July 2022 arXiv papers — page 17

Yuqi Ouyang, Guodong Shen, Victor Sanchez

We propose a solution to detect anomalous events in videos without the need to train a model offline. Specifically, our solution is based on a randomly-initialized multilayer perceptron that is optimized online to reconstruct video frames, pixel-by-pixel, from their frequency information. Based on the information shifts between adjacent frames, an incrementa

Karthik Rajkumar

These notes shows how to do inference on the Demographic Parity (DP) metric. Although the metric is a complex statistic involving min and max computations, we propose a smooth approximation of those functions and derive its asymptotic distribution. The limit of these approximations and their gradients converge to those of the true max and min functions, wher

Mohamed Amine Ben Amor, Omer Gok, Damla Yaman

In this study we give an answer to the open question about the Riesz tensor product of ideals and bands of a Riesz space. We prove among other results that the Dedekind completion of the Riesz tensor product of two ideals is again an ideal.

Ataberk Olgun, F. Nisa Bostanci, Geraldo F. Oliveira, Yahya Can Tugrul

We propose Sectored DRAM, a new, low-overhead DRAM substrate that reduces wasted energy by enabling fine-grained DRAM data transfers and DRAM row activation. Sectored DRAM leverages two key ideas to enable fine-grained data transfers and row activation at low chip area cost. First, a cache block transfer between main memory and the memory controller happens

Ilya Shpitser

Graphical models such as Markov random fields (MRFs) that are associated with undirected graphs, and Bayesian networks (BNs) that are associated with directed acyclic graphs, have proven to be a very popular approach for reasoning under uncertainty, prediction problems and causal inference. Parametric MRF likelihoods are well-studied for Gaussian and categor

Samuel Haney, Damien Desfontaines, Luke Hartman, Ruchit Shrestha

Despite being raised as a problem over ten years ago, the imprecision of floating point arithmetic continues to cause privacy failures in the implementations of differentially private noise mechanisms. In this paper, we highlight a new class of vulnerabilities, which we call \emph{precision-based attacks}, and which affect several open source libraries. To a

Trevor V McCaffrey, Amy E Kimball, Emmanuel Momjian, Gordon T Richards

We present analysis of a homogeneous, optically selected, volume-limited ($0.2<z<0.3$) sample of 128 radio-quiet quasi-stellar objects (QSOs) recently observed at 6 GHz with the Very Large Array (VLA) in A-configuration ($\sim0.33''$ resolution). We compare these new results to earlier (2010--2011) 6-GHz observations with the VLA in C-configuration ($\sim3.5

Seyyed Ahmad Hosseini, Paolo Moretti, Michael Zaiser

Hierarchical microstructures are often invoked to explain the high resilience and fracture toughness of biological materials such as bone and nacre. Biomimetic material models inspired by those structural arrangements face the obvious challenge of capturing their inherent multi-scale complexity, both in experiments and in simulations. To study the influence

Tamás Tasnádi, Péter Vrana

We propose a generalization of the asymptotic equipartition property to discrete sources with an ambiguous alphabet, and prove that it holds for irreducible stationary Markov sources with an arbitrary distinguishability relation. Our definition is based on the limiting behavior of graph parameters appearing in a recent dual characterization of the Shannon ca

Mercè Claverol, Andrea de las Heras Parrilla, Clemens Huemer

For a given set of points $U$ on a sphere $S$, the order $k$ spherical Voronoi diagram $SV_k(U)$ decomposes the surface of $S$ into regions whose points have the same $k$ nearest points of $U$. Hyeon-Suk Na, Chung-Nim Lee, and Otfried Cheong (Comput. Geom., 2002) applied inversions to construct $SV_1(U)$. We generalize their construction for spherical Vorono

Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Martin M. Stein

Optical imaging is commonly used for both scientific and technological applications across industry and academia. In image sensing, a measurement, such as of an object's position, is performed by computational analysis of a digitized image. An emerging image-sensing paradigm breaks this delineation between data collection and analysis by designing optical co

Roberto C. Budzinski, Tung T. Nguyen, Gabriel B. Benigno, Jacqueline Doàn

We introduce an analytical approach that allows predictions and mechanistic insights into the dynamics of nonlinear oscillator networks with heterogeneous time delays. We demonstrate that time delays shape the spectrum of a matrix associated to the system, leading to the emergence of waves with a preferred direction. We then create analytical predictions for

Jiaxi Jiang, Paul Streli, Huajian Qiu, Andreas Fender

Today's Mixed Reality head-mounted displays track the user's head pose in world space as well as the user's hands for interaction in both Augmented Reality and Virtual Reality scenarios. While this is adequate to support user input, it unfortunately limits users' virtual representations to just their upper bodies. Current systems thus resort to floating avat

