July 2022 arXiv papers — page 23

Bruce W. Jordan, Kenneth A. Ribet, Anthony J. Scholl

Let $X$ be a smooth geometrically connected projective curve over the field of fractions of a discrete valuation ring $R$, and $\mathfrak{m}$ a modulus on $X$, given by a closed subscheme of $X$ which is geometrically reduced. The generalized Jacobian $J_\mathfrak{m}$ of $X$ with respect to $\mathfrak{m}$ is then an extension of the Jacobian of $X$ by a toru

Atsushi Higuchi, Lasse Schmieding, David Serrano Blanco

We study non-interacting automorphic quantum scalar fields with positive mass in two-dimensional de Sitter space. We find that there are no Hadamard states which are de Sitter invariant except in the periodic case, extending the result of Epstein and Moschella for the anti-periodic case. We construct the two-point Wightman functions for the non-Hadamard de S

Mikhail Silaev

Anderson-Higgs mechanism of mass generation is a generic concept in high-energy and condensed matter physics. It shows up through the Meissner effect providing the expulsion of static and low-frequency magnetic fields from superconductors. However, it does not affect propagating electromagnetic waves with a spectrum gap determined by the plasma frequency, wh

Shirin Shoushtari, Jiaming Liu, Yuyang Hu, Ulugbek S. Kamilov

There is a growing interest in deep model-based architectures (DMBAs) for solving imaging inverse problems by combining physical measurement models and learned image priors specified using convolutional neural nets (CNNs). For example, well-known frameworks for systematically designing DMBAs include plug-and-play priors (PnP), deep unfolding (DU), and deep e

Debanjana Kundu, Lawrence C. Washington

This paper studies Iwasawa invariants in anti-cyclotomic towers. We do this by proposing two heuristics supported by computations. First we propose the Intersection Heuristics: these model `how often' the $p$-Hilbert class field of an imaginary quadratic field intersects the anti-cyclotomic tower and to what extent. Second we propose the Invariants Heuristic

Renbo Zhao

We develop and analyze the Generalized Multiplicative Gradient (GMG) method for solving a class of convex optimization problems over symmetric cones, where the objective function does not have Lipschitz gradient over the feasible region. This problem class includes several applications, such as positron emission tomography, D-optimal design, quantum state to

Jeffrey Streets

We derive a family of weighted scalar curvature monotonicity formulas for generalized Ricci flow, involving an auxiliary dilaton field evolving by a certain reaction-diffusion equation motivated by renormalization group flow. These scalar curvature monotonicities are dual to a new family of Perelman-type energy and entropy monotonicity formulas by coupling t

M. Relano, I. De Looze, A. Saintonge, K. -C. Hou

The evolution of the dust grain size distribution has been studied in recent years with great detail in cosmological hydrodynamical simulations taking into account all the channels under which dust evolves in the interstellar medium. We present a systematic analysis of the observed spectral energy distribution of a large sample of galaxies in the local unive

Alexandre M. R. Almeida, Júlio C. Fabris, Mahamadou Hamani Daouda, Richard Kerner

We propose a unimodular version of the Brans-Dicke theory designed with a constrained Lagrangian formulation. The resulting field equations are traceless. The vacuum solutions in the cosmological background reproduce the corresponding solutions of the usual Brans-Dicke theory but with a cosmological constant term. A perturbative analysis of the scalar modes

G. Simutis, A. Bollhalder, M. Zolliker, J. Küspert

We present an in-situ uniaxial pressure device optimized for small angle X-ray and neutron scattering experiments at low-temperatures and high magnetic fields. A stepper motor generates force, which is transmitted to the sample via a rod with integrated transducer that continuously monitors the force. The device has been designed to generate forces up to 200

Alexander Bertoloni Meli, Linus Hamann, Kieu Hieu Nguyen

We study unramified unitary and unitary similitude groups in an odd number of variables. Using work of the first and third named authors on the Kottwitz Conjecture for the similitude groups, we show that the Fargues--Scholze local Langlands correspondence agrees with the semi-simplification of the local Langlands correspondences constructed by Mok for the gr

Rui Duan, Zhe Qu, Shangqing Zhao, Leah Ding

Recently, adversarial machine learning attacks have posed serious security threats against practical audio signal classification systems, including speech recognition, speaker recognition, and music copyright detection. Previous studies have mainly focused on ensuring the effectiveness of attacking an audio signal classifier via creating a small noise-like p

Alexander J. Bisberg, Emilio Ferrara

Win prediction is crucial to understanding skill modeling, teamwork and matchmaking in esports. In this paper we propose GCN-WP, a semi-supervised win prediction model for esports based on graph convolutional networks. This model learns the structure of an esports league over the course of a season (1 year) and makes predictions on another similar league. Th

