Quasi Quantum Computing
A revolutionary quantum circuit simulator powered by three independent neural network physics backends—Hamiltonian, Schrödinger, and Dirac—achieving exact constraint preservation without explicit enforcement.
Key Features
Neural Physics Backends
Three independently trained neural networks that preserve quantum constraints
Quantum Circuits
Full quantum gate library with entanglement support
Molecular Simulation
VQE and UCCSD calculations for molecular ground states
Constraint Preservation
Phase coherence, norm, and entropy preserved to machine precision
Quick Start
Core Capabilities
Stark Effect
Electric polarizability calculations with zero error
Relativistic QM
Dirac equation solver for hydrogen
QED Corrections
Lamb shift and anomalous magnetic moment
Visualization
Orbital and state evolution visualization
Entanglement
Entangled state analysis and entropy tracking
Benchmarks
Performance metrics and validation results
Research Foundation
QC is built on peer-reviewed research demonstrating that neural network backends can preserve quantum mechanical constraints without explicit enforcement. All three backends—Hamiltonian, Schrödinger, and Dirac—produce identical results across standard algorithms and achieve 100% correlation energy recovery for molecular hydrogen.Constraint Preservation
Neural backends preserve phase, norm, and entropy
Extended Capabilities
Stark effect, QED corrections, and polyatomic molecules
Get Started
Installation Guide
Set up your environment and dependencies
Quickstart Tutorial
Run your first quantum simulation in minutes
API Reference
Explore the complete API documentation
View on GitHub
Contribute to the open-source project