March 2023 arXiv papers — page 22

Reza Mahroo, Amin Kargarian

The advent of quantum computing can potentially revolutionize how complex problems are solved. This paper proposes a two-loop quantum-classical solution algorithm for generation scheduling by infusing quantum computing, machine learning, and distributed optimization. The aim is to facilitate employing noisy near-term quantum machines with a limited number of

Samuel Lanthaler

PCA-Net is a recently proposed neural operator architecture which combines principal component analysis (PCA) with neural networks to approximate operators between infinite-dimensional function spaces. The present work develops approximation theory for this approach, improving and significantly extending previous work in this direction: First, a novel univer

Tuneer Chakraborty, Joydeep Chakravarty, Victor Godet, Priyadarshi Paul

We study the natural norm on the space of solutions to the Wheeler-DeWitt equation in an asymptotically de Sitter spacetime. We propose that the norm is obtained by integrating the squared wavefunctional over field configurations and dividing by the volume of the diff-and-Weyl group. We impose appropriate gauge conditions to fix the diff-and-Weyl redundancy

Tuneer Chakraborty, Joydeep Chakravarty, Victor Godet, Priyadarshi Paul

We obtain solutions of the Wheeler-DeWitt equation with positive cosmological constant for a closed universe in the large-volume limit. We argue that this space of solutions provides a complete basis for the Hilbert space of quantum gravity in an asymptotically de Sitter spacetime. Our solutions take the form of a universal phase factor multiplied by distinc

Axel A. Araneda

Fractional Brownian motion has become a standard tool to address long-range dependence in financial time series. However, a constant memory parameter is too restrictive to address different market conditions. Here we model the price fluctuations using a multifractional Brownian motion assuming that the Hurst exponent is a time-deterministic function. Through

Shasha Zheng, Zhenyu Wang, Yipu Wang, Fengxiao Sun

Nonlinear magnonics studies the nonlinear interaction between magnons and other physical platforms (phonon, photon, qubit, spin texture) to generate novel magnon states for information processing. In this tutorial, we first introduce the nonlinear interactions of magnons in pure magnetic systems and hybrid magnon-phonon and magnon-photon systems. Then we sho

Danish Khan, Stefan Heinen, O. Anatole von Lilienfeld

The feature vector mapping used to represent chemical systems is a key factor governing the superior data-efficiency of kernel based quantum machine learning (QML) models applicable throughout chemical compound space. Unfortunately, the most accurate representations require a high dimensional feature mapping, thereby imposing a considerable computational bur

Koretaka Yuge

For classical discrete system under constant composition, typically reffered to as substitutional alloys, canonical average acts as nonlinear map F from a set of potential energy surface U to that of microscopic configuration in thermodynamic equilibrium, Q, which is called canonical nonlinearity (CN). On statistical manifold, at any given configuration, F c

Varun Mandalapu, Lavanya Elluri, Piyush Vyas, Nirmalya Roy

Predicting crime using machine learning and deep learning techniques has gained considerable attention from researchers in recent years, focusing on identifying patterns and trends in crime occurrences. This review paper examines over 150 articles to explore the various machine learning and deep learning algorithms applied to predict crime. The study provide

Nicholas Miller

Recent work of Chinburg, Reid, and Stover has shown that certain arithmetic and algebro-geometric properties of the character variety of a hyperbolic knot complement in the 3-sphere $M=S^3\setminus K$ yields topological and number theoretic information about Dehn fillings of M. Specifically, they show how the study of a certain extension problem for quaterni

Aounon Kumar, Vinu Sankar Sadasivan, Soheil Feizi

The literature on provable robustness in machine learning has primarily focused on static prediction problems, such as image classification, in which input samples are assumed to be independent and model performance is measured as an expectation over the input distribution. Robustness certificates are derived for individual input instances with the assumptio

Michael J. Weisman, Alexander Kott, Jason E. Ellis, Brian J. Murphy

Cyber resilience is the ability of a system to resist and recover from a cyber attack, thereby restoring the system's functionality. Effective design and development of a cyber resilient system requires experimental methods and tools for quantitative measuring of cyber resilience. This paper describes an experimental method and test bed for obtaining resilie

Andres F. Gomez-Bastidas, Oleg Rubel

We present two modules that expand functionalities of the all-electron full-potential density functional theory package WIEN2k for computation of the Chern and $Z_2$ topological invariants. Characterization of topological properties relies on two methods: computing an evolution of hybrid Wannier charge centers for $Z_2$ topological insulators (construction o

