July 2023 arXiv papers — page 95

Maciej Sikora, Patryk Krukowski, Anna Paszynska, Maciej Paszynski

This paper deals with the following important research questions. Is it possible to solve challenging advection-dominated diffusion problems in one and two dimensions using Physics Informed Neural Networks (PINN) and Variational Physics Informed Neural Networks (VPINN)? How does it compare to the higher-order and continuity Finite Element Method (FEM)? How t

Amy A. Winecoff, Johannes Lenhard

Proponents and developers of Web3 and blockchain argue that these technologies can revolutionize how people live and work by empowering individuals and distributing decision-making power. While technologists often have expansive hopes for what their technologies will accomplish over the long term, the practical challenges of developing, scaling, and maintain

Tenzin Rabga, Kevin G. Bailey, Michael Bishof, Donald W. Booth

We demonstrate laser frequency stabilization with at least 6 GHz of offset tunability using an in-phase/quadrature (IQ) modulator to generate electronic sidebands (ESB) on a titanium sapphire laser at 714 nm and we apply this technique to the precision spectroscopy of $^{226}$Ra, and $^{225}$Ra. By locking the laser to a single resonance of a high finesse op

Yiwei Luo, Kristina Gligorić, Dan Jurafsky

Identifying implicit attitudes toward food can mitigate social prejudice due to food's salience as a marker of ethnic identity. Stereotypes about food are representational harms that may contribute to racialized discourse and negatively impact economic outcomes for restaurants. Understanding the presence of representational harms in online corpora in particu

L. L. Sales, F. C. Carvalho

We investigate the non-Gaussian effects of the Saha equation in Rindler space via Tsallis statistics. By considering a system with cylindrical geometry, we deduce the non-Gaussian Saha ionization equation for a partially ionized hydrogen plasma that expands with uniform acceleration. We demonstrate conditions for the validity of the equivalence principle wit

Chenyu Zhang, Zhaozheng Yin, Ruwen Qin

Efficiently monitoring the condition of civil infrastructure requires automating the structural condition assessment in visual inspection. This paper proposes an Attention-Enhanced Co-Interactive Fusion Network (AECIF-Net) for automatic structural condition assessment in visual bridge inspection. AECIF-Net can simultaneously parse structural elements and seg

Roberta Paladini, Catherine Zucker, Robert Benjamin, David Nataf

A wide-field near-infrared survey of the Galactic disk and bulge/bar(s) is supported by a large representation of the community of Galactic astronomers. The combination of sensitivity, angular resolution and large field of view make Roman uniquely able to study the crowded and highly extincted lines of sight in the Galactic plane. A ~1000 deg2 survey of the

Chentao Yang, Susanne Aalto, Sabine König, Santiago Del Palacio

We here present 0.02-0.04'' resolution ALMA observation of the compact obscured nucleus (CON) of IRAS17578-0400. A dusty torus within the nucleus, approximately 4 pc in radius, has been uncovered, exhibiting a usually flat spectral index at ALMA band 3, likely due to the millimeter corona emission from the central supermassive black hole (SMBH). The dense ga

Rama Adithya Varanasi, Nitesh Goyal

Recently, the AI/ML research community has indicated an urgent need to establish Responsible AI (RAI) values and practices as part of the AI/ML lifecycle. Several organizations and communities are responding to this call by sharing RAI guidelines. However, there are gaps in awareness, deliberation, and execution of such practices for multi-disciplinary ML pr

Ido Hadi, Tamir Bendory, Nir Sharon

In synchronization problems, the goal is to estimate elements of a group from noisy measurements of their ratios. A popular estimation method for synchronization is the spectral method. It extracts the group elements from eigenvectors of a block matrix formed from the measurements. The eigenvectors must be projected, or "rounded", onto the group. The roundin

Donglai Ma, Jacob Bortnik, Qianli Ma, Man Hua

We investigate the response of outer radiation belt electron fluxes to different solar wind and geomagnetic indices using an interpretable machine learning method. We reconstruct the electron flux variation during 19 enhancement and 7 depletion events and demonstrate a feature attribution analysis on the superposed epoch results for the first time. We find t

Ulderico Dardano, Fausto De Mari

We consider a very weak chain condition for a poset, that is the absence of subsets which are order isomorphic to the set of real numbers in their natural ordering; we study generalised radical groups in which this finiteness condition is set on the poset of subgroups which do not have certain properties which are generalizations of normality. This completes

