March 2023 arXiv papers — page 69

Harishchandra Dubey, Ashkan Aazami, Vishak Gopal, Babak Naderi

Deep Speech Enhancement Challenge is the 5th edition of deep noise suppression (DNS) challenges organized at ICASSP 2023 Signal Processing Grand Challenges. DNS challenges were organized during 2019-2023 to stimulate research in deep speech enhancement (DSE). Previous DNS challenges were organized at INTERSPEECH 2020, ICASSP 2021, INTERSPEECH 2021, and ICASS

Alberto Accardi, Xiaoxian Jing, Joseph Francis Owens, Sanghwa Park

We present a new parton distribution function analysis which includes new data for W boson production in proton-proton collisions and lepton pair production in proton-proton and proton-deuteron collisions. The new data provide strong constraints on the light antiquark parton distribution functions in the proton. We identify an interesting correlation between

Julius Schöning, Clemens Westerkamp

Artificial intelligence (AI) and human-machine interaction (HMI) are two keywords that usually do not fit embedded applications. Within the steps needed before applying AI to solve a specific task, HMI is usually missing during the AI architecture design and the training of an AI model. The human-in-the-loop concept is prevalent in all other steps of develop

Qi Xu, Haoda Fu, Annie Qu

The individualized treatment rule (ITR), which recommends an optimal treatment based on individual characteristics, has drawn considerable interest from many areas such as precision medicine, personalized education, and personalized marketing. Existing ITR estimation methods mainly adopt one of two or more treatments. However, a combination of multiple treat

Giorgos Eleftheriou

The Schur index of a $4$ dimensional $\mathcal{N}=2$ superconformal field theory counts (with sign) bosonic and fermionic states that preserve $4$ supercharges. We consider the Schur indices of $4$d $\mathcal{N}=4$ super Yang-Mills and $\mathcal{N}=2$ circular quiver gauge theories with gauge groups $U(N)$ or $SU(N)$. We calculate the exponentially dominant

J. Guo, V. Dugaev, A. Ernst, G. Yumnam

Vortex magnetic structure in artificial honeycomb lattice provides a unique platform to explore emergent properties due to the additional Berry phase curvature imparted by chiral magnetization to circulating electrons via direct interaction. We argue that while the perpendicularly-aligned magnetic component leads to the quantized flux of monopole at the cent

Vladimir I. Komarov

The problem of the structure of nucleons and their interaction in the concept of nonperturbative QCD is discussed as an approach to studying the transformation of current quarks into constituent ones and the search for the mechanism of such a transformation, creating the bulk of the nucleon mass. Attention is drawn to the possibilities offered by studying ce

Tyler A. Chang, Benjamin K. Bergen

Transformer language models have received widespread public attention, yet their generated text is often surprising even to NLP researchers. In this survey, we discuss over 250 recent studies of English language model behavior before task-specific fine-tuning. Language models possess basic capabilities in syntax, semantics, pragmatics, world knowledge, and r

Leyou Xu, Bo Zhou

Ahanjideh, Akbari, Fakharan and Trevisan proposed a conjecture in [Linear Algebra Appl. 632 (2022) 1--14] on the distribution of the Laplacian eigenvalues of graphs: for any connected graph of order $n$ with diameter $d\ge 2$ that is not a path, the number of Laplacian eigenvalues in the interval $[n-d+2,n]$ is at most $n-d$. We show that the conjecture is t

Ayan Kumar Bhunia, Subhadeep Koley, Amandeep Kumar, Aneeshan Sain

Human sketch has already proved its worth in various visual understanding tasks (e.g., retrieval, segmentation, image-captioning, etc). In this paper, we reveal a new trait of sketches - that they are also salient. This is intuitive as sketching is a natural attentive process at its core. More specifically, we aim to study how sketches can be used as a weak

Vangelis Kostoulas, Peter A. N. Bosman, Tanja Alderliesten

Segmentation of regions of interest in images of patients, is a crucial step in many medical procedures. Deep neural networks have proven to be particularly adept at this task. However, a key question is what type of deep neural network to choose, and whether making a certain choice makes a difference. In this work, we will answer this question for the task

Wiliam S. Oliveira, Thereza Paiva, Richard T. Scalettar, Natanael C. Costa

Heavy fermion materials are compounds in which localized $f$-orbitals hybridize with delocalized $d$ ones, leading to quasiparticles with large renormalized masses. The presence of strongly correlated $f$-electrons at the Fermi level may also lead to long-range order, such as magnetism, or unconventional superconductivity. From a theoretical point of view, t

Hafida Massit, Mohamed Rossafi, Samir Kabbaj

In this present paper we introduce weaving Hilbert space frames in the continuous case, we give new approaches for manufacturing pairs of woven continuous frames and we obtain new properties in continuous weaving frame theory related to dual frames. Also, we provide some approaches for constructing weaving continuous frames by using small perturbations.

