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We consider an inverse problem for the compressible Euler's equations in polytropic fluid. We show that by taking active measurements near a particle trajectory one can determine the background flow in a set where pressure waves can…

Analysis of PDEs · Mathematics 2026-04-17 Gunther Uhlmann , Yuchao Yi , Jian Zhai

Experimental studies of the optical properties of compressible, viscous and rapidly-rotating gas flows (vortices) are presented. Gas vortices can function as optical elements such as lenses or waveguides. The optical properties are…

Optics · Physics 2020-07-15 D. Kaganovich , B. Hafizi , L. A. Johnson , D. F. Gordon

Recent advances in signal processing have focused on the use of sparse representations in various applications. A new field of interest based on sparsity has recently emerged: compressed sensing. This theory is a new sampling framework that…

Astrophysics · Physics 2009-11-13 J. Bobin , J-L Starck , R. Ottensamer

The density fluctuations of quantum vortex lines are measured in a turbulent flow of superfluid He, at temperatures corresponding to superfluid fraction of 16%, 47% and 81%. The probe is a micro-fabricated second sound resonator that allows…

Fluid Dynamics · Physics 2021-08-11 Eric Woillez , Jérôme Valentin , Philippe-E Roche

Compressed Sensing decoding algorithms can efficiently recover an N dimensional real-valued vector x to within a factor of its best k-term approximation by taking m = 2klog(N/k) measurements y = Phi x. If the sparsity or approximate…

Numerical Analysis · Mathematics 2008-12-09 Rachel Ward

Sampling the Boltzmann distribution using forces that violate detailed balance can be faster than with the equilibrium evolution, but the acceleration depends on the nature of the nonequilibrium drive and the physical situation. Here, we…

Soft Condensed Matter · Physics 2023-12-20 Federico Ghimenti , Ludovic Berthier , Grzegorz Szamel , Frédéric van Wijland

We continue our work on developing techniques for studying turbulence with spectroscopic data. We show that Doppler-broadened absorption spectral lines, in particularly, saturated absorption lines, can be used within the framework of the…

Astrophysics · Physics 2009-11-13 A. Lazarian , D. Pogosyan

Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals and images that enables sampling rates significantly below the classical Nyquist rate. Despite significant progress in the theory and methods of…

Computer Vision and Pattern Recognition · Computer Science 2013-06-27 Aswin C Sankaranarayanan , Pavan K Turaga , Rama Chellappa , Richard G Baraniuk

The VKS experiment has evidenced dynamo action in a highly turbulent liquid sodium von K\'arm\'an flow [R. Monchaux et al., Phys. Rev. Lett. {\bf 98}, 044502 (2007)]. However, the existence and the onset of a dynamo happen to depend on the…

Fluid Dynamics · Physics 2011-06-10 A. Pinter , B. Dubrulle , F. Daviaud , J. Leorat

We present a Parseval tight wavelet frame for the representation and analysis of velocity vector fields of incompressible fluids. Our wavelets have closed form expressions in the frequency and spatial domains, are divergence free in the…

Numerical Analysis · Computer Science 2019-03-27 Christian Lessig

Vorticity in two-dimensional superfluids is subject to intense research efforts due to its role in quantum turbulence, dissipation and the BKT phase transition. Interaction of sound and vortices is of broad importance in Bose-Einstein…

Steady-state RANS simulations are reported for 2D flow around an ellipse and a von-K\'arm\'an-Trefftz airfoil at seven different angles of attack and two different Reynolds numbers, computed using the $k \omega SST$ turbulence model in…

Fluid Dynamics · Physics 2026-04-13 Christian Bak Winther , Peter Ammundsen , Fynn Jerome Aschmoneit

Based on machine learning techniques, we propose a novel method to estimate flow fields using only floating sensor locations. This method does not require either ground-truth velocity fields or governing equations for fluid flows, which is…

Fluid Dynamics · Physics 2026-04-07 Tomoya Oura , Reno Miura , Koji Fukagata

We present an energy-conserving multiple-relaxation-time finite difference lattice Boltzmann model for compressible flows. This model is based on a 16-discrete-velocity model. The collision step is first calculated in the moment space and…

Statistical Mechanics · Physics 2015-05-14 Feng Chen , Aiguo Xu , Guangcai Zhang , Yingjun Li

This paper presents a tutorial for CS applications in communications networks. The Shannon's sampling theorem states that to recover a signal, the sampling rate must be as least the Nyquist rate. Compressed sensing (CS) is based on the…

Networking and Internet Architecture · Computer Science 2014-02-07 Hong Huang , Satyajayant Misra , Wei Tang , Hajar Barani , Hussein Al-Azzawi

Compressive sensing is a signal processing technique that enables the reconstruction of sparse signals from a limited number of measurements, leveraging the signal's inherent sparsity to facilitate efficient recovery. Recent works on the…

Quantum Physics · Physics 2025-01-22 Naveed Naimipour , Collin Frink , Harry Shaw , Haleh Safavi , Mojtaba Soltanalian

We analyze a volumetric formulation of lattice Boltzmann for compressible thermal fluid flows. The velocity set is chosen with the desired accuracy, based on the Gauss-Hermite quadrature procedure, and tested against controlled problems in…

Soft Condensed Matter · Physics 2015-05-18 M. Sbragaglia , K. Sugiyama

We discuss a long-standing problem of how turbulence can be studied using observations of Doppler broadened emission and absorption lines. The focus of the present review is on two new techniques, the Velocity-Channel Analysis (VCA), which…

Astrophysics · Physics 2011-05-10 A. Lazarian

Hybrid magnetometers based on a normal conducting sensor and a superconducting flux concentrator have been investigated. When this sensor is operated in an unshielded environment flux vortices can be trapped in the superconducting body when…

Superconductivity · Physics 2008-09-19 K. H. Kuit , J. R. Kirtley , H. Rogalla , J. Flokstra

Quantum waveform estimation, in which quantum sensors sample entire time series, promises to revolutionize the sensing of weak and stochastic signals, such as the biomagnetic impulses emitted by firing neurons. For long duration signals…