The Experts below are selected from a list of 72156 Experts worldwide ranked by ideXlab platform
D. Maurin - One of the best experts on this subject based on the ideXlab platform.
-
a markov chain Monte Carlo Technique to sample transport and source parameters of galactic cosmic rays ii results for the diffusion model combining b c and radioactive nuclei
Astronomy and Astrophysics, 2010Co-Authors: A. Putze, L. Derome, D. MaurinAbstract:Context. Ongoing measurements of the cosmic radiation (nuclear, electronic, and γ-ray) are providing additional insight into cosmicray physics. A comprehensive picture of these data relies on an accurate determination of the transport and source parameters of propagation models. Aims. A Markov Chain Monte Carlo method is used to obtain these parameters in a diffusion model. By measuring the B/C ratio and radioactive cosmic-ray clocks, we calculate their probability density functions, placing special emphasis on the halo size L of the Galaxy and the local underdense bubble of size rh. We also derive the mean, best-fit model parameters and 68% confidence level for the various parameters, and the envelopes of other quantities. Methods. The analysis relies on the USINE code for propagation and on a Markov Chain Monte Carlo Technique previously developed by ourselves for the parameter determination. Results. The B/C analysis leads to a most probable diffusion slope δ = 0.86 +0.04
-
A Markov Chain Monte Carlo Technique to sample transport and source parameters of Galactic cosmic rays: II. Results for the diffusion model combining B/C and radioactive nuclei
Astronomy and Astrophysics - A&A, 2010Co-Authors: A. Putze, L. Derome, D. MaurinAbstract:On-going measurements of the cosmic radiation (nuclear, electronic, and gamma-ray) are shedding new light on cosmic-ray physics. A comprehensive picture of these data relies on an accurate determination of the transport and source parameters of propagation models. A Markov Chain Monte Carlo is used to obtain these parameters in a diffusion model. From the measurement of the B/C ratio and radioactive cosmic-ray clocks, we calculate their probability density functions, with a special emphasis on the halo size L of the Galaxy and the local underdense bubble of size r_h. The analysis relies on the USINE code for propagation and on a Markov Chain Monte Carlo Technique (Putze et al. 2009, paper I of this series) for the parameter determination. As found in previous studies, the B/C best-fit model favours diffusion/convection/reacceleration (Model III) over diffusion/reacceleration (Model II). A combined fit on B/C and the isotopic ratios (10Be/9Be, 26Al/27Al, 36Cl/Cl) leads to L ~ 8 kpc and r_h ~ 120 pc for the best-fit Model III. This value for r_h is consistent with direct measurements of the local interstallar medium. For Model II, L ~ 4 kpc and r_h is consistent with zero. We showed the potential and usefulness of the Markov Chain Monte Carlo Technique in the analysis of cosmic-ray measurements in diffusion models. The size of the diffusive halo depends crucially on the value of the diffusion slope delta, and also on the presence/absence of the local underdensity damping effect on radioactive nuclei. More precise data from on-going experiments are expected to clarify this issue.
