November 2022 arXiv papers — page 10

A. Saccardi, S. D. Vergani, A. De Cia, V. D'Elia

The study of the properties of galaxies in the first billion years after the Big Bang is one of the major topic of current astrophysics. Optical/near-infrared spectroscopy of the afterglows of long Gamma-ray bursts (GRBs) provide a powerful diagnostic tool to probe the interstellar medium (ISM) of their host galaxies and foreground absorbers, even up to the

Newlin C. Weatherford, Fulya Kıroğlu, Giacomo Fragione, Sourav Chatterjee

The theory of stellar escape from globular clusters (GCs) dates back nearly a century, especially the gradual evaporation of GCs via two-body relaxation coupled with external tides. More violent ejection can also occur via strong gravitational scattering, supernovae, gravitational wave-driven mergers, tidal disruption events, and physical collisions, but com

Diana B. Chamaki, Stuart Hadfield, Katherine Klymko, Bryan O'Gorman

It is crucial to reduce the resources required to run quantum algorithms and simulate physical systems on quantum computers due to coherence time limitations. With regards to Hamiltonian simulation, a significant effort has focused on building efficient algorithms using various factorizations and truncations, typically derived from the Hamiltonian alone. We

M. J. Jiménez-Donaire, T. Brown, C. D. Wilson, I. D. Roberts

In this VERTICO science paper we aim to study how the star formation process depends on galactic environment and gravitational interactions in the context of galaxy evolution. We explore the scaling relation between the star formation rate (SFR) surface density and the molecular gas surface density, also known as the Kennicutt-Schmidt (KS) relation, in a sub

Thomas Rink, Manibrata Sen

Neutrinos can be pseudo-Dirac in Nature - they can be Majorana fermions while behaving effectively as Dirac fermions. Such scenarios predict active-sterile neutrino oscillations driven by a tiny mass-squared difference $(\delta m^2)$, which is an outcome of soft lepton number violation. Oscillations due to tiny $\delta m^2$ can only take place over astrophys

Stefano Baiguera, Troels Harmark, Yang Lei

Spin Matrix theory describes near-BPS limits of $\mathcal{N}=4$ SYM theory, which enables us to probe finite $N$ effects like D-branes and black hole physics. In previous works, we have developed the spherical reduction and spin chain methods to construct Spin Matrix theory for various limits. In this paper, by considering a supercharge $\mathcal{Q}$ which i

Yaroslav Herasymenko, Maarten Stroeks, Jonas Helsen, Barbara Terhal

We consider the problem of approximating the ground state energy of a fermionic Hamiltonian using a Gaussian state. In sharp contrast to the dense case, we prove that strictly $q$-local $\rm {\textit {sparse}}$ fermionic Hamiltonians have a constant Gaussian approximation ratio; the result holds for any connectivity and interaction strengths. Sparsity means

Céline Péroux, Simon Weng, Arjun Karki, Ramona Augustin

The gas cycling in the circumgalactic regions of galaxies is known to be multi-phase. The MUSE-ALMA Haloes survey gathers a large multi-wavelength observational sample of absorption and emission data with the goal to significantly advance our understanding of the physical properties of such CGM gas. A key component of the MUSE-ALMA Haloes survey is the multi

Markus Michael Rau, Roohi Dalal, Tianqing Zhang, Xiangchong Li

We present posterior sample redshift distributions for the Hyper Suprime-Cam Subaru Strategic Program Weak Lensing three-year (HSC Y3) analysis. Using the galaxies' photometry and spatial cross-correlations, we conduct a combined Bayesian Hierarchical Inference of the sample redshift distributions. The spatial cross-correlations are derived using a subsample

Zi-Yu Dong, Teng Ma, Jing Shu, Zi-Zheng Zhou

We present the explicit construction of the effective field theory (EFT) of standard model mass eigenstates. The EFT, which is invariant under $U(1)_{\text{e.m.}}\times SU(3)_c$, is constructed based on the on-shell method and Young Tableau technique. This EFT serves as a new formulation of the Higgs EFT (HEFT), which can describe the infrared effects of new

Domingo Gallegos, Umut Gursoy, Natale Zinnato

We generalize Gopakumar's microscopic derivation of Witten diagrams in large N free quantum field theory [1] to interacting theories in perturbative expansion. For simplicity we consider a matrix scalar field with $\Phi^h$ interaction in d dimensions. Using Schwinger's proper time formulation and organizing the sum over Feynman diagrams by the number of loop