M. Beccaria, G. P. Korchemsky, A. A. Tseytlin

We study non-planar corrections in two special $\mathcal N=2$ superconformal $SU(N)$ gauge theories that are planar-equivalent to $\mathcal N=4$ SYM theory: two-nodes quiver model with equal couplings and $\mathcal N=2$ vector multiplet coupled to two hypermultiplets in rank-2 symmetric and antisymmetric representations. We focus on two observables in these

Hiroyoshi Mitake, Connor Mooney, Hung V. Tran, Jack Xin

The level-set curvature G-equation, a well-known model in turbulent combustion, has the following form $G_t + \left(1-d\, \mathrm{dvi}\left({\frac{DG}{|DG|}}\right)\right)_+|DG|+V(X)\cdot DG=0.$ Here the cutoff correction $()_+$ is imposed to avoid non-physical negative local burning velocity. The existence of the effective burning velocity has been establis

Timothy M. Chan, Zhengcheng Huang

In SoCG 2022, Conroy and T\'oth presented several constructions of sparse, low-hop spanners in geometric intersection graphs, including an $O(n\log n)$-size 3-hop spanner for $n$ disks (or fat convex objects) in the plane, and an $O(n\log^2 n)$-size 3-hop spanner for $n$ axis-aligned rectangles in the plane. Their work left open two major questions: (i) can

Rod Abhari, Esteban Villa-Turek, Nicholas Vincent, Henry Dambanemuya

Retracted scientific articles about COVID-19 vaccines have proliferated false claims about vaccination harms and discouraged vaccine acceptance. Our study analyzed the topical content of 4,876 English-language tweets about retracted COVID-19 vaccine research and found that 27.4% of tweets contained retraction-related misinformation. Misinformed tweets either

Shreya Agrawal, Rob Carver, Cenk Gazen, Eric Maddy

Post-processing typically takes the outputs of a Numerical Weather Prediction (NWP) model and applies linear statistical techniques to produce improve localized forecasts, by including additional observations, or determining systematic errors at a finer scale. In this pilot study, we investigate the benefits and challenges of using non-linear neural network

Maria F. Gamal'

An operator $T$ on a Hilbert space $\mathcal H$ is called expansive, if $\|Tx\|\geq \|x\|$ ($x\in\mathcal H$). Expansive operators $T$ quasisimilar to the unilateral shift $S_N$ of finite multiplicity $N$ are studied. It is proved that $I-T^*T$ is of trace class for such $T$. Also the lattice $\mathrm{Lat}T$ of invariant subspaces of an expansive operator $T

Ruilong Yue, Giray Ökten

We present a new dimension reduction method called the global active subspace method. The method uses expected values of finite differences of the underlying function to identify the important directions, and builds a surrogate model using the important directions on a lower dimensional subspace. The method is a generalization of the active subspace method w

Carly Lupton Brantner, Trang Quynh Nguyen, Tengjie Tang, Congwen Zhao

Individualized treatment decisions can improve health outcomes, but using data to make these decisions in a reliable, precise, and generalizable way is challenging with a single dataset. Leveraging multiple randomized controlled trials allows for the combination of datasets with unconfounded treatment assignment to better estimate heterogeneous treatment eff

Siddarth Singh, Benjamin Rosman

In the field of cooperative multi-agent reinforcement learning (MARL), the standard paradigm is the use of centralised training and decentralised execution where a central critic conditions the policies of the cooperative agents based on a central state. It has been shown, that in cases with large numbers of redundant agents these methods become less effecti

Patrick Ballard, Flaviana Iurlano

In this article, the structure of the incremental quasistatic contact problem with Coulomb friction in linear elasticity (Signorini-Coulomb problem) is unraveled and sharp existence results are proved for the most general two-dimensional problem with arbitrary geometry and elasticity modulus tensor. The problem is reduced to a variational inequality involvin

Servet Martínez, Werner Nagel

Processes of random tessellations of the Euclidean space $\mathbb{R}^d$, $d\geq 1$, are considered which are generated by subsequent division of their cells. Such processes are characterized by the laws of the life times of the cells until their division and by the laws for the random hyperplanes that divide the cells at the end of their life times. The STIT

Zifu Wang, Teodora Popordanoska, Jeroen Bertels, Robin Lemmens

The soft Dice loss (SDL) has taken a pivotal role in numerous automated segmentation pipelines in the medical imaging community. Over the last years, some reasons behind its superior functioning have been uncovered and further optimizations have been explored. However, there is currently no implementation that supports its direct utilization in scenarios inv

