# ACT DR6 Lensing Likelihood
[](https://pypi.org/project/act_dr6_lenslike/)
[](https://github.com/ACTCollaboration/act_dr6_lenslike/actions)
This repository contains likelihood software for the ACT DR6 CMB lensing analysis. If you use this software and/or the associated data, please cite both of the following papers:
- [Madhavacheril, Qu, Sherwin, MacCrann, Li et al ACT Collaboration (2023), arxiv:2304.05203](https://arxiv.org/abs/2304.05203)
- [Qu, Sherwin, Madhavacheril, Han, Crowley et al ACT Collaboration (2023), arxiv:2304.05202](https://arxiv.org/abs/2304.05202)
In addition, if you use the ACT+Planck lensing combination variant from the likelihood, please also cite:
- [Carron, Mirmelstein, Lewis (2022), arxiv:2206.07773, JCAP09(2022)039](https://arxiv.org/abs/2206.07773)
## Chains
A pre-release version of the chains from Madhavacheril et al are available [here](https://portal.nersc.gov/project/act/act_dr6_lensing/chains/). Please make sure to read the README file.
## Step 1: Install
### Option 1: Install from PyPI
You can install the likelihood directly with:
pip install act_dr6_lenslike
### Option 2: Install from Github
If you wish to be able to make changes to the likelihood for development, first clone this repository. Then install with symbolic links:
pip install -e . --user
Tests can be run using
python setup.py test
## Step 2: download and unpack data
This can be performed automatically with the supplied `get-act-data.sh` script. Otherwise follow the steps below.
Download the likelihood data tarball for ACT DR6 lensing from [NASA's LAMBDA archive](https://lambda.gsfc.nasa.gov/product/act/actadv_prod_table.html).
Extract the tarball into the `act_dr6_lenslike/data/` directory in the cloned repository such the directory `v1.2` is directly inside it. Only then should you proceed with the next steps.
## Step 3: use in Python codes
### Generic Python likelihood
```
import act_dr6_lenslike as alike
variant = 'act_baseline'
lens_only = False # use True if not combining with any primary CMB data
like_corrections = True # should be False if lens_only is True
# Do this once
data_dict = alike.load_data(variant,lens_only=lens_only,like_corrections=like_corrections)
# This dict will now have entries like `data_binned_clkk` (binned data vector), `cov`
# (covariance matrix) and `binmat_act` (binning matrix to be applied to a theory
# curve starting at ell=0).
# Get cl_kk, cl_tt, cl_ee, cl_te, cl_bb predictions from your Boltzmann code.
# These are the CMB lensing convergence spectra (not potential or deflection)
# as well as the TT, EE, TE, BB CMB spectra (needed for likelihood corrections)
# in uK^2 units. All of these are C_ell (not D_ell), no ell or 2pi factors.
# Then call
lnlike=alike.generic_lnlike(data_dict,ell_kk,cl_kk,ell_cmb,cl_tt,cl_ee,cl_te,cl_bb)
```
### Cobaya likelihood
Your Cobaya YAML or dictionary should have an entry of this form
```
likelihood:
act_dr6_lenslike.ACTDR6LensLike:
lens_only: False
stop_at_error: True
lmax: 4000
variant: act_baseline
```
No other parameters need to be set. (e.g. do not manually set `like_corrections` or `no_like_corrections` here).
An example is provided in `ACTDR6LensLike-example.yaml`. If, however, you are combining with
the ACT DR4 CMB 2-point power spectrum likelihood, you should also set `no_actlike_cmb_corrections: True`
(in addition to `lens_only: True` as described below). You do not need to do this if you are combining
with Planck CMB 2-point power spectrum likelihoods.
