SimQ¶
Quantum computing at Rust speed
SimQ is a high-performance quantum computing SDK written in Rust — designed to be 8–10× faster than Qiskit for variational algorithms, with type-safe circuit construction and first-class Python bindings.
use simq::QuantumCircuit;
fn main() {
// 3-qubit GHZ state
let mut qc = QuantumCircuit::new(3);
qc.h(0).cnot(0, 1).cnot(1, 2);
let result = qc.simulate_with_shots(1024).unwrap();
println!("{:?}", result.measurements.unwrap().sorted());
// [("000", 517), ("111", 507)]
}
import simq
builder = simq.CircuitBuilder(2)
builder.h(0)
builder.cx(0, 1)
circuit = builder.build()
simulator = simq.Simulator(simq.SimulatorConfig(shots=1024))
result = simulator.run(circuit)
print(result.state_vector)
Why SimQ?¶
Sparse state vectors, SIMD-optimized gate kernels, parallel execution, and compile-time gate matrix caching with ~0–5 ns matrix access.
Compile-time verification of quantum operations. Invalid circuits are caught before they ever run — often before they even compile.
Hybrid sparse/dense state representation lets you simulate up to 35–40 qubits on 32 GB of RAM.
Exact expectation values, automatic gradients, and ready-made VQE/QAOA helpers and optimizers.
The same circuit runs on the local simulator or real quantum hardware via the backend abstraction (IBM Quantum and more).
A familiar, Qiskit-like Python API backed by the full-speed Rust core — including noise models and visualization.
Explore the documentation¶
Install SimQ and run your first circuit in Rust or Python in under five minutes.
Circuits, simulation, observables, VQE/QAOA, the compiler, noise models, and hardware backends.
Runnable, end-to-end examples: Bell states, teleportation, H₂ ground-state VQE, MaxCut QAOA, and more.
How the eight workspace crates fit together — for contributors and the curious.
Development setup, coding standards, testing, and how to send your first pull request.
Rust API docs (rustdoc) and the Python binding reference.