Raveesh Garg, Michael Pellauer, Sivasankaran Rajamanickam, Tushar Krishna

Tensor algebra accelerators have been gaining popularity for running high-performance computing (HPC) workloads. Identifying optimal schedules for individual tensor operations and designing hardware to run these schedules is an active area of research. Unfortunately, operators in HPC workloads such as Conjugate Gradient often have operators with skewed shape

Rick Salmon, Nick Pizzo

Equilibrium statistical mechanics predicts that inviscid, two-dimensional, incompressible flow on the sphere eventually reaches a state in which spherical harmonic modes of degrees $n=1$ and $n=2$ hold all the energy. By a separate theory, such flow is static in a reference frame rotating at angular speed $2\Omega/3$ with respect to the inertial frame. The v

J. E. Norris, D. Yong, A. Frebel, S. G. Ryan

We investigate the distribution of the lithium abundances, A(Li), of metal-poor dwarf and subgiant stars within the limits 5500 K < Teff < 6700 K, -6.0 < [Fe/H] < -1.5, and logg > ~3.5 (a superset of parameters first adopted by Spite and Spite), using literature data for some 200 stars. We address the problem of the several methods that yield Teff difference

Avner Peleg, Debananda Chakraborty

We demonstrate transmission stabilization against radiation emission by frequency-dependent linear gain-loss and perturbation-induced frequency shifting for solitons of the cubic-quintic nonlinear Schr\"odinger (CQNLS) equation. We consider soliton propagation in a nonlinear optical waveguide with focusing cubic nonlinearity, defocusing quintic nonlinearity,

Kenny Wiratama, Kenneth Duru, Stephen Roberts, Christopher Zoppou

We derive well-posed boundary conditions for the linearized Serre equations in one spatial dimension by utilizing the energy method. An energy stable and conservative discontinuous Galerkin spectral element method with simple upwind numerical fluxes is proposed for solving the initial boundary value problem. We derive discrete energy estimates for the numeri

Patricia Suriana, Joseph M. Paggi, Ron O. Dror

Most widely used ligand docking methods assume a rigid protein structure. This leads to problems when the structure of the target protein deforms upon ligand binding. In particular, the ligand's true binding pose is often scored very unfavorably due to apparent clashes between ligand and protein atoms, which lead to extremely high values of the calculated va

Cristina Ballantine, George Beck

The Fibonacci numbers are the prototypical example of a recursive sequence, but grow too quickly to enumerate sets of integer partitions. The same is true for the other classical sequences $a(n)$ defined by Fibonacci-like recursions: the tribonacci, Padovan, Pell, Narayana's cows, and Lucas sequences. For each sequence $a(n)$, however, we can define a relate

Doğanalp Ergenç, Robin Schenderlein, Mathias Fischer

IEEE 802.1 Time-sensitive Networking~(TSN) standards are envisioned to replace legacy network protocols in critical domains to ensure reliable and deterministic communication over off-the-shelf Ethernet equipment. However, they lack security countermeasures and can even impose new attack vectors that may lead to hazardous consequences. This paper presents th

Ziwen Huang, Yunwei Lu, Anna Grassellino, Alexander Romanenko

Accurate modeling of decoherence errors in quantum processors is crucial for analyzing and improving gate fidelities. To increase the accuracy beyond that of the Lindblad dynamical map, several generalizations have been proposed, and the exploration of simpler and more systematic frameworks is still ongoing. In this paper, we introduce a decoherence model ba

Jared Miller, Mario Sznaier

Peak estimation of hybrid systems aims to upper bound extreme values of a state function along trajectories, where this state function could be different in each subsystem. This finite-dimensional but nonconvex problem may be lifted into an infinite-dimensional linear program (LP) in occupation measures with an equal objective under mild finiteness/compactne

Jaap Eising, Shenyu Liu, Sonia Martinez, Jorge Cortes

This paper considers the stabilization of unknown switched linear systems using data. Instead of a full system model, we have access to a finite number of trajectories of each of the different modes prior to the online operation of the system. On the basis of informative enough measurements, formally characterized in terms of linear matrix inequalities, we d

