue, the complex discretization approximation for the environment is proposed to study the quantum phase transition in the ext

Fernando Gonzalez, François-Xavier Demoulin, Simon Bernard

This paper explores Neural Operators to predict turbulent flows, focusing on the Fourier Neural Operator (FNO) model. It aims to develop reduced-order/surrogate models for turbulent flow simulations using Machine Learning. Different model configurations are analyzed, with U-NET structures (UNO and U-FNET) performing better than the standard FNO in accuracy a

Rehema Iddi Mrutu, Kabir Mustapha Umar, Adnan Abdulhamid, Morris Agaba

The most recent and promising strategies for mitigating methane emissions in ruminants are reviewed highlighting the potential of reductive acetogenesis as a viable alternative to methanogenesis. The emergence of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology, and its exceptional precision in genome editing, further enhances th

Vinith Kishore, Valentin Debarnot, Ivan Dokmanić

Cryo-electron tomography (cryoET) is a technique that captures images of biological samples at different tilts, preserving their native state as much as possible. Along with the partial tilt series and noise, one of the major challenges in estimating the accurate 3D structure of the sample is the deformations in the images incurred during the acquisition. We

Adriano Peixoto

In this work, we prove the existence of a positive solution to the second-order nonlinear problem $u''+f(t,u,u')=0$ with mixed boundary conditions, where $f$ is an $L^p$-Carath\'eodory function satisfying certain properties. Three boundary conditions are analyzed. The proofs of the results are based on the Mawhin's. coincidence degree.

Sandro Mereghetti, Michela Rigoselli, Ruben Salvaterra, Andrea Tiengo

230307A is the second brightest gamma ray burst detected in more than 50 years of observations and is located in the direction of the Magellanic Bridge. Despite its long duration, it is most likely the result of the compact merger of a binary ejected from a galaxy in the local universe (redshift z=0.065). Our XMM-Newton observation of its afterglow at 4.5 da

Ben Schilling, Timothy G. McGee, Ryan Mitch, Ryan Watson

Dragonfly is scheduled to begin exploring Titan by 2034 using a series of multi-kilometer surface flights. This paper outlines the preliminary design of the navigation filter for the Dragonfly Mobility subsystem. The software architecture and filter formulation for lidar, visual odometry, pressure sensors, and redundant IMUs are described in detail. Special

William Balderrama, Kyle Ormsby, J. D. Quigley

We identify the motivic $KGL/2$-local sphere as the fiber of $\psi^3-1$ on $(2,\eta)$-completed Hermitian $K$-theory, over any base scheme containing $1/2$. This is a motivic analogue of the classical resolution of the $K(1)$-local sphere, and extends to a description of the $KGL/2$-localization of an arbitrary motivic spectrum. Our proof relies on a novel c

Sangyun Lee, Hyukjoon Kwon, Jae Sung Lee

Entropy plays a crucial role in both physics and information science, encompassing classical and quantum domains. In this work, we present the Quantum Neural Entropy Estimator (QNEE), a novel approach that combines classical neural network (NN) with variational quantum circuits to estimate the von Neumann and Renyi entropies of a quantum state. QNEE provides

Yiming Wu, Ruixiang Li, Zequn Qin, Xinhai Zhao

Vision-based Bird's Eye View (BEV) representation is an emerging perception formulation for autonomous driving. The core challenge is to construct BEV space with multi-camera features, which is a one-to-many ill-posed problem. Diving into all previous BEV representation generation methods, we found that most of them fall into two types: modeling depths in im

Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Mark Harman

Existing research mostly improves the fairness of Machine Learning (ML) software regarding a single protected attribute at a time, but this is unrealistic given that many users have multiple protected attributes. This paper conducts an extensive study of fairness improvement regarding multiple protected attributes, covering 11 state-of-the-art fairness impro

Jeremy Oguamalam, Una Radojičić, Peter Filzmoser

In this paper, we propose the Minimum Regularized Covariance Trace (MRCT) estimator, a novel method for robust covariance estimation and functional outlier detection. The MRCT estimator employs a subset-based approach that prioritizes subsets exhibiting greater centrality based on the generalization of the Mahalanobis distance, resulting in a fast-MCD type a

Yeonji Seo, Okyu Kwon, Hang-Hyun Jo

A transmission interval for an infectious disease is important to understand epidemic processes in complex networks. The transmission interval is defined as a time interval between one person's infection and their infection to another person. To study statistical properties of transmission intervals, we analyze a COVID-19 dataset of confirmed cases in Republ

