HMcode2020 Emulator

Emulated HMcode2020 non-linear power spectra for fast weak lensing analysis. The structure of the code is based on baccoemu.

Installation

To install it, just clone the repository, go to the folder and do

pip install . [--user]

Requirements

Required python packages:

• numpy
• scipy

For tutorials:

• matplotlib
• emcee
• getdist

Usage

import HMcode2020Emu as hmcodeemu


params = {
    'omega_cdm'     :  [0.315],
    'As'            :  [np.exp(3.07)*1.e-10],
    'omega_baryon'  :  [0.05],
    'ns'            :  [0.96],
    'hubble'        :  [0.67],
    'neutrino_mass' :  [0.0],
    'w0'            :  [-1.0],
    'wa'            :  [0.0],
    'log10TAGN'     :  [7.8],
    'z'             :  [0.]
}
emulator = hmcodeemu.Matter_powerspectrum()

k_lin, pk_lin_total = emulator.get_linear_pk(nonu=False, **params)
k_lin, pk_lin_nonu = emulator.get_linear_pk(nonu=True, **params)

k_nonlin, pk_nonlin_total = emulator.get_nonlinear_pk(baryonic_boost=True, **params)

Note that for neutrino calculations we assume 2 massless neutrinos and 1 massive neutrino with the mass equal to 'neutrino_mass'. You can also see an example in the tutorials-folder as well as an initialising CAMB file.

Parameter ranges

parameter	limits
omega_cdm	[0.1, 0.8]
omega_baryon	[0.01, 0.1]
hubble	[0.4, 1.]
As	[0.495e-9, 5.459e-9]
ns	[0.6, 1.2]
neutrino_mass [eV]	[0., 0.5]
w0	[-3., -0.3]
wa	[-3., 3.]
log10TAGN	[7.6, 8.3]
z	[0.0, 4.]
:---:	:---:
k_lin [h/Mpc]	[3.7e-4, 50]
k_nonlin [h/Mpc]	[0.01, 50]

Note that $w = w_0 + (1-a)w_a$ must be negative at all redshifts, hence we impose the following condition: $w_0 + w_a \leq 0$. One could add it on the level of priors into analysis too.

Citation

If you use HMcode2020Emu at any point in your work please cite the HMcode2020 paper:

@article{Mead2020,
        author = {Mead, Alexander and Brieden, Samuel and Tr\"oster, Tilman and Heymans, Catherine},
        title = {HMcode-2020: Improved modelling of non-linear cosmological power spectra with baryonic feedback},
        journal={Monthly Notices of the Royal Astronomical Society},
        publisher={Oxford University Press (OUP)},
        year = {2021},
        month = {Mar},
        volume = {502},
        number = {1},
        ISSN = {0035-8711},
        url = {https://doi.org/10.1093/mnras/stab082},
        pages = {1401-1422},
        DOI = {10.1093/mnras/stab082},
        archivePrefix = {arXiv},
        eprint = {2009.01858},
        primaryClass = {astro-ph.CO},
}

the CosmoPower paper:

@article{SpurioMancini2022,
         title={CosmoPower: emulating cosmological power spectra for accelerated Bayesian inference from next-generation surveys},
         volume={511},
         ISSN={1365-2966},
         url={http://dx.doi.org/10.1093/mnras/stac064},
         DOI={10.1093/mnras/stac064},
         number={2},
         journal={Monthly Notices of the Royal Astronomical Society},
         publisher={Oxford University Press (OUP)},
         author={Spurio Mancini, Alessio and Piras, Davide and Alsing, Justin and Joachimi, Benjamin and Hobson, Michael P},
         year={2022},
         month={Jan},
         pages={1771–1788}
         }

as well as this paper where the similar data production and emulation pipelines have been used:

@article{Tsedrik2024,
    author = Tsedrik, Maria and Bose, Benjamin and Carrilho, Pedro and Pourtsidou, Alkistis and Pamuk, Sefa and Casas, Santiago and Lesgourgues, Julien,
    title = {Stage-IV Cosmic Shear with Modified Gravity and Model-independent Screening},
    journal = {JCAP},
    year = {2024},
    month = {Oct},
    volume = {2024},
    number = {10},
    eid = {099},
    pages = {099},
    doi = {10.1088/1475-7516/2024/10/099},
    eprint = {2404.11508},
    archivePrefix = {arXiv}
}

License

MIT