Junhan Chen, Joseph Subotnik

In order to study electron-transfer mediated chemical processes on a metal surface, one requires not one but two potential energy surfaces (one ground state and one excited state) as in Marcus theory. In this letter, we report that a novel, dynamically-weighted, state-averaged constrained CASSCF(2,2) (DW-SA-cCASSCF(2,2)) can produce such surfaces for the And

Fangzhou Cai, Dominik Kwietniak, Jian Li, Habibeh Pourmand

Given a topological dynamical system $(X,T)$, we study properties of the mean orbital pseudo-metric $\bar E$ defined by \[ \bar E(x,y)= \limsup_{n\to\infty } \min_{\sigma\in S_n}\frac{1}{n}\sum_{k=0}^{n-1}d(T^k(x),T^{\sigma(k)}(y)), \] where $x,y\in X$ and $S_n$ is the permutation group of $\{0,1,\ldots,n-1\}$. Let $\hat\omega_T(x)$ denote the set of measure

Eric Thoma

We prove existence of infinite volume $d$-dimensional Coulomb gases which are not number rigid for $d \geq 3$. This makes the Coulomb gas the Gibbs point process with the longest range pairwise interaction (i.e.\ with the smallest $s$ in the interaction kernel $g(x) = |x|^{-s}$) for which number non-rigidity has been proved in $d \geq 3$. We rule out propert

Igor Bandos, Kurt Lechner, Dmitri Sorokin, Paul K. Townsend

The Hamiltonian formulation for nonlinear chiral 2-form electrodynamics in six-dimensional Minkowski spacetime is used to show that small-amplitude plane-wave perturbations of a generic uniform constant `magnetic' background exhibit trirefringence: all three independent wave-polarisations have distinct dispersion relations. While two coincide for Lorentz inv

Matteo Piccolini, Vittorio Giovannetti, Rosario Lo Franco

We introduce a theoretical scheme to prepare a pure Bell singlet state of two bosonic qubits, in a way that is robust under the action of arbitrary local noise. Focusing on a photonic platform, the proposed procedure employs passive optical devices and a polarization-insensitive, non-absorbing, parity check detector in an iterative process which achieves det

Eric Yeh, Briland Hitaj, Vidyasagar Sadhu, Anirban Roy

The recent explosion of high-quality image-to-image methods has prompted interest in applying image-to-image methods towards artistic and design tasks. Of interest for architects is to use these methods to generate design proposals from conceptual sketches, usually hand-drawn sketches that are quickly developed and can embody a design intent. More specifical

Yury A. Neretin

We show that the group of all homeomorphisms of the Basilica fractal coincides with a group of transformations of a certain non-locally finite ribbon tree. Also, we show that Basilica Thompson group defined by Belk and Forrest is dense in the group of all orientation preserving homeomorphisms of the Basilica.

Alberto Verjovsky, Adrian Zenteno

In a series of papers, published in Mathematische Annalen, Bianchi and Blumenthal introduced the notions of Bianchi orbifolds and Hilbert-Blumnethal surfaces as generalizations of modular curves associated to quadratic fields. In this paper, in the same spirit, and following a similar line of reasoning, we introduce the concept of Bianchi and Hilbert-Blument

Martin T. Brolly

Using a probabilistic neural network and Lagrangian observations from the Global Drifter Program, we model the single particle transition probability density function (pdf) of ocean surface drifters. The transition pdf is represented by a Gaussian mixture whose parameters (weights, means and covariances) are continuous functions of latitude and longitude det

Jarrod Hollis, Raviv Raich, Jinsub Kim, Barak Fishbain

The problem of foreground material signature extraction in an intimate (nonlinear) mixing setting is considered. It is possible for a foreground material signature to appear in combination with multiple background material signatures. We explore a framework for foreground material signature extraction based on a patch model that accounts for such background

Daniel Suarez, Elisabet Mas de les Valls, Lluis Batet

In recent years, several simulation codes for reproducing liquid metal magnetohydrodynamic (MHD) phenomena have been validated and benchmarked. Accurate simulation codes are crucial to enhance our understanding of how flow behavior affects heat transport in liquid metal-based breeding blankets. Using heat transfer correlations, that model the influence of fl

Aman Shrivastava, P. Thomas Fletcher

In recent years, computational pathology has seen tremendous progress driven by deep learning methods in segmentation and classification tasks aiding prognostic and diagnostic settings. Nuclei segmentation, for instance, is an important task for diagnosing different cancers. However, training deep learning models for nuclei segmentation requires large amount