Jacopo Ghiglieri, Jan Schütte-Engel, Enrico Speranza

The thermal plasma in the early universe produced a stochastic gravitational wave (GW) background, which peaks today in the microwave regime and was dubbed the cosmic gravitational microwave background (CGMB). In previous works only single graviton production processes that contribute to the CGMB have been considered. Here we also investigate graviton pair p

Jan de Boer, Daniel Louis Jafferis, Lampros Lamprou

We propose a CFT definition of local observables in both the exterior and interior of bulk black holes, whenever such an interior exists. We achieve this by introducing a small microcanonical black hole as a "probe" and using its modular flow to propagate operators from the asymptotic boundary to the interior of other black holes along its worldline, elabora

Shuquan Ye, Yujia Xie, Dongdong Chen, Yichong Xu

This paper focuses on analyzing and improving the commonsense ability of recent popular vision-language (VL) models. Despite the great success, we observe that existing VL-models still lack commonsense knowledge/reasoning ability (e.g., "Lemons are sour"), which is a vital component towards artificial general intelligence. Through our analysis, we find one i

António Antunes, Connor Behan

We study coupled unitary Virasoro minimal models in the large rank ($m \rightarrow \infty$) limit. In large $m$ perturbation theory, we find two non-trivial IR fixed points which exhibit irrational coefficients in several anomalous dimensions and the central charge. For $N>4$ copies, we show that the IR theory breaks all possible currents that would otherwis

Rob Trangucci, Yang Chen, Jon Zelner

In order to meet regulatory approval, pharmaceutical companies often must demonstrate that new vaccines reduce the total risk of a post-infection outcome like transmission, symptomatic disease, severe illness, or death in randomized, placebo-controlled trials. Given that infection is a necessary precondition for a post-infection outcome, one can use principa

Luigi Castiglioni, Silvia Penati, Marcia Tenser, Diego Trancanelli

We study new $1/24$ BPS circular Wilson loops in ABJ(M) theory, which are defined in terms of several parameters that continuously interpolate between previously known $1/6$ BPS loops (both bosonic and fermionic) and $1/2$ BPS fermionic loops. We compute the expectation value of these operators up to second order in perturbation theory using a one-dimensiona

Tianqi Wu

Many real-world networks exhibit the so-called small-world phenomenon: their typical distances are much smaller than their sizes. One mathematical model for this phenomenon is a long-range percolation graph on a $d$-dimensional box $\{0, 1, \cdots, N\}^d$, in which edges are independently added between far-away sites with probability falling off as a power o

Nataniel Ruiz, Sarah Adel Bargal, Cihang Xie, Kate Saenko

Modern deep neural networks tend to be evaluated on static test sets. One shortcoming of this is the fact that these deep neural networks cannot be easily evaluated for robustness issues with respect to specific scene variations. For example, it is hard to study the robustness of these networks to variations of object scale, object pose, scene lighting and 3

Xavier Bekaert, Andrea Campoleoni, Simon Pekar

We show that, in any space-time dimension, the on-shell (electric) conformal Carrollian scalar can be interpreted as the flat-space limit of the singleton representation of the conformal algebra. In fact, a recently proposed higher-spin algebra for Minkowski spacetime amounts to the Poincar\'e enveloping algebra on the corresponding module. This higher-spin

Ayu Parmar, Spanddhana Sara, Ayush Kumar Dwivedi, C. Rajashekar Reddy

Particulate matter (PM) is considered the primary contributor to air pollution and has severe implications for general health. PM concentration has high spatial variability and thus needs to be monitored locally. Traditional PM monitoring setups are bulky, expensive and cannot be scaled for dense deployments. This paper argues for a densely deployed network

Anirudh Srinivasan, Eunsol Choi

We study politeness phenomena in nine typologically diverse languages. Politeness is an important facet of communication and is sometimes argued to be cultural-specific, yet existing computational linguistic study is limited to English. We create TyDiP, a dataset containing three-way politeness annotations for 500 examples in each language, totaling 4.5K exa

Lilas Alrahis, Johann Knechtel, Ozgur Sinanoglu

Graph neural networks (GNNs) have pushed the state-of-the-art (SOTA) for performance in learning and predicting on large-scale data present in social networks, biology, etc. Since integrated circuits (ICs) can naturally be represented as graphs, there has been a tremendous surge in employing GNNs for machine learning (ML)-based methods for various aspects of

Noam Razin, Tom Verbin, Nadav Cohen

Graph neural networks (GNNs) are widely used for modeling complex interactions between entities represented as vertices of a graph. Despite recent efforts to theoretically analyze the expressive power of GNNs, a formal characterization of their ability to model interactions is lacking. The current paper aims to address this gap. Formalizing strength of inter