Julia Berezutskaya, Anne-Lise Saive, Karim Jerbi, Marcel van Gerven

Artificial intelligence (AI) is a fast-growing field focused on modeling and machine implementation of various cognitive functions with an increasing number of applications in computer vision, text processing, robotics, neurotechnology, bio-inspired computing and others. In this chapter, we describe how AI methods can be applied in the context of intracrania

Vahid Nikkhah, Dimitrios C. Tzarouchis, Ahmad Hoorfar, Nader Engheta

Wave-based analog computing in the forms of inverse-designed metastructures and the meshes of Mach-Zehnder interferometers (MZI) have recently received considerable attention due to their capability in emulating linear operators, performing vector-matrix multiplication, inverting matrices, and solving integral and differential equations, via electromagnetic

Mungo Frost, Emma E. McBride, Dean Smith, Jesse S. Smith

Dehydrogenation of alkanes is of increasing importance in fulfilling global demand for olefins and offers a potential source of carbon-neutral hydrogen as a co-product. Currently commercial dehydrogenation processes occur at high-temperatures (500-900$^\circ$C) which is energy intensive and results in side reactions and rapid coking of the catalysts. In addi

Florian Barkmann, Yair Censor, Niklas Wahl

We apply the superiorization methodology to the intensity-modulated radiation therapy (IMRT) treatment planning problem. In superiorization, linear voxel dose inequality constraints are the fundamental modeling tool within which a feasibility-seeking projection algorithm will seek a feasible point. This algorithm is then perturbed with gradient descent steps

Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczyński

The propensity model introduced by Jain et al. 2016 has become a standard approach for dealing with missing and long-tail labels in extreme multi-label classification (XMLC). In this paper, we critically revise this approach showing that despite its theoretical soundness, its application in contemporary XMLC works is debatable. We exhaustively discuss the fl

Alessandro Casella, Sophia Bano, Francisco Vasconcelos, Anna L. David

In Twin-to-Twin Transfusion Syndrome (TTTS), abnormal vascular anastomoses in the monochorionic placenta can produce uneven blood flow between the two fetuses. In the current practice, TTTS is treated surgically by closing abnormal anastomoses using laser ablation. This surgery is minimally invasive and relies on fetoscopy. Limited field of view makes anasto

Armando Cabrera, Miriam Cha, Prafull Sharma, Michael Newey

This paper explores the use of multi-conditional adversarial networks for SAR-to-EO image translation. Previous methods condition adversarial networks only on the input SAR. We show that incorporating multiple complementary modalities such as Google maps and IR can further improve SAR-to-EO image translation especially on preserving sharp edges of manmade ob

Federico Settimo, Heinz-Peter Breuer, Bassano Vacchini

We analyze and compare different measures for the degree of non-Markovianity in the dynamics of open quantum systems. These measures are based on the distinguishability of quantum states which is quantified, on the one hand, by the trace distance or, more generally, by the trace norm of the Helstrom matrix, and, on the other hand, by entropic quantifiers: th

Qasem Exirifard, Ebrahim Karimi

Propagation of a localised wave function of a massive scalar field is investigated in its rest frame. The complete orthogonal Hermite-Gauss basis is presented, and the Gouy phase and Rayleigh scale notions are adapted. The leading and sub-leading gravitational corrections to a localised quantum wave function propagating in a general curved spacetime geometry

Daniel Reti

The ground state solution of the random dimer model is at a critical point after, which has been shown with random link excitations. In this paper we test the robustness of the random dimer model to the random link excitation by imposing the maximum weight excitation. We numerically compute the scaling exponents of the curves arising in the model as well as

Kevin Osanlou, Christophe Guettier, Tristan Cazenave, Eric Jacopin

This short review aims to make the reader familiar with state-of-the-art works relating to planning, scheduling and learning. First, we study state-of-the-art planning algorithms. We give a brief introduction of neural networks. Then we explore in more detail graph neural networks, a recent variant of neural networks suited for processing graph-structured in

Manley Roberts, Pranav Mani, Saurabh Garg, Zachary C. Lipton

What sorts of structure might enable a learner to discover classes from unlabeled data? Traditional approaches rely on feature-space similarity and heroic assumptions on the data. In this paper, we introduce unsupervised learning under Latent Label Shift (LLS), where we have access to unlabeled data from multiple domains such that the label marginals $p_d(y)

