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Introduction to QC

QC (Quasi Quantum Computing) is a quantum circuit simulator that uses neural network physics backends to simulate quantum systems on classical hardware. Unlike traditional quantum simulators, QC leverages three independently trained neural networks to model quantum mechanical evolution through different physical formulations.

What is QC?

QC is a collapse-free quantum computer simulator that maintains quantum states in the full joint Hilbert space without wavefunction collapse. The simulator represents n-qubit states as tensors in C^(2^n) and uses neural network backends trained on physics principles to evolve quantum states. The key innovation is that measurement is non-destructive - the simulator reads Born probabilities without collapsing the quantum state, allowing you to observe quantum systems while preserving their coherence.

Key Innovations

Neural Physics Backends

QC implements three independently trained neural network backends, each modeling quantum evolution through a different physical formulation:

Hamiltonian Backend

Spectral convolution network that applies a learned Hamiltonian operator H|ψ⟩ using Fourier-domain operations

Schrödinger Backend

2-channel network trained to propagate wavefunctions according to the Schrödinger equation

Dirac Backend

8-channel relativistic network operating on 4-component spinors for Dirac equation evolution

Constraint Preservation

The backends preserve fundamental quantum mechanical constraints without explicit enforcement:
  • Phase coherence: 22/22 phase coherence tests passed
  • Unitarity: Norm preserved across all gate operations
  • Entanglement: True multi-qubit entanglement with joint Hilbert space representation
  • Response properties: Electric polarizability matches exact diagonalization with zero error
All three backends produce identical results across standard quantum algorithms, demonstrating structural consistency beyond simple constraint satisfaction.

Architecture Overview

State Representation

The quantum state is stored as a tensor of shape (2^n, 2, G, G):
  • Dimension 0: Computational basis index k ∈ {0, …, 2^n - 1}
  • Dimension 1: Complex channels (real, imaginary)
  • Dimension 2-3: Spatial wavefunction grid (G × G points)
Each amplitude αₖ is encoded as a 2D spatial wavefunction on a 16×16 grid. Born probabilities are computed by integrating the squared modulus over the spatial grid:
P(k) = ∫∫ |αₖ(x,y)|² dx dy
This representation correctly supports:
  • Superposition: Multiple basis states with non-zero amplitude
  • Entanglement: Amplitudes do not factorize across qubits
  • Coherent gates: Exact permutation and mixing of amplitudes

Component Structure

1

State Initialization

Create quantum state in computational basis using JointStateFactory
2

Circuit Construction

Build gate sequence with QuantumCircuit using quantum gates (H, CNOT, etc.)
3

Backend Selection

Choose physics backend: hamiltonian, schrodinger, or dirac
4

Execution

Apply gates sequentially using selected backend’s evolution operators
5

Measurement

Non-destructive Born-rule readout of probability distribution

Validated Results

QC has been experimentally validated across multiple domains:

Quantum Algorithms

  • Bell States: P(|00⟩) = 0.5, P(|11⟩) = 0.5, entropy = 1 bit
  • GHZ States: Perfect 3-qubit entanglement
  • Grover’s Algorithm: 94.53% success probability on marked state |101⟩
  • Quantum Fourier Transform: Uniform distribution across 8 basis states

Molecular Simulation

  • H₂ Ground State: VQE recovers 100% of correlation energy
  • Error: |VQE - FCI| = 1.31×10⁻¹¹ Ha (machine precision)
  • Stark Effect: Electric polarizability α = 2.750 a₀³ (exact match with reference)

Extended Capabilities

  • Polyatomic molecules: H₂O, NH₃, CH₄ processed through same pipeline
  • QED corrections: Anomalous magnetic moment with 0.3% relative error
  • Visualization: Publication-quality figures matching numerical logs
QC is a research simulator designed for quantum algorithm development and validation. It scales to ~8 qubits on classical hardware due to the 2^n dimensional Hilbert space.

Use Cases

QC is ideal for:
  • Quantum algorithm prototyping: Test quantum circuits before running on real hardware
  • Educational demonstrations: Visualize quantum state evolution without collapse
  • Molecular chemistry: VQE-based ground state calculations for small molecules
  • Method validation: Compare neural backend results with analytical solutions

What’s Next?

Installation

Install QC and set up your environment with all dependencies

Quick Start

Run your first quantum simulation in minutes

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