July 2022 arXiv papers — page 97

Kai-En Lin, Lin Yen-Chen, Wei-Sheng Lai, Tsung-Yi Lin

Although neural radiance fields (NeRF) have shown impressive advances for novel view synthesis, most methods typically require multiple input images of the same scene with accurate camera poses. In this work, we seek to substantially reduce the inputs to a single unposed image. Existing approaches condition on local image features to reconstruct a 3D object,

José Andrés Armario, Ronan Egan, Dane Flannery

In a recent survey, Schmidt compiled equivalences between generalized bent functions, group invariant Butson Hadamard matrices, and abelian splitting relative difference sets. We establish a broader network of equivalences by considering Butson matrices that are cocyclic rather than strictly group invariant. This result has several applications; for example,

Sugumi Kanno, Jiro Soda, Kazushige Ueda

It is believed that relic gravitons are squeezed during inflation. If so, quantum noise induced by them can be significantly enhanced in current interferometers. However, decoherence of the gravitons during cosmic history may change the degree of squeezing. As a first step for analyzing the decoherence of the gravitons, we assume the presence of a sizable ma

Martin Nisser, Leon Cheng, Yashaswini Makaram, Ryo Suzuki

This paper introduces a cube-based reconfigurable robot that utilizes an electromagnet-based actuation framework to reconfigure in three dimensions via pivoting. While a variety of actuation mechanisms for self-reconfigurable robots have been explored, they often suffer from cost, complexity, assembly and sizing requirements that prevent scaled production of

Jinmin Wang, Zhizhang Xie

In this paper, we prove a rigidity theorem for smooth strictly convex domains in Euclidean spaces.

Caterina Chiari, Pierfrancesco Di Cintio

We extend the classical formulation of the dynamical friction effect on a test star by Chandrasekhar to the case of relativistic velocities and velocity distributions also accounting for post-Newtonian corrections to the gravitational force. The original kinetic framework is revised and used to construct a special-relativistic dynamical friction formula wher

Andrèe Dafne Bolognino, Francesco Giovanni Celiberto, Dmitry Yu. Ivanov, Alessandro Papa

We present a new study on helicity amplitudes and cross sections for the exclusive production of $\rho$ mesons at the EIC in high-energy factorization. In this framework the analytic expression of amplitudes takes the form of a convolution between an off-shell impact factor, depicting the ($\gamma^* \to \rho$) transition, and a nonperturbative density, known

Andrei Konstantinov, Lev Utkin, Stanislav Kirpichenko

A new attention-based model for the gradient boosting machine (GBM) called AGBoost (the attention-based gradient boosting) is proposed for solving regression problems. The main idea behind the proposed AGBoost model is to assign attention weights with trainable parameters to iterations of GBM under condition that decision trees are base learners in GBM. Atte

Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Stefan Bauer

Learning predictors that do not rely on spurious correlations involves building causal representations. However, learning such a representation is very challenging. We, therefore, formulate the problem of learning a causal representation from high dimensional data and study causal recovery with synthetic data. This work introduces a latent variable decoder m

Thomas Cope, Roope Uola

We introduce a measure of average dimensionality (or coherence) for high-dimensional quantum devices. This includes sets of quantum measurements, steering assemblages, and quantum channels. For measurements and channels, our measure corresponds to an average compression dimension, whereas for quantum steering we get a semi-device independent quantifier for t

Guilherme Sadovski

We investigate the scenarios in which a holonomic versus a non-holonomic frame description of gravity theories are equivalent. It turns out that classically, the equivalence holds in a way that is independent of the particular dynamics and/or spacetime dimension. This includes general metric-affine dynamics. A global bundle-theoretical investigation is carri

Silvio Franz, Jorge Kurchan

In this note we summarize the connections between equilibrium and slow out of equilibrium dynamics in finite dimensional glasses, such as we understand them today. If we assume that a finite-dimensional system is stable with respect to a family of weak random perturbations (stochastic stability), then its dynamics have a `Multithermalization' structure if an

Ariane Soret, Vasco Cavina, Massimiliano Esposito

Starting from a microscopic system-baths description, we derive the general conditions for a time-local quantum master equation (QME) to satisfy the first and second law of thermodynamics at the fluctuating level. Using counting statistics, we show that the fluctuating second law can be rephrased as a Generalized Quantum Detailed Balance condition (GQDB), i.