Zach Shahn

Under what circumstances is it a threat to the parallel trends assumption required for Difference in Differences (DiD) studies if treatment decisions are based on past values of the outcome? We explore via simulation studies whether parallel trends holds across a grid of data generating processes generally conducive to parallel trends (random walk, Hidden Ma

Mingxuan Yi, Song Liu

Variational Inference approximates an unnormalized distribution via the minimization of Kullback-Leibler (KL) divergence. Although this divergence is efficient for computation and has been widely used in applications, it suffers from some unreasonable properties. For example, it is not a proper metric, i.e., it is non-symmetric and does not preserve the tria

David Noever, Samuel Hyams

Physics-based simulations typically operate with a combination of complex differentiable equations and many scientific and geometric inputs. Our work involves gathering data from those simulations and seeing how well tree-based machine learning methods can emulate desired outputs without "knowing" the complex backing involved in the simulations. The selected

Vivek Nair, Gonzalo Munilla Garrido, Dawn Song, James F. O'Brien

Fifty study participants playtested an innocent-looking "escape room" game in virtual reality (VR). Within just a few minutes, an adversarial program had accurately inferred over 25 of their personal data attributes, from anthropometrics like height and wingspan to demographics like age and gender. As notoriously data-hungry companies become increasingly inv

Philipp König, Thomas Richthammer

A layered graph $G^\times$ is the Cartesian product of a graph $G = (V,E)$ with the linear graph $Z$, e.g. $Z^\times$ is the 2D square lattice $Z^2$. For Bernoulli percolation with parameter $p \in [0,1]$ on $G^\times$ one intuitively would expect that $P_p((o,0) \leftrightarrow (v,n)) \ge P_p((o,0) \leftrightarrow (v,n+1))$ for all $o,v \in V$ and $n \ge 0$

Xiaotian Fang, Jin-Su Oh, Matt Kramer, A. Romanenko

Niobium superconducting radiofrequency cavities enable applications in modern accelerators and quantum computers. However, the surface resistance significantly deteriorates the cavities performance. Nitrogen doping surface treatment can consistently increase cavity performance by reducing surface resistance, but the improvement mechanism is not fully underst

Teddy Lazebnik, Stephan Beck, Labib Shami

Conducting a research project with multiple participants is a complex task that involves not only scientific but also multiple social, political, and psychological interactions. This complexity becomes particularly evident when it comes to navigating the selection process for the number and order of co-authors on the resulting manuscript for publication due

Taras Bodnar, Dmitry Otryakhin, Erik Thorsen

The sub-Gaussian stable distribution is a heavy-tailed elliptically contoured law which has interesting applications in signal processing and financial mathematics. This work addresses the problem of feasible estimation of distributions. We present a method based on application of the method of moments to the empirical characteristic function. Further, we sh

Paweł Żuk, Bartłomiej Przybylski, Krzysztof Rzadca

In an overloaded FaaS cluster, individual worker nodes strain under lengthening queues of requests. Although the cluster might be eventually horizontally-scaled, adding a new node takes dozens of seconds. As serving applications are tuned for tail serving latencies, and these greatly increase under heavier loads, the current workaround is resource over-provi

Piotr Tempczyk, Ksawery Smoczyński, Philip Smolenski-Jensen, Marek Cygan

One of the most popular estimation methods in Bayesian neural networks (BNN) is mean-field variational inference (MFVI). In this work, we show that neural networks with ReLU activation function induce posteriors, that are hard to fit with MFVI. We provide a theoretical justification for this phenomenon, study it empirically, and report the results of a serie

Markus Heß, Qiang Li

A rigorous theory for solving tangential contacts between three-dimensional power-law graded elastic solids of arbitrary geometry is presented. For multiple contacts such as those occurring between two nominally flat but rough half-spaces, the well-known Ciavarella-J\"ager theorem is established accompanied by a discussion of tangential coupling. Nevertheles

Siddharth Ganjoo

License plate scanners have grown in popularity in parking lots during the past few years. In order to quickly identify license plates, traditional plate recognition devices used in parking lots employ a fixed source of light and shooting angles. For skewed angles, such as license plate images taken with ultra-wide angle or fisheye lenses, deformation of the

Michael Frank

Considering the deeper reasons of the appearance of a remarkable counterexample by J.~Kaad and M.~Skeide [17] we consider situations in which two Hilbert C*-modules $M \subset N$ with $M^\bot = \{ 0 \}$ over a fixed C*-algebra $A$ of coefficients cannot be separated by a non-trivial bounded $A$-linear functional $r_0: N \to A$ vanishing on $M$. In other word

