December 2020 arXiv papers — page 113

Nan Jiang, Weijun Xie

In a chance constrained program (CCP), the decision-makers aim to seek the best decision whose probability of violating the uncertainty constraints is within the prespecified risk level. As a CCP is often nonconvex and is difficult to solve to optimality, much effort has been devoted to developing convex inner approximations for a CCP, among which the condit

Michael Weylandt, T. Mitchell Roddenberry, Genevera I. Allen

Clustering is a ubiquitous problem in data science and signal processing. In many applications where we observe noisy signals, it is common practice to first denoise the data, perhaps using wavelet denoising, and then to apply a clustering algorithm. In this paper, we develop a sparse convex wavelet clustering approach that simultaneously denoises and discov

Otto B. Bischof

The cause for the difference in crustal thickness between the far and near sides of the moon has been considered an open problem in astronomy since 1959 when the Soviet spacecraft Luna 3 sent back the first images of the lunar farside. The problem is referred to as the lunar farside highlands problem. In this article, the author deduces the center of mass sh

Justin Faber, Hancheng Li, Dolores Bozovic

Hair cells of the auditory and vestibular systems display astonishing sensitivity, frequency selectivity, and temporal resolution to external signals. These specialized cells utilize an internal active amplifier to achieve highly sensitive mechanical detection. One of the manifestations of this active process is the occurrence of spontaneous limit-cycle moti

Yiming Xu, Diego Klabjan

In model serving, having one fixed model during the entire often life-long inference process is usually detrimental to model performance, as data distribution evolves over time, resulting in lack of reliability of the model trained on historical data. It is important to detect changes and retrain the model in time. The existing methods generally have three w

Sobhit Singh, Logan Lang, Viviana Dovale-Farelo, Uthpala Herath

The MechElastic Python package evaluates the mechanical and elastic properties of bulk and 2D materials using the elastic coefficient matrix ($C_{ij}$) obtained from any ab-initio density-functional theory (DFT) code. The current version of this package reads the output of VASP, ABINIT, and Quantum Espresso codes (but it can be easily generalized to any othe

Michael Weylandt, George Michailidis

Clustering of time series data exhibits a number of challenges not present in other settings, notably the problem of registration (alignment) of observed signals. Typical approaches include pre-registration to a user-specified template or time warping approaches which attempt to optimally align series with a minimum of distortion. For many signals obtained f

Thomas Sandholm, Sayandev Mukherjee

We argue for giving users the ability to lease bandwidth temporarily from any mobile network operator. We propose, prototype, and evaluate a spectrum market for mobile network access, where multiple network operators offer blocks of bandwidth at specified prices for short-term leases to users, with autonomous agents on user devices making purchase decisions

Paolo Ciafaloni, Gabriele Martelli, Mauro Raggi

Electron positron collisions are a very promising environment to search for new physics, and in particular for dark sector related observables. The most challenging experimental problem in detecting dark sector candidates is the very high associated Standard Model background. For this reason it is important to identify observables that are, at the same time,

Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar

We propose a kernelized classification layer for deep networks. Although conventional deep networks introduce an abundance of nonlinearity for representation (feature) learning, they almost universally use a linear classifier on the learned feature vectors. We advocate a nonlinear classification layer by using the kernel trick on the softmax cross-entropy lo

K. Sardashti, T. Nguyen, M. Hatefipour, W. L. Sarney

Hyperdoping with gallium (Ga) has been established as a route to observe superconductivity in silicon (Si). The relatively large critical temperatures (T$_{\rm c}$) and magnetic fields (B$_{\rm c}$) make this phase attractive for cryogenic circuit applications, particularly for scalable hybrid superconductor--semiconductor platforms. However, the robustness

Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos, Cao Xiao

Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures. In this work, we develop a tensor method to predict the evolution of epidemic trends for many regions simultaneously. We construct a 3-way spatio-temporal tensor (location, attribute, time) of case counts and propose a nonn

Siyan Dong, Qingnan Fan, He Wang, Ji Shi

Localizing the camera in a known indoor environment is a key building block for scene mapping, robot navigation, AR, etc. Recent advances estimate the camera pose via optimization over the 2D/3D-3D correspondences established between the coordinates in 2D/3D camera space and 3D world space. Such a mapping is estimated with either a convolution neural network

S. Valère Bitseki Penda, Jean-François Delmas

Bifurcating Markov chains (BMC) are Markov chains indexed by a full binary tree representing the evolution of a trait along a population where each individual has two children. We provide a central limit theorem for general additive functionals of BMC, and prove the existence of three regimes. This corresponds to a competition between the reproducing rate (e