Anne Theurkauf, Justin Kottinger, Nisar Ahmed, Morteza Lahijanian

We consider a chance-constrained multi-robot motion planning problem in the presence of Gaussian motion and sensor noise. Our proposed algorithm, CC-K-CBS, leverages the scalability of kinodynamic conflict-based search (K-CBS) in conjunction with the efficiency of the Gaussian belief trees used in the Belief-A framework, and inherits the completeness guarant

Andrea Civilini, Onkar Sadekar, Federico Battiston, Jesús Gómez-Gardeñes

Understanding how cooperative behaviours can emerge from competitive interactions is an open problem in biology and social sciences. While interactions are usually modelled as pairwise networks, the units of many real-world systems can also interact in groups of three or more. Here, we introduce a general framework to extend pairwise games to higher-order ne

Nicolas Dutertre, Vincent Grandjean

Fix an o-minimal structure expanding the ordered field of real numbers. Let $(W_y)_{y\in\mathbb{R}^s}$ be a definable family of closed subsets of $\mathbb{R}^n$ whose total space $W = \cup_y W_y\times y$ is a closed connected $C^2$ definable sub-manifold of $\mathbb{R}^n\times\mathbb{R}^s$. Let $\varphi:W \to\mathbb{R}^s$ be the restriction of the projection

Berivan Isik, Onur G. Guleryuz, Danhang Tang, Jonathan Taylor

We propose sandwiched video compression -- a video compression system that wraps neural networks around a standard video codec. The sandwich framework consists of a neural pre- and post-processor with a standard video codec between them. The networks are trained jointly to optimize a rate-distortion loss function with the goal of significantly improving over

Cedric Westphal, Alexander Clemm

Reducing energy consumption - and especially carbon emissions - is one of the most important challenges facing humankind. ICT (Information and Communication Technology) is a powerful tool to reduce emissions as it offers alternatives to activities that are costly in energy: video streaming saves energy vs driving to a movie theater, for instance. Still, the

Norbert Ankri, Païkan Marcaggi

The unit value of a commodity that Michio Morishima's method and its variations enable to determine correctly, is the sum of the value of the commodities it contains (inputs) and the quantity of labor required for its production. However, goods are sold at their price of production only when they meet a solvent social need that involves the entire economy wi

Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang

The huge supporting training data on the Internet has been a key factor in the success of deep learning models. However, this abundance of public-available data also raises concerns about the unauthorized exploitation of datasets for commercial purposes, which is forbidden by dataset licenses. In this paper, we propose a backdoor-based watermarking approach

Gianluca Bianchin

The exact pole placement problem concerns computing a feedback gain that will assign the poles of a system, controlled via static state feedback, at a set of pre-specified locations. This is a classic problem in feedback control and numerous methodologies have been proposed in the literature for cases where a model of the system to control is available. In t

Giacomo Hermes Ferraro

In the setting of a Drinfeld module $\phi$ over a curve $X/\mathbb{F}_q$, we use a functorial point of view to define $\textit{Anderson eigenvectors}$, a generalization of the so called "special functions" introduced by Angl\`es, Ngo Dac and Tavares Ribeiro, and prove the existence of a universal object $\omega_\phi$. We adopt an analogous approach with the

Sanjay Lall, Calin Cascaval, Martin Izzard, Tammo Spalink

We discuss distributed reframing control of bittide systems. In a bittide system, multiple processors synchronize by monitoring communication over the network. The processors remain in logical synchrony by controlling the timing of frame transmissions. The protocol for doing this relies upon an underlying dynamic control system, where each node makes only lo

Arsen Hambardzumyan, Levon Muradyan

An edge-coloring of a graph $G$ with colors $1,\ldots,t$ is called an \emph{interval $t$-coloring} if all colors are used and the colors of edges incident to each vertex of $G$ are distinct and form an interval of integers. In 1990, Kamalian proved that if a graph $G$ with at least one edge has an interval $t$-coloring, then $t\leq 2|V(G)|-3$. In 2002, Axeno

Kenneth Goodenough, Sébastian de Bone, Vaishnavi L. Addala, Stefan Krastanov

Noisy hardware forms one of the main hurdles to the realization of a near-term quantum internet. Distillation protocols allows one to overcome this noise at the cost of an increased overhead. We consider here an experimentally relevant class of distillation protocols, which distill $n$ to $k$ end-to-end entangled pairs using bilocal Clifford operations, a si

Sinan G. Aksoy, Ryan Bennink, Yuzhou Chen, José Frías

We present and discuss seven different open problems in applied combinatorics. The application areas relevant to this compilation include quantum computing, algorithmic differentiation, topological data analysis, iterative methods, hypergraph cut algorithms, and power systems.