Fadil Chabbabi, Maëva Ostermann

Let $B(H)$ be the algebra of all bounded operators on a Hilbert space $H$. Let $T=V|T|$ be the polar decomposition of an operator $T\in B(H)$. The mean transform of $T$ is defined by $M(T)=\frac{T+|T|V}{2}$. In this paper, we discuss several properties related to the spectrum, the kernel, the image, the polar decomposition of mean transform. Moreover, we inv

Sara Sarto, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara

Image captioning models aim at connecting Vision and Language by providing natural language descriptions of input images. In the past few years, the task has been tackled by learning parametric models and proposing visual feature extraction advancements or by modeling better multi-modal connections. In this paper, we investigate the development of an image c

Andreas Gleis, Jheng-Wei Li, Jan von Delft

Any matrix product state $|\Psi\rangle$ has a set of associated kept and discarded spaces, needed for the description of $|\Psi\rangle$, and changes thereof, respectively. These induce a partition of the full Hilbert space of the system into mutually orthogonal spaces of irreducible $n$-site variations of $|\Psi\rangle$. Here, we introduce a convenient proje

Steven R. Bell

We characterize the space of restrictions of real rational functions to certain algebraic Jordan curves in the plane via the Dirichlet-to-Neumann map associated to the domain in the complex plane bounded by the curve and its Bergman kernel. The characterization leads to a partial fractions-like decomposition for such rational functions and new ways to descri

Andrea Codegoni, Gabriele Lombardi, Alessandro Ferrari

In this paper, we present a lightweight and effective change detection model, called TinyCD. This model has been designed to be faster and smaller than current state-of-the-art change detection models due to industrial needs. Despite being from 13 to 140 times smaller than the compared change detection models, and exposing at least a third of the computation

Christian Eistrup, L. Ilsedore Cleeves, Sebastiaan Krijt

[Abridged] Planets and their atmospheres are built from gas and solid material in protoplanetary disks. This solid material grows from smaller, micron-sized grains to larger sizes in the disks, during the process of planet formation. Our goal is to model the compositional evolution of volatile ices on grains of different sizes, assuming both time-dependent g

Felix Finster, Niky Kamran, Moritz Reintjes

This paper is dedicated to a detailed analysis and computation of quantum states of causal fermion systems. The mathematical core is to compute integrals over the unitary group asymptotically for a large dimension of the group, for various integrands with a specific scaling behavior in this dimension. It is shown that, in a well-defined limiting case, the lo

Laura Gwilliams, Graham Flick, Alec Marantz, Liina Pylkkanen

The "MEG-MASC" dataset provides a curated set of raw magnetoencephalography (MEG) recordings of 27 English speakers who listened to two hours of naturalistic stories. Each participant performed two identical sessions, involving listening to four fictional stories from the Manually Annotated Sub-Corpus (MASC) intermixed with random word lists and comprehensio

Mohamed Elhamdadi, Emanuele Zappala

We introduce a cohomology theory of $n$-ary self-distributive objects in the tensor category of vector spaces that classifies their infinitesimal deformations. For $n$-ary self-distributive objects obtained from $n$-Lie algebras we show that ($n$-ary) Lie cohomology naturally injects in the self-distributive cohomology and we prove, under mild additional ass

Dmitry Kleinbock, Shahriar Mirzadeh

Let $X = G/\Gamma$, where $G$ is a Lie group and $\Gamma$ is a lattice in $G$, let $O$ be an open subset of $X$, and let $F = \{g_t: t\ge 0\}$ be a one-parameter subsemigroup of $G$. Consider the set of points in $X$ whose $F$-orbit misses $O$; it has measure zero if the flow is ergodic. It has been conjectured that this set has Hausdorff dimension strictly

Selcan Karaz, Mertcan Han, Gizem Akay, Asim Onal

Understanding dynamic and complex interaction of biological membranes with extracellular matrices plays a crucial role in controlling a variety of cell behavior and functions, from cell adhesion and growth to signaling and differentiation. Tremendous interest in tissue engineering has made it possible to design polymeric scaffolds mimicking the topology and

W. Narloch, G. Pietrzyński, W. Gieren, A. E. Piatti

We study 147 star clusters in the Large Magellanic Cloud (LMC) in order to determine their mean metallicities and ages, as well as the mean metallicities of 80 surrounding fields. We construct an age-metallicity relation (AMR) for the clusters in the LMC. For this purpose, we used Str\"omgren photometry obtained with the SOI camera on the 4.1 m SOAR telescop

T. -S. Huang, Yang-Zhi Chou, C. L. Baldwin, Fengcheng Wu

We develop a systematic theory for excitons subject to Fermi-Hubbard physics in moir\'e twisted transition metal dichalcogenides (TMDs). Specifically, we consider excitons in moir\'e systems for which the valence band is in the Mott-insulating regime. These "Mott-moir\'e excitons", which are achievable in twisted TMD heterobilayers, are bound states of a mag

