January 2022 arXiv papers — page 49

Komlan Payne, Leslie L. Ying, Xiaoliang Zhang

Electromagnetic decoupling among a close-fitting or high-density transceiver RF array elements is required to maintain the integrity of the magnetic flux density from individual channel for enhanced performance in detection sensitivity and parallel imaging. High-impedance RF coils have demonstrated to be a prominent design method to circumvent these coupling

José Carlos Bellido, Javier Cueto, Carlos Mora-Corral

In this paper we develop a new set of results based on a nonlocal gradient jointly inspired by the Riesz s-fractional gradient and Peridynamics, in the sense that its integration domain depends on a ball of radius delta > 0 (horizon of interaction among particles, in the terminology of Peridynamics), while keeping at the same time the singularity of the Ries

Weihong Zhang, Shengqi Feng

Stiffener layout optimization of complex surfaces is fulfilled within the framework of topology optimization. A combined parameterization method is developed in two aspects. One is to parameterize the material distribution of the stiffener layout by means of B-spline. The other is to build the mapping relationship from the known 3D surface mesh of the thin-w

Nicolas Chastrette, Michael Baudoin, Philippe Brunet, Laurent Royon

The oscillation instability of sessile drops is ubiquitous in surface acoustic wave (SAW)-powered digital microfluidics. Yet, the physics underlying these phenomena has not been elucidated owing to the interplay between hydrodynamics, acoustics and capillarity. We decipher the instability by combining high-speed imaging with pressure measurements. We rationa

Navdeep Singh Dhindsa, Raghav G. Jha, Anosh Joseph, Abhishek Samlodia

We study the bosonic part of the BMN matrix model for wide ranges of temperatures, values of the deformation parameter, and numbers of colors $16 \leq N \leq 48$. Using lattice computations, we analyze phase transitions in the model, observing a single first-order transition from a uniform to a gapped phase for all values of the deformation parameter. We stu

Dakota K. Keblbeck, Ramesh Bhandari, Nadeesha D. Gamage, Madhawa Horana Gamage

"Ultra-low" Q value $\beta$ decays are referred to as such due to their low decay energies of less than $\sim$1 keV. Such a low energy decay is possible when the parent nucleus decays into an excited state in the daughter, with an energy close to that of the Q value. These decays are of interest as potential new candidates for neutrino mass determination exp

Akshansh Mishra, Raheem Al-Sabur, Ahmad K. Jassim

Nowadays, manufacturing sectors harness the power of machine learning and data science algorithms to make predictions for the optimization of mechanical and microstructure properties of fabricated mechanical components. The application of these algorithms reduces the experimental cost beside leads to reduce the time of experiments. The present research work

Raoni Arroyo

This book deals with some ontological implications of standard non-relativistic quantum mechanics, and the use of the notion of `consciousness' to solve the measurement problem.

Ivica Dimitrovski, Ivan Kitanovski, Panče Panov, Nikola Simidjievski

The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite imagery as well as repository of AI-ready Earth Observation (EO) datasets. It can be easily applied for a variety of Earth Observation tasks, such as land use and cover classificati

Debasis Dwibedy, Rakesh Mohanty

We study the computational complexity of the non-preemptive scheduling problem of a list of independent jobs on a set of identical parallel processors with a makespan minimization objective. We make a maiden attempt to explore the combinatorial structure showing the exhaustive solution space of the problem by defining the \textit{Scheduling Solution Space Tr

Jiaxin Wang, Jianning Fu, Weikai Zong, Yang Pan

The spotted detached eclipsing binary (DEB) offers insights into starspots on the binary. Three spotted DEBs, KIC 8097825, KIC 6859813, and KIC 5527172, which were observed by the Kepler photometry and LAMOST spectroscopy, are studied in this work. The physical parameters of binaries are determined by binary modeling. The sizes, lifetimes, and single/double-

Dorjan Hitaj, Giulio Pagnotta, Briland Hitaj, Fernando Perez-Cruz

Proposed as a solution to mitigate the privacy implications related to the adoption of deep learning, Federated Learning (FL) enables large numbers of participants to successfully train deep neural networks without having to reveal the actual private training data. To date, a substantial amount of research has investigated the security and privacy properties

Luana M. Modafferi, Joan Moragues, David Keitel, LIGO Scientific Collaboration

Pulsars are spinning neutron stars which emit an electromagnetic beam. We expect pulsars to slowly decrease their rotational frequency. However, sudden increases of the rotational frequency have been observed from different pulsars. These events are called "glitches" and they are followed by a relaxation phase with timescales from days to months. Gravitation