Hlib Kupianskyi, Simon A. R. Horsley, David B. Phillips

When light propagates through a complex medium, such as a multimode optical fibre (MMF), the spatial information it carries is scrambled. In this work we experimentally demonstrate an all-optical strategy to unscramble this light again. We first create a digital model capturing the way light has been scattered, and then use this model to inverse-design and b

Rama Adithya Varanasi, Shulong Yan, Dhavni Toprani, Marcela Borge

The role of design in K-12 education has increased in recent years. We argue that many of these design experiences do not help develop important habits of mind associated with Human Centered Design (HCD). In this paper, we present an approach for developing higher-order thinking processes associated with HCD as part of embedded design practice - an approach

M. J. Ablowitz, J. T. Cole

A two-dimensional honeycomb lattice composed of gyrotropic rods is studied. Beginning with Maxwell's equations, a perturbed Wannier method is introduced which yields a tight-binding model with nearest and next-nearest neighbors. The resulting discrete model leads to a Haldane model and as such, topologically protected modes, associated with nonzero Chern num

Akanksha Y. Gavade, Annie Sidotam, Rama Adithya Varanasi

Support plays a vital role in the teaching profession. A good support system can empower teachers to regulate their emotions and effectively manage stress while working in isolation. The COVID-19 pandemic has ushered in a hybrid form of education, necessitating the acquisition of new skills by teachers and compelling them to adapt to remote teaching. This ne

Tuo Wang, Teresa A. Kent, Sarah Bergbreiter

This research develops a novel sensor for aquatic robots inspired by the whiskers of harbor seals. This sensor can detect the movement of water, offering valuable data on speed, currents, barriers, and water disturbance. It employs a mechano-magnetic system, separating the whisker-like drag part from the electronic section, enhancing water resistance and dur

Zifeng Ding, Jingcheng Wu, Jingpei Wu, Yan Xia

Stemming from traditional knowledge graphs (KGs), hyper-relational KGs (HKGs) provide additional key-value pairs (i.e., qualifiers) for each KG fact that help to better restrict the fact validity. In recent years, there has been an increasing interest in studying graph reasoning over HKGs. Meanwhile, as discussed in recent works that focus on temporal KGs (T

Omer Reingold, Judy Hanwen Shen, Aditi Talati

While explainability is a desirable characteristic of increasingly complex black-box models, modern explanation methods have been shown to be inconsistent and contradictory. The semantics of explanations is not always fully understood - to what extent do explanations "explain" a decision and to what extent do they merely advocate for a decision? Can we help

Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova

We introduce CoTracker, a transformer-based model that tracks a large number of 2D points in long video sequences. Differently from most existing approaches that track points independently, CoTracker tracks them jointly, accounting for their dependencies. We show that joint tracking significantly improves tracking accuracy and robustness, and allows CoTracke

Sourav Chatterjee

A longstanding open question in the theory of disordered systems is whether short-range models, such as the random field Ising model or the Edwards-Anderson model, can indeed have the famous properties that characterize mean-field spin glasses at nonzero temperature. This article shows that this is at least partially possible in the case of the random field

Jean Elsner

Franka Emika robots have gained significant popularity in research and education due to their exceptional versatility and advanced capabilities. This work introduces panda-py - a Python interface and framework designed to empower Franka Emika robotics with accessible and efficient programming. The panda-py interface enhances the usability of Franka Emika rob

Aziza Gouda, H. Nabiel

The aim of this article is to introduce the concept of centrally-extended Jordan endomorphisms and proving that if $R$ is a non-commutative prime ring of characteristic not two, and $G$ is a CE- Jordan epimorphism such that $[G(x), x] \in Z(R)$ ($[G(x), x^*] \in Z(R)$) for all $x \in R$, then $R$ is an order in a central simple algebra of dimension at most $

Francesco Marchetti

Cross validation is an important tool in the RBF collocation setting, especially for the crucial tuning of the shape parameter related to the radial basis function. In this paper, we define a new efficient surrogate cross validation algorithm, which computes an accurate approximation of the true validation error with much less computational effort with respe

Davide Giacomini, Maeesha Binte Hashem, Jeremiah Suarez, Swarup Bhunia

The rapid advancement of deep neural networks has significantly improved various tasks, such as image and speech recognition. However, as the complexity of these models increases, so does the computational cost and the number of parameters, making it difficult to deploy them on resource-constrained devices. This paper proposes a novel memorization-based infe