S. E. Chorfi, L. Maniar, M. Yamamoto

In this paper, we consider the backward problem for fractional in time evolution equations $\partial_t^\alpha u(t)= A u(t)$ with the Caputo derivative of order $0<\alpha \le 1$, where $A$ is a self-adjoint and bounded above operator on a Hilbert space $H$. First, we extend the logarithmic convexity technique to the fractional framework by analyzing the prope

Anya Ji, Noriyuki Kojima, Noah Rush, Alane Suhr

We introduce KiloGram, a resource for studying abstract visual reasoning in humans and machines. Drawing on the history of tangram puzzles as stimuli in cognitive science, we build a richly annotated dataset that, with >1k distinct stimuli, is orders of magnitude larger and more diverse than prior resources. It is both visually and linguistically richer, mov

Frank Taipe

In the present work, we study Yetter-Drinfeld algebras over a pairing of multiplier Hopf algebras. Our main motivation is the construction of a self-dual theory of (C*-)algebraic quantum transformation groupoids. Instead of the standard characterization of Yetter-Drinfeld algebras given in the case of Hopf algebras, we develop an equivalent "only coaction" c

Tianyi Zhang, Tao Yu, Tatsunori B. Hashimoto, Mike Lewis

Sampling diverse programs from a code language model and reranking with model likelihood is a popular method for code generation but it is prone to preferring degenerate solutions. Inspired by collaborative programming, we propose Coder-Reviewer reranking. We augment Coder language models from past work, which generate programs given language instructions, w

Siwei Hu, Yu Jia, Zhewen Mo, Xiaonu Xiong

We present a detailed investigation on the intrinsic charm content in a light meson within the 't Hooft model, namely, the two-dimensional QCD in large $N_c$ limit. The intrinsic charm parton distribution function (PDF) of a light meson, which first arises at order $N_c^{-1}$, is explicitly expressed in terms of the 't Hooft wave functions of the light meson

Shimon Malnick, Shai Avidan, Ohad Fried

We propose an algorithm for taming Normalizing Flow models - changing the probability that the model will produce a specific image or image category. We focus on Normalizing Flows because they can calculate the exact generation probability likelihood for a given image. We demonstrate taming using models that generate human faces, a subdomain with many intere

Karl Holmquist, Bastian Wandt

Traditionally, monocular 3D human pose estimation employs a machine learning model to predict the most likely 3D pose for a given input image. However, a single image can be highly ambiguous and induces multiple plausible solutions for the 2D-3D lifting step which results in overly confident 3D pose predictors. To this end, we propose \emph{DiffPose}, a cond

Janice Lan, Aini Palizhati, Muhammed Shuaibi, Brandon M. Wood

Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is the need to accurately compute the adsorption energy for an adsorbate and a catalyst surface of interest. Traditionally, the identification of low energy adsorbate-surface configur

A. Basdew-Sharma, A. Pelloni, Franz Herzog, A. Vogt

We have calculated the n_f^2 and n_f^3 contributions to the flavour non-singlet structure functions F_2 and F_L in inclusive deep-inelastic scattering at the fourth order in the strong coupling alpha_s. The coefficient functions have been obtained by computing a very large number of Mellin-N moments using the method of differential equations, and then determ

Robin Piedeleu, Fabio Zanasi

We develop a fully diagrammatic approach to finite-state automata, based on reinterpreting their usual state-transition graphical representation as a two-dimensional syntax of string diagrams. In this setting, we are able to provide a complete equational theory for language equivalence, with two notable features. First, the proposed axiomatisation is finite.

Zhihong Shao, Fei Huang, Minlie Huang

Given that rich information is hidden behind ubiquitous numbers in text, numerical reasoning over text should be an essential skill of AI systems. To derive precise equations to solve numerical reasoning problems, previous work focused on modeling the structures of equations, and has proposed various structured decoders. Though structure modeling proves to b

Samuel M. Factor, Adam L. Kraus

Star formation theories have struggled to reproduce binary brown dwarf population demographics (frequency, separation, mass-ratio). Kernel-phase interferometry is sensitive to companions at separations inaccessible to classical imaging, enabling tests of formation at new physical scales below the hydrogen burning limit. We analyze the detections and sensitiv

Ashwin Rao, Fred Morstatter, Kristina Lerman

The growing prominence of social media in public discourse has led to a greater scrutiny of the quality of online information and the role it plays in amplifying political polarization. However, studies of polarization on social media platforms like Twitter have been hampered by the difficulty of collecting data about the social graph, specifically follow li

