28.4 % admired Fortran in StackOverflow survey

[septc]

I often see python + some fast libraries have been used rather often for computationally “heavy” calculations. For example, a recent one (for climate modeling, by Google Research, published recently in Nature) is:

https://research.google/blog/fast-accurate-climate-modeling-with-neuralgcm/

• Neural general circulation models for weather and climate | Nature
• Google AI predicts long-term climate trends and weather — in minutes
• [2311.07222] Neural General Circulation Models for Weather and Climate
• Code (Python/JAX)
  GitHub - google-research/neuralgcm: Hybrid ML + physics model of the Earth's atmosphere

I remember the Boltzmann generator (a kind of canonical sampling method for molecular/protein configurations) also used Python (together with ML libraries):

• https://www.science.org/doi/full/10.1126/science.aaw1147
• [1812.01729] Boltzmann Generators -- Sampling Equilibrium States of Many-Body Systems with Deep Learning
• GitHub - noegroup/bgflow: Boltzmann Generators and Normalizing Flows in PyTorch

Another example may be FermiNet,

FermiNet: Quantum Physics and Chemistry from First Principles

• Phys. Rev. Research 2, 033429 (2020) - Ab initio solution of the many-electron Schr\"odinger equation with deep neural networks
• Code: GitHub - google-deepmind/ferminet: An implementation of the Fermionic Neural Network for ab-initio electronic structure calculations