Peter Rassolov, Alfredo Scigliani, Hadi Mohammadigoushki

We investigate the flow evolution of a linear and a branched wormlike micellar solution with matched rheology in a Taylor-Couette (TC) cell using a combination of particle-tracking velocimetry, birefringence, and turbidity measurements. Both solutions exhibit a stress plateau within a range of shear rates. Under startup of a steady shear rate flow within the

C. A. Perroni, A. De Candia, V. Cataudella, R. Fazio

We show that tailoring the dissipative environment allows to change the features of continuous quantum phase transitions and, even, induce first order transitions in ferromagnetic spin chains. In particular, using a numerically exact quantum Monte Carlo method for the paradigmatic Ising chain of one-half spins in a transverse magnetic field, we find that spi

Jiaming Chen

We consider the fractional stochastic heat equation on the $d$-dimensional torus $\mathbb{T}^d:=\left[-\frac{1}{2},\frac{1}{2}\right]^d$, $d\geq 1$, with periodic boundary conditions: \[ \partial_t u(t,\textbf{x})= -(-\Delta)^{\alpha/2}u(t,\textbf{x})+\sigma(t,\textbf{x},u)\dot{F}(t,\textbf{x})\quad \textbf{x}\in \mathbb{T}^d,t\in\mathbb{R}_+ ,\] where $\alp

Connor Donovan, Nicholas A. Scoville

In this paper, we determine the homotopy type of the Morse complex and matching complex of multiple families of complexes by utilizing star cluster collapses and the Cluster Lemma. We compute the homotopy type of the Morse complex of an extended notion of a star graph, as well as the homotopy type of the matching complex of a Dutch windmill graph. Additional

Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe

Graph neural networks (GNNs) are emerging in chemical engineering for the end-to-end learning of physicochemical properties based on molecular graphs. A key element of GNNs is the pooling function which combines atom feature vectors into molecular fingerprints. Most previous works use a standard pooling function to predict a variety of properties. However, u

Tomás Chacón Rebollo, Daniel Franco Coronil

In this article, we address the solution of advection-dominated flow problems by stabilised methods, by means of least-squares computed stabilised coefficients. As main methodological tool, we introduce a data-driven off-line/on-line strategy to compute them with low computational cost. We compare the errors provided by the least-squares stabilised coefficie

Sophia Ohnemus, Heinz-Peter Breuer, Andreas Ketterer

Randomized measurements constitute a simple measurement primitive that exploits the information encoded in the outcome statistics of samples of local quantum measurements defined through randomly selected bases. In this work we exploit the potential of randomized measurements in order to probe the amount of entanglement contained in multiparticle quantum sys

Joonho Lee, David R. Reichman, Ryan Babbush, Nicholas C. Rubin

A recent preprint by Mazzola and Carleo numerically investigates exponential challenges that can arise for the QC-QMC algorithm introduced in our work, "Unbiasing fermionic quantum Monte Carlo with a quantum computer." As discussed in our original paper, we agree with this general concern. However, here we provide further details and numerics to emphasize th

Ionut Chifan, Sayan Das, Bin Sun

Using an interplay between geometric methods in group theory and soft von Neuman algebraic techniques we prove that for any icc, acylindrically hyperbolic group $\Gamma$ its von Neumann algebra $L(\Gamma)$ satisfies the so-called ISR property: \emph{any von Neumann subalgebra $N\subseteq L(\Gamma)$ that is normalized by all group elements in $\Gamma$ is of t

Hiroki Matsui, Ryo Takahashi

In this paper, we consider the Frobenius pushforward endofunctor $F_\ast$ of the bounded derived category of finitely generated modules over an $F$-finite noetherian local ring. We completely determine the categorical entropy of $F_\ast$ in the sense of Dimitrov, Haiden, Katzarkov, and Kontsevich.

E. Palmerduca, H. Qin, S. A. Cohen

The stability of charged particle motion in a uniform magnetic field with an added spatially uniform transverse rotating magnetic field (RMF) is studied analytically. It is found that the stability diagram of a single-particle's orbit depends critically on the chosen boundary conditions. We show that for many boundary conditions and wide regions in the param

M. Soria-Carro, P. R. Stinga

We develop the regularity theory of viscosity solutions to transmission problems for fully nonlinear second order uniformly elliptic equations. Our results give a complete theory of existence, uniqueness, comparison principle, and regularity of solutions to flat interface transmission problems; and the $C^{0,\alpha}$, $C^{1,\alpha}$ and $C^{2,\alpha}$ regula