Malgorzata Worek

We briefly report on NLO QCD corrections to the $pp \to t\bar{t} B +X$ process, where $B$ stands for $H,\,W^\pm$ or $Z$. In the calculation all double-, single and non-resonant Feynman diagrams, interferences and finite-width effects are included for the top quark and $W^\pm/Z$ gauge bosons. Numerical results are shown at the differential cross section level

Chih-Wei Chang, Raanan Marants, Yuan Gao, Matthew Goette

Mapping computed tomography (CT) number to material property dominates the proton range uncertainty. This work aims to develop a physics-constrained deep learning-based multimodal imaging (PDMI) framework to integrate physics, deep learning, magnetic resonance imaging (MRI), and advanced dual-energy CT (DECT) to derive accurate patient mass density maps. Sev

A. Islas, A. Rodríguez Fernández, C. Betegón, E. Martínez-Pañeda

Determination of the explosion severity parameters of biomass is crucial for the safety management and dust explosion risk assessment of biomass-processing industries. These are commonly determined following experimental tests in the 20L sphere according to the international standards. Recently, CFD simulations have emerged as a reliable alternative to predi

Soumen Basu, Somanshu Singla, Mayank Gupta, Pratyaksha Rana

Rich temporal information and variations in viewpoints make video data an attractive choice for learning image representations using unsupervised contrastive learning (UCL) techniques. State-of-the-art (SOTA) contrastive learning techniques consider frames within a video as positives in the embedding space, whereas the frames from other videos are considered

Nofel Yaseen, Liangcheng Yu, Caleb Stanford, Ryan Beckett

Compared to fixed-function switches, the flexibility of programmable switches comes at a cost, as programmer mistakes frequently result in subtle bugs in the network data plane. In this paper, we present the design and implementation of FP4, a fuzz-testing framework for P4 switches that achieves high expressiveness, coverage, and scalability. FP4 directly te

Thanasis Karakasis, George Koutsoumbas, Andri Machattou, Eleftherios Papantonopoulos

We study the Einstein-Euler-Heisenberg theory in the presence of a self interacting scalar field, minimally coupled to gravity. We solve analytically the field equations for the magnetically charged case and we obtain novel magnetically charged hairy black holes. The scalar field dresses the black hole with a secondary scalar hair. The hairy black hole devel

Graça R. M. de Almeida, N. Amaral, A. R. C. Buarque, W. S. Dias

We study how discrete-time quantum walks behave under short-range correlated noise. By considering noise as a source of inhomogeneity of quantum gates, we introduce a primitive relaxation in the assumption of uncorrelated stochastic noise: binary pair correlations manifesting in the random distribution. Using different quantum gates, we examined the transpor

Edward G. Hohenstein, Oumarou Oumarou, Rachael Al-Saadon, Gian-Luca R. Anselmetti

Efficient representations of the Hamiltonian such as double factorization drastically reduce circuit depth or number of repetitions in error corrected and noisy intermediate scale quantum (NISQ) algorithms for chemistry. We report a Lagrangian-based approach for evaluating relaxed one- and two-particle reduced density matrices from double factorized Hamilton

Eitan Farchi, Krithika Prakash, Vitali Sokhin

Cloud high quality API (Application Programming Interface) testing is essential for supporting the API economy. Autotest is a random test generator that addresses this need. It reads the API specification and deduces a model used in the test generation. This paper describes Autotest. It also address the topic of API specification pitfalls which Autotest may

Hanxun Yao, George Papadakis

We investigate the role of laminar/turbulent interface in the interscale energy transfer in a boundary layer undergoing bypass transition, with the aid of the Karman-Howarth-Monin-Hill (KHMH) equation. A local binary indicator function is used to detect the interface and employed subsequently to define two-point intermittencies. These are used to decompose t

Yifeng Zhang, Qihan Xuan, Qiyuan Fu, Chen Li

Snake moves across various terrains by bending its elongated body. Recent studies discovered that snakes can use vertical bending to traverse terrain of large height variation, such as horizontally oriented cylinders, a wedge (Jurestovsky, Usher, Astley, 2021, J. Exp. Biol.), and uneven terrain (Fu & Li, 2020, Roy. Soc. Open Sci.; Fu, Astley, Li, 2022 Bioins

