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use ndarray::{Array1, Array2, Array3, ArrayViewMut2};
use numpy::{
IntoPyArray, PyArray1, PyArray2, PyArray3, PyReadonlyArray1, PyReadonlyArray2, PyReadonlyArray3,
PyReadonlyArray4,
};
use pyo3::prelude::*;
use rand::distributions::WeightedIndex;
use rand::prelude::*;
use rayon::prelude::*;
use thiserror::Error;
pub mod circuit;
pub mod execution;
pub use circuit::*;
pub use execution::*;
/// Custom error type for kernel operations
#[derive(Error, Debug)]
pub enum KernelError {
#[error("Circuit error: {0}")]
CircuitError(#[from] crate::circuit::CircuitError),
#[error("Numpy array conversion error: {0}")]
NumpyError(String),
#[error("Invalid dimensions: expected {expected}, got {actual}")]
DimensionError { expected: String, actual: String },
#[error("Qubit index {0} out of range for {1}-qubit system")]
QubitRangeError(usize, usize),
#[error("Probability validation failed: {0}")]
ProbabilityError(String),
#[error("Serialization error: {0}")]
SerializationError(String),
}
/// Square each element on CPU (baseline kernel; also validates numpy interop).
#[pyfunction]
fn square_u32<'py>(
py: Python<'py>,
x: PyReadonlyArray1<'py, u32>,
) -> PyResult<&'py PyArray1<u32>> {
let x = x.as_array();
let out: Array1<u32> = py.allow_threads(|| {
if let Some(x_slice) = x.as_slice() {
let mut out = vec![0u32; x_slice.len()];
out.par_iter_mut()
.enumerate()
.for_each(|(i, dst)| *dst = x_slice[i].wrapping_mul(x_slice[i]));
Array1::from(out)
} else {
x.mapv(|v| v.wrapping_mul(v))
}
});
Ok(out.into_pyarray_bound(py).into_gil_ref())
}
/// Apply a single-qubit Pauli channel (I/X/Y/Z) to a statevector via Monte Carlo sampling.
///
/// - `psi`: complex128 statevector encoded as shape (2^n, 2) with columns [re, im].
/// - `target_qubit`: 0 = least-significant bit.
/// - `probs`: length-4 probabilities for [pI, pX, pY, pZ]. Must sum ~ 1.
/// - `seed`: RNG seed for reproducibility.
///
/// Returns a new statevector with the sampled Pauli applied.
#[pyfunction]
fn apply_pauli_channel_statevector<'py>(
py: Python<'py>,
psi: PyReadonlyArray2<'py, f64>,
n_qubits: usize,
target_qubit: usize,
probs: PyReadonlyArray1<'py, f64>,
seed: u64,
) -> PyResult<&'py PyArray2<f64>> {
let psi = psi.as_array();
let probs = probs.as_array();
if psi.ndim() != 2 || psi.shape()[1] != 2 {
return Err(pyo3::exceptions::PyValueError::new_err(
"psi must have shape (2^n, 2) with columns [re, im]",
));
}
let dim = 1usize << n_qubits;
if psi.shape()[0] != dim {
return Err(pyo3::exceptions::PyValueError::new_err(
"psi first dimension must be 2^n_qubits",
));
}
if target_qubit >= n_qubits {
return Err(pyo3::exceptions::PyValueError::new_err(
"target_qubit out of range",
));
}
if probs.len() != 4 {
return Err(pyo3::exceptions::PyValueError::new_err(
"probs must have length 4",
));
}
let w = WeightedIndex::new(probs.iter().cloned()).map_err(|e| {
pyo3::exceptions::PyValueError::new_err(format!("invalid probs: {e}"))
})?;
let mut rng = StdRng::seed_from_u64(seed);
let choice = w.sample(&mut rng);
let out: Array2<f64> = py.allow_threads(|| {
// Copy into owned array and apply the chosen Pauli.
