April 2023 arXiv papers — page 131

Maximilian Stubbemann, Tobias Hille, Tom Hanika

Real-world datasets are often of high dimension and effected by the curse of dimensionality. This hinders their comprehensibility and interpretability. To reduce the complexity feature selection aims to identify features that are crucial to learn from said data. While measures of relevance and pairwise similarities are commonly used, the curse of dimensional

J. Peterson, P. Costa, R. Kumar, V. Dexheimer

We study consistently the effects of magnetic field on hot and dense matter. In particular, we look for differences that arise due to assumptions that reproduce the conditions produced in particle collisions or astrophysical scenarios, such as in the core of fully evolved neutron stars (beyond the protoneutron star stage). We assume the magnetic field to be

Ganga Meghanath, Bryan Jimenez, Joseph G. Makin

The proliferation of multi-unit cortical recordings over the last two decades, especially in macaques and during motor-control tasks, has generated interest in neural "population dynamics": the time evolution of neural activity across a group of neurons working together. A good model of these dynamics should be able to infer the activity of unobserved neuron

George Cooper

We prove the existence of quasi-projective coarse moduli spaces parametrising certain complete flags of subschemes of a fixed projective space $\mathbb{P}(V)$ up to projective automorphisms. The flags of subschemes being parametrised are obtained by intersecting non-degenerate subvarieties of $\mathbb{P}(V)$ of dimension $n$ by flags of linear subspaces of $

Y. I. Izotov, D. Schaerer, G. Worseck, D. Berg

We present observations with the Space Telescope Imaging Spectrograph (STIS) onboard the Hubble Space Telescope of eleven Lyman continuum (LyC) leaking galaxies at redshifts, z, in the range 0.29-0.43, with oxygen abundances 12+log(O/H)=7.64-8.16, stellar masses Mstar~10^7.8-10^9.8 Msun and O32=[OIII]5007/[OII]3727 of ~5-20, aiming to detect CIII]1908 emissi

Yuhan Zhang, He Zhu, Shan Yu

In computer vision, contrastive learning is the most advanced unsupervised learning framework. Yet most previous methods simply apply fixed composition of data augmentations to improve data efficiency, which ignores the changes in their optimal settings over training. Thus, the pre-determined parameters of augmentation operations cannot always fit well with

Rupali Chandar, Miranda Caputo, Angus Mok, Sean Linden

Nearly all current simulations predict that outcomes of the star formation process, such as the fraction of stars that form in bound clusters (Gamma), depend on the intensity of star formation activity (SigmaSFR) in the host galaxy. The exact shape and strength of the predicted correlations, however, vary from simulation to simulation. Observational results

Johannes Lankeit, Michael Winkler

We give an overview of analytical results concerned with chemotaxis systems where the signal is absorbed. We recall results on existence and properties of solutions for the prototypical chemotaxis-consumption model and various variants and review more recent findings on its ability to support the emergence of spatial structures.

G. A. P. Ribeiro, Gustavo Rigolin

We show that the quantum teleportation protocol is a powerful tool to study quantum phase transitions (QPTs) at finite temperatures. We consider a pair of spins from an infinite spin-1/2 chain (XXZ model) in equilibrium with a reservoir at temperature T as the resource used by Alice and Bob to implement the teleportation protocol. We show that the efficiency

Chengjie Zhang, Sophia Denker, Ali Asadian, Otfried Gühne

Characterizing entanglement is central for quantum information science. Special observables which indicate entanglement, so-called entanglement witnesses, are a widely used tool for this task. The construction of these witnesses typically relies on the observation that quantum states with a high fidelity to some entangled target state are entangled, too. We

Dominik Trnka

We present a Markl-style definition of operads colored by a small category. In the presence of a unit these are equivalent to substitudes of Day and Street. We show that operads colored by a category are internal algebras of a certain categorical operad of functors. We describe a groupoid-colored quadratic binary operad, whose algebras are non-unital Markl o

L. Besombes, S. Ando, S. Kuroda, H. Boukari

Two electrons in a quantum dot (QD) can form triplet states. We analyze the exchange coupling of the triplet states of the negatively charged exciton in a QD (X$^-$, two electrons and one hole) with the spin of a magnetic atom (Mn). Two techniques are used to access the spin structure of this magnetic complex: the resonant excitation of the excited states of

Péter Antal, Tamás Péni, Roland Tóth

Payload grasping and transportation with quadcopters is an active research area that has rapidly developed over the last decade. To grasp a payload without human interaction, most state-of-the-art approaches apply robotic arms that are attached to the quadcopter body. However, due to the large weight and power consumption of these aerial manipulators, their

