Theories

primordial_cosmology

class: Cosmoprimo

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute primordial cosmology quantity
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  engine: class

params:
  h:
    value: 0.6736
    prior:
      dist: uniform
      limits: [0.4, 0.9]
    latex: h
  omega_cdm:
    value: 0.12
    prior:
      dist: uniform
      limits: [0.05, 0.2]
    latex: \omega_{cdm}
  omega_b:
    value: 0.02237
    prior:
      dist: uniform
      limits: [0.01, 0.03]
    latex: \omega_{b}
  A_s:
    value: 2.083e-09
    prior:
      dist: uniform
      limits: [1.8e-9, 3e-9]
    latex: A_{s}
  n_s:
    value: 0.9649
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    latex: n_s
  omega_ncdm:
    value: 0.0006442
    latex: \omega_{ncdm}
    fixed: True
  N_ur:
    value: 2.0328
    latex: N_{ur}
    fixed: True
  tau_reio:
    value: 0.0544
    latex: \tau
    fixed: True
  w0_fld:
    value: -1.
    latex: w_{0}
    fixed: True
  wa_fld:
    value: 0.
    latex: w_{a}
    fixed: True

galaxy_clustering/primordial_non_gaussianity

class: PrimordialNonGaussianityPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute primordial non-Gaussianity power spectrum multipoles
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  bfnl_loc:
    value: 0.
    prior:
      dist: uniform
      limits: [-100, 100]
    latex: bf_{NL}^{\mathrm{loc}}
  bias:
    value: 2.
    prior:
      dist: uniform
      limits: [0.1, 10]
    latex: b
  sn0:
    value: 0.
    prior:
      dist: uniform
      limits: [-1e5, 1e5]
    latex: s_{n, 0}
  sigmas:
    value: 0.
    prior:
      dist: uniform
      limits: [0., 10]
    latex: \Sigma_{s}

galaxy_clustering/power_template

class: BasePowerSpectrumWiggles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute power spectrum BAO wiggles
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  engine: wallish2018


---

class: FullPowerSpectrumParameterization

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Full-fit parameterization
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:

params:
  .delete: '*'
  h:
    value: 0.6736
    prior:
      dist: uniform
      limits: [0.4, 0.9]
    latex: h
  Omega_m:
    value: 0.3
    prior:
      dist: uniform
      limits: [0.05, 0.6]
    latex: \Omega_{m}
  omega_b:
    value: 0.02237
    fixed: True
    prior:
      dist: uniform
      limits: [0.01, 0.03]
    latex: \omega_{b}
  A_s:
    value: 2.083e-09
    prior:
      dist: uniform
      limits: [1.8e-9, 3e-9]
    latex: A_{s}
  n_s:
    value: 0.9649
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    latex: n_s
  omega_ncdm:
    value: 0.0006442
    latex: \omega_{ncdm}
    fixed: True
  N_ur:
    value: 2.0328
    latex: N_{ur}
    fixed: True
  tau_reio:
    value: 0.0544
    latex: \tau
    fixed: True
  w0_fld:
    value: -1.
    latex: w_{0}
    fixed: True
  wa_fld:
    value: 0.
    latex: w_{a}
    fixed: True

---

class: ShapeFitPowerSpectrumParameterization

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Shapefit-parameterized template power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  fiducial: DESI
  a: 0.6
  kp: 0.03