let mut out: Array2<f64> = psi.to_owned();
match choice {
0 => {} // I
1 => apply_x(out.view_mut(), target_qubit),
2 => apply_y(out.view_mut(), target_qubit),
3 => apply_z(out.view_mut(), target_qubit),
_ => unreachable!(),
}
out
});
Ok(out.into_pyarray_bound(py).into_gil_ref())
}
#[derive(Clone, Copy, Debug, Default)]
struct C64 {
re: f64,
im: f64,
}
#[inline]
fn c(re: f64, im: f64) -> C64 {
C64 { re, im }
}
#[inline]
fn c_add(a: C64, b: C64) -> C64 {
c(a.re + b.re, a.im + b.im)
}
#[inline]
fn c_mul(a: C64, b: C64) -> C64 {
c(a.re * b.re - a.im * b.im, a.re * b.im + a.im * b.re)
}
#[inline]
fn c_conj(a: C64) -> C64 {
c(a.re, -a.im)
}
/// Apply a single-qubit Kraus channel to a density matrix:
///
/// ρ' = Σ_i K_i ρ K_i†
///
/// - `rho`: complex128 density matrix encoded as shape (2^n, 2^n, 2) with last dim [re, im]
/// - `kraus_ops`: complex128 Kraus matrices encoded as shape (k, 2, 2, 2)
/// - `target_qubit`: 0 = least-significant bit
#[pyfunction]
fn apply_kraus_1q_density_matrix<'py>(
py: Python<'py>,
rho: PyReadonlyArray3<'py, f64>,
n_qubits: usize,
target_qubit: usize,
kraus_ops: PyReadonlyArray4<'py, f64>,
) -> PyResult<&'py PyArray3<f64>> {
let rho = rho.as_array();
let kraus = kraus_ops.as_array();
if rho.ndim() != 3 || rho.shape()[2] != 2 {
return Err(pyo3::exceptions::PyValueError::new_err(
"rho must have shape (2^n, 2^n, 2) with last dim [re, im]",
));
}
let dim = 1usize << n_qubits;
if rho.shape()[0] != dim || rho.shape()[1] != dim {
return Err(pyo3::exceptions::PyValueError::new_err(
"rho must have shape (2^n, 2^n, 2)",
));
}
if target_qubit >= n_qubits {
return Err(pyo3::exceptions::PyValueError::new_err(
"target_qubit out of range",
));
}
if kraus.ndim() != 4 || kraus.shape()[1] != 2 || kraus.shape()[2] != 2 || kraus.shape()[3] != 2
{
return Err(pyo3::exceptions::PyValueError::new_err(
"kraus_ops must have shape (k, 2, 2, 2)",
));
}
let out: Array3<f64> = py.allow_threads(|| {
let bit = 1usize << target_qubit;
let mut out = Array3::<f64>::zeros((dim, dim, 2));
for r0 in 0..dim {
if (r0 & bit) != 0 {
continue;
}
let r1 = r0 ^ bit;
for c0 in 0..dim {
if (c0 & bit) != 0 {
continue;
}
let c1 = c0 ^ bit;
// Load 2x2 block
let r00 = c(rho[[r0, c0, 0]], rho[[r0, c0, 1]]);
let r01 = c(rho[[r0, c1, 0]], rho[[r0, c1, 1]]);
let r10 = c(rho[[r1, c0, 0]], rho[[r1, c0, 1]]);
let r11 = c(rho[[r1, c1, 0]], rho[[r1, c1, 1]]);
let mut o00 = C64::default();
let mut o01 = C64::default();
let mut o10 = C64::default();
let mut o11 = C64::default();
for ki in 0..kraus.shape()[0] {
let k00 = c(kraus[[ki, 0, 0, 0]], kraus[[ki, 0, 0, 1]]);
let k01 = c(kraus[[ki, 0, 1, 0]], kraus[[ki, 0, 1, 1]]);
let k10 = c(kraus[[ki, 1, 0, 0]], kraus[[ki, 1, 0, 1]]);
let k11 = c(kraus[[ki, 1, 1, 0]], kraus[[ki, 1, 1, 1]]);
// temp = K * rho_block
let t00 = c_add(c_mul(k00, r00), c_mul(k01, r10));
let t01 = c_add(c_mul(k00, r01), c_mul(k01, r11));
let t10 = c_add(c_mul(k10, r00), c_mul(k11, r10));
let t11 = c_add(c_mul(k10, r01), c_mul(k11, r11));
// out_block = temp * K†
let ck00 = c_conj(k00);
let ck01 = c_conj(k01);
let ck10 = c_conj(k10);
let ck11 = c_conj(k11);
o00 = c_add(o00, c_add(c_mul(t00, ck00), c_mul(t01, ck01)));
o01 = c_add(o01, c_add(c_mul(t00, ck10), c_mul(t01, ck11)));
o10 = c_add(o10, c_add(c_mul(t10, ck00), c_mul(t11, ck01)));
o11 = c_add(o11, c_add(c_mul(t10, ck10), c_mul(t11, ck11)));
}
out[[r0, c0, 0]] = o00.re;
out[[r0, c0, 1]] = o00.im;
out[[r0, c1, 0]] = o01.re;
out[[r0, c1, 1]] = o01.im;
out[[r1, c0, 0]] = o10.re;
out[[r1, c0, 1]] = o10.im;
out[[r1, c1, 0]] = o11.re;
out[[r1, c1, 1]] = o11.im;
}
}
out
});
Ok(out.into_pyarray_bound(py).into_gil_ref())
}
fn apply_x(mut psi: ArrayViewMut2<f64>, target: usize) {
let dim = psi.shape()[0];
let bit = 1usize << target;
// swap amplitudes where that bit differs: i <-> i^bit
// To avoid double swaps, only process i where bit is 0.