Samir Assuena

In this paper, we shall give an explicit proof that constacyclic codes over finite commutative rings can be realized as ideals in some twisted group rings. Also, we shall study isometries between those codes and, finally, we shall study k-Galois LCD constacyclic codes over finite fields. In particular, we shall characterize constacyclic LCD codes with respec

Carlos M. Duque, Carl D. Modes

Epithelial morphogenesis, a signature problem of tissue biology and tissue mechanics, continues to inspire biologists and physicists alike. Many treatments focus on tissue fluidization, apical/basal ratio changes, or mechanical instabilities. In contrast to these approaches, shape-programmable materials, where the local lengths in the material change in a pr

Yahia Idriss Benalioua, Nathan Lhote, Pierre-Alain Reynier

Weighted automata (WA) are an extension of finite automata that define functions from words to values in a given semiring. An alternative deterministic model, called Cost Register Automata (CRA), was introduced by Alur et al. It enriches deterministic finite automata with a finite number of registers, which store values, updated at each transition using the

Tobias Kehrer, Tobias Nadolny, Christoph Bruder

The Hilbert space of a physical qubit typically features more than two energy levels. Using states outside the qubit subspace can provide advantages in quantum computation. To benefit from these advantages, individual states of the $d$-dimensional qudit Hilbert space have to be discriminated during readout. We propose and analyze two measurement strategies t

Taylor W. Killian, Haoran Zhang, Thomas Hartvigsen, Ava P. Amini

Prevalent in many real-world settings such as healthcare, irregular time series are challenging to formulate predictions from. It is difficult to infer the value of a feature at any given time when observations are sporadic, as it could take on a range of values depending on when it was last observed. To characterize this uncertainty we present EDICT, a stra

Fred Torres Cruz, Evelyn Eliana Coaquira Flores, Sebastian Jarom Condori Quispe

This study presents a machine learning model based on the Naive Bayes classifier for predicting the level of depression in university students, the objective was to improve prediction accuracy using a machine learning model involving 70% training data and 30% validation data based on the Naive Bayes classifier, the collected data includes factors associated

Matthew Collins

It is well known for an irreducible free group automorphism that its growth rate is equal to the minimal Lipschitz displacement of its action on Culler-Vogtmann space. This follows as a consequence of the existence of train track representatives for the automorphism. We extend this result to the general - possibly reducible - case as well as to the free prod

Tessa Bauman, Bruno Gašperov, Stjepan Begušić, Zvonko Kostanjčar

Goal-based investing is an approach to wealth management that prioritizes achieving specific financial goals. It is naturally formulated as a sequential decision-making problem as it requires choosing the appropriate investment until a goal is achieved. Consequently, reinforcement learning, a machine learning technique appropriate for sequential decision-mak

Tinne Pauwels, Maddalena Reggiani, Hugues Sana, Alan Rainot

One of the most remarkable properties of massive stars is that almost all of them are found in binaries or higher-order multiple systems. Observations that cover the full companion mass ratio and separation regime are essential to constrain massive star and binary formation theories. We used VLT/SPHERE to characterise the multiplicity properties of 20 OB sta

Fredrik Johannessen, Martin Jullum

Current anti-money laundering (AML) systems, predominantly rule-based, exhibit notable shortcomings in efficiently and precisely detecting instances of money laundering. As a result, there has been a recent surge toward exploring alternative approaches, particularly those utilizing machine learning. Since criminals often collaborate in their money laundering

Lior Alon, Cynthia Vinzant

Recent work of Kurasov and Sarnak provides a method for constructing one-dimensional Fourier quasicrystals (FQ) from the torus zero sets of a special class of multivariate polynomials called Lee-Yang polynomials. In particular, they provided a non-periodic FQ with unit coefficients and uniformly discrete support, answering an open question posed by Meyer. Th

G. E. Volovik

In the paper "Life, the Universe, and everything--42 fundamental questions", Roland Allen and Suzy Lidstr\"om presented personal selection of the fundamental questions. Here, based on the condensed matter experience, we suggest the answers to some questions concerning the vacuum energy, black hole entropy and the origin of gravity. In condensed matter we kno

Gabriele Picco, Marcos Martínez Galindo, Alberto Purpura, Leopold Fuchs

The Zero-Shot Learning (ZSL) task pertains to the identification of entities or relations in texts that were not seen during training. ZSL has emerged as a critical research area due to the scarcity of labeled data in specific domains, and its applications have grown significantly in recent years. With the advent of large pretrained language models, several