Brianna Lacy, Adam Burrows

Y dwarfs are the coolest spectral class of brown dwarf. They have effective temperatures less than 500 K, with the coolest detection as low as ~250 K. Their spectra are shaped predominantly by gaseous water, methane, and ammonia. At the warmer end of the Y dwarf temperature range, spectral signatures of disequilibrium carbon monoxide have been observed. Cool

Debanjan Polley, Jyotirmoy Chatterjee, Hyejin Jang, Jeffrey Bokor

Magnetization switching in ferromagnets has so far been limited to the current-induced spin-orbit-torque effects. Recent observation of helicity-independent all-optical magnetization switching in exchange-coupled ferromagnet ferrimagnet heterostructures expanded the range and applicability of such ultrafast heat-driven magnetization switching. Here we report

Jae Joong Lee, Bedrich Benes

Deep learning-based 3D object reconstruction has achieved unprecedented results. Among those, the transformer deep neural model showed outstanding performance in many applications of computer vision. We introduce SnakeVoxFormer, a novel, 3D object reconstruction in voxel space from a single image using the transformer. The input to SnakeVoxFormer is a 2D ima

Xuhai Xu, Mengjie Yu, Tanya R. Jonker, Kashyap Todi

Explainable AI (XAI) has established itself as an important component of AI-driven interactive systems. With Augmented Reality (AR) becoming more integrated in daily lives, the role of XAI also becomes essential in AR because end-users will frequently interact with intelligent services. However, it is unclear how to design effective XAI experiences for AR. W

Willdauany C. de Freitas Silva, Maykon V. M. Araujo, Sayantan Roy, Abhisek Samanta

We obtain the Seebeck coefficient or thermopower $S$, which determines the conversion efficiency from thermal to electrical energy, for the two-dimensional Hubbard model on different geometries (square, triangular, and honeycomb lattices) for different electronic densities and interaction strengths. Using Determinantal Quantum Monte Carlo (DQMC) we find the

Song Liu, Yang Liu, Luke Nemetz Holtzman, Baichang Li

Here, we describe synthesis of TMD crystals using a two-step flux growth method that eliminates a major potential source of contamination. Detailed characterization of TMDs grown by this two-step method reveals charged and isovalent defects with densities an order of magnitude lower than in TMDs grown by a single-step flux technique. Initial temperature-depe

Simon Thorsteinsson, Alex Arash Sand Kalaee, Pierre Vogler-Finck, Henrik Lund Stærmose

The continuous introduction of renewable electricity and increased consumption through electrification of the transport and heating sector challenges grid stability. This study investigates load shifting through demand side management as a solution. We present a four-month experimental study of a low-complexity, hierarchical Model Predictive Control approach

Popov R. V., Shabaev V. M., Maltsev I. A., Telnov D. A.

The problem of spontaneous vacuum decay in low-energy collisions of heavy nuclei is considered beyond the scope of the monopole approximation. The time-dependent Dirac equation is solved in a rotating coordinate system with $z$-axis directed along the internuclear line and the origin placed at the center of mass. The probabilities of electron-positron pair c

Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Shay Sapir

Many streaming algorithms provide only a high-probability relative approximation. These two relaxations, of allowing approximation and randomization, seem necessary -- for many streaming problems, both relaxations must be employed simultaneously, to avoid an exponentially larger (and often trivial) space complexity. A common drawback of these randomized appr

Indranil Nayak, Fernando L. Teixeira, Dong-Yeop Na, Mrinal Kumar

We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh.

Jingwei Sun, Zhixu Du, Anna Dai, Saleh Baghersalimi

Vertical federated learning (VFL) enables a service provider (i.e., active party) who owns labeled features to collaborate with passive parties who possess auxiliary features to improve model performance. Existing VFL approaches, however, have two major vulnerabilities when passive parties unexpectedly quit in the deployment phase of VFL - severe performance

Manali Dutta, Rahul Singh

We consider the problem of transmission scheduling for the remote estimation of a discrete-time autoregressive Markov process that is driven by white Gaussian noise. A sensor observes this process, and then decides to either encode the current state of this process into a data packet and attempts to transmit it to the estimator over an unreliable wireless ch

Hong-Bin Chen

We propose a simpler approach to identifying the limit of free energy in a vector spin glass model by adding a self-overlap correction to the Hamiltonian. This avoids constraining the self-overlap and allows us to identify the limit with the classical Parisi formula, similar to the proof for scalar models with Ising spins. For the upper bound, the correction

