# FRECKLL: Full and Reduced Exoplanet Chemical Kinetics distiLLed

Source: [FRECKLL: Full and Reduced Exoplanet Chemical Kinetics distiLLed](<https://www.sota2.com/research/paper/68fa46ff1e209131ce9249f8>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T06:06:08.752Z

Authors: Ahmed Faris Al-Refaie, Olivia Venot, Quentin Changeat, Billy Edwards

Published: 2022-09-22T17:45:00.000Z

## Abstract

We introduce a new Python 1D chemical kinetic code FRECKLL (Full and Reduced Exoplanet Chemical Kinetics distiLLed) to evolve large chemical networks efficiently. FRECKLL employs \`distillation' in computing the reaction rates, which minimizes the error bounds to the minimum allowed by double precision values ($\\epsilon \\leq 10^{-15}$). Compared to summation of rates with traditional algorithms like pairwise summation, distillation provides a tenfold reduction in solver time for both full and reduced networks. Both the full and reduced Venot2020 networks are packaged in FRECKLL as well as a TauREx 3.1 plugin for usage in forward modelling and retrievals of exoplanet atmospheres. We present TauREx retrievals performed on a simulated HD189733 JWST spectra using the full and reduced Venot2020 chemical networks and demonstrate the viability of total disequilibrium chemistry retrievals and the ability for JWST to detect disequilibrium processes.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2209.11203>)

[PDF](<https://arxiv.org/pdf/2209.11203.pdf>)