Federica Bertolotti

Let $M$ be an oriented closed $3$-manifold. We prove that there exists a constant $A_M$, depending only on the manifold $M$, such that for every self-homotopy equivalence $f$ of $M$ there is an integer $k$ such that $1 \leq k \leq A_M$ and $f^k$ is homotopic to a homeomorphism.

Anderson Ramos, Róbert Kovács, Mirelson Freitas, Almeida Júnior

The Guyer-Krumhansl heat equation has numerous important practical applications in both low-temperature and room temperature heat conduction problems. In recent years, it turned out that the Guyer-Krumhansl model can effectively describe the thermal behaviour of macroscale heterogeneous materials. Thus, the Guyer-Krumhansl equation is a promising candidate t

Dmitry Grinko, Maris Ozols

Unitary equivariance is a natural symmetry that occurs in many contexts in physics and mathematics. Optimization problems with such symmetry can often be formulated as semidefinite programs for a $d^{p+q}$-dimensional matrix variable that commutes with $U^{\otimes p} \otimes \bar{U}^{\otimes q}$, for all $U \in \mathrm{U}(d)$. Solving such problems naively c

N. Medvedev, R. Voronkov, A. E. Volkov

This contribution is a brief introduction to nonthermal effects related to modifications of the interatomic potential upon ultrafast excitation of the electronic system of solids, primarily focusing on the swift heavy ion track problem. We clarify the difference between the exchange of the kinetic energy of electrons (and holes) scattering on the lattice (el

Mohammad Jamil Ahmad, Katerina Goseva-Popstojanova, Robyn R. Lutz

Software fault-proneness prediction is an active research area, with many factors affecting prediction performance extensively studied. However, the impact of the learning approach (i.e., the specifics of the data used for training and the target variable being predicted) on the prediction performance has not been studied, except for one initial work. This p

Keren Sharon, Catherine Cerny, Jane R. Rigby, Michael K. Florian

The strongly lensed z=2.9233 Lyman break galaxy, SGAS J122651.3+215220, lensed by a cluster at z=0.4358, was first targeted by JWST as part of the JWST-ERS program TEMPLATES: Targeting Extremely Magnified Panchromatic Lensed Arcs and their Extended Star formation. Aiming to combine the exquisite capabilities of JWST with the extreme magnification provided by

Ting Fung Lam, Yony Bresler, Ahmed Khorshid, Nathan Perlmutter

Irregular time series data are prevalent in the real world and are challenging to model with a simple recurrent neural network (RNN). Hence, a model that combines the use of ordinary differential equations (ODE) and RNN was proposed (ODE-RNN) to model irregular time series with higher accuracy, but it suffers from high computational costs. In this paper, we

Sven Günther, Julien Lesgourgues, Georgios Samaras, Nils Schöneberg

In modern analysis pipelines, Einstein-Boltzmann Solvers (EBSs) are an invaluable tool for obtaining CMB and matter power spectra. To accelerate the computation of these observables, the CosmicNet strategy is to replace the bottleneck of an EBS, which is the integration of a system of differential equations for linear cosmological perturbations, by neural ne

Benjamin Gess, Rishabh S. Gvalani, Vitalii Konarovskyi

The convergence of stochastic interacting particle systems in the mean-field limit to solutions of conservative stochastic partial differential equations is established, with optimal rate of convergence. As a second main result, a quantitative central limit theorem for such SPDEs is derived, again, with optimal rate of convergence. The results apply, in part

Lukas Mehl, Azin Jahedi, Jenny Schmalfuss, Andrés Bruhn

Recently, neural network for scene flow estimation show impressive results on automotive data such as the KITTI benchmark. However, despite of using sophisticated rigidity assumptions and parametrizations, such networks are typically limited to only two frame pairs which does not allow them to exploit temporal information. In our paper we address this shortc

Shoma Fujino, Makoto Matsumoto

Let $\mathcal C$ be the category of finite graphs. Lov\`{a}sz shows that the semi-ring of isomorphism classes of $\mathcal C$ (with coproduct as sum, and product as multiplication) is embedded into the direct product of the semi-ring of natural numbers. Our aim is to generalize this result to other categories. For this, one crucial property is that every obj

Sebastian Dörner, Jannis Clausius, Sebastian Cammerer, Stephan ten Brink

We propose and practically demonstrate a joint detection and decoding scheme for short-packet wireless communications in scenarios that require to first detect the presence of a message before actually decoding it. For this, we extend the recently proposed serial Turbo-autoencoder neural network (NN) architecture and train it to find short messages that can

