August 2022 arXiv papers — page 57

Katepalli R. Sreenivasan, Victor Yakhot

A recent discovery about the inertial range of homogeneous and isotropic turbulence is the saturation of the scaling exponents $\zeta_n$ for large $n$, defined via structure functions of order $n$ as $S_{n}(r)=\overline{(\delta_r u)^{n}}=A(n)r^{\zeta_{n}}$. We focus on longitudinal structure functions for $\delta_r u$ between two positions that are $r$ apart

Anthony I. Huber, Scott C. Chapman, Adrian K. Sinclair, Locke D. Spencer

Prime-Cam is a first-generation instrument for the Cerro Chajnantor Atacama Telescope-prime (CCAT-prime) Facility. The 850$~$GHz module for Prime-Cam will probe the highest frequency of all the instrument modules. We describe the parameter space of the 850$~$GHz optical system between the F$\lambda$ spacing, beam size, pixel sensitivity, and detector count.

Chengyu Liu, Wei Wang

Developing models with high interpretability and even deriving formulas to quantify relationships between biological data is an emerging need. We propose here a framework for ab initio derivation of sequence motifs and linear formula using a new approach based on the interpretable neural network model called contextual regression model. We showed that this l

Scott Mueller, Judea Pearl

Personalized decision making targets the behavior of a specific individual, while population-based decision making concerns a sub-population resembling that individual. This paper clarifies the distinction between the two and explains why the former leads to more informed decisions. We further show that by combining experimental and observational studies we

Yupeng Li, Ezra Miller, Erika Ordog

A canonical minimal free resolution of an arbitrary co-artinian lattice ideal over the polynomial ring is constructed over any field whose characteristic is 0 or any but finitely many positive primes. The differential has a closed-form combinatorial description as a sum over lattice paths in $\mathbb{Z}^n$ of weights that come from sequences of faces in simp

Worasait Suwannik

Teaching programming effectively is difficult. This paper explores the benefits of using Minecraft Education Edition to teach Python programming. Educators can use the game to teach various programming concepts ranging from fundamental programming concepts, object-oriented programming, event-driven programming, and parallel programming. It has several benefi

Stamatina Lamprinakou, Axel Gandy

We extend the unstructured homogeneously mixing epidemic model introduced by Lamprinakou et al. [arXiv:2208.07340] considering a finite population stratified by age bands. We model the actual unobserved infections using a latent marked Hawkes process and the reported aggregated infections as random quantities driven by the underlying Hawkes process. We apply

James R. Kirk, Robert E. Wray, Peter Lindes, John E. Laird

Autonomous agents are able to draw on a wide variety of potential sources of task knowledge; however current approaches invariably focus on only one or two. Here we investigate the challenges and impact of exploiting diverse knowledge sources to learn online, in one-shot, new tasks for a simulated office mobile robot. The resulting agent, developed in the So

M. S. Mirakhor, S. A. Walker, J. Runge, P. Diwanji

Non-thermal emission from clusters of galaxies at the high-energy X-ray regime has been searched with various instruments, but the detection significance of this emission has yet been found to be either marginal or controversial. Taking advantage of NuSTAR's unique capability to focus X-rays in the hard energy band, we present a detailed analysis of 238 ks N

Stephen Gourlay, Tor Raubenheimer, Vladimir Shiltsev

The US particle physics community planning exercise (a.k.a. Snowmass) is organized every 7 to 9 years to provide a forum for discussions among the entire particle physics community to develop a scientific vision for the future of particle physics in the U.S. and its international partners. The Snowmass 21 Accelerator Frontier activities include discussions o

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

A variety of problems in econometrics and machine learning, including instrumental variable regression and Bellman residual minimization, can be formulated as satisfying a set of conditional moment restrictions (CMR). We derive a general, game-theoretic strategy for satisfying CMR that scales to nonlinear problems, is amenable to gradient-based optimization,

Jean Pierre Gazeau, Romain Murenzi

Covariant integral quantizations are based on the resolution of the identity by continuous or discrete families of normalised positive operator valued measures (POVM), which have appealing probabilistic content and which transform in a covariant way. One of their advantages is to allow to circumvent problems due to the presence of singularities in the classi

Michael Celentano

In many problems in modern statistics and machine learning, it is often of interest to establish that a first order method on a non-convex risk function eventually enters a region of parameter space in which the risk is locally convex. We derive an asymptotic comparison inequality, which we call the Sudakov-Fernique post-AMP inequality, which, in a certain c