Suvi Varshney, Divjeet Singh Jas

A common practice in Natural Language Processing (NLP) is to visualize the text corpus without reading through the entire literature, still grasping the central idea and key points described. For a long time, researchers focused on extracting topics from the text and visualizing them based on their relative significance in the corpus. However, recently, rese

Peter Xenopoulos, Joao Rulff, Luis Gustavo Nonato, Brian Barr

Analyzing classification model performance is a crucial task for machine learning practitioners. While practitioners often use count-based metrics derived from confusion matrices, like accuracy, many applications, such as weather prediction, sports betting, or patient risk prediction, rely on a classifier's predicted probabilities rather than predicted label

G. V. Dedkov

This paper presents the results of calculating Casimir-Lifshitz friction force and heating rate of a small metal particle moving above a metal surface (thick plate) in the case of their different local temperatures. The case of normal nonmagnetic metals (Au) is considered. There is a strong interplay of temperatures, particle velocity and separation distance

Ahmet Erdem, Derya Surgit, Burcu Ozkardes, Petr Hadrava

New spectrometric (HERCULES) and ground-based multi-colour photometric data on the multiple star V410 Puppis are combined with satellite photometry (HIPPARCOS and TESS), as well as historic astrometric observations. Absolute parameters for V410 Pup Aab are derived: $M_{Aa}$ = $3.15 \pm 0.10$, $M_{Ab}$ = $1.83 \pm 0.08$ (M$_{\odot}$); $R_{Aa}$ = $2.12 \pm 0.1

Alexander B. Watson, Tianyu Kong, Allan H. MacDonald, Mitchell Luskin

The Bistritzer-MacDonald (BM) model, introduced in \cite{Bistritzer2011}, attempts to capture the electronic properties of twisted bilayer graphene (TBG), even at incommensurate twist angles, by an effective periodic model over the bilayer moir\'e pattern. Starting from a tight-binding model, we identify a regime where the BM model emerges as the effective d

Mauro Conti, Jiaxin Li, Stjepan Picek, Jing Xu

Graph Neural Networks (GNNs), inspired by Convolutional Neural Networks (CNNs), aggregate the message of nodes' neighbors and structure information to acquire expressive representations of nodes for node classification, graph classification, and link prediction. Previous studies have indicated that GNNs are vulnerable to Membership Inference Attacks (MIAs),

Jingxi Weng, Benjamin Wildman-Tobriner, Mateusz Buda, Jichen Yang

Objectives: The purpose is to apply a previously validated deep learning algorithm to a new thyroid nodule ultrasound image dataset and compare its performances with radiologists. Methods: Prior study presented an algorithm which is able to detect thyroid nodules and then make malignancy classifications with two ultrasound images. A multi-task deep convoluti

Esra Yüksel, Florian Mercier, Jean-Paul Ebran, Elias Khan

We investigate the localization and clustering features in $^{20}$Ne ($N=Z$) and neutron-rich $^{32}$Ne nuclei at zero and finite temperatures. The finite temperature Hartree-Bogoliubov theory is used with the relativistic density-dependent meson-nucleon coupling functional DD-ME2. It is shown that clustering features gradually weaken with increasing tempera

K. A. Williams, J. J. Hermes, Z. P. Vanderbosch

The distribution of white dwarf rotation periods provides a means for constraining angular momentum evolution during the late stages of stellar evolution, as well as insight into the physics and remnants of double degenerate mergers. Although the rotational distribution of low mass white dwarfs is relatively well constrained via asteroseismology, that of hig

Jared Weed, Lingyun Ding, Jingfang Huang, Min Hyung Cho

In this paper, a Quadrature by Two Expansions (QB2X) numerical integration technique is developed for the single and double layer potentials of the Helmholtz equation in two dimensions. The QB2X method uses both local complex Taylor expansions and plane wave type expansions to achieve a resulting representation which is numerically accurate for all target po

Sajad A. Bhat, Pankaj Saini, Marc Favata, K. G. Arun

The inspiral-merger-ringdown (IMR) consistency test checks the consistency of the final mass and final spin of a binary black hole merger remnant, independently inferred via the inspiral and merger-ringdown parts of the waveform. As binaries are expected to be nearly circularized when entering the frequency band of ground-based detectors, tests of general re

Felix Wittwer, Peter Modregger

X-ray ptychography utilizes overlapping illuminations to reconstruct the object's phase and absorption signal with spatial resolutions much smaller than the focus size. Usually, the illumination overlap is chosen to be between 50% and 60% in order to ensure high quality reconstructions at reasonable scan times and/or doses. Here, we experimentally demonstrat

