Catumba, G., Ramos, A., & Zaldivar, B. (2025). Stochastic automatic differentiation for Monte Carlo processes. Comput. Phys. Commun., 307, 109396–13pp.
Abstract: Monte Carlo methods represent a cornerstone of computer science. They allow sampling high dimensional distribution functions in an efficient way. In this paper we consider the extension of Automatic Differentiation (AD) techniques to Monte Carlo processes, addressing the problem of obtaining derivatives (and in general, the Taylor series) of expectation values. Borrowing ideas from the lattice field theory community, we examine two approaches. One is based on reweighting while the other represents an extension of the Hamiltonian approach typically used by the Hybrid Monte Carlo (HMC) and similar algorithms. We show that the Hamiltonian approach can be understood as a change of variables of the reweighting approach, resulting in much reduced variances of the coefficients of the Taylor series. This work opens the door to finding other variance reduction techniques for derivatives of expectation values.
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Langer, C., Algora, A., Couture, A., Csatlos, M., Gulyas, J., Heil, M., et al. (2011). Simulations and developments of the Low Energy Neutron detector Array LENA. Nucl. Instrum. Methods Phys. Res. A, 659(1), 411–418.
Abstract: Prototypes of the Low Energy Neutron detector Array (LENA) have been tested and compared with detailed GEANT simulations. LENA will consist of plastic scintillation bars with the dimensions 1000 x 45 x 10 mm(3). The tests have been performed with gamma-ray sources and neutrons originating from the neutron-induced fission of (235)U. The simulations agreed very well with the measured response and were therefore used to simulate the response to mono-energetic neutrons with different detection thresholds. LENA will be used to detect low-energy neutrons from (p,n)-type reactions with low momentum transfer foreseen at the R(3)B and EXL setups at FAIR, Darmstadt.
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Martin-Luna, P., Esperante, D., Prieto, A. F., Fuster-Martinez, N., Rivas, I. G., Gimeno, B., et al. (2024). Simulation of electron transport and secondary emission in a photomultiplier tube and validation. Sens. Actuator A-Phys., 365, 114859–10pp.
Abstract: The electron amplification and transport within a photomultiplier tube (PMT) has been investigated by developing an in-house Monte Carlo simulation code. The secondary electron emission in the dynodes is implemented via an effective electron model and the Modified Vaughan's model, whereas the transport is computed with the Boris leapfrog algorithm. The PMT gain, rise time and transit time have been studied as a function of supply voltage and external magnetostatic field. A good agreement with experimental measurements using a Hamamatsu R13408-100 PMT was obtained. The simulations have been conducted following different treatments of the underlying geometry: three-dimensional, two-dimensional and intermediate (2.5D). The validity of these approaches is compared. The developed framework will help in understanding the behavior of PMTs under highly intense and irregular illumination or varying external magnetic fields, as in the case of prompt gamma-ray measurements during pencil-beam proton therapy; and aid in optimizing the design of voltage dividers with behavioral circuit models.
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Migueis, F., Casaña, J. V., Garcia-Fernandez, D., Hueso-Gonzalez, F., Llosa, G., Prieto, A. F., et al. (2025). Sensitivity of coaxial prompt gamma-ray monitoring in heterogeneous geometries: A Monte Carlo simulation study. Radiat. Phys. Chem., 232, 112639–11pp.
Abstract: Proton beams offer significant advantages over conventional radiotherapy due to their unique interaction with matter. Specifically, the ionization density caused by these beams is higher in a well-defined region (the Bragg peak) with a sharp decline in intensity beyond a specific depth. However, variations in proton range – often caused by changes in patient anatomy and morphology during treatment – can introduce uncertainties in dose distribution. To account for this, clinicians apply conservative margins, which limit the full potential of proton therapy. Efforts have been focused on developing proton range and dose distribution monitoring systems to reduce the need for large safety margins. These systems are based on detecting and analyzing the byproducts that result from the interaction between the proton beams and tissue. In this article, we focused specifically on a system that aims to detect photons called prompt gamma (PG) rays. We conducted Monte Carlo simulations of proton beams interacting with anthropomorphic phantoms of varying densities to simulate morphological changes. A single scintillation detector was positioned coaxially with the beam and behind the phantom to capture the emitted PG rays in each scenario. Our analysis focused on discrepancies in proton range that resulted from irradiating an anthropomorphic head phantom with varying brain tissue densities and detecting secondary particles resulting from these interactions. We observed potential correlations between gamma-ray signatures and variations in proton range and energy deposition, suggesting that this monitoring technique could be effective for real-world clinical applications.
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Mansour, I. R., Valdes-Cortez, C., Ayala Alvarez, D. S., Berumen, F., Côte, J. S., Ndoutoume-Paquet, G., et al. (2025). Reference datasets for commissioning of model-based dose calculation algorithms for electronic brachytherapy. Med. Phys., , 11pp.
Abstract: PurposeThis work provides the first two clinical test cases for commissioning electronic brachytherapy (eBT) model-based dose calculation algorithms (MBDCAs) for skin irradiation using surface applicators.Acquisition and Validation MethodsThe test cases utilize the INTRABEAM 30 mm surface applicator. Test Case I: water phantom is used to evaluate the algorithm's performance in a uniform medium consisting of a voxelized water cube surrounded by air. Test Case II: Surface eBT represents a heterogeneous medium with four distinct layers: skin tissue, adipose tissue, cortical bone, and soft tissue. Treatment plans for both cases were created and exported into the Radiance treatment planning system (TPS). Dose-to-medium calculations were then performed using this Monte Carlo (MC)-based TPS and compared with MC simulations conducted independently by three different groups using two codes: EGSnrc and PENELOPE. The results agreed within expected Type A and B statistical uncertainties.Data Format and Usage NotesThe dataset is available online at https://doi.org/10.52519/00005. A proprietary file designed for use within Radiance containing CT images and the treatment plan for both test cases, the LINAC modeling, and the CT calibration are included, as well as reference MC and TPS dose data in RTdose format and all files required to run the MC simulations.Potential ApplicationsThis dataset serves as a valuable resource for commissioning eBT MBDCAs and lays the groundwork for developing clinical test cases for other eBT systems. It is also a helpful educational tool for exploring various eBT devices and their advantages and drawbacks. Furthermore, brachytherapy researchers seeking a benchmark for dosimetric calculations in the low-energy domain will find this dataset indispensable.
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