Abstract: We attempt to clarify several aspects concerning the recently presented four-dimensional Einstein-Gauss-Bonnet gravity. We argue that the limiting procedure outlined in [Phys. Rev. Lett. 124, 081301 (2020)] generally involves ill-defined terms in the four dimensional field equations. Potential ways to circumvent this issue are discussed, alongside remarks regarding specific solutions of the theory. We prove that, although linear perturbations are well behaved around maximally symmetric backgrounds, the equations for second-order perturbations are ill-defined even around a Minkowskian background. Additionally, we perform a detailed analysis of the spherically symmetric solutions and find that the central curvature singularity can be reached within a finite proper time.

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.

Abstract: We introduce FlexibleSUSY, a Mathematica and C++ package, which generates a fast, precise C++ spectrum generator for any SUSY model specified by the user. The generated code is designed with both speed and modularity in mind, making it easy to adapt and extend with new features. The model is specified by supplying the superpotential, gauge structure and particle content in a SARAH model file; specific boundary conditions e.g. at the GUT, weak or intermediate scales are defined in a separate FlexibleSUSY model file. From these model files, FlexibleSUSY generates C++ code for self-energies, tadpole corrections, renormalization group equations (RGEs) and electroweak symmetry breaking (EWSB) conditions and combines them with numerical routines for solving the RGEs and EWSB conditions simultaneously. The resulting spectrum generator is then able to solve for the spectrum of the model, including loop-corrected pole masses, consistent with user specified boundary conditions. The modular structure of the generated code allows for individual components to be replaced with an alternative if available. FlexibleSUSY has been carefully designed to grow as alternative solvers and calculators are added. Predefined models include the MSSM, NMSSM, E6SSM, USSM, R-symmetric models and models with right-handed neutrinos. Program Summary Program title: FlexibleSUSY Catalogue identifier: AEVIv10 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEVIv10.html obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 129406 No. of bytes in distributed program, including test data, etc.: 854831 Distribution format: tar.gz Programming language: C++, Wolfram/Mathematica, FORTRAN, Bourne shell. Computer: Personal computer. Operating system: Tested on Linux 3.x, Mac OS X. Classification: 11.1, 11.6, 6.5. External routines: SARAH 4.0.4, Boost library, Eigen, LAPACK Nature of problem: Determining the mass spectrum and mixings for any supersymmetric model. The generated code must find simultaneous solutions to constraints which are specified at two or more different renormalization scales, which are connected by renormalization group equations forming a large set of coupled first-order differential equations. Solution method: Nested iterative algorithm and numerical minimization of the Higgs potential. Restrictions: The couplings must remain perturbative at all scales between the highest and the lowest boundary condition. FlexibleSUSY assumes that all couplings of the model are real (i.e. CP-conserving). Due to the modular nature of the generated code, adaption and extension to overcome restrictions in scope is quite straightforward. Running time: 0.06-0.2 seconds per parameter point.