Scientific-Computing

🎄🎁 Advent of Open Source – Day 23/24: Making efficient Pfaffian computations accessible to Python users with optimized C and FORTRAN under the hood.

🎄🎁 Advent of Open Source – Day 20/24: Simplifying complex computational workflows with automatic DAG construction and parallelization.

🎄🎁 Advent of Open Source – Day 17/24: Scaling adaptive sampling to 100,000+ cores with a novel meta-scheduling approach.

🎄🎁 Advent of Open Source – Day 16/24: Revolutionizing parameter space exploration with adaptive sampling algorithms.

🎄🎁 Advent of Open Source – Day 11/24: Contributing to the backbone of scientific Python through the conda-forge community.

🎄🎁 Advent of Open Source – Day 07/24: Solving a common performance pitfall in scientific computing with a tiny yet powerful tool.

🎄🎁 Advent of Open Source – Day 06/24: Making scientific research truly reproducible with fully open-source code and data.

Exploring quantum device simulations, adaptive sampling, and neural networks to create beautiful thesis covers