Vsevolod Ivanov, Alexander Ivanov, Jacopo Simoni, Prabin Parajuli

Solid-state point defects are attracting increasing attention in the field of quantum information science, because their localized states can act as a spin-photon interface in devices that store and transfer quantum information, which have been used for applications in quantum computing, sensing, and networking. In this work we have performed high-throughput

Adam Caulfield, Norrathep Rattanavipanon, Ivan De Oliveira Nunes

Low-end embedded devices are increasingly used in various smart applications and spaces. They are implemented under strict cost and energy budgets, using microcontroller units (MCUs) that lack security features available in general-purpose processors. In this context, Remote Attestation (RA) was proposed as an inexpensive security service to enable a verifie

Queenie Luo, Michael J. Puett, Michael D. Smith

Contrary to Google Search's mission of delivering information from "many angles so you can form your own understanding of the world," we find that Google and its most prominent returned results - Wikipedia and YouTube - simply reflect a narrow set of culturally dominant views tied to the search language for complex topics like "Buddhism," "Liberalism," "colo

Dmitrii Torbunov, Yi Huang, Huan-Hsin Tseng, Haiwang Yu

An unpaired image-to-image (I2I) translation technique seeks to find a mapping between two domains of data in a fully unsupervised manner. While initial solutions to the I2I problem were provided by generative adversarial neural networks (GANs), diffusion models (DMs) currently hold the state-of-the-art status on the I2I translation benchmarks in terms of Fr

Cheuk Yin Lin, Chaobing Song, Jelena Diakonikolas

Exploiting partial first-order information in a cyclic way is arguably the most natural strategy to obtain scalable first-order methods. However, despite their wide use in practice, cyclic schemes are far less understood from a theoretical perspective than their randomized counterparts. Motivated by a recent success in analyzing an extrapolated cyclic scheme

Zhuoyang Liu, Haiyang Zhang, Tianyao Huang, Feng Xu

Dual-function radar-communication (DFRC) technology is emerging in next-generation wireless systems. Reconfigurable intelligent surface (RIS) arrays have been suggested as a crucial sensor component of the DFRC. In this paper, we propose a hybrid RIS (HRIS)-assisted multiple-input multiple-output (MIMO) DFRC system, where the HRIS is capable of reflecting co

Aris Daniilidis, Dmitriy Drusvyatskiy

We show that the deviation between the slopes of two convex functions controls the deviation between the functions themselves. This result reveals that the slope -- a one dimensional construct -- robustly determines convex functions, up to a constant of integration.

Eric Norrgard, Yuly Chamorro, Catherine Cooksey, Stephen Eckel

We report measured and calculated values of radiative decay rates and vibrational branching fractions for the A$^2\Pi$ state of MgF. The decay rate measurements use time-correlated single photon counting with roughly 1% total uncertainty. Branching-fraction measurements are performed using two calibrated imaging systems to achieve few percent total uncertain

Vivek Kulkarni, Vipul Raheja

Intelligent writing assistants powered by large language models (LLMs) are more popular today than ever before, but their further widespread adoption is precluded by sub-optimal performance. In this position paper, we argue that a major reason for this sub-optimal performance and adoption is a singular focus on the information content of language while ignor

Sokratis Anagnostopoulos, Jens Bauer, Mariana C. A. Clare, Matthew D. Piggott

Wind farm modelling has been an area of rapidly increasing interest with numerous analytical as well as computational-based approaches developed to extend the margins of wind farm efficiency and maximise power production. In this work, we present the novel ML framework WakeNet, which can reproduce generalised 2D turbine wake velocity fields at hub-height ove

I. A. Aleksandrov, V. M. Shabaev

In the present study, we consider the effects of vacuum birefringence and dichroism in strong electromagnetic fields. According to quantum electrodynamics, the vacuum state exhibits different refractive properties depending on the probe photon polarization and one also obtains different probabilities of the photon decay via production of electron-positron pa

Anna Volpara, Michele Piana, Anna Maria Massone

Multi-scale deconvolution is an ill-posed inverse problem in imaging, with applications ranging from microscopy, through medical imaging, to astronomical remote sensing. In the case of high-energy space telescopes, multi-scale deconvolution algorithms need to account for the peculiar property of native measurements, which are sparse samples of the Fourier tr

Luke Conners

We give a recursive construction of the categorified Young symmetrizer introduced by Abel-Hogancamp in arXiv:1510.05330 corresponding to the single-column partition. As a consequence, we obtain new expressions for the uncolored $y$-ified HOMFLYPT homology of positive torus links and the $y$-ified column-colored HOMFLYPT homology of positive torus knots. In t

Jingwei Sun, Ziyue Xu, Dong Yang, Vishwesh Nath

Federated learning is a popular collaborative learning approach that enables clients to train a global model without sharing their local data. Vertical federated learning (VFL) deals with scenarios in which the data on clients have different feature spaces but share some overlapping samples. Existing VFL approaches suffer from high communication costs and ca

Piero D'Ancona, Angelo Zanni

We prove $H^{1}$ scattering for a defocusing NLS on the line with fully variable coefficients. The result is proved by adapting the Kenig--Merle scheme to a non translation invariant setting. In addition, we give an abstract version of the scheme which can be applied to other operators.

