WE‐F‐105‐02: Fano Cavity Test of the Monte Carlo Codes GEANT4 and PENH for Proton Transport
Bibliographic record
Abstract
Purpose: In the scope of reference dosimetry of radiotherapy beams, Monte Carlo (MC) simulations are widely used to compute ionization chamber dose response accurately. Uncertainties related to the transport algorithm can be verified performing self‐consistency tests, e.g. the so‐called Fano cavity test. The Fano cavity test is based on the Fano theorem, which states that under charged particle equilibrium (CPE) conditions, the charged particle fluence is independent of the mass density of the media as long as the cross‐sections are uniform. Such tests have not been performed yet for MC codes simulating proton transport. The objectives of this communication are 1) presenting a new methodology for Fano cavity test of MC codes for protons and other charged particles; 2) applying the methodology for two MC codes: GEANT4 and PENELOPE extended to protons (PENH). Methods: The geometry considered is a 10×10 cm2 parallel virtual field and a cavity (2×2×0.2 mm3) in a water phantom with dimensions large enough to ensure CPE. Virtual particles of energy E and attenuation coefficient μ are transported. During each interaction, the virtual particle triggers a proton with kinetic energy E and is then regenerated. Assuming no nuclear reactions and no generation of other secondaries, we theoretically demonstrate that the computed cavity dose should equal μE/ρ times the incident fluence. Simulations satisfying those assumptions were implemented in GEANT4 and PENH. Results: For conservative user‐inputs (small step sizes), both GEANT4 and PENH pass the FANO cavity test within 0.1%. However, differences of 0.6% were observed for PENH using larger step sizes. The difference was attributed to the random‐hinge method that introduces an artificial energy straggling if step size is not small enough. Conclusion: Using safe user‐inputs, both PENH and GEANT4 pass the Fano cavity test for proton transport. Our methodology is valid for any type of charged particle. Jefferson Sorriaux is sponsored by a public‐private partnership IBA ‐ Region Wallonne
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".