params:
  dm:
    value: 0.
    prior:
      dist: uniform
      limits: [-3., 3.]
    ref:
      limits: [-0.01, 0.01]
    latex: dm
  dn:
    value: 0.
    fixed: True
    prior:
      dist: uniform
      limits: [-0.5, 0.5]
    ref:
      dist: norm
      loc: 0.
      scale: 0.1
    latex: dn
  Ap:
    derived: True
    latex: 'A_{p}'
  kp_rs:
    derived: True
    latex: 'k_{p} r_{\mathrm{drag}}'
  f_sqrt_Ap:
    derived: True
    latex: 'f A_{p}^{1/2}'
  m:
    derived: True
    latex: 'm'
  n:
    derived: True
    latex: 'n_{s}'
  f:
    value: 0.8
    prior:
      dist: uniform
      limits: [0., 1.]
    ref:
      limits: [0.75, 0.85]
    latex: 'f'
  qpar:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      limits: [0.99, 1.01]
    latex: '\alpha_{\parallel}'
  qper:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      limits: [0.99, 1.01]
    latex: '\alpha_{\perp}'
  DM_over_rd:
    derived: True
    latex: 'D_{\mathrm{M}}/r_{d}'
  DH_over_rd:
    derived: True
    latex: 'D_{\mathrm{H}}/r_{d}'
  DH_over_DM:
    derived: True
    latex: 'D_{\mathrm{H}}/D_{\mathrm{M}}'
  DV_over_rd:
    derived: True
    latex: '(D_{\mathrm{H}} D_{\mathrm{M}}^{2} z)^{1/3}/r_{d}'
  zeff:
    derived: True
    latex: 'z_{\mathrm{eff}}'

---

class: WiggleSplitPowerSpectrumParameterization

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Wiggle-split-parameterized template velocity power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  fiducial: DESI
  r: 8.

params:
  fsigmar:
    value: 0.5
    prior:
      dist: uniform
      limits: [0.1, 1.2]
    latex: 'f\sigma_{R}'
  qbao:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    latex: '\alpha_{\mathrm{BAO}}'
  qap:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      limits: [0.99, 1.01]
    latex: '\alpha_{ap}'
  dm:
    value: 0.
    prior:
      dist: uniform
      limits: [-0.5, 0.5]
    ref:
      limits: [-0.01, 0.01]
    latex: dm
  m:
    derived: True
    latex: 'm'
  kp:
    derived: True
    latex: 'k_{p}'
  r:
    derived: True
    latex: 'R'
  zeff:
    derived: True
    latex: 'z_{\mathrm{eff}}'

---

class: BandVelocityPowerSpectrumParameterization

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Bandpower-parameterized template velocity power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  fiducial: DESI

params:
  rptt*:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1.
      limits: [-1., 5]
    ref:
      limits: [-0.05, 0.05]
  ptt:
    derived: True
    latex: 'P_{\theta\theta}'
  kptt:
    derived: True
    latex: 'k'
  f:
    value: 0.8
    prior:
      dist: uniform
      limits: [0.1, 1.]
    ref:
      limits: [0.75, 0.85]
    latex: 'f'
  qap:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      limits: [0.99, 1.01]
    latex: '\alpha_{ap}'
  zeff:
    derived: True
    latex: 'z_{\mathrm{eff}}'

---

class: BAOPowerSpectrumParameterization

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Power spectrum parameterization for BAO
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  fiducial: DESI

params:
  qpar:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      dist: norm
      loc: 1.
      scale: 0.02
    latex: '\alpha_{\parallel}'
  qper:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      limits: [0.99, 1.01]
    latex: '\alpha_{\perp}'
  qiso:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      limits: [0.99, 1.01]
    latex: '\alpha_{\mathrm{iso}}'
  qap:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    ref:
      limits: [0.99, 1.01]
    latex: '\alpha_{\mathrm{ap}}'
  DM_over_rd:
    derived: True
    latex: 'D_{\mathrm{M}}/r_{d}'
  DH_over_rd:
    derived: True
    latex: 'D_{\mathrm{H}}/r_{d}'
  DH_over_DM:
    derived: True
    latex: 'D_{\mathrm{H}}/D_{\mathrm{M}}'
  DV_over_rd:
    derived: True
    latex: '(D_{\mathrm{H}} D_{\mathrm{M}}^{2} z)^{1/3}/r_{d}'
  zeff:
    derived: True
    latex: 'z_{\mathrm{eff}}'

galaxy_clustering/bao

class: DampedBAOWigglesTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Empirical model for BAO power spectrum multipoles
  url:
  licence:
  bibtex: [arxiv:1607.03149]
  requirements: []
  long_description: BAO model used in the BOSS DR12 BAO analysis by Beutler et al. 2017; supports pre-, reciso, recsym, real (f = 0) and redshift-space reconstruction

