Particle Transport in Young Pulsar Wind Nebulae

The model for pulsar wind nebulae (PWNe) as the result of the magnetohydrodynamic (MHD) downstream flow from a shocked, relativistic pulsar wind has been successful in reproducing many features of the nebulae observed close to the central pulsars. However, observations of well-studied young nebulae like the Crab Nebula, 3C 58, and G21.5--0.9 do not show the toroidal magnetic field on a larger scale that might be expected in the MHD flow model; in addition, the radial variation of spectral index due to synchrotron losses is smoother than expected in the MHD flow model. We find that pure diffusion models can reproduce the basic data on nebular size and spectral index variation for the Crab, 3C 58, and G21.5--0.9. Most of our models use an energy independent diffusion coefficient; power law variations of the coefficient with energy are degenerate with variation in the input particle energy distribution index in the steady state, transmitting boundary case. Energy dependent diffusion is a possible reason for the smaller diffusion coefficient inferred for the Crab. Monte Carlo simulations of the particle transport allowing for advection and diffusion of particles suggest that diffusion dominates over much of the total nebular volume of the Crab. Advection dominates close to the pulsar and is likely to play a role in the X-ray half-light radius. The source of diffusion and mixing of particles is uncertain, but may be related to the Rayleigh-Taylor instability at the outer boundary of a young PWN or to instabilities in the toroidal magnetic field structure.Comment: 13 pages, ApJ, in press, corrected typ

Fractional Fourier detection of L\'evy Flights: application to Hamiltonian chaotic trajectories

A signal processing method designed for the detection of linear (coherent) behaviors among random fluctuations is presented. It is dedicated to the study of data recorded from nonlinear physical systems. More precisely the method is suited for signals having chaotic variations and sporadically appearing regular linear patterns, possibly impaired by noise. We use time-frequency techniques and the Fractional Fourier transform in order to make it robust and easily implementable. The method is illustrated with an example of application: the analysis of chaotic trajectories of advected passive particles. The signal has a chaotic behavior and encounter L\'evy flights (straight lines). The method is able to detect and quantify these ballistic transport regions, even in noisy situations

A Chandra View Of Nonthermal Emission In The Northwestern Region Of Supernova Remnant RCW 86: Particle Acceleration And Magnetic Fields

The shocks of supernova remnants (SNRs) are believed to accelerate particles to cosmic ray (CR) energies. The amplification of the magnetic field due to CRs propagating in the shock region is expected to have an impact on both the emission from the accelerated particle population, as well as the acceleration process itself. Using a 95 ks observation with the Advanced CCD Imaging Spectrometer (ACIS) onboard the Chandra X-ray Observatory, we map and characterize the synchrotron emitting material in the northwestern region of RCW 86. We model spectra from several different regions, filamentary and diffuse alike, where emission appears dominated by synchrotron radiation. The fine spatial resolution of Chandra allows us to obtain accurate emission profiles across 3 different non-thermal rims in this region. The narrow width (l = 10''-30'') of these filaments constrains the minimum magnetic field strength at the post-shock region to be approximately 80 {\mu}G.Comment: 7 pages, 3 figures, submitted for publication at the Astrophysical Journa

Imaging of a fluid injection process using geophysical data - A didactic example

In many subsurface industrial applications, fluids are injected into or withdrawn from a geologic formation. It is of practical interest to quantify precisely where, when, and by how much the injected fluid alters the state of the subsurface. Routine geophysical monitoring of such processes attempts to image the way that geophysical properties, such as seismic velocities or electrical conductivity, change through time and space and to then make qualitative inferences as to where the injected fluid has migrated. The more rigorous formulation of the time-lapse geophysical inverse problem forecasts how the subsurface evolves during the course of a fluid-injection application. Using time-lapse geophysical signals as the data to be matched, the model unknowns to be estimated are the multiphysics forward-modeling parameters controlling the fluid-injection process. Properly reproducing the geophysical signature of the flow process, subsequent simulations can predict the fluid migration and alteration in the subsurface. The dynamic nature of fluid-injection processes renders imaging problems more complex than conventional geophysical imaging for static targets. This work intents to clarify the related hydrogeophysical parameter estimation concepts