MO-E-AUD B-04: Fast, Accurate Photon Beam Accelerator Modeling Using BEAMnrc and VMC++: A Systematic Investigation of Variance Reduction and Efficiency Enhancing Methods and Cross-Section Data
Bibliographic record
Abstract
Purpose: To report on the accuracy of cross-section data in BEAMnrc and on the performance of variance reduction and efficiency enhancing techniques for fast, accurate linac simulations using the BEAMnrc and VMC++ code systems. Method and Materials: BEAMnrc and VMC++ were used to simulate a 6 MV photon beam from a Siemens Primus linac. Phase space (PHSP) files were generated for a range of field sizes, from 10×10 to 40×40 cm2. BEAMnrc parameters under investigation were grouped by: i) photon and bremsstrahlung cross-sections; ii) approximate efficiency improving techniques (AEIT); iii) variance reduction techniques (VRT); iv) VRT (bremsstrahlung splitting) with AEIT (range rejection). Efficiencies were obtained for the mean energy, fluence, angular and spectral distributions and PHSP files were subsequently used as input for DOSXYZnrc-based phantom dose calculations; these calculations were verified against measurements. Results: Efficiencies were calculated for the various VRT/AEIT combinations in BEAMnrc, relative to simulations without VRT/AEIT, namely: (a) 935 (∼111 min. on a single 2.6 GHz CPU) and 200 for 10×10 and 40×40 resp. using directional bremsstrahlung splitting (DBS) and no electron splitting, (b) 420 and 175 for 10×10 and 40×40 resp. using DBS and electron splitting combined with augmented range rejection, a technique recently introduced in BEAMnrc. Calculations with VMC++ produced efficiencies of 1400 (∼6 min. on a single CPU) for 10×10 versus BEAMnrc (no VRT/AEIT). Noteworthy differences (±1–3%) were observed with the NIST bremsstrahlung cross-sections compared with those of Bethe-Heitler (default). However, MC calculated dose distributions (using all combinations of VRT/AEIT and cross-section data) agreed within 2%/2 mm of measurements. Conclusion: VRT/AEIT related to DBS significantly improves the efficiency of BEAMnrc PHSP simulations. VMC++ can be used to perform simulations of the entire linac and phantom within minutes on a single processor. Further investigation of bremsstrahlung cross-section data is warranted. Acknowledgement: NIH-R01CA106770.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".