Frank Aurzada, Martin Kilian, Ercan Sönmez

We consider the sum of two self-similar centred Gaussian processes with different self-similarity indices. Under non-negativity assumptions of covariance functions and some further minor conditions, we show that the asymptotic behaviour of the persistence probability of the sum is the same as for the single process with the greater self-similarity index. In

S. S. Harilal, M. C. Phillips, D. H. Froula, K. K. Anoop

Laser-produced plasmas (LPPs) engulf exotic and complex conditions ranging in temperature, density, pressure, magnetic and electric fields, charge states, charged particle kinetics, and gas-phase reactions, based on the irradiation conditions, target geometries, and the background cover gas. The application potential of the LPP is so diverse that it generate

Nicola Bartolo, Daniele Bertacca, Robert Caldwell, Carlo R. Contaldi

We investigate the sensitivity of the Laser Interferometer Space Antenna (LISA) to the anisotropies of the Stochastic Gravitational Wave Background (SGWB). We first discuss the main astrophysical and cosmological sources of SGWB which are characterized by anisotropies in the GW energy density, and we build a Signal-to-Noise estimator to quantify the sensitiv

Wouter Heyvaert, Adrián Pedrazo-Tardajos, Ajinkya Kadu, Nathalie Claes

Chirality in inorganic nanoparticles and nanostructures has gained increasing scientific interest, because of the possibility to tune their ability to interact differently with left- and right-handed circularly polarized light. In some cases, the optical activity is hypothesized to originate from a chiral morphology of the nanomaterial. However, quantifying

Kwanhyung Lee, Hyewon Jeong, Seyun Kim, Donghwa Yang

Electroencephalogram (EEG) is an important diagnostic test that physicians use to record brain activity and detect seizures by monitoring the signals. There have been several attempts to detect seizures and abnormalities in EEG signals with modern deep learning models to reduce the clinical burden. However, they cannot be fairly compared against each other a

Zhuowei Li, Zihao Liu, Zhiqiang Hu, Qing Xia

Medical image segmentation has been widely recognized as a pivot procedure for clinical diagnosis, analysis, and treatment planning. However, the laborious and expensive annotation process lags down the speed of further advances. Contrastive learning-based weight pre-training provides an alternative by leveraging unlabeled data to learn a good representation

Gian Marti, Christoph Studer

Wireless systems must be resilient to jamming attacks. Existing mitigation methods require knowledge of the jammer's transmit characteristics. However, this knowledge may be difficult to acquire, especially for smart jammers that attack only specific instants during transmission in order to evade mitigation. We propose a novel method that mitigates attacks b

Gilyoung Cheong, Nathan Kaplan

Let $p$ be prime and $X$ be a Haar-random $n \times n$ matrix over $\mathbb{Z}_{p}$, the ring of $p$-adic integers. Let $P_{1}(t), \dots, P_{l}(t) \in \mathbb{Z}_{p}[t]$ be monic polynomials of degree at most $2$ whose images modulo $p$ are distinct and irreducible in $\mathbb{F}_{p}[t]$. For each $j$, let $G_{j}$ be a finite module over $\mathbb{Z}_{p}[t]/(

Stefan Vamosi, Michael Platzer, Thomas Reutterer

AI-based face recognition, i.e., the re-identification of individuals within images, is an already well established technology for video surveillance, for user authentication, for tagging photos of friends, etc. This paper demonstrates that similar techniques can be applied to successfully re-identify individuals purely based on their behavioral patterns. In

Luca Zampieri, Sandro Mereghetti, Roberto Turolla, Giampiero Naletto

In September 2021 the magnetar SGR J1935+2154 entered a stage of burst/flaring activity in the hard X-ray band. On September 10, 2021 we observed SGR J1935+2154 with the fiber-fed fast optical photon counter IFI+Iqueye, mounted at the 1.22 m Galileo telescope in Asiago. During one of the IFI+Iqueye observing windows a hard X-ray burst was detected with the F

Peter A. Gao, Jon Wakefield

In countries where population census data are limited, generating accurate subnational estimates of health and demographic indicators is challenging. Existing model-based geostatistical methods leverage covariate information and spatial smoothing to reduce the variability of estimates but often ignore survey design, while traditional small area estimation ap

Hadi Hosseini, Fatima Umar, Rohit Vaish

Strategic behavior in two-sided matching markets has been traditionally studied in a "one-sided" manipulation setting where the agent who misreports is also the intended beneficiary. Our work investigates "two-sided" manipulation of the deferred acceptance algorithm where the misreporting agent and the manipulator (or beneficiary) are on different sides. Spe

