A Monte Carlo Primer

Dupree, S.A.; Fraley, Stanley K.

doi:10.1007/978-1-4419-8491-3

Cited by 48 publications

(33 citation statements)

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“…However, the probability of an individual packet escaping by chance towards a particular direction can be incredibly small, depending on the geometric properties of the simulation, and can produce noisy results if not enough Monte Carlo packets are simulated (e.g. see Dupree & Fraley 2002). Therefore, variance reduction techniques were developed for MCRT, which allows for a much improved signal to noise and greater computational efficiency than the basic scheme.…”

Section: Mcrt Variance Reduction Techniquesmentioning

confidence: 99%

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Dynamic mineral clouds on HD 189733b

Lee

Wood

Dobbs-Dixon

et al. 2017

A&A

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Context. As the 3D spatial properties of exoplanet atmospheres are being observed in increasing detail by current and new generations of telescopes, the modelling of the 3D scattering effects of cloud forming atmospheres with inhomogeneous opacity structures becomes increasingly important to interpret observational data. Aims. We model the scattering and emission properties of a simulated cloud forming, inhomogeneous opacity, hot Jupiter atmosphere of HD 189733b. We compare our results to available Hubble Space Telescope (HST) and Spitzer data and quantify the effects of 3D multiple scattering on observable properties of the atmosphere. We discuss potential observational properties of HD 189733b for the upcoming Transiting Exoplanet Survey Satellite (TESS) and CHaracterising ExOPlanet Satellite (CHEOPS) missions. Methods. We developed a Monte Carlo radiative transfer code and applied it to post-process output of our 3D radiative-hydrodynamic, cloud formation simulation of HD 189733b. We employed three variance reduction techniques, i.e. next event estimation, survival biasing, and composite emission biasing, to improve signal to noise of the output. For cloud particle scattering events, we constructed a log-normal area distribution from the 3D cloud formation radiative-hydrodynamic results, which is stochastically sampled in order to model the Rayleigh and Mie scattering behaviour of a mixture of grain sizes. Results. Stellar photon packets incident on the eastern dayside hemisphere show predominantly Rayleigh, single-scattering behaviour, while multiple scattering occurs on the western hemisphere. Combined scattered and thermal emitted light predictions are consistent with published HST and Spitzer secondary transit observations. Our model predictions are also consistent with geometric albedo constraints from optical wavelength ground-based polarimetry and HST B band measurements. We predict an apparent geometric albedo for HD 189733b of 0.205 and 0.229, in the TESS and CHEOPS photometric bands respectively. Conclusions. Modelling the 3D geometric scattering effects of clouds on observables of exoplanet atmospheres provides an important contribution to the attempt to determine the cloud properties of these objects. Comparisons between TESS and CHEOPS photometry may provide qualitative information on the cloud properties of nearby hot Jupiter exoplanets.

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Section: Mcrt Variance Reduction Techniquesmentioning

confidence: 99%

“…Dupree & Fraley 2002) is applied to stochastically terminate packets below a predefined weight cut-off. The packet is then given a 1 in 10 chance of surviving, with the new weight of the surviving packets W new = 10 · W. In our model, packets with weight W < 10 −3 are entered into the Russian Roulette scheme.…”

Section: Survival Biasingmentioning

confidence: 99%

Dynamic mineral clouds on HD 189733b

Lee

Wood

Dobbs-Dixon

et al. 2017

A&A

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“…It is the same approximation as the prompt jump approximation or zero lifetime approximation. 7) 4. Governing Equations of the Kinetics of Subcritical Assembly At the time t and position r, the flux È Èðr; ; E; tÞ of the neutron with the energy E and moving in the direction and the j-th delayed neutron precursor density C j C j ðr; tÞ satisfy the following balance equations.…”

Section: Neutron Static Approximationmentioning

confidence: 99%

“…Then in the Monte Carlo calculation, 7) we can choose x with the proper probability distribution function in the following way. At first we choose a random number $ where 0 $ 1, and substitute it for FðxÞ in Eq.…”

Section: Difficulty Of Neutron Random Walk In Changing Mediummentioning

confidence: 99%

“…However, after the random walk is continued for a long enough time, flux ampli- tude decreases sufficiently and the relative flux distribution is considered to converge to its fundamental mode and its dumping factor (the ratio of the neutron flux amplitudes between successive neutron cycles) converges to a constant which is equal to the neutron multiplication factor of this system without a neutron source. The flux distribution for Table 2 Nuclear data of delayed neutron precursors for U-235 fast reactor fission [7][8][9][10][11] (a) Nuclear data of delayed neutron precursors (Br-Cs)…”

Section: Initial Steady Statementioning

confidence: 99%

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Application of Monte Carlo Method to Solve the Neutron Kinetics Equation for a Subcritical Assembly

Iwanaga

Sekimoto

Mori

2008

Journal of Nuclear Science and Technology

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There is a need to understand the space-dependent kinetics of fast or thermal reactor physics and the Monte Carlo method should be implemented in kinetics codes as well. In a transient accident (for example, control rod ejection accident or loss of coolant accident), changes in the system are much slower than the prompt neutron lifetime. In the present paper, a method is proposed in which the Monte Carlo method is used to solve the neutron kinetics of reactors, such as the case of a subcritical static reactor with an external neutron source. In the proposed method the time derivative of the neutron equation is set to zero, though the time derivative of the delayed neutron precursor equation is treated without any approximation in the time differentiation of delayed neutron precursor equation. Most kinetics calculation methods originate from the point kinetics method, and they require calculation of excess reactivity at each time step, but the present method does not need calculation of excess reactivity. The neutron counts measured with small fission chambers in the subcritical kinetics experiment using the JAEA fast critical assembly are compared with counts calculated by the proposed method and compared with the measured values. The agreement is good, and the excellent performance of the method for space-dependent neutron kinetics is shown.

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Efficiency Calculation of Gamma Detectors byMonteCarlo Methods

Sima

2012

Encyclopedia of Analytical Chemistry

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γ‐Ray spectrometry is a powerful nondestructive multielemental analysis technique. Its quantitative application requires efficiency calibration. Among the methods available for the computation of the efficiency calibration curve, Monte Carlo simulation is ever increasing in popularity. The need for Monte Carlo simulation is the consequence of the inability of experimental calibration to cope with the broader scope and measuring configurations (shape, volume, and matrices of the samples), with the enhanced coincidence‐summing nuclide specific effects (favored by the current tendency to use high‐efficiency detectors) and with the desired performance parameters (detection limit and uncertainty) met in present‐day applications of γ‐ray spectrometry. The availability of a variety of Monte Carlo packages that can be applied to efficiency computation, several of them user friendly indeed, enlarged the class of potential users of this method. While experimental calibration remains the preferred method in the case of point sources and specific volume sources, such as solutions, it is the flexibility of Monte Carlo calculation that can provide a comprehensive calibration of γ‐ray detectors for a broad range of applications. In this article, the principles of Monte Carlo method are introduced, the applications to detector simulation are presented, and the solutions of typical problems in the calibration of γ‐spectrometry systems are reviewed.

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A Monte Carlo Primer

Cited by 48 publications

References 0 publications

Dynamic mineral clouds on HD 189733b

Dynamic mineral clouds on HD 189733b

Application of Monte Carlo Method to Solve the Neutron Kinetics Equation for a Subcritical Assembly

Efficiency Calculation of Gamma Detectors byMonteCarlo Methods

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