Chuan He, Zhaosong Lu

In this paper we consider finding an approximate second-order stationary point (SOSP) of nonconvex conic optimization that minimizes a twice differentiable function over the intersection of an affine subspace and a convex cone. In particular, we propose a Newton-conjugate gradient (Newton-CG) based barrier method for finding an $(\epsilon,\sqrt{\epsilon})$-S

Prateek Chhikara, Anil Goyal, Chirag Sharma

Real-estate image tagging is one of the essential use-cases to save efforts involved in manual annotation and enhance the user experience. This paper proposes an end-to-end pipeline (referred to as RE-Tagger) for the real-estate image classification problem. We present a two-stage transfer learning approach using custom InceptionV3 architecture to classify i

Chenguang Wan, Zhi Yu, Alessandro Pau, Xiaojuan Liu

Nuclear fusion represents one of the best alternatives for a sustainable source of clean energy. Tokamaks allow to confine fusion plasma with magnetic fields and one of the main challenges in the control of the magnetic configuration is the prediction/reconstruction of the Last Closed-Flux Surface (LCFS). The evolution in time of the LCFS is determined by th

Chandan Datta, Tulja Varun Kondra, Marek Miller, Alexander Streltsov

In chemistry, a catalyst is a substance which enables a chemical reaction or increases its rate, while remaining unchanged in the process. Instead of chemical reactions, quantum catalysis enhances our ability to convert quantum states into each other under physical constraints. The nature of the constraints depends on the problem under study and can arise, e

C. Vargas, S. Villanova, D. Geisler, C. Muñoz

NGC 362 is a non-common Type II Galactic globular cluster, showing a complex pseudo two-color diagram or 'chromosome map'. The clear separation of its stellar populations in the color-magnitude diagram and the distribution of the giant stars in the chromosome map strongly suggests that NGC 362 could host stars with both cluster-nominal as well as enhanced he

Robin Croft, Thomas Helfer, Bo-Xuan Ge, Miren Radia

In this work we study the long-lived post-merger gravitational wave signature of a boson-star binary coalescence. We use full numerical relativity to simulate the post-merger and track the gravitational afterglow over an extended period of time. We implement recent innovations for the binary initial data, which significantly reduce spurious initial excitatio

Travis A. Rector, Allen W. Shafter, William A. Burris, Matthew J. Walentosky

A long-term (1995-2016) survey for novae in the nearby Andromeda galaxy (M31) was conducted as part of the Research-Based Science Education initiative. During the course of the survey 180 nights of observation were completed at Kitt Peak, Arizona. A total of 262 novae were either discovered or confirmed, 40 of which have not been previously reported. Of thes

Chen Zhang, Luchin Chang, Songruoyao Wu, Xu Tan

Lyric-to-melody generation, which generates melody according to given lyrics, is one of the most important automatic music composition tasks. With the rapid development of deep learning, previous works address this task with end-to-end neural network models. However, deep learning models cannot well capture the strict but subtle relationships between lyrics

Nanoom Lee, Selim C. Hotinli, Marc Kamionkowski

If the physics behind dark energy and/or dark matter violates the parity symmetry assumed in the standard cosmological paradigm, the linear polarization of the cosmic microwave background (CMB) photons can rotate due to their coupling to the dark sector. Recent 3$\sigma$ hints of this ``cosmic birefringence" in the EB spectrum of the CMB polarization motivat

Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang

Multiclass neural networks are a common tool in modern unsupervised domain adaptation, yet an appropriate theoretical description for their non-uniform sample complexity is lacking in the adaptation literature. To fill this gap, we propose the first PAC-Bayesian adaptation bounds for multiclass learners. We facilitate practical use of our bounds by also prop

Tamon Nakano, Alessandro Michele Bucci, Jean-Marc Gratien, Thibault Faney

The volume of fluid (VoF) method is widely used in multi-phase flow simulations to track and locate the interface between two immiscible fluids. A major bottleneck of the VoF method is the interface reconstruction step due to its high computational cost and low accuracy on unstructured grids. We propose a machine learning enhanced VoF method based on Graph N

Kiri L. Wagstaff, Ingrid J. Daubar, Gary Doran, Michael J. Munje

The current inventory of recent (fresh) impacts on Mars shows a strong bias towards areas of low thermal inertia. These areas are generally visually bright, and impacts create dark scours and rays that make them easier to detect. It is expected that impacts occur at a similar rate in areas of higher thermal inertia, but those impacts are under-detected. This

