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qevedo-simulator

Python bindings of qvd, a fast quantum circuit simulator written in Rust. It installs as qevedo-simulator and imports as qevedo.simulator.

pip install qevedo-simulator          # add [numpy] for NumPy state vectors
from qevedo.simulator import Circuit, expectation, run, statevector

bell = Circuit(2).h(0).cx(0, 1).measure_all()
result = run(bell, shots=1000, seed=1)
print(result.counts, result.backend)  # {'00': ..., '11': ...} stabilizer

# OpenQASM 2 or 3 text works anywhere a circuit does.
result = run("""
OPENQASM 3.0;
include "stdgates.inc";
qubit[3] q;
bit[3] c;
h q[0];
cx q[0], q[1];
ccx q[0], q[1], q[2];
c = measure q;
""", shots=1000)

state = statevector(Circuit(3).h(0).cx(0, 1).t(2))  # NumPy complex128 array

# Expectation values by Pauli propagation, far beyond a state vector:
# a Pauli string, a {string: coefficient} dict or a Qiskit SparsePauliOp.
e = expectation(Circuit(2).h(0).cx(0, 1), {"Z0 Z1": 1.0, "X0 X1": 0.5})
print(e.value, e.truncated_one_norm)  # 1.5, and a bound on its error (0)

Clifford circuits can carry Pauli noise channels (x_error, y_error, z_error, pauli_channel_1, depolarize1, depolarize2, Stim's channels), sampled independently in every shot by the stabilizer backend. sample returns the raw measurement records, measurement-major like Stim's FlipSimulator, and to_stim writes the same circuit for Stim:

from qevedo.simulator import Circuit, sample

c = Circuit(3)
for _ in range(10):                      # a small repetition code
    c.reset(1).x_error(1, 0.001)
    c.cx(0, 1).depolarize2(0, 1, 0.001).cx(2, 1).depolarize2(2, 1, 0.001)
    c.x_error(1, 0.001).measure(1, c.num_clbits)
bits = sample(c, 100_000, seed=1)        # NumPy bool array, (10, 100000)
print(c.to_stim().splitlines()[:3])      # ['R 1', 'X_ERROR(0.001) 1', 'CX 0 1']

run chooses the simulation method automatically:

Backend For Scale on one workstation
stabilizer Clifford circuits, with Pauli noise tens of thousands of qubits
near_clifford Clifford circuits with few non-Clifford gates hundreds of qubits, ~30 active
statevector anything that fits in memory (AVX2 kernels, gate fusion) ~32 qubits
mps low-entanglement circuits 100+ qubits, approximate beyond χ

Pass backend= to force one. The result reports the method that ran, its timings, and the MPS fidelity estimate or the near-Clifford peak active qubits. Simulations release the GIL.

expectation propagates the observable backwards through the circuit (Cliffords for free, small coefficients dropped), for up to 1024 qubits: <Z62> of IBM's 127-qubit, 20-step kicked Ising circuit takes 0.25–9.6 s at the thresholds in the main README's benchmark.

x86-64 wheels are built for AVX2 + FMA processors (2013–2015 or newer); other x86-64 machines can build from source with a Rust toolchain.

License: MIT.

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