November 2022 arXiv papers — page 56

Maureen Cohen, Massimo A. Bollasina, Denis E. Sergeev, Paul I. Palmer

Cloud cover at the planetary limb of water-rich Earth-like planets is likely to weaken chemical signatures in transmission spectra, impeding attempts to characterize these atmospheres. However, based on observations of Earth and solar system worlds, exoplanets with atmospheres should have both short-term weather and long-term climate variability, implying th

Pascal Leroy, Jonathan Pisane, Damien Ernst

In this paper, we identify the best learning scenario to train a team of agents to compete against multiple possible strategies of opposing teams. We evaluate cooperative value-based methods in a mixed cooperative-competitive environment. We restrict ourselves to the case of a symmetric, partially observable, two-team Markov game. We selected three training

Tobias Reinhard

In this early technical report on an ongoing project, we present -- to the best of our knowledge -- the first study of completeness thresholds for memory safety proofs. Specifically we consider heap-manipulating programs that iterate over arrays without allocating or freeing memory. We present the first notion of completeness thresholds for program verificat

Predrag Pilipovic, Adeline Samson, Susanne Ditlevsen

The likelihood functions for discretely observed nonlinear continuous-time models based on stochastic differential equations are not available except for a few cases. Various parameter estimation techniques have been proposed, each with advantages, disadvantages, and limitations depending on the application. Most applications still use the Euler-Maruyama dis

Aditi Agrawal, Archit Jain, Benjamin Reed

CodEval is a code evaluation tool that integrates with the Canvas Learning Management System to automatically evaluates students' work within a few minutes of the submission. This early feedback allows students to catch and correct problems in their submissions before their submission is graded and gives them a clear idea of the quality of their submission.

Michael Reefe, Remington O. Sexton, Sara M. Doan, Shobita Satyapal

Coronal lines are a powerful, yet poorly understood, tool to identify and characterize Active Galactic Nuclei (AGNs). There have been few large scale surveys of coronal lines in the general galaxy population in the literature so far. Using a novel pre-selection technique with a flux-to-RMS ratio $F$, followed by Markov-Chain Monte Carlo (MCMC) fitting, we se

Miguel F. Morales, Jonathan Pober, Bryna J. Hazelton

Through a very careful analysis Kolopanis and collaborators identified a negative power spectrum (PS) systematic. The 21 cm cosmology community has assumed that any observational systematics would add power, as negative PS are non-physical. In addition to the mystery of their origin, negative PS systematics raise the spectre of artificially lowering upper li

Natalie Abreu, Nathan Vaska, Victoria Helus

Robustness in deep neural networks and machine learning algorithms in general is an open research challenge. In particular, it is difficult to ensure algorithmic performance is maintained on out-of-distribution inputs or anomalous instances that cannot be anticipated at training time. Embodied agents will be deployed in these conditions, and are likely to ma

Chin-Wei Hsu, Hun-Seok Kim, Achilleas Anastasopoulos

Variable-length feedback codes can provide advantages over fixed-length feedback or non-feedback codes. This letter focuses on uncoded variable-symbol-length feedback communication and analyzes the autocorrelation and spectrum of the signal. We provide a mathematical expression for the autocorrelation that can be evaluated numerically. We then numerically ev

Ziyi Wang, Augustinos D. Saravanos, Hassan Almubarak, Oswin So

We systematically review the Variational Optimization, Variational Inference and Stochastic Search perspectives on sampling-based dynamic optimization and discuss their connections to state-of-the-art optimizers and Stochastic Optimal Control (SOC) theory. A general convergence and sample complexity analysis on the three perspectives is provided through the

Lubomíra Dvořáková, Edita Pelantová

We colour the Fibonacci sequence by suitable constant gap sequences to provide an upper bound on the asymptotic repetitive threshold of $d$-ary balanced sequences. The bound is attained for $d=2, 4$ and $8$ and we conjecture that it happens for infinitely many even $d$'s. Our bound reveals an essential difference in behavior of the repetitive threshold and t

Christian Gourieroux, Joann Jasiak

This paper considers nonlinear dynamic models where the main parameter of interest is a nonnegative matrix characterizing the network (contagion) effects. This network matrix is usually constrained either by assuming a limited number of nonzero elements (sparsity), or by considering a reduced rank approach for nonnegative matrix factorization (NMF). We follo