Lee Peleg, David Schwerdt, Jonathan Nemirovsky, Yotam Shapira

Quantum computers based on crystals of trapped ions are a prominent technology for quantum computation. A unique feature of trapped ions is their long-range Coulomb interactions, which can be exploited to realize large-scale multiqubit entanglement gates. However, scaling up the number of qubits, $N$, in these systems, while retaining high-fidelity and high-

John R. Thorstensen, Chase K. Alvarado-Anderson, Abigail D. Burrows, Rowan M. Goebel-Bain

We report spectroscopic observations of seven bright southern cataclysmic variable stars, collected on a single two-week observing run using the 1.9-m Radcliffe telescope at the South African Astronomical Observatory. We used radial velocity time series, in some cases in combination with other data, to determine or clarify orbital periods for five of them, n

Han Wang

We study the design of contracts that incentivize a researcher to conduct a costly experiment, extending the work of Yoder (2022) from binary states to a general state space. The cost is private information of the researcher. When the experiment is observable, we find the optimal contract and show that higher types choose more costly experiments, but not nec

Marianna B. Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia

Nudging is a behavioral strategy aimed at influencing people's thoughts and actions. Nudging techniques can be found in many situations in our daily lives, and these nudging techniques can targeted at human fast and unconscious thinking, e.g., by using images to generate fear or the more careful and effortful slow thinking, e.g., by releasing information tha

Noah Greenberg, Brendan M. White, Pei Jiang Low, Crystal Senko

Trapped ions have emerged as a front runner in quantum information processing due to their identical nature, all-to-all connectivity, and high fidelity quantum operations. As current trapped ion technologies are scaled, it will be important to improve the efficiency of loading ions, which is currently the slowest process in operating a trapped ion quantum co

Davide Macera

In [10] Jitomirskaya, Kr\"uger and Liu analysed the dynamical decay in expectation for the super-critical almost-Mathieu operator in function of the coupling parameter , showing that it is equal to the Lyapunov exponent of its transfer matrix cocycle, and asked whether the same is true for the 1d Anderson model. We show that this is essentially never true wh

Frederic Koehler, Noam Lifshitz, Dor Minzer, Elchanan Mossel

The theory of influences in product measures has profound applications in theoretical computer science, combinatorics, and discrete probability. This deep theory is intimately connected to functional inequalities and to the Fourier analysis of discrete groups. Originally, influences of functions were motivated by the study of social choice theory, wherein a

Xiang Guo, Arash Tavakoli, T. Donna Chen, Arsalan Heydarian

The National Highway Traffic Safety Administration reported that the number of bicyclist fatalities has increased by more than 35% since 2010. One of the main reasons associated with cyclists' crashes is the adverse effect of high cognitive load due to distractions. However, very limited studies have evaluated the impact of secondary tasks on cognitive distr

Conrado da Costa, Jonathon Peterson, Yongjia Xie

Random Walks in Cooling Random Environments (RWCRE) is a model of random walks in dynamic random environments where the environment is frozen between a fixed sequence of times (called the cooling map) where it is resampled. Naturally the limiting distributions for this model depend both on the structure of the cooling sequence and on distribution $\mu$ from

Leandro M. Del Pezzo, Alexander Quaas

In this article, we find the fundamental solution of the fractional p-laplacian and use them to prove two different Liouville-type theorems. A non-existence classical Liouville-type theorem for p-superharmonic and a Louville type results for an Emden-Folder type equation with the fractional p-laplacian.

Yeti Z. Gurbuz, A. Aydin Alatan

Global average pooling (GAP) is a popular component in deep metric learning (DML) for aggregating features. Its effectiveness is often attributed to treating each feature vector as a distinct semantic entity and GAP as a combination of them. Albeit substantiated, such an explanation's algorithmic implications to learn generalizable entities to represent unse

Roland Bauerschmidt, Thierry Bodineau, Benoit Dagallier

This introduction surveys a renormalisation group perspective on log-Sobolev inequalities and related properties of stochastic dynamics. We also explain the relationship of this approach to related recent and less recent developments such as Eldan's stochastic localisation and the F\"ollmer process, the Bou\'e--Dupuis variational formula and the Barashkov--G

Nabeel Rehemtulla, Adam A. Miller, Michael W. Coughlin, Theophile Jegou du Laz

The Bright Transient Survey (BTS) relies on visual inspection ("scanning") to select sources for accomplishing its mission of spectroscopically classifying all bright extragalactic transients found by the Zwicky Transient Facility (ZTF). We present $\texttt{BTSbot}$, a multi-input convolutional neural network, which provides a bright transient score to indiv