Hannes Kallwies, Martin Leucker, Cesar Sanchez

Runtime Verification deals with the question of whether a run of a system adheres to its specification. This paper studies runtime verification in the presence of partial knowledge about the observed run, particularly where input values may not be precise or may not be observed at all. We also allow declaring assumptions on the execution which permits to obt

Hervé Yviquel, Marcio Pereira, Emílio Francesquini, Guilherme Valarini

Despite the various research initiatives and proposed programming models, efficient solutions for parallel programming in HPC clusters still rely on a complex combination of different programming models (e.g., OpenMP and MPI), languages (e.g., C++ and CUDA), and specialized runtimes (e.g., Charm++ and Legion). On the other hand, task parallelism has shown to

Hao Li, Zeyu Tang, Yang Nan, Guang Yang

Various structures in human physiology follow a treelike morphology, which often expresses complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal blood vessels, and hepatic blood vessels. Large collections of 2D and 3D images have been made available by medical imaging modalities such as magnetic resonance imaging (MRI

Alexander Smith

In this paper and its sequel, we develop a technique for finding the distribution of $\ell^{\infty}$-Selmer groups in degree $\ell$ twist families of Galois modules over number fields. Given an elliptic curve E over a number field satisfying certain technical conditions, this technique can be used to show that 100% of the quadratic twists of E have rank at m

Ling Xiao

In this paper, we prove a generalized Minkowski inequality holds for any smooth, $(k-1)$-convex, starshaped domain $\Omega.$ Our proof relies on the solvability of the degenerate $k$-Hessian equation on the exterior domain $\mathbb R^n\setminus\Omega.$

Farhan Tanvir, Khaled Mohammed Saifuddin, Esra Akbas

Polypharmacy, defined as the use of multiple drugs together, is a standard treatment method, especially for severe and chronic diseases. However, using multiple drugs together may cause interactions between drugs. Drug-drug interaction (DDI) is the activity that occurs when the impact of one drug changes when combined with another. DDIs may obstruct, increas

Eugene Wickett, Matthew Plumlee, Karen Smilowitz, Souly Phanouvong

Substandard and falsified pharmaceuticals, prevalent in low- and middle-income countries, substantially increase levels of morbidity, mortality and drug resistance. Regulatory agencies combat this problem using post-market surveillance by collecting and testing samples where consumers purchase products. Existing analysis tools for post-market surveillance da

Victor E. Ambrus, Etele Molnár, Dirk H. Rischke

We derive the transport coefficients of second-order fluid dynamics with $14$ dynamical moments using the method of moments and the Chapman-Enskog method in the relaxation-time approximation for the collision integral of the relativistic Boltzmann equation. Contrary to results previously reported in the literature, we find that the second-order transport coe

Matteo Bunino

Graph Convolutional Networks (GCNs) have been shown to be a powerful concept that has been successfully applied to a large variety of tasks across many domains over the past years. In this work we study the theory that paved the way to the definition of GCN, including related parts of classical graph theory. We also discuss and experimentally demonstrate key

Yixian Zhang, Sophie Musset, Lindsay Glesener, Navdeep Panesar

We present a multi-wavelength analysis of two flare-related jets on November 13, 2014, using data from SDO/AIA, RHESSI, Hinode/XRT, and IRIS. Unlike most coronal jets where hard X-ray (HXR) emissions are usually observed near the jet base, in these events HXR emissions are found at several locations, including in the corona. We carry out the first differenti

Eli Hawkins, Christoph Minz, Kasia Rejzner

Geometric quantization is a natural way to construct quantum models starting from classical data. In this work, we start from a symplectic vector space with an inner product and -- using techniques of geometric quantization -- construct the quantum algebra and equip it with a distinguished state. We compare our result with the construction due to Sorkin -- w

Shijie Wu, Benjamin Van Durme, Mark Dredze

Pretrained multilingual encoders enable zero-shot cross-lingual transfer, but often produce unreliable models that exhibit high performance variance on the target language. We postulate that this high variance results from zero-shot cross-lingual transfer solving an under-specified optimization problem. We show that any linear-interpolated model between the

Bin Yan, Nikolai A. Sinitsyn

Grover's search algorithm was originally proposed for circuit-based quantum computers. A crucial part of it is to query an oracle -- a black-box unitary operation. Generation of this oracle is formally beyond the original algorithm design. Here, we propose a realization of Grover's oracle for a large class of searching problems using a quantum annealing step

