Upload noise_model.py

quread/noise_model.py

@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+from typing import Dict, Optional
+
+import numpy as np
+
+from .metrics import parse_calibration_json
+
+
+def sample_noisy_counts(
+    state: np.ndarray,
+    n_qubits: int,
+    shots: int,
+    *,
+    calibration_json: str = "",
+    readout_scale: float = 1.0,
+    depolarizing_prob: float = 0.0,
+    seed: Optional[int] = None,
+) -> Dict[str, int]:
+    """
+    Sample measurement outcomes from a statevector, then apply a simple hardware-noise proxy:
+    - Depolarizing stage: with probability depolarizing_prob, replace shot with random basis state.
+    - Readout stage: independent bit-flip per qubit using scaled readout_error from calibration JSON.
+    """
+    n = int(n_qubits)
+    s = int(shots)
+    if n < 1:
+        raise ValueError("n_qubits must be >= 1")
+    if s < 1:
+        raise ValueError("shots must be >= 1")
+
+    vec = np.asarray(state, dtype=complex).reshape(-1)
+    dim = 2 ** n
+    if vec.size != dim:
+        raise ValueError(f"State size mismatch: expected {dim}, got {vec.size}")
+
+    probs = np.abs(vec) ** 2
+    total = float(np.sum(probs))
+    if total <= 0:
+        raise ValueError("State probabilities are all zero.")
+    probs = probs / total
+
+    cal, _note = parse_calibration_json(calibration_json, n)
+    readout_error = np.clip(cal["readout_error"] * float(readout_scale), 0.0, 1.0)
+    depol = float(np.clip(float(depolarizing_prob), 0.0, 1.0))
+
+    rng = np.random.default_rng(seed)
+    ideal = rng.choice(np.arange(dim), size=s, p=probs)
+
+    counts: Dict[str, int] = {}
+    for idx in ideal:
+        idx_i = int(idx)
+
+        # Depolarizing replacement
+        if rng.random() < depol:
+            idx_i = int(rng.integers(0, dim))
+
+        bits = list(format(idx_i, f"0{n}b"))
+
+        # Readout bit flips
+        for q in range(n):
+            if rng.random() < float(readout_error[q]):
+                bits[q] = "1" if bits[q] == "0" else "0"
+
+        b = "".join(bits)
+        counts[b] = counts.get(b, 0) + 1
+
+    return dict(sorted(counts.items()))