Eduardo Canale, Guillermo Rela, Franco Robledo, Pablo Romero

There is a vast literature focused on network reliability evaluation. In the last decades, reliability optimization has been also addressed. Frank Boesch in 1986 introduced the concept of uniformly most reliable graph (UMRG). Later, Boesch \emph{et al.} presented the first UMRGs and conjectured that some special subdivisions of the bipartite complete graph $

Eric M. Kenney, Brenden R. Ortiz, Chennan Wang, Stephen D. Wilson

We have carried out muon spin relaxation and rotation measurements on the newly discovered kagome metal KV3Sb5, and find a local field dominated by weak magnetic disorder which we associate with the nuclear moments present, and a modest temperature dependence which tracks the bulk magnetic susceptibility. We find no evidence for the existence of V4+ local mo

Fernando Arias-Aragon, Francesco D'Eramo, Ricardo Z. Ferreira, Luca Merlo

Light axions can potentially leave a cosmic background, just like neutrinos. We complete the study of thermal axion production across the electroweak scale by providing a smooth and continuous treatment through the two phases. Focusing on both flavor conserving and violating couplings to third generation quarks, we compute the amount of axions produced via s

Vahid Azizi, Muhammad Usman, Honglu Zhou, Petros Faloutsos

Floorplans are commonly used to represent the layout of buildings. In computer aided-design (CAD) floorplans are usually represented in the form of hierarchical graph structures. Research works towards computational techniques that facilitate the design process, such as automated analysis and optimization, often use simple floorplan representations that igno

Sena Kiciroglu, Wei Wang, Mathieu Salzmann, Pascal Fua

Long term human motion prediction is essential in safety-critical applications such as human-robot interaction and autonomous driving. In this paper we show that to achieve long term forecasting, predicting human pose at every time instant is unnecessary. Instead, it is more effective to predict a few keyposes and approximate intermediate ones by interpolati

Daniel Kunin, Javier Sagastuy-Brena, Surya Ganguli, Daniel L. K. Yamins

Understanding the dynamics of neural network parameters during training is one of the key challenges in building a theoretical foundation for deep learning. A central obstacle is that the motion of a network in high-dimensional parameter space undergoes discrete finite steps along complex stochastic gradients derived from real-world datasets. We circumvent t

Harald Schmid, Sauro Succi, Stefano Ruffo

We investigate the equilibration process of the strongly coupled quartic Fermi-Pasta-Ulam-Tsingou (FPUT) model by adding Langevin baths to the ends of the chain. The time evolution of the system is investigated by means of extensive numerical simulations and shown to match the results expected from equilibrium statistical mechanics in the time-asymptotic lim

Jeff Da, Maxwell Forbes, Rowan Zellers, Anthony Zheng

Multimodal disinformation, from 'deepfakes' to simple edits that deceive, is an important societal problem. Yet at the same time, the vast majority of media edits are harmless -- such as a filtered vacation photo. The difference between this example, and harmful edits that spread disinformation, is one of intent. Recognizing and describing this intent is a m

Andrew Reicks, Alfred Tsubaki, Mark Anderson, Jace Wieseler

It is very challenging to achieve near perfect absorption/emission that is both broadband and omnidirectional while utilizing a scalable fabrication process. Femtosecond laser surface processing is an emerging low-cost and large-scale manufacturing technique used to directly and permanently modify the surface properties of a material. The versatility of this

Tineke Blom, Joris M. Mooij

Mathematical models of the real world are simplified representations of complex systems. A caveat to using mathematical models is that predicted causal effects and conditional independences may not be robust under model extensions, limiting applicability of such models. In this work, we consider conditions under which qualitative model predictions are preser

A. O. Macchiavelli, H. L. Crawford, R. M. Clark, P. Fallon

Spectroscopic factors to low-lying negative-parity states in $^{11}$Be extracted from the $^{12}$B($d$,$^3$He)$^{11}$Be proton-removal reaction are interpreted within the rotational model. Earlier predictions of the $p$-wave proton removal strengths in the strong coupling limit of the Nilsson model underestimated the spectroscopic factors to the $3/2^-_1$ an

Junming Huang, Gavin Cook, Yu Xie

Do mass media influence people's opinion of other countries? Using BERT, a deep neural network-based natural language processing model, we analyze a large corpus of 267,907 China-related articles published by The New York Times since 1970. We then compare our output from The New York Times to a longitudinal data set constructed from 101 cross-sectional surve