Vassilis Tsafas, Theocharis Lamprou, Emmanouil Skantzakis, Arjun Nayak

In the present work we report on the current progress of the recently constructed GW attosecond extreme ultraviolet (XUV) source developed at the Institute of Electronic Structure and Laser of the Foundation for Research and Technology-Hellas (I.E.S.L-FO.R.T.H.). By the implementation of a compact-collinear polarization gating arrangement, the generation of

Hong Li, Siyu Cheng, Brenden R. Ortiz, Hengxin Tan

Layered crystalline materials that consist of transition metal atoms on a kagome network have emerged as a versatile platform to study unusual electronic phenomena. For example, in the vanadium-based kagome superconductors AV3Sb5 (where A can stand for K, Cs, or Rb) there is a parent charge density wave phase that appears to simultaneously break both the tra

Jan Dudák, Benjamin Vejnar

It is well known due to Hahn and Mazurkiewicz that every Peano continuum is a continuous image of the unit interval. We prove that an assignment, which takes as an input a Peano continuum and produces as an output a continuous mapping whose range is the Peano continuum, can be realized in a Borel measurable way. Similarly, we find a Borel measurable assignme

Eva M. González-Ruiz, Javier Rivera-Dean, Marina F. B. Cenni, Anders S. Sørensen

Device Independent Quantum Key Distribution (DIKQD) aims at generating secret keys between distant parties without the parties trusting their devices. We investigate a proposal for performing fully photonic DIQKD, based on single-photon sources and heralding measurements at a central station placed between the two parties. We derive conditions to attain non-

David de Laat, Fabrício Caluza Machado, Willem de Muinck Keizer

We compute the second and third levels of the Lasserre hierarchy for the spherical finite distance problem. A connection is used between invariants in representations of the orthogonal group and representations of the general linear group, which allows computations in high dimensions. We give new linear bounds on the maximum number of equiangular lines in di

Miguel Abreu, Hui Liu, Leonardo Macarini

A long standing conjecture in Hamiltonian Dynamics states that every contact form on the standard contact sphere $S^{2n+1}$ has at least $n+1$ simple periodic Reeb orbits. In this work, we consider a refinement of this problem when the contact form has a suitable symmetry and we ask if there are at least $n+1$ simple symmetric periodic orbits. We show that t

Andrew Litteken, Jonathan M. Baker, Frederic T. Chong

Quantum computing promises speedup of classical algorithms in the long term. Current hardware is unable to support this goal and programs must be efficiently compiled to use of the devices through reduction of qubits used, gate count and circuit duration. Many quantum systems have access to higher levels, expanding the computational space for a device. We de

Marcel Wienöbst, Benito van der Zander, Maciej Liśkiewicz

Causal effect estimation from observational data is a fundamental task in empirical sciences. It becomes particularly challenging when unobserved confounders are involved in a system. This paper focuses on front-door adjustment -- a classic technique which, using observed mediators allows to identify causal effects even in the presence of unobserved confound

Chandler Squires, Anna Seigal, Salil Bhate, Caroline Uhler

Causal disentanglement seeks a representation of data involving latent variables that relate to one another via a causal model. A representation is identifiable if both the latent model and the transformation from latent to observed variables are unique. In this paper, we study observed variables that are a linear transformation of a linear latent causal mod

Mert Gürbüzbalaban, Yuanhan Hu, Lingjiong Zhu

We consider the constrained sampling problem where the goal is to sample from a target distribution $\pi(x)\propto e^{-f(x)}$ when $x$ is constrained to lie on a convex body $\mathcal{C}$. Motivated by penalty methods from continuous optimization, we propose penalized Langevin Dynamics (PLD) and penalized underdamped Langevin Monte Carlo (PULMC) methods that

Miao Xiong, Shen Li, Wenjie Feng, Ailin Deng

How do we know when the predictions made by a classifier can be trusted? This is a fundamental problem that also has immense practical applicability, especially in safety-critical areas such as medicine and autonomous driving. The de facto approach of using the classifier's softmax outputs as a proxy for trustworthiness suffers from the over-confidence issue

Gaurav Jain, Yuanyang Teng, Dong Heon Cho, Yunhao Xing

Navigation assistance systems (NASs) aim to help visually impaired people (VIPs) navigate unfamiliar environments. Most of today's NASs support VIPs via turn-by-turn navigation, but a growing body of work highlights the importance of exploration as well. It is unclear, however, how NASs should be designed to help VIPs explore unfamiliar environments. In this

A. J. Crilly, N. P. L. Niasse, A. R. Fraser, D. A. Chapman

SpK is part of the numerical codebase at Imperial College London used to model high energy density physics (HEDP) experiments. SpK is an efficient atomic and microphysics code used to perform detailed configuration accounting calculations of electronic and ionic stage populations, opacities and emissivities for use in post-processing and radiation hydrodynam