Danièle Gardy, Frédéric Lardeux, Frédéric Saubion

Initially introduced by Peter Hammer, Logical Analysis of Data is a methodology that aims at computing a logical justification for dividing a group of data in two groups of observations, usually called the positive and negative groups. Consider this partition into positive and negative groups as the description of a partially defined Boolean function; the da

Francisco J. Aragón-Artacho, Yair Censor, Aviv Gibali, David Torregrosa-Belén

In this paper we study the split minimization problem that consists of two constrained minimization problems in two separate spaces that are connected via a linear operator that maps one space into the other. To handle the data of such a problem we develop a superiorization approach that can reach a feasible point with reduced (not necessarily minimal) objec

Alexandre E. Adler, Adriaan J. Duivenvoorden, Jon E. Gudmundsson

Microwave telescopes require an ever-increasing control of experimental systematics in their quest to measure the Cosmic Microwave Background (CMB) to exquisite levels of precision. One important systematic for ground and balloon-borne experiments is ground pickup, where beam sidelobes detect the thermal emission of the much warmer ground while the main beam

Ahmad Alachkar, John Ellis, Malcolm Fairbairn

OJ 287 is a blazar thought to be a binary system containing a ~ 18 billion solar mass primary black hole accompanied by a ~ 150 million solar mass secondary black hole in an eccentric orbit, which triggers electromagnetic flares twice in every ~ 12 year orbital period when it traverses the accretion disk of the primary. The times of these emissions are consi

Vinod Kumar Solet, Shamim Sk, Sudhir K. Pandey

Here, we present a theoretical study in the context of photovoltaic (PV) and thermoelectric (TE) applications of ScAgC. The electronic, optical, and thermoelectric properties have been investigated systematically using density functional theory (DFT) and semi-classical Boltzmann transport theory. DFT calculates a direct band gap of 0.47 eV, whereas the $G_{0

Minas Karamanis, David Nabergoj, Florian Beutler, John A. Peacock

pocoMC is a Python package for accelerated Bayesian inference in astronomy and cosmology. The code is designed to sample efficiently from posterior distributions with non-trivial geometry, including strong multimodality and non-linearity. To this end, pocoMC relies on the Preconditioned Monte Carlo algorithm which utilises a Normalising Flow in order to deco

Hung Le

Thorup [FOCS'01, JACM'04] and Klein [SODA'01] independently showed that there exists a $(1+\epsilon)$-approximate distance oracle for planar graphs with $O(n (\log n)\epsilon^{-1})$ space and $O(\epsilon^{-1})$ query time. While the dependency on $n$ is nearly linear, the space-query product of their oracles depend quadratically on $1/\epsilon$. Many follow-

Eric Duverger, Damien Riedel

The use and the study of semi-insulating layers on metals and semiconductors surfaces have found continuous interest in the past decades. So far, the control of the sizes and growth location of the insulating islands on the substrate is either ill-defined or usually constrained to the use of evaporation masks which size can easily exceed tenth of nanometers.

Xiao Pan, Hao Luo, Weihua Chen, Fan Wang

We study the backward compatible problem for person re-identification (Re-ID), which aims to constrain the features of an updated new model to be comparable with the existing features from the old model in galleries. Most of the existing works adopt distillation-based methods, which focus on pushing new features to imitate the distribution of the old ones. H

Vianney Lebouteiller, Lise Ramambason

(abridged) Spectroscopic observations of high-redshift galaxies slowly reveal the same complexity of the interstellar medium (ISM) as expected from resolved observations in nearby galaxies. While providing a wealth of diagnostics, such high-z spectra are often unresolved, and inferring reliable diagnostics represents a major obstacle. Bright, nearby, unresol

D. Munoz-Lahoz, J. Calsamiglia, J. A. Bergou, E. Bagan

We investigate the ultimate precision limits for quantum phase estimation in terms of the coherence, $C$, of the probe. For pure states, we give the minimum estimation variance attainable, $V(C)$, and the optimal state, in the asymptotic limit when the probe system size, $n$, is large. We prove that pure states are optimal only if $C$ scales as $n$ with a su

Zhiwen Zhao

The insulated and perfect conductivity problems arising from high-contrast composite materials are considered in all dimensions. The solution and its gradient, respectively, represent the electric potential and field. The novelty of this paper lies in finding exact solutions for the insulated and perfect conductivity problems with concentric balls. Our resul

L. B. Shao, Z. Y. Chen, K. Wang, S. A. Yang

It was commonly believed that a mirror Chern insulator (MCI) must require spin-orbital coupling, since time-reversal symmetry for spinless systems contradicts with the mirror Chern number. So MCI cannot be realized in spinless systems which include the large field of topological artificial crystals. Here, we disprove this common belief. The first point to cl

