StateVector vs MPS vs Stabilizer Simulation | Choosing Optimal Backends
Quick Technical Answer:
Quantum simulation engines balance precision against qubit capacity: StateVector computes exact 2^N amplitudes up to ~30 qubits; Matrix Product States (MPS) contract low-entanglement systems up to 100+ qubits; and Stabilizer Clifford engines simulate 1,000+ qubits with zero truncation error.
Formula / Unitary:
\text{StateVector: } O(2^N), \quad \text{MPS: } O(N d \chi^2), \quad \text{Stabilizer: } O(N^2)
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Simulation Engine Benchmark Matrix
| Backend Engine | Max Practical Qubits | Memory Scaling | Gate Support | Entanglement Limit |
|---|---|---|---|---|
| Exact StateVector | 30–32 Qubits | O(2^N) Exponential (16GB @ 30Q) | Universal (All Gates) | Arbitrary (Maximal Entanglement) |
| Matrix Product State (MPS) | 100+ Qubits | O(N · χ²) Polynomial | Universal with Truncation | 1D Area-Law (Low/Moderate) |
| Stabilizer Tableau | 1,000+ Qubits | O(N²) Polynomial | Clifford Group (H, S, CX) | Arbitrary within Clifford |
| Density Matrix | 15–16 Qubits | O(4^N) Exponential (16GB @ 15Q) | Universal Open Systems | Includes Environmental Noise |
Frequently Asked Questions
How does Itachi Quantum Studio select the simulation backend?
The platform offers an 'Auto' backend selector that analyzes circuit gate types, qubit width, and entanglement cuts, automatically delegating to Stabilizer for Clifford circuits, MPS for large widths, or StateVector for high entanglement.