add mipt examples

Author: refraction-ray

examples/mipt.py

@@ -0,0 +1,83 @@
+"""
+demo example of mipt in tc style
+"""
+from functools import partial
+import time
+import numpy as np
+from scipy import stats
+import tensorcircuit as tc
+
+K = tc.set_backend("jax")
+# tf backend is slow (at least on cpu)
+
+
+@partial(K.jit, static_argnums=(2, 3, 4))
+def circuit_output(random_matrix, status, n, d, p):
+    """
+    mipt circuit
+
+    :param random_matrix: a float or complex tensor containing 4*4 random haar matrix wth size [d*n, 4, 4]
+    :type random_matrix: _type_
+    :param status: a int tensor with element in 0 or 1 or 2 (no meausrement) with size d*n
+    :type status: _type_
+    :param n: number of qubits
+    :type n: _type_
+    :param d: number of depth
+    :type d: _type_
+    :param p: measurement ratio
+    :type p: float
+    :return: output state
+    """
+    random_matrix = K.reshape(random_matrix, [d, n, 4, 4])
+    status = K.reshape(status, [d, n])
+    inputs = None
+    for j in range(d):
+        if inputs is None:
+            c = tc.Circuit(n)
+        else:
+            c = tc.Circuit(n, inputs=inputs)
+        for i in range(0, n, 2):
+            c.unitary(i, (i + 1) % n, unitary=random_matrix[j, i])
+        for i in range(1, n, 2):
+            c.unitary(i, (i + 1) % n, unitary=random_matrix[j, i])
+        inputs = c.state()
+        c = tc.Circuit(n, inputs=inputs)
+        for i in range(n):
+            c.general_kraus(
+                [
+                    np.sqrt(p) * np.array([[1.0, 0], [0, 0]]),
+                    np.sqrt(p) * np.array([[0, 0], [0, 1.0]]),
+                    np.sqrt(1 - p) * np.eye(2),
+                ],
+                i,
+                status=status[j, i],
+            )
+            inputs = c.state()
+            c = tc.Circuit(n, inputs=inputs)
+        inputs = c.state()
+        inputs /= K.norm(inputs)
+    return inputs
+
+
+@partial(K.jit, static_argnums=(2, 3, 4))
+def cals(random_matrix, status, n, d, p):
+    state = circuit_output(random_matrix, status, n, d, p)
+    rho = tc.quantum.reduced_density_matrix(state, cut=[i for i in range(n // 2)])
+    return tc.quantum.entropy(rho), tc.quantum.renyi_entropy(rho, k=2)
+
+
+if __name__ == "__main__":
+    n = 12
+    d = 12
+    st = np.random.uniform(size=[d * n])
+    ## assume all X gate instead
+    rm = [stats.unitary_group.rvs(4) for _ in range(d * n)]
+    rm = [r / np.linalg.det(r) for r in rm]
+    rm = np.stack(rm)
+    time0 = time.time()
+    print(cals(rm, st, n, d, 0.1))
+    time1 = time.time()
+    st = np.random.uniform(size=[d * n])
+    print(cals(rm, st, n, d, 0.1))
+    time2 = time.time()
+    print(f"compiling time {time1-time0}, running time {time2-time1}")