Nora Lüthen, Stefano Marelli, Bruno Sudret

Stochastic simulators are non-deterministic computer models which provide a different response each time they are run, even when the input parameters are held at fixed values. They arise when additional sources of uncertainty are affecting the computer model, which are not explicitly modeled as input parameters. The uncertainty analysis of stochastic simulat

Minas Karamanis, Florian Beutler, John A. Peacock, David Nabergoj

We introduce Preconditioned Monte Carlo (PMC), a novel Monte Carlo method for Bayesian inference that facilitates efficient sampling of probability distributions with non-trivial geometry. PMC utilises a Normalising Flow (NF) in order to decorrelate the parameters of the distribution and then proceeds by sampling from the preconditioned target distribution u

Stanisław Baran, Aleksandra Deptuch, Andreas Hoser, Bogusław Penc

Crystal and magnetic structures of $R_2$Ni$_2$In ($R$ = Tb and Ho) have been studied by powder neutron diffraction at low temperatures. The compounds crystallize in an orthorhombic crystal structure of the Mn$_2$AlB$_2$-type. At low temperatures, the magnetic moments localized solely on the rare earth atoms form antiferromagnetic structures. The Tb magnetic

Songtao Lu

Nonconvex constrained optimization problems can be used to model a number of machine learning problems, such as multi-class Neyman-Pearson classification and constrained Markov decision processes. However, such kinds of problems are challenging because both the objective and constraints are possibly nonconvex, so it is difficult to balance the reduction of t

Christopher A. Browne, Richard B. Huang, Callie W. Zheng, Sujit S. Datta

Many key environmental, industrial, and energy processes rely on controlling fluid transport within subsurface porous media. These media are typically structurally heterogeneous, often with vertically-layered strata of distinct permeabilities -- leading to uneven partitioning of flow across strata, which can be undesirable. Here, using direct in situ visuali

Antoine Fosset, Mohamed El-Mennaoui, Amine Rebei, Paul Calligaro

Recommendation systems have been widely used in various domains such as music, films, e-shopping etc. After mostly avoiding digitization, the art world has recently reached a technological turning point due to the pandemic, making online sales grow significantly as well as providing quantitative online data about artists and artworks. In this work, we presen

Gaojun Luo, Martianus Frederic Ezerman, Markus Grassl, San Ling

In the setting of entanglement-assisted quantum error-correcting codes (EAQECCs), the sender and the receiver have access to pre-shared entanglement. Such codes promise better information rates or improved error handling properties. Entanglement incurs costs and must be judiciously calibrated in designing quantum codes with good performance, relative to thei

Stefano Chessa, Vittorio Giovannetti

We introduce a new set of quantum channels: resonant multilevel amplitude damping (ReMAD) channels. Among other instances, they can describe energy dissipation effects in multilevel atomic systems induced by the interaction with a zero-temperature bosonic environment. At variance with the already known class of multilevel amplitude damping (MAD) channels, th

Vivek Pandey, Divyansh Shrimali, Brij Mohan, Siddhartha Das

Quantum speed limit is bound on the minimum time a quantum system requires to evolve from an initial state to final state under a given dynamical process. It sheds light on how fast a desired state transformation can take place which is pertinent for design and control of quantum technologies. In this paper, we derive speed limits on correlations such as ent

Benoit Pausader, Klaus Widmayer, Jiaqi Yang

We consider solutions of the repulsive Vlasov-Poisson system which are a combination of a point charge and a small gas, i.e.\ measures of the form $\delta_{(\mathcal{X}(t),\mathcal{V}(t))}+\mu^2d{\bf x}d{\bf v}$ for some $(\mathcal{X}, \mathcal{V}):\mathbb{R}\to\mathbb{R}^6$ and a small gas distribution $\mu:\mathbb{R}\to L^2_{{\bf x},{\bf v}}$, and study as

Koorosh Aslansefat, Panagiota Nikolaou, Martin Walker, Mohammed Naveed Akram

The use of Unmanned Arial Vehicles (UAVs) offers many advantages across a variety of applications. However, safety assurance is a key barrier to widespread usage, especially given the unpredictable operational and environmental factors experienced by UAVs, which are hard to capture solely at design-time. This paper proposes a new reliability modeling approac