S. J. D. MacIntosh

Projection matrices are necessary for a large portion of rendering computer graphics. There are primarily two different types of projection matrices -- perspective and orthographic -- which are used frequently, and are traditionally treated as mutually incompatible with each other in how they are defined. Here, we bridge the gap between the two different for

Jiahao Gong, Vaseem A. Shaik, Gwynn J. Elfring

Active particles (living or synthetic) often move through inhomogeneous environments, such as gradients in light, heat or nutrient concentration, that can lead to directed motion (or taxis). Recent research has explored inhomogeneity in the rheological properties of a suspending fluid, in particular viscosity, as a mechanical (rather than biological) mechani

A. D. Alhaidari

With the present trend in experimental particle physics of probing yet shorter distances and with the requirement on the theoretical side of renormalizability, conformal invariance becomes an attractive symmetry for particle interactions. That is because conformal field theories form a large class of massless no-scale renormalizable quantum field theories. I

David R. Ardila, Evgenya Shkolnik, John Ziemer, Mark Swain

UV-SCOPE is a mission concept to determine the causes of atmospheric mass loss in exoplanets, investigate the mechanisms driving aerosol formation in hot Jupiters, and study the influence of the stellar environment on atmospheric evolution and habitability. As part of these investigations, the mission will generate a broad-purpose legacy database of time-dom

Sajjad Ghiasvand, Arash Nasri, Ali H. Abdollahi Bafghi, Masoumeh Nasiri-Kenari

Reconfigurable Intelligent Surface (RIS) plays a pivotal role in the sixth generation networks to enhance communication rate and localization accuracy. In this letter, we propose a positioning algorithm in a RIS-assisted environment, where the Base Station (BS) is multi-antenna, and the Mobile Station (MS) is single-antenna. We show that our method can achie

Sangeeta Rajpurohit, Tadashi Ogitsu, Liang Z. Tan

We investigate the effect of local electron-phonon coupling on nonlinear optical conductivity in an interacting ferroelectric system. Using real-time simulations, we show an enhancement in nonlinear conductivity under linearly-polarized light due to generation of the phonon-assisted ballistic-current in addition to the injection-current generated by electron

John P. D'Angelo, Jiri Lebl

The first author recently introduced an integer sequence now numbered A355519 in OEIS. This sequence arose from counting bracket tournaments; its study evokes the analysis of the Catalan triangle (sequence A009766 in OEIS) and the related Catalan numbers, sequence A000108 in OEIS. We therefore introduce a general construction that places these sequences on t

Garrett T. Floyd, David P. Landau, Michael R. Geller

It has been shown that the Metropolis algorithm can be implemented on quantum computers in a way that avoids the sign problem. However, flat histogram techniques are often preferred as they don't suffer from the same limitations that afflict Metropolis for problems of real-world interest and provide a host of other benefits. In particular, the Wang-Landau me

Yixiang Luo, William Fithian, Lihua Lei

The knockoff filter of Barber and Candes (arXiv:1404.5609) is a flexible framework for multiple testing in supervised learning models, based on introducing synthetic predictor variables to control the false discovery rate (FDR). Using the conditional calibration framework of Fithian and Lei (arXiv:2007.10438), we introduce the calibrated knockoff procedure,

Rachelle DeCoste, Lisa DeMeyer, Meera Mainkar, Allie Ray

We consider real 2-step metric nilpotent Lie algebras associated to graphs with possibly repeated edge labels as constructed by Ray in 2016. We determine how the structure of the egde labeling within the graph contributes to the abelian factor in these Lie algebras. Furthermore, we explicitly compute the abelian factor of the 2-step nilpotent Lie algebras as

Jacob Nelson-Slivon, Lewis Tseng, Roberto Palmieri

Coordinating concurrent access to a shared resource using mutual exclusion is a fundamental problem in computation. In this paper, we present a novel approach to mutual exclusion designed specifically for distributed systems leveraging a popular network communication technology, remote direct memory access (RDMA). Our approach enables local processes to avoi

Huiming Xie, Jean Honorio

In this paper, we consider the meta learning problem for estimating the graphs associated with high-dimensional Ising models, using the method of $\ell_1$-regularized logistic regression for neighborhood selection of each node. Our goal is to use the information learned from the auxiliary tasks in the learning of the novel task to reduce its sufficient sampl

Huseyin Bahtiyar

Recently, there have been significant developments in neural networks, which led to the frequent use of neural networks in the physics literature. This work is focused on predicting the masses of exotic hadrons, doubly charmed and bottomed baryons using neural networks trained on meson and baryon masses that are determined by experiments. The original data s