Kaushar Vaidya, Anju Panthi, Manan Agarwal, Sindhu Pandey

NGC 7789 is a $\sim$1.6 Gyr old, populous open cluster located at $\sim$2000 pc. We characterize the blue straggler stars (BSS) of this cluster using the Ultraviolet (UV) data from the UVIT/AstroSat. We present spectral energy distributions (SED) of 15 BSS candidates constructed using multi-wavelength data ranging from UV to IR wavelengths. In 8 BSS candidat

Alexander Bork, Joost-Pieter Katoen, Tim Quatmann

We consider the problem: is the optimal expected total reward to reach a goal state in a partially observable Markov decision process (POMDP) below a given threshold? We tackle this -- generally undecidable -- problem by computing under-approximations on these total expected rewards. This is done by abstracting finite unfoldings of the infinite belief MDP of

Ding Chen, Peixi Peng, Tiejun Huang, Yonghong Tian

With the help of special neuromorphic hardware, spiking neural networks (SNNs) are expected to realize artificial intelligence (AI) with less energy consumption. It provides a promising energy-efficient way for realistic control tasks by combining SNNs with deep reinforcement learning (RL). There are only a few existing SNN-based RL methods at present. Most

Eugenio Megias, Evandro Andrade, Airton Deppman, Arnaldo Gammal

We study the applications of non-extensive Tsallis statistics to high energy and hadron physics. These applications include studies of $pp$ collisions, equation of state of QCD, as well as Bose-Einstein condensation. We also analyze the connections of Tsallis statistics with thermofractals, and address some of the conceptual aspects of the fractal approach,

Kaitlin Gili, Marta Mauri, Alejandro Perdomo-Ortiz

As the quantum computing community gravitates towards understanding the practical benefits of quantum computers, having a clear definition and evaluation scheme for assessing practical quantum advantage in the context of specific applications is paramount. Generative modeling, for example, is a widely accepted natural use case for quantum computers, and yet

Masahiro Yamamoto

For fractional derivatives and time-fractional differential equations, we construct a framework on the basis of the operator theory in fractional Sobolev spaces. Our framework provides a feasible extension of the classical Caputo and the Riemann-Liouville derivatives within Sobolev spaces of fractional orders including negative ones. Our approach enables a u

Christel Baier, Florian Funke, Jakob Piribauer, Robin Ziemek

The purpose of this paper is to introduce a notion of causality in Markov decision processes based on the probability-raising principle and to analyze its algorithmic properties. The latter includes algorithms for checking cause-effect relationships and the existence of probability-raising causes for given effect scenarios. Inspired by concepts of statistica

A. Nicholas Day, Allan Lo

The upper density of an infinite graph $G$ with $V(G) \subseteq \mathbb{N}$ is defined as $\overline{d}(G) = \limsup_{n \rightarrow \infty}{|V(G) \cap \{1,\ldots,n\}|}/{n}$. Let $K_{\mathbb{N}}$ be the infinite complete graph with vertex set $\mathbb{N}$. Corsten, DeBiasio, Lamaison and Lang showed that in every $2$-edge-colouring of $K_{\mathbb{N}}$, there

Warren Massonneau, Marta Volonteri, Yohan Dubois, Ricarda S. Beckmann

Super-Eddington accretion is one scenario that may explain the rapid assembly of $\sim 10^9\rm\, M_\odot$ supermassive black holes (BHs) within the first billion year of the Universe. This critical regime is associated with radiatively inefficient accretion and accompanied by powerful outflows in the form of winds and jets. By means of hydrodynamical simulat

Da Eun Kang, Eric W. Pellegrini, Lynton Ardizzone, Ralf S. Klessen

Young massive stars play an important role in the evolution of the interstellar medium (ISM) and the self-regulation of star formation in giant molecular clouds (GMCs) by injecting energy, momentum, and radiation (stellar feedback) into surrounding environments, disrupting the parental clouds, and regulating further star formation. Information of the stellar

P. G. Romeo, Alanka Thomas

Group action on an algebraic structure gives a representation of the group by automorphisms on the structure. An action of a group on a lattice gives a group lattice. K.S.S. Nambooripad introduced G-lattice in 1990. In this paper revisits Nambooripad construction of G-lattice.