init:
  ells: [0, 2]
  smoothing_radius: 15.
  mode: ''  # '' for pre-recon, reciso, recsym

params:
  bias:
    value: 2.
    fixed: False
    prior:
      dist: uniform
      limits: [0.2, 4.]
    latex: b
  sigmas:
    value: 0.
    fixed: True
    latex: \Sigma_{s}
    prior:
      limits: [0, 10]
  sigmapar:
    value: 9.
    fixed: True
    latex: \Sigma_{\parallel}
    prior:
      limits: [0.1, 10]
  sigmaper:
    value: 6.
    fixed: True
    latex: \Sigma_{\perp}
    prior:
      limits: [0.1, 10]
  al[:5:2]_[-3:2]:
    value: 0.
    fixed: False
    latex: a_{[], []}
    prior:
      limits: [-1e4, 1e4]
    ref:
      limits: [-1e2, 1e2]

---

class: ResummedBAOWigglesTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 07/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Model for BAO power spectrum multipoles with resummed BAO wiggles
  url:
  licence:
  bibtex: [arxiv:1907.00043]
  requirements: []
  long_description: Supports pre-, reciso, recsym, real (f = 0) and redshift-space reconstruction

init:
  ells: [0, 2]
  smoothing_radius: 15.
  mode: ''  # '' for pre-recon, reciso, recsym

params:
  bias:
    value: 2.
    fixed: False
    prior:
      dist: uniform
      limits: [0.2, 4.]
    latex: b
  sigmas:
    value: 0.
    fixed: True
    latex: \Sigma_{s}
    prior:
      limits: [0, 10]
  al[:5:2]_[-3:2]:
    value: 0.
    fixed: False
    latex: a_{[], []}
    prior:
      limits: [-1e4, 1e4]
    ref:
      limits: [-1e2, 1e2]

---

class: DampedBAOWigglesTracerCorrelationFunctionMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Empirical model for BAO correlation function multipoles
  url:
  licence:
  bibtex: [arxiv:1607.03149]
  requirements: []
  long_description: BAO model used in the BOSS DR12 BAO analysis by Beutler et al. 2017; supports pre-, reciso, recsym, real (f = 0) and redshift-space reconstruction

init:
  ells: [0, 2]
  smoothing_radius: 15.
  mode: ''  # '' for pre-recon, reciso, recsym

params:
  bias:
    value: 2.
    fixed: False
    prior:
      dist: uniform
      limits: [0.2, 4.]
    latex: b
  sigmas:
    value: 0.
    fixed: True
    latex: \Sigma_{s}
    prior:
      limits: [0, 10]
  sigmapar:
    value: 9.
    fixed: True
    latex: \Sigma_{\parallel}
    prior:
      limits: [0.1, 10]
  sigmaper:
    value: 6.
    fixed: True
    latex: \Sigma_{\perp}
    prior:
      limits: [0.1, 10]
  al[:5:2]_[-3:2]:
    value: 0.
    fixed: False
    latex: a_{[], []}
    prior:
      limits: [-1e4, 1e4]
    ref:
      limits: [-0.1, 0.1]

---

class: ResummedBAOWigglesTracerCorrelationFunctionMultipoles

info:
  version: 0.0.1
  date: 07/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Model for BAO correlation function multipoles with resummed BAO wiggles
  url:
  licence:
  bibtex: [arxiv:1907.00043]
  requirements: []
  long_description: Supports pre-, reciso, recsym, real (f = 0) and redshift-space reconstruction

init:
  ells: [0, 2]
  smoothing_radius: 15.
  mode: ''  # '' for pre-recon, reciso, recsym