Timothy A. Elmslie, Jacob Startt, Yang Yang, Sujeily Soto-Medina

Magnetic properties of more than twenty Cantor alloy samples of varying composition were investigated over a temperature range of 5 K to 300 K and in fields of up to 70 kOe using magnetometry and muon spin relaxation. Two transitions are identified: a spin-glass-like transition that appears between 55 K and 190 K depending on composition, and a ferrimagnetic

Rohit Ranjan, Himadri Bhakta, Animesh Jha, Parv Maheshwari

This report covers our reproduction effort of the paper 'Differentiable Spatial Planning using Transformers' by Chaplot et al. . In this paper, the problem of spatial path planning in a differentiable way is considered. They show that their proposed method of using Spatial Planning Transformers outperforms prior data-driven models and leverages differentiabl

Bhaskar DasGupta, Elena Grigorescu, Tamalika Mukherjee

Characterizing shapes of high-dimensional objects via Ricci curvatures plays a critical role in many research areas in mathematics and physics. However, even though several discretizations of Ricci curvatures for discrete combinatorial objects such as networks have been proposed and studied by mathematicians, the computational complexity aspects of these dis

Sergey Bobkov, Gennadiy Chistyakov, Friedrich Götze

We give a detailed exposition of the proof of Richter's local limit theorem in a refined form, and establish the stability of the remainder term in this theorem under small perturbations of the underlying distribution (including smoothing). We also discuss related quantitative bounds for characteristic functions and Laplace transforms.

Michael D. Fried

To figure properties of a curve of form $C_{f,g} = {(x,y)| f(x) - g(y)= 0}$ you must address the genus 0 and 1 components of its projective normalization $\tilde C_{f,g}$. For $f$ and $g$ polynomials with $f$ indecomposable, [Fr73a] distinguished $\tilde C_{f,g}$ with $u=1$ versus $u > 1$ components (Schinzel's problem). For $u = 1$, [Prop. 1, Fr73b] gave a

R. Abbasi, M. Ackermann, J. Adams, N. Aggarwal

Using data from the IceCube Neutrino Observatory, we searched for high-energy neutrino emission from the gravitational-wave events detected by advanced LIGO and Virgo detectors during their third observing run. We did a low-latency follow-up on the public candidate events released during the detectors' third observing run and an archival search on the 80 con

Anton Cleverley, Richard Beanland

Recent interest in structure solution and refinement using electron diffraction (ED) has been fuelled by its inherent advantages when applied to crystals of sub-micron size, as well as a better sensitivity to light elements. Currently, data is often processed using software written for X-ray diffraction, using the kinematic theory of diffraction to generate

Marianne Guillet, Maximilian Schiffer

Current electric vehicle market trends indicate an increasing adoption rate across several countries. To meet the expected growing charging demand, it is necessary to scale up the current charging infrastructure and to mitigate current reliability deficiencies, e.g., due to broken connectors or misreported charging station availability status. However, even

Ali Vardasbi, Maarten de Rijke, Mostafa Dehghani

A common way to avoid overfitting in supervised learning is early stopping, where a held-out set is used for iterative evaluation during training to find a sweet spot in the number of training steps that gives maximum generalization. However, such a method requires a disjoint validation set, thus part of the labeled data from the training set is usually left

Manas Kar, Jesse Railo, Philipp Zimmermann

This article investigates nonlocal, fully nonlinear generalizations of the classical biharmonic operator $(-\Delta)^2$. These fractional $p$-biharmonic operators appear naturally in the variational characterization of the optimal fractional Poincar\'e constants in Bessel potential spaces. We study the following basic questions for anisotropic fractional $p$-

Yuri Bahturin, Alexander Olshanskii

We study finite-dimensional nonassociative algebras. We prove the implicit function theorem for such algebras. This allows us to establish a correspondence between such algebras and quasigroups, in the spirit of classical correspondence between divisible torsion-free nilpotent groups and rational nilpotent Lie algebras. We study the related questions of the

Gojko Vujanovic

The penetrating nature of electromagnetic probes makes them an ideal candidate to study properties of the Quark-Gluon Plasma (QGP). A selection of recent developments in the theory and phenomenology of electromagnetic probes is discussed, with an emphasis given towards how these probes can be used to constrain QGP trapnsport coefficients. A Bayesian treatmen

Lorenzo Martinico, Aydin Abadi, Thomas Zacharias, Thomas Win

The highly transmissible COVID-19 disease is a serious threat to people's health and life. To automate tracing those who have been in close physical contact with newly infected people and/or to analyse tracing-related data, researchers have proposed various ad-hoc programs that require being executed on users' smartphones. Nevertheless, the existing solution