Sergio Martín Serrano, Rubén Izquierdo, Iván García Daza, Miguel Ángel Sotelo

This paper presents the results of tests of interactions between real humans and simulated vehicles in a virtual scenario. Human activity is inserted into the virtual world via a virtual reality interface for pedestrians. The autonomous vehicle is equipped with a virtual Human-Machine interface (HMI) and drives through the digital twin of a real crosswalk. T

Lars van der Laan, Peter B. Gilbert

We develop semiparametric methods for estimating subgroup-specific relative vaccine efficacy against multiple viral strains in a partially vaccinated population. Focusing on observational case-only studies, we address informative missingness in strain type due to vaccination status, pre-vaccination characteristics, and post-infection factors such as viral lo

Alexander N. Manashov

We prove the unitarity of the separation of variables transform for $\mathrm{SL}(2,\mathbb C)$ spin chains by a method based on the use of Gustafson integrals.

Marc Suñé, Cristóbal Arratia, A. F. Bonfils, Dominic Vella

We examine the buckling shape and critical compression of confined inhomogeneous composite sheets lying on a liquid foundation. The buckling modes are controlled by the bending stiffness of the sheet, the density of the substrate, and the size and the spatially dependent elastic coefficients of the sheet. We solve the (linearized) F\"oppl-von K\'arm\'an equa

O. Deniz Kose, Yanning Shen, Gonzalo Mateos

Graphs are mathematical tools that can be used to represent complex real-world systems, such as financial markets and social networks. Hence, machine learning (ML) over graphs has attracted significant attention recently. However, it has been demonstrated that ML over graphs amplifies the already existing bias towards certain under-represented groups in vari

Gabriela D. Martinez, Chao Li, Alexander Staron, John Kitching

Atomic beams are a longstanding technology for atom-based sensors and clocks with widespread use in commercial frequency standards. Here, we report the demonstration a chip-scale microwave atomic beam clock using coherent population trapping (CPT) interrogation in a passively pumped atomic beam device. The beam device consists of a hermetically sealed vacuum

Sara Oughourli, Manshi Limbu, Zechen Hu, Xuan Wang

This paper studies a team coordination problem in a graph environment. Specifically, we incorporate "support" action which an agent can take to reduce the cost for its teammate to traverse some edges that have higher costs otherwise. Due to this added feature, the graph traversal is no longer a standard multi-agent path planning problem. To solve this new pr

Bendegúz Sulyok, Gergely Palla

Finding the optimal embedding of networks into low-dimensional hyperbolic spaces is a challenge that received considerable interest in recent years, with several different approaches proposed in the literature. In general, these methods take advantage of the exponentially growing volume of the hyperbolic space as a function of the radius from the origin, all

Kevin Jesse, Toufique Ahmed, Premkumar T. Devanbu, Emily Morgan

With the advent of powerful neural language models, AI-based systems to assist developers in coding tasks are becoming widely available; Copilot is one such system. Copilot uses Codex, a large language model (LLM), to complete code conditioned on a preceding "prompt". Codex, however, is trained on public GitHub repositories, viz., on code that may include bu

Jakob Heiss, Josef Teichmann, Hanna Wutte

Randomized neural networks (randomized NNs), where only the terminal layer's weights are optimized constitute a powerful model class to reduce computational time in training the neural network model. At the same time, these models generalize surprisingly well in various regression and classification tasks. In this paper, we give an exact macroscopic characte

Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran

Pruning schemes have been widely used in practice to reduce the complexity of trained models with a massive number of parameters. In fact, several practical studies have shown that if a pruned model is fine-tuned with some gradient-based updates it generalizes well to new samples. Although the above pipeline, which we refer to as pruning + fine-tuning, has b

Uri Abraham, Robert Bonnet, Mirna Džamonja, Maurice Pouzet

The following is a 2008 conjecture of Abraham, Bonnet and Kubi\'s: [ABK Conjecture] Every well quasi order (wqo) is a countable union of better quasi orders (bqo). We obtain a partial progress on the conjecture, by showing that the class of orders that are a countable union of better quasi orders (sigma-bqo) is closed under various operations. These include

Alice Di Tucci

The very early universe is understood in terms of quantum field theories on curved spacetime, where the classical background spacetime is typically an FLRW cosmology and the quantum fields which propagate on it include gravitational waves and energy density fluctuations. Many open questions seem to relate to the fact that we very little understand this regim