Lavina Sahijwani, N. Sukavanam

The artefact is dedicated towards the inspection of nonlinear fractional differential systems involving Riemann-Liouville derivative with higher order and fixed lower limit, including non-instantaneous impulses for existence and uniqueness results in Banach spaces. The motive of the paper is to set sufficient conditions to guarantee the existence of mild sol

Magda Peligrad, Sergey Utev

In this paper, we investigate the functional central limit theorem for stochastic processes associated to partial sums of additive functionals of reversible Markov chains with general spate space, under the normalization standard deviation of partial sums. For this case, we show that the functional central limit theorem is equivalent to the fact that the var

Nicholas J Dobbins, Tony Mullen, Ozlem Uzuner, Meliha Yetisgen

Identifying cohorts of patients based on eligibility criteria such as medical conditions, procedures, and medication use is critical to recruitment for clinical trials. Such criteria are often most naturally described in free-text, using language familiar to clinicians and researchers. In order to identify potential participants at scale, these criteria must

Jean-Christophe Pain

In previous works, we presented series representations for $\pi^3$ and $\pi^5$, in which the prefactor depends only on the golden ratio appears. In this article, we derive a general relation involving trigonometric functions and an infinite series. Such an identity is likely to provide many series representations for any positive power of $\pi$, among them t

Cheryl Henkels, Emmanuel G. de Oliveira, Roman Pasechnik, Haimon Trebien

In this paper, we study total and differential observables of electro- and photoproduction of light $\rho$, $\omega$ and $\phi$ mesons as functions of the center-of-mass energy of the $\gamma p$ collision and momentum transfer squared $|t|$. The corresponding vector mesons wave functions have been computed in the framework of relativistic AdS/QCD holographic

Mattis Reisner, Yanel Tahmi, Frédéric Piéchon, Ulrich Kuhl

The tight-binding model for a chain, where the hopping constants follow a Fibonacci sequence, predicts multifractality in the spectrum and wavefunctions. Experimentally, we realize this model by chains of small dielectric resonators with high refractive index ($\epsilon_r \approx 45$) of cylindrical form that exhibit evanescent coupling. We show that the fra

Huan Yang, Beatrice Bonga, Zhen Pan

We show that a generic relativistic membrane with in-plane pressure and surface density having the same sign is unstable with respect to a series of warping mode instabilities with high wave numbers. We also examine the criteria of instability for commonly studied exotic compact objects with membranes, such as gravastars, AdS bubbles and thin-shell wormholes

Mark J. Henriksen

We make the first observation-based calculation of the energy that goes into cosmic-ray protons versus cosmic ray electrons in shock acceleration during structure formation. We find a ratio of energy in cosmic ray protons to energy in cosmic ray electrons of 0.86. This value, calculated from the non-thermal X-ray component reported here from RTXE and the Fer

Miguel Angel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott

We introduce GAUDI, a generative model capable of capturing the distribution of complex and realistic 3D scenes that can be rendered immersively from a moving camera. We tackle this challenging problem with a scalable yet powerful approach, where we first optimize a latent representation that disentangles radiance fields and camera poses. This latent represe

Greg Kaplanek, Erickson Tjoa

We revisit the problem involving two constantly accelerating Unruh-DeWitt detectors using Open Effective Field Theory methods. We study the time evolution of the joint detector state using a Markovian approximation which differs from the standard one taken in the literature. We show that this Markovian limit already implies the complete positivity of the dyn

Freya Pfau, Johannes Pfau, Bastian Dänekas, Robert Porzel

Due to contact restrictions, closure of fitness centers and quarantine measures, the SARS-CoV-2 pandemic led to a considerable decline of sporting activities. The first relaxation of these restrictions allowed German citizens to mostly return to their normal training and exercise behavior, yet the long-term impact of the recurring measures (i.e. the "Lockdow

Victor Drouin-Touchette

This is a set of notes recalling some of the most important results on the XY model from the ground up. They are meant for a junior researcher wanting to get accustomed to the Kosterlitz-Thouless phase transition in the context of the 2D classical XY model. The connection to the 2D Coulomb gas is presented in detail, as well as the renormalization group flow

Jason T. Maddox, Ryan Sides, Jane L. Harvill

Maddox, et al. [9, 10] establish Bayesian methods for estimating home-team in-game win probability for college and NBA basketball. This paper introduces a Bayesian approach for estimating in-game home-team win probability for Division-I FBS college (American) football that uses expected number of remaining possessions and expected score as two predictors. Mo

Ibrokhimbek Akramov, Hans Knüpfer, Martin Kružík, Angkana Rüland

We are concerned with a variant of the isoperimetric problem, which in our setting arises in a geometrically nonlinear two-well problem in elasticity. More precisely, we investigate the optimal scaling of the energy of an elastic inclusion of a fixed volume for which the energy is determined by a surface and an (anisotropic) elastic contribution. Following i