Ishan Rajendrakumar Dave, Mamshad Nayeem Rizve, Chen Chen, Mubarak Shah

Semi-Supervised Learning can be more beneficial for the video domain compared to images because of its higher annotation cost and dimensionality. Besides, any video understanding task requires reasoning over both spatial and temporal dimensions. In order to learn both the static and motion related features for the semi-supervised action recognition task, exi

Andrew Moisa, Boris Faleichik

Stabilized methods (also called Chebyshev methods) are explicit methods with extended stability domains along the negative real axis. These methods are intended for large mildly stiff problems, originating mainly from parabolic PDEs. In this paper we present explicit two-step Runge-Kutta methods, which have an increased stability interval in comparison with

Łukasz Lepak, Paweł Wawrzyński

An increasing share of energy is produced from renewable sources by many small producers. The efficiency of those sources is volatile and, to some extent, random, exacerbating the problem of energy market balancing. In many countries, this balancing is done on the day-ahead (DA) energy markets. This paper considers automated trading on the DA energy market b

Jinlu Li

Let X be a real uniformly convex and uniformly smooth Banach space and C a nonempty closed and convex subset of X. Let Pc from X to C denote the (standard) metric projection operator. In this paper, we define the Gateaux directional differentiability of Pc. We investigate some properties of the Gateaux directional differentiability of Pc. In particular, if C

Michael T. Roman

The mid-infrared spectral region provides a unique window into the atmospheric temperature, chemistry, and dynamics of the giant planets. From more than a century of mid-infrared remote sensing, progressively clearer pictures of the composition and thermal structure of these atmospheres have emerged, along with a greater insight into the processes that shape

Luca Chiantini, Lucja Farnik, Giuseppe Favacchio, Brian Harbourne

In this short note we develop new methods toward the ultimate goal of classifying geproci sets in $\mathbb P^3$. We apply these methods to show that among sets of $16$ points distributed evenly on $4$ skew lines, up to projective equivalence there are only two distinct geproci sets. We give different geometric distinctions between these sets. The methods we

Zhen Yang, Guangyu Bao, Shuaibing Jiang, Xingwei Yang

Hydrogel adhesion that can be easily modulated in magnitude, space, and time is desirable in many emerging applications ranging from tissue engineering, and soft robotics, to wearable devices. In synthetic materials, these complex adhesion behaviors are often achieved individually with mechanisms and apparatus that are difficult to integrate. Here, we report

Daniele Di Miceli, Eduárd Zsurka, Julian Legendre, Kristof Moors

We theoretically discuss electronic transport via Majorana states in magnetic topological insulator-superconductor junctions with an asymmetric split of the applied bias voltage. We study normal-superconductor-normal (NSN) junctions made of narrow (wire-like) or wide (film-like) magnetic topological insulator slabs with a central proximitized superconducting

Natalie Neumeyer, Marek Omelka

We consider the copula mapping, which maps a joint cumulative distribution function to the corresponding copula. Its Hadamard differentiablity was shown in van der Vaart and Wellner (1996), Fermanian et al. (2004) and (under less strict assumptions) in B\"ucher and Volgushev (2013). This differentiability result has proved to be a powerful tool to show weak

Alexander Braverman, David Kazhdan, Alexander Polishchuk

We define and study the subspace of cuspidal functions for $G$-bundles on a class of nilpotent extensions $C$ of curves over a finite field. We show that this subspace is preserved by the action of a certain noncommutative Hecke algebra $\mathcal{H}_{G,C}$. In the case $G=\rm{GL}_2$, we construct a commutative subalgebra in $\mathcal{H}_{G,C}$ of Hecke opera

Konstantin Klemm, Anita Mehta, Peter F. Stadler

Difficult, in particular NP-complete, optimization problems are traditionally solved approximately using search heuristics. These are usually slowed down by the rugged landscapes encountered, because local minima arrest the search process. Cover-encoding maps were devised to circumvent this problem by transforming the original landscape to one that is free o

S. Mercimek, L. Podio, C. Codella, L. Chahine

More than 50% of solar-mass stars form in multiple systems. It is therefore crucial to investigate how multiplicity affects the star and planet formation processes at the protostellar stage. We report continuum and C$^{18}$O (2-1) observations of the VLA 1623-2417 protostellar system at 50 au angular resolution as part of the ALMA Large Program FAUST. The 1.

