Work Description

Title: Dataset for singlet-doublet dark matter revisited Open Access Deposited

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Methodology
  • To generate this dataset, we utilized the following tools: SARAH v4.15.2 ( https://sarah.hepforge.org/): Used to implement the singlet-doublet fermion model and generate the model files for SPheno and micrOMEGAs. These files contain the interaction vertices of the model. SPheno v4.0.5 ( https://spheno.hepforge.org/): Employed to numerically diagonalize the neutral Majorana mass matrix and compute the tree-level particle spectrum and mixing angles. micrOMEGAs v6.0 ( https://lapth.cnrs.fr/micromegas/): Used to numerically solve the Boltzmann equations and calculate the thermal relic abundance and direct detection cross sections. A wide parameter scan of the singlet-doublet fermion model was performed to identify regions of parameter space that reproduce the correct dark matter relic abundance.
Description
  • This dataset stems from research on the singlet-doublet model of dark matter, an economical model of weakly interacting dark matter. We revisit it in light of improved dark matter detection limits. We characterize the regions of parameter space that have suppressed direct detection cross sections and discuss predictions for the Large Hadron Collider.
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Creator ORCID iD
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Depositor creator
  • true
Contact information
Discipline
Funding agency
  • Department of Energy (DOE)
ORSP grant number
  • AWD000291
Keyword
Citations to related material
Resource type
Last modified
  • 06/03/2025
Published
  • 06/03/2025
DOI
  • https://doi.org/10.7302/27j9-nw17
License
To Cite this Work:
Bhattiprolu, P. N., Petrosky, E., Pierce, A. (2025). Dataset for singlet-doublet dark matter revisited [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/27j9-nw17

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########
# Date #
########

02 June, 2025

#################
# Dataset Title #
#################

Dataset for singlet-doublet dark matter revisited

####################
# Dataset Creators #
####################

Name: Prudhvi N. Bhattiprolu
Email: [email protected]
Institution: INFN Florence; University of Michigan Department of Physics
ORCID: https://orcid.org/0000-0003-1819-1733

Name: Evan Petrosky
Email: [email protected]
Institution: University of Michigan Department of Physics
ORCID: https://orcid.org/0000-0003-2427-4287

Name: Aaron Pierce
Email: [email protected]
Institution: University of Michigan Department of Physics
ORCID: https://orcid.org/0000-0002-6238-7429

###################
# Dataset Contact #
###################

Prudhvi N. Bhattiprolu ([email protected])

###########
# Funding #
###########

This work is supported in part by the Department of Energy under grant number
DE-SC0007859. This research is supported in part through computational resources
and services provided by Advanced Research Computing (ARC), a division of
Information and Technology Services (ITS) at the University of Michigan,
Ann Arbor.

###############
# Methodology #
###############

To generate this dataset, we utilized the following tools:

SARAH v4.15.2: Used to implement the singlet-doublet fermion model and generate
the model files for SPheno and micrOMEGAs. These files contain the interaction
vertices of the model.
Link: https://sarah.hepforge.org/

SPheno v4.0.5: Employed to numerically diagonalize the neutral Majorana mass
matrix and compute the tree-level particle spectrum and mixing angles.
Link: https://spheno.hepforge.org/

micrOMEGAs v6.0: Used to numerically solve the Boltzmann equations and calculate
the thermal relic abundance and direct detection cross sections.
Link: https://lapth.cnrs.fr/micromegas/

A wide parameter scan of the singlet-doublet fermion model was performed to
identify regions of parameter space that reproduce the correct dark matter relic
abundance.

###############
# Description #
###############

This dataset stems from research on the singlet-doublet model of dark matter, an
economical model of weakly interacting dark matter. We revisit it in light of
improved dark matter detection limits. We characterize the regions of parameter
space that have suppressed direct detection cross sections and discuss
predictions for the Large Hadron Collider.

############
# Acronyms #
############

DM: Dark Matter
SI: Spin-independent
SD: Spin-dependent
GeV: Giga-electron Volts
pb: Picobarn (unit of cross section)
FO: Freeze-out

###########
# Dataset #
###########

This dataset contains parameter points in the singlet-doublet fermion dark
matter model that reproduce the correct thermal relic abundance of dark matter.
The columns in the dataset are:

# Model Input Parameters

Column 1 (MS): Singlet fermion mass in GeV
Column 2 (MD): Doublet fermion mass in GeV
Column 3 (y1): Yukawa coupling of Higgs–Singlet–Doublet (1, 2, –1/2) interaction
Column 4 (y2): Yukawa coupling of Higgs–Singlet–Doublet (1, 2, 1/2) interaction

# Physical Mass Spectrum

Column 5 (mN1): Mass of the lightest neutral Majorana state (DM) in GeV
Column 6 (mN2): Mass of the second neutral Majorana state in GeV
Column 7 (mN3): Mass of the heaviest neutral Majorana state in GeV
Column 8 (mC): Mass of the charged Dirac state in GeV

# Neutral Mixing Matrix Elements

Columns 9–11 (V11, V12, V13): First row of the neutral Majorana mixing matrix
Columns 12–14 (V21, V22, V23): Second row of the mixing matrix
Columns 15–17 (V31, V32, V33): Third row of the mixing matrix

# Direct Detection Cross Sections

Column 18 (sigmaSIp): Spin-independent DM–proton scattering cross section in pb
Column 19 (sigmaSIn): Spin-independent DM–neutron scattering cross section in pb
Column 20 (sigmaSDp): Spin-dependent DM–proton scattering cross section in pb
Column 21 (sigmaSDn): Spin-dependent DM–neutron scattering cross section in pb

# Relic Abundance

Column 22 (xFO): Freeze-out temperature, specifically, xFO = m/T at freeze-out
Column 23 (Omegah2): Dark matter relic abundance

# Chemical Equilibrium

Column 24 (GamH): Minimum reaction rate between sub-components of the dark
sector normalized to Hubble at freeze-out (Gamma/(H xFO))

# Freeze-out Processes

Column 25 (p1percent): Contribution (%) of the leading freeze-out process
Column 26 (p1): Leading freeze-out process
Column 27 (p2percent): Contribution (%) of the second leading freeze-out process
Column 28 (p2): Second leading freeze-out process
Column 29 (p3percent): Contribution (%) of the third leading freeze-out process
Column 30 (p3): Third leading freeze-out process

#####################
# To Cite this work #
#####################

# Dataset
Bhattiprolu, P. N., Petrosky, E., Pierce, A.
Dataset for singlet-doublet dark matter revisited [Data set],
University of Michigan - Deep Blue Data.
https://doi.org/10.7302/27j9-nw17

# Article
Bhattiprolu, P. N., Petrosky, E., Pierce, A.
Singlet-doublet dark matter revisited,
[arXiv:2505.11607 [hep-ph]]

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