def test_option7_algorithm():
algorithm = get_algorithm_by_name('option7')
assert algorithm.name == "option7"
assert algorithm.cascade_iterations == 14
assert algorithm.block_size_function(0.0, 10000, 1) == 131072
assert algorithm.block_size_function(0.1, 10000, 1) == 16
assert algorithm.block_size_function(0.01, 10000, 1) == 128
assert algorithm.block_size_function(0.01, 10000, 2) == 512
assert algorithm.block_size_function(0.01, 10000, 3) == 5000
assert algorithm.block_size_function(0.001, 10000, 1) == 1024
assert algorithm.biconf_iterations == 0
assert not algorithm.biconf_error_free_streak
assert not algorithm.biconf_correct_complement
assert not algorithm.biconf_cascade
assert algorithm.sub_block_reuse
assert not algorithm.block_parity_inference
def test_biconf_algorithm():
algorithm = get_algorithm_by_name('biconf')
assert algorithm.name == "biconf"
assert algorithm.cascade_iterations == 2
assert algorithm.block_size_function(0.0, 10000, 1) == 92000
assert algorithm.block_size_function(0.1, 10000, 1) == 10
assert algorithm.block_size_function(0.01, 10000, 1) == 92
assert algorithm.block_size_function(0.01, 10000, 2) == 276
assert algorithm.block_size_function(0.01, 10000, 3) == 828
assert algorithm.block_size_function(0.001, 10000, 1) == 920
assert algorithm.biconf_iterations == 10
assert algorithm.biconf_error_free_streak
assert not algorithm.biconf_correct_complement
assert not algorithm.biconf_cascade
assert not algorithm.sub_block_reuse
assert not algorithm.block_parity_inference
def test_yanetal_algorithm():
algorithm = get_algorithm_by_name('yanetal')
assert algorithm.name == "yanetal"
assert algorithm.cascade_iterations == 10
assert algorithm.block_size_function(0.0, 10000, 1) == 80000
assert algorithm.block_size_function(0.1, 10000, 1) == 8
assert algorithm.block_size_function(0.01, 10000, 1) == 80
assert algorithm.block_size_function(0.01, 10000, 2) == 400
assert algorithm.block_size_function(0.01, 10000, 3) == 5000
assert algorithm.block_size_function(0.001, 10000, 1) == 800
assert algorithm.biconf_iterations == 0
assert not algorithm.biconf_error_free_streak
assert not algorithm.biconf_correct_complement
assert not algorithm.biconf_cascade
assert not algorithm.sub_block_reuse
assert not algorithm.block_parity_inference
def __init__(self, algorithm_name, classical_channel, noisy_key,
estimated_bit_error_rate):
"""
Create a Cascade reconciliation.
Args:
algorithm_name (str): The name of the Cascade algorithm.
classical_channel (subclass of ClassicalChannel): The classical channel over which
Bob communicates with Alice.
noisy_key (Key): The noisy key as Bob received it from Alice that needs to be
reconciliated.
estimated_bit_error_rate (float): The estimated bit error rate in the noisy key.
"""
# Store the arguments.
self._classical_channel = classical_channel
self._algorithm = get_algorithm_by_name(algorithm_name)
assert self._algorithm is not None
self._estimated_bit_error_rate = estimated_bit_error_rate
self._noisy_key = noisy_key
self._reconciled_key = None
# Map key indexes to blocks.
self._key_index_to_blocks = {}
# Keep track of statistics.
self.stats = Stats()
# A set of blocks that are suspected to contain an error, pending to be corrected later.
# These are stored as a priority queue with items (block.size, block) so that we can correct
# the pending blocks in order of shortest block first.
self._pending_try_correct = []
# A set of blocks for which we have to ask Alice for the correct parity. To minimize the
# number of message that Bob sends to Alice (i.e. the number of channel uses), we queue up
# these pending parity questions until we can make no more progress correcting errors. Then
# we send a single message to Alice to ask all queued parity questions, and proceed once we
# get the answers.
self._pending_ask_correct_parity = []