G. S. Diniz, E. Vernek

In this work we investigate Majorana correlations in quantum impurities coupled to a topological superconducting wire. By employing a density matrix renormalization group approach, we have calculated the Majorana correlation functions in the ground state of the system for different positions of the impurities along the wire. We observe that the correlations

Robert J. Koch, Niraj Aryal, Oleh Ivashko, Yu Liu

Superconductivity in binary ruthenium pnictides occurs proximal to and upon suppression of a mysterious non-magnetic ground state, preceded by a pseudogap phase associated with Fermi surface instability, and its critical temperature, T$_{c}$, is maximized around the pseudogap quantum critical point. By analogy with isoelectronic iron based counterparts, anti

Will Rosenbaum

We consider packet forwarding in the adversarial queueing theory (AQT) model introduced by Borodin et al. We introduce a refinement of the AQT $(\rho, \sigma)$-bounded adversary, which we call a \emph{locally bursty adversary} (LBA) that parameterizes injection patterns jointly by edge utilization and packet origin. For constant ($O(1)$) parameters, the LBA

Zachary B. Huber, Steve K. Choi, Cody J. Duell, Rodrigo G. Freundt

The Epoch of Reionization Spectrometer (EoR-Spec) will be an instrument module for the Prime-Cam receiver on the CCAT-prime Collaboration's Fred Young Submillimeter Telescope (FYST), a 6-m primary mirror Crossed Dragone telescope. With its Fabry-Perot interferometer (FPI), EoR-Spec will step through frequencies between 210 and 420 GHz to perform line intensi

Bradley McDanel, Chi Phuong Huynh

We introduce the notion of a Patch Sampling Schedule (PSS), that varies the number of Vision Transformer (ViT) patches used per batch during training. Since all patches are not equally important for most vision objectives (e.g., classification), we argue that less important patches can be used in fewer training iterations, leading to shorter training time wi

Simon Kassing, Ingo Müller, Gustavo Alonso

Data lakes hold a growing amount of cold data that is infrequently accessed, yet require interactive response times. Serverless functions are seen as a way to address this use case since they offer an appealing alternative to maintaining (and paying for) a fixed infrastructure. Recent research has analyzed the potential of serverless for data processing. In

Ali Pourranjbar, Georges Kaddoum, Walid Saad

Conventional anti-jamming methods mainly focus on preventing single jammer attacks with an invariant jamming policy or jamming attacks from multiple jammers with similar jamming policies. These anti-jamming methods are ineffective against a single jammer following several different jamming policies or multiple jammers with distinct policies. Therefore, this

Douglas R. Turnbull, Sean McQuillan, Vera Crabtree, John Hunter

Popularity bias is the idea that a recommender system will unduly favor popular artists when recommending artists to users. As such, they may contribute to a winner-take-all marketplace in which a small number of artists receive nearly all of the attention, while similarly meritorious artists are unlikely to be discovered. In this paper, we attempt to measur

Michael Hoefnagel, Pierre-Alain Jacqmin

Matrix conditions extend linear Mal'tsev conditions from Universal Algebra to exactness properties in Category Theory. Some can be stated in the finitely complete context while, in general, they can only be stated for regular categories. We study when such a matrix condition implies the Mal'tsev property. Our main results assert that, for both types of matri

Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez

Representation learning often plays a critical role in reinforcement learning by managing the curse of dimensionality. A representative class of algorithms exploits a spectral decomposition of the stochastic transition dynamics to construct representations that enjoy strong theoretical properties in an idealized setting. However, current spectral methods suf

Raphael M. Tromer, Levi C. Felix, Cristiano F. Woellner, Douglas S. Galvao

Schwarzites are porous structures that present negative Gaussian curvatures. Although initially proposed for carbon, in principle, schwarzites of other elements are possible. In this work, we have carried out a detailed investigation of the effect of element composition (C, Ge, Si, SiC, and BN) on the structural, electronic and optical properties of a gyroid

Ryan Chard, Jim Pruyne, Kurt McKee, Josh Bryan

Research process automation -- the reliable, efficient, and reproducible execution of linked sets of actions on scientific instruments, computers, data stores, and other resources -- has emerged as an essential element of modern science. We report here on new services within the Globus research data management platform that enable the specification of divers