Eric Mitchell, Joseph J. Noh, Siyan Li, William S. Armstrong

While large pre-trained language models are powerful, their predictions often lack logical consistency across test inputs. For example, a state-of-the-art Macaw question-answering (QA) model answers 'Yes' to 'Is a sparrow a bird?' and 'Does a bird have feet?' but answers 'No' to 'Does a sparrow have feet?'. To address this failure mode, we propose a framewor

Guoqing Zhang, Qianwen Zhao, Long Wang

Most aerial manipulators use serial rigid-link designs, which results in large forces when initiating contacts during manipulation and could cause flight stability difficulty. This limitation could potentially be improved by the compliance of continuum manipulators. To achieve this goal, we present the novel design of a compact, lightweight, and modular cabl

Li Xiang, Dominic H. Ryan, Paul C. Canfield, Sergey L. Bud'ko

The structural characterization and electrical transport measurements at ambient and applied pressures of the compounds of the La(Ag1-xAux)Sb2 family are presented. Up to two charge density wave (CDW) transitions could be detected upon cooling from room temperature and an equivalence of the effects of chemical and physical pressure on the CDW ordering temper

Sanya Sinha, Nilay Gupta

Skin cancer is a fatal disease that takes a heavy toll over human lives annually. The colored skin images show a significant degree of resemblance between different skin lesions such as melanoma and nevus, making identification and diagnosis more challenging. Melanocytic nevi may mature to cause fatal melanoma. Therefore, the current management protocol invo

Matteo Levi, Federico Santagati

We study the mapping properties of the Hardy--Littlewood fractional maximal operator between Lorentz spaces of the homogeneous tree and discuss the optimality of all the results.

Fengyi Shen, Zador Pataki, Akhil Gurram, Ziyuan Liu

Due to the lack of training labels and the difficulty of annotating, dealing with adverse driving conditions such as nighttime has posed a huge challenge to the perception system of autonomous vehicles. Therefore, adapting knowledge from a labelled daytime domain to an unlabelled nighttime domain has been widely researched. In addition to labelled daytime da

Anton Dereventsov, Andrew Starnes, Clayton G. Webster

This effort is focused on examining the behavior of reinforcement learning systems in personalization environments and detailing the differences in policy entropy associated with the type of learning algorithm utilized. We demonstrate that Policy Optimization agents often possess low-entropy policies during training, which in practice results in agents prior

Armin van de Venn, David Vasak, Johannes Kirsch, Jürgen Struckmeier

The Covariant Canonical Gauge theory of Gravity (CCGG) is a gauge field formulation of gravity which a priori includes non-metricity and torsion. It extends the Lagrangian of Einstein's theory of general relativity by terms at least quadratic in the Riemann-Cartan tensor. This paper investigates the implications of metric compatible CCGG on cosmological scal

Phillip Allen Lane, Jessica Lobrano

With the rapid growth of AMD as a competitor in the CPU industry, it is imperative that high-performance and architectural engineers analyze new AMD CPUs. By understanding new and unfamiliar architectures, engineers are able to adapt their algorithms to fully utilize new hardware. Furthermore, engineers are able to anticipate the limitations of an architectu

Michael Kuchnik, Virginia Smith, George Amvrosiadis

Although large language models (LLMs) have been touted for their ability to generate natural-sounding text, there are growing concerns around possible negative effects of LLMs such as data memorization, bias, and inappropriate language. Unfortunately, the complexity and generation capacities of LLMs make validating (and correcting) such concerns difficult. I

Luke Thomas Peachey

Ricci flow spacetimes were introduced by Kleiner & Lott as a way to describe Ricci flow through singularities, and have since been used elsewhere in the literature, prompting the question of their rigidity. In $(2+1)$-dimensions, we show that every complete and sufficiently regular spacetime must be a cylindrical spacetime. That is, if the metric is complete

Martin Magris, Alexandros Iosifidis

The last decade witnessed a growing interest in Bayesian learning. Yet, the technicality of the topic and the multitude of ingredients involved therein, besides the complexity of turning theory into practical implementations, limit the use of the Bayesian learning paradigm, preventing its widespread adoption across different fields and applications. This sel

Jeremy Echeverria, Maximiliano Binder, Ivan Schmidt

We apply the functional renormalization group approach to a $\mathcal{N}=1$ supersymmetric gauge model with one chiral superfield coupled to a vector $U(1)$ superfield. We find that the nonrenormalization theorem still works at leading order in the supercovariant derivative expansion of the fields. We also find the beta functions and we study the behavior of