A. Ersin Üreyen

We determine precisely when the Bergman projection $P_\beta$ is bound\-ed from Lebesgue spaces $L^p_\alpha$ to weighted Bergman spaces $\mathcal B^p_\alpha$ of $\mathcal H$-harmonic functions on the hyperbolic ball, and verify a recent conjecture of M. Stoll. We obtain upper estimates for the reproducing kernel of the $\mathcal H$-harmonic Bergman space $\ma

Hannah Alpert, Matthew Kahle, Robert MacPherson

We study configuration spaces $C(n; p, q)$ of $n$ ordered unit squares in a $p$ by $q$ rectangle. Our goal is to estimate the Betti numbers for large $n$, $j$, $p$, and $q$. We consider sequences of area-normalized coordinates, where $(\frac{n}{pq}, \frac{j}{pq})$ converges as $n$, $j$, $p$, and $q$ approach infinity. For every sequence that converges to a p

Sarah Croke

One notion of non-locality in quantum theory is the fact that information may be encoded in a composite system in such a way that it is not accessible through local measurements, even with the assistance of classical communication. Thus, contrary to the classical case, there exists information in quantum many body systems which cannot be accessed locally. We

Christa Cuchiero, Guido Gazzani, Sara Svaluto-Ferro

We consider asset price models whose dynamics are described by linear functions of the (time extended) signature of a primary underlying process, which can range from a (market-inferred) Brownian motion to a general multidimensional continuous semimartingale. The framework is universal in the sense that classical models can be approximated arbitrarily well a

Andrey Boris Khesin, Jonathan Z. Lu, Peter W. Shor

Publicly verifiable quantum money is a protocol for the preparation of quantum states that can be efficiently verified by any party for authenticity but is computationally infeasible to counterfeit. We develop a cryptographic scheme for publicly verifiable quantum money based on Gaussian superpositions over random lattices. We introduce a verification-of-aut

David Shulman

This study presents a novel and user-friendly technique for detecting the lateral capillary force on a floating spherical particle. The technique leverages the interplay between the capillary attracting forces, hydrostatic pressure forces, and magnetic repulsion forces. A magnetic field is applied to induce a surface curvature in the liquid, resulting in a n

Tsung-Han Yeh, Jessie Shelton, Keith A. Olive, Brian D. Fields

We present new Big Bang Nucleosynthesis (BBN) limits on the cosmic expansion rate or relativistic energy density, quantified via the number $N_\nu$ of equivalent neutrino species. We use the latest light element observations, neutron mean lifetime, and update our evaluation for the nuclear rates $d+d \rightarrow He3 + n$ and $d+d \rightarrow H3 + p$. Combini

Ricardo Herrera Romero, Miguel Angel Bastarrachea-Magnani, Román Linares

We study the quantum phase diagram and the onset of quantum critical phenomena in a generalized Dicke model that includes collective qubit-qubit interactions. By employing semiclassical techniques, we analyze the corresponding classical energy surfaces, fixed points, and the smooth Density of States as a function of the Hamiltonian parameters to determine qu

Yuri Chervonyi, Praneet Dutta, Piotr Trochim, Octavian Voicu

We present a hybrid industrial cooling system model that embeds analytical solutions within a multi-physics simulation. This model is designed for reinforcement learning (RL) applications and balances simplicity with simulation fidelity and interpretability. The model's fidelity is evaluated against real world data from a large scale cooling system. This is

Fumika Suzuki, William G. Unruh

We numerically study two methods of measuring tunneling times using a quantum clock. In the conventional method using the Larmor clock, we show that the Larmor tunneling time can be shorter for higher tunneling barriers. In the second method, we study the probability of a spin-flip of a particle when it is transmitted through a potential barrier including a

Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon

We propose transferability from Large Geometric Vicinity (LGV), a new technique to increase the transferability of black-box adversarial attacks. LGV starts from a pretrained surrogate model and collects multiple weight sets from a few additional training epochs with a constant and high learning rate. LGV exploits two geometric properties that we relate to t

Pieter-Jan Stas, Yan Qi Huan, Bartholomeus Machielse, Erik N. Knall

Long-distance quantum communication and networking require quantum memory nodes with efficient optical interfaces and long memory times. We report the realization of an integrated two-qubit network node based on silicon-vacancy centers (SiVs) in diamond nanophotonic cavities. Our qubit register consists of the SiV electron spin acting as a communication qubi

Jean-Luc Gach, Isaure De Kernier, Philippe Feautrier

The photon counting imaging paradigm in the visible and the infrared comes from the very small energy carried by a single photon at these wavelengths. Usually to detect photons the photoelectric effect is used. It converts a photon to a single electron making it very difficult to detect because of the readout noise of the electronics. To overcome this there