Kerim Kahraman, Mutlu Senturk, Mumin Tolga Emirler, Ismail Meric Can Uygan

There is growing interest in fully electric vehicles in the automotive industry as it becomes increasingly more difficult to meet new and upcoming emission regulations based on internal combustion engines. Fully electric vehicles do not have an internal combustion engine. Hence, drive torque change for a traction control system and for a yaw stability contro

Weiwei Sun, Andrea Tagliasacchi, Boyang Deng, Sara Sabour

We propose a self-supervised capsule architecture for 3D point clouds. We compute capsule decompositions of objects through permutation-equivariant attention, and self-supervise the process by training with pairs of randomly rotated objects. Our key idea is to aggregate the attention masks into semantic keypoints, and use these to supervise a decomposition t

Antonio Pich

The inclusive production of hadrons through electroweak currents can be rigorously analysed with short-distance theoretical tools. The associated observables are insensitive to the involved infrared behaviour of the strong interaction, allowing for very precise tests of Quantum Chromodynamics. The theoretical predictions for $σ(e^+e^-\to\mathrm{hadrons})$ an

Curtis Bright, Kevin K. H. Cheung, Brett Stevens, Ilias Kotsireas

In 1989, computer searches by Lam, Thiel, and Swiercz experimentally resolved Lam's problem from projective geometry$\unicode{x2014}$the long-standing problem of determining if a projective plane of order ten exists. Both the original search and an independent verification in 2011 discovered no such projective plane. However, these searches were each perform

Yueying Ni, Tiziana Di Matteo, Yu Feng

In this work, we use the constrained Gaussian realization technique to study the early growth of supermassive black holes (SMBHs) in cosmological hydrodynamic simulations, exploring its relationship with features of the initial density peaks on large scales, ~1 Mpc/h. Our constrained simulations of volume (20 Mpc/h)^3 successfully reconstruct the large-scale

Ruslan Shaydulin, Stuart Hadfield, Tad Hogg, Ilya Safro

We study the relationship between the Quantum Approximate Optimization Algorithm (QAOA) and the underlying symmetries of the objective function to be optimized. Our approach formalizes the connection between quantum symmetry properties of the QAOA dynamics and the group of classical symmetries of the objective function. The connection is general and includes

Luis Ferroni

In this paper we investigate the Ehrhart Theory of the independence matroid polytope of uniform matroids. It is proved that these polytopes have an Ehrhart polynomial with positive coefficients. To do that, we prove that indeed all half-open-hypersimplices are Ehrhart positive, and tile disjointly our polytope using them.

Samuel G. Carter, Stefan C. Badescu, Allan S. Bracker, Michael K. Yakes

Optical spin rotations and cycling transitions for measurement are normally incompatible in quantum dots, presenting a fundamental problem for quantum information applications. Here we show that for a hole spin this problem can be addressed using a trion with one hole in an excited orbital, where strong spin-orbit interaction tilts the spin. Then, a particul

Fabrizio Sgrignuoli, Yuyao Chen, Sean Gorsky, Weasley A. Britton

Optical rogue waves are demonstrated in the far-field scattered radiation from photonic arrays designed according to the aperiodic distributions of prime elements in complex quadratic fields. Specifically, by studying light diffraction from Eisenstein and Gaussian prime arrays we establish a connection between the formation of optical rogue waves and multifr

Yusuf H. Sahin, Alican Mertan, Gozde Unal

Learning new representations of 3D point clouds is an active research area in 3D vision, as the order-invariant point cloud structure still presents challenges to the design of neural network architectures. Recent works explored learning either global or local features or both for point clouds, however none of the earlier methods focused on capturing context

Juan Estrada, Roni Harnik, Dario Rodrigues, Matias Senger

We propose a new way to use optical tools from quantum imaging and quantum communication to search for physics beyond the standard model. Spontaneous parametric down conversion (SPDC) is a commonly used source of entangled photons in which pump photons convert to a signal-idler pair. We propose to search for "dark SPDC" (dSPDC) events in which a new dark sec

Kota Srinivas Reddy, Nikhil Karamchandani

Index coding and coded caching are two active research topics in information theory with strong ties to each other. Motivated by the multi-access coded caching problem, we study a new class of structured index coding problems (ICPs) which are formed by the union of several symmetric ICPs. We derive upper and lower bounds on the optimal server transmission ra

Jaime Souto-Casares, Nicola A. Spaldin, Claude Ederer

We address the long-standing question of the nature of oxygen vacancies in strontium titanate, using a combination of density functional theory and dynamical mean-field theory (DFT+DMFT) to investigate in particular the effect of vacancy-site correlations on the electronic properties. Our approach uses a minimal low-energy electronic subspace including the T