Hongchao Shu, Ruixing Liang, Zhaoshuo Li, Anna Goodridge

Purpose: Digital twins are virtual interactive models of the real world, exhibiting identical behavior and properties. In surgical applications, computational analysis from digital twins can be used, for example, to enhance situational awareness. Methods: We present a digital twin framework for skull-base surgeries, named Twin-S, which can be integrated with

Jean-François Delmas, Dylan Dronnier, Pierre-André Zitt

Motivated by the question of optimal vaccine allocation strategies in heterogeneous population for epidemic models, we study various properties of the \emph{effective reproduction number}. In the simplest case, given a fixed, non-negative matrix $K$, this corresponds mathematically to the study of the spectral radius $R_e(\eta)$ of the matrix product $\mathr

Salvatore Spina

This essay aims to bid analogue historians assume that digitisation is the first step to creating historical heritage based on the new language of Science: Computer Science. As we know, Humanities disciplines cannot easily be encapsulated in a few understandable numbers and names. However, historians must boost Artificial Intelligence (such as Transkribus) a

Sophie Huiberts, Yin Tat Lee, Xinzhi Zhang

The simplex method for linear programming is known to be highly efficient in practice, and understanding its performance from a theoretical perspective is an active research topic. The framework of smoothed analysis, first introduced by Spielman and Teng (JACM '04) for this purpose, defines the smoothed complexity of solving a linear program with $d$ variabl

Aleksey S. Gvozdarev

The proposed research performs the capacity analysis of the wireless channel described by the fluctuating double-Rayleigh with the line-of-sight model. The closed-form analytical expressions for the conditional capacity (in the case of arbitrary noninteger fading parameter) and the ergodic capacity (in the case of the integer fading parameter) are derived in

Temple He, Veronika E. Hubeny, Massimiliano Rota

Given a multipartite quantum system, what are the possible ways to impose mutual independence among some subsystems, and the presence of correlations among others, such that there exists a quantum state which satisfies these demands? This question and the related notion of a \textit{pattern of marginal independence} (PMI) were introduced in arXiv:1912.01041,

N. I. Chott, R. W. Schnee

Radon emanation was projected to account for $>50$% of the electron recoil background in the WIMP region of interest for the LUX-ZEPLIN (LZ) experiment. To mitigate the amount of radon inside the detector volume, materials with inherently low radioactivity content were selected for LZ construction through an extensive screening campaign. The SD Mines radon e

Neerja Mhaskar, W. F. Smyth

The study of strings is an important combinatorial field that precedes the digital computer. Strings can be very long, trillions of letters, so it is important to find compact representations. Here we first survey various forms of one potential compaction methodology, the cover of a given string x, initially proposed in a simple form in 1990, but increasingl

Chaoqun Shen, Jiliang Zhang, Gang Qu

Multi-process concurrency is effective in improving program efficiency and maximizing CPU utilization. The correct execution of concurrency is ensured by the mutual exclusion and synchronization mechanism (MESM) that manages the shared hardware and software resources. We propose MES-Attacks, a new set of software-controlled covert channel attacks based on ME

Bruno de Mendonça Braga, Timur Oikhberg

The nonlinear geometry of operator spaces has recently started to be investigated. Many notions of nonlinear embeddability have been introduced so far, but, as noticed before by other authors, it was not clear whether they could be considered ``correct notions''. The main goal of these notes is to provide the missing evidence to support that \emph{almost com

Adrián Javaloy, Pablo Sanchez-Martin, Amit Levi, Isabel Valera

Existing Graph Neural Networks (GNNs) compute the message exchange between nodes by either aggregating uniformly (convolving) the features of all the neighboring nodes, or by applying a non-uniform score (attending) to the features. Recent works have shown the strengths and weaknesses of the resulting GNN architectures, respectively, GCNs and GATs. In this w

K. Łempicka-Mirek, M. Król, L. De Marco, A. Coriolano

Efficient optical classical and quantum information processing imposes on light novel requirements: chirality with low threshold non-linearities. In this work we demonstrate a chiral lasing from an optical modes due to emerging photonic Rashba-Dresselhaus spin-orbit coupling (SOC). For this purpose we developed a new electrically tunable device based on an o

Robert D. Polak, Michael R. Harris, Kiet A. Nguyen, Anthony Kearns

We have created an experimental procedure for determining the temperature coefficient of resistivity, $\alpha_R$, for introductory physics laboratories. This method examines the relationship between temperature and resistivity to establish $\alpha_R$ within 10% of the accepted value.