J. Kraśkiewicz, K. Murawski, Z. E. Musielak

We study vertical variations of wave-periods of magnetoacoustic two-fluid waves in the partially ionized lower solar atmosphere, consisting of ion (proton) + electron and neutral (atomic hydrogen) fluids, which are coupled by ion-neutral collisions. The study allows finding the wave period cutoffs and their variations in the solar atmosphere, as well as esta

Alexander Guyer, Thomas G. Dietterich

As an autonomous system performs a task, it should maintain a calibrated estimate of the probability that it will achieve the user's goal. If that probability falls below some desired level, it should alert the user so that appropriate interventions can be made. This paper considers settings where the user's goal is specified as a target interval for a real-

Yongseok Jo, Shy Genel, Benjamin Wandelt, Rachel Somerville

In a novel approach employing implicit likelihood inference (ILI), also known as likelihood-free inference, we calibrate the parameters of cosmological hydrodynamic simulations against observations, which has previously been unfeasible due to the high computational cost of these simulations. For computational efficiency, we train neural networks as emulators

Tony E. Wong, Catherine Ledna, Lisa Rennels, Hannah Sheets

Sea-level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing coastal adaptation and impacts are important tools to inform the design of strategies to manage these risks. Representing the often deep uncertainties influencing these risks poses nontrivial challenges. A common uncer

Aishik Mandal, Michaël Perrot, Debarghya Ghoshdastidar

Comparison-based learning addresses the problem of learning when, instead of explicit features or pairwise similarities, one only has access to comparisons of the form: \emph{Object $A$ is more similar to $B$ than to $C$.} Recently, it has been shown that, in Hierarchical Clustering, single and complete linkage can be directly implemented using only such com

J. M. Hoff da Silva, R. T. Cavalcanti, D. Beghetto, G. M. Caires da Rocha

Exotic spinors arise in non-simply connected base manifolds due to the nonequivalent spinor structure. The dynamics of exotic spinors are endowed with an additional differential factor. In this work, we merge the exotic spinor scenario with Cartan's spinor viewpoint, according to which a given spacetime point is understood as a kind of composition of spinor

Arya Akhavan, Davit Gogolashvili, Alexandre B. Tsybakov

We propose a new method for estimating the minimizer $\boldsymbol{x}^*$ and the minimum value $f^*$ of a smooth and strongly convex regression function $f$ from the observations contaminated by random noise. Our estimator $\boldsymbol{z}_n$ of the minimizer $\boldsymbol{x}^*$ is based on a version of the projected gradient descent with the gradient estimated

Ian M. Musson

Let $\mathtt{k}$ be an algebraically closed field of characteristic zero. Let $\mathfrak{g} $ be a finite dimensional classical simple Lie superalgebra over $\mathtt{k}$ or $\mathfrak{g} l(m,n)$. In the case that $\mathfrak{g} $ is a Kac-Moody algebra of finite type with set of roots $\Delta$, Sergeev and Veselov introduced the Weyl groupoid $\mathfrak{W}=\m

Bo Peng, Martha P. Haynes, Catie J. Ball, Michael G. Jones

Modelling the integrated H I spectra of galaxies has been a difficult task due to their diverse shapes, but more dynamical information is waiting to be explored in Hi line profiles. Based on simple assumptions, we construct a physically motivated model for the integrated Hi spectra: Parametrized Asymmetric Neutral hydrogen Disk Integrated Spectrum Characteri

Julia Gaudio, Miklós Z. Rácz, Anirudh Sridhar

We propose a simple and efficient local algorithm for graph isomorphism which succeeds for a large class of sparse graphs. This algorithm produces a low-depth canonical labeling, which is a labeling of the vertices of the graph that identifies its isomorphism class using vertices' local neighborhoods. Prior work by Czajka and Pandurangan showed that the degr

Lénaïc Chizat, Maria Colombo, Xavier Fernández-Real, Alessio Figalli

This paper studies the infinite-width limit of deep linear neural networks initialized with random parameters. We obtain that, when the number of neurons diverges, the training dynamics converge (in a precise sense) to the dynamics obtained from a gradient descent on an infinitely wide deterministic linear neural network. Moreover, even if the weights remain

B. T. Nadiga, D. N. Straub

Analyses of both altimetric data and in-situ measurements reveal patterns of meridionally-alternating, nearly zonal, coherent jet-like structures in many of the world ocean basins. In this context, recent Ocean General Circulation Model (OGCM) simulations that resolve such zonal jet-like features show that they also propagate, largely in the meridional direc