Alexander Bernal, Paweł Caban, Jakub Rembieliński

We discuss entanglement and violation of Bell-type inequalities for a system of two $Z$ bosons produced in Higgs decays. We take into account beyond the Standard Model (anomalous) coupling between $H$ and daughter bosons but we limit ourselves to an overall scalar $ZZ$ state (we exclude the possibility that $H$ contains a pseudo-scalar component). In particu

Lassaad Aloui, Sirine Jbari, Slim Tayachi

We are interested in the behavior of solutions to the damped inhomogeneous nonlinear Schr\"odinger equation $ i\partial_tu+\Delta u+\mu|x|^{-b}|u|^{\alpha}u+iau=0$, $\mu \in\mathbb{C} $, $b>0$, $a \in \mathbb{C}$ such that $\Re \textit{e}(a) \geq 0$, $\alpha>0$. We establish lower and upper bound estimates of the life-span. In particular for $a\geq 0$, we ob

Kaixin Zhang, Hongzhi Wang, Yabin Lu, Ziqi Li

Learned cardinality estimation methods have achieved high precision compared to traditional methods. Among learned methods, query-driven approaches have faced the workload drift problem for a long time. Although both data-driven and hybrid methods are proposed to avoid this problem, most of them suffer from high training and estimation costs, limited scalabi

Duong Van Loi, Phung Van Dong

There is no reason why the gauge symmetry extension is family universal as in the standard model and the most well-motivated models, e.g. left-right symmetry and grand unification. Hence, we propose a simplest extension of the standard model -- a flavor-dependent $U(1)$ gauge symmetry -- and find the new physics insight. For this aim, the $U(1)$ charge, call

Lei Qi, Hongpeng Yang, Yinghuan Shi, Xin Geng

Deep learning has made significant advancements in supervised learning. However, models trained in this setting often face challenges due to domain shift between training and test sets, resulting in a significant drop in performance during testing. To address this issue, several domain generalization methods have been developed to learn robust and domain-inv

R. Bandiera, N. Bucciantini, B. Olmi, D. F. Torres

The vast majority of Pulsar Wind Nebulae (PWNe) present in the Galaxy is formed by middle-aged systems characterized by a strong interaction of the PWN itself with the supernova remnant (SNR). Unfortunately, modelling these systems can be quite complex and numerically expensive, due to the non-linearity of the PWN-SNR evolution even in the simple 1D / one-zo

Matthew Brahlek, Alessandro R. Mazza, Abdulgani Annaberdiyev, Michael Chilcote

The current challenge to realizing continuously tunable magnetism lies in our inability to systematically change properties such as valence, spin, and orbital degrees of freedom as well as crystallographic geometry. Here, we demonstrate that ferromagnetism can be externally turned on with the application of low-energy helium implantation and subsequently era

Manuel Del Piano, Stefan Hohenegger, Francesco Sannino

Quantum gravity theories predict deformations of black hole solutions relative to their classical counterparts. A model-independent approach was advocated in \cite{Binetti:2022xdi} that uses metric deformations parametrised in terms of physical quantities, such as the proper distance. While such a description manifestly preserves the invariance of the space-

Zoheir Ziani, Thomas Bunel, Auro M. Perego, Arnaud Mussot

We analyse the nonlinear dynamics of Fabry-Perot cavities of arbitrary finesse filled by a dispersive Kerr medium, pumped by a continuous wave laser or a synchronous train of flat-top pulses. The combined action of feedback, group velocity dispersion and Kerr nonlinearity leads to temporal instability with respect to perturbations at specified frequencies. W

K. Sugimoto, Y. He, N. Iwata, I-L. Yeh

We discovered a simple regime where a near-critical plasma irradiated by a laser of experimentally available intensity can self-organize to produce positrons and accelerate them to ultra-relativistic energies. The laser pulse piles up electrons at its leading edge, producing a strong longitudinal plasma electric field. The field creates a moving gamma-ray co

Hannah Friedman, Bernd Sturmfels, Maksym Zubkov

We study determinantal point processes (DPP) through the lens of algebraic statistics. We count the critical points of the log-likelihood function, and we compute them for small models, thereby disproving a conjecture of Brunel, Moitra, Rigollet and Urschel.

