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from cmath import sqrt
import random
class PureState:
A superposition of classical states.
def __init__(self, classical_to_amplitude):
err = abs(1 - sum(abs(a)**2 for a in classical_to_amplitude.values()))
if err > 0.00001:
raise ValueError("Squared magnitudes must sum to 1.")
# Discard negligible amplitudes as an approximation/optimization.
self.superposition = {c: a
for c, a in classical_to_amplitude.items()
if abs(a) >= 0.0000001}
def _weigh(self, predicate):
return sum(abs(a)**2
for s, a in self.superposition.items()
if predicate(s))
def post_select(self, predicate):
:param predicate: Determines which classical states to keep. All
non-matching states are discarded out of the superposition (the
resulting superposition is renormalized to compensate for the missing
:return: A (probability, PureState) pair with the probability of the
desired predicate being satisfied (the post-selection's "power") and the
renormalized superposition of the matching values.
p = self._weigh(predicate)
if p == 0:
return 0, None
d = sqrt(p)
return p, PureState({val: amp/d
for val, amp in self.superposition.items()
if predicate(val)})
def measure(self, selector):
:param selector: Returns measurement results for given classical states.
Classical states with differing measurement results end up in separate
branches of the resulting mixed state.
:return: The mixed state created by the measurement.
from mixed_state import MixedState # Avoid top-level circular dep.
used_measurement_results = {selector(c) for c in self.superposition}
return MixedState({
s: p
for k in used_measurement_results
for p, s in [self.post_select(lambda c: selector(c) == k)]
def unitary_transform(self, op):
:param: op Maps inputs to a superposition of outputs.
Must be a unitary operation (i.e. length preserving in all cases).
:return: The resulting pure state, after the operation has been applied
and colliding states have been interfered.
# Each input in our superposition turns into a superposition of outputs.
outputs = [(c2, a2*a1)
for c1, a1 in self.superposition.items()
for c2, a2 in op(c1).superposition.items()]
# Because itertools.groupby implements the wrong thing.
def group_by(items, key_func=lambda e: e[0], val_func=lambda e: e[1]):
result = {}
for e in items:
k, v = key_func(e), val_func(e)
if k in result:
result[k] = [v]
return result
# When the same output is reached multiple ways, sum up the amplitudes.
interfered = {k: sum(g) for k, g in group_by(outputs).items()}
return PureState(interfered)
def collapsed(self):
Picks a classical state at random, with frequency proportional to
the associated amplitude's squared magnitude.
:return: A classical state from the superposition.
t = random.random()
for c, a in self.superposition.items():
t -= abs(a)**2
if t <= 0.000001:
return c
raise AssertionError("Probabilities didn't sum to 1")
def __str__(self):
return " + ".join("{:.3f}".format(a) + "*" + str(c)
for c, a in self.superposition.items())
def __repr__(self):
return "PureState(" + repr(self.superposition) + ")"