Alexey Gordeev, Yana Teplitskaya

We study the properties of sets $\Sigma$ which are the solutions of the maximal distance minimizer problem, i.e. of sets having the minimal length (one-dimensional Hausdorff measure) over the class of closed connected sets $\Sigma \subset \mathbb{R}^n$ satisfying the inequality \[ max_{y \in M} dist(y,\Sigma) \leq r \] for a given compact set $M \subset \mat

Hany Farid

Whereas generative adversarial networks are capable of synthesizing highly realistic images of faces, cats, landscapes, or almost any other single category, paint-by-text synthesis engines can -- from a single text prompt -- synthesize realistic images of seemingly endless categories with arbitrary configurations and combinations. This powerful technology po

Abhishek Sivaram, Venkat Venkatasubramanian

The physics of active biological matter, such as bacterial colonies and bird flocks, exhibiting interesting self-organizing dynamical behavior has gained considerable importance in recent years. Recent theoretical advances use techniques from hydrodynamics, kinetic theory, and non-equilibrium statistical physics. However, for biological agents, these don't s

Garreth Ruane, A J Eldorado Riggs, Eugene Serabyn, Wesley Baxter

The unparalleled theoretical performance of an ideal vector vortex coronagraph makes it one of the most promising technologies for directly imaging exoplanets with a future, off-axis space telescope. However, the image contrast required for observing the light reflected from Earth-sized planets ($\sim10^{-10}$) has yet to be demonstrated in a laboratory sett

Mohsen Ghassemi, Eleonora Kreačić, Niccolò Dalmasso, Vamsi K. Potluru

Hawkes processes have recently gained increasing attention from the machine learning community for their versatility in modeling event sequence data. While they have a rich history going back decades, some of their properties, such as sample complexity for learning the parameters and releasing differentially private versions, are yet to be thoroughly analyze

Robin Buehler, Vincent Desjacques

We investigate the dynamical friction (DF) acting on circularly-moving perturbers in fuzzy dark matter (FDM) backgrounds. After condensation, FDM is described by a single wave function satisfying a Schr\"odinger-Poisson equation. An equivalent, hydrodynamic formulation can be obtained through the Madelung transform. Here, we consider both descriptions and re

Narinder Singh, Anikesh Pal

We investigate the influence of rotation on the onset and saturation of the Faraday instability in a vertically oscillating two-layer miscible fluid using a theoretical model and direct numerical simulations (DNS). Our analytical approach utilizes the Floquet analysis to solve a set of the Mathieu equations obtained from the linear stability analysis. The so

Aaron Walsman, Muru Zhang, Klemen Kotar, Karthik Desingh

Visual understanding of geometric structures with complex spatial relationships is a fundamental component of human intelligence. As children, we learn how to reason about structure not only from observation, but also by interacting with the world around us -- by taking things apart and putting them back together again. The ability to reason about structure

Jenna E. Moore, Tanay Bhandarkar, Brooke DiGia, Cody Duell

The Simons Observatory (SO) is a ground-based cosmic microwave background (CMB) survey experiment that consists of three 0.5 m small-aperture telescopes and one 6 m large-aperture telescope, sited at an elevation of 5200 m in the Atacama Desert in Chile. SO will utilize more than 60,000 transition edge sensors (TES) to observe CMB temperature and polarizatio

Xue Hong, Jing-Mei Qiu

We propose an Eulerian-Lagrangian (EL) Runge-Kutta (RK) discontinuous Galerkin (DG) method for wave equations. The method is designed based on the ELDG method for transport problems [J. Comput. Phy. 446: 110632, 2021.], which tracks solution along approximations to characteristics in the DG framework, allowing extra large time stepping sizes with stability.

D. Britzger, A. Gehrmann-De Ridder, T. Gehrmann, E. W. N. Glover

Fast interpolation-grid frameworks facilitate an efficient and flexible evaluation of higher-order predictions for any choice of parton distribution functions or value of the strong coupling $\alpha_s$. They constitute an essential tool for the extraction of parton distribution functions and Standard Model parameters, as well as studies of the dependence of

Marelot de Vos, Rolf Nelson van Lieshout, Twan Dollevoet

This paper considers the scheduling of electric vehicles in a public transit system. Our main innovation is that we take into account that charging stations have limited capacity, while also considering partial charging. To solve the problem, we expand a connection-based network in order to track the state of charge of vehicles and model recharging actions.

Alexander Cardona, Juan José Villamarín

We show that the geometric notion of duality behind $T$-duality, between two string theories on different manifolds $E, \hat{E}$ in the sense of \cite{BHM1}\cite{BHM2}, is precisely that of Lie bialgebroids due to Mackenzie and Xu \cite{MX}.