Harvey Liszt

Hydrogen column densities inferred from X-ray absorption are typically 5 - 30 times larger than the neutral atomic hydrogen column densities derived from 21cm HI absorption toward radio-loud active galactic nuclei. Some part of the difference is ascribed to uncertainty in the spin temperature \Tsp\ = 100 K that is often used to convert 21cm HI HI absorption

Nishtha Madaan, Inkit Padhi, Naveen Panwar, Diptikalyan Saha

Machine Learning has seen tremendous growth recently, which has led to larger adoption of ML systems for educational assessments, credit risk, healthcare, employment, criminal justice, to name a few. The trustworthiness of ML and NLP systems is a crucial aspect and requires a guarantee that the decisions they make are fair and robust. Aligned with this, we p

Mengtao Tang, Daniel Stark, Jacopo Chevallard, Stephane Charlot

Spectroscopic observations of massive $z>7$ galaxies selected to have extremely large [OIII]+H$\beta$ equivalent width (EW $\sim1500$ \r{A}) have recently revealed large Ly$\alpha$ detection rates, in contrast to the weak emission seen in the general population. Why these systems are uniquely visible in Ly$\alpha$ at redshifts where the IGM is likely signifi

Marcel Guardia, Jaime Paradela, Tere-M. Seara, Claudio Vidal

The elliptic isosceles restricted three body problem (REI3BP) models the motion of a massless body under the influence of the Newtonian gravitational force caused by two other bodies called the primaries. The primaries of masses $m_{1}=m_{2}$ move along a degenerate Keplerian elliptic collision orbit (on a line) under their gravitational attraction, whereas

Hemza Azri, Salah Nasri

Scalar-tensor theories of gravity are known to allow significant deviations from general relativity through various astrophysical phenomena. In this paper, we formulate a scalar-connection gravity by setting up scalars and connection configurations instead of metric. Since the matter sector is not straightforward to conceive without a metric, we invoke cosmo

Charuhas Shiveshwarkar, Drew Jamieson, Marilena Loverde

We investigate the gravitational effect of large-scale radiation perturbations on small-scale structure formation. In addition to making the growth of matter perturbations scale dependent, the free-streaming of radiation also affects the coupling between structure formation at small and large scales. We study this using Separate Universe N-body simulations t

Evan Petrosky, Hsiang-Chih Hwang, Nadia L. Zakamska, Vedant Chandra

The time-series component of WISE is a valuable resource for the study of variable objects. We present an analysis of an all-sky sample of ~450,000 AllWISE+NEOWISE infrared light curves of likely variables identified in AllWISE. By computing periodograms of all these sources, we identify ~56,000 periodic variables. Of these, ~42,000 are short-period (P<1 day

Otto Brookes, Tilo Burghardt

We put forward a video dataset with 5k+ facial bounding box annotations across a troop of 7 western lowland gorillas at Bristol Zoo Gardens. Training on this dataset, we implement and evaluate a standard deep learning pipeline on the task of facially recognising individual gorillas in a zoo environment. We show that a basic YOLOv3-powered application is able

Tom Struck, Javed Lindner, Arne Hollmann, Floyd Schauer

Establishing low-error and fast detection methods for qubit readout is crucial for efficient quantum error correction. Here, we test neural networks to classify a collection of single-shot spin detection events, which are the readout signal of our qubit measurements. This readout signal contains a stochastic peak, for which a Bayesian inference filter includ

S. Bailey, T. Cridge, L. A. Harland-Lang, A. D. Martin

We present the new MSHT20 set of parton distribution functions (PDFs) of the proton, determined from global analyses of the available hard scattering data. The PDFs are made available at NNLO, NLO, and LO, and supersede the MMHT14 sets. They are obtained using the same basic framework, but the parameterisation is now adapted and extended, and there are 32 pa

Lisa Wölfer, Stefano Facchini, Nicolas T. Kurtovic, Richard Teague

In the past years, high angular resolution observations have revealed that circumstellar discs appear in a variety of shapes with diverse substructures being ubiquitous. This has given rise to the question of whether these substructures are triggered by planet-disc interactions. Besides direct imaging, one of the most promising methods to distinguish between

Runshi Geng, J. M. Landsberg

We make a geometric study of the Geometric Rank of tensors recently introduced by Kopparty et al. Results include classification of tensors with degenerate geometric rank in $C^3\otimes C^3\otimes C^3$, classification of tensors with geometric rank two, and showing that upper bounds on geometric rank imply lower bounds on tensor rank.