Shixiao W. Jiang, Rongji Li, Qile Yan, John Harlim

In this paper, we extend the Generalized Finite Difference Method (GFDM) on unknown compact submanifolds of the Euclidean domain, identified by randomly sampled data that (almost surely) lie on the interior of the manifolds. Theoretically, we formalize GFDM by exploiting a representation of smooth functions on the manifolds with Taylor's expansions of polyno

Arpit Bhardwaj, Phanish Suryanarayana

We study the influence of mechanical deformations on the Zeeman and Rashba effects in synthesized transition metal dichalcogenide (TMD) nanotubes and their Janus variants from first principles. In particular, we perform symmetry-adapted density functional theory simulations with spin-orbit coupling to determine the variation in the Zeeman and Rashba splittin

Sebastian Dalleiger, Jilles Vreeken

Addressing the interpretability problem of NMF on Boolean data, Boolean Matrix Factorization (BMF) uses Boolean algebra to decompose the input into low-rank Boolean factor matrices. These matrices are highly interpretable and very useful in practice, but they come at the high computational cost of solving an NP-hard combinatorial optimization problem. To red

Valdemar Švábenský, Ryan S. Baker, Andrés Zambrano, Yishan Zou

Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and students may l

Anika Götz, Martin Hohenadler, Fakher F. Assaad

We study a Su-Schrieffer-Heeger electron-phonon model on a square lattice by means of auxiliary-field quantum Monte Carlo simulations. The addition of a symmetry-allowed interaction permits analytical integration over the phonons at the expense of discrete Hubbard-Stratonovich fields with imaginary-time correlations. Using single-spin-flip and global updates

Xi Chen, Jong E. Han

A fundamental instability in the nonequilibrium conduction band under a electric field bias is proposed via the spontaneous emission of coherent phonons. Analytic theory, supported by numerical calculations, establishes that the quantum avalanche, an abrupt nonequilibrium occupation of excited bands, results from the competition between the collapse of the b

Mohamed Kamel Riahi

In this paper, we introduce novel fast matrix inversion algorithms that leverage triangular decomposition and recurrent formalism, incorporating Strassen's fast matrix multiplication. Our research places particular emphasis on triangular matrices, where we propose a novel computational approach based on combinatorial techniques for finding the inverse of a g

Blake Anderson, David McGrew

Cloud providers' support for network evasion techniques that misrepresent the server's domain name is more prevalent than previously believed, which has serious implications for security and privacy due to the reliance on domain names in common security architectures. Domain fronting is one such evasive technique used by privacy enhancing technologies and ma

Santosh Adhikari, Christopher J. Bartel, Christopher Sutton

This study investigates the use of machine learning (ML) to correct the enthalpy of formation (Hf) from two separate DFT functionals, PBE and SCAN, to the experimental Hf across 1011 solid-state compounds. The ML model uses a set of 25 properties that characterize the electronic structure as calculated using PBE and SCAN. The ML model significantly decreases

Lydia Kraus, Valdemar Švábenský, Martin Horák, Vashek Matyáš

As cyber threats endanger everyone, from regular users to computing professionals, spreading cybersecurity awareness becomes increasingly critical. Therefore, our university designed an innovative cybersecurity awareness course that is freely available online for students, employees, and the general public. The course offers simple, actionable steps that any

Shibo Zhao, Yuanjun Gao, Tianhao Wu, Damanpreet Singh

Simultaneous localization and mapping (SLAM) is a fundamental task for numerous applications such as autonomous navigation and exploration. Despite many SLAM datasets have been released, current SLAM solutions still struggle to have sustained and resilient performance. One major issue is the absence of high-quality datasets including diverse all-weather cond

Alex Saad-Falcon, Christopher Howard, Justin Romberg, Kenneth Allen

Global optimization techniques are increasingly preferred over human-driven methods in the design of electromagnetic structures such as metasurfaces, and careful construction and parameterization of the physical structure is critical in ensuring computational efficiency and convergence of the optimization algorithm to a globally optimal solution. While many

Wei Liu, Qihang Lin, Yangyang Xu

Many recent studies on first-order methods (FOMs) focus on \emph{composite non-convex non-smooth} optimization with linear and/or nonlinear function constraints. Upper (or worst-case) complexity bounds have been established for these methods. However, little can be claimed about their optimality as no lower bound is known, except for a few special \emph{smoo