Dalia Ortiz Pablo, Sushruth Badri, Erik Norén, Christoph Nötzli

A major problem with using automated classification systems is that if they are not engineered correctly and with fairness considerations, they could be detrimental to certain populations. Furthermore, while engineers have developed cutting-edge technologies for image classification, there is still a gap in the application of these models in human heritage c

Jimmy Aronsson, David I. Müller, Daniel Schuh

Lattice gauge equivariant convolutional neural networks (L-CNNs) are a framework for convolutional neural networks that can be applied to non-Abelian lattice gauge theories without violating gauge symmetry. We demonstrate how L-CNNs can be equipped with global group equivariance. This allows us to extend the formulation to be equivariant not just under trans

Shanti Bhushan, Greg W. Burgreen, Wesley Brewer, Ian D. Dettwiller

A machine-learned (ML) model is developed to enhance the accuracy of turbulence transport equations of Reynolds Averaged Navier Stokes (RANS) solver and applied for periodic hill test case, which involves complex flow regimes, such as attached boundary layer, shear-layer, and separation and reattachment. The accuracy of the model is investigated in extrapola

Eric Brussel, Madeleine E. Goertz

We prove the 2-torus $\mathbb T$, an abelian linear algebraic group, is a fine moduli space of labeled, oriented, possibly-degenerate inscribable similarity classes of triangles, where a triangle is {\it inscribable} if it can be inscribed in a circle. A natural action by the dihedral group $D_6$ defines a quotient stack $[\mathbb T/D_6]$, which is the stack

Štěpán Starosta

We present a formalization of basics related to infinite words in the generic proof assistant Isabelle/HOL. Furthermore, we present a formalization of purely morphic and morphic languages. Finally, we present a formalized definition of Sturmian words as lower mechanical words and prove some very elementary facts. The formalization is based on an ongoing larg

Salma Ichekhlef, Étienne Villemure, Shokoufeh Naderi, François Ferland

Localization plays a critical role in the field of distributed swarm robotics. Previous work has highlighted the potential of relative localization for position tracking in multi-robot systems. Ultra-wideband (UWB) technology provides a good estimation of the relative position between robots but suffers from some limitations. This paper proposes improving th

Monicka Kullappan, Wes Patel, Manoj K. Chaudhury

Micro and/or Nano sized emulsions are formed when an organic liquid gently comes in contact with water in the presence of a surfactant, where no external agitation is required. Many years of research made it clear that the driving force for spontaneous emulsification arises from the differences of the chemical potentials of various components in the organic

C. Buttitta, E. M. Corsini, J. A. L. Aguerri, L. Coccato

We investigate the link between the bar rotation rate and dark matter content in barred galaxies by concentrating on the cases of the lenticular galaxies NGC4264 and NGC4277. These two gas-poor galaxies have similar morphologies, sizes, and luminosities. But, NGC4264 hosts a fast bar, which extends to nearly the corotation, while the bar embedded in NGC4277

Vladimir Kozlov

Steady surface waves in a two-dimensional channel are considered. We study bifurcations, which occur on a branch of Stokes water waves starting from a uniform stream solution. Two types of bifurcations are considered: bifurcations in the class of Stokes waves (Stokes bifurcation) and bifurcations in a class of periodic waves with the period M times the perio

Valentina Franceschi, Roberto Monti, Alessandro Socionovo

We prove (sub)mean value formulas at the point $0\in\Sigma$ for (sub)harmonic functions a on a hypersurface $\Sigma\subset\mathbb{R}^{n+1}$ where the differentiable structure and the surface measure depend on the ambient Grushin structure.

Khulood Al-sakkaf, Monicka Kullappan, Manoj K. Chaudhury

Recent studies demonstrated that an elastomer containing hygroscopic inclusions absorbs moisture and swell. Here we show that a thin film of such an elastomer bonded to a rigid substrate undergoes morphological instability upon absorption of water, the wavelength of which increases linearly with its thickness. As the driving force for such a morphological in

Sifatkaur Dhingra, Manmeet Singh, Vaisakh SB, Neetiraj Malviya

Cognitive psychology delves on understanding perception, attention, memory, language, problem-solving, decision-making, and reasoning. Large language models (LLMs) are emerging as potent tools increasingly capable of performing human-level tasks. The recent development in the form of GPT-4 and its demonstrated success in tasks complex to humans exam and comp

