-
Notifications
You must be signed in to change notification settings - Fork 0
/
timeevolution_trotter.py
47 lines (37 loc) · 1.08 KB
/
timeevolution_trotter.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
"""
Time evolution of Heisenberg model realized by Trotter decomposition
"""
import numpy as np
import tensorcircuit as tc
K = tc.set_backend("tensorflow")
tc.set_dtype("complex128")
xx = tc.gates._xx_matrix
yy = tc.gates._yy_matrix
zz = tc.gates._zz_matrix
nqubit = 4
t = 1.0
tau = 0.1
def Trotter_step_unitary(input_state, tau, nqubit):
c = tc.Circuit(nqubit, inputs=input_state)
for i in range(nqubit - 1): ### U_zz
c.exp1(i, i + 1, theta=tau, unitary=zz)
for i in range(nqubit - 1): ### U_yy
c.exp1(i, i + 1, theta=tau, unitary=yy)
for i in range(nqubit - 1): ### U_xx
c.exp1(i, i + 1, theta=tau, unitary=xx)
TSUstate = c.state() ### return state U(τ)|ψ_i>
z0 = c.expectation_ps(z=[0])
return TSUstate, z0
TSU_vmap = tc.backend.jit(
tc.backend.vmap(
Trotter_step_unitary,
vectorized_argnums=0,
)
)
ninput = 2
input_state = np.zeros((ninput, 2**nqubit))
input_state[0, 0] = 1.0
input_state[1, -1] = 1.0
for _ in range(int(t / tau)):
input_state, z0 = TSU_vmap(input_state, tau, nqubit)
print("z: ", z0)