for i in 0..dim {
if (i & bit) != 0 {
continue;
}
let j = i ^ bit;
let a_re = psi[[i, 0]];
let a_im = psi[[i, 1]];
let b_re = psi[[j, 0]];
let b_im = psi[[j, 1]];
psi[[i, 0]] = b_re;
psi[[i, 1]] = b_im;
psi[[j, 0]] = a_re;
psi[[j, 1]] = a_im;
}
}
fn apply_z(mut psi: ArrayViewMut2<f64>, target: usize) {
let dim = psi.shape()[0];
let bit = 1usize << target;
for i in 0..dim {
if (i & bit) == 0 {
continue;
}
psi[[i, 0]] = -psi[[i, 0]];
psi[[i, 1]] = -psi[[i, 1]];
}
}
fn apply_y(mut psi: ArrayViewMut2<f64>, target: usize) {
// Y = iXZ; action:
// |0> -> i|1>, |1> -> -i|0>
let dim = psi.shape()[0];
let bit = 1usize << target;
for i in 0..dim {
if (i & bit) != 0 {
continue;
}
let j = i ^ bit;
// a = psi[i], b = psi[j]
let a_re = psi[[i, 0]];
let a_im = psi[[i, 1]];
let b_re = psi[[j, 0]];
let b_im = psi[[j, 1]];
// psi[i] = -i * b
// (-i)(b_re + i b_im) = b_im - i b_re
psi[[i, 0]] = b_im;
psi[[i, 1]] = -b_re;
// psi[j] = i * a
// i(a_re + i a_im) = -a_im + i a_re
psi[[j, 0]] = -a_im;
psi[[j, 1]] = a_re;
}
}
/// Execute a quantum circuit on a statevector
#[pyfunction(signature = (circuit_json, initial_state=None))]
fn execute_quantum_circuit<'py>(
py: Python<'py>,
circuit_json: &str,
initial_state: Option<PyReadonlyArray2<'py, f64>>,
) -> PyResult<&'py PyArray2<f64>> {
let circuit = QuantumCircuit::from_json(circuit_json)
.map_err(|e| pyo3::exceptions::PyValueError::new_err(format!("Circuit parsing error: {}", e)))?;
// Copy initial state to owned to move into thread if provided
let init_state_owned = initial_state.map(|arr| arr.as_array().to_owned());
let final_state = py.allow_threads(|| {
execute_circuit(&circuit, init_state_owned.as_ref())
.map_err(|e| pyo3::exceptions::PyValueError::new_err(format!("Execution error: {}", e)))
})?;
Ok(final_state.into_pyarray_bound(py).into_gil_ref())
}
/// Apply multi-qubit correlated Pauli noise
#[pyfunction]
fn apply_correlated_pauli_noise_statevector<'py>(
py: Python<'py>,
psi: PyReadonlyArray2<'py, f64>,
n_qubits: usize,
error_probs: PyReadonlyArray2<'py, f64>, // Shape: (2^n, 2^n) correlation matrix
seed: u64,
) -> PyResult<&'py PyArray2<f64>> {
let psi_owned = psi.as_array().to_owned();
let error_probs_owned = error_probs.as_array().to_owned();
if error_probs_owned.shape() != &[1 << n_qubits, 1 << n_qubits] {
return Err(pyo3::exceptions::PyValueError::new_err(
"error_probs must be (2^n, 2^n)"
));
}
let out = py.allow_threads(|| {
// Sample error pattern from correlation matrix
let error_pattern = sample_correlated_error(&error_probs_owned, seed);
// Apply the sampled Pauli error
let mut out = psi_owned;
apply_pauli_error_pattern(out.view_mut(), error_pattern, n_qubits);
out
});
Ok(out.into_pyarray_bound(py).into_gil_ref())