Naty Peter, Eliad Tsfadia, Jonathan Ullman

Fingerprinting arguments, first introduced by Bun, Ullman, and Vadhan (STOC 2014), are the most widely used method for establishing lower bounds on the sample complexity or error of approximately differentially private (DP) algorithms. Still, there are many problems in differential privacy for which we don't know suitable lower bounds, and even for problems

Dibya Nath, G. M. Shahariar

Gastrointestinal diseases pose significant healthcare chall-enges as they manifest in diverse ways and can lead to potential complications. Ensuring precise and timely classification of these diseases is pivotal in guiding treatment choices and enhancing patient outcomes. This paper introduces a novel approach on classifying gastrointestinal diseases by leve

Abdel Zaro, Ardalan Tajbakhsh, Aaron M. Johnson

This paper presents a novel and efficient collision checking approach called Updating and Collision Check Skipping Quad-tree (USQ) for multi-robot motion planning. USQ extends the standard quad-tree data structure through a time-efficient update mechanism, which significantly reduces the total number of collision checks and the collision checking time. In ad

Jörg Endrullis, Roy Overbeek

We refine the weighted type graph technique for proving termination of double pushout (DPO) graph transformation systems. We increase the power of the approach for graphs, we generalize the technique to other categories, and we allow for variations of DPO that occur in the literature.

Leon Trapman, Giovanni Rosotti, Ke Zhang, Benoit Tabone

It remains unclear what mechanism is driving the evolution of protoplanetary disks. Direct detection of the main candidates, either turbulence driven by magnetorotational instability or magnetohydrodynamical disk winds, has proven difficult, leaving the time evolution of the disk size as one of the most promising observables able to differentiate between the

Aurelien Le Bail, Emanuele Daddi, David Elbaz, Mark Dickinson

We investigate the morphology and resolved physical properties of a sample of 22 IR-selected DSFG at cosmic noon using the JWST/NIRCam images obtained in the EGS field for the CEERS survey. The resolution of the NIRCam images allowed to spatially resolve these galaxies up to 4.4um and identify their bulge even when extinguished by dust. The goal of this stud

Elyar Sedaghati, Andrés Jordán, Rafael Brahm, Diego J. Muñoz

Warm Jupiters lay out an excellent laboratory for testing models of planet formation and migration. Their separation from the host star makes tidal reprocessing of their orbits ineffective, which preserves the orbital architectures that result from the planet-forming process. Among the measurable properties, the orbital inclination with respect to the stella

WT Al-shaibani, Tareq Babaqi, Abdulraqeeb Alsarori

The use of steel is essential in many industries, including infrastructure, transportation, and modern architecture. Predicting power consumption in the steel industry is crucial to meet the rising demand for steel and promoting city development. However, predicting energy consumption in the steel industry is challenging due to several factors, such as the t

Katharina Klioba, Mark Veraar

In this paper, we prove convergence for contractive time discretisation schemes for semi-linear stochastic evolution equations with irregular Lipschitz nonlinearities, initial values, and additive or multiplicative Gaussian noise on $2$-smooth Banach spaces $X$. The leading operator $A$ is assumed to generate a strongly continuous semigroup $S$ on $X$, and t

Tobias Schröder, Zijing Ou, Yingzhen Li, Andrew B. Duncan

Training energy-based models (EBMs) on discrete spaces is challenging because sampling over such spaces can be difficult. We propose to train discrete EBMs with energy discrepancy (ED), a novel type of contrastive loss functional which only requires the evaluation of the energy function at data points and their perturbed counter parts, thus not relying on sa

Maria Laura Piscopo, Aleksey Rusov

In light of the current discrepancies between the recent predictions based on QCD factorisation (QCDF) and the experimental data for several non-leptonic colour-allowed two-body $B$-meson decays, we obtain new determinations of the non-factorisable soft-gluon contribution to the decays $\bar B_{s}^0 \to D_{s}^+ \pi^-$ and $\bar B^0 \to D^+ K^-$, using the fr

L. Huang, Z. Y. Tu, N. Chang, F. F. Song

We obtain a new sample of 1192 Type I quasars with the UV-optical, radio and X-ray wavebands coverage by combining \citet{Huang2022} and other matching data of SDSS-DR16 with FIRST, XMM-Newton, and Chandra Source Catalog, and a sample of 407 flat-spectrum radio-loud quasars (FSRLQs) of blazars from the Roma-BZCAT, which can be used to investigate their multi

Jérôme Pétri

(Abridged) Following particle trajectories in the intense electromagnetic field of a neutron star is prohibited by the large ratio between the cyclotron frequency $\omega_{\rm B}$ and the stellar rotation frequency $\Omega$. No fully kinetic simulations on a macroscopic scale and with realistic field strengths have been performed so far due to the huge compu