Arvind Rajaraman

We develop a method for finding the independent invariant tensors of a gauge theory. Our method uses a theorem relating invariant tensors and constant configurations in field space. We apply our method to an $SU(3)$ gauge theory with matter in the adjoint representation, and find the independent invariant tensors of this theory.

Ana Flack, Satya N. Majumdar, Gregory Schehr

We consider the jellium model of $N$ particles on a line confined in an external harmonic potential and with a pairwise one-dimensional Coulomb repulsion of strength $\alpha > 0$. Using a Coulomb gas method, we study the statistics of $s = (1/N) \sum_{i=1}^N f(x_i)$ where $f(x)$, in principle, is an arbitrary smooth function. While the mean of $s$ is easy to

B. Posselt, A. Karastergiou, S. Johnston, A. Parthasarathy

We present the largest single survey to date of average profiles of radio pulsars, observed and processed using the same telescope and data reduction software. Specifically, we present measurements for 1170 pulsars, observed by the Thousand Pulsar Array (TPA) programme at the 64-dish SARAO MeerKAT radio telescope, in a frequency band from 856 to 1712 MHz. We

Nikunjkumar Prajapati, Narayan Bhusal, Andrew P. Rotunno, Samuel Berweger

We investigate the sensitivity of three-photon EIT in Rydberg atoms to radio frequency detection and compare it against conventional two-photon systems. Specifically, we model the 4-level and 5-level atomic system and compare how the transmission of the probe changes with different powers of the lasers used and strengths of the RF field. In this model, we al

Guangyu Ren, Michalis Lazarou, Jing Yuan, Tania Stathaki

Polyp segmentation is a crucial step towards computer-aided diagnosis of colorectal cancer. However, most of the polyp segmentation methods require pixel-wise annotated datasets. Annotated datasets are tedious and time-consuming to produce, especially for physicians who must dedicate their time to their patients. We tackle this issue by proposing a novel fra

Arnold Filtser

Chan, Har-Peled, and Jones [SICOMP 2020] developed locality-sensitive orderings (LSO) for Euclidean space. A $(\tau,\rho)$-LSO is a collection $\Sigma$ of orderings such that for every $x,y\in\mathbb{R}^d$ there is an ordering $\sigma\in\Sigma$, where all the points between $x$ and $y$ w.r.t. $\sigma$ are in the $\rho$-neighborhood of either $x$ or $y$. In e

Anton Kabelac, Georg Wolschin

We calculate the time-dependent formation of Bose--Einstein condensates (BECs) in potassium vapours based on a previously derived exactly solvable nonlinear boson diffusion equation (NBDE). Thermalization following a sudden energy quench from an initial temperature $T_\mathrm{i}$ to a final temperature $T_\mathrm{f}$ below the critical value and BEC formatio

Felix Riexinger, Mirco Kutas, Björn Haase, Michael Bortz

Quantum sensing encompasses highly promising techniques with diverse applications including noise-reduced imaging, super-resolution microscopy as well as imaging and spectroscopy in challenging spectral ranges. These detection schemes use biphoton correlations to surpass classical limits or transfer information to different spectral ranges. Theoretical analy

Kevin Dai, Ravesh Sukhnandan, Michael Bennington, Karen Whirley

Living systems can use a single periphery to perform a variety of tasks and adapt to a dynamic environment. This multifunctionality is achieved through the use of neural circuitry that adaptively controls the reconfigurable musculature. Current robotic systems struggle to flexibly adapt to unstructured environments. Through mimicry of the neuromechanical cou

Luke Fina, Matthew Hale

We solve large-scale mixed-integer linear programs (MILPs) via distributed asynchronous saddle point computation. This is motivated by the MILPs being able to model problems in multi-agent autonomy, e.g., task assignment problems and trajectory planning with collision avoidance constraints in multi-robot systems. To solve a MILP, we relax it with a nonlinear

Madison Brady, Jacob Bean, Andreas Seifahrt, David Kasper

A star's obliquity with respect to its planetary system can provide us with insight into the system's formation and evolution, as well as hinting at the presence of additional objects in the system. However, M dwarfs, which are the most promising targets for atmospheric follow-up, are underrepresented in terms of obliquity characterization surveys due to the

Benjamín M. Moraga

For an arbitrary 5-fold ramified covering between compact Riemann surfaces, every possible Galois closure is determined in terms of the ramification data of the map; namely, the ramification divisor of the covering map. Since the group that acts on the Galois closure also acts on the Jacobian variety of the covering surface, we describe its group algebra dec

Lily Chung, Erik D. Demaine

We investigate the complexity of the platform video game Celeste. We prove that navigating Celeste is PSPACE-hard in five different ways, corresponding to different subsets of the game mechanics. In particular, we prove the game PSPACE-hard even without player input.