}
/// Apply CNOT gate error (bit flip on control + target with correlation)
#[pyfunction]
fn apply_cnot_error_statevector<'py>(
py: Python<'py>,
psi: PyReadonlyArray2<'py, f64>,
n_qubits: usize,
control: usize,
target: usize,
error_prob: f64,
seed: u64,
) -> PyResult<&'py PyArray2<f64>> {
let mut out = psi.as_array().to_owned();
py.allow_threads(|| {
apply_cnot_gate_error(out.view_mut(), n_qubits, control, target, error_prob, seed);
});
Ok(out.into_pyarray_bound(py).into_gil_ref())
}
/// Compute expectation value of a Pauli string
#[pyfunction]
fn expectation_value_pauli_string_py<'py>(
py: Python<'py>,
state: PyReadonlyArray2<'py, f64>,
pauli_string: &str,
) -> PyResult<f64> {
let state_owned = state.as_array().to_owned();
py.allow_threads(|| {
expectation_value_pauli_string(&state_owned, pauli_string)
.map_err(|e| pyo3::exceptions::PyValueError::new_err(format!("Expectation error: {}", e)))
})
}
fn sample_correlated_error<T: ndarray::Data<Elem = f64>>(
error_probs: &ndarray::ArrayBase<T, ndarray::Ix2>,
seed: u64,
) -> u64 {
let mut rng = StdRng::seed_from_u64(seed);
let flat_probs = error_probs.as_slice().unwrap();
let dist = WeightedIndex::new(flat_probs.iter().cloned()).unwrap();
dist.sample(&mut rng) as u64
}
fn apply_pauli_error_pattern(mut psi: ArrayViewMut2<f64>, error_pattern: u64, n_qubits: usize) {
for qubit in 0..n_qubits {
let pauli_type = (error_pattern >> (qubit * 2)) & 0x3;
match pauli_type {
0 => {} // I
1 => apply_pauli_x(&mut psi, qubit, n_qubits), // X
2 => apply_pauli_y(&mut psi, qubit, n_qubits), // Y
3 => apply_pauli_z(&mut psi, qubit, n_qubits), // Z
_ => unreachable!(),
}
}
}
fn apply_cnot_gate_error(
mut psi: ArrayViewMut2<f64>,
n_qubits: usize,
control: usize,
target: usize,
error_prob: f64,
seed: u64,
) {
let mut rng = StdRng::seed_from_u64(seed);
if rng.r#gen::<f64>() < error_prob {
// Apply correlated error: flip both control and target
apply_pauli_x(&mut psi, control, n_qubits);
apply_pauli_x(&mut psi, target, n_qubits);
}
}
#[pymodule]
fn rust_kernels(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
m.add_function(wrap_pyfunction!(square_u32, m)?)?;
m.add_function(wrap_pyfunction!(apply_pauli_channel_statevector, m)?)?;
m.add_function(wrap_pyfunction!(apply_kraus_1q_density_matrix, m)?)?;
m.add_function(wrap_pyfunction!(execute_quantum_circuit, m)?)?;
m.add_function(wrap_pyfunction!(apply_correlated_pauli_noise_statevector, m)?)?;
m.add_function(wrap_pyfunction!(apply_cnot_error_statevector, m)?)?;
m.add_function(wrap_pyfunction!(expectation_value_pauli_string_py, m)?)?;
// Add a class for Production readiness
m.add_class::<QuantumCircuit>()?;
Ok(())
}
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