Juan Munoz, Subash Balsamy, Juan P. Bernal-Tamayo, Ali Balubaid

Discovering non-linear dynamical models from data is at the core of science. Recent progress hinges upon sparse regression of observables using extensive libraries of candidate functions. However, it remains challenging to model hidden non-observable control variables governing switching between different dynamical regimes. Here we develop a data-efficient d

Nikita Kornilov, Alexander Gasnikov, Pavel Dvurechensky, Darina Dvinskikh

We present two easy-to-implement gradient-free/zeroth-order methods to optimize a stochastic non-smooth function accessible only via a black-box. The methods are built upon efficient first-order methods in the heavy-tailed case, i.e., when the gradient noise has infinite variance but bounded $(1+\kappa)$-th moment for some $\kappa \in(0,1]$. The first algori

Yangyang Xu

Minimax problems have recently attracted a lot of research interests. A few efforts have been made to solve decentralized nonconvex strongly-concave (NCSC) minimax-structured optimization; however, all of them focus on smooth problems with at most a constraint on the maximization variable. In this paper, we make the first attempt on solving composite NCSC mi

N. A. Cruz, O. O. Melo, C. A. Martinez, R. Alberich

Crossover designs are widely applied in medicine, agriculture, and other biological sciences, yet their analysis remains challenging due to longitudinal observations within each unit and the presence of carry-over effects. Despite their prevalence, there is no comprehensive R package dedicated to the statistical modeling of crossover data. The CrossCarry pac

S. R. Mohanty, Sayantan Ghosh, Bharat Kumar

Neutron stars (NSs) are incredibly versatile for studying various important aspects of high-energy and compact-object physics. These celestial objects contain extreme matter at incredibly high densities in their interiors, leading to the risk of instabilities that may cause them to collapse into a black hole (BH). This paper focuses on exploring the stabilit

Nicolo Valdi Biesuz, Rimsky Caballero, Davide Cieri, Nico Giangiacomi

Hog (HDL on Git) is an open-source tool designed to manage Git-based HDL repositories. It aims to simplify HDL project development, maintenance, and versioning by using Git to guarantee synthesis and implementation reproducibility and binary file traceability. This is ensured by linking each produced binary file to a specific Git commit, embedding the Git co

Geva Arwas, Vladimir E. Manucharyan, Cristiano Ciuti

Multi-mode cavity quantum electrodynamics (QED) describes, for example, the coupling between an atom and a multi-mode electromagnetic resonator. The gauge choice is important for practical calculations in truncated Hilbert spaces, because the exact gauge-invariance is recovered only in the whole space. An optimal gauge can be defined as the one predicting th

Giacomo Aletti, Irene Crimaldi, Andrea Ghiglietti

In this work, we introduce an extremely general model for a collection of innovation processes in order to model and analyze the interaction among them. We provide theoretical results, analytically proven, and we show how the proposed model fits the behaviors observed in some real data sets (from Reddit and Gutenberg). It is worth mentioning that the given a

Qihang Zhao, Rui-jie Zhu, Liu Yang, He Yongming

In the realm of search systems, multi-stage cascade architecture is a prevalent method, typically consisting of sequential modules such as matching, pre-ranking, and ranking. It is generally acknowledged that the model used in the pre-ranking stage must strike a balance between efficacy and efficiency. Thus, the most commonly employed architecture is the rep

Jit Koley, Binoy Krishna Roy

This study presents a novel, continuous finite-time control strategy for a class of nonlinear systems subject to matched uncertainties with unknown bounds. We propose an Adaptive Disturbance Observer-based Full-order Integral-Terminal Sliding Mode Control (ADO-FOITSMC) to stabilize a chain of integrators in presence of exogenous disturbances whose time deriv

Jie Han, Lin Sun, Guanghui Wang

Let $Y_{3,2}$ be the 3-graph with two edges intersecting in two vertices. We prove that every 3-graph $ H $ on $ n $ vertices with at least $ \max \left \{ \binom{4\alpha n}{3}, \binom{n}{3}-\binom{n-\alpha n}{3} \right \}+o(n^3) $ edges contains a $Y_{3,2}$-tiling covering more than $ 4\alpha n$ vertices, for sufficiently large $ n $ and $0<\alpha< 1/4$. Th