Youssef Elmir, Yassine Himeur, Abbes Amira

This paper study provides a novel contribution to the field of signal processing and DL for ECG signal analysis by introducing a new feature representation method for ECG signals. The proposed method is based on transforming time frequency 1D vectors into 2D images using Gramian Angular Field transform. Moving on, the classification of the transformed ECG si

Gratianus Wesley Putra Data, Henry Howard-Jenkins, David Murray, Victor Prisacariu

We propose Cos R-CNN, a simple exemplar-based R-CNN formulation that is designed for online few-shot object detection. That is, it is able to localise and classify novel object categories in images with few examples without fine-tuning. Cos R-CNN frames detection as a learning-to-compare task: unseen classes are represented as exemplar images, and objects ar

Martina Ćosićová, Jan Dvořák, Martin Čížek

We present a general two-dimensional model of conical intersection between metastable states that are vibronically coupled not only directly but also indirectly through a virtual electron in the autodetachment continuum. This model is used as a test ground for design and comparison of iterative solvers for resonance dynamics in low-energy electron-molecule c

Y. X. Jane Yap, Albert Kong, Kwan Lok Li

We report optical observations of the millisecond pulsar binary system PSR J1622-0315 with the Lulin 1m telescope in Taiwan and the Lijiang 2.4m telescope in China between 2019 and 2021. The companion of the pulsar, which is of V~19 mag, showed ellipsoidal-distorted orbital variations in its light curves. The best-fit model to the light curves, with the bina

Nicki Holighaus, Günther Koliander

We provide an example for the generating matrix $A$ of a two-dimensional lattice $\Gamma = A\mathbb{Z}^2$, such that the following holds: For any sufficiently smooth and localized mother wavelet $\psi$, there is a constant $\beta(A,\psi)>0$, such that $\beta\Gamma\cap (\mathbb{R}\times\mathbb{R}^+)$ is a set of stable sampling for the wavelet system generate

Kiara Hansenne, Otfried Gühne

Quantum networks offer a realistic and practical scheme for generating multiparticle entanglement and implementing multiparticle quantum communication protocols. However, the correlations that can be generated in networks with quantum sources and local operations are not yet well understood. Covariance matrices, which are powerful tools in entanglement theor

Naoki Endo, Naoyuki Matsuoka

This paper investigates the relation between the almost Gorenstein properties for graded rings and for local rings. Once $R$ is an almost Gorenstein graded ring, the localization $R_M$ of $R$ at the graded maximal ideal $M$ is almost Gorenstein as a local ring. The converse does not hold true in general. However, it does for one-dimensional graded domains wi

Gil M. Marques, Sílvio Gama, Fernando L. Pereira

In a system of point vortices, there exist regions of stability around each vortex, even if the system is chaotic. These regions are usually called stability islands and they have a morphology that is hard to characterise. We study and characterise them in two point vortex systems in the infinite two-dimensional plane -- the simplest scenario -- by studying

Zhu Cao

Indefinite causal order has found numerous applications in quantum computation, quantum communication, and quantum metrology. Before its usage, the quality of the indefinite causal order needs to be first certified, and the certification should ideally be device-independent (DI) to avoid the impact of device imperfections. In this work, we initiate the study

Maude Charmetant, Jens Erler

The Fred Young Submillimeter Telescope (FYST) and the Simons Observatory Large Aperture Telescope (SO\ LAT) will deliver unprecedented high-resolution measurements of microwave sky emissions. Notably, one of those microwave sky emissions, the thermal Sunyaev-Zeldovich (tSZ) signal, is an essential probe for cluster astrophysics and cosmology. However, an obs

Hua Sun

Secure aggregation usually aims at securely computing the sum of the inputs from $K$ users at a server. Noticing that the sum might inevitably reveal information about the inputs (when the inputs are non-uniform) and typically the users (not the server) desire the sum (in applications such as federated learning), we consider a variant of secure aggregation w

A. Aligayev, F. J. Dominguez-Gutierrez, M. Chourashiya, S. Papanikolaou

In this study, we employ a computational chemistry-based modeling approach to investigate the adsorption mechanisms of CH$_4$ and CO$_2$ on monolayer GPNL, with a specific focus on their effects on optical adsorption and electrical transport properties at room temperature. To simulate the adsorption dynamics as closely as possible to experimental conditions,