Hashmat Shadab Malik, Ikboljon Sobirov, Abdelrahman Mohamed

Object detection is a challenging and popular computer vision problem. The problem is even more challenging in aerial images due to significant variation in scale and viewpoint in a diverse set of object categories. Recently, deep learning-based object detection approaches have been actively explored for the problem of object detection in aerial images. In t

L. V. Bork, N. B. Muzhichkov, E. S. Sozinov

We investigate the structure of the five-point W boson scattering amplitude in N=4 SYM on the Coulomb branch in a small mass limit. We show that up to two loops the IR divergences exponentiate and are controlled by the $\Gamma_{oct}$ anomalous dimension similar to the four-point amplitude case considered recently in the literature. We also make a conjecture

Daniel Sucerquia, Cristian Parra, Pilar Cossio, Olga Lopez-Acevedo

Ab initio metadynamics enables extracting free-energy landscapes having the accuracy of first principles electronic structure methods. We introduce an interface between the PLUMED code that computes free-energy landscapes and enhanced-sampling algorithms and the ASE module, which includes several ab initio electronic structure codes. The interface is validat

Andrei Seymour-Howell

We derive an algorithm to rigorously compute and verify Maass cusp forms of squarefree level and trivial character. The main tool we use is an explicit version of the Selberg trace formula with Hecke operators due to Str\"{o}mbergsson. We use this algorithm to compute several thousand Maass forms for a range of levels and use this data to obtain numerical ev

F. Yan, A. Reiners, E. Pallé, D. Shulyak

Ultra-hot Jupiters (UHJs) are gas giants with very high equilibrium temperatures. In recent years, multiple chemical species, including various atoms and ions, have been discovered in their atmospheres. Most of these observations have been performed with transmission spectroscopy, although UHJs are also ideal targets for emission spectroscopy due to their st

Dietrich Burde, Wolfgang Alexander Moens

We study {\em disemisimple} Lie algebras, i.e., Lie algebras which can be written as a vector space sum of two semisimple subalgebras. We show that a Lie algebra $\mathfrak{g}$ is disemisimple if and only if its solvable radical coincides with its nilradical and is a prehomogeneous $\mathfrak{s}$-module for a Levi subalgebra $\mathfrak{s}$ of $\mathfrak{g}$.

Callum T. Donnan, Rita Tojeiro, Katarina Kraljic

Understanding the relationship between the cosmic web and the gas content of galaxies is a key step towards understanding galaxy evolution. However, the impact of the cosmic web on the growth of galaxies and dark matter halos is not yet properly understood. We report a detection of the effect of the cosmic web on the galaxy stellar mass - gas phase metallici

Per Mattsson, Dave Zachariah, Petre Stoica

We consider the problem of finding tuned regularized parameter estimators for linear models. We start by showing that three known optimal linear estimators belong to a wider class of estimators that can be formulated as a solution to a weighted and constrained minimization problem. The optimal weights, however, are typically unknown in many applications. Thi

Suman Paul, Tanuka Chattopadhyay

The advancement in the field of data science especially in machine learning along with vast databases of variable star projects like the Optical Gravitational Lensing Experiment (OGLE) encourages researchers to analyse as well as classify light curves of different variable stars automatically with efficiency. In the present work, we have demonstrated the rel

Robert Shah, Thomas Barrett, Andrea Colcelli, Fedja Orucevic

We experimentally study a gas of quantum degenerate $^{87}$Rb atoms throughout the full dimensional crossover, from a one-dimensional (1D) system exhibiting phase fluctuations consistent with 1D theory to a three-dimensional (3D) phase-coherent system, thereby smoothly interpolating between these distinct, well-understood regimes. Using a hybrid trapping arc

Benjamin Aram Berendsohn, Simona Boyadzhiyska, László Kozma

We study edge-labelings of the complete bidirected graph $\overset{\tiny\leftrightarrow}{K}_n$ with functions from the set $[d] = \{1, \dots, d\}$ to itself. We call a cycle in $\overset{\tiny\leftrightarrow}{K}_n$ a fixed-point cycle if composing the labels of its edges results in a map that has a fixed point, and we say that a labeling is fixed-point-free

Daniel Tay, Benoît Grémaud, Christian Miniatura

In this work, we consider a two-dimensional square lattice of pinned magnetic spins with nearest-neighbour interactions and we randomly replace a fixed proportion of spins with nonmagnetic defects carrying no spin. We focus on the linear spin-wave regime and address the propagation of a spin-wave excitation with initial momentum $k_0$. We compute the disorde

Kourosh Shoele

We investigate the dynamics and energy production capability of a flexible piezoelectric plate submerged close to the free surface and exposed to incident head gravity waves and current. A theoretical model is derived in which the flag and its wake are represented with a vortex line while the body of the fluid is considered to be inviscid. The model is emplo