params:
  bias:
    value: 2.
    fixed: False
    prior:
      dist: uniform
      limits: [0.2, 4.]
    latex: b
  sigmas:
    value: 0.
    fixed: True
    latex: \Sigma_{s}
    prior:
      limits: [0, 10]
  al[:5:2]_[-3:2]:
    value: 0.
    fixed: False
    latex: a_{[], []}
    prior:
      limits: [-1e4, 1e4]
    ref:
      limits: [-0.1, 0.1]

galaxy_clustering/full_shape

class: LPTTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: 'Compute Lagrangian perturbation theory (LPT) power spectrum. Can be exactly marginalized over: alpha*, sn*'
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  .fixed: ['b3']
  b1:
    value: 0.6
    prior:
      dist: uniform
      limits: [-1., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
  b2:
    value: -3.
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: -3.
      scale: 0.5
    latex: b_{2}
  bs:
    value: -0.71
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.
      scale: 0.5
    latex: b_{s}
  b3:
    value: -0.479
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: b_{3}
  alpha[0:7:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100
    ref:
      dist: norm
      loc: 0.
      scale: 1.
    latex: \alpha_{[]}
  sn[:5:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1e7
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: s_{n, []}

---

class: EPTMomentsTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Eulerian perturbation theory (EPT) power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]
  beyond_gauss: True
  reduced: True  # reduced set of parameters

params:
  b1:
    value: 1.69
    prior:
      dist: uniform
      limits: [-1., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
    latex: 'b_{1}'
  b2:
    value: -1.17
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: -3.
      scale: 0.5
    latex: 'b_{2}'
  bs:
    value: -0.71
    prior:
      dist: norm
      loc: 0.
      scale: 3.
    ref:
      dist: norm
      loc: 1.
      scale: 0.5
    latex: 'b_{s}'
  b3:
    value: -0.479
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: 'b_{3}'
  alpha[0:7:2]:
    value: 0.
    latex: '\alpha_{[]}'
  alpha*:
    prior:
      dist: norm
      loc: 0.
      scale: 50.
    ref:
      dist: norm
      loc: 0.
      scale: 1.0
  sn[:5:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: s_{n, []}
  alpha:
    value: 0.
    latex: '\alpha'
  alpha_v:
    value: 0.
    latex: '\alpha_{v}'
  alpha_s0:
    value: 0.
    latex: '\alpha_{s,0}'
  alpha_s2:
    value: 0.
    latex: '\alpha_{s,2}'
  alpha_g1:
    value: 0.
    latex: '\alpha_{g,1}'
  alpha_g3:
    value: 0.
    latex: '\alpha_{g,3}'
  alpha_k2:
    value: 0.
    latex: '\alpha_{k,2}'
  sv:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: 's_{v}'
  sigma0:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: '\sigma_{0}'
  stoch_k0:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: 's_{k,0}'
  counterterm_c3:
    value: 0.
    fixed: True
    latex: 'c_{3}'

---

class: EPTFullResummedTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Eulerian perturbation theory (EPT) power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  b1:
    value: 1.69
    prior:
      dist: uniform
      limits: [-1., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
    latex: 'b_{1}'
  b2:
    value: -1.17
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: -3.
      scale: 0.5
    latex: 'b_{2}'
  bs:
    value: -0.71
    prior:
      dist: norm
      loc: 0.
      scale: 3.
    ref:
      dist: norm
      loc: 1.
      scale: 0.5
    latex: 'b_{s}'
  b3:
    value: -0.479
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: 'b_{3}'
  alpha[0:7:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 50.
    ref:
      dist: norm
      loc: 0.
      scale: 1.0
    latex: '\alpha_{[]}'
  sn[:5:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: s_{n, []}
  bFoG:
    value: 0.
    fixed: True
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    ref:
      limits: [0, 2]
    latex: s_{n, []}