Valentina Salvatelli, Luiz F. G. dos Santos, Souvik Bose, Brad Neuberg

The Solar Dynamics Observatory (SDO), a NASA multi-spectral decade-long mission that has been daily producing terabytes of observational data from the Sun, has been recently used as a use-case to demonstrate the potential of machine learning methodologies and to pave the way for future deep-space mission planning. In particular, the idea of using image-to-im

David Stefan Lohr-Robles, Giovani Erick Morales-Hernández, Enrique Lopez-Moreno, Peter Otto Hess

A particular quantum phase transition (QPT) is studied at excited energies of light nuclei within the Semimicroscopic Algebraic Cluster Model (SACM), using a combination of catastrophe theory and a direct minimization of the potential. A distinct change from a compact nucleus to a nuclear molecule is described as a second order QPT occurring at a certain val

A. I. Breev, S. P. Gavrilov, D. M. Gitman

In the framework of strong-field QED with $x$-steps, we study vacuum mean values of the current density and energy--momentum tensor of the quantized spinor field placed in the so-called $L$-constant electric background. The latter background can be, for example, understood as the electric field confined between capacitor plates, which are separated by a suff

Michael Hoefnagel, Pierre-Alain Jacqmin

In a recent paper, an algorithm has been presented for determining implications between a particular kind of category theoretic property represented by matrices -- the so called `matrix properties'. In this paper we extend this algorithm to include matrix properties involving pointedness of a category, such as the properties of a category to be unital, stron

Joshua R. Nugent, Carina Marquez, Edwin D. Charlebois, Rachel Abbott

Cluster randomized trials (CRTs) often enroll large numbers of participants, but due to logistical and fiscal challenges, only a subset of participants may be selected for measurement of certain outcomes, and those sampled may, purposely or not, be unrepresentative of all participants. Missing data also present a challenge: if sampled individuals with measur

Wan-Jin Yeo, Eric Larson, Joonas Iivanainen, Amir Borna

Optically-pumped magnetometers (OPM) -- next-generation magnetoencephalography (MEG) sensors -- may be placed directly on the head, unlike the more commonly used superconducting quantum interference device (SQUID) sensors, which must be placed a few centimeters away. This allows for signals of higher spatial resolution to be captured, resulting in potentiall

M. F. Sousa, J. G. Coelho, J. C. N. de Araujo, S. O. Kepler

Double white dwarf (DWD) mergers are possibly the leading formation channel of massive, rapidly rotating, high-field magnetic white dwarfs (HFMWDs). However, the direct link connecting a DWD merger to any observed HFMWD is still missing. We here show that the HFMWDs SDSS J221141.80+113604.4 (hereafter J2211+1136) and ZTF J190132.9+145808.7 (hereafter J1901+1

Nazanin Bayati Chaleshtari, Fabrizio Pastore, Arda Goknil, Lionel C. Briand

Security testing aims at verifying that the software meets its security properties. In modern Web systems, however, this often entails the verification of the outputs generated when exercising the system with a very large set of inputs. Full automation is thus required to lower costs and increase the effectiveness of security testing. Unfortunately, to achie

R. Avella, J. Nisperuza, JP Rubio, D. Grajales

The time evolution of probability density, the ground-state fidelity and the entanglement of a Bose-Fermi mixture in a 1D double well potential, are studied through the two mode approximation. We found that the behaviour of the quantum return probability shows three distinct regions. The first region is characterized by a complete miscibility, and correlated

Per Calissendorff, Markus Janson, Laetitia Rodet, Rainer Köhler

Young M-type binaries are particularly useful for precise isochronal dating by taking advantage of their extended pre-main sequence evolution. Orbital monitoring of these low-mass objects becomes essential in constraining their fundamental properties, as dynamical masses can be extracted from their Keplerian motion. Here, we present the combined efforts of t

Sergey Finashin, Viatcheslav Kharlamov

We prove that the space of affine, transversal at infinity, non-singular real cubic surfaces has 15 connected components. We give a topological criterion to distinguish them and show also how these 15 components are adjacent to each other via wall-crossing.