Joan Hernández

In the present paper we characterize the $(1/2,+)$-caloric capacity (associated with the $1/2$-fractional heat equation) of the usual corner-like Cantor set of $\mathbb{R}^{n+1}$. The results obtained for the latter are analogous to those found for Newtonian capacity. Moreover, we also characterize the BMO and $\text{Lip}_\alpha$ variants ($0<\alpha<1$) of t

Mina Huh, Yi-Hao Peng, Amy Pavel

Blind and low vision (BLV) creators use images to communicate with sighted audiences. However, creating or retrieving images is challenging for BLV creators as it is difficult to use authoring tools or assess image search results. Thus, creators limit the types of images they create or recruit sighted collaborators. While text-to-image generation models let

C. Abel, N. J. Ayres, G. Ban, G. Bison

We present a novel Active Magnetic Shield (AMS), designed and implemented for the n2EDM experiment at the Paul Scherrer Institute. The experiment will perform a high-sensitivity search for the electric dipole moment of the neutron. Magnetic-field stability and control is of key importance for n2EDM. A large, cubic, 5m side length, magnetically shielded room

Matthew Rosenzweig, Sylvia Serfaty

We consider mean-field limits for overdamped Langevin dynamics of $N$ particles with possibly singular interactions. It has been shown that a modulated free energy method can be used to prove the mean-field convergence or propagation of chaos for a certain class of interactions, including Riesz kernels. We show here that generation of chaos, i.e. exponential

Sajad Sotudeh, Nazli Goharian

Query-focused summarization (QFS) is a challenging task in natural language processing that generates summaries to address specific queries. The broader field of Generative Information Retrieval (Gen-IR) aims to revolutionize information extraction from vast document corpora through generative approaches, encompassing Generative Document Retrieval (GDR) and

Massimo Tinto, Sanjeev Dhurandhar

Time-Delay Interferometry (TDI) is the data processing technique that cancels the large laser phase fluctuations affecting the one-way Doppler measurements made by unequal-arm space-based gravitational wave interferometers. In a previous publication we derived TDI combinations that exactly cancel the laser phase fluctuations up to first order in the inter-sp

ATLAS Collaboration

A search for the single production of a vector-like top partner ($T$) with mass greater than 1 TeV decaying into a $Z$ boson and a top quark is presented, using the full Run 2 dataset corresponding to 139 fb$^{-1}$ of $pp$ collisions at $\sqrt{s}$ = 13 TeV, collected in 2015-2018 with the ATLAS detector at the Large Hadron Collider. The targeted final state

Amir Abboud, Mina Dalirrooyfard, Ray Li, Virginia Vassilevska-Williams

Computing the diameter of a graph, i.e. the largest distance, is a fundamental problem that is central in fine-grained complexity. In undirected graphs, the Strong Exponential Time Hypothesis (SETH) yields a lower bound on the time vs. approximation trade-off that is quite close to the upper bounds. In \emph{directed} graphs, however, where only some of the

Abhiroop Satheesh, Christoph P. Schmidt, Wolfgang A. Wall, Christoph Meier

The accuracy of finite element solutions is closely tied to the mesh quality. In particular, geometrically nonlinear problems involving large and strongly localized deformations often result in prohibitively large element distortions. In this work, we propose a novel mesh regularization approach allowing to restore a non-distorted high-quality mesh in an ada

M. Borst, P. H. Vree, A. Lowther, A. Teepe

Superconductors are materials with zero electrical resistivity and the ability to expel magnetic fields known as the Meissner effect. Their dissipationless diamagnetic response is central to magnetic levitation and circuits such as quantum interference devices. Here, we use superconducting diamagnetism to shape the magnetic environment governing the transpor

David Pérez-Piñeiro, Sigurd Skogestad, Stephen Boyd

We consider the problem of operating a battery in a home connected to the grid to minimize electricity cost, which combines an energy charge and a tiered peak power charge based on the average of the $N$ largest daily peak powers in each billing month. With perfect foresight of loads and prices, the minimum cost is the solution of a mixed-integer linear prog

Haojing Yan, Zhiyuan Ma, Bangzheng Sun, Lifan Wang

With its unprecedented sensitivity and spatial resolution, the James Webb Space Telescope (JWST) has opened a new window for time-domain discoveries in the infrared. Here we report observations in the only field that has received four epochs (spanning 126 days) of JWST NIRCam observations in Cycle 1. This field is towards MACS J0416.1-2403, which is a rich g