Mauricio Delbracio, Peyman Milanfar

Inversion by Direct Iteration (InDI) is a new formulation for supervised image restoration that avoids the so-called "regression to the mean" effect and produces more realistic and detailed images than existing regression-based methods. It does this by gradually improving image quality in small steps, similar to generative denoising diffusion models. Image r

H. Nazar, M. Azam, G. Abbas, R. Ahmed

In this paper, we have introduced new viable solutions of Einstein-Maxwell field equations by incorporating the features of anisotropic matter distribution in the realm of General theory of Relativity ($GR$). For this procurement, we have employed a Finch-Skea spacetime along with a generalized polytropic equation of state ($EoS$). We have constructed variou

Partho Ghosh, Md. Aynal Haque

The discovery of novel drug target (DT) interactions is an important step in the drug development process. The majority of computer techniques for predicting DT interactions have focused on binary classification, with the goal of determining whether or not a DT pair interacts. Protein ligand interactions, on the other hand, assume a continuous range of bindi

Azmy S. Ackleh, Rainey Lyons, Nicolas Saintier

In this paper we develop explicit and semi-implicit second-order high-resolution finite difference schemes for a structured coagulation-fragmentation model formulated on the space of Radon measures. We prove the convergence of each of the two schemes to the unique weak solution of the model. We perform numerical simulations to demonstrate that the second ord

Rishabh Jha, Jan C. Louw

It is known that the large-$q$ complex Sachdev-Ye-Kitaev (SYK) dot thermalizes instantaneously under rather general dynamical protocols. We consider a lattice of such dots coupled together, allowing for $r/2$ body hopping of particles between nearest neighbors. We develop a rather general analytical framework to study the dynamics to leading order in $1/q$ o

Ivan Chajda, Helmut Länger

Effect algebras were introduced in order to describe the structure of effects, i.e. events in quantum mechanics. They are partial algebras describing the logic behind the corresponding events. It is natural to ask how to introduce the logical connective implication in effect algebras. For lattice-ordered effect algebras this task was already solved by severa

Matteo Barbetti

About 90% of the computing resources available to the LHCb experiment has been spent to produce simulated data samples for Run 2 of the Large Hadron Collider at CERN. The upgraded LHCb detector will be able to collect larger data samples, requiring many more simulated events to analyze the data to be collected in Run 3. Simulation is a key necessity of analy

Nikolaos Kolliopoulos, Martin Larsson, Zeyu Zhang

We study the asymptotics of the point process induced by an interacting particle system with mean-field drift interaction. Under suitable assumptions, we establish propagation of chaos for this point process: it has the same weak limit as the point process induced by i.i.d. copies of the solution of a limiting Mckean--Vlasov equation. This weak limit is a Po

G. Abbas, R. H. Ali

This paper deals with the thermodynamical properties of black hole formulated in Einstein theory of relativity and associated with a nonlinear electromagnetic field. The transition of the black hole is analyzed using the parameters mass, electric charge, coupling constant, and cosmological constant. We find-out the thermodynamical aspects of exact black hole

Jixuan Zhi, Jyh-Ming Lien

When robots entered our day-to-day life, the shared space surrounding humans and robots is critical for effective Human-Robot collaboration. The design of shared space should satisfy humans' preferences and robots' efficiency. This work uses kitchen design as an example to illustrate the importance of good space design in facilitating such collaboration. Giv

Rajhans Singh, Ankita Shukla, Pavan Turaga

Implicit neural representations (INR) have gained significant popularity for signal and image representation for many end-tasks, such as superresolution, 3D modeling, and more. Most INR architectures rely on sinusoidal positional encoding, which accounts for high-frequency information in data. However, the finite encoding size restricts the model's represent

Sanghita Sengupta, Thomas Frederiksen, Geza Giedke

We investigate hyperfine interaction (HFI) using density-functional theory for several open-shell planar $sp^2$-carbon nanostructures displaying $\pi$ magnetism. Our prototype structures include both benzenoid ([$n$]triangulenes and a graphene nanoribbon) as well as non-benzenoid (indene, fluorene, and indene[2,1-b]fluorene) molecules. Our results obtained w

Meir Yossef Levi, Guy Gilboa

Robust point cloud classification is crucial for real-world applications, as consumer-type 3D sensors often yield partial and noisy data, degraded by various artifacts. In this work we propose a general ensemble framework, based on partial point cloud sampling. Each ensemble member is exposed to only partial input data. Three sampling strategies are used joi

