Evidence map›Paper›PMID 34593837›Full record

ArticleScientific reports2021

Verification method of Monte Carlo codes for transport processes with arbitrary accuracy.

Fabrizio Martelli, Federico Tommasi, Angelo Sassaroli, Lorenzo Fini, Stefano Cavalieri

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Anomalous Radiative Transfer in Heterogeneous Media.Advanced theory and simulations · 2024
    Article
  3. Article
  4. ACS photonics · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Fabrizio MartelliDipartimento di Fisica e Astronomia dell'Università degli Studi di Firenze, via Giovanni Sansone 1, 50019, Sesto Fiorentino, Italy. fabrizio.martelli@unifi.it.
Federico TommasiDipartimento di Fisica e Astronomia dell'Università degli Studi di Firenze, via Giovanni Sansone 1, 50019, Sesto Fiorentino, Italy.
Angelo SassaroliDepartment of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA, 02155, USA.
Lorenzo FiniDipartimento di Fisica e Astronomia dell'Università degli Studi di Firenze, via Giovanni Sansone 1, 50019, Sesto Fiorentino, Italy.
Stefano CavalieriDipartimento di Fisica e Astronomia dell'Università degli Studi di Firenze, via Giovanni Sansone 1, 50019, Sesto Fiorentino, Italy.

Funding

Coherent hemodynamics spectroscopy for cerebral autoregulation and blood flowR01NS095334 · NINDS · TUFTS UNIVERSITY MEDFORD · PI FANTINI, SERGIO · 2016 to 2020
$2.6M
NINDS NIH HHS R01 NS095334
6 · The paper itself

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.

Indexed as

AlgorithmsModels, TheoreticalMonte Carlo MethodHumans

Identifiers

PMID34593837
PMCPMC8484597

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.