Jan Idziak, Artjoms Šeļa, Michał Woźniak, Albert Leśniak

The paper discusses an approach to decipher large collections of handwritten index cards of historical dictionaries. Our study provides a working solution that reads the cards, and links their lemmas to a searchable list of dictionary entries, for a large historical dictionary entitled the Dictionary of the 17th- and 18th-century Polish, which comprizes 2.8

Swapan Biswas, Anal Bhowmik, Arghya Das, Radha Raman Pal

The growing interest in atomic structures of moderately-stripped alkali-like ions in diagnostic study and modeling of astrophysical and laboratory plasma makes an accurate many-body study of atomic properties inevitable. This work presents transition line parameters in the absence or presence of plasma atmosphere for astrophysically important candidates, Ar$

Xinhang Liu, Yan Zeng, Yifan Qin, Hao Li

Cryo-electron microscopy (cryo-EM) allows for the high-resolution reconstruction of 3D structures of proteins and other biomolecules. Successful reconstruction of both shape and movement greatly helps understand the fundamental processes of life. However, it is still challenging to reconstruct the continuous motions of 3D structures from hundreds of thousand

Kevin Pedro, Prasanth Shyamsundar

Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with standard model hadrons in the form of semivisible jets. Classical mass reconstruction techniques may not be optimal for these unusual topologies, in which the missing transverse momentum comes from massive particles and has a nontrivi

Adib Mosharrof, M. H. Maqbool, A. B. Siddique

Task-oriented dialog systems empower users to accomplish their goals by facilitating intuitive and expressive natural language interactions. State-of-the-art approaches in task-oriented dialog systems formulate the problem as a conditional sequence generation task and fine-tune pre-trained causal language models in the supervised setting. This requires label

Tyler Lekang, Andrew Lamperski

Classical results in neural network approximation theory show how arbitrary continuous functions can be approximated by networks with a single hidden layer, under mild assumptions on the activation function. However, the classical theory does not give a constructive means to generate the network parameters that achieve a desired accuracy. Recent results have

Matej Ditte, Matteo Barborini, Leonardo Medrano Sandonas, Alexandre Tkatchenko

We develop a quantum embedding method that enables accurate and efficient treatment of interactions between molecules and an environment, while explicitly including many-body correlations. The molecule is composed of classical nuclei and quantum electrons, whereas the environment is modeled via charged quantum harmonic oscillators. We construct a general Ham

Ives Torriente-García, Francisco M. Muñoz-Pérez, Arturo C. Marti, Martín Monteiro

Simple, portable and low-cost experiments as RC and RL series circuits are proposed to experiment with DC circuits. Very common elements are used: a few electronics components (resistors, capacitors, coils and connecting wires) and two smartphones. We consider the charging and discharging of a capacitor in the RC circuit and also that of coil in the RL circu

Pawel Sarkowicz, Aaron Tikuisis

We show that the Hausdorffized algebraic K-theory of a C*-algebra decomposes naturally as a direct sum of the Hausdorffized unitary algebraic K-theory and the space of continuous affine functions on the trace simplex. Under mild regularity hypotheses, an analogous natural direct sum decomposition holds for the ordinary (non-Hausdorffized) algebraic K-theory.

Tahsin Reasat, Asif Sushmit, David S. Smith

Deep learning (DL) based diagnostics systems can provide accurate and robust quantitative analysis in digital pathology. These algorithms require large amounts of annotated training data which is impractical in pathology due to the high resolution of histopathological images. Hence, self-supervised methods have been proposed to learn features using ad-hoc pr

Matthew J. Holman, Arya Akmal, Davide Farnocchia, Hanno Rein

We introduce ASSIST, a software package for ephemeris-quality integrations of test particles. ASSIST is an extension of the REBOUND framework and makes use of its IAS15 integrator to integrate test particle trajectories in the field of the Sun, Moon, planets, and 16 massive asteroids, with the positions of the masses coming from the JPL DE441 ephemeris and i