Mingzhou Yin, Andrea Iannelli, Roy S. Smith

The paper presents a data-driven predictive control framework based on an implicit input-output mapping derived directly from the signal matrix of collected data. This signal matrix model is derived by maximum likelihood estimation with noise-corrupted data. By linearizing online, the implicit model can be used as a linear constraint to characterize possible

Niccolò Cribiori, Susha Parameswaran, Flavio Tonioni, Timm Wrase

The study of non-supersymmetric string theories is shedding light on an important corner of the string landscape and might ultimately explain why, so far, we did not observe supersymmetry in our universe. We review how misaligned supersymmetry in closed-string theories leads to a cancellation between bosons and fermions even in non-supersymmetric string theo

Paul A. Dalba, Stephen R. Kane, Howard Isaacson, Steven Giacalone

Despite the severe bias of the transit method of exoplanet discovery toward short orbital periods, a modest sample of transiting exoplanets with orbital periods greater than 100 days is known. Long-term radial velocity (RV) surveys are pivotal to confirming these signals and generating a set of planetary masses and densities for planets receiving moderate to

P. L. Taylor, T. Kitching, V. F. Cardone, A. Ferté

Modelling uncertainties at small scales, i.e. high $k$ in the power spectrum $P(k)$, due to baryonic feedback, nonlinear structure growth and the fact that galaxies are biased tracers poses a significant obstacle to fully leverage the constraining power of the {\it Euclid} wide-field survey. $k$-cut cosmic shear has recently been proposed as a method to opti

Hao Geng, Andreas Karch, Carlos Perez-Pardavila, Suvrat Raju

Late-time dominance of entanglement islands plays a critical role in addressing the information paradox for black holes in AdS coupled to an asymptotic non-gravitational bath. A natural question is how this observation can be extended to gravitational systems. To gain insight into this question, we explore how this story is modified within the context of Kar

Jakob Stegmann, Fabio Antonini

Close stellar binaries are prone to undergo a phase of stable mass transfer in which a star loses mass to its companion. Assuming that the donor star loses mass along the instantaneous interstellar axis, we derive the orbit-averaged equations of motion describing the evolution of the donor rotational angular momentum vector (spin) which accompanies the trans

Michela Rigoselli, Sandro Mereghetti, Roberto Taverna, Roberto Turolla

The radio-quiet pulsar PSR J2021+4026 is mostly known because it is the only rotation-powered pulsar that shows variability in its {\gamma}-ray emission. Using XMM-Newton archival data, we first confirmed that its flux is steady in the X-ray band, and then we showed that both the spectral and timing X-ray properties, i.e. the narrow pulse profile, the high p

Benjamin D. Boizelle, Jonelle L. Walsh, Aaron J. Barth, David A. Buote

We present Atacama Large Millimeter/submillimeter Array (ALMA) Cycle 5 and Cycle 6 observations of CO(2$-$1) and CO(3$-$2) emission at 0.2''$-$0.3'' resolution in two radio-bright, brightest group/cluster early-type galaxies, NGC 315 and NGC 4261. The data resolve CO emission that extends within their black hole (BH) spheres of influence ($r_\mathrm{g}$), tr

Christopher M. Carroll, Ryan C. Hickox, Alberto Masini, Lauranne Lanz

We present a large sample of infrared-luminous candidate active galactic nuclei (AGNs) that lack X-ray detections in Chandra, XMM-Newton, and NuSTAR fields. We selected all optically detected SDSS sources with redshift measurements, combined additional broadband photometry from WISE, UKIDSS, 2MASS, and GALEX, and modeled the spectral energy distributions (SE

Jonathan Freundlich, Nicolas F. Bouché, Thierry Contini, Emanuele Daddi

We present a pilot program using IRAM&#39;s NOrthern Extended Millimeter Array (NOEMA) to probe the molecular gas reservoirs of six $z=0.6-1.1$ star-forming galaxies whose circumgalactic medium has been observed in absorption along quasar lines-of-sight as part of the MusE GAs FLOw and Wind (MEGAFLOW) survey and for which we have estimates of either the accr

Chao-Ming Jian, Bela Bauer, Anna Keselman, Andreas W. W. Ludwig

Models for non-unitary quantum dynamics, such as quantum circuits that include projective measurements, have been shown to exhibit rich quantum critical behavior. There are many complementary perspectives on this behavior. For example, there is a known correspondence between d-dimensional local non-unitary quantum circuits and tensor networks on a D=(d+1)-di

Jacob Maresca, Simon Dye, Nan Li

With the advent of next-generation surveys and the expectation of discovering huge numbers of strong gravitational lens systems, much effort is being invested into developing automated procedures for handling the data. The several orders of magnitude increase in the number of strong galaxy-galaxy lens systems is an insurmountable challenge for traditional mo