Derek Hansen, Ismael Mendoza, Runjing Liu, Ziteng Pang

We present a new probabilistic method for detecting, deblending, and cataloging astronomical sources called the Bayesian Light Source Separator (BLISS). BLISS is based on deep generative models, which embed neural networks within a Bayesian model. For posterior inference, BLISS uses a new form of variational inference known as Forward Amortized Variational I

Yuhua Sun, Tailai Zhang, Xingjun Ma, Pan Zhou

Crowd counting is a regression task that estimates the number of people in a scene image, which plays a vital role in a range of safety-critical applications, such as video surveillance, traffic monitoring and flow control. In this paper, we investigate the vulnerability of deep learning based crowd counting models to backdoor attacks, a major security threa

Ching Him Leung

The Fermilab SeaQuest experiment has measured dimuon events from the interactions of 120GeV proton beam on liquid hydrogen and deuterium targets with dimuon mass between 2 and 9GeV. These dimuon events contain both the Drell-Yan process and the charmonium ($J/\psi$ and $\psi^\prime$) production. Unlike the Drell-Yan process which probes the antiquark distrib

Anastasia Halfpap, Nathan Lemons, Cory Palmer

The \emph{minimum positive co-degree} of a non-empty $r$-graph ${H}$, denoted $\delta_{r-1}^+( {H})$, is the maximum $k$ such that if $S$ is an $(r-1)$-set contained in a hyperedge of $ {H}$, then $S$ is contained in at least $k$ distinct hyperedges of $ {H}$. Given an $r$-graph ${F}$, we introduce the \emph{positive co-degree Tur\'an number} $\mathrm{co^+ex

Bülent Köklüce

In this article, we find bases for the spaces of modular forms $M_{3}(\Gamma _{0}(40),\left( \frac{d}{\cdot }\right) )$ for $d=-4,-8,-20\text{ and }-40.$ We then derive formulas for the number of representations of a positive integer by all the diagonal sextenary quadratic forms with coefficients $% 1,2,5$ and $10$.

Ekrem Aydiner

Neutrino physics is one of the most important topics in particle physics and cosmology. Despite the many physical properties of neutrinos that are understood theoretically and experimentally, it is known that there are many unsolved problems in this area. In this study, we suppose that the deformed space-time caused by the gravitational perturbation can play

Justine Zeghal, François Lanusse, Alexandre Boucaud, Benjamin Remy

Simulation-Based Inference (SBI) is a promising Bayesian inference framework that alleviates the need for analytic likelihoods to estimate posterior distributions. Recent advances using neural density estimators in SBI algorithms have demonstrated the ability to achieve high-fidelity posteriors, at the expense of a large number of simulations ; which makes t

Fabian Grünewald, Mats H. Punt, Elizabeth E. Jefferys, Petteri A. Vainikka

The Martini 3 force field is a full re-parametrization of the Martini coarse-grained model for biomolecular simulations. Due to the improved interaction balance it allows for more accurate description of condensed phase systems. In the present work we develop a consistent strategy to parametrize carbohydrate molecules accurately within the framework of Marti

Davide Talon, Alessio Del Bue, Stuart James

Puzzle solving is a combinatorial challenge due to the difficulty of matching adjacent pieces. Instead, we infer a mental image from all pieces, which a given piece can then be matched against avoiding the combinatorial explosion. Exploiting advancements in Generative Adversarial methods, we learn how to reconstruct the image given a set of unordered pieces,

Eva Kopfer, Jeffrey Streets

As a consequence of the Bochner formula for the Bismut connection acting on gradients, we show sharp universal Poincar\'e and log-Sobolev inequalities along solutions to generalized Ricci flow. Using the two-form potential we define a twisted connection on spacetime which determines an adapted Brownian motion on the frame bundle, yielding an adapted Malliavi

Jane Rigby, Marshall Perrin, Michael McElwain, Randy Kimble

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is full

Wentse Chen, Shiyu Huang, Yuan Chiang, Tim Pearce

Most reinforcement learning algorithms seek a single optimal strategy that solves a given task. However, it can often be valuable to learn a diverse set of solutions, for instance, to make an agent's interaction with users more engaging, or improve the robustness of a policy to an unexpected perturbance. We propose Diversity-Guided Policy Optimization (DGPO)

Alexander Stephens, Ross Stokke

We introduce the notion of an introverted Boolean algebra $\cal B$ of closed-and-open subsets of a topological group $G$, show that the associated Stone space $(\nu_{\cal B} G, \nu_{\cal B})$ is a totally disconnected semigroup compactification of $G$, and show that every totally disconnected semigroup compactification of $G$ takes this form. We identify and

Sam Mundy

We study the variation of admissible representations of $p$-adic $GL_n$ in families from the point of view of the Bernstein--Zelevinsky classification and show that the ramified parts of these families are rigid. We explain how to apply our results in the context of $GL_n$-eigenvarieties.