Arindam Ghosh, Thomas Schaaf, Matthew R. Gormley

Much recent work has been devoted to the problem of ensuring that a neural network's confidence scores match the true probability of being correct, i.e. the calibration problem. Of note, it was found that training with focal loss leads to better calibration than cross-entropy while achieving similar level of accuracy \cite{mukhoti2020}. This success stems fr

Xiaoyin Li, Feng Liu

Topology is a key ingredient driving the emergence of quantum devices. Topological field-effect transistor (TFET) has been proposed to outperform the conventional FET by replacing the ON state with topology-protected quantized conductance, while the OFF state remains the same normal insulating characteristics and hence bears similar drawbacks. Here, we demon

David Ramirez, Suren Jayasuriya, Andreas Spanias

Mixed reality (MR) is a key technology which promises to change the future of warfare. An MR hybrid of physical outdoor environments and virtual military training will enable engagements with long distance enemies, both real and simulated. To enable this technology, a large-scale 3D model of a physical environment must be maintained based on live sensor obse

Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck

The remarkable performance of deep learning models and their applications in consequential domains (e.g., facial recognition) introduces important challenges at the intersection of equity and security. Fairness and robustness are two desired notions often required in learning models. Fairness ensures that models do not disproportionately harm (or benefit) so

Kostas I. Psaromiligkos

We construct the Lafforgue variety, an affine scheme equipped with an open dense subscheme parametrizing the simple modules of a non-commutative unital algebra $R$ over any field $k$, provided that the center $Z(R)$ is finitely generated and $R$ is finitely generated as a $Z(R)$-module. Our main technical tool is a generalization of the Hilbert scheme for no

Paolo Gambino, Shoji Hashimoto, Sandro Mächler, Marco Panero

We present the lattice QCD calculation of inclusive semileptonic $B_s$-meson decays. We follow a recently proposed method, which is based on the extraction of smeared spectral densities from Euclidean correlation functions and on the numerical reconstruction of the integration kernel relevant for the inclusive decay rate calculation. We compute four-point Eu

Alfredo Naef, Ted V. Tsoulos, Giulia Tagliabue

Thermonanophotonics, i.e. the study of photothermal effects in optical nanoantennas, has recently attracted growing interest. While thermoplasmonic structures enable a broad range of applications, from imaging and optofluidics devices to medical and photochemical systems, dielectric nanoantennas open new opportunities for thermo-optical modulation and reconf

Dong Liu, Nicolas Brantut

The rheology of rocks transitions from a localized brittle behaviour to distributed plastic behaviour with increasing pressure and temperature. This brittle-plastic is empirically observed to occur when the material strength becomes lower than the confining stress, which is termed Goetze's criterion. Such a criterion works well for most silicates but is not

Gargya Gokhale, Bert Claessens, Chris Develder

Large-scale integration of intermittent renewable energy sources calls for substantial demand side flexibility. Given that the built environment accounts for approximately 40% of total energy consumption in EU, unlocking its flexibility is a key step in the energy transition process. This paper focuses specifically on energy flexibility in residential buildi

Montie Avery

We show that propagation speeds in invasion processes modeled by reaction-diffusion systems are determined by marginal spectral stability conditions, as predicted by the marginal stability conjecture. This conjecture was recently settled in scalar equations; here we give a full proof for the multi-component case. The main new difficulty lies in precisely cha

Andre Nobre Barrocas, Alberto Rodrigues da Silva, Joao Paulo Saraiva

Considering the market's competitiveness and the complexity of organizations and projects, analyzing data is crucial to decision support on software development and project management processes. These practices are essential to increase performance, reduce costs and risks of failure, and guarantee the quality of results, keeping the work organized and contro