---

class: LPTMomentsTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Eulerian perturbation theory (EPT) power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]
  beyond_gauss: True
  shear: True
  third_order: True
  reduced: True  # reduced set of parameters

params:
  b1:
    value: 1.69
    prior:
      dist: uniform
      limits: [-1., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
    latex: 'b_{1}'
  b2:
    value: -1.17
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: -3.
      scale: 0.5
    latex: 'b_{2}'
  bs:
    value: -0.71
    prior:
      dist: norm
      loc: 0.
      scale: 3.
    ref:
      dist: norm
      loc: 1.
      scale: 0.5
    latex: 'b_{s}'
  b3:
    value: -0.479
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: 'b_{3}'
  alpha[0:7:2]:
    value: 0.
    latex: '\alpha_{[]}'
  alpha*:
    prior:
      dist: norm
      loc: 0.
      scale: 50.
    ref:
      dist: norm
      loc: 0.
      scale: 1.0
  sn[:5:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: s_{n, []}
  alpha:
    value: 0.
    latex: '\alpha'
  alpha_v:
    value: 0.
    latex: '\alpha_{v}'
  alpha_s0:
    value: 0.
    latex: '\alpha_{s,0}'
  alpha_s2:
    value: 0.
    latex: '\alpha_{s,2}'
  alpha_g1:
    value: 0.
    latex: '\alpha_{g,1}'
  alpha_g3:
    value: 0.
    latex: '\alpha_{g,3}'
  alpha_k2:
    value: 0.
    latex: '\alpha_{k,2}'
  sv:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: 's_{v}'
  sigma0:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: '\sigma_{0}'
  sigma0_stoch:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: 's_{k,0}'
  counterterm_c3:
    value: 0.
    fixed: True
    latex: 'c_{3}'


---

class: LPTFourierStreamingTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Lagrangian perturbation theory (LPT) power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]
  shear: True
  third_order: True

params:
  b1:
    value: 1.69
    prior:
      dist: uniform
      limits: [-1., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
    latex: 'b_{1}'
  b2:
    value: -1.17
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: -3.
      scale: 0.5
    latex: 'b_{2}'
  bs:
    value: -0.71
    prior:
      dist: norm
      loc: 0.
      scale: 3.
    ref:
      dist: norm
      loc: 1.
      scale: 0.5
    latex: 'b_{s}'
  b3:
    value: -0.479
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: 'b_{3}'
  sn0:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: s_{n, []}
  alpha:
    value: 0.
    latex: '\alpha'
  alpha_v:
    value: 0.
    latex: '\alpha_{v}'
  sv:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: 's_{v}'
  sigma0_stoch:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: 's_{k,0}'
  counterterm_c3:
    value: 0.
    fixed: True
    latex: 'c_{3}'


---

class: LPTGaussianStreamingTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Lagrangian perturbation theory (LPT) correlation function
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]
  shear: True
  third_order: True

params:
  b1:
    value: 1.69
    prior:
      dist: uniform
      limits: [-1., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
    latex: 'b_{1}'
  b2:
    value: -1.17
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: -3.
      scale: 0.5
    latex: 'b_{2}'
  bs:
    value: -0.71
    prior:
      dist: norm
      loc: 0.
      scale: 3.
    ref:
      dist: norm
      loc: 1.
      scale: 0.5
    latex: 'b_{s}'
  b3:
    value: -0.479
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: 'b_{3}'
  alpha:
    value: 0.
    latex: '\alpha'
  alpha_v:
    value: 0.
    latex: '\alpha_{v}'
  sv:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: 's_{v}'
  s2FoG:
    value: 0.
    fixed: True
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    ref:
      limits: [0, 2]
    latex: s_{n, []}

---

class: KaiserTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Kaiser power spectrum
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  b1:
    value: 1.69
    prior:
      dist: uniform
      limits: [0., 4.0]
    ref:
      limits: [1.0, 2.0]
    latex: b_{1}
  sn0:
    value: 0.
    fixed: False
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    latex: s_{n, 0}

