Per-paper detail pages

For each paper progenax cites, this section provides:

• The full bibliographic reference.

• A paraphrased abstract.

• A list of progenax modules and chapters that depend on the paper.

• Notes on caveats, conventions, and use cases.

The pages are organised alphabetically by first-author surname.

Spatial profiles¶

• Plummer (1911)

• King (1966)

• Gieles & Zocchi (2015)

• Elson, Fall & Freeman (1987)

Velocity distribution functions¶

• Merritt (1985)

• Michie (1963)

• Binney & Mamon (1982)

• Dejonghe (1987)

• Strigari, Bullock & Kaplinghat (2007)

Initial mass functions¶

• Salpeter (1955)

• Kroupa (2001)

• Chabrier (2003)

• Maschberger (2013)

• Parravano, McKee & Hollenbach (2011)

Environment-dependent IMF (IGIMF)¶

• Marks et al. (2012)

• Marks & Kroupa (2012)

• Jeřábková et al. (2018)

Binaries¶

• Duquennoy & Mayor (1991)

• Kroupa (1995a)

• Sana et al. (2012)

• Moe & Di Stefano (2017)

• Moe, Kratter & Badenes (2019)

• Raghavan et al. (2010)

• Heggie (1975)

Tidal fields & substructure & mass segregation¶

• King (1962)

• Küpper, Maschberger, Kroupa & Baumgardt (2011)

• Cartwright & Whitworth (2004)

• Goodwin & Whitworth (2004)

• Lomax, Bates & Whitworth (2018)

• Allison et al. (2009)

• Baumgardt, De Marchi & Kroupa (2008)

• Baumgardt & Makino (2003)

Gravoturbulence¶

• Federrath et al. (2010)

• Federrath & Klessen (2012)

• Kritsuk, Norman & Wagner (2011)

• Tan, Krumholz & McKee (2006)

• Kim & Ryu (2005)

• Heyer et al. (2009)

• Burkhart (2018)

• Burkhart & Mocz (2019)

• Parmentier & Pasquali (2020)

• Padoan & Nordlund (2011)

• Kainulainen, Federrath & Henning (2014)

Gaussianization & log-density inference¶

The differentiable inference layer (gravoturb; see Differentiable inference — natal cloud parameters from cluster substructure) predicts log-density statistics analytically and differentiates them. This lineage grounds that machinery: lognormal fields, the Hermite/Gaussianization of the two-point function, the information-optimality of the log transform, the counts-in-cells likelihood, and the simulation-based-inference alternative.

• Coles & Jones (1991)

• Szapudi & Pan (2004)

• Szapudi, Pan, Prunet & Budavári (2005)

• Neyrinck, Szapudi & Szalay (2009)

• Neyrinck, Szapudi & Szalay (2011)

• Carron & Szapudi (2013)

• Carron & Szapudi (2014)

• Carron, Wolk & Szapudi (2014)

• Bairagi & Wandelt (2026)

Stellar evolution¶

• Tout, Pols, Eggleton & Han (1996)

• Hurley, Pols & Tout (2000)

• Hurley, Tout & Pols (2002)

Calibration & convergence diagnostics¶

The gravoturb trustworthiness arc (workstream ①; see Differentiable inference — natal cloud parameters from cluster substructure) validates the differentiable-inference engine with simulation-based calibration (SBC) and HMC convergence diagnostics. These papers ground that machinery: the SBC rank statistic, the graphical uniformity test with simultaneous bands, and the data-conditional posterior-SBC extension.

• Talts et al. (2018)

• Säilynoja et al. (2022)

• Säilynoja et al. (2026)

Reference constants & units¶

• Prša et al. (2016)

How to add a new per-paper page¶

1. Add the BibTeX entry to references.bib.

2. Create a new file 99-bibliography/per-paper/<author>-<year>.md following the template of an existing page.

3. Add a link to this index under the appropriate category.

4. Reference the new page from any chapters that cite the paper.

The per-paper detail page format is:

• Frontmatter with title and description.

• First section. admonition block with title, authors, reference, DOI, optional arXiv.

• Abstract (paraphrased). 4–6 sentences in your own words; do not copy the publisher abstract.

• Use in progenax. Bullet list of modules and chapters that cite the paper.

• Notes. Caveats, conventions, edge cases.

For an exemplar see Parmentier & Pasquali (2020), which has the fullest treatment because of its central role in the BM19 framework.