Philip Easo

Let $(G_n)$ be a sequence of finite connected vertex-transitive graphs with volume tending to infinity. We say that a sequence of parameters $(p_n)$ is a percolation threshold if for every $\varepsilon > 0$, the proportion $\left\lVert K_1 \right\rVert$ of vertices contained in the largest cluster under bond percolation $\mathbb{P}_p^G$ satisfies both \[ \be

Pedro C. Neto, Tiago Gonçalves, João Ribeiro Pinto, Wilson Silva

As two sides of the same coin, causality and explainable artificial intelligence (xAI) were initially proposed and developed with different goals. However, the latter can only be complete when seen through the lens of the causality framework. As such, we propose a novel causality-inspired framework for xAI that creates an environment for the development of x

F. J. Beron-Vera, M. J. Olascoaga, L. Helfmann, P. Miron

In this note, we apply Transition Path Theory (TPT) from Markov chains to shed light on the problem of Iceland-Scotland Overflow Water (ISOW) equatorward export. A recent analysis of observed trajectories of submerged floats demanded revision of the traditional abyssal circulation theory, which postulates that ISOW should steadily flow along a deep boundary

Dariusz Buraczewski, Piotr Dyszewski, Alexander Marynych

We study a class of kinetic-type differential equations $\partial \phi_t/\partial t+\phi_t=\widehat{\mathcal{Q}}\phi_t$, where $\widehat{\mathcal{Q}}$ is an inhomogeneous smoothing transform and, for every $t\geq 0$, $\phi_t$ is the Fourier--Stieltjes transform of a probability measure. We show that under mild assumptions on $\widehat{\mathcal{Q}}$ the above

Daniel Keliher

We investigate the rank growth of elliptic curves from $\mathbb{Q}$ to $S_4$ and $A_4$ quartic extensions $K/\mathbb{Q}$. In particular, we are interested in the quantity $\mathrm{rk}(E/K) - \mathrm{rk}(E/\mathbb{Q})$ for fixed $E$ and varying $K$. When $\mathrm{rk}(E/\mathbb{Q}) \leq 1$, with $E$ subject to some other conditions, we prove there are infinite

Mikaela Irene Fudolig, Thayer Alshaabi, Kathryn Cramer, Christopher M. Danforth

While quantitative methods have been used to examine changes in word usage in books, studies have focused on overall trends, such as the shapes of narratives, which are independent of book length. We instead look at how words change over the course of a book as a function of the number of words, rather than the fraction of the book, completed at any given po

Agathe Lherondelle, Varun Babbar, Yash Satsangi, Fran Silavong

This paper presents Topical, a novel deep neural network for repository level embeddings. Existing methods, reliant on natural language documentation or naive aggregation techniques, are outperformed by Topical's utilization of an attention mechanism. This mechanism generates repository-level representations from source code, full dependency graphs, and scri

Udit Kumar Agarwal, Shikhar Makhija, Varun Tripathi, Kunwar Singh

The memristance of a memristor depends on the amount of charge flowing through it and when current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for implementation of memory units. Memristors find great application in neuromorphic circuits as it is possible to couple memory and processing, compared to traditional Von

Lisa Wölfer, Stefano Facchini, Nienke van der Marel, Ewine F. van Dishoeck

In recent years, high-angular-resolution observations of the dust and gas in circumstellar discs have revealed a variety of morphologies, naturally triggering the question of whether these substructures are driven by forming planets. While it remains difficult to directly image embedded planets, a promising method to distinguish disc-shaping mechanisms is to

Aaron Potechin, Paxton Turner, Prayaag Venkat, Alexander S. Wein

Given independent standard Gaussian points $v_1, \ldots, v_n$ in dimension $d$, for what values of $(n, d)$ does there exist with high probability an origin-symmetric ellipsoid that simultaneously passes through all of the points? This basic problem of fitting an ellipsoid to random points has connections to low-rank matrix decompositions, independent compon

Andrea Solfanelli, Guido Giachetti, Michele Campisi, Stefano Ruffo

The employment of long-range interactions in quantum devices provides a promising route towards enhancing their performance in quantum technology applications. Here, the presence of long-range interactions is shown to enhance the performances of a quantum heat engine featuring a many-body working substance. We focus on the paradigmatic example of a Kitaev ch

Dushko Kuzmanovski, Jonathan Schmidt, Nicola A. Spaldin, Henrik M. Rønnow

Dynamical perturbations modify the states of classical systems in surprising ways and give rise to important applications in science and technology. For example, Floquet engineering exploits the possibility of band formation in the frequency domain when a strong, periodic variation is imposed on parameters such as spring constants. We describe here Kapitza e

Michele Fava, Sarang Gopalakrishnan, Romain Vasseur, Fabian H. L. Essler

We demonstrate that nonlinear response functions in many-body systems carry a sharp signature of interactions between gapped low-energy quasiparticles. Such interactions are challenging to deduce from linear response measurements. The signature takes the form of a divergent-in-time contribution to the response -- linear in time in the case when quasiparticle

Eduardo Martín-Martínez, T. Rick Perche

We revisit the Bose-Marletto-Vedral (BMV) table-top experimental proposal - which aims to witness quantum gravity using gravity mediated entanglement - analyzing the role of locality in the experiment. We first carry out a fully quantum modelling of the interaction of matter and gravity and then show in what way gravity mediated entanglement in the BMV exper