Debajyoti Choudhury, Diganta Das, Jaydeb Das

We calculate QED corrections to the semileptonic decays $H_1 \to H_2\ell^+\ell^-$ where $\ell=e, \mu$ and $H_{1,2}$ are hadrons. The soft and/or collinear divergences are regulated in a gauge-invariant manner and demonstrably cancel, leaving behind a finite residue that depends on the (infrared) momentum cutoff below which a photon is considered to be indist

Krish Matta, Xiaoyuan Liu, Ilya Safro

The shortest path network interdiction (SPNI) problem poses significant computational challenges due to its NP-hardness. Current solutions, primarily based on integer programming methods, are inefficient for large-scale instances. In this paper, we introduce a novel hybrid algorithm that can utilize Ising Processing Units (IPUs) alongside classical solvers.

R. Abbasi, M. Ackermann, J. Adams, S. K. Agarwalla

The Galactic plane, harboring a diffuse neutrino flux, is a particularly interesting target to study potential cosmic-ray acceleration sites. Recent gamma-ray observations by HAWC and LHAASO have presented evidence for multiple Galactic sources that exhibit a spatially extended morphology and have energy spectra continuing beyond 100 TeV. A fraction of such

Ryan Pyle, Sebastian Musslick, Jonathan D. Cohen, Ankit B. Patel

A key property of neural networks (both biological and artificial) is how they learn to represent and manipulate input information in order to solve a task. Different types of representations may be suited to different types of tasks, making identifying and understanding learned representations a critical part of understanding and designing useful networks.

Xiaorui Zhu, Yichen Qin, Peng Wang

Statistical inference of the high-dimensional regression coefficients is challenging because the uncertainty introduced by the model selection procedure is hard to account for. A critical question remains unsettled; that is, is it possible and how to embed the inference of the model into the simultaneous inference of the coefficients? To this end, we propose

Jaike van Twiller, Agnieszka Sivertsen, Dario Pacino, Rune Møller Jensen

Container shipping drives the global economy and is an eco-friendly mode of transportation. A key objective is to maximize the utilization of vessels, which is challenging due to the NP-hardness of stowage planning. This article surveys the literature on the Container Stowage Planning Problem (CSPP). We introduce a classification scheme to analyze single-por

Cheng Shi, Giulio Poggiali, Chris Marone, Maarten V. de Hoop

Earthquake science and seismology rely on the ability to associate seismic waves with their originating earthquakes. Earthquake detection algorithms based on deep learning have progressed rapidly and now routinely detect microearthquakes with unprecedented clarity, providing information about fault dynamics on increasingly finer spatiotemporal scales. Howeve

Condori Condori Nelyda Ayde, Mamani Mamani Ilma Magda, Cruz Paredes Soledad Epifania, Torres-Cruz Fred

Abstract Cancer is a tumor that affects people worldwide, with a higher incidence in females but not excluding males. It ranks among the top five deadliest types of cancer, particularly prevalent in less developed countries with deficient healthcare programs. Finding the best algorithm for effective breast cancer prediction with minimal error is crucial. In

M. Barrios, G. Mata

In this article, we prove that, under certain conditions, Morita context algebras that arise from Igusa-Todorov (LIT) algebras and have zero bimodule morphisms are also Igusa-Todorov (LIT). For a finite dimensional algebra $A$, we prove that the class $\phi_0^{-1}(A) = \{M: \phi(M)=0\}$ is a 0-Igusa-Todorov subcategory if and only if $A$ is selfinjective or

Simon Guilloud, Viktor Kuncak

We study the proof theory and algorithms for orthologic, a logical system based on ortholattices, which have shown practical relevance in simplification and normalization of verification conditions. Ortholattices weaken Boolean algebras while having polynomial-time equivalence checking that is sound with respect to Boolean algebra semantics. We generalize or

Alexander A. Alemi, Ben Poole

Bayesian inference offers benefits over maximum likelihood, but it also comes with computational costs. Computing the posterior is typically intractable, as is marginalizing that posterior to form the posterior predictive distribution. In this paper, we present variational prediction, a technique for directly learning a variational approximation to the poste

Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann

Finding diverse solutions to optimization problems has been of practical interest for several decades, and recently enjoyed increasing attention in research. While submodular optimization has been rigorously studied in many fields, its diverse solutions extension has not. In this study, we consider the most basic variants of submodular optimization, and prop