John Bulava, Bárbara Cid-Mora, Andrew D. Hanlon, Ben Hörz

A lattice QCD computation of the coupled channel $\pi\Sigma-\bar{K}N$ scattering amplitudes in the $\Lambda(1405)$ region is detailed. Results are obtained using a single ensemble of gauge field configurations with $N_{\rm f} = 2+1$ dynamical quark flavors and $m_{\pi} \approx 200$ MeV and $m_K\approx487$ MeV. Hermitian correlation matrices using both single

Awadelrahman M. A. Ahmed, Frank Eliassen, Yan Zhang

This paper proposes a new combinatorial auction framework for local energy flexibility markets, which addresses the issue of prosumers' inability to bundle multiple flexibility time intervals. To solve the underlying NP-complete winner determination problems, we present a simple yet powerful heterogeneous tri-partite graph representation and design graph neu

D. H. Jakubassa-Amundsen, X. Roca-Maza

Dispersion corrections to elastic electron scattering from $^{208}$Pb at energies up to 150 MeV are estimated within the second-order Born approximation. All strong transient nuclear excited states with angular momentum up to $L=3$ and natural parity are taken into consideration. It is found that at small scattering angles the high-lying $L=1$ isovector stat

Zhao-Yang Liu, Liucheng Sun, Chenwei Weng, Qijin Chen

Bundle recommendation aims to provide a bundle of items to satisfy the user preference on e-commerce platform. Existing successful solutions are based on the contrastive graph learning paradigm where graph neural networks (GNNs) are employed to learn representations from user-level and bundle-level graph views with a contrastive learning module to enhance th

Antonio Alberto D'Amico, Luca Sanguinetti

Holographic MIMO refers to a (possibly large) array with a large number of individually controlled and densely deployed antennas. The objective of this paper is to provide further insight into the use of closely spaced antennas in the uplink and downlink of a multi-user Holographic MIMO system. To this end, we utilize multiport communication theory, which en

Michiel G. J. Kallenberg, Bernardo Maestrini, Ron van Bree, Paul Ravensbergen

Crop yield prediction typically involves the utilization of either theory-driven process-based crop growth models, which have proven to be difficult to calibrate for local conditions, or data-driven machine learning methods, which are known to require large datasets. In this work we investigate potato yield prediction using a hybrid meta-modeling approach. A

Amir Suhail, Anuradha Banerjee, R. Rajesh

The hysteretic behavior exhibited by collagen fibrils, when subjected to cyclic loading, is known to result in both dissipation as well as accumulation of residual strain. On subsequent relaxation, partial recovery has also been reported. Cross-links have been considered to play a key role in overall mechanical properties. Here, we modify an existing coarse

Rocco D'Agostino, Rafael C. Nunes

Measurements of the $H_0$ and $\sigma_8$ parameters within the standard cosmological model recently highlighted significant statistical tensions between the cosmic microwave background and low-redshift probes, such as local distance ladder, weak lensing and galaxy clustering surveys. In this work, we frame geometrical distances in a model-independent way by

James Z. Wang, Sicheng Zhao, Chenyan Wu, Reginald B. Adams

The emergence of artificial emotional intelligence technology is revolutionizing the fields of computers and robotics, allowing for a new level of communication and understanding of human behavior that was once thought impossible. While recent advancements in deep learning have transformed the field of computer vision, automated understanding of evoked or ex

Francisco J. T. Salazar, Antonio F. B. A. Prado

This study focuses on attitude and control motion of two bodies (a base-satellite and a sub-satellite) connected by an inextensible and massless tether in a circular orbit under the influence of the Earths gravitational force. The base-satellite is assumed to be far more heavier than the sub-satellite. In such cases, the base-satellite is regarded as the ref

Yang A. Li, Luis C. Ho, Jinyi Shangguan

Interactions and mergers play an important role in regulating the physical properties of galaxies, such as their morphology, gas content, and star formation rate (SFR). Controversy exists as to the degree to which these events, even gas-rich major mergers, enhance star formation activity. We study merger pairs selected from a sample of massive ($M_* \ge 10^{

Yang A. Li, Luis C. Ho, Jinyi Shangguan, Ming-Yang Zhuang

The broadband spectral energy distribution of a galaxy encodes valuable information on its stellar mass, star formation rate (SFR), dust content, and possible fractional energy contribution from nonstellar sources. We present a comprehensive catalog of panchromatic photometry, covering 17 bands from the far-ultraviolet to 500 $\mu$m, for 2685 low-redshift (z