Sean Man, Guy Ohayon, Theo Adrai, Michael Elad

JPEG is arguably the most popular image coding format, achieving high compression ratios via lossy quantization that may create visual artifacts degradation. Numerous attempts to remove these artifacts were conceived over the years, and common to most of these is the use of deterministic post-processing algorithms that optimize some distortion measure (e.g.,

Ali Kaya

The wave-function in quantum gravity is supposed to obey the Wheeler-DeWitt (WDW) equation, however there is neither a satisfactory probability interpretation nor a successful solution to the problem of time in the WDW framework. To gain some insight on these issues we compare quantization of ordinary systems, first in the usual way having the Schr\"{o}dinge

Chen Naveh, Yacov Hel-Or

This paper describes a new technique for finding disentangled semantic directions in the latent space of StyleGAN. Our method identifies meaningful orthogonal subspaces that allow editing of one human face attribute, while minimizing undesired changes in other attributes. Our model is capable of editing a single attribute in multiple directions, resulting in

Van Duong Dinh, Sahbi Keraani

We consider a class of biharmonic nonlinear Schr\"odinger equations with a focusing inhomogeneous power-type nonlinearity \[ i\partial_t u -\Delta^2 u+\mu\Delta u +|x|^{-b} |u|^\alpha u=0, \quad \left. u\right|_{t=0}=u_0 \in H^2(\mathbb{R}^d) \] with $d\geq 1, \mu\geq 0$, $0<b<\min\{d,4\}$, $\alpha>0$, and $\alpha<\frac{8-2b}{d-4}$ if $d\geq 5$. We first det

Hans Christian Öttinger

For the Yang-Mills-type gauge-field theory with Lorentz symmetry group, we propose and verify an explicit expression for the conserved currents in terms of the energy-momentum tensor. A crucial ingredient is the assumption that the gauge symmetry arises from the decomposition of a metric in terms of tetrad variables. The currents exist under the weak conditi

Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones

In this paper, the CONFIG algorithm, a simple and provably efficient constrained global optimization algorithm, is applied to optimize the closed-loop control performance of an unknown system with unmodeled constraints. Existing Gaussian process based closed-loop optimization methods, either can only guarantee local convergence (e.g., SafeOPT), or have no kn

A. A. Araújo Filho, J. R. Nascimento, A. Yu. Petrov, P. J. Porfírio

We consider a metric-affine extension to the gravitational sector of the Standard-Model Extension for the Lorentz-violating coefficients $u$ and $s^{\mu\nu}$. The general results, which are applied to a specific model called metric--affine bumblebee gravity, are obtained. A Schwarzschild-like solution, incorporating effects of the Lorentz symmetry breaking t

Anna Kwa, Spencer K. Clark, Brian Henn, Noah D. Brenowitz

Due to computational constraints, running global climate models (GCMs) for many years requires a lower spatial grid resolution (${\gtrsim}50$ km) than is optimal for accurately resolving important physical processes. Such processes are approximated in GCMs via subgrid parameterizations, which contribute significantly to the uncertainty in GCM predictions. On

Aris Daniilidis, Laurent Miclo, David Salas

The norm of the gradient $\nabla$f (x) measures the maximum descent of a real-valued smooth function f at x. For (nonsmooth) convex functions, this is expressed by the distance dist(0, $\partial$f (x)) of the subdifferential to the origin, while for general real-valued functions defined on metric spaces by the notion of metric slope |$\nabla$f |(x). In this

Pietro Beri, Laurent Manivel

Given a general K3 surface S of degree 18, lattice theoretic considerations allow to predict the existence of an anti-symplectic birational involution $\phi$ of the Hilbert cube $S^{[3]}$. We describe this involution in terms of the Mukai model of $S$, with the help of the famous transitive action of the exceptional group $G_2(R)$ on the six-dimensional sphe

John Gliksberg, Jean-Noel Quintin, Pedro Javier Garcia

High-Performance Computing (HPC) clusters are made up of a variety of node types (usually compute, I/O, service, and GPGPU nodes) and applications don't use nodes of a different type the same way. Resulting communication patterns reflect organization of groups of nodes, and current optimal routing algorithms for all-to-all patterns will not always maximize p

John Gliksberg, Antoine Capra, Alexandre Louvet, Pedro Javier Garcia

Coupling regular topologies with optimized routing algorithms is key in pushing the performance of interconnection networks of HPC systems. In this paper we present Dmodc, a fast deterministic routing algorithm for Parallel Generalized Fat-Trees (PGFTs) which minimizes congestion risk even under massive topology degradation caused by equipment failure. It ap

Uwe Hassler

The controversy about statistical significance vs. scientific relevance is more than 100 years old. But still nowadays null hypothesis significance testing is considered as gold standard in many empirical fields from economics and social sciences over psychology to medicine, and small $p$-values are often the key to publish in journals of high scientific rep

Paul Laurain

We prove that simply connected H-surfaces with small diameter in a 3-manifold necessarily concentrate at a critical point of the scalar curvature.