Georgios Palkanoglou, Alexandros Gezerlis

Superfluid neutron matter is a key ingredient in the composition of neutron stars. The physics of the inner crust is largely dependent on that of its $S$-wave neutron superfluid which has made its presence known through pulsar glitches and modifications on the neutron star cooling. Moreover, with recent gravitational-wave observations of neutron star mergers

Shane P. Kelly, Ana Maria Rey, Jamir Marino

We study the far-from-equilibrium dynamical regimes of a many-body spin boson model with disordered couplings relevant for cavity QED and trapped ions experiments, using the discrete truncated Wigner approximation (DTWA). We focus on the dynamics of spin observables upon varying the disorder strength and the frequency of the photons, finding that the latter

Donghyeon J. Khim, Sukyoung K. Yi, Christophe Pichon, Yohan Dubois

There have been many studies aiming to reveal the origins of the star-gas misalignment found in galaxies, but there still is a lack of understanding of the contribution from each formation channel candidate. We aim to answer the question by investigating the misaligned galaxies in Horizon-AGN, a cosmological large-volume simulation of galaxy formation. There

Lara B. Anderson, Mathis Gerdes, James Gray, Sven Krippendorf

We use machine learning to approximate Calabi-Yau and SU(3)-structure metrics, including for the first time complex structure moduli dependence. Our new methods furthermore improve existing numerical approximations in terms of accuracy and speed. Knowing these metrics has numerous applications, ranging from computations of crucial aspects of the effective fi

Maximilian Dax, Dominik Stamen, Bastian Kubis

We provide a dispersion-theoretical representation of the reaction amplitudes $\gamma K\to K \pi$ in all charge channels, based on modern pion-kaon $P$-wave phase shift input. Crossed-channel singularities are fixed from phenomenology as far as possible. We demonstrate how the subtraction constants can be matched to a low-energy theorem and radiative couplin

Tim Linden, John F. Beacom, Annika H. G. Peter, Benjamin J. Buckman

The solar disk is among the brightest gamma-ray sources in the sky. It is also among the most mysterious. No existing model fully explains the luminosity, spectrum, time variability, and morphology of its emission. We perform the first analysis of solar-disk gamma rays over a full 11-year solar cycle, utilizing a powerful new method to differentiate solar si

Shao-Kai Jian, Sankar Das Sarma

In a recent paper by Lucas and Das Sarma [Physical Review B 97, 115449 (2018)], a solvable model of collective modes in 2D metals was considered in the hydrodynamic regime. In the current work, we generalize the hydrodynamic theory to 3D metals for which the calculation of sound modes in a strongly-coupled quantum Coulomb plasma can be made explicit. The spe

Nima Arkani-Hamed, Raffaele Tito D'Agnolo, Hyung Do Kim

Does the value of the Higgs mass parameter affect the expectation value of local operators in the Standard Model? For essentially all local operators the answer to this question is "no", and this is one of the avatars of the hierarchy problem: nothing is "triggered" when the Higgs mass parameter crosses zero. In this letter, we explore settings in which Higg

Zhentao Tan, Dongdong Chen, Qi Chu, Menglei Chai

Spatially-adaptive normalization (SPADE) is remarkably successful recently in conditional semantic image synthesis \cite{park2019semantic}, which modulates the normalized activation with spatially-varying transformations learned from semantic layouts, to prevent the semantic information from being washed away. Despite its impressive performance, a more thoro

Sharath Girish, Shishira R. Maiya, Kamal Gupta, Hao Chen

Recognition tasks, such as object recognition and keypoint estimation, have seen widespread adoption in recent years. Most state-of-the-art methods for these tasks use deep networks that are computationally expensive and have huge memory footprints. This makes it exceedingly difficult to deploy these systems on low power embedded devices. Hence, the importan

Kevis-Kokitsi Maninis, Stefan Popov, Matthias Nießner, Vittorio Ferrari

We address the task of aligning CAD models to a video sequence of a complex scene containing multiple objects. Our method can process arbitrary videos and fully automatically recover the 9 DoF pose for each object appearing in it, thus aligning them in a common 3D coordinate frame. The core idea of our method is to integrate neural network predictions from i

Guadalupe Cañas-Herrera, Jesús Torrado, Ana Achúcarro

We update the search for features, due to transient reductions in inflaton's speed of sound, in the Cosmic Microwave Background (CMB) angular power spectrum using Planck 2018 temperature, polarization and lensing data. We develop a new methodology to test more flexible templates to reconstruct the reduction of the speed of sound based on Gaussian Processes.