Yunfei Wang, Yuri Alexeev, Liang Jiang, Frederic T. Chong

Quantum devices should operate in adherence to quantum physics principles. Quantum random access memory (QRAM), a fundamental component of many essential quantum algorithms for tasks such as linear algebra, data search, and machine learning, is often proposed to offer $\mathcal{O}(\log N)$ circuit depth for $\mathcal{O}(N)$ data size, given $N$ qubits. Howev

Jinnan Chen, Chen Li, Gim Hee Lee

The main challenges of 3D pose transfer are: 1) Lack of paired training data with different characters performing the same pose; 2) Disentangling pose and shape information from the target mesh; 3) Difficulty in applying to meshes with different topologies. We thus propose a novel weakly-supervised keypoint-based framework to overcome these difficulties. Spe

S. V. Mikhailov, N. Volchanskiy

We calculate the two-point massless QCD correlator of nonlocal (composite) vector quark currents with chains of fermion one-loop radiative corrections inserted into gluon lines. The correlator depends on the Bjorken fraction $x$ related to the composite current and, under large-$\beta_0$ approximation, gives the main contributions in each order of perturbati

Pablo Calvo-Barlés, Sergio G. Rodrigo, Eduardo Sánchez-Burillo, Luis Martín-Moreno

We introduce a machine-learning approach (denoted Symmetry Seeker Neural Network) capable of automatically discovering discrete symmetry groups in physical systems. This method identifies the finite set of parameter transformations that preserve the system's physical properties. Remarkably, the method accomplishes this without prior knowledge of the system's

Wojciech Górny

We use the framework of the first-order differential structure in metric measure spaces introduced by Gigli to define a notion of weak solutions to gradient flows of convex, lower semicontinuous and coercive functionals. We prove their existence and uniqueness and show that they are also variational solutions; in particular, this is an existence result for v

Tiziano Schiavone, Enea Di Dio, Giuseppe Fanizza

Starting from a recently proposed framework for the evaluation of the cosmological averages, we evaluate the higher-order moments for the distribution of a given observable. Then, we explicitly discuss the case of the Hubble-Lema\^itre diagram and evaluate its skewness at the leading order in the cosmological perturbative expansion of the gravitational poten

Mahdis Ghodrati

In the background of several holographic confining backgrounds, we present the connections between the behaviors of string scattering amplitudes and mutual information. We lay down the analogies between the logarithmic branch cut behavior of the string scattering amplitude in $4d$, $ \mathcal{A}_4 $, at low and medium Mandelstam variable $s$ observed in \cit

Yelisey Pitanov, Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev

In this work we study a well-known and challenging problem of Multi-agent Pathfinding, when a set of agents is confined to a graph, each agent is assigned a unique start and goal vertices and the task is to find a set of collision-free paths (one for each agent) such that each agent reaches its respective goal. We investigate how to utilize Monte-Carlo Tree

Elena M. Golubeva, Akash Biswas, Anna I. Khlystova, Pawan Kumar

The polar field reversal is a crucial process in the cyclic evolution of the large-scale magnetic field of the Sun.Various important characteristics of a solar cycle, such as its duration and strength, and also the cycle predictability, are determined by the polar field reversal time. While the regular measurements of solar magnetic field have been accumulat

Federico Lanza, Santanu Sinha, Alex Hansen, Alberto Rosso

We investigate the behavior of drainage displacements in heterogeneous porous media finding a transition from viscous fingering to foam-like region. A pore network model incorporating the formation of blobs is adopted to study this phenomenon. By imposing a pressure difference between the inlet and outlet, we observe that the displacement pattern undergoes a

Aranya Bhattacharya, Himanshu Sahu, Ahmadullah Zahed, Kallol Sen

We compute the complexity for the mixed state density operator derived from a one-dimensional discrete-time quantum walk (DTQW). The complexity is computed using a two-qubit quantum circuit obtained from canonically purifying the mixed state. We demonstrate that the Nielson complexity for the unitary evolution oscillates around a mean circuit depth of $k$. F

S. D. Campos

This work examines some aspects related to the existence of negative mass. The requirement for the partition function to converge leads to two distinct approaches. Initially, convergence is achieved by assuming a negative absolute temperature, which results in an imaginary partition function and complex entropy. Subsequently, convergence is maintained by kee