Fausto Barbero, Fan Yang

We analyze the causal-observational languages that were introduced in Barbero and Sandu (2018), which allow discussing interventionist counterfactuals and functional dependencies in a unified framework. In particular, we systematically investigate the expressive power of these languages in causal team semantics, and we provide complete natural deduction calc

Judit Clopés Llahí, Aitor Martín-Gómez, Gerhard Gompper, Roland G. Winkler

The conformational and dynamical properties of active Brownian polymers embedded in a fluid depend on the nature of the driving mechanism, e.g., self-propulsion or external actuation of the monomers. Implementations of self-propelled and actuated active Brownian polymers in a multiparticle collision dynamics (MPC) fluid are presented, which capture the disti

Jürgen Knödlseder, Sylvie Brau-Nogué, Mickael Coriat, Philippe Garnier

The carbon footprint of astronomical research is an increasingly topical issue with first estimates of research institute and national community footprints having recently been published. As these assessments have typically excluded the contribution of astronomical research infrastructures, we complement these studies by providing an estimate of the contribu

Jalal Mirakhorli

Recent studies have shown that multi-modeling methods can provide new insights into the analysis of brain components that are not possible when each modality is acquired separately. The joint representations of different modalities is a robust model to analyze simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI)

Jan Cychnerski, Tomasz Dziubich, Adam Brzeski

The article presents a new multi-label comprehensive image dataset from flexible endoscopy, colonoscopy and capsule endoscopy, named ERS. The collection has been labeled according to the full medical specification of 'Minimum Standard Terminology 3.0' (MST 3.0), describing all possible findings in the gastrointestinal tract (104 possible labels), extended wi

Lukas Hahn, Johannes Walcher

Associativity of the quantum product ensures flatness of the Dubrovin connection and is the basis for Hodge-theoretic mirror symmetry of Calabi-Yau threefolds. We use ring and module structure on cohomology pertaining to a Lagrangian submanifold to define an extension of the A-model Variation of mixed Hodge structure that matches the predictions from extende

Pia Stammer, Lucas Burigo, Oliver Jäkel, Martin Frank

Fast and accurate predictions of uncertainties in the computed dose are crucial for the determination of robust treatment plans in radiation therapy. This requires the solution of particle transport problems with uncertain parameters or initial conditions. Monte Carlo methods are often used to solve transport problems especially for applications which requir

Shahab Boumi, Adan Vela

Many studies in the field of education analytics have identified student grade point averages (GPA) as an important indicator and predictor of students' final academic outcomes (graduate or halt). And while semester-to-semester fluctuations in GPA are considered normal, significant changes in academic performance may warrant more thorough investigation and c

Sam Azadi, N. D. Drummond

Variational and diffusion quantum Monte Carlo methods are employed to investigate the zero-temperature phase diagram of the three-dimensional homogeneous electron gas at very low density. Fermi fluid and body-centered cubic Wigner crystal ground state energies are determined using Slater-Jastrow-backflow and Slater-Jastrow many-body wave functions at differe

Leif Azzopardi, Mohammad Aliannejadi, Evangelos Kanoulas

Various conceptual and descriptive models of conversational search have been proposed in the literature -- while useful, they do not provide insights into how interaction between the agent and user would change in response to the costs and benefits of the different interactions. In this paper, we develop two economic models of conversational search based on

Vishwanatha M. Rao, Zihan Wan, Soroush Arabshahi, David J. Ma

Brain tissue segmentation has demonstrated great utility in quantifying MRI data through Voxel-Based Morphometry and highlighting subtle structural changes associated with various conditions within the brain. However, manual segmentation is highly labor-intensive, and automated approaches have struggled due to properties inherent to MRI acquisition, leaving

José M. Conde-Alonso, Adrián M. González-Pérez, Javier Parcet, Eduardo Tablate

We establish regularity conditions for $L_p$-boundedness of Fourier multipliers on the group von Neumann algebras of higher rank simple Lie groups. This provides a natural H\"ormander-Mikhlin criterion in terms of Lie derivatives of the symbol and a metric given by the adjoint representation. In line with Lafforgue/de la Salle's rigidity theorem, our conditi

Isabel Wagner

It is well-known that most users do not read privacy policies, but almost all users tick the box to agree with them. In this paper, we analyze the 25-year history of privacy policies using methods from transparency research, machine learning, and natural language processing. Specifically, we collect a large-scale longitudinal corpus of privacy policies from

Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund

The design of privacy mechanisms for two scenarios is studied where the private data is hidden or observable. In the first scenario, an agent observes useful data $Y$, which is correlated with private data $X$, and wants to disclose the useful information to a user. A privacy mechanism is employed to generate data $U$ that maximizes the revealed information