Darren Tsai, Julie Stephany Berrio, Mao Shan, Eduardo Nebot

We introduce Multi-Source 3D (MS3D), a new self-training pipeline for unsupervised domain adaptation in 3D object detection. Despite the remarkable accuracy of 3D detectors, they often overfit to specific domain biases, leading to suboptimal performance in various sensor setups and environments. Existing methods typically focus on adapting a single detector

Samidh Pal

This paper investigates the inter-regional intra-industry disparity within selected Indian manufacturing industries and industrial states. The study uses three measures - the Output-Capital Ratio, the Capital-Labor Ratio, and the Output-Labor Ratio - to critically evaluate the level of disparity in average efficiency of labor and capital, as well as capital

Shangkun Weng, Zhouping Xin

We establish the existence and stability of cylindrical transonic shock solutions under three dimensional perturbations of the incoming flows and the exit pressure without any further restrictions on the background transonic shock solutions. The strength and position of the perturbed transonic shock are completely free and uniquely determined by the incoming

Disha Hou, Yuhai Liu, Toshihiro Sato, Fakher F. Assaad

We carry out large-scale quantum Monte Carlo simulations of a candidate field theory for the onset of superconductivity in magic-angle twisted bilayer graphene. The correlated insulating state at charge neutrality spontaneously breaks U(1) Moir\'e valley symmetry. Owing to the topological nature of the bands, skyrmion defects of the order parameter carry cha

Gaston Andres Garcia, Mitja Mastnak

This paper is a first step toward the full description of a family of Hopf algebras whose coradical is isomorphic to a semisimple Hopf algebra K_{n}, n an odd positive integer, obtained by a cocentral abelian cleft extension. We describe the simple Yetter-Drinfeld modules, compute the fusion rules and determine the finite-dimensional Nichols algebras for som

Wenxiang Jiao, Jen-tse Huang, Wenxuan Wang, Zhiwei He

Large language models (LLMs) like ChatGPT have exhibited remarkable abilities on a wide range of natural language processing~(NLP) tasks, including various machine translation abilities accomplished during chat. However, these models are only accessible through restricted APIs, which creates barriers to new research and advancements in the field. Therefore,

Rabia Sonmez, Robert A. Handler, Ryan Kelly, David B. Goldstein

It is shown that laminar vortex rings can be generated by impulsive body forces having particular spatial and temporal characteristics. The method produces vortex rings in a fluid initially at rest, and once generated, the flow field automatically satisfies the boundary conditions and is divergence-free. Numerical simulations and analytical models show that

Jiliang Zhang, Wei Liu, Alan Tennant, Weijie Qi

In this paper, a multipath component aggregation (MCA) mechanism is introduced for spatial scattering modulation (SSM) to overcome the limitation in conventional SSM that the transmit antenna array steers the beam to a single multipath (MP) component at each instance. In the proposed MCA-SSM system, information bits are divided into two streams. One is mappe

Simon Akar, Michael Peters, Henry Schreiner, Michael D Sokoloff

Using deep neural networks to identify and locate proton-proton collision points, or primary vertices, in LHCb has been studied for several years. Preliminary results demonstrated the ability for a hybrid deep learning algorithm to achieve similar or better physics performances compared to standard heuristic approaches. The previously studied architectures r

Osmi Vilhu, Karri Koljonen, Diana Hannikainen

In wind-fed X-ray binaries, the radiatively driven wind of the primary star can be suppressed by the EUV irradiation of the compact secondary star, leading to an increased accretion rate. This causes feedback between the released accretion power and the luminosity of the compact star. We investigate the feedback process between the released accretion power a

Yuqing Du, Lianqiang Qu, Ting Yan, Yuan Zhang

We extend the well-known $\beta$-model for directed graphs to dynamic network setting, where we observe snapshots of adjacency matrices at different time points. We propose a kernel-smoothed likelihood approach for estimating $2n$ time-varying parameters in a network with $n$ nodes, from $N$ snapshots. We establish consistency and asymptotic normality proper

Joseph Rowell

The Structure from Motion (SfM) challenge in computer vision is the process of recovering the 3D structure of a scene from a series of projective measurements that are calculated from a collection of 2D images, taken from different perspectives. SfM consists of three main steps; feature detection and matching, camera motion estimation, and recovery of 3D str

Kehong Gong, Dongze Lian, Heng Chang, Chuan Guo

We propose a novel task for generating 3D dance movements that simultaneously incorporate both text and music modalities. Unlike existing works that generate dance movements using a single modality such as music, our goal is to produce richer dance movements guided by the instructive information provided by the text. However, the lack of paired motion data w