Sukŗti Bansal

We present polynomial and manifestly covariant M5-brane Lagrangians along with their analyses involving their dynamics, gauge symmetries and their nonlinear selfduality condition. Such Lagrangians can be particularly useful for developments that are otherwise hindered by a non-polynomial structure and singularity of the Lagrangian such as its quantisation. A

Shruti Chakravarty, Sunil Nair

We report the nonlinear dielectric properties of three triple-perovskite ruthenates: Ba$_3$CoRu$_2$O$_9$, Ba$_3$BiRu$_2$O$_9$, and Sr$_3$CaRu$_2$O$_9$. These compounds exhibit notable correlations among their spin, charge, lattice, and polar degrees of freedom. Ba$_3$CoRu$_2$O$_9$ displays a pronounced frequency-dependent relaxation in $\chi_{2,3}$ just abov

Ruaridh Mon-Williams, Theodoros Stouraitis, Sethu Vijayakumar

A key challenge in human-robot collaboration is the non-stationarity created by humans due to changes in their behaviour. This alters environmental transitions and hinders human-robot collaboration. We propose a principled meta-learning framework to explore how robots could better predict human behaviour, and thereby deal with issues of non-stationarity. On

Quentin Marécat, Matthieu Saubanère

The performance of embedding methods is directly tied to the quality of the bath orbitals construction. In this paper, we develop a versatile framework, enabling the investigation of the optimal construction of the orbitals of the bath. As of today, in state-of-the-art embedding methods, the orbitals of the bath are constructed by performing a Singular Value

Dušan Dragutinović

We extend Moonen's definition of Ekedahl-Oort types of smooth curves in terms of Hasse-Witt triples to all stable curves and show that it matches Ekedahl and van der Geer's definition of Ekedahl-Oort types of their generalized Jacobians as semi-abelian varieties. Using this intrinsic insight, we can compute the dimensions of certain Ekedahl-Oort loci of curv

Apostolos Panagiotopoulos, Temur Maksudov, George Kakavelakis, George Perrakis

Ultrathin, solution-processed emerging solar cells with high power-per-weight (PPW) outputs demonstrate unique potential for applications where low weight, high power output, and flexibility are indispensable. The following perspective explores the literature of emerging PVs and highlights the maximum reported PPW values of Perovskite Solar Cells (PSCs) 29.4

Sourav Bhattacharya, Nitin Joshi

The decoherence mechanism is believed to be possibly connected to the quantum to classical transition of the primordial cosmological perturbations in the early universe. In this paper, we extend our previous analysis on decoherence in a fermion and scalar quantum field theory coupled via the Yukawa interaction in the Minkowski spacetime, to the inflationary

Jingpeng Wu

In this article, we investigate the gyrokinetic limit for the two dimensional Vlasov-Poisson system with multi-point charges. We show that the solution converges to a measure-valued solution of the Euler equation with a defect measure, which extends the results of Miot (Nonlinearity 32(2):654-677, 2019) to the case of multi-point charges and removes the smal

Aryan Taneja, Debopam Bhattacherjee, Saikat Guha, Venkata N. Padmanabhan

Multiple low-Earth orbit satellite constellations, aimed at beaming broadband connectivity from space, are currently under active deployment. While such space-based Internet is set to augment, globally, today's terrestrial connectivity, and has managed to generate significant hype, it has been largely difficult for the community to measure, quantify, or unde

Xi-Jing Wang, Guoyang Fu, Peng Liu, Xiao-Mei Kuang

We construct novel scalarized black hole (BH) solutions beyond the general relativity (GR) framework. These scalarized BH solutions are extended from the Schwarzschild one and the non-Schwarzschild one in the pure Einstein-Weyl gravity. By studying the BH entropy and free energy, we demonstrate that the scalarized BH extending from the Schwarzschild one exhi

Ayyadurai Sankaranarayanan, Lalit Vaishya

Let $f \in S_{k}(SL_2(\mathbb{Z}))$ be a normalized Hecke eigenforms of integral weight $k$ for the full modular group. In the article, we study the average behaviour of Fourier coefficients of $\ell$-fold product $L$-function. More precisely, we establish the asymptotics of power moments associated to the sequence $\{\lambda_{f \otimes f \otimes \cdots \oti

Svend-Age Biehs, Achim Kittel, Zhenghua An

We analytically calculate the contribution to the local density of states due to thermal sources in a disk-like patch within the framework of fluctuational electrodynamics. We further introduce a wavevector cutoff method to approximate this contribution. We compare the results obtained with the source and cutoff method with the numerical exact LDOS above a m