diff --git a/docs/source/index.rst b/docs/source/index.rst
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--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -42,78 +42,180 @@ Table of contents
developer/copyright_and_authorship
Citing
-------
+^^^^^^
-If you are using |a| for your project, please cite the following articles for ARES2 and ARES3:
+.. sectionauthor:: Florent Leclercq (last update: 20 June 2023)
-* Jasche, Kitaura, Wandelt, 2010, MNRAS, 406, 1 (arxiv 0911.2493)
-* Jasche & Lavaux, 2015, MNRAS, 447, 2 (arxiv 1402.1763)
-* Lavaux & Jasche, 2016, MNRAS, 455, 3 (arxiv 1509.05040)
-* Jasche & Lavaux, 2019, A&A, 625, A64 (arxiv 1806.11117)
-
-However, bear in mind that depending on the features that you are using you may want to cite other papers as well.
-Here is a non-exhaustive list of those articles:
-
-* Model development:
-
- * HADES epoch:
-
- * HMC, exponential transform, linear bias: Jasche, Kitaura, Wandelt, 2010, 406, 1 (arXiv 0911.2493)
- * HMC, exponential transform, power law bias:
-
- * Jasche, Leclercq, Wandelt, 2015
- * Jasche, Wandelt, 2012, MNRAS, 425, 1042 (arXiv 1106.2757)
-
- * Foreground/Robustification:
-
- * Jasche, Lavaux, 2017, A&A (arXiv:1706.08971)
- * Porqueres, Kodi Ramanah, Jasche, Lavaux, 2019, A&A (arXiv: 1812.05113)
-
- * Cosmic expansion model:
-
- * Kodi Ramanah, Lavaux, Jasche, Wandelt, 2019, A&A (arXiv: 1808.07496)
-
- * Photometric redshifts
-
- * HADES with Photo-Z: Jasche & Wandelt, 2012, MNRAS, 425, 1042 (arXiv: 1106.2757)
-
- * Galaxy shear:
-
- * Porqueres, Heavens, Mortlock & Lavaux, 2021, MNRAS, 502, 3035 (arXiv 2011.07722)
- * Porqueres, Heavens, Mortlock & Lavaux, 2022, MNRAS, 509, 3194 (arXiv 2108.04825)
-
- * Cosmic velocity field:
-
- * Prideaux-Ghee, Leclercq, Lavaux, Heavens, Jasche, 2022, MNRAS (arXiv: 2204.00023)
- * Boruah, Lavaux, Hudson, 2022, MNRAS (arXiv 2111.15535)
-
- * BORG-PM
-
- * Jasche & Lavaux, 2019, A&A, 625, A64 (arXiv 1806.11117)
-
- * EFT bias model and likelihood
-
- * Schmidt, Elsner, Jasche, Nguyen, Lavaux, JCAP 01, 042 (2019) (arXiv:1808.02002)
- * Schmidt, Cabass, Jasche, Lavaux, JCAP 11, 008 (2020) (arXiv:2004.06707)
-
-* Data applications
-
- * SDSS Main Galaxy sample:
- * SDSS3 LRG sample:
-
- * Lavaux, Jasche & Leclercq, 2019, arXiv:1909.06396
-
- * 2M++ sample:
-
- * Lavaux & Jasche, 2016, MNRAS, 455, 3 (arXiv 1509.05040)
- * Jasche & Lavaux, 2019, A&A, 625, A64 (arXiv 1806.11117)
-
-
-*HADES* and *BORG* papers have a different listing.
-
-For a full listing of publications from the Aquila consortium, please check the
+The following section gives the references for the |ares|, |hades|, and |borg| algorithms and codes (including their direct application to real data, but excluding further scientific exploitation).
+For the full list of publications from the Aquila consortium, please check the
`Aquila website `_.
