daniel/quantum
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

todo: how to apply hadamard gates after entanglement

Browse Source
This commit is contained in:
Daniel Tsvetkov 2019-09-24 22:49:58 +02:00
parent e839ac4006
commit e6ee65c35d
1 changed files with 20 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

29
computer.py
View File

@ -29,15 +29,16 @@ class Qubit(list):
return rv return rv
def measure(qubits): def measure(qubits, times=10):
""" """
Measure result from computation Measure result from computation based on the qubit population
""" """
probabilites = [q[0] ** 2 for q in qubits] probabilites = [q[0] ** 2 for q in qubits]
return bin(random.choices( return [bin(m) for m in random.choices(
population=range(len(qubits)), population=range(len(qubits)),
weights=probabilites weights=probabilites,
)[0]) k=times
)]
_0 = Qubit([[1], [0]]) _0 = Qubit([[1], [0]])
@ -89,13 +90,23 @@ def main():
assert CNOT * (_1 * _1) == (_1 * _0) assert CNOT * (_1 * _1) == (_1 * _0)
# TEST HADAMARD # TEST HADAMARD
# Put two qubits in superposition
superposition = Qubit(H * _0) * Qubit(H * _0) superposition = Qubit(H * _0) * Qubit(H * _0)
print(superposition) print(superposition)
CNOT_superposition = Qubit(CNOT * superposition) # Entangle the qubits
print(CNOT_superposition) entanglement = Qubit(CNOT * superposition)
print(entanglement)
print(measure(CNOT_superposition)) # TODO: What does it mean to apply H gate on the entangled qubits???
# print(INVERTED_CNOT) # https://en.wikipedia.org/wiki/Controlled_NOT_gate#Behaviour_in_the_Hadamard_transformed_basis
# Should it be:
# q1 = Qubit(H * entanglement[:2])
# q2 = Qubit(H * entanglement[3:])
# /TODO
# this should get us 1/4 chance for each combination of 00 01 10 and 10;
# measure 42 times
print(measure(entanglement, times=42))
# TEST MY MEMORY # TEST MY MEMORY
# rv = _0 # rv = _0