Xingfu Wu, Prasanna Balaprakash, Michael Kruse, Jaehoon Koo

As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to exp

Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh

The Object Constraint Language (OCL) is a declarative language that adds constraints and object query expressions to MOF models. Despite its potential to provide precision and conciseness to UML models, the unfamiliar syntax of OCL has hindered its adoption. Recent advancements in LLMs, such as GPT-3, have shown their capability in many NLP tasks, including

S. Afanasiev, G. Agakishiev, E. Aleksandrov, I. Aleksandrov

First physics results of the BM@N experiment at the Nuclotron/NICA complex are presented on {\pi}+ and K+ meson production in interactions of an argon beam with fixed targets of C, Al, Cu, Sn and Pb at 3.2 AGeV. Transverse momentum distributions, rapidity spectra and multiplicities of $\pi^+$ and $K^+$ mesons are measured. The results are compared with predi

Zixuan Chen, Jian-Huang Lai, Lingxiao Yang, Xiaohua Xie

Medical image arbitrary-scale super-resolution (MIASSR) has recently gained widespread attention, aiming to super sample medical volumes at arbitrary scales via a single model. However, existing MIASSR methods face two major limitations: (i) reliance on high-resolution (HR) volumes and (ii) limited generalization ability, which restricts their application in

Uday Kiran Reddy Tadipatri, Mathukumalli Vidyasagar

In this paper, we establish the convergence of the stochastic Heavy Ball (SHB) algorithm under more general conditions than in the current literature. Specifically, (i) The stochastic gradient is permitted to be biased, and also, to have conditional variance that grows over time (or iteration number). This feature is essential when applying SHB with zeroth-o

Shira Zerbib

A family of sets has the $(p, q)$ property if among any $p$ members of it some $q$ intersect. It is shown that if a finite family of compact convex sets in $\R^2$ has the $(p+1,2)$ property then it is pierced by $\lfloor \frac{p}{2} \rfloor +1$ lines. A colorful version of this result is proved as well. As a corollary, the following is proved: Let $\F$ be a

Junyan Cao, Mihai Păun

It contains the proof of a very general $\partial\bar\partial$-lemma, together with a decomposition theorem for currents with values in a (singular) Hermitian line bundle. As a corollary, we establish the K\"ahler version on an injectivity theorem due to O. Fujino in the projective case.

Robert Kealhofer, Hanbyeol Jeong, Arman Rashidi, Leon Balents

A superconductor with broken time reversal and inversion symmetry may exhibit nonreciprocal charge transport, including a nonreciprocal critical current, also known as superconducting diode effect. We report an intrinsic superconducting diode effect in a polar strontium titanate film. Differential resistance measurements reveal a superconducting state whose

Tianyi Tao

For a graph $G$, a vertex coloring $f$ is called nonrepetitive if for all $k\in\mathbb N$ and all $P_{2k}=\langle v_1, \cdots, v_k,v_{k+1}, \cdots, v_{2k}\rangle$ (path of $2k$ vertices) in $G$, there must be some $1\le i\le k$ such that $f(v_i)\not=f(v_{k+i})$. We use $\pi(G)$ to denote the minimum number of colors required for $G$ to be nonrepetitively col

J. Michael Burgess

`ronswanson` provides a simple-to-use framework for building so-called table or template models for `astromodels`the modeling package for multi-messenger astrophysical data-analysis framework, `3ML`. With `astromodels` and `3ML` one can build the interpolation table of a physical model result of an expensive computer simulation. This then enables efficient r

Tomoya Kemmochi

Maximal regularity for the Stokes operator plays a crucial role in the theory of the non-stationary Navier--Stokes equations. In this paper, we consider the finite element semi-discretization of the non-stationary Stokes problem and establish the discrete counterpart of maximal regularity in $L^q$ for $q \in \left( \frac{2N}{N+2}, \frac{2N}{N-2} \right)$. Fo

Yanhao Wu, Tong Zhang, Wei Ke, Sabine Süsstrunk

Self-supervised learning (SSL) has the potential to benefit many applications, particularly those where manually annotating data is cumbersome. One such situation is the semantic segmentation of point clouds. In this context, existing methods employ contrastive learning strategies and define positive pairs by performing various augmentation of point clusters

Rosa M. Mérida, Pablo G. Pérez-González, Patricia Sánchez-Blázquez, Ángela García-Argumánez

We investigate the star formation main sequence (MS) (SFR-M$_{\star}$) down to 10$^{8-9}\mathrm{M}_\odot$ using a sample of 34,061 newly-discovered ultra-faint ($27\lesssim i \lesssim 30$ mag) galaxies at $1<z<3$ detected in the GOODS-N field. Virtually these galaxies are not contained in previous public catalogs, effectively doubling the number of known sou

