Devanik21/The-Schrodinger-Paradox
The Schrödinger Dream is a high-precision computational framework designed for solving the Time-Independent Schrödinger Equation (TISE) using a novel hybrid of Geometric Deep Learning and Generative Flow Matching.
What's novel
The Schrödinger Dream is a high-precision computational framework designed for solving the Time-Independent Schrödinger Equation (TISE) using a novel hybrid of Geometric Deep Learning and Generative Flow Matching.
Code Analysis
10 files read · 7 roundsA high-performance PyTorch implementation of Neural Quantum States (NQS) using Selective State Space Models (Mamba) to solve the electronic Schrödinger equation for atoms and molecules via Variational Monte Carlo.
Strengths
The project demonstrates genuine algorithmic innovation by integrating Mamba-style SSMs into quantum chemistry, offering a novel O(N log N) approach to electron correlation. The code is well-documented with rigorous physics-informed constraints (Kato cusp, Slater determinants) and includes robust stability mechanisms like dynamic energy multipliers and walker resets.
Weaknesses
The project lacks an automated testing suite, relying instead on manual verification against NIST benchmarks. Some error handling is defensive but not exhaustive, and the dependency list is minimal which may obscure required specific versions or auxiliary libraries for full functionality.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
270
Contributors
3
Files
25
Active weeks
5
Repository
Language
Python
Stars
1
Forks
0
License
Apache-2.0