Hanlin Mo, Guoying Zhao

In recent years, convolutional neural network has shown good performance in many image processing and computer vision tasks. However, a standard CNN model is not invariant to image rotations. In fact, even slight rotation of an input image will seriously degrade its performance. This shortcoming precludes the use of CNN in some practical scenarios. Thus, in

Yann de Mont-Marin, Jean Ponce, Jean-Paul Laumond

Borrowing elementary ideas from solid mechanics and differential geometry, this presentation shows that the volume swept by a regular solid undergoing a wide class of volume-preserving deformations induces a rather natural metric structure with well-defined and computable geodesics on its configuration space. This general result applies to concrete classes o

Daniel Grier, Hakop Pashayan, Luke Schaeffer

We consider the classical shadows task for pure states in the setting of both joint and independent measurements. The task is to measure few copies of an unknown pure state $\rho$ in order to learn a classical description which suffices to later estimate expectation values of observables. Specifically, the goal is to approximate $\mathrm{Tr}(O \rho)$ for any

Constance Thierry, Arthur Hoarau, Arnaud Martin, Jean-Christophe Dubois

The theory of belief functions allows the fusion of imperfect data from different sources. Unfortunately, few real, imprecise and uncertain datasets exist to test approaches using belief functions. We have built real birds datasets thanks to the collection of numerous human contributions that we make available to the scientific community. The interest of our

Lana X. Garmire, Yijun Li, Qianhui Huang, Chuan Xu

Deciphering cell type heterogeneity is crucial for systematically understanding tissue homeostasis and its dysregulation in diseases. Computational deconvolution is an efficient approach estimating cell type abundances from a variety of omics data. Despite significant methodological progress in computational deconvolution in recent years, challenges are stil

Georges Bossis, Yan Grasselli, Olga Volkova

In this work we explore the rheology of very concentrated (0.55<$\Phi$<0.67) suspensions of carbonyl iron (CI) particles coated by a small polymer. A strong DST is observed in a large range of volume fraction presenting some specificities relatively to other systems. In particular, in a given range of volume fraction, the DST transition appears suddenly with

Paul Laurain

We prove that simply connected H-surfaces with bounded area and free boundary in a domain necessarily concentrate at a critical point of the mean curvature of the boundary of this domain.

Olivier Druet, Paul Laurain

We investigate problems connected to the stability of the wellknown Poho\v{z}aev obstruction. We generalize results which were obtained in the minimizing setting by Brezis and Nirenberg [2] and more recently in the radial situation by Brezis and Willem [3].

Xavier Roulleau, Alessandra Sarti

A generalized Kummer surface $X$ of order $3$ is the minimal resolution of the quotient of an abelian surface $A$ by an order $3$ symplectic automorphism. We study a generalization of a problem of Shioda for classical Kummer surfaces, which is to understand how much $X$ is determined by $A$ and conversely. The surface $X$ posses a big and nef divisor $L_{X}$

Chinonso Nwankwo, Nneka Umeorah, Tony Ware, Weizhong Dai

We propose a deep learning method for solving the American options model with a free boundary feature. To extract the free boundary known as the early exercise boundary from our proposed method, we introduce the Landau transformation. For efficient implementation of our proposed method, we further construct a dual solution framework consisting of a novel aux

Alex Beeson, Giovanni Montana

The ability to discover optimal behaviour from fixed data sets has the potential to transfer the successes of reinforcement learning (RL) to domains where data collection is acutely problematic. In this offline setting, a key challenge is overcoming overestimation bias for actions not present in data which, without the ability to correct for via interaction

Andrej Janda, Brandon Wagstaff, Edwin G. Ng, Jonathan Kelly

Reducing the quantity of annotations required for supervised training is vital when labels are scarce and costly. This reduction is especially important for semantic segmentation tasks involving 3D datasets that are often significantly smaller and more challenging to annotate than their image-based counterparts. Self-supervised pre-training on large unlabell