Chen Quan, Saikiran Bulusu, Baocheng Geng, Pramod K. Varshney

The ordered transmission (OT) scheme reduces the number of transmissions needed in the network to make the final decision, while it maintains the same probability of error as the system without using OT scheme. In this paper, we investigate the performance of the system using OT scheme in the presence of Byzantine attacks for binary hypothesis testing proble

Jae H. Lee, Sharun Kuhar, Jung-Hee Seo, Pankaj J. Pasricha

The oral route is the most common choice for drug administration because of convenience, low cost, and high patient compliance, but is also a complex route. The rate of dissolution and gastric emptying of the dissolved active pharmaceutical ingredient (API) into the duodenum is modulated by factors such as gastric motility, but current in-vitro procedures fo

Xuanhao Wang, Chenglin Shang, An Pan, Xingran Cheng

We successfully demonstrate a monolithic integrated dual-polarization (DP) IQ modulator based on thin-film lithium niobate (TFLN) platform with a silicon substrate, which consists of IQ modulators, spot-size converters (SSCs) and a polarization rotator combiner (PRC). After coupled with polarization maintaining fibers, the measured insertion loss of the modu

Malika Denis, Pi A. B. Haase, Maarten C. Mooij, Yuly Chamorro

We present an investigation of the performance of the relativistic multi-reference Fock-space coupled cluster (FSCC) method for predicting molecular hyperfine structure (HFS) constants, including a thorough computational study to estimate the associated uncertainties. In particular, we considered the $^{19}$F HFS constant in the ground and excited states of

Davis M. Welakuh, Johannes Flick, Michael Ruggenthaler, Heiko Appel

The rapid progress in quantum-optical experiments especially in the field of cavity quantum electrodynamics and nanoplasmonics, allows to substantially modify and control chemical and physical properties of atoms, molecules and solids by strongly coupling to the quantized field. Alongside such experimental advances has been the recent development of ab-initi

Hamed Dehghanpour Baruj, Iklim Yurdakul, Betul Canimkurbey, Ahmet Tarik Isik

Semiconductor colloidal quantum wells (CQWs) make an exciting quasi-2D class of nanocrystals thanks to their unique properties including their highly anisotropic optical transition dipole moment (TDM). Thus, employing a film of CQWs with face-down orientation as an emissive layer (EML) in an electroluminescent device is expected to substantially boost photon

Robert Müller, Aldo Pacchiano

We study meta-learning in Markov Decision Processes (MDP) with linear transition models in the undiscounted episodic setting. Under a task sharedness metric based on model proximity we study task families characterized by a distribution over models specified by a bias term and a variance component. We then propose BUC-MatrixRL, a version of the UC-Matrix RL

K. S. Khaw, A. Adelmann, M. Backhaus, N. Berger

The presence of a permanent electric dipole moment in an elementary particle implies Charge-Parity symmetry violation and thus could help explain the matter-antimatter asymmetry observed in our universe. Within the context of the Standard Model, the electric dipole moment of elementary particles is extremely small. However, many Standard Model extensions suc

Y. M. Bidasyuk, K. S. Kovtunenko, O. O. Prikhodko

We report on a theoretical study of a ring-shaped Bose-Einstein condensate with Raman-induced spin-orbital-angular-momentum coupling. We analyze the structure of the ground-state of the system depending different physical parameters and reveal a peculiar fine structure within the stripe phase on the phase diagram. We demonstrate the existence of the predicte

Vincent Boudart, Maxime Fays

Minute-long Gravitational Wave (GW) transients are events lasting from few to hundreds of seconds. In opposition to compact binary mergers, their GW signals cover a wide range of poorly understood astrophysical phenomena such as accretion disk instabilities and magnetar flares. The lack of accurate and rapidly generated gravitational-wave emission models pre

G. A. Carvalho, R. Lobato, P. H. R. S. Moraes, D. Deb

This work analyses the hydrostatic equilibrium configurations of strange stars in a non-minimal geometry-matter coupling (GMC) theory of gravity. Those stars are made of strange quark matter, whose distribution is governed by the MIT equation of state. The non-minimal GMC theory is described by the following gravitational action: $f(R,L)=R/2+L+\sigma RL$, wh

Laura N. Casses, Korbinian J. Kaltenecker, Sanshui Xiao, Martijn Wubs

The subwavelength confinement of surface plasmon polaritons (SPPs) makes them attractive for various applications such as sensing, light generation and solar energy conversion. Near-field microscopy associated with interferometric detection allows to visualize both the amplitude and phase of SPPs. However, their full quantitative characterization in a reflec

Olivier Poisson

We consider an inverse boundary value problem for the heat equation with a nonsmooth coefficient of conductivity which models the displacement of a moving body inside a nonhomogeneous background. We prove the uniqueness of the moving inclusion from the knowledge of the Dirichlet-to-Neumann operator by using a dynamical probe method.