---

class: LPTTracerCorrelationFunctionMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Lagrangian perturbation theory (LPT) correlation function
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  .fixed: ['b3']
  b1:
    value: 0.6
    prior:
      dist: uniform
      limits: [-1., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
  b2:
    value: -3.
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: -3.
      scale: 0.5
    latex: b_{2}
  bs:
    value: -0.71
    prior:
      dist: norm
      loc: 0.
      scale: 3.
    ref:
      dist: norm
      loc: 1.
      scale: 0.5
    latex: b_{s}
  b3:
    value: -0.479
    fixed: True
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: b_{3}
  alpha[0:7:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 50.
    ref:
      dist: norm
      loc: 0.
      scale: 1.0
    latex: \alpha_{[]}
  sn[:5:2]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 1000.
    ref:
      dist: norm
      loc: 0
      scale: 50.
    latex: s_{n, []}

---

class: PyBirdTracerPowerSpectrumMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: 'Compute PyBird power spectrum. Can be exactly marginalized over: c*'
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  .fixed: ['b2m4']
  b1:
    value: 1.3
    prior:
      limits: [0., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
  b3:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: b_{3}
  b2:
    value: 0.
    prior:
      limits: [-10., 10.]
    ref:
      limits: [-1., 1.]
    latex: b_{2}
  b4:
    value: 0.
    prior:
      limits: [-10., 10.]
    ref:
      limits: [-1., 1.]
    latex: b_{4}
  # west coast
  b2p4:
    value: 0.
    prior:
      limits: [-10., 10.]
    latex: '(b_{2} + b_{4})/\sqrt{2}'
  b2m4:
    value: 0.
    prior:
      limits: [-10., 10.]
    latex: '(b_{2} - b_{4})/\sqrt{2}'
  cct:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{t}
  cr1:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 1}
  cr2:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 2}
  cr4:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 4}
  cr6:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 6}
  ce[:3]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{e, []}

---

class: PyBirdTracerCorrelationFunctionMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: 'Compute PyBird correlation function. Can be exactly marginalized over: c*'
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  .fixed: ['b2m4']
  b1:
    value: 1.3
    prior:
      limits: [0., 4.0]
    ref:
      limits: [0., 1.]
    latex: b_{1}
  b3:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 15.
    ref:
      dist: norm
      loc: 1.0
      scale: 0.5
    latex: b_{3}
  b2:
    value: 0.
    prior:
      limits: [-10., 10.]
    ref:
      limits: [-1., 1.]
    latex: b_{2}
  b4:
    value: 0.
    prior:
      limits: [-10., 10.]
    ref:
      limits: [-1., 1.]
    latex: b_{4}
  # west coast
  b2p4:
    value: 0.
    prior:
      limits: [-10., 10.]
    latex: '(b_{2} + b_{4})/\sqrt{2}'
  b2m4:
    value: 0.
    prior:
      limits: [-10., 10.]
    latex: '(b_{2} - b_{4})/\sqrt{2}'
  cct:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{t}
  cr1:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 1}
  cr2:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 2}
  cr4:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 4}
  cr6:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{r, 6}
  ce[:3]:
    value: 0.
    prior:
      dist: norm
      loc: 0.
      scale: 100.
    latex: c_{e, []}

---

class: KaiserTracerCorrelationFunctionMultipoles

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Compute Kaiser correlatiom function
  url:
  licence:
  bibtex: []
  requirements: []
  long_description:

init:
  ells: [0, 2, 4]

params:
  b1:
    value: 1.69
    prior:
      dist: uniform
      limits: [0., 4.0]
    ref:
      limits: [1.0, 2.0]
    latex: b_{1}

galaxy_clustering/base

class: EffectAP

info:
  version: 0.0.1
  date: 05/04/2022
  author: Arnaud de Mattia
  maintainer: Arnaud de Mattia
  description: Alcock-Paczynski effect
  url:
  licence:
  bibtex: [doi:10.1038/281358a0]
  requirements: []
  long_description:

init:
  fiducial: DESI

params:
  qpar:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    latex: '\alpha_{\parallel}'
  qper:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    latex: '\alpha_{\perp}'
  qiso:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    latex: '\alpha_{\mathrm{iso}}'
  qap:
    value: 1.
    prior:
      dist: uniform
      limits: [0.8, 1.2]
    latex: '\alpha_{\mathrm{ap}}'