Related papers: FRECKLL: Full and Reduced Exoplanet Chemical Kinet…
Constraining the chemical structure of exoplanetary atmospheres is pivotal for interpreting spectroscopic data and understanding planetary evolution. Traditional retrieval methods often assume thermochemical equilibrium or free profiles,…
We present an open-source and validated chemical kinetics code for studying hot exoplanetary atmospheres, which we name VULCAN. It is constructed for gaseous chemistry from 500 to 2500 K using a reduced C-H-O chemical network with about 300…
Thermochemical equilibrium is one of the most commonly used assumptions in current exoplanet retrievals. As the James Webb Space Telescope (JWST) and Ariel launch draw near, assessing the underlying biases and assumptions made when applying…
Characterizing exoplanetary atmospheres via Bayesian retrievals requires assuming some chemistry model, such as thermochemical equilibrium or parameterized abundances. The higher-resolution data offered by upcoming telescopes enables more…
Astrochemical modeling is needed for understanding the formation and evolution of interstellar molecules, and for extracting physical information from spectroscopic observations of interstellar clouds. The modeling usually involves handling…
We present high-precision chemical abundances for 25 FGK-type stars hosting exoplanets observed in JWST Cycle 3 programs and all GTO and DDT programs from Cycles 1-3, based on high-resolution, high signal-to-noise ratio optical spectra from…
In this era of exoplanet characterisation with JWST, the need for a fast implementation of classical forward models to understand the chemical and physical processes in exoplanet atmospheres is more important than ever. Notably, the…
We aimed to build a new and updated C0-C2 chemical network to study the CHON disequilibrium chemistry of warm and hot exoplanet atmospheres that relies on extensively validated and recent state-of-the-art combustion networks. The…
Residual connection has been extensively studied and widely applied at the model architecture level. However, its potential in the more challenging data-centric approaches remains unexplored. In this work, we introduce the concept of Data…
Growing evidence has indicated that the global composition distribution plays an indisputable role in interpreting observational data. 3D general circulation models (GCMs) with a reliable treatment of chemistry and clouds are particularly…
The unprecedented wavelength coverage and sensitivity of the James Webb Space Telescope (JWST) permits to measure the absorption features of a wide range of condensate species from Silicates to Titan tholins. Atmospheric retrievals are…
We present FerKD, a novel efficient knowledge distillation framework that incorporates partial soft-hard label adaptation coupled with a region-calibration mechanism. Our approach stems from the observation and intuition that standard data…
A novel search method for large polarization kernels is proposed. The algorithm produces a kernel with given partial distances by employing the depth-first search combined with the computation of coset leaders weight tables and sufficient…
Exoplanet atmospheric modeling is advancing from chemically diverse one-dimensional (1D) models to three-dimensional (3D) global circulation models (GCMs), which are crucial for interpreting observations from facilities like the James Webb…
In this paper, we present BitNet Distillation (BitDistill), a lightweight pipeline that fine-tunes off-the-shelf full-precision LLMs (e.g., Qwen) into 1.58-bit precision (i.e., ternary weights {-1, 0, 1}) for specific downstream tasks,…
Predicting the degradation processes of molecules over long timescales is a key aspect of industrial materials design. However, it is made computationally challenging by the need to construct large networks of chemical reactions that are…
This letter proposes a novel communication-efficient and privacy-preserving distributed machine learning framework, coined Mix2FLD. To address uplink-downlink capacity asymmetry, local model outputs are uploaded to a server in the uplink as…
Chemical reaction datasets such as USPTO suffer from substantial incompleteness, frequently missing byproducts, co-reactants, and stoichiometric coefficients. This limits their applicability and reliability in downstream applications. Here,…
Several chemical networks have been developed to study warm (exo)planetary atmospheres. The kinetics of the reactions related to the methanol chemistry included in these schemes have been questioned. The goal of this paper is to update the…
Knowledge distillation (KD) is the process of transferring knowledge from a large model to a small one. It has gained increasing attention in the natural language processing community, driven by the demands of compressing ever-growing…