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Part 1: Document Description
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Citation |
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Title: |
cMSSM parameter space points generated with SPheno and micrOMEGAS |
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Identification Number: |
doi:10.5072/FK2/3RLHRM |
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Distributor: |
Repositório ACNCA |
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Date of Distribution: |
2025-12-30 |
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Version: |
1 |
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Bibliographic Citation: |
Miguel Crispim Romão, 2025, "cMSSM parameter space points generated with SPheno and micrOMEGAS", https://doi.org/10.5072/FK2/3RLHRM, Repositório ACNCA, V1 |
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Citation |
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Title: |
cMSSM parameter space points generated with SPheno and micrOMEGAS |
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Identification Number: |
doi:10.5072/FK2/3RLHRM |
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Identification Number: |
10.5281/zenodo.8146635 |
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Authoring Entity: |
Miguel Crispim Romão (LIP, University of Southampton) |
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Producer: |
Laboratório de Instrumentação e Física Experimental de Partículas |
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Distributor: |
Repositório ACNCA |
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Access Authority: |
LIP |
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Depositor: |
Gomes, Jorge |
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Date of Deposit: |
2025-12-29 |
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Holdings Information: |
https://doi.org/10.5072/FK2/3RLHRM |
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Study Scope |
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Keywords: |
Physics, LIP-Machine Learning, SUSY, cMSSM, SPheno, micrOMEGAS, pre-SUSY 2023 |
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Abstract: |
These two datasets were produced to be used in two lectures on Machine Learning for SUSY Model Building taught in pre-SUSY 2023 summer school in Southampton. The code used to generate and to analyse these data can be found here. The datasets are as following: 1 million points generated using SPheno only (so no Dark Matter relic density) for the cMSSM with the physical parameters randomly sampled from the table bellow. The columns are 'm0', 'm12', 'A0', 'tanb': the four physical parameters of the theory 'idx': an utility identifier used during generation, can/should be ignored The flattened SPheno outputs. These are obtained by reading the resulting slha spectrum file outputted by SPheno and flatten the blocks. For example from the 'MINPAR' block, the key-value pairs are given by the columns 'MINPAR_1', 'MINPAR_2', 'MINPAR_3', 'MINPAR_4', 'MINPAR_5', and likewise for all blocks in the slha file. 10 thousand points generated using SPheno, and which spectrum outputs was then fed to micrOMEGAS (MSSM model configured to accept low-scale slha files as input), with the physical parameters randomly sampled from the same table bellow. The columns are: The same as above, in addition to 'Omega', 'dm_spin', 'dm_mass' obtained from the micrOMEGAS output, representing Dark Matter relic density, Dark Matter spin, Dark Matter mass, respectively. The full list of columns can be seen in `column_names.txt` file. Versions: SPheno 4.0.5, with a patch to output a warning when the LSP is charged. This version can be found here. micrOMEGAS 5.3.41, with the MSSM model adapted for low-scale slha inputs. The datasets are provided in Apache `parquet` format. In order to read them using `pandas`, an installation with the optional flag `[parquet]` should be used. Alternatively, one can use `pyarrow`. |
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Notes: |
Miguel Crispim Romao. (2023). cMSSM parameter space points generated with SPheno and micrOMEGAS (1.0.0) [Data set]. pre-SUSY 2023: School on Supersymmetry and Unification of Fundamental forces (pre-SUSY 2023), Southampton. Zenodo. https://doi.org/10.5281/zenodo.8146636 |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</a> |
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Other Study Description Materials |
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Label: |
column_names.txt |
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Notes: |
text/plain |
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Label: |
Points-10k-With-Omega.parquet |
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Notes: |
application/octet-stream |
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Label: |
Points-1M-Without-Omega.parquet |
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Notes: |
application/octet-stream |