CNF:Monte Carlo Event Generator using a Tessellation: Difference between revisions
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# Generate randomly uniform points inside a cell using: ✔ | # Generate randomly uniform points inside a cell using: ✔ | ||
## [https://www.researchgate.net/publication/275348534_Picking_a_Uniformly_Random_Point_from_an_Arbitrary_Simplex Picking a Uniformly Random Point from an Arbitrary Simplex] | ## [https://www.researchgate.net/publication/275348534_Picking_a_Uniformly_Random_Point_from_an_Arbitrary_Simplex Picking a Uniformly Random Point from an Arbitrary Simplex] | ||
== Spring 2021 == | |||
# Use meshes with double precision weights array ✔ | |||
= References = | = References = | ||
[https://github.com/gavalian/clas12ai/blob/add-crtc-ml/cnf/main.cc Gagik's MC kernel] | [https://github.com/gavalian/clas12ai/blob/add-crtc-ml/cnf/main.cc Gagik's MC kernel] | ||
Latest revision as of 11:07, 13 April 2021
Repository
Documentation
Summer 2020
- Add README.md file ✔
Code
Summer 2020
- Organize Gagik's code ✔
- Add command-line interface ✔
- Template code for 2-3 dimensions using:
- Replace linear search (O(n)) of tetrahedrons with given weight threshold with binary search (O(log(n))) ✔
- Parallelize code using OpenMP ✔
Fall 2020
- Use Lebesque integral ✔
- Incorporate Smart Look-up table utilities ✔
- Extend Monte Carlo Event Generation to work with negative values ✔
- Generate randomly uniform points inside a cell using: ✔
Spring 2021
- Use meshes with double precision weights array ✔