Yifan Bai, Christoforos Kanellakis, George Nikolakopoulos

In this paper, we study the multi-robot task assignment and path-finding problem (MRTAPF), where a number of agents are required to visit all given goal locations while avoiding collisions with each other. We propose a novel two-layer algorithm SA-reCBS that cascades the simulated annealing algorithm and conflict-based search to solve this problem. Compared

Tamíris R. Calixto, Pablo L. Saldanha

In a recent work [Phys. Rev. A \textbf{102}, 053723 (2020)] we have shown that experiments that produce and characterize single-mode light squeezing can be explained in a way where no single-mode squeezed light state is produced in the setup. Here we apply the same ideas to demonstrate that experiments that produce and characterize two-mode light squeezing c

Mostafa Behtouei, Emanuela Carideo, Mikhail Zobov, Mauro Migliorati

The purpose of this paper is to calculate the longitudinal and transverse wakefields of the FCC collimators by using the electromagnetic codes ECHO3D and IW2D. We cross-checked our results using CST particle studio for long bunches, and found them to be in good agreement. The obtained results show that the collimators give one of the highest contributions to

Antoine Ducros

In this article, we carry out the flattening techniques developped in a former work in order to ``embellish" a map between compact analytic spaces, to describe the structure of its image, getting this way a substitute for Chevalley's theorem in the non-archimedean setting, and finally to show that flatness in the world of Berkovich spaces amounts to naive fl

Wilhelm Klingenberg, Ben Lambert, Julian Scheuer

Consider a convex cone in three-dimensional Minkowski space which either contains the lightcone or is contained in it. This work considers mean curvature flow of a proper spacelike strictly mean convex disc in the cone which is graphical with respect to its rays. Its boundary is required to have constant intersection angle with the boundary of the cone. We p

Shuanghong Shen, Enhong Chen, Bihan Xu, Qi Liu

Knowledge tracing (KT) aims to assess individuals' evolving knowledge states according to their learning interactions with different exercises in online learning systems (OIS), which is critical in supporting decision-making for subsequent intelligent services, such as personalized learning source recommendation. Existing researchers have broadly studied KT

Lauro Silini

We prove that in any rank one symmetric space of non-compact type $M\in\{\mathbb{R} H^n,\mathbb{C} H^m,\mathbb{H} H^m,\mathbb{O} H^2\}$, geodesic spheres are uniformly quantitatively stable with respect to small $C^1$-volume preserving perturbations. We quantify the gain of perimeter in terms of the $W^{1,2}$-norm of the perturbation, taking advantage of the

Amit Kumar Chatterjee, Satoshi Takada, Hisao Hayakawa

We demonstrate the quantum Mpemba effect in a quantum dot coupled to two reservoirs, described by the Anderson model. We show that the system temperatures starting from two different initial values (hot and cold), cross each other at finite time (and thereby reverse their identities i.e. hot becomes cold and vice versa) to generate thermal quantam Mpemba eff

Alexander Walsemann, Michael Karagounis, Alexander Stanitzki, Dietmar Tutsch

While microprocessors are used in various applications, they are precluded from the use in high-energy physics applications due to the harsh radiation present. To overcome this limitation a microprocessor design must withstand high doses of radiation and mitigate radiation induced soft errors. A TMR protection scheme is applied to protect a RISC-V microproce

Xuyang Wang, Bo Tang, Wenjun Wu, Da Li

In this paper, we consider waveform design for dualfunction radar-communication systems based on multiple-inputmultiple-out arrays. To achieve better Rician target detection performance, we use the relative entropy associated with the formulated detection problem as the design metric. We also impose a multiuser interference energy constraint on the waveforms

Lorenzo Dania, Dmitry S. Bykov, Florian Goschin, Markus Teller

A levitated nanomechanical oscillator under ultra-high vacuum (UHV) is highly isolated from its environment. It has been predicted that this isolation leads to very low mechanical dissipation rates. However, a gap persists between predictions and experimental data. Here, we levitate a silica nanoparticle in a linear Paul trap at room temperature, at pressure

Burak Ekim, Michael Schmitt

Jointly harnessing complementary features of multi-modal input data in a common latent space has been found to be beneficial long ago. However, the influence of each modality on the models decision remains a puzzle. This study proposes a deep learning framework for the modality-level interpretation of multimodal earth observation data in an end-to-end fashio