J. W. S. McCullough, P. V. Coveney

An arteriovenous fistula, created by artificially connecting segments of a patient's vasculature, is the preferred way to gain access to the bloodstream for kidney dialysis. The increasing power and availability of supercomputing infrastructure means that it is becoming more realistic to use simulations to help identify the best type and location of a fistul

Rodrigo Voivodic, Alexandre Barreira

Halo occupation distribution (HOD) models describe the number of galaxies that reside in different haloes, and are widely used in galaxy-halo connection studies using the halo model (HM). Here, we introduce and study HOD response functions $R_\mathcal{O}^g$ that describe the response of the HODs to long-wavelength perturbations $\mathcal{O}$. The linear gala

Shi-Fan Chen, Zvonimir Vlah, Emanuele Castorina, Martin White

We present the one-loop 2-point function of biased tracers in redshift space computed with Lagrangian perturbation theory, including a full resummation of both long-wavelength (infrared) displacements and associated velocities. The resulting model accurately predicts the power spectrum and correlation function of halos and mock galaxies from two different se

Abdulrahim Al Balushi, Zhencheng Wang, Donald Marolf

We generalize the Gao-Jafferis-Wall construction of traversable two-sided wormholes to multi-boundary wormholes. In our construction, we take the background spacetime to be multi-boundary black holes in AdS$_3$. We work in the hot limit where the dual CFT state in certain regions locally resembles the thermofield double state. Furthermore, in these regions,

Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön

Accurate 3D object detection (3DOD) is crucial for safe navigation of complex environments by autonomous robots. Regressing accurate 3D bounding boxes in cluttered environments based on sparse LiDAR data is however a highly challenging problem. We address this task by exploring recent advances in conditional energy-based models (EBMs) for probabilistic regre

Djalil Chafaï, David García-Zelada, Paul Jung

We consider a one-dimensional classical Wigner jellium, not necessarily charge neutral, for which the electrons are allowed to exist beyond the support of the background charge. The model can be seen as a one-dimensional Coulomb gas in which the external field is generated by a smeared background on an interval. It is a true one-dimensional Coulomb gas and n

Dídac Surís, Dave Epstein, Carl Vondrick

Machine translation between many languages at once is highly challenging, since training with ground truth requires supervision between all language pairs, which is difficult to obtain. Our key insight is that, while languages may vary drastically, the underlying visual appearance of the world remains consistent. We introduce a method that uses visual observ

Andisheh Khedri, Antonio Štrkalj, Alessio Chiocchetta, Oded Zilberberg

We investigate the impact of an Ohmic-class environment on the conduction and correlation properties of one-dimensional interacting systems. Interestingly, we reveal that inter-particle interactions can be engineered by the environment's noise statistics. Introducing a backscattering impurity to the system, we address Kane-Fisher's metal-to-insulator quantum

Sheel Ganatra, Kyler Siegel

We define a family of symplectic invariants which obstruct exact symplectic embeddings between Liouville manifolds, using the general formalism of linearized contact homology and its L-infinity structure. As our primary application, we investigate embeddings between normal crossing divisor complements in complex projective space, giving a complete characteri

Marc Rigter, Bruno Lacerda, Nick Hawes

The parameters for a Markov Decision Process (MDP) often cannot be specified exactly. Uncertain MDPs (UMDPs) capture this model ambiguity by defining sets which the parameters belong to. Minimax regret has been proposed as an objective for planning in UMDPs to find robust policies which are not overly conservative. In this work, we focus on planning for Stoc

Dana G. Korssjoen, Biyao Li, Stefan Steinerberger, Raghavendra Tripathi

We investigate a method of generating a graph $G=(V,E)$ out of an ordered list of $n$ distinct real numbers $a_1, \dots, a_n$. These graphs can be used to test for the presence of interesting structure in the sequence. We describe sequences exhibiting intricate hidden structure that was discovered this way. Our list includes sequences of Deutsch, Erd\H{o}s,

T. V. Anoop, Nirjan Biswas, Ujjal Das

Let $k,N \in \mathbb{N}$ with $1\le k\le N$ and let $\Omega=\Omega_1 \times \Omega_2$ be an open set in $\mathbb{R}^k \times \mathbb{R}^{N-k}$. For $p\in (1,\infty)$ and $q \in (0,\infty),$ we consider the following Hardy-Sobolev type inequality: \begin{align} \int_{\Omega} |g_1(y)g_2(z)| |u(y,z)|^q \, dy \, dz \leq C \left( \int_{\Omega} | \nabla u(y,z) |^p

Alex Turzillo, Minyoung You

It has recently been demonstrated that protected supersymmetry emerges on the boundaries of one-dimensional intrinsically fermionic symmetry protected trivial (SPT) phases. Here we investigate the boundary supersymmetry of one-dimensional fermionic phases beyond SPT phases. Using the connection between Majorana edge modes and real supercharges, we compute, i