Anjali Sonkariya, Awadh Pratap Singh, Shiv Prasad Yadav

Data Envelopment Analysis (DEA) is a technique used to measure the efficiency of decision-making units (DMUs). In order to measure the efficiency of DMUs, the essential requirement is input-output data. Data is usually collected by humans, machines, or both. Due to human/machine errors, there are chances of having some missing values or inaccuracy, such as v

Ignatios Antoniadis, Anthony Guillen, Kyriakos Tamvakis

We investigate the effect of the quadratic correction $\alpha R^2$ and non-minimal coupling $\xi \phi^2 R$ on a quintessence model with an exponential potential $V(\phi) = M^4\exp(-\lambda\phi)$ in the Palatini formulation of gravity. We use dynamical system techniques to analyze the attractor structure of the model and uncover the possible trajectories of t

G. A. Matzeu, M. Lieu, M. T. Costa, J. N. Reeves

We present a new X-Ray Accretion Disk-wind Emulator (\textsc{xrade}) based on the 2.5D Monte Carlo radiative transfer code which provides a physically-motivated, self-consistent treatment of both absorption and emission from a disk-wind by computing the local ionization state and velocity field within the flow. \textsc{xrade} is then implemented through a pr

Takuya Kanazawa, Haiyan Wang, Chetan Gupta

Uncertainty quantification is one of the central challenges for machine learning in real-world applications. In reinforcement learning, an agent confronts two kinds of uncertainty, called epistemic uncertainty and aleatoric uncertainty. Disentangling and evaluating these uncertainties simultaneously stands a chance of improving the agent's final performance,

Jinqi Huang, Alex Serb, Spyros Stathopoulos, Themis Prodromakis

Memristors, emerging non-volatile memory devices, have shown promising potential in neuromorphic hardware designs, especially in spiking neural network (SNN) hardware implementation. Memristor-based SNNs have been successfully applied in a wide range of various applications, including image classification and pattern recognition. However, implementing memris

Tomás Ramos, Álvaro Gómez-León, Juan José García-Ripoll, Alejandro González-Tudela

Low-noise microwave amplifiers are crucial for detecting weak signals in fields such as quantum technology and radio astronomy. However, designing an ideal amplifier is challenging, as it must cover a wide frequency range, add minimal noise, and operate directionally - amplifying signals only in the observer's direction while protecting the source from envir

Avi M. Mandell, Jacob Lustig-Yaeger, Kevin Stevenson, Johannes Staguhn

Recent investigations have demonstrated the potential for utilizing a new observational and data analysis technique for studying the atmospheres of non-transiting exoplanets with combined light that relies on acquiring simultaneous, broad-wavelength spectra and resolving planetary infrared emission from the stellar spectrum through simultaneous fitting of th

Martin Enriquez-Rojo, Tobias Schroeder

In this paper, we investigate the asymptotic structure of gauge theories in decelerating and spatially flat Friedmann-Lema\^itre-Robertson-Walker universes. Firstly, we thoroughly explore the asymptotic symmetries of electrodynamics in this background, which reveals a major inconsistency already present in the flat case. Taking advantage of this treatment, w

Shyam Sundar, N. Azari, M. Goeks, S. Gheidi

In most superconductors electrons form Cooper pairs in a spin-singlet state mediated by either phonons or by long-range interactions such as spin fluctuations. The superconductor UTe$_2$ is a rare material wherein electrons are believed to form pairs in a unique spin-triplet state with potential topological properties. While spin-triplet pairing may be media

Jing Zhou, Zhi-Yu Zhang, Yu Gao, Junzhi Wang

Both Galactic and extragalactic studies on star formation suggest that stars form directly from dense molecular gas. To trace such high volume density gas, HCN and HCO+ J=1-0 have been widely used for their high dipole moments, relatively high abundances, and often being the strongest lines after CO. However, HCN and HCO+ J=1-0 emission could be arguably dom

Kianna Wan, William J. Huggins, Joonho Lee, Ryan Babbush

"Classical shadows" are estimators of an unknown quantum state, constructed from suitably distributed random measurements on copies of that state [Nature Physics 16, 1050-1057]. Here, we analyze classical shadows obtained using random matchgate circuits, which correspond to fermionic Gaussian unitaries. We prove that the first three moments of the Haar distr

Francesca Vidotto

Time, space, and matter are categories of our reasoning, whose properties appear to be fundamental. However, these require a scrutiny as in the extreme regime of the primordial universe these present quantum properties. What does it mean for time to be quantum? What does it mean for space? Are space and time disappearing, or what is disappearing are simply t