A. Putze - One of the best experts on this subject based on the ideXlab platform.
-
a markov chain Monte Carlo Technique to sample transport and source parameters of galactic cosmic rays ii results for the diffusion model combining b c and radioactive nuclei
Astronomy and Astrophysics, 2010Co-Authors: A. Putze, L. Derome, D. MaurinAbstract:Context. Ongoing measurements of the cosmic radiation (nuclear, electronic, and γ-ray) are providing additional insight into cosmicray physics. A comprehensive picture of these data relies on an accurate determination of the transport and source parameters of propagation models. Aims. A Markov Chain Monte Carlo method is used to obtain these parameters in a diffusion model. By measuring the B/C ratio and radioactive cosmic-ray clocks, we calculate their probability density functions, placing special emphasis on the halo size L of the Galaxy and the local underdense bubble of size rh. We also derive the mean, best-fit model parameters and 68% confidence level for the various parameters, and the envelopes of other quantities. Methods. The analysis relies on the USINE code for propagation and on a Markov Chain Monte Carlo Technique previously developed by ourselves for the parameter determination. Results. The B/C analysis leads to a most probable diffusion slope δ = 0.86 +0.04
-
A Markov Chain Monte Carlo Technique to sample transport and source parameters of Galactic cosmic rays: II. Results for the diffusion model combining B/C and radioactive nuclei
Astronomy and Astrophysics - A&A, 2010Co-Authors: A. Putze, L. Derome, D. MaurinAbstract:On-going measurements of the cosmic radiation (nuclear, electronic, and gamma-ray) are shedding new light on cosmic-ray physics. A comprehensive picture of these data relies on an accurate determination of the transport and source parameters of propagation models. A Markov Chain Monte Carlo is used to obtain these parameters in a diffusion model. From the measurement of the B/C ratio and radioactive cosmic-ray clocks, we calculate their probability density functions, with a special emphasis on the halo size L of the Galaxy and the local underdense bubble of size r_h. The analysis relies on the USINE code for propagation and on a Markov Chain Monte Carlo Technique (Putze et al. 2009, paper I of this series) for the parameter determination. As found in previous studies, the B/C best-fit model favours diffusion/convection/reacceleration (Model III) over diffusion/reacceleration (Model II). A combined fit on B/C and the isotopic ratios (10Be/9Be, 26Al/27Al, 36Cl/Cl) leads to L ~ 8 kpc and r_h ~ 120 pc for the best-fit Model III. This value for r_h is consistent with direct measurements of the local interstallar medium. For Model II, L ~ 4 kpc and r_h is consistent with zero. We showed the potential and usefulness of the Markov Chain Monte Carlo Technique in the analysis of cosmic-ray measurements in diffusion models. The size of the diffusive halo depends crucially on the value of the diffusion slope delta, and also on the presence/absence of the local underdensity damping effect on radioactive nuclei. More precise data from on-going experiments are expected to clarify this issue.
Iain D. Boyd - One of the best experts on this subject based on the ideXlab platform.
-
computation of hypersonic flows using the direct simulation Monte Carlo method
Journal of Spacecraft and Rockets, 2015Co-Authors: Iain D. BoydAbstract:The direct simulation Monte Carlo method has evolved over 50 years into a powerful numerical Technique for the computation of complex, nonequilibrium gas flows. In this context, “nonequilibrium” means that the velocity distribution function is not in an equilibrium form due to a low number of intermolecular collisions within a fluid element. In hypersonic flow, nonequilibrium conditions occur at high altitude and in regions of flowfields with small length scales. In this paper, the theoretical basis of the direct simulation Monte Carlo Technique is discussed. In addition, the methods used in direct simulation Monte Carlo are described for simulation of high-temperature, real gas effects and gas–surface interactions. Several examples of the application of direct simulation Monte Carlo to flows around blunt hypersonic vehicles are presented to illustrate current capabilities. Areas are highlighted where further research on the direct simulation Monte Carlo Technique is required.
-
statistical error analysis for the direct simulation Monte Carlo Technique
Journal of Computational Physics, 1996Co-Authors: Gang Chen, Iain D. BoydAbstract:The statistical error associated with the direct simulation Monte Carlo Technique is studied when it is applied to nonequilibrium hypersonic and nozzle flows. A root mean square (rms) error is employed as an indicator of the level of the statistical fluctuations. The effects of number of particles per cell and sample size are analyzed and quantified. It is found that in order to adequately model the physics of interest, the number of particles in the simulation must be greater than a certain minimum. An equation is developed to model and analyze the rms errors. A range is provided of the appropriate number of particles to be employed in the simulation in order to achieve the smallest statistical error at a fixed computational cost. Values are also recommended for the maximum number of sampling time steps to be used for efficient computation on memory limited computers. The effects of collision model and of cloning particles on the statistical scatter are analyzed.
David R Reichman - One of the best experts on this subject based on the ideXlab platform.
-
numerically exact long time magnetization dynamics at the nonequilibrium kondo crossover of the anderson impurity model
Physical Review B, 2013Co-Authors: Guy Cohen, David R Reichman, Emanuel Gull, A J Millis, Eran RabaniAbstract:We investigate the dynamical and steady-state spin response of the nonequilibrium Anderson model to magnetic fields, bias voltage, and temperature using a numerically exact method combining a bold-line quantum Monte Carlo Technique with the memory function formalism. We obtain converged results in a range of previously inaccessible regimes, in particular the crossover to the Kondo domain. We provide detailed predictions for novel nonequilibrium phenomena, including non-monotonic temperature dependence of observables at high bias voltage and oscillatory quench dynamics at high magnetic fields.