Mohammad Sarhil, Oleg Shchyglo, Hesham Salama, Dominik Brands

To model mechanically-driven phase transformations using the phase-field theory, suitable models are needed for describing the mechanical fields related to individual phase-fields in the interfacial regions. They play a crucial role in obtaining the mechanical driving forces of phase-field evolution. Quantitative modeling requires satisfying the interfacial

Florian Haberberger, Christian Hainzl, Phan Thành Nam, Robert Seiringer

We consider a low density Bose gas interacting through a repulsive potential in the thermodynamic limit. We justify, as a rigorous lower bound, a Lee--Huang--Yang type formula for the free energy at suitably low temperatures, where the modified excitation spectrum leads to a second order correction of the same order as the Lee--Huang--Yang correction to the

Pawan Bharadwaj, Madhusudan Sharma, Isha Lohan, Pragna Sahoo

This study examines almost thirty deep-focus earthquakes, magnitudes starting from Mw 6.0 and higher, with the aim of accurately determining the source-time function (STF) of P arrival and its azimuthal dependence. We use the variational symmetric autoencoder (SymVAE), a neural network architecture designed to automatically isolate earthquake information fro

M. Fabbrichesi, R. Floreanini, E. Gabrielli, L. Marzola

Quantum tomography provides the full reconstruction of the density matrix of a state. We use it to study the Higgs boson decay into weak gauge bosons. Anomalous couplings beyond the Standard Model can be constrained by means of observables easily defined in terms of the polarization density matrix. We describe a strategy based on three observables that toget

Mario Beraha, Matteo Pegoraro

We consider the 2-Wasserstein space of probability measures supported on the unit-circle, and propose a framework for Principal Component Analysis (PCA) for data living in such a space. We build on a detailed investigation of the optimal transportation problem for measures on the unit-circle which might be of independent interest. In particular, we derive an

Quan Yuan, Zhikun Zhang, Linkang Du, Min Chen

Graph data is used in a wide range of applications, while analyzing graph data without protection is prone to privacy breach risks. To mitigate the privacy risks, we resort to the standard technique of differential privacy to publish a synthetic graph. However, existing differentially private graph synthesis approaches either introduce excessive noise by dir

Paolo Molaro

An intriguing reference to the existence of a self-portrait by Galileo Galilei is contained in the biography of the scientist by Thomas Salusbury dated ca. 1665, of which only one incomplete and inaccessible copy exists. Galileo grew up in a Renaissance atmosphere, acquiring an artistic touch. He was a musician, a writer and also a painter, as reported by Vi

P. E. Georgoudis

This contribution discusses a new perception of the structure of compound nuclei by introducing intermediate states of the Feshbach formalism of nuclear reactions in the Interacting Boson Model of nuclear structure. The stake is to explore the manifestation of the unitary limit in heavy, even-even nuclei. Interactions that govern Feshbach resonances of cold

Andrea Addazi, Antonino Marcianò, António P. Morais, Roman Pasechnik

We formulate a version of the low-scale Majoron model equipped with an inverse seesaw mechanism featuring lepton-number preserving dimension-6 operators in the scalar potential. Contrary to its dimension-4 counterpart, we find that the model can simultaneously provide light and ultralight Majorons, neutrino masses and their mixing, while featuring strong fir

Bin Lyu, Chao Zhou, Shimin Gong, Dinh Thai Hoang

In this paper, we propose a robust secure transmission scheme for an active reconfigurable intelligent surface (RIS) enabled symbiotic radio (SR) system in the presence of multiple eavesdroppers (Eves). In the considered system, the active RIS is adopted to enable the secure transmission of primary signals from the primary transmitter to multiple primary use

Marco Boldrin, Mattia Dan, Vanni Toigo, Loris Zanotto

MITICA (Megavolt ITER Injector & Concept Advancement), the full scale prototype of ITER Heating Neutral Beam, is under realization at the Neutral Beam Test Facility (Padova, Italy). It is designed to deliver 16.5 MW to ITER plasma, obtained by accelerating negative Deuterium ions up to 1 MeV for a total ion current of 40 A and then neutralized. MITICA Accele

Aditya Mohan, Carolin Benjamins, Konrad Wienecke, Alexander Dockhorn

Although Reinforcement Learning (RL) has shown to be capable of producing impressive results, its use is limited by the impact of its hyperparameters on performance. This often makes it difficult to achieve good results in practice. Automated RL (AutoRL) addresses this difficulty, yet little is known about the dynamics of the hyperparameter landscapes that h