+ARES
+''''
+
+References for the |ares| algorithm (linear data model, Wiener filtering with Gibbs sampling/messenger field)
+are the following papers:
+
+* J. Jasche, F. S. Kitaura, B. D. Wandelt, T. A. Enßlin, *Bayesian power-spectrum inference for large-scale structure data*,
+ `Monthly Notices of the Royal Astronomical Society (2010) 406, 60 `_;
+ `arXiv:0911.2493 `_
+ (linear data model, Wiener filtering and power spectrum inference with Gibbs sampling)
+* J. Jasche, B. D. Wandelt, *Methods for Bayesian Power Spectrum Inference with Galaxy Surveys*,
+ `The Astrophysical Journal (2013) 779, 15 `_;
+ `arXiv:1306.1821 `_
+ (luminosity-dependent galaxy bias, calibration of noise levels, reversible jump algorithm)
+* J. Jasche, G. Lavaux, *Matrix-free large-scale Bayesian inference in cosmology*,
+ `Monthly Notices of the Royal Astronomical Society (2015) 447, 1204 `_;
+ `arXiv:1402.1763 `_
+ (inference with messenger field)
+* J. Jasche, G. Lavaux, *Bayesian power spectrum inference with foreground and target contamination treatment*,
+ `Astronomy and Astrophysics (2017) 606, A37 `_;
+ `arXiv:1706.08971 `_
+ (joint inference of density field and known foregrounds)
+
+HADES
+'''''
+
+References for the |hades| algorithm (log-normal data model, Hamiltonian Monte Carlo sampling, photometric redshift inference) are the following papers:
+
+* J. Jasche, F. S. Kitaura, *Fast Hamiltonian sampling for large-scale structure inference*,
+ `Monthly Notices of the Royal Astronomical Society (2010) 407, 29 `_;
+ `arXiv:0911.2496 `_
+ (HMC method paper)
+* J. Jasche, F. S. Kitaura, C. Li, T. A. Enßlin, *Bayesian non-linear large-scale structure inference of the Sloan Digital
+ Sky Survey Data Release 7*,
+ `Monthly Notices of the Royal Astronomical Society (2010) 409, 355 `_;
+ `arXiv:0911.2498 `_
+ (data application with log-normal data model)
+* J. Jasche, B. D. Wandelt, *Bayesian inference from photometric redshift surveys*,
+ `Monthly Notices of the Royal Astronomical Society (2012) 425, 1042 `_;
+ `arXiv:1106.2757 `_
+ (method paper: joint inference of density and photometric redshifts)
+
+BORG
+''''
+
+Methodological papers that shall be cited when referring to the |borg| algorithm (inference with a structure formation model and Hamiltonian Monte Carlo) are the following:
+
+* J. Jasche, B. D. Wandelt, *Bayesian physical reconstruction of initial conditions from large-scale structure surveys*,
+ `Monthly Notices of the Royal Astronomical Society (2013) 432, 894 `_;
+ `arXiv:1203.3639 `_
+ (original BORG method paper with differentiable LPT data model and HMC)
+* J. Jasche, F. Leclercq, B. D. Wandelt, *Past and present cosmic structure in the SDSS DR7 main sample*,
+ `Journal of Cosmology and Astroparticle Physics (2015) 01, 036 `_;
+ `arXiv:1409.6308 `_
+ (luminosity-dependent galaxy bias, power-law bias model, calibration of noise levels)
+* G. Lavaux, J. Jasche, *Unmasking the masked Universe: the 2M++ catalogue through Bayesian eyes*,
+ `Monthly Notices of the Royal Astronomical Society (2016) 455, 3169 `_;
+ `arXiv:1509.05040 `_
+ (data model with redshift-space distortions)
+* J. Jasche, G. Lavaux, *Physical Bayesian modelling of the non-linear matter distribution: New insights into the nearby universe*,
+ `Astronomy and Astrophysics (2019) 625, A64 `_;
+ `arXiv:1806.11117 `_
+ (BORGPM: particle-mesh data model, observer velocity sampling, "heating up" the likelihood)
+* G. Lavaux, J. Jasche, F. Leclercq, *Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data*,
+ `arXiv:1909.06396 `_
+ (data model with light-cone effects, quadratic form bias model)
+
+Data application papers of |borg| are the following:
+
+* J. Jasche, F. Leclercq, B. D. Wandelt, *Past and present cosmic structure in the SDSS DR7 main sample*,
+ `Journal of Cosmology and Astroparticle Physics (2015) 01, 036 `_;
+ `arXiv:1409.6308 `_
+ (application to SDSS DR7 main galaxy sample)
+* G. Lavaux, J. Jasche, *Unmasking the masked Universe: the 2M++ catalogue through Bayesian eyes*,
+ `Monthly Notices of the Royal Astronomical Society (2016) 455, 3169 `_;
+ `arXiv:1509.05040 `_
+ (application to 2M++, LPT data model)
+* J. Jasche, G. Lavaux, *Physical Bayesian modelling of the non-linear matter distribution: New insights into the nearby universe*,
+ `Astronomy and Astrophysics (2019) 625, A64 `_;