Tao Lin, Yiling Chen

We consider a Bayesian forecast aggregation model where $n$ experts, after observing private signals about an unknown binary event, report their posterior beliefs about the event to a principal, who then aggregates the reports into a single prediction for the event. The signals of the experts and the outcome of the event follow a joint distribution that is u

Kevin M. Ryan, Carlos G. Torres-Castanedo, Dominic P. Goronzy, David A. Garcia Wetter

Continued advances in superconducting qubit performance require more detailed understandings of the many sources of decoherence. Within these devices, two-level systems arise due to defects, interfaces, and grain boundaries, and are thought to be a major source of qubit decoherence at millikelvin temperatures. In addition to Al, Nb is a commonly used metaliz

Abdulrahman Alajmi, Jenya Soprunova

The lattice size $\operatorname{ls_\Delta}(P)$ of a lattice polytope $P$ is a geometric invariant, which was formally introduced in relation to the problem of bounding the total degree and the bi-degree of the defining equation of an algebraic curve, but appeared implicitly earlier in geometric combinatorics. In this paper, we show that for an empty lattice

Shruthi B. C., N. Suresh

The study is conducted to establish the framework for comparing the relation in performance of the derivatives of BSE and NSE in India and to analyse the relationship of derivatives with the cash market and the market volatility. The exchange-traded equity derivatives were considered for the study. It was found that the performance of derivatives in NSE is a

Tomás Chacón Rebollo, Samuele Rubino, Mourad Oulghelou, Cyrille Allery

This article presents error bounds for a velocity-pressure segregated POD reduced order model discretization of the Navier-Stokes equations. The stability is proven in L infinity (L 2 ) and energy norms for velocity, with bounds that do not depend on the viscosity, while for pressure it is proven in a semi-norm of the same asymptotic order as the L 2 norm wi

Rajmohan Rajaraman, David Stalfa, Sheng Yang

We study the problem of scheduling precedence-constrained jobs on heterogenous machines in the presence of non-uniform job and machine communication delays. We are given as input $n$ unit size precedence-ordered jobs and $m$ related machines such that machine $i$ can execute up to $m_i$ jobs at a time. Each machine $i$ has an in-delay $\rho^{\mathrm{in}}_i$

Luis Rodrigues, Sidney Givigi

This paper addresses the analysis and design of quadratic neural networks, which have been recently introduced in the literature, and their applications to regression, classification, system identification and control of dynamical systems. These networks offer several advantages, the most important of which are the fact that the architecture is a by-product

Nirmal Roy, David Maxwell, Claudia Hauff

The Search Engine Results Page (SERP) has evolved significantly over the last two decades, moving away from the simple ten blue links paradigm to considerably more complex presentations that contain results from multiple verticals and granularities of textual information. Prior works have investigated how user interactions on the SERP are influenced by the p

Zeljko Cuckovic, Zhenghui Huo, Sonmez Sahutoglu

We give sufficient conditions for the essential spectrum of the Hermitian square of a class of Hankel operators on the Bergman space of the polydisc to contain intervals. We also compute the spectrum in case the symbol is a monomial.

Anibal M. Medina-Mardones

We show that the Ranicki-Weiss assembly functor, going from chain complex valued presheaves on a simplicial complex to comodules over its Alexander-Whitney coalgebra, factors fully faithfully through the category of comodules over its Steenrod cup-$i$ coalgebra.

Yves Brihaye, Carlos Herdeiro, Eugen Radu

A mechanism for circumventing the Mayo-Bekenstein no-hair theorem allows endowing four dimensional $(D=4)$ asymptotically flat, spherical, electro-vacuum black holes with a minimally coupled $U(1)$-gauged scalar field profile: $Q$-$hair$. The scalar field must be massive, self-interacting and obey a {\it resonance condition} at the threshold of (charged) sup

Xin Wang, Tucker Jones, Benedetta Vulcani, Tommaso Treu

We report the first gas-phase metallicity map of a distant galaxy measured with the James Webb Space Telescope (JWST). We use the NIRISS slitless spectroscopy acquired by the GLASS Early Release Science program to spatially resolve the rest-frame optical nebular emission lines in a gravitationally lensed galaxy at $z=3.06$ behind the Abell 2744 galaxy cluste

Massimo Bianchi, Maurizio Firrotta, Jacob Sonnenschein, Dorin Weissman

We propose a novel measure of chaotic scattering amplitudes. It takes the form of a log-normal distribution function for the ratios $r_n={\delta_n}/{\delta_{n+1}}$ of (consecutive) spacings $\delta_n$ between two (consecutive) peaks of the scattering amplitude. We show that the same measure applies to the quantum mechanical scattering on a leaky torus as wel