Mischa Huisman, Carlos Murguia, Erjen Lefeber, Nathan van de Wouw

Cooperative Adaptive Cruise Control (CACC) is a technology that allows groups of vehicles to form in automated, tightly-coupled platoons. CACC schemes exploit Vehicle-to-Vehicle (V2V) wireless communications to exchange information between vehicles. However, the use of communication networks brings security concerns as it exposes network access points that t

Zohreh Aliabadi, Tekgül Kalaycı

The Euclidean hull of a linear code $C$ is defined as $C\cap C^{\perp}$, where $C^\perp$ denotes the dual of $C$ under the Euclidean inner product. A linear code with zero hull dimension is called a linear complementary dual (LCD) code. A pair $(C, D)$ of linear codes of length $n$ over $\mathbb{F}_q$ is called a linear complementary pair (LCP) of codes if $

Elise Bonnail, Eric Lecolinet, Wen-Jie Tseng, Samuel Huron

Human memory has notable limitations (e.g., forgetting) which have necessitated a variety of memory aids (e.g., calendars). As we grow closer to mass adoption of everyday Extended Reality (XR), which is frequently leveraging perceptual limitations (e.g., redirected walking), it becomes pertinent to consider how XR could leverage memory limitations (forgettin

Christian Hespe, Herbert Werner

Recently, a scalable approach to system analysis and controller synthesis for homogeneous multi-agent systems with Bernoulli distributed packet loss has been proposed. As a key result of that line of work, it was shown how to obtain upper bounds on the $H_2$-norm that are robust with respect to uncertain interconnection topologies. The main contribution of t

Canchen Jiang, Ariel Liebman, Hao Wang

The increased adoption of electric vehicles (EVs) has led to the development of vehicle-to-anything (V2X) technologies, including vehicle-to-home (V2H), vehicle-to-grid (V2G), and energy trading of EVs in the local grid. The EV coordination can provide value to the grid and generate benefits for EVs. However, network constraints and uncertainties in renewabl

Henri Gouin

The invariance theorems obtained in analytical mechanics and derived from Noether's theorems can be adapted to fluid mechanics. For this purpose, it is useful to give a functional representation of the fluid motion and to interpret the invariance group with respect to time in the quadri-dimensional reference space of Lagrangian variables. A powerful method o

Dylan Lewis, João P. Moutinho, António Costa, Yasser Omar

The transfer of information between two physical locations is an essential component of both classical and quantum computing. In quantum computing the transfer of information must be coherent to preserve quantum states and hence the quantum information. We establish a simple protocol for transferring one- and two-electron encoded logical qubits in quantum do

I. Ciraldo, G. A. Brischetto, D. Torresi, M. Cavallaro

A new gas detector prototype for the upgrade of the focal plane detector of the MAGNEX large-acceptance magnetic spectrometer has been developed and tested in view of the NUMEN project. It has been designed to operate at low gas pressure for detecting medium to heavy ions in the energy range between 15 and 60 AMeV. It is a drift chamber based on Multi-layer

Bo Qian, Hao Chen, Xiangning Wang, Haoxuan Che

Computer-assisted automatic analysis of diabetic retinopathy (DR) is of great importance in reducing the risks of vision loss and even blindness. Ultra-wide optical coherence tomography angiography (UW-OCTA) is a non-invasive and safe imaging modality in DR diagnosis system, but there is a lack of publicly available benchmarks for model development and evalu

Oskar Vågerö, Anders Bråte, Alexandra Wittemann, Jessica Yarin Robinson

Across Europe negative public opinion has and may continue to limit the deployment of renewable energy infrastructure required for the transition to net-zero energy systems. Understanding public sentiment and its spatio-temporal variations is as such important for decision-making and socially accepted energy systems. In this study, we apply a sentiment class

Volker Branding

This article is concerned with the stability of triharmonic maps and in particular triharmonic hypersurfaces. After deriving a number of general statements on the stability of triharmonic maps we focus on the stability of triharmonic hypersurfaces in space forms, where we pay special attention to their normal stability. We show that triharmonic hypersurfaces

Elise Bayraktar, Emmanuelle Clément

We consider a pure-jump stable Cox-Ingersoll-Ross ($\alpha$-stable CIR) process driven by a non-symmetric stable L{\'e}vy process with jump activity $\alpha$ $\in$ (1, 2) and we address the joint estimation of drift, scaling and jump activity parameters from high-frequency observations of the process on a fixed time period. We first prove the existence of a

Anton Baranov, Philippe Jaming, Karim Kellay, Michael Speckbacher

The aim of this paper is to extend two results from the Paley--Wiener setting to more generalmodel spaces. The first one is an analogue of the oversampling Shannon sampling formula. The second one is a version of the Donoho--Logan Large Sieve Theorem which is a quantitative estimate of the embedding of the Paley--Wiener space into an $L^2(\R,\mu)$ space.

