QTQt software include different systems model and statical exploration methods, this page list available models/methods and give a short explanation of each. (after the User Guide of QTQt, K. Gallagher)

Fission tracks annealing kinetic :

For predicting fission track annealing in apatite, the program includes :

• the original Durango apatite-based algorithm of Laslett et al. (1987)
• the multicompositional algorithms of Ketcham et al (2007)

And in zircon :

• Tagami et al (1998)
• Yamada (2007)

Currently, a given sample can be modelled with a constant composition (if appropriate). The composition could be taken as the average of measured single grain compositions or alternatively a single real sample could be divided up into multiple samples based on different compositions, for example, and then treated as multiple samples for modelling purposes. Similarly, a sample with both apatite and zircon data should be treated as 2 samples, choosing the appropriate annealing model for each.

Helium diffusion and alpha damage annealing kinetic :

For predicting He diffusion, standard diffusion equations are used (typically a spherical grain with the same surface area to volume ratio as the dimensions specified for a real grain). You can input kinetic parameters to simulate He diffusion in any mineral. The helium diffusion model also includes the recent developments on radiation damage trapping using fission track annealing as a proxy to recalibrate the helium diffusion coefficient.

Apatite models :

• Farley (2000), simple helium diffusion in a perfect crystal
• Flowers et al. (2009), diffusion perturbed by the alpha damaging (Shuster et al. (2006))
• Gautheron et al. (2009), diffusion perturbed by the alpha damaging (Shuster et al. (2006))
• Gerin et al. (2017), Gautheron model modified with a new alpha damage model
• Willett et al. (2017), Flowers model modified with a new alpha damage annealing model

Zircon models :

• Guenthner et al. (2013)
• Ginster et al. (2019)

Multi Dimensionnal Diffusion model (MDD) :

It is also possible to include 4He/3He degassing spectrum as part of the helium data modelling process. A similar approach is used for ⁴⁰Ar/³⁹Ar spectra and the modelling routines incorporate the MDD method of Lovera et al. (1989, 1991).

It is also possible to use the same routines for modelling diffusion in other systems, such as U-Pb in apatite and K-Ar (or Ar-Ar) in mica. This requires specifying the mineral and isotope systems either from a range of predefined values, or you can define a single parent-daughter pair by providing the appropriate decay constant, and diffusion parameters.

Vitrinite reflectance model :

Vitrinite reflectance data can be incorporated, being used either as a direct constraint on the inferred thermal histories, or it is possible just to predict vitrinite reflectance and make a qualitative comparison to the observed values. The default algorithm is from Sweeney and Burnham (1990), equivalent to EasyRo, but the more recent IKU model of Ritter et al. (1996) and the basin%Ro model of Neilsen et al. (2015) is also available.