Daniel Gilman, Yi-Ming Zhong, Jo Bovy

We devise a method to constrain self-interacting dark matter (SIDM) from observations of quadruply-imaged quasars, and apply it to five self-interaction potentials with a long-range dark force. We consider several SIDM models with an attractive potential that allows for the formation of quasi-bound states, giving rise to resonant features in the cross sectio

Yossef Zenati, Hagai B. Perets, Luc Dessart, Wynn V. Jacobson-Gal'an

Calcium-rich (SN 2005E-like) explosions are very faint (typical -15.5, type I supernovae (SNe) showing strong Ca-lines, mostly observed in old stellar environments. Several models for such SNe had been explored and debated, but non were able to consistently reproduce the observed properties of Ca-rich SNe, nor their rates and host-galaxy distributions. Here

Danielle Sponseller, Alan Kogut

One of the primary challenges facing upcoming CMB polarization experiments aiming to measure the inflationary B-mode signal is the removal of polarized foregrounds. The thermal dust foreground is often modeled as a single modified blackbody, however overly simplistic foreground models can bias measurements of the tensor-to-scalar ratio r. As CMB polarization

Roberta Angius, Matilda Delgado, Angel M. Uranga

We describe timelike linear dilaton backgrounds of supercritical string theories as time-dependent Dynamical Cobordisms in string theory, with their spacelike singularity as a boundary defining the beginning of time. We propose and provide compelling evidence that its microscopic interpretation corresponds to a region of (a strong coupling version of) closed

Yanou Cui, Jui-Lin Kuo, Josef Pradler, Yu-Dai Tsai

While most searches for cosmic axions so far focused on their cold relics as (a component of) dark matter, various well-motivated cosmological sources can produce "boosted" axions that remain relativistic today. We demonstrate that existing/upcoming neutrino experiments such as Super-Kamiokande, Hyper-Kamiokande, DUNE, JUNO, and IceCube can probe such energe

Rossella Gamba, Sebastiano Bernuzzi

Resonant excitations of $f$-modes in binary neutron star coalescences influence the gravitational waves (GWs) emission in both quasicircular and highly eccentric mergers and can deliver information on the star interior. Most models of resonant tides are built using approximate, perturbative approaches and thus require to be carefully validated against numeri

Li Ern Chern, Yong Baek Kim, Claudio Castelnovo

We use the projective symmetry group analysis to classify the quantum spin liquids on the $S=1/2$ pyrochlore magnet with a breathing anisotropy. We find 40 $\mathbb{Z}_2$ spin liquids and 16 $U(1)$ spin liquids that respect the $F\bar{4}3m$ space group and the time reversal symmetry. As an application, we consider the antiferromagnetic Heisenberg model, whic

Paolo Andrea Erdman, Alberto Rolandi, Paolo Abiuso, Martí Perarnau-Llobet

The full optimization of a quantum heat engine requires operating at high power, high efficiency, and high stability (i.e. low power fluctuations). However, these three objectives cannot be simultaneously optimized - as indicated by the so-called thermodynamic uncertainty relations - and a systematic approach to finding optimal balances between them includin

Eugenio Bottacini

Ever since the launch of the NuSTAR mission, the hard X-ray range is being covered to an unprecedented sensitivity. This range encodes the reflection features arising from active galactic nuclei (AGN). Especially, the reflection of the primary radiation off the accretion disk carries the features of the manifestation of General Relativity described by the Ke

Jenny G. Sorce, Pierre Ocvirk, Dominique Aubert, Stefan Gottloeber

Patchy cosmic reionization resulted in the ionizing UV background asynchronous rise across the Universe. The latter might have left imprints visible in present day observations. Several numerical simulation-based studies show correlations between reionization time and overdensities and object masses today. To remove the mass from the study, as it may not be

Lilan Yang, T. Morishita, N. Leethochawalit, M. Castellano

We present the first rest-frame optical size-luminosity relation of galaxies at $z>7$, using the NIRCam imaging data obtained by the GLASS James Webb Space Telescope Early Release Science (GLASS-JWST-ERS) program, providing the deepest extragalactic data of the ERS campaign. Our sample consist of 19 photometrically selected bright galaxies with $m_\text{F444

Paul Bennet, Mayte Alfaro-Cuello, Andrés del Pino, Laura L. Watkins

We have determined bulk proper motions (PMs) for 31 LMC GCs from Gaia eDR3 and Hubble Space Telescope data using multiple independent analysis techniques. Combined with literature values for distances, line-of-sight velocities and existing bulk PMs, we extract full 6D phase-space information for 32 clusters, allowing us to examine the kinematics of the LMC G