Facundo Argañaraz, Juan Carlos Escanciano

Locally Robust (LR)/Orthogonal/Debiased moments have proven useful with machine learning first steps, but their existence has not been investigated for general parameters. In this paper, we provide a necessary and sufficient condition, referred to as Restricted Local Non-surjectivity (RLN), for the existence of such orthogonal moments to conduct robust infer

Jie Feng, Wenqi Cui, Jorge Cortés, Yuanyuan Shi

Deep reinforcement learning approaches are becoming appealing for the design of nonlinear controllers for voltage control problems, but the lack of stability guarantees hinders their deployment in real-world scenarios. This paper constructs a decentralized RL-based controller featuring two components: a transient control policy and a steady-state performance

Marco Buratti, Dieter Jungnickel

We say that a linear space is harmonious if it is resolvable and admits an automorphism group acting sharply transitively on the points and transitively on the parallel classes. Generalizing old results by the first author et al. we present some difference methods to construct harmonious linear spaces. We prove, in particular, that for any finite non-singlet

H. Fetsch, T. E. Foster, N. J. Fisch

In moderately-coupled plasmas, a significant fraction of the internal energy resides in electric fields. As these plasmas are heated or compressed, the shifting partition of energy between particles and fields leads to surprising effects, particularly when ions and electrons have different temperatures. In this work, quasi-equations of state (quasi-EOS) are

Simiam Ghan, Elias Diesen, Christian Kunkel, Karsten Reuter

We study the electronic coupling between an adsorbate and a metal surface by calculating tunneling matrix elements H$_{\text{ad}}$ directly from first principles. For this we employ a projection of the Kohn-Sham Hamiltonian upon a diabatic basis using a version of the popular Projection-Operator Diabatization approach. An appropriate integration of couplings

Chengchao Xu, B. S. D. Ch. S Varaprasad, David E. Laughlin, Jian-Gang

In this paper, we present an experimental study of $\text{L1}_0$-FePt granular films with crystalline/amorphous boron nitride (BN) grain boundary materials for heat assisted magnetic recording (HAMR). It is found that an adequate RF substrate bias yields the formation of hexagonal boron nitride (h-BN) nanosheets in grain boundaries, facilitating the columnar

Chenguang Wang, Ensieh Sharifnia, Simon H. Tindemans, Peter Palensky

Variational autoencoder (VAE) neural networks can be trained to generate power system states that capture both marginal distribution and multivariate dependencies of historical data. The coordinates of the latent space codes of VAEs have been shown to correlate with conceptual features of the data, which can be leveraged to synthesize targeted data with desi

Min Chen, Minzhao Liu, Changhun Oh, Liang Jiang

The efficient simulation of complex quantum systems remains a central challenge due to the exponential growth of Hilbert space with system size. Tensor network methods have long been established as powerful approximation schemes, and their efficiency can be further enhanced by incorporating physics-informed priors. A prominent example is symmetry: recent pro

Alexandra Sasha Luccioni, Christopher Akiki, Margaret Mitchell, Yacine Jernite

As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly prevalent and seeing growing adoption as commercial services, characterizing the social biases they exhibit is a necessary first step to lowering their risk of discriminatory outcomes. This evaluation, however, is made more difficult by the synthetic nature of these systems' ou

Mohammad Khajenejad, Scott Brown, Sonia Martinez

This paper proposes a novel distributed interval-valued simultaneous state and input observer for linear time-invariant (LTI) systems that are subject to attacks or unknown inputs injected both on their sensors and actuators. Each agent in the network leverages a singular value decomposition (SVD) based transformation to decompose its observations into two c

Pablo Rojas, Oreste Piro, Martin E. Garcia

Common models of circadian rhythms are constructed as compartmental reactions of well mixed biochemicals involving a negative-feedback loop containing several intermediate reaction steps in order to enable oscillations. Spatial transport of reactants is mimicked as an extra compartmental reaction step. In this letter, we show that a single activation-repress

Martin Knor, Riste Škrekovski, Aleksandra Tepeh

The Wiener index is defined as the sum of distances between all unordered pairs of vertices in a graph. It is one of the most recognized and well-researched topological indices, which is on the other hand still a very active area of research. This work presents a natural continuation of the paper Mathematical aspects of Wiener index (Ars Math. Contemp., 2016

Conrad P. Koziol, Eldad Haber

Geological processes determine the distribution of resources such as critical minerals, water, and geothermal energy. However, direct observation of geology is often prevented by surface cover such as overburden or vegetation. In such cases, remote and in-situ surveys are frequently conducted to collect physical measurements of the earth indicative of the ge