Gabriella Kazai, Bhaskar Mitra, Anlei Dong, Nick Craswell

Traditional information retrieval (IR) ranking models process the full text of documents. Newer models based on Transformers, however, would incur a high computational cost when processing long texts, so typically use only snippets from the document instead. The model's input based on a document's URL, title, and snippet (UTS) is akin to the summaries that a

Nandor Verba, Pablo Baldivieso-Monasterios, Siyuan Dong, Andrei Braitor

Adding renewable energy sources and storage units to an electric grid has led to a change in the way energy is generated and billed. This shift cannot be managed without a unified view of energy systems and their components. This unified view is captured within the idea of a Smart Local Energy System (SLES). Currently, various isolated control and market ele

Anthony Bonato, Ryan Cushman, Trent G. Marbach

We provide new constructions of Meyniel extremal graphs, which are families of graphs with the conjectured largest asymptotic cop number. Using spanning subgraphs, we prove that there are an exponential number of new Meyniel extremal families with specified degrees. Using a linear programming problem on hypergraphs, we explore the degrees in families that ar

Hajar Hasannejadasl, Cheryl Roumen, Yolba Smit, Andre Dekker

Given the impact of health literacy (HL) on patients outcomes, limited health literacy (LHL) is a major barrier in cancer care globally. HL refers to the degree in which an individual is able to acquire, process and comprehend information in a way to be actively involved in their health decisions. Previous research found that almost half of the population in

Sakdipat Ontoum, Jonathan H. Chan

The term personality may be expressed in terms of the individual differences in characteristics pattern of thinking, feeling, and behavior. This work presents several machine learning techniques including Naive Bayes, Support Vector Machines, and Recurrent Neural Networks to predict people personality from text based on Myers-Briggs Type Indicator (MBTI). Fu

M. Marras, S. Vernier-Piro, T. Yokota

In this paper we consider nonnegative solutions of the following parabolic-elliptic cross-diffusion system \begin{equation*} \left\{ \begin{array}{l} \begin{aligned} &u_t = \Delta u - \nabla(u f(|\nabla v|^2 )\nabla v), \\[6pt] &0= \Delta v -\mu + u , \quad \int_{\Omega}v =0, \ \ \mu := \frac 1 {|\Omega|} \int_{\Omega} u dx, \\[6pt] &u(x,0)= u_0(x), \end{ali

Achintya Priydarshi, Yogesh Singh Chauhan, Somnath Bhowmick, Amit Agarwal

2D Ferroelectric materials are promising for designing low-dimensional memory devices. Here, we explore strain tunable ferroelectric properties of group-IV monochalcogenides MX (M=Ge, Sn; X=S, Se) and their potential application in lateral field tunnel junction devices. We find that these monolayers have in-plane ferroelectricity, with their ferroelectric pa

Ioana Ciotir, Dan Goreac, Ionut Munteanu

We aim at providing a characterization of the ability to maintain a stochastic coupled system with porous media components in a prescribed set of constraints by using internal controls. This property is proven via a quasi-tangency local-in-time condition in the spirit of Euler approximation schemes. In particular, by employing one of the components of the sy

Jonas Wacker, Motonobu Kanagawa, Maurizio Filippone

Dot product kernels, such as polynomial and exponential (softmax) kernels, are among the most widely used kernels in machine learning, as they enable modeling the interactions between input features, which is crucial in applications like computer vision, natural language processing, and recommender systems. We make several novel contributions for improving t

Jason Hirtz, Alain Letourneau, Loïc Thulliez, Angel Ibarra

The IFMIF-DONES facility will be dedicated to the irradiation of structural materials planned for the use in future fusion reactors such as DEMO (Demonstration Fusion Power Plant). The potentialities of the IFMIF-DONES facility to complement its principal purpose by other experiments that would open the facility to other communities is addressed in this work

J. Hartke, M. Arnaboldi, O. Gerhard, L. Coccato

M105 is an early-type galaxy in the nearby Leo I group, the closest galaxy group to contain all galaxy types and therefore an excellent environment to explore the low-mass end of intra-group light (IGL) assembly. We present a new extended kinematic survey of planetary nebulae (PNe) in M105 and the surrounding 30'x30' in the Leo I group with the Planetary Neb

