ArticleScientific reports2021
Verification method of Monte Carlo codes for transport processes with arbitrary accuracy.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Comparative Review of the SWEET Simulator: Theoretical Verification Against Other Simulators.Journal of imaging · 2024Article
- Anomalous Radiative Transfer in Heterogeneous Media.Advanced theory and simulations · 2024Article
- Application limits of the scaling relations for Monte Carlo simulations in diffuse optics. Part 2: results.Optics express · 2024Article
- Article
- Fluence rate directly derived from photon pathlengths: a tool for Monte Carlo simulations in biomedical optics.Biomedical optics express · 2023Article
- On the mean path length invariance property for random walks of animals in open environment.Scientific reports · 2022Article
- Efficient computation of the steady-state and time-domain solutions of the photon diffusion equation in layered turbid media.Scientific reports · 2022Article
- Experimental imaging and Monte Carlo modeling of ultrafast pulse propagation in thin scattering slabs.Journal of biomedical optics · 2022Article
- Two-step verification method for Monte Carlo codes in biomedical optics applications.Journal of biomedical optics · 2022Article
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5 authors.
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Abstract
In this work, we present a robust and powerful method for the verification, with arbitrary accuracy, of Monte Carlo codes for simulating random walks in complex media. Such random walks are typical of photon propagation in turbid media, scattering of particles, i.e., neutrons in a nuclear reactor or animal/humans' migration. Among the numerous applications, Monte Carlo method is also considered a gold standard for numerically "solving" the scalar radiative transport equation even in complex geometries and distributions of the optical properties. In this work, we apply the verification method to a Monte Carlo code which is a forward problem solver extensively used for typical applications in the field of tissue optics. The method is based on the well-known law of average path length invariance when the entrance of the entities/particles in a medium obeys to a simple cosine law, i.e., Lambertian entrance, and annihilation of particles inside the medium is absent. By using this law we achieve two important points: (1) the invariance of the average path length guarantees that the expected value is known regardless of the complexity of the medium; (2) the accuracy of a Monte Carlo code can be assessed by simple statistical tests. We will show that we can reach an arbitrary accuracy of the estimated average pathlength as the number of simulated trajectories increases. The method can be applied in complete generality versus the scattering and geometrical properties of the medium, as well as in presence of refractive index mismatches in the optical case. In particular, this verification method is reliable to detect inaccuracies in the treatment of boundaries of finite media. The results presented in this paper, obtained by a standard computer machine, show a verification of our Monte Carlo code up to the sixth decimal digit. We discuss how this method can provide a fundamental tool for the verification of Monte Carlo codes in the geometry of interest, without resorting to simpler geometries and uniform distribution of the scattering properties.
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