-
finite temperature auxiliary field quantum Monte Carlo Technique for bose fermi mixtures
Physical Review A, 2012Co-Authors: Brenda M Rubenstein, Shiwei Zhang, David R ReichmanAbstract:We present a quantum Monte Carlo (QMC) Technique for calculating the exact finite-temperature properties of Bose-Fermi mixtures. The Bose-Fermi auxiliary-field quantum Monte Carlo (BFAFQMC) algorithm combines two methods, a finite-temperature AFQMC algorithm for bosons and a variant of the standard AFQMC algorithm for fermions, into one algorithm for mixtures. We demonstrate the accuracy of our method by comparing its results for the Bose-Hubbard and Bose-Fermi-Hubbard models against those produced using exact diagonalization for small systems. Comparisons are also made with mean-field theory and the worm algorithm for larger systems. As is the case with most fermion Hamiltonians, a sign or phase problem is present in the BFAFQMC algorithm. We discuss the nature of these problems in this framework and describe how they can be controlled with well-studied approximations to expand the BFAFQMC algorithm's reach. This algorithm can serve as an essential tool for answering many unresolved questions about many-body physics in mixed Bose-Fermi systems.
L. Derome - One of the best experts on this subject based on the ideXlab platform.
-
a markov chain Monte Carlo Technique to sample transport and source parameters of galactic cosmic rays ii results for the diffusion model combining b c and radioactive nuclei
Astronomy and Astrophysics, 2010Co-Authors: A. Putze, L. Derome, D. MaurinAbstract:Context. Ongoing measurements of the cosmic radiation (nuclear, electronic, and γ-ray) are providing additional insight into cosmicray physics. A comprehensive picture of these data relies on an accurate determination of the transport and source parameters of propagation models. Aims. A Markov Chain Monte Carlo method is used to obtain these parameters in a diffusion model. By measuring the B/C ratio and radioactive cosmic-ray clocks, we calculate their probability density functions, placing special emphasis on the halo size L of the Galaxy and the local underdense bubble of size rh. We also derive the mean, best-fit model parameters and 68% confidence level for the various parameters, and the envelopes of other quantities. Methods. The analysis relies on the USINE code for propagation and on a Markov Chain Monte Carlo Technique previously developed by ourselves for the parameter determination. Results. The B/C analysis leads to a most probable diffusion slope δ = 0.86 +0.04
-
A Markov Chain Monte Carlo Technique to sample transport and source parameters of Galactic cosmic rays: II. Results for the diffusion model combining B/C and radioactive nuclei
Astronomy and Astrophysics - A&A, 2010Co-Authors: A. Putze, L. Derome, D. MaurinAbstract:On-going measurements of the cosmic radiation (nuclear, electronic, and gamma-ray) are shedding new light on cosmic-ray physics. A comprehensive picture of these data relies on an accurate determination of the transport and source parameters of propagation models. A Markov Chain Monte Carlo is used to obtain these parameters in a diffusion model. From the measurement of the B/C ratio and radioactive cosmic-ray clocks, we calculate their probability density functions, with a special emphasis on the halo size L of the Galaxy and the local underdense bubble of size r_h. The analysis relies on the USINE code for propagation and on a Markov Chain Monte Carlo Technique (Putze et al. 2009, paper I of this series) for the parameter determination. As found in previous studies, the B/C best-fit model favours diffusion/convection/reacceleration (Model III) over diffusion/reacceleration (Model II). A combined fit on B/C and the isotopic ratios (10Be/9Be, 26Al/27Al, 36Cl/Cl) leads to L ~ 8 kpc and r_h ~ 120 pc for the best-fit Model III. This value for r_h is consistent with direct measurements of the local interstallar medium. For Model II, L ~ 4 kpc and r_h is consistent with zero. We showed the potential and usefulness of the Markov Chain Monte Carlo Technique in the analysis of cosmic-ray measurements in diffusion models. The size of the diffusive halo depends crucially on the value of the diffusion slope delta, and also on the presence/absence of the local underdensity damping effect on radioactive nuclei. More precise data from on-going experiments are expected to clarify this issue.