### Important parameters
- `variant` should be
- `act_baseline` for the ACT-only lensing power spectrum with the baseline multipole range
- `act_extended` for the ACT-only lensing power spectrum with the extended multipole range (L<1250)
- `actplanck_baseline` for the ACT+Planck lensing power spectrum with the baseline multipole range
- `actplanck_extended` for the ACT+Planck lensing power spectrum with the extended multipole range (L<1250)
- `lens_only` should be
- False when combining with any primary CMB measurement
- True when not combining with any primary CMB measurement
### Recommended theory accuracy
For CAMB calls, we recommend the following (or higher accuracy):
- `lmax`: 4000
- `lens_margin`:1250
- `lens_potential_accuracy`: 4
- `AccuracyBoost`:1
- `lSampleBoost`:1
- `lAccuracyBoost`:1
- `halofit_version`:`mead2016`
Raw data
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"description": "# ACT DR6 Lensing Likelihood\n[](https://pypi.org/project/act_dr6_lenslike/)\n[](https://github.com/ACTCollaboration/act_dr6_lenslike/actions)\n\nThis repository contains likelihood software for the ACT DR6 CMB lensing analysis. If you use this software and/or the associated data, please cite both of the following papers:\n- [Madhavacheril, Qu, Sherwin, MacCrann, Li et al ACT Collaboration (2023), arxiv:2304.05203](https://arxiv.org/abs/2304.05203)\n- [Qu, Sherwin, Madhavacheril, Han, Crowley et al ACT Collaboration (2023), arxiv:2304.05202](https://arxiv.org/abs/2304.05202)\n\nIn addition, if you use the ACT+Planck lensing combination variant from the likelihood, please also cite:\n- [Carron, Mirmelstein, Lewis (2022), arxiv:2206.07773, JCAP09(2022)039](https://arxiv.org/abs/2206.07773)\n\n## Chains\n\nA pre-release version of the chains from Madhavacheril et al are available [here](https://portal.nersc.gov/project/act/act_dr6_lensing/chains/). Please make sure to read the README file.\n\n## Step 1: Install\n### Option 1: Install from PyPI\nYou can install the likelihood directly with:\n\n pip install act_dr6_lenslike\n\n### Option 2: Install from Github\nIf you wish to be able to make changes to the likelihood for development, first clone this repository. Then install with symbolic links:\n\n pip install -e . --user\n\nTests can be run using \n\n python setup.py test\n\n## Step 2: download and unpack data\n\nThis can be performed automatically with the supplied `get-act-data.sh` script. Otherwise follow the steps below.\n\nDownload the likelihood data tarball for ACT DR6 lensing from [NASA's LAMBDA archive](https://lambda.gsfc.nasa.gov/product/act/actadv_prod_table.html).\n\nExtract the tarball into the `act_dr6_lenslike/data/` directory in the cloned repository such the directory `v1.2` is directly inside it. Only then should you proceed with the next steps.\n \n## Step 3: use in Python codes\n\n### Generic Python likelihood\n\n```\nimport act_dr6_lenslike as alike\n\nvariant = 'act_baseline'\nlens_only = False # use True if not combining with any primary CMB data\nlike_corrections = True # should be False if lens_only is True\n\n# Do this once\ndata_dict = alike.load_data(variant,lens_only=lens_only,like_corrections=like_corrections)\n# This dict will now have entries like `data_binned_clkk` (binned data vector), `cov`\n# (covariance matrix) and `binmat_act` (binning matrix to be applied to a theory\n# curve starting at ell=0).\n\n# Get cl_kk, cl_tt, cl_ee, cl_te, cl_bb predictions from your Boltzmann code.\n# These are the CMB lensing convergence spectra (not potential or deflection)\n# as well as the TT, EE, TE, BB CMB spectra (needed for likelihood corrections)\n# in uK^2 units. All of these are C_ell (not D_ell), no ell or 2pi factors.\n# Then call\nlnlike=alike.generic_lnlike(data_dict,ell_kk,cl_kk,ell_cmb,cl_tt,cl_ee,cl_te,cl_bb)\n```\n\n### Cobaya likelihood\n\nYour Cobaya YAML or dictionary should have an entry of this form\n\n```\nlikelihood:\n act_dr6_lenslike.ACTDR6LensLike:\n lens_only: False\n stop_at_error: True\n lmax: 4000\n variant: act_baseline\n```\n\nNo other parameters need to be set. (e.g. do not manually set `like_corrections` or `no_like_corrections` here).\nAn example is provided in `ACTDR6LensLike-example.yaml`. If, however, you are combining with\nthe ACT DR4 CMB 2-point power spectrum likelihood, you should also set `no_actlike_cmb_corrections: True`\n(in addition to `lens_only: True` as described below). You do not need to do this if you are combining\nwith Planck CMB 2-point power spectrum likelihoods.\n\n### Important parameters\n\n- `variant` should be\n - `act_baseline` for the ACT-only lensing power spectrum with the baseline multipole range\n - `act_extended` for the ACT-only lensing power spectrum with the extended multipole range (L<1250)\n - `actplanck_baseline` for the ACT+Planck lensing power spectrum with the baseline multipole range\n - `actplanck_extended` for the ACT+Planck lensing power spectrum with the extended multipole range (L<1250)\n- `lens_only` should be\n - False when combining with any primary CMB measurement\n - True when not combining with any primary CMB measurement\n\n### Recommended theory accuracy\n\nFor CAMB calls, we recommend the following (or higher accuracy):\n- `lmax`: 4000\n- `lens_margin`:1250\n- `lens_potential_accuracy`: 4\n- `AccuracyBoost`:1\n- `lSampleBoost`:1\n- `lAccuracyBoost`:1\n- `halofit_version`:`mead2016`\n",
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