Kasper Hunnestad, Constantinos Hatzoglou, Francois Vurpillot, Inger-Emma Nylund

Atom probe tomography (APT) is a 3D analysis technique that offers unique chemical accuracy and sensitivity with sub-nanometer spatial resolution. Recently, there is an increasing interest in the application of APT to complex oxides materials, giving new insight into the relation between local variations in chemical composition and emergent physical properti

Hui-Jie Hu, Qi Guo, Zheng Zheng, Hang Yang

The baryonic Tully-Fisher relation (BTFR), which connects the baryonic mass of galaxies with their circular velocities, has been validated across a wide range of galaxies, from dwarf galaxies to massive galaxies. Recent studies have found that several ultra-diffuse galaxies (UDGs) deviate significantly from the BTFR, indicating a galaxy population with abnor

Itai Linial, Brian D. Metzger

Roughly half of the quasi-periodic eruption (QPE) sources in galactic nuclei exhibit a remarkably regular alternating "long-short'' pattern of recurrence times between consecutive flares. We show that a main-sequence star (brought into the nucleus as an extreme mass-ratio inspiral; EMRI) which passes twice per orbit through the accretion disk of the supermas

Taj Jankovič, Clément Bonnerot, Andreja Gomboc

Tidal disruption events occur when a star is disrupted by a supermassive black hole, resulting in an elongated stream of gas that partly falls back to the pericenter. Due to apsidal precession, the returning stream may collide with itself, leading to a self-crossing shock that launches an outflow. If the black hole spins, this collision may additionally be a

Riccardo Spinelli, Francesco Borsa, Giancarlo Ghirlanda, Gabriele Ghisellini

The dozens of rocky exoplanets discovered in the Circumstellar Habitable Zone (CHZ) currently represent the most suitable places to host life as we know it outside the Solar System. However, the presumed presence of liquid water on the CHZ planets does not guarantee suitable environments for the emergence of life. According to experimental studies, the build

Diego Sotillo-Ramos, Martina Donnari, Annalisa Pillepich, Neige Frankel

We use the sample of 198 Milky Way (MW) and Andromeda (M31) analogs from TNG50 to quantify the level of disk flaring predicted by a modern, high-resolution cosmological hydrodynamical simulation. Disk flaring refers to the increase of vertical stellar disk height with galactocentric distance. The TNG50 galaxies are selected to have stellar disky morphology,

F. Rizzo, F. Roman-Oliveira, F. Fraternali, D. Frickmann

Spatially-resolved studies of the kinematics of galaxies provide crucial insights into their assembly and evolution, enabling to infer the properties of the dark matter halos, derive the impact of feedback on the ISM, characterize the outflow motions. To date, most of the kinematic studies at z=0.5-3.5 were obtained using emission lines tracing the warm, ion

Luca Di Mascolo, Alexandro Saro, Tony Mroczkowski, Stefano Borgani

Galaxy clusters are the most massive gravitationally bound structures in the Universe, comprising thousands of galaxies and pervaded by a diffuse, hot ``intracluster medium'' (ICM) that dominates the baryonic content of these systems. The formation and evolution of the ICM across cosmic time is thought to be driven by the continuous accretion of matter from

Callum Witten, Nicolas Laporte, Sergio Martin-Alvarez, Debora Sijacki

During the epoch of reionisation the first galaxies were enshrouded in pristine neutral gas, with one of the brightest emission lines in star-forming galaxies, Lyman-$\alpha$ (Ly$\alpha$), expected to remain undetected until the Universe became ionised. Providing an explanation for the surprising detection of Ly$\alpha$ in these early galaxies is a major cha

Siyao Xu, Hsiang-Chih Hwang, Chris Hamilton, Dong Lai

The ubiquitous interstellar turbulence regulates star formation and the scaling relations between the initial velocity differences and the initial separations of stars. We propose that the formation of wide binaries with initial separations $r$ in the range $\sim 10^3~\text{AU} \lesssim r \lesssim 10^5$ AU is a natural consequence of star formation in the tu

Maria Edvige Ravasio, Om Sharan Salafia, Gor Oganesyan, Alessio Mei

The highly variable and energetic pulsed emission of a long gamma-ray burst (GRB) is thought to originate from local, rapid dissipation of kinetic or magnetic energy within an ultra-relativistic jet launched by a newborn compact object, formed during the collapse of a massive star. The spectra of GRB pulses are best modelled by power-law segments, indicating