Ali Ghaddar, Sanae Touil, B. Sauviac, Bernard Bayard

This comparative study allows to evaluate the performance of an electromagnetic jet to determine the electromagnetic response of materials, without being in usual far field conditions. In this work, the reflection coefficient of a substrate with ground plane, calculated analytically, is compared with that determined in simulation by the electromagnetic jet.

Umais Zahid, Qinghai Guo, Zafeirios Fountas

Backpropagation has rapidly become the workhorse credit assignment algorithm for modern deep learning methods. Recently, modified forms of predictive coding (PC), an algorithm with origins in computational neuroscience, have been shown to result in approximately or exactly equal parameter updates to those under backpropagation. Due to this connection, it has

Antoine Passemiers, Pietro Folco, Daniele Raimondi, Giovanni Birolo

Saliency Maps (SMs) have been extensively used to interpret deep learning models decision by highlighting the features deemed relevant by the model. They are used on highly nonlinear problems, where linear feature selection (FS) methods fail at highlighting relevant explanatory variables. However, the reliability of gradient-based feature attribution methods

R. Mosseri, J. Vidal

We study the energy spectrum of tight-binding Hamiltonian for regular hyperbolic tilings. More specifically, we compute the density of states using the continued-fraction expansion of the Green function on finite-size systems with more than $10^9$ sites and open boundary conditions. The coefficients of this expansion are found to quickly converge so that the

Maximilian P Niroomand, David J Wales

The ability to explain decisions made by machine learning models remains one of the most significant hurdles towards widespread adoption of AI in highly sensitive areas such as medicine, cybersecurity or autonomous driving. Great interest exists in understanding which features of the input data prompt model decision making. In this contribution, we propose a

Vartika Singh, Veeraruna Kavitha

Celebrities can significantly influence the public towards any desired outcome. In a bid to tackle an infectious disease, a leader (government) exploits such influence towards motivating a fraction of public to get vaccinated, sufficient enough to ensure eradication. The leader also aims to minimize the vaccinated fraction of public (that ensures eradication

Amber Srivastava, Mingzhou Yin, Andrea Iannelli, Roy S. Smith

This work presents a dual system-level parameterization (D-SLP) method for closed-loop system identification. The recent system-level synthesis framework parameterizes all stabilizing controllers via linear constraints on closed-loop response functions, known as system-level parameters. It was demonstrated that several structural, locality, and communication

Raúl Martínez-Bohórquez

In this work we prove that there are no electromagnetic energy tensors in second order Lovelock gravities that verify properties equivalent to those of the Maxwell electromagnetic energy tensor in General Relativity.

Zirui Cao, Haowei Wang, Ek Peng Chew, Haobin Li

Simulation-based ranking and selection (R&S) is a popular technique for optimizing discrete-event systems (DESs). It evaluates the mean performance of system designs by simulation outputs and aims to identify the best system design from a set of alternatives by intelligently allocating a limited simulation budget. In R&S, the optimal computing budget allocat

Caroline Hillairet, Anthony Reveillac

In this paper we fill a gap in the literature by providing exact and explicit expressions for the correlation of general Hawkes processes together with its intensity process. Our methodology relies on the Poisson imbedding representation and on recent findings on Malliavin calculus and pseudo-chaotic representation for counting processes.

Jun Sun, Xiaobao Zhu

In this note we will provide a gradient estimate for harmonic maps from a complete noncompact Riemannian manifold with compact boundary (which we call "Kasue manifold") into a simply connected complete Riemannian manifold with non-positive sectional curvature. As a consequence, we can obtain a Liouville theorem. We will also show the nonexistence of positive

P. V. Akacevich, A. V. Ivanov

In this paper, we study two-loop contribution to the effective action of a two-dimensional sigma model. We derive a new formula, which can be applicable to a regularization of general type. As examples, we obtain known results for dimensional regularization and investigate new types of cutoff one. Also, we discuss non-local contributions and restrictions on

G. A. Souliotis, S. Koulouris, F. Cappuzzello, D. Carbone

An approach to identify medium-mass ejectiles from peripheral heavy-ion reactions in the energy region of 15 MeV/nucleon is developed for data obtained with a large acceptance magnetic spectrometer. This spectrometer is equipped with a focal plane multidetector, providing position, angle, energy loss and residual energy of the ions along with measurement of