Raymond Ehlers

Jets are generated in hard interactions in high-energy nuclear collisions. Jets propagate through the quark-gluon plasma (QGP) as the jet shower evolves; their interaction with the QGP, known as jet quenching, generates observable phenomena that provide incisive probes of the structure and dynamics of the QGP. For instance, medium-induced modification of jet

Petr Zelina, Jana Halámková, Vít Nováček

This work is motivated by the scarcity of tools for accurate, unsupervised information extraction from unstructured clinical notes in computationally underrepresented languages, such as Czech. We introduce a stepping stone to a broad array of downstream tasks such as summarisation or integration of individual patient records, extraction of structured informa

Rafal Kocielnik, Sara Kangaslahti, Shrimai Prabhumoye, Meena Hari

Labeling social-media data for custom dimensions of toxicity and social bias is challenging and labor-intensive. Existing transfer and active learning approaches meant to reduce annotation effort require fine-tuning, which suffers from over-fitting to noise and can cause domain shift with small sample sizes. In this work, we propose a novel Active Transfer F

Utkarsh Singhal, Stella X. Yu, Zackery Steck, Scott Kangas

Multi-spectral imagery is invaluable for remote sensing due to different spectral signatures exhibited by materials that often appear identical in greyscale and RGB imagery. Paired with modern deep learning methods, this modality has great potential utility in a variety of remote sensing applications, such as humanitarian assistance and disaster recovery eff

Philip K. Schwartz

We discuss a teleparallel version of Newton--Cartan gravity. This theory arises as a formal large-speed-of-light limit of the teleparallel equivalent of general relativity (TEGR). Thus, it provides a geometric formulation of the Newtonian limit of TEGR, similar to standard Newton--Cartan gravity being the Newtonian limit of general relativity. We show how by

M. Billo, M. Frau, A. Lerda, A. Pini

We study the 3-point functions of gauge-invariant scalar operators in four dimensional $\mathcal{N}=2$ superconformal quiver theories using supersymmetric localization in the planar limit of a large number of colors. By exploiting a web of nontrivial relations, we show that the 3-point functions can be expressed in terms of the 2-point functions through exac

Martin Sasieta

We construct higher dimensional Euclidean AdS wormhole solutions that reproduce the statistical description of the correlation functions of an ensemble of heavy CFT operators. We consider an operator which effectively backreacts on the geometry in the form of a thin shell of dust particles. Assuming dynamical chaos in the form of the ETH ansatz, we demonstra

Pierre-Alexis Roy, Björn Benneke, Caroline Piaulet, Ian J. M. Crossfield

The Kepler and TESS missions revealed a remarkable abundance of sub-Neptune exoplanets. Despite this abundance, our understanding of the nature and compositional diversity of sub-Neptunes remains limited, to a large part because atmospheric studies via transmission spectroscopy almost exclusively aimed for low-density sub-Neptunes and even those were often a

M. Siudek, K. Lisiecki, M. Mezcua, K. Małek

While we already seem to have a general scenario of the evolution of different types of galaxies, a complete and satisfactory understanding of the processes that led to the formation of all the variety of today's galaxy types is still beyond our reach. To solve this problem, we need both large datasets reaching high redshifts and novel methodologies for deal

Simon Caron-Huot

We consider four-point correlators in an excited quantum state of a field theory. We show that, when the theory and state are holographic, a judiciously applied Fourier transform produces high-quality images of point-like bulk particles, revealing the geometry in which they move. For translation-invariant states, the bulk Einstein's equations amount to local

Regina Sarmiento, Marc Huertas-Company, Johan H. Knapen, Héctor Ibarra-Medel

Modern astronomical observations give unprecedented access to the physical properties of nearby galaxies, including spatially resolved stellar populations. However, observations can only give a present-day view of the Universe, whereas cosmological simulations give access to the past record of the processes that galaxies have experienced in their evolution.

Leticia Cunqueiro, Davide Napoletano, Alba Soto-Ontoso

We explore the possibility of using the dead cone of heavy quarks as a region of the Lund plane where medium-induced gluon radiation can be isolated and characterised. The filling of the dead cone by medium-induced gluons is expected to be the result of the interplay between the minimum angle of such radiation due to transverse momentum broadening and the de