Konstantinos Tsagkaris, Erik Plauschinn

We study moduli stabilization in Calabi-Yau orientifold compactifications of type IIB string theory with O3- and O7-planes. We consider a Calabi-Yau three-fold with Hodge number $h^{2,1}=50$ and stabilize all axio-dilaton and complex-structure moduli by three-form fluxes. This is a challenging task, especially for large moduli-space dimensions. To address th

A. E. E. Dubois, D. A. Broadway, A. Stark, M. A. Tschudin

Predicting measurement outcomes from an underlying structure often follows directly from fundamental physical principles. However, a fundamental challenge is posed when trying to solve the inverse problem of inferring the underlying source-configuration based on measurement data. A key difficulty arises from the fact that such reconstructions often involve i

Riccardo Gonzo, Tristan McLoughlin, Andrea Puhm

We explore the celestial holography proposal for non-trivial asymptotically flat backgrounds including the Coulomb field of a static and spinning point charge, their gravitational counterparts described by the Schwarzschild and Kerr metrics, as well as the Aichelburg-Sexl shockwave and spinning shockwave geometries and their electromagnetic cousins. We compu

Daniel López-Cano, Raúl E. Angulo, Aaron D. Ludlow, M. Zennaro

The concentrations of dark matter haloes provide crucial information about their internal structure and how it depends on mass and redshift -- the so-called concentration-mass-redshift relation, denoted $c(M,z)$. We present here an extensive study of the cosmology-dependence of $c(M,z)$ that is based on a suite of 72 gravity-only, full N-body simulations in

Vedant Chandra, Charlie Conroy, Nelson Caldwell, Ana Bonaca

We report the discovery of Specter, a disrupted ultrafaint dwarf galaxy revealed by the H3 Spectroscopic Survey. We detected this structure via a pair of comoving metal-poor stars at a distance of 12.5 kpc, and further characterized it with Gaia astrometry and follow-up spectroscopy. Specter is a $25^\circ \times 1^\circ$ stream of stars that is entirely inv

Pierluca Carenza, Roman Pasechnik, Gustavo Salinas, Zhi-Wei Wang

We revisit the possibility that Dark Matter is composed of stable scalar glueballs of a confining dark ${\rm SU}(3)$ gauge theory coupled only to gravity. The relic abundance of dark glueballs is studied for the first time in a thermal effective theory accounting for strong-coupling dynamics. An important ingredient of our analysis is the use of an effective

Álvaro Gómez-León, Tomás Ramos, Alejandro González-Tudela, Diego Porras

We study the phenomena of topological amplification in arrays of parametric oscillators. We find two phases of topological amplification, both with directional transport and exponential gain with the number of sites, and one of them featuring squeezing. We also find a topologically trivial phase with zero-energy modes which produces amplification but lacks t

Ricardo Cepedello, Fabian Esser, Martin Hirsch, Veronica Sanz

The matching of specific new physics scenarios onto the SMEFT framework is a well-understood procedure. The inverse problem, the matching of the SMEFT to UV scenarios, is more difficult and requires the development of new methods to perform a systematic exploration of models. In this paper we use a diagrammatic technique to construct in an automated way a co

Pedro V. P. Cunha, Carlos Herdeiro, Eugen Radu, Nicolas Sanchis-Gual

Ultracompact objects with light-rings (LRs) but without an event horizon could mimic black holes (BHs) in their strong gravity phenomenology. But are such objects dynamically viable? Stationary and axisymmetric ultracompact objects that can form from smooth, quasi-Minkowski initial data must have at least one stable LR, which has been argued to trigger a spa

Yun-Ting Cheng, James J. Bock

Several fluctuation studies on the near-infrared extragalactic background light (EBL) find an excess power at tens of arcminute scales ($\ell\sim10^3$). Emission from the intra-halo light (IHL) has been proposed as a possible explanation for the excess signal. In this work, we investigate the emission from the integrated galaxy light (IGL) and IHL in the pow

Valentina Missaglia, Matteo Murgia, Francesco Massaro, Alessandro Paggi

We present multifrequency observations of the radio source 3CR 403.1, a nearby (z=0.055), extended ($\sim$0.5 Mpc) radio galaxy hosted in a small galaxy group. Using new high frequency radio observations from the Sardinia Radio Telescope (SRT), augmented with archival low frequency radio observations, we investigated radio spectral and polarimetric propertie

Milena Valentini, Klaus Dolag, Stefano Borgani, Giuseppe Murante

The reservoir of molecular gas (H$_{\rm 2}$) represents the fuel for the star formation (SF) of a galaxy. Connecting the star formation rate (SFR) to the available H$_{\rm 2}$ is key to accurately model SF in cosmological simulations of galaxy formation. We investigate how modifying the underlying modelling of H$_{\rm 2}$ and the description of stellar feedb