S. Mennou, A. Chillali, A. Kacha

In this paper we recall some results and some criteria on the convergence of matrix continued fractions. The aim of this paper is to give some properties and results of continued fractions with matrix arguments. Then we give continued fraction expansions of the error function erf(A) where A is a matrix. At the end, some numerical examples illustrating the th

Michael Bentley, Caleb Rucker, Alan Kuntz

Tendon-driven robots, where one or more tendons under tension bend and manipulate a flexible backbone, can improve minimally invasive surgeries involving difficult-to-reach regions in the human body. Planning motions safely within constrained anatomical environments requires accuracy and efficiency in shape estimation and collision checking. Tendon robots th

Jia-Wei Luo, Fei-Fei Wang, Jia-Ming Zhu-Ge, Ye Li

The empirical classification of gamma-ray bursts (GRBs) into long and short GRBs based on their durations is already firmly established. This empirical classification is generally linked to the physical classification of GRBs originating from compact binary mergers and GRBs originating from massive star collapses, or Type I and II GRBs, with the majority of

Ruiheng Su, Manabendra Kuiri, Kenji Watanabe, Takashi Taniguchi

Superconductivity has been previously observed in magic-angle twisted stacks of monolayer graphene but conspicuously not in twisted stacks of bilayer graphene, although both systems host topological flat bands and symmetry-broken states. Here, we report the discovery of superconductivity in twisted double bilayer graphene (TDBG) in proximity to WSe$_2$. Samp

Amr Ahmadain, Aron C. Wall

In 1994, Susskind and Uglum argued that it is possible to derive the Bekenstein-Hawking entropy $A/4G_N$ from string theory. In this article we explain the conceptual underpinnings of this argument, while elucidating its relationship to induced gravity and ER=EPR. Following an off-shell calculation by Tseytlin, we explicitly derive the classical closed strin

Jérémy Bonnard

In the last years, a new family of energy density functionals directly inspired by effective field theory (EFT) has been developed, among which the ELYO (extended Lee-Yang Orsay) functional. In this paper, a new extension of ELYO that includes the recently calculated fourth-order EFT terms is presented. Compared to the previous version, the description of ne

Jasmina Nasufi

NLO QCD corrections to the process $pp \rightarrow e^+\nu_e \mu^- \bar{\nu}_{\mu} \tau^+\tau^- b \bar{b}+X$ are presented with the full off-shell effects included. The calculation includes all resonant and non-resonant Feynman diagrams, photon and $Z$-gauge boson contributions, as well as interference effects, all incorporated at the matrix element level. Fu

Jan Bouwe van den Berg, Olivier Hénot, Jean-Philippe Lessard

Ground state solutions of elliptic problems have been analyzed extensively in the theory of partial differential equations, as they represent fundamental spatial patterns in many model equations. While the results for scalar equations, as well as certain specific classes of elliptic systems, are comprehensive, much less is known about these localized solutio

Rob Procter, Peter Tolmie, Mark Rouncefield

The need for AI systems to provide explanations for their behaviour is now widely recognised as key to their adoption. In this paper, we examine the problem of trustworthy AI and explore what delivering this means in practice, with a focus on healthcare applications. Work in this area typically treats trustworthy AI as a problem of Human-Computer Interaction

Moufid Bouhentala, Mouna Ghanai, Kheireddine Chafaa

In this paper, a combination of fuzzy clustering estimation and sliding mode control is used to control a quadrotor system, whose mathematical model is complex and has unknown elements, including structure, parameters, and so on. In addition, they may be affected by external environmental disturbances. At first, the nonlinear unknown part of the system is es

Giuseppe Morello, Jeffrey Gerber, Bertrand Plez, Maria Bergemann

We release the first grid of stellar limb-darkening coefficients (LDCs) and intensity profiles (IPs) computed by the consortium of the PLAnetary Transits and Oscillations of stars (PLATO), the next medium-class (M3) mission under development by the European Space Agency (ESA) to be launched in 2026. We have performed spectral synthesis with \texttt{TurboSpec

John L. A. Gardner, Zoé Faure Beaulieu, Volker L. Deringer

Machine-learning models are increasingly used to predict properties of atoms in chemical systems. There have been major advances in developing descriptors and regression frameworks for this task, typically starting from (relatively) small sets of quantum-mechanical reference data. Larger datasets of this kind are becoming available, but remain expensive to g

Alberto Del Pia

In this paper, we give an algorithm that finds an epsilon-approximate solution to a mixed integer quadratic programming (MIQP) problem. The algorithm runs in polynomial time if the rank of the quadratic function and the number of integer variables are fixed. The running time of the algorithm is expected unless P=NP. In order to design this algorithm we intro