Kai Ma

Invisible particles frequently appear in final state in studying physics at colliders. Experimental precision is also low in measuring missing energy. In this paper, we propose a general approach for studying process involving invisible particles. We provided two kinematical observables which are sensitive to production kinematics in different regions, and h

Andrew O'Desky, David Harry Richman

We introduce a $p$-adic analogue of the incomplete gamma function. We also introduce quantities ($m$-values) associated to a function on natural numbers and prove a new characterization of $p$-adic continuity for functions with $p$-integral $m$-values. Combinatorial interpretations for the integral values of the incomplete gamma function and functions with $

Luis Inzunza, Mikhail S. Plyushchay

Hidden symmetries of non-relativistic $\mathfrak{so} (2,1)\cong \mathfrak{sl}(2, {\mathbb R})$ invariant systems in a cosmic string background are studied using the conformal bridge transformation. Geometric properties of this background are analogous to those of a conical surface with a deficiency/excess angle encoded in the "geometrical parameter" $\alpha$

Alexis Schotte, Guanyu Zhu, Lander Burgelman, Frank Verstraete

We consider a two-dimensional quantum memory of qubits on a torus which encode the extended Fibonaccistring-net code, and devise strategies for error correction when those qubits are subjected to depolarizing noise.Building on the concept of tube algebras, we construct a set of measurements and of quantum gates whichmap arbitrary qubit errors to the string-n

Carlos F. Álvarez, Adriana Sánchez, Régis Varão

In this work we address the problem of existence and uniqueness (finiteness) of ergodic equilibrium states for partially hyperbolic diffeomorphisms isotopic to Anosov on $\mathbb{T}^4$, with 2-dimensional center foliation. To do so we propose to study the disintegration of measures along 1-dimensional subfoliations of the center bundle. Moreover, we obtain a

Daniel Huybrechts

We describe the Hodge theory of brilliant families of K3 surfaces. Their characteristic feature is a close link between the Hodge structures of any two fibres over points in the Noether-Lefschetz locus. Twistor deformations, the analytic Tate-Safarevic group, and one-dimensional Shimura special cycles are covered by the theory. In this setting, the Brauer gr

Ralf K. Heilmann, Alexander R. Bruccoleri, Jungki Song, Matthew T. Cook

High-resolution ($R = \lambda /\Delta \lambda > 2000$) x-ray absorption and emission line spectroscopy in the soft x-ray band is a crucial diagnostic for the exploration of the properties of ubiquitous warm and hot plasmas and their dynamics in the cosmic web, galaxy clusters, galaxy halos, intragalactic space, and star atmospheres. Soft x-ray grating spectr

Samuel Duffield, Sumeetpal S. Singh

We introduce a novel method for online smoothing in state-space models that utilises a fixed-lag approximation to overcome the well known issue of path degeneracy. Unlike classical fixed-lag techniques that only approximate certain marginals, we introduce an online resampling algorithm, called particle stitching, that converts these marginal samples into a f

Meng-Lin Du, Feng-Kun Guo, Christoph Hanhart, Bastian Kubis

The lightest charmed scalar meson is known as the $D_0^*(2300)$, which is one of the earliest new hadron resonances observed at modern $B$ factories. We show here that the parameters assigned to the lightest scalar $D$-meson are in conflict with the precise LHCb data of the decay $B^-\to D^+ \pi^- \pi^-$. On the contrary, these data can be well described by

Joscha Diehl, Kurusch Ebrahimi-Fard, Nikolas Tapia

We explore the algebraic properties of a generalized version of the iterated-sums signature, inspired by previous work of F.~Kir\'aly and H.~Oberhauser. In particular, we show how to recover the character property of the associated linear map over the tensor algebra by considering a deformed quasi-shuffle product of words on the latter. We introduce three no

A. Maevskiy, F. Ratnikov, A. Zinchenko, V. Riabov

High energy physics experiments rely heavily on the detailed detector simulation models in many tasks. Running these detailed models typically requires a notable amount of the computing time available to the experiments. In this work, we demonstrate a new approach to speed up the simulation of the Time Projection Chamber tracker of the MPD experiment at the

Adam Papp, Wolfgang Porod, Gyorgy Csaba

We demonstrate the design of a neural network, where all neuromorphic computing functions, including signal routing and nonlinear activation are performed by spin-wave propagation and interference. Weights and interconnections of the network are realized by a magnetic field pattern that is applied on the spin-wave propagating substrate and scatters the spin