add any and exp rotation gate

Author: refraction-ray

README.md

@@ -14,7 +14,7 @@ c.CNOT(0,1)
 print(c.perfect_sampling())
 print(c.wavefunction())
 print(c.measure(1))
-print(c.expectation((tc.gates.z(), 1)))
+print(c.expectation((tc.gates.z(), [1])))
 ```
 
 Runtime behavior changing:

tensorcircuit/circuit.py

@@ -19,7 +19,7 @@ class Circuit:
     sgates = (
         ["i", "x", "y", "z", "h", "t", "s", "rs"] + ["cnot", "cz", "swap"] + ["toffoli"]
     )
-    vgates = ["r", "cr", "rx", "ry", "rz"]
+    vgates = ["r", "cr", "rx", "ry", "rz", "any", "exp"]
 
     def __init__(self, nqubits: int) -> None:
         _prefix = "qb-"

tensorcircuit/gates.py

@@ -5,7 +5,8 @@
 import sys
 from copy import deepcopy
 from typing import Optional, Any
-from functools import partial
+from functools import partial, reduce
+from operator import mul
 
 import numpy as np
 from scipy.stats import unitary_group
@@ -242,3 +243,30 @@ def random_two_qubit_gate() -> Gate:
     unitary = unitary_group.rvs(dim=4)
     unitary = np.reshape(unitary, newshape=(2, 2, 2, 2))
     return Gate(deepcopy(unitary), name="R2Q")
+
+
+def any_gate(unitary: Tensor) -> Gate:
+    """
+    Note one should provide the gate with properly reshaped
+
+    :param unitary: corresponding gate
+    """
+    return Gate(deepcopy(unitary), name="any")
+
+
+any = any_gate
+
+
+def exponential_gate(unitary: Tensor, theta: float, name: str = "none") -> Gate:
+    """
+    $\exp{-i\theta unitary}$
+    """
+    theta = num_to_tensor(theta)
+    mat = backend.expm(-backend.i() * theta * unitary)
+    dimension = reduce(mul, mat.shape)
+    nolegs = int(np.log(dimension) / np.log(2))
+    mat = backend.reshape(mat, shape=[2 for _ in range(nolegs)])
+    return Gate(mat, name="exp-" + name)
+
+
+exp = exponential_gate

tests/test_gates.py

@@ -15,3 +15,22 @@ def test_rgate(highp):
         tc.gates.rgate(1, 2, 3).tensor, tc.gates.rgate_theoretical(1, 2, 3).tensor
     )
     # tc.set_dtype("complex64")
+
+
+def test_exp_gate():
+    c = tc.Circuit(2)
+    c.exp(
+        0,
+        1,
+        unitary=tc.gates.array_to_tensor(
+            np.array([[1.0, 0, 0, 0], [0, -1.0, 0, 0], [0, 0, -1, 0], [0, 0, 0, 1]])
+        ),
+        theta=tc.gates.num_to_tensor(np.pi / 2),
+    )
+    assert np.allclose(c.wavefunction()[0, 0], -1j)
+
+
+def test_any_gate():
+    c = tc.Circuit(2)
+    c.any(0, unitary=np.eye(2))
+    assert np.allclose(c.expectation((tc.gates.z(), [0])), 1.0)