Daniel M. Levinstein, Saavidra Perera, Quinn M. Konopacky, Alex Madurowicz

The Earth's turbulent atmosphere results in speckled and blurred images of astronomical objects when observed by ground based visible and near-infrared telescopes. Adaptive optics (AO) systems are employed to reduce these atmospheric effects by using wavefront sensors (WFS) and deformable mirrors. Some AO systems are not fast enough to correct for strong, fa

Jayakrishnan M. P. Nair

The Su-Schrieffer-Heeger (SSH) model describes a paradigmatic one-dimensional (1-D) system that exhibits a non-trivial band topology. In this paper, we foreground a new scheme involving a 1-D chain of $2N+1$ Bosonic modes with nearest-neighbor interactions, in which, the topology of the system is regulated by the selective excitation of intrinsic anharmonici

Sean Greenaway, Adam Smith, Florian Mintert, Daniel Malz

We experimentally assess the suitability of transmon qubits with fixed frequencies and fixed interactions for the realization of analogue quantum simulations of spin systems. We test a set of necessary criteria for this goal on a commercial quantum processor using full quantum process tomography and more efficient Hamiltonian tomography. Significant single q

Andrea Cristofoli, Asaad Elkhidir, Anton Ilderton, Donal O'Connell

We show that large gauge transformations modify the structure of momentum conservation leading to non-vanishing three-point amplitudes in a simple toy model of a gravitational wave event. This phenomenon resolves an apparent tension between perturbative scattering amplitude computations and exact methods in field theory. The tension is resolved to all orders

D. P. Lozano, M. Mongillo, X. Piao, S. Couet

The performance of state-of-the-art superconducting quantum devices is currently limited by microwave dielectric losses at different surfaces and interfaces. {\alpha}-tantalum is a superconductor that has proven effective in reducing dielectric loss and improving device performance due to its thin low-loss oxide. However, without the use of a seed layer, thi

Yachun Li, Shihao Wang, Liang Zhao

This paper is concerned with the global-in-time convergence from bipolar Euler-Poisson system (BEP) to unipolar one (UEP) through the infinity-ion-mass limit by letting the ratio of the mass of ion $m_i$ over that of electron $m_e$ goes to infinity. The global convergence of the limit is obtained for smooth solutions sufficiently close to constant equilibriu

Zhongmin Shen, Runzhong Zhao

Locally projectively flat metrics (or sprays) form a rich class of metrics (or sprays) in Finsler and spray geometry. The characterization of such metrics is the Hilbert Fourth Problem in the regular case. In this paper we study the Pontrjagin classes of a manifold given a spray structure, and show that a manifold equipped with a locally projectively flat Fi

Ilya Alekseev

We provide a combinatorial characterisation of positive diagrams satisfying the equality in the Morton-Franks-Williams bound for the degrees of the HOMFLY-PT polynomial. This characterisation allows generating with relative ease examples of diagrams realizing the crossing number, the braid index, and the maximal self-linking number. Besides, we suggest a con

Tong Zhang, Ying Tan, Xiang Chen, Zike Lei

Onboard visual sensing has been widely used in the unmanned ground vehicle (UGV) and/or unmanned aerial vehicle (UAV), which can be modeled as dynamic systems on SE(3). The onboard sensing outputs of the dynamic system can usually be applied to derive the relative position between the feature marks and the system, but bearing with explicit geometrical constr

Julien Portier, Leo Versteegen

In this paper we describe a strategy for Dominator that finishes the total domination game in at most $3/4n$ moves for every graph $G$ on $n$ vertices without any isolated vertices or edges, confirming the 3/4-conjecture for the total domination game made by Henning, Klav{\v{z}}ar, and Rall.

Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan

Virtual reality and augmented reality (XR) bring increasing demand for 3D content. However, creating high-quality 3D content requires tedious work that a human expert must do. In this work, we study the challenging task of lifting a single image to a 3D object and, for the first time, demonstrate the ability to generate a plausible 3D object with 360{\deg} v

Leo Shaposhnik

We study the behaviour of entanglement entropy in two-dimensional CFTs under Weyl transformations from the Weyl anomaly. Using the Ryu-Takayanagi-formula, we show that these deformations correspond to local deformations of the IR cutoff of AdS$_3$, which gives an example of the local validity of the IR/UV Connection in AdS/CFT. We then use Matrix Product Sta

