Monte Carlo Model of Reflection Nebulae: Intensity Gradients

Roark, T. P.; Roark, B. B.; Collins, Gilbert

doi:10.1086/152847

Cited by 8 publications

(7 citation statements)

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“…However, this would only be accurate for optically thin nebulae. Roark et al (1974) have shown, through the use of Monte Carlo methods, that multiple scattering can have a significant effect on the observed surface brightness distribution. The intrinsic random nature and statistical approach to the scattering process has allowed for radiative transfer models of dusty nebulae to be constructed, including some with arbitrary dust density and source distributions (Witt 1977;Yusef-Zadeh, Morris, & White 1984;Wood and Reynolds 1999;Gordon et al 2001).…”

Section: Monte Carlo Model Fittingmentioning

confidence: 99%

Rocket Observations of Far‐Ultraviolet Dust Scattering in NGC 2023

Burgh

McCandliss

Feldman

2002

ApJ

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The reflection nebula NGC 2023 was observed by a rocket-borne long-slit imaging spectrograph in the 900 -1400Å bandpass on 2000 February 11. A spectrum of the star, as well as that of the nebular scattered light, was recorded. Through the use of a Monte Carlo modeling process, the scattering properties of the dust were derived. The albedo is low, 0.2 -0.4, and decreasing toward shorter wavelengths, while the phase function asymmetry parameter is consistent with highly forward-scattering grains, g ∼ 0.85. The decrease in albedo, while the optical depth increases to shorter wavelengths, implies that the far-UV rise in the extinction curve is due to an increase in absorption efficiency.

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Section: Monte Carlo Model Fittingmentioning

confidence: 99%

Rocket Observations of Far‐Ultraviolet Dust Scattering in NGC 2023

Burgh

McCandliss

Feldman

2002

ApJ

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“…For a general overview of MC methods as a tool for transport problems, see, e.g., Dupree & Fraley (2002), Kalos & Whitlock (2009) orWhitney (2011). Its application to dust RT problems in an astrophysical context has a history of more than 40 years (see, e.g., Mattila 1970, Roark, Roark & Collins 1974, Witt 1977, Witt & Stephens 1974. In the past four decades, it has become a mainstream method for 3D dust RT calculations.…”

Section: The Monte Carlo Solution Methodsmentioning

confidence: 99%

Three-Dimensional Dust Radiative Transfer

Steinacker

Baes

Gordon

2013

Annu. Rev. Astron. Astrophys.

184

190

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Cosmic dust is present in many astrophysical objects, and recent observations across the electromagnetic spectrum show that the dust distribution is often strongly three-dimensional (3D). Dust grains are effective in absorbing and scattering ultraviolet (UV)/optical radiation, and they re-emit the absorbed energy at infrared wavelengths. Understanding the intrinsic properties of these objects, including the dust itself, therefore requires 3D dust radiative transfer (RT) calculations. Unfortunately, the 3D dust RT problem is nonlocal and nonlinear, which makes it one of the hardest challenges in computational astrophysics. Nevertheless, significant progress has been made in the past decade, with an increasing number of codes capable of dealing with the complete 3D dust RT problem. We discuss the complexity of this problem, the two most successful solution techniques [ray-tracing (RayT) and Monte Carlo (MC)], and the state of the art in modeling observational data using 3D dust RT codes. We end with an outlook on the bright future of this field.Comment: 41 pages, 7 figures, Annual Reviews of Astronomy and Astrophysics, volume 51 (in press

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“…The now most commonly used technique, the Monte Carlo (MC) method, was introduced in dust radiative transfer around the 1970s (e.g. Mattila 1970;Roark et al 1974;Witt and Stephens 1974;Witt 1977;Witt and Oshel 1977). Over the past decennia, the technique has been significantly refined and improved with additional acceleration mechanisms, including the peeloff method (Yusef-Zadeh et al 1984), continuous absorption (Lucy 1999;Niccolini et al 2003), forced scattering (Cashwell and Everett 1959), instantaneous dust emission (Bjorkman and Wood 2001;Baes et al 2005;Pinte et al 2006), the library mechanism for dust emissivities (Juvela and Padoan 2003;Baes et al 2011), the diffusion approximation for high optical depths (Min et al 2009;Robitaille 2010) and variants of the photon packet splitting technique (Cashwell and Everett 1959;Jonsson 2006;Harries 2015).…”

Section: Introductionmentioning

confidence: 99%

SKIRT: Hybrid parallelization of radiative transfer simulations

Verstocken

Putte

Camps

et al. 2017

Astronomy and Computing

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We describe the design, implementation and performance of the new hybrid parallelization scheme in our Monte Carlo radiative transfer code SKIRT, which has been used extensively for modeling the continuum radiation of dusty astrophysical systems including late-type galaxies and dusty tori. The hybrid scheme combines distributed memory parallelization, using the standard Message Passing Interface (MPI) to communicate between processes, and shared memory parallelization, providing multiple execution threads within each process to avoid duplication of data structures. The synchronization between multiple threads is accomplished through atomic operations without high-level locking (also called lock-free programming). This improves the scaling behavior of the code and substantially simplifies the implementation of the hybrid scheme. The result is an extremely flexible solution that adjusts to the number of available nodes, processors and memory, and consequently performs well on a wide variety of computing architectures.

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Monte Carlo Model of Reflection Nebulae: Intensity Gradients

Cited by 8 publications

References 0 publications

Rocket Observations of Far‐Ultraviolet Dust Scattering in NGC 2023

Rocket Observations of Far‐Ultraviolet Dust Scattering in NGC 2023

Three-Dimensional Dust Radiative Transfer

SKIRT: Hybrid parallelization of radiative transfer simulations

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