Abstract: We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that forces the model to partially ignore high-gradients in the physical variables, achieved by introducing a suitable weighting function. The method relies on a set of hyperparameters that control how gradients are treated in the physical loss. The performance of our methodology is demonstrated by solving Riemann problems in special relativistic hydrodynamics, extending earlier studies with PINNs in the context of the classical Euler equations. The solutions obtained with the GA-PINN model correctly describe the propagation speeds of discontinuities and sharply capture the associated jumps. We use the relative l(2) error to compare our results with the exact solution of special relativistic Riemann problems, used as the reference ''ground truth'', and with the corresponding error obtained with a second-order, central, shock-capturing scheme. In all problems investigated, the accuracy reached by the GA-PINN model is comparable to that obtained with a shock-capturing scheme, achieving a performance superior to that of the baseline PINN algorithm in general. An additional benefit worth stressing is that our PINN-based approach sidesteps the costly recovery of the primitive variables from the state vector of conserved variables, a well-known drawback of grid-based solutions of the relativistic hydrodynamics equations. Due to its inherent generality and its ability to handle steep gradients, the GA-PINN methodology discussed in this paper could be a valuable tool to model relativistic flows in astrophysics and particle physics, characterized by the prevalence of discontinuous solutions.

Abstract: The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lya spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at .

Abstract: Beta-delayed neutron emission is important for nuclear structure and astrophysics as well as for reactor applications. Significant advances in nuclear experimental techniques in the past two decades have led to a wealth of new measurements that remain to be incorporated in the databases. We report on a coordinated effort to compile and evaluate all the available beta-delayed neutron emission data. The different measurement techniques have been assessed and the data have been compared with semi-microscopic and microscopic-macroscopic models. The new microscopic database has been tested against aggregate total delayed neutron yields, time-dependent group parameters in 6-and 8-group re-presentation, and aggregate delayed neutron spectra. New recommendations of macroscopic delayed-neutron data for fissile materials of interest to applications are also presented.

Abstract: PurposeA joint working group was created by the American Association of Physicists in Medicine (AAPM), the European Society for Radiotherapy and Oncology (ESTRO), and the Australasian Brachytherapy Group (ABG) with the charge, among others, to develop a set of well-defined test case plans and perform calculations and comparisons with model-based dose calculation algorithms (MBDCAs). Its main goal is to facilitate a smooth transition from the AAPM Task Group No. 43 (TG-43) dose calculation formalism, widely being used in clinical practice for brachytherapy, to the one proposed by Task Group No. 186 (TG-186) for MBDCAs. To do so, in this work a hypothetical, generic high-dose rate (HDR) Ir-192 shielded applicator has been designed and benchmarked. MethodsA generic HDR Ir-192 shielded applicator was designed based on three commercially available gynecological applicators as well as a virtual cubic water phantom that can be imported into any DICOM-RT compatible treatment planning system (TPS). The absorbed dose distribution around the applicator with the TG-186 Ir-192 source located at one dwell position at its center was computed using two commercial TPSs incorporating MBDCAs (Oncentra((R)) Brachy with Advanced Collapsed-cone Engine, ACE, and BrachyVision ACUROS) and state-of-the-art Monte Carlo (MC) codes, including ALGEBRA, BrachyDose, egs_brachy, Geant4, MCNP6, and Penelope2008. TPS-based volumetric dose distributions for the previously reported source centered in water and source displaced test cases, and the new source centered in applicator test case, were analyzed here using the MCNP6 dose distribution as a reference. Volumetric dose comparisons of TPS results against results for the other MC codes were also performed. Distributions of local and global dose difference ratios are reported. ResultsThe local dose differences among MC codes are comparable to the statistical uncertainties of the reference datasets for the source centered in water and source displaced test cases and for the clinically relevant part of the unshielded volume in the source centered in applicator case. Larger local differences appear in the shielded volume or at large distances. Considering clinically relevant regions, global dose differences are smaller than the local ones. The most disadvantageous case for the MBDCAs is the one including the shielded applicator. In this case, ACUROS agrees with MC within [-4.2%, +4.2%] for the majority of voxels (95%) while presenting dose differences within [-0.12%, +0.12%] of the dose at a clinically relevant reference point. For ACE, 95% of the total volume presents differences with respect to MC in the range [-1.7%, +0.4%] of the dose at the reference point. ConclusionsThe combination of the generic source and generic shielded applicator, together with the previously developed test cases and reference datasets (available in the Brachytherapy Source Registry), lay a solid foundation in supporting uniform commissioning procedures and direct comparisons among treatment planning systems for HDR Ir-192 brachytherapy.

Abstract: Purpose Monte Carlo (MC) simulation studies, aimed at evaluating the magnitude of tissue heterogeneity in I-125 prostate permanent seed implant brachytherapy (BT), customarily use clinical post-implant CT images to generate a virtual representation of a realistic patient model (virtual patient model). Metallic artifact reduction (MAR) techniques and tissue assignment schemes (TAS) are implemented on the post-implant CT images to mollify metallic artifacts due to BT seeds and to assign tissue types to the voxels corresponding to the bright seed spots and streaking artifacts, respectively. The objective of this study is to assess the combined influence of MAR and TAS on MC absorbed dose calculations in post-implant CT-based phantoms. The virtual patient models used for I-125 prostate implant MC absorbed dose calculations in this study are derived from the CT images of an external radiotherapy prostate patient without BT seeds and prostatic calcifications, thus averting the need to implement MAR and TAS. Methods The geometry of the IsoSeed I25.S17plus source is validated by comparing the MC calculated results of the TG-43 parameters for the line source approximation with the TG-43U1S2 consensus data. Four MC absorbed dose calculations are performed in two virtual patient models using the egs_brachy MC code: (1) TG-43-based D-w,w-TG(43), (2) D-w,D-w-MBDC that accounts for interseed scattering and attenuation (ISA), (3) D-m,D-m that examines ISA and tissue heterogeneity by scoring absorbed dose in tissue, and (4) D-w,D-m that unlike D-m,D-m scores absorbed dose in water. The MC absorbed doses (1) and (2) are simulated in a TG-43 patient phantom derived by assigning the densities of every voxel to 1.00 g cm(-3) (water), whereas MC absorbed doses (3) and (4) are scored in the TG-186 patient phantom generated by mapping the mass density of each voxel to tissue according to a CT calibration curve. The MC absorbed doses calculated in this study are compared with VariSeed v8.0 calculated absorbed doses. To evaluate the dosimetric effect of MAR and TAS, the MC absorbed doses of this work (independent of MAR and TAS) are compared to the MC absorbed doses of different I-125 source models from previous studies that were calculated with different MC codes using post-implant CT-based phantoms generated by implementing MAR and TAS on post-implant CT images. Results The very good agreement of TG-43 parameters of this study and the published consensus data within 3% validates the geometry of the IsoSeed I25.S17plus source. For the clinical studies, the TG-43-based calculations show a D-90 overestimation of more than 4% compared to the more realistic MC methods due to ISA and tissue composition. The results of this work generally show few discrepancies with the post-implant CT-based dosimetry studies with respect to the D-90 absorbed dose metric parameter. These discrepancies are mainly Type B uncertainties due to the different I-125 source models and MC codes. Conclusions The implementation of MAR and TAS on post-implant CT images have no dosimetric effect on the I-125 prostate MC absorbed dose calculation in post-implant CT-based phantoms.