Nadine El-Naggar, Pranava Madhyastha, Tillman Weyde

In this study, we investigate the generalization of LSTM, ReLU and GRU models on counting tasks over long sequences. Previous theoretical work has established that RNNs with ReLU activation and LSTMs have the capacity for counting with suitable configuration, while GRUs have limitations that prevent correct counting over longer sequences. Despite this and so

E. Serrano-Ensástiga, F. Mireles

We study the variational perturbations for the mean-field solution of an interacting spinor system with underlying rotational symmetries. An approach based upon the Majorana stellar representation for mixed states and group theory is introduced to this end. The method reduces significantly the unknown degrees of freedom of the perturbation, allowing us a sim

Di Zhou, Michael P. Whitmore, Kevin P. Griffin, H. Jane Bae

We develop a wall model for large-eddy simulation (LES) that takes into account various pressure-gradient effects using multi-agent reinforcement learning (MARL). The model is trained using low-Reynolds-number flow over periodic hills with agents distributed on the wall along the computational grid points. The model utilizes a wall eddy-viscosity formulation

Harkirat Singh Sahota, Kinjalk Lochan

One of the standard approaches of incorporating the quantum gravity (QG) effects into the semiclassical analysis is to adopt the notion of a quantum-corrected spacetime arising from the QG model. This procedure assumes that the expectation value of the metric variable effectively captures the relevant QG subtleties in the semiclassical regime. We investigate

Luke Lippstreu, Marcus Spradlin, Anastasia Volovich

We compute the leading (first-type Landau) singularities of a certain four-loop 7-point graph that is related to the 7-point ``ziggurat'' graph by the graphical moves familiar from equivalent circuit theory. We find perfect agreement with a subset of the ``heptagon symbol alphabet'' that has appeared in the context of planar $\mathcal{N}=4$ super-Yang-Mills

Ryszard Kukulski, Hanna Wojewódka-Ściążko

The relations between asymptotic stability, the eventual e-property and the e-property of Markov semigroups, acting on measures defined on general (Polish) metric spaces, are studied. While usually much attention is paid to asymptotic stability (and the e-property has been for years verified only to establish it), it should be noted that the e-property itsel

Ufuk Korkmaz, Deniz Türkpençe

We investigate the open dynamics of a probe qubit weakly interacting with distinct qubit environments bearing quantum information. We show that the proposed dissipative model yields a binary classification of the reservoir qubits' quantum information in the steady state in the Bloch qubit parameter space, depending on the coupling rates. To describe the diss

Jeongsoo Park, Justin Johnson

Most neural networks for computer vision are designed to infer using RGB images. However, these RGB images are commonly encoded in JPEG before saving to disk; decoding them imposes an unavoidable overhead for RGB networks. Instead, our work focuses on training Vision Transformers (ViT) directly from the encoded features of JPEG. This way, we can avoid most o

Ciaran Mullan, Sergey Slizovskiy, Jun Yin, Ziwei Wang

Van der Waals assembly enables exquisite design of electronic states in two-dimensional (2D) materials, often by superimposing a long-wavelength periodic potential on a crystal lattice using moir\'e superlattices. Here we show that electronic states in three-dimensional (3D) crystals such as graphite can also be tuned by the superlattice potential arising at

Alexander Roth, Wolf-Peter Schill

To reduce greenhouse gas emissions, many countries plan to massively expand wind power and solar photovoltaic capacities. These variable renewable energy sources require additional flexibility in the power sector. Both geographical balancing enabled by interconnection and electricity storage can provide such flexibility. In a 100% renewable energy scenario o

Binesh Mohan, Thejus Mary S., Avijit Hazra, Rohit Dhir

Motivated by the precision measurements of heavy flavor baryon masses, we analyze the modification of quark charge by employing the screening effect inside the baryon. In addition, we calculate the isospin mass splitting up to charmed baryons employing isospin symmetry breaking. Consequently, we obtain the masses, magnetic moments, and transition moments of

James M. Kurdzo, Betty J. Bennett, John Y. N. Cho, Michael F. Donovan

Military chaff is a metallic, fibrous radar countermeasure that is released by aircraft and rockets for diversion and masking of targets. It is often released across the United States for training purposes, and, due to its resonant cut lengths, is often observed on the S-band Weather Surveillance Radar - 1988 Doppler (WSR-88D) network. Efforts to identify an

Zhisheng Zhao, Debankur Mukherjee, Ruoyu Wu

We consider load balancing in large-scale heterogeneous server systems in the presence of data locality that imposes constraints on which tasks can be assigned to which servers. The constraints are naturally captured by a bipartite graph between the servers and the dispatchers handling assignments of various arrival flows. When a task arrives, the correspond