Philipp Grohs, Lukas Liehr

The reconstruction of a function from its spectrogram (i.e., the absolute value of its short-time Fourier transform (STFT)) arises as a key problem in several important applications, including coherent diffraction imaging and audio processing. It is a classical result that for suitable windows any function can, in principle, be uniquely recovered up to a glo

G. Zicari, B. Çakmak, Özgür E. Müstecaplıoğlu, M. Paternostro

Recent studies have pointed out the intrinsic dependence of figures of merit of thermodynamic relevance -- such as work, heat and entropy production -- on the amount of quantum coherences that is made available to a system. However, whether coherences hinder or enhance the value taken by such quantifiers of thermodynamic performance is yet to be ascertained.

Amirmohammad Farzaneh, Mihai-Alin Badiu, Justin P. Coon

Routing tables in ad hoc and wireless routing protocols can be represented using rooted trees. The constant need for communication and storage of these trees in routing protocols demands an efficient rooted tree coding algorithm. This efficiency is defined in terms of the average code length, and the optimality of the algorithm is measured by comparing the a

A. C. Alvarez, J. Bruining, D. Marchesin

This paper is concerned with the study of the main wave interactions in a system of conservation laws in geochemical modeling. We study the modeling of the chemical complexes on the rock surface. The presence of stable surface complexes affects the relative permeability. We add terms representing surface complexes to the accumulation function in the model pr

Sepehr Abbasi, Shiva Ketabi, Ali Munir, Mahmoud Bahnasy

Congestion control algorithms rely on a variety of congestion signals (packet loss, Explicit Congestion Notification, delay, etc.) to achieve fast convergence, high utilization, and fairness among flows. A key limitation of these congestion signals is that they are either late in feedback or they incur significant overheads. An ideal congestion control must

G. Longo, E. Russo, A. Armando, A. Merlo

Operation of radar equipment is one of the key facilities used by navigators to gather situational awareness about their surroundings. With an ever increasing need for always-running logistics and tighter shipping schedules, operators are relying more and more on computerized instruments and their indications. As a result, modern ships have become a complex

Enrico Ferrentino, Heitor J. Savino, Antonio Franchi, Pasquale Chiacchio

Offline optimal planning of trajectories for redundant robots along prescribed task space paths is usually broken down into two consecutive processes: first, the task space path is inverted to obtain a joint space path, then, the latter is parametrized with a time law. If the two processes are separated, they cannot optimize the same objective function, ulti

Sixiang Chen, Tian Ye, Yun Liu, Taodong Liao

Snow removal causes challenges due to its characteristic of complex degradations. To this end, targeted treatment of multi-scale snow degradations is critical for the network to learn effective snow removal. In order to handle the diverse scenes, we propose a multi-scale projection transformer (MSP-Former), which understands and covers a variety of snow degr

António J. Abreu, Luís A. Alexandre, João A. Santos, Filippo Basso

Remote sensing is the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance. It is being broadly used to monitor ecosystems, mainly for their preservation. Ever-growing reports of invasive species have affected the natural balance of ecosystems. Exotic invasive species have

Yu Wang, J. A. Rueda, R. Ruffini, R. Moradi

GRB 190829A is the fourth closest gamma-ray burst (GRB) to date ($z=0.0785$). Owing to its wide range of radio, optical, X-ray, and the very-high-energy (VHE) observations by H.E.S.S., it has become an essential new source examined by various models with complementary approaches. We here show in GRB 190829A the double-prompt pulses and the three-multiwavelen

Wilhem Barbier, Jonathan Dupuy

We introduce per-halfedge texturing (Htex) a GPU-friendly method for texturing arbitrary polygon-meshes without an explicit parameterization. Htex builds upon the insight that halfedges encode an intrinsic triangulation for polygon meshes, where each halfedge spans a unique triangle with direct adjacency information. Rather than storing a separate texture pe

Michael Borkowski, Niki Vazou, Ranjit Jhala

Practical checkers based on refinement types use the combination of implicit semantic sub-typing and parametric polymorphism to simplify the specification and automate the verification of sophisticated properties of programs. However, a formal meta-theoretic accounting of the soundness of refinement type systems using this combination has proved elusive. We