Mohammad Muntasir Rahman, Amirtahà Taebi

This pilot study aims to develop a deep learning model for predicting seismocardiogram (SCG) signals in the dorsoventral direction from the SCG signals in the right-to-left and head-to-foot directions ($\textrm{SCG}_x$ and $\textrm{SCG}_y$). The dataset used for the training and validation of the model was obtained from 15 healthy adult subjects. The SCG sig

Andrea Ghira

In this work we present a new approach to threshold resummation in processes with heavy quarks. In particular we will focus on the differential decay rate of a color-singlet particle into a $b \bar b$ pair and we will show how to resum in a consistent way both the logarithms of the mass and the logarithms of the heavy flavor energy fraction. Within this fram

Annika Lang, Ioanna Motschan-Armen

The stochastic heat equation on the sphere driven by additive isotropic Wiener noise is approximated by a spectral method in space and forward and backward Euler-Maruyama schemes in time. The spectral approximation is based on a truncation of the series expansion with respect to the spherical harmonic functions. Optimal strong convergence rates for a given r

Navneet Roshan, Rahul Pandit

Disturbances in calcium homeostasis in a cardiac myocyte can lead to calcium-overload conditions and abnormal calcium releases, which occur primarily in the following two phases of the action potential (AP): (a) triggered or late calcium release (LCR) during the plateau phase; (b) spontaneous calcium release (SCR) during the diastolic interval (DI). Experime

Anshuman Bhardwaj, Ivan Agullo, Dimitrios Kranas, Justin H. Wilson

Recent experiments have employed rapidly expanding toroidal Bose-Einstein condensates (BECs) to mimic the inflationary expansion in the early universe. One expected signature of the expansion in such experiments is spontaneous particle creation (of phonons) which is observable in density-density correlations. We study entanglement of these particles, which a

Martin Groenewegen, Jan Lub

(abridged) In this study, we constructed spectral energy distributions (SEDs) for a sample of 142 LMC and 77 SMC fundamental-mode classical Cepheids (CCs) using photometric data from the literature. When possible, the data were taken to be representative of mean light or averaged over the light curve. The sample was built from stars that either have a metall

Xinyang Wang, Igor A. Shovkovy

We study the higher-order anisotropy coefficients $v_4$ and $v_6$ in the photon and dilepton emission from a hot magnetized quark-gluon plasma. Together with the earlier predictions for $v_2$, these results show a distinctive pattern of the anisotropy coefficients in several kinematic regimes. In the case of photon emission, nonzero coefficients $v_n$ (with

Leander Thiele, Elena Massara, Alice Pisani, ChangHoon Hahn

Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, $\sum m_\nu$, promise to benefit from the inclusion of void statistics. We perform inference on the CMASS NGC sample of SDSS-III/BOSS with the aim of constraining $\sum m_\nu$. We util

Zijian Zhang, Bin Luo, W. N. Brandt, Pu Du

We report \hbox{XMM-Newton} observations of two examples of an unclassified type of \hbox{X-ray} weak quasars from the \citet{2020ApJ...900..141P} survey of \hbox{X-ray} weak quasars in the Chandra archive, SDSS J083116.62+321329.6 at $z=1.797$ and SDSS J142339.87+042041.1 at $z=1.702$. They do not belong to the known populations of \hbox{X-ray} weak quasars

Takeshi Kobayashi, Daniele Perri

We present a comprehensive study of Parker-type bounds on magnetic monopoles with arbitrary magnetic charge, including minicharged monopoles and magnetic black holes. We derive the bounds based on the survival of galactic magnetic fields, seed magnetic fields, as well as primordial magnetic fields. We find that monopoles with different magnetic charges are b

Oles Shtanko, Derek S. Wang, Haimeng Zhang, Nikhil Harle

Interacting many-body quantum systems and their dynamics, while fundamental to modern science and technology, are formidable to simulate and understand. However, by discovering their symmetries, conservation laws, and integrability one can unravel their intricacies. Here, using up to 124 qubits of a fully programmable quantum computer, we uncover local conse

David Nagy, Miroslava Dessauges-Zavadsky, Matteo Messa, Johan Richard

We study the star formation rate (SFR) versus molecular gas mass ($M_\mathrm{mol}$) scaling relation from hundreds to thousands parsec scales in two strongly lensed galaxies at redshift $z\sim 1$, the Cosmic Snake and A521. We trace SFR using extinction-corrected rest-frame UV observations with the Hubble Space Telescope (HST), and $M_\mathrm{mol}$ using det