Naoki Kitazawa

In our previous work, we have constructed explicit smooth real algebraic functions which may have both compact and non-compact preimages on smooth real algebraic manifolds. This paper presents its variant. Our result is new in obtaining non-proper smooth real algebraic functions on smooth real algebraic manifolds satisfying explicit conditions on (non-)compa

Shuhang Zhang, Bokeon Kwak, Dario Floreano

Edible robotics is an emerging research field with potential use in environmental, food, and medical scenarios. In this context, the design of edible control circuits could increase the behavioral complexity of edible robots and reduce their dependence on inedible components. Here we describe a method to design and manufacture edible control circuits based o

Colin Vignon, Jean Rabault, Joel Vasanth, Francisco Alcántara-Ávila

Rayleigh-B\'enard convection (RBC) is a recurrent phenomenon in several industrial and geoscience flows and a well-studied system from a fundamental fluid-mechanics viewpoint. However, controlling RBC, for example by modulating the spatial distribution of the bottom-plate heating in the canonical RBC configuration, remains a challenging topic for classical c

Matteo Lapucci, Pierluigi Mansueto

In this paper, we consider multi-objective optimization problems with a sparsity constraint on the vector of variables. For this class of problems, inspired by the homonymous necessary optimality condition for sparse single-objective optimization, we define the concept of L-stationarity and we analyze its relationships with other existing conditions and Pare

Shan Yu, Yair Censor, Ming Jiang, Guojie Luo

The feasibility-seeking approach provides a systematic scheme to manage and solve complex constraints for continuous problems, and we explore it for the floorplanning problems with increasingly heterogeneous constraints. The classic legality constraints can be formulated as the union of convex sets. However, the convergence of conventional projection-based a

Manfried Faber

We describe particles in a potential by a special diffusion process, the maximal entropy random walk (MERW) on a lattice. Since MERW originates in a variational problem, it shares the linear algebra of Hilbert spaces with quantum mechanics. The Born rule appears from measurements between equilibrium states in the past and the same equilibrium states in the f

Steven Kim, Fabian Hassler

Open quantum systems that interact with a Markovian environment can be described by a Lindblad master equation. The generator of time-translation is given by a Liouvillian superoperator $\mathcal{L}$ acting on the density matrix of the system. As the Fock space for a single bosonic mode is already infinite-dimensional, the diagonalization of the Liouvillian

Oliver Withington, Laurissa Tokarchuk

Expressive Range Analysis (ERA), an approach for visualising the output of Procedural Content Generation (PCG) systems, is widely used within PCG research to evaluate and compare generators, often to make comparative statements about their relative performance in terms of output diversity and search space exploration. Producing a standard ERA visualisation r

Cordula Reisch, Hendrik Ranocha

We guide the reader on a journey through mathematical modeling and numerical analysis, emphasizing the crucial interplay of both disciplines. Targeting undergraduate students with basic knowledge in dynamical systems and numerical methods for ordinary differential equations, we explore a model from mathematical biology where numerical methods fail badly due

Kai Han, Xiaohu Huang, Yandong Li, Sagar Vaze

Existing machine learning models demonstrate excellent performance in image object recognition after training on a large-scale dataset under full supervision. However, these models only learn to map an image to a predefined class index, without revealing the actual semantic meaning of the object in the image. In contrast, vision-language models like CLIP are

Pietro Bonfà, Sangeeta Sharma, John Kay Dewhurst

Mejia-Rodriguez and Trickey recently proposed a procedure for removing the explicit dependence of meta-GGA exchange-correlation energy functionals $E_{\rm xc}$ on the kinetic energy density $\tau$. We present a simple modification to this approach in which the exact Kohn-Sham $\tau$ is used as input for $E_{\rm xc}$ but the functional derivative of $\tau$ wi

Roberto Cianci, Stefano Vignolo, Luca Fabbri

We consider the Dirac equations in static spherically-symmetric space-times, and we present a type of spinor field whose structure allows the separation of elevation angle and radial coordinate in very general situations. We demonstrate that after such a separation of variables the Dirac equations reduce to two equations that can always be integrated, at lea

Ruixue Jing, Luis Enrique Correa Rocha

A cryptocurrency is a digital asset maintained by a decentralised system using cryptography. Investors in this emerging digital market are exploring the profitability potential of portfolios in place of single coins. Portfolios are particularly useful given that price forecasting in such a volatile market is challenging. The crypto market is a self-organised