Lingfeng Li, JiJi Fan

Jupiter, the fascinating largest planet in the solar system, has been visited by nine spacecraft, which have collected a significant amount of data about Jovian properties. In this paper, we show that one type of the in situ measurements on the relativistic electron fluxes could be used to probe dark matter (DM) and dark mediator between the dark sector and

Prateek Mayank, Bhargav Vaidya, D. Chakrabarty

Solar wind streams, acting as background, govern the propagation of space weather drivers in the heliosphere, which induce geomagnetic storm activities. Therefore, predictions of the solar wind parameters are the core of space weather forecasts. This work presents an indigenous three-dimensional (3D) Solar Wind model (SWASTi-SW). This numerical framework for

Philippe Faist, Mischa P. Woods, Victor V. Albert, Joseph M. Renes

Detection of weak forces and precise measurement of time are two of the many applications of quantum metrology to science and technology. We consider a quantum system initialized in a pure state and whose evolution is governed by a Hamiltonian $H$; a measurement can later estimate the time $t$ for which the system has evolved. In this work, we introduce and

Alexander B. Gurvich, Aaron M. Geller

We present Firefly, a new browser-based interactive tool for visualizing 3D particle data sets. On a typical personal computer, Firefly can simultaneously render and enable real-time interactions with > ~10 million particles, and can interactively explore datasets with billions of particles using the included custom-built octree render engine. Once created,

George N. Wong, Charles F. Gammie

The centers of our galaxy and the nearby Messier 87 are known to contain supermassive black holes, which support accretion flows that radiate across the electromagnetic spectrum. Although the composition of the accreting gas is unknown, it is likely a mix of ionized hydrogen and helium. We use a simple analytic model and a suite of numerical general relativi

Harley Katz, Aayush Saxena, Alex J. Cameron, Stefano Carniani

We present a detailed analysis of the rest-frame optical emission line ratios for three spectroscopically confirmed galaxies at $z>7.5$. The galaxies were identified in the James Webb Space Telescope (JWST) Early Release Observations field SMACS J0723.3$-$7327. By quantitatively comparing Balmer and oxygen line ratios of these galaxies with various low-redsh

Sergio E. Aguilar-Gutierrez, Klaas Parmentier, Thomas Van Riet

We argue that a type IIB Euclidean supergravity solution of the form $\mathbb{R}\times S^1\times \mathbb{T}^8$ with imaginary self-dual $F_1$ flux through $\mathbb{R}\times S^1$ belongs to the chain of $AdS_d\times S^d\times \mathbb{T}^{10-2d}$ vacua with (imaginary) self-dual $F_d$ flux, where $d\leq 5$. Such vacua come from the near-horizon of D$(d-2)$/D$(

Muhammad Zubair Irshad, Sergey Zakharov, Rares Ambrus, Thomas Kollar

Our method studies the complex task of object-centric 3D understanding from a single RGB-D observation. As it is an ill-posed problem, existing methods suffer from low performance for both 3D shape and 6D pose and size estimation in complex multi-object scenarios with occlusions. We present ShAPO, a method for joint multi-object detection, 3D textured recons

Vivian U

Galaxy mergers provide a mechanism for galaxies to effectively funnel gas and materials toward their nuclei and fuel the central starbursts and accretion of supermassive black holes. In turn, the active nuclei drive galactic-scale outflows that subsequently impact the evolution of the host galaxies. The details of this transformative process as they pertain

Juan Magaña, Marco San Martín, Joaquín Sureda, Marcelo E. Rubio

We introduce a modification of the Press-Schechter formalism aimed to derive general mass functions for primordial black holes (PBHs). In this case, we start from primordial power spectra (PPS) which include a monochromatic spike, typical of ultra slow-roll inflation models. We consider the PBH formation as being associated to the amplitude of the spike on t

Ken K. W. Ma, A. Volya, Kun Yang

The recent discovery of quantum many-body scar states has revealed the possibility of having states with low entanglement that violate the eigenstate thermalization hypothesis in nonintegrable systems. Such states with low entanglement entropy are rare but naturally exist in the integrable system of free fermions. Here, we demonstrate analytically that these

Josh Mutch, Wei-Chih Chen, Cheng-Yi Huang, Paul Malinowski

p x n-type materials refer to materials with a p-type Seebeck coefficient in one direction and a n-type coefficient in the orthogonal direction. This type of materials allows for a transverse thermoelectric response, which is highly desirable for energy applications. Here, we report the observation of p x n-type behavior in TaIrTe4, a type-II Weyl semimetal,