William E. East, Frans Pretorius

Binary neutron star mergers, which can lead to less massive black holes relative to other known astrophysical channels, have the potential to probe modifications to general relativity that arise at smaller curvature scales compared to more massive compact object binaries. As a representative example of this, here we study binary neutron star mergers in shift

Gang Li, Sébastien Deheuvels, Jérôme Ballot, François Lignières

A red giant star is an evolved low- or intermediate-mass star that has exhausted its central hydrogen content, leaving a helium core and a hydrogen-burning shell. Oscillations of stars can be observed as periodic dimmings and brightenings in the optical light curves. In red giant stars, non-radial acoustic waves couple to gravity waves and give rise to mixed

Zian Wang, Wenzheng Chen, David Acuna, Jan Kautz

We consider the challenging problem of outdoor lighting estimation for the goal of photorealistic virtual object insertion into photographs. Existing works on outdoor lighting estimation typically simplify the scene lighting into an environment map which cannot capture the spatially-varying lighting effects in outdoor scenes. In this work, we propose a neura

Ian J. M. Crossfield, Matej Malik, Michelle L. Hill, Stephen R. Kane

The increasing numbers of rocky, terrestrial exoplanets known to orbit nearby stars (especially M dwarfs) has drawn increased attention to the possibility of studying these planets' surface properties, and atmospheric compositions & escape histories. Here we report the detection of the secondary eclipse of the terrestrial exoplanet GJ1252b using the Spitzer

Yuto Hoshino, Hiroki Kawakami, Hiroki Matsutani

Federated learning is a distributed machine learning approach in which clients train models locally with their own data and upload them to a server so that their trained results are shared between them without uploading raw data to the server. There are some challenges in federated learning, such as communication size reduction and client heterogeneity. The

Alain J. Brizard, Anthony A. Chan

Hamiltonian formulations of quasilinear theory are presented for the cases of uniform and nonuniform magnetized plasmas. First, the standard quasilinear theory of Kennel and Engelmann (1966) is reviewed and reinterpreted in terms of a general Hamiltonian formulation. Within this Hamiltonian representation, we present the transition from two-dimensional quasi

Michael D. Fried

Using Felgner's problem I revisit a key issue in using the "Galois Stratification Procedure" that first appeared in [FrS76]. The emphasis here is on using arithmetic homotopy to make the production of Poincare; series attached to general diophantine statements canonical. According to work in progress of Michael Benedikt and E. Hrushovski, Galois stratificati

Nikola Maksimovic, Ryan Day, Na-Hyun Jo, Chris Jozwiak

Metallic ferromagnets with strongly interacting electrons often exhibit remarkable electronic phases such as ferromagnetic superconductivity, complex spin textures, and nontrivial topology. In this report, we discuss the synthesis of a layered magnetic metal NiTa$_4$Se$_8$ (or Ni$_{1/4}$TaSe$_{2}$) with a Curie temperature of 58 Kelvin. Magnetization data an

Younghan Bae, Martijn Kool, Hyeonjun Park

This is the first part in a series of papers on counting surfaces on Calabi-Yau 4-folds. Besides the Hilbert scheme of 2-dimensional subschemes, we introduce \emph{two} types of moduli spaces of stable pairs. We show that all three moduli spaces are related by GIT wall-crossing and parametrize stable objects in the bounded derived category. We construct \emp

Antonios Mamalakis, Elizabeth A. Barnes, Imme Ebert-Uphoff

Methods of eXplainable Artificial Intelligence (XAI) are used in geoscientific applications to gain insights into the decision-making strategy of Neural Networks (NNs) highlighting which features in the input contribute the most to a NN prediction. Here, we discuss our lesson learned that the task of attributing a prediction to the input does not have a sing

Prakash Sarkar, Biswajit Pandey, Suman Sarkar

Filaments and sheets are striking visual patterns in cosmic web. The maximum extent of these large-scale structures are difficult to determine due to their structural variety and complexity. We construct a volume-limited sample of galaxies in a cubic region from the SDSS, divide it into smaller subcubes and shuffle them around. We quantify the average filame

Jason Olsthoorn

Turbulent Rayleigh-B\'{e}nard convection is often modelled with a constant surface temperature. However, the surface temperature of many geophysical systems, such as lakes, is coupled to the atmospheric forcing. In this paper, we account for this dynamic surface temperature through an additional parameter $\beta$. Using an appropriately defined dynamical Ray