+ `arXiv:1806.11117 `_
+ (application to 2M++, PM data model)
+* G. Lavaux, J. Jasche, F. Leclercq, *Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data*,
+ `arXiv:1909.06396 `_
+ (application to SDSS3 BOSS, LPT data model)
+
+Additional papers extend the |borg| algorithm and shall be cited depending on the context. The list includes (but may not be limited to):
+
+* Foregrounds/Systematic effects:
+
+ * J. Jasche, G. Lavaux, *Bayesian power spectrum inference with foreground and target contamination treatment*,
+ `Astronomy and Astrophysics (2017) 606, A37 `_;
+ `arXiv:1706.08971 `_
+ (joint inference of density field and known foregrounds)
+ * N. Porqueres, D. Kodi Ramanah, J. Jasche, G. Lavaux, *Explicit Bayesian treatment of unknown foreground contaminations
+ in galaxy surveys*,
+ `Astronomy and Astrophysics (2019) 624, A115 `_;
+ `arXiv:1812.05113 `_
+ (robust likelihood for unknown foregrounds effects)
+
+* Cosmic expansion model (Alcock-Paczynski effect):
+
+ * D. Kodi Ramanah, G. Lavaux, J. Jasche, B. Wandelt, *Cosmological inference from Bayesian forward modelling
+ of deep galaxy redshift surveys*,
+ `Astronomy and Astrophysics (2019) 621, A69 `_;
+ `arXiv:1808.07496 `_
+ (Alcock-Paczynski expansion test)
+
+* Lyman-α forest:
+
+ * N. Porqueres, J. Jasche, G. Lavaux, T. Enßlin, *Inferring high-redshift large-scale structure dynamics from the Lyman-α forest*,
+ `Astronomy and Astrophysics (2019) 630, A151 `_;
+ `arXiv:1907.02973 `_ (Lyman alpha data model)
+ * N. Porqueres, O. Hahn, J. Jasche, G. Lavaux, *A hierarchical field-level inference approach to reconstruction from
+ sparse Lyman-α forest data*,
+ `Astronomy and Astrophysics (2020) 642, A139 `_;
+ `arXiv:2005.12928 `_
+
+* Weak lensing (cosmic shear):
+
+ * N. Porqueres, A. Heavens, D. Mortlock, G. Lavaux, *Bayesian forward modelling of cosmic shear data*,
+ `Monthly Notices of the Royal Astronomical Society (2021) 502, 3035 `_;
+ `arXiv:2011.07722 `_
+ (original BORG-WL paper)
+ * N. Porqueres, A. Heavens, D. Mortlock, G. Lavaux, *Lifting weak lensing degeneracies with a field-based likelihood*,
+ `Monthly Notices of the Royal Astronomical Society (2022) 509, 3194 `_;
+ `arXiv:2108.04825 `_
+ (cosmological parameter inference)
+ * N. Porqueres, A. Heavens, D. Mortlock, G. Lavaux, T. L. Makinen, *Field-level inference of cosmic shear with intrinsic
+ alignments and baryons*,
+ `arXiv:2304.04785 `_
+ (intrinsic alignments and baryons)
+
+* Cosmic velocity field:
+
+ * S. S. Boruah, G. Lavaux, M. J. Hudson, *Bayesian reconstruction of dark matter distribution from peculiar velocities:
+ accounting for inhomogeneous Malmquist bias*,
+ `Monthly Notices of the Royal Astronomical Society (2022) 517, 4529 `_;
+ `arXiv:2111.15535 `_
+ (linear model for the velocity field, inhomogeneous Malmquist bias, observational effects)
+ * J. Prideaux-Ghee, F. Leclercq, G. Lavaux, A. Heavens, J. Jasche, *Field-Based Physical Inference From Peculiar Velocity Tracers*,
+ `Monthly Notices of the Royal Astronomical Society (2023) 518, 4191 `_;
+ `arXiv:2204.00023 `_
+ (LPT structure formation model in the data model)
+
+* Primordial non-Gaussianity:
+
+ * A. Andrews, J. Jasche, G. Lavaux, F. Schmidt, *Bayesian field-level inference of primordial
+ non-Gaussianity using next-generation galaxy surveys*,
+ `Monthly Notices of the Royal Astronomical Society (2023) 520, 5746 `_;
+ `arXiv:2203.08838 `_ (local fNL sampling)
+
+* Photometric redshift inference:
+
+ * E. Tsaprazi, J. Jasche, G. Lavaux, F. Leclercq, *Higher-order statistics of the large-scale structure from photometric redshifts*,
+ `arXiv:2301.03581 `_
+ (photometric redshift sampling with a structure formation model)
+
+* Effective Field Theory (EFT) bias model and likelihood:
+
+ * F. Schmidt, F. Elsner, J. Jasche, N. M. Nguyen, G. Lavaux, *A rigorous EFT-based forward model for large-scale structure*,
+ `Journal of Cosmology and Astroparticle Physics (2019) 01, 042 `_;
+ `arXiv:1808.02002 `_ (EFT likelihood)
+ * F. Schmidt, G. Cabass, J. Jasche, G. Lavaux, *Unbiased cosmology inference from biased tracers using the EFT likelihood*,
+ `Journal of Cosmology and Astroparticle Physics (2020) 11, 008 `_;
+ `arXiv:2004.06707 `_ (biased tracers with EFT bias model and likelihood)
+
Acknowledgements
----------------