Shohini Bhattacharya, Renaud Boussarie, Yoshitaka Hatta

We propose a novel observable for the experimental detection of the gluon orbital angular momentum (OAM) that constitutes the proton spin sum rule. We consider longitudinal double spin asymmetry in exclusive dijet production in electron-proton scattering and demonstrate that the $\cos \phi$ azimuthal angle correlation between the scattered electron and proto

D. S. M. Alencar, T. F. A. Alves, G. A. Alves, R. S. Ferreira

We show results for the contact process on Barabasi networks. The contact process is a model for an epidemic spreading without permanent immunity that has an absorbing state. For finite lattices, the absorbing state is the true stationary state, which leads to the need for simulation of quasi-stationary states, which we did in two ways: reactivation by inser

G. G. Plunk, Per Helander

We introduce modes of instantaneous optimal growth of free energy for the fully electromagnetic gyrokinetic equations. We demonstrate how these "optimal modes" arise naturally from the free energy balance equation, allowing its convenient decomposition, and yielding a simple picture of energy flows. Optimal modes have a number of other favorable features, su

Poulami Somanya Ganguly, Felix Lucka, Holger Kohr, Erik Franken

Tilt-series alignment is crucial to obtaining high-resolution reconstructions in cryo-electron tomography. Beam-induced local deformation of the sample is hard to estimate from the low-contrast sample alone, and often requires fiducial gold bead markers. The state-of-the-art approach for deformation estimation uses (semi-)manually labelled marker locations i

Salvatore Capozziello, Carlo Alberto Mantica, Luca Guido Molinari

A main issue in cosmology and astrophysics is whether the dark sector phenomenology originates from particle physics, then requiring the detection of new fundamental components, or it can be addressed by modifying General Relativity. Extended Theories of Gravity are possible candidates aimed in framing dark energy and dark matter in a comprehensive geometric

Aryeh Kontorovich, Menachem Sadigurschi, Uri Stemmer

The vast majority of the work on adaptive data analysis focuses on the case where the samples in the dataset are independent. Several approaches and tools have been successfully applied in this context, such as differential privacy, max-information, compression arguments, and more. The situation is far less well-understood without the independence assumption

N. Mohan Kumar, Poornapushkala Narayanan, A. J. Parameswaran

In this article, we prove that any smooth projective variety $X$ which is a double cover of the projective space $\mathbb{P}^n$ ($n\geq 2$) admits an Ulrich bundle. When $n=2$, we show that on any such $X$, there is an Ulrich bundle of rank two.

Qianben Chen, Richong Zhang, Yaowei Zheng, Yongyi Mao

Contrastive learning has achieved remarkable success in representation learning via self-supervision in unsupervised settings. However, effectively adapting contrastive learning to supervised learning tasks remains as a challenge in practice. In this work, we introduce a dual contrastive learning (DualCL) framework that simultaneously learns the features of

Martin Westerkamp, Axel Küpper

Cross-Blockchain communication has gained traction due to the increasing fragmentation of blockchain networks and scalability solutions such as side-chaining and sharding. With SmartSync, we propose a novel concept for cross-blockchain smart contract interactions that creates client contracts on arbitrary blockchain networks supporting the same execution env

Kabir Chakravarti, Rajes Ghosh, Sudipta Sarkar

Recent gravitational wave observation based on the data from GW150914 has confirmed Hawking's area theorem and estimated the increase in total horizon area during a merger process of two Kerr black holes. We use this result and the validity of the second law to obtain the first observational bound on the 4D topological Gauss-Bonnet coupling as $\gamma \lesss

Ángel González-Prieto, Márton Hablicsek, Jesse Vogel

In this paper, we extend the Topological Quantum Field Theory developed by Gonz\'alez-Prieto, Logares, and Mu\~noz for computing virtual classes of $G$-representation varieties of closed orientable surfaces in the Grothendieck ring of varieties to the setting of the character stacks. To this aim, we define a suitable Grothendieck ring of representable stacks

Zhou Yang, Jieke Shi, Junda He, David Lo

Pre-trained models of code have achieved success in many important software engineering tasks. However, these powerful models are vulnerable to adversarial attacks that slightly perturb model inputs to make a victim model produce wrong outputs. Current works mainly attack models of code with examples that preserve operational program semantics but ignore a f

Jana Lasser, Timotheus Hell, David Garcia

Returning universities to full on-campus operations while the COVID-19 pandemic is ongoing has been a controversial discussion in many countries. The risk of large outbreaks in dense course settings is contrasted by the benefits of in-person teaching. Transmission risk depends on a range of parameters, such as vaccination coverage and efficacy, number of con