Abhijit Biswas, Qiyuan Ruan, Frank Lee, Chenxi Li

Two-dimensional van der Waals (2D-vdW) layered hexagonal boron nitride (h-BN) has gained tremendous research interest over recent years due to its unconventional domain growth morphology, fascinating properties and application potentials as an excellent dielectric layer for 2D-based nano-electronics. However, the unidirectional domain growth of h-BN thin fil

Abhijit Biswas, Rishi Maiti, Frank Lee, Cecilia Y. Chen

Room temperature growth of two-dimensional van der Waals (2D-vdW) materials is indispensable for state-of-the-art nanotechnology. The low temperature growth supersedes the requirement of elevated growth temperature accompanied with high thermal budgets. Moreover, for electronic applications, low or room temperature growth reduces the possibility of intrinsic

Giacomo Cordoni, Antonino P. Milone, Anna F. Marino, Michele Cignoni

The origin of young star clusters represents a major challenge for modern stellar astrophysics. While stellar rotation partially explains the colour spread observed along main-sequence turn-offs, i.e. where stars leave the main-sequence after the exhaustion of hydrogen in their core, and the multiple main sequences in the colour-magnitude diagrams of stellar

Vyas Raina, Mark Gales

Grammatical Error Correction (GEC) systems perform a sequence-to-sequence task, where an input word sequence containing grammatical errors, is corrected for these errors by the GEC system to output a grammatically correct word sequence. With the advent of deep learning methods, automated GEC systems have become increasingly popular. For example, GEC systems

Aleks Scholz, Koraljka Muzic, Ray Jayawardhana, Lyra Quinlan

Free-floating (or rogue) planets are planets that are liberated (or ejected) from their host systems. Although simulations predict their existence in substantial numbers, direct observational evidence for free-floating planets with masses below ~5 MJup is still lacking. Several cycle-1 observing programs with JWST aim to hunt for them in four different star-

Alonso J. Campos-Hernandez, Yang Zhang, Adolfo G. Grushin, Fernando de Juan

The generation of shift and ballistic photocurrents in non-centrosymmetric materials represents a promising alternative mechanism for light energy harvesting. Many studies have focused on finding the best suited materials by maximizing the photocurrent magnitude, but estimating the actual efficiency requires knowledge of the light-induced DC photoconductivit

Nagabhushan Somraj, Pranali Sancheti, Rajiv Soundararajan

The challenge of graphically rendering high frame-rate videos on low compute devices can be addressed through periodic prediction of future frames to enhance the user experience in virtual reality applications. This is studied through the problem of temporal view synthesis (TVS), where the goal is to predict the next frames of a video given the previous fram

Juan Carlos Hidalgo, Luis E. Padilla, Gabriel German

At times prior to Big Bang Nucleosynthesis, the universe could show a primordial structure formation period if dominated by a fast oscillating inflaton field during reheating. In this context, we have postulated a new mechanism of primordial black hole formation [L. E. Padilla, J. C. Hidalgo, and K. A. Malik, Phys. Rev. D, vol. 106, p. 023519, Jul 2022], tha

Charles Packard, Daniel M. Sussman

Many models of flocking involve alignment rules based on the mean orientation of neighboring particles, which we show introduces microscopic non-reciprocal interactions. In the absence of this microscopic non-reciprocity an exceptional phase transition is predicted at low noise strength within the Toner-Tu framework of polar aligning matter; we demonstrate t

Fabian Marxer, Antti Vepsäläinen, Shan W. Jolin, Jani Tuorila

Tunable coupling of superconducting qubits has been widely studied due to its importance for isolated gate operations in scalable quantum processor architectures. Here, we demonstrate a tunable qubit-qubit coupler based on a floating transmon device which allows us to place qubits at least 2 mm apart from each other while maintaining over 50 MHz coupling bet

Dale Frymark, Jessica Stewart Kelly

Exceptional Laguerre-type differential expressions make up an infinite class of Schr\"odinger operators having rational potentials and one limit-circle endpoint. In this manuscript, the spectrum of all self-adjoint extensions for a general exceptional Laguerre-type differential expression is given in terms of the Darboux transformations which relate the expr

Samuel Brevitt, Rainer Klages

The Pomeau-Manneville map is a paradigmatic intermittent dynamical system exhibiting weak chaos and anomalous dynamics. In this paper we analyse the parameter dependence of superdiffusion for the map lifted periodically onto the real line. From numerical simulations we compute the generalised diffusion coefficient (GDC) of this model as a function of the map