View source on GitHub 
A mutable list of groups of operations to apply to some qubits.
qsimcirq.QSimCircuit(
cirq_circuit: cirq.Circuit, allow_decomposition: bool = False
)
Methods returning information about the circuit (inherited from AbstractCircuit):
 next_moment_operating_on
 earliest_available_moment
 prev_moment_operating_on
 next_moments_operating_on
 operation_at
 all_qubits
 all_operations
 findall_operations
 findall_operations_between
 findall_operations_until_blocked
 findall_operations_with_gate_type
 reachable_frontier_from
 has_measurements
 are_all_matches_terminal
 are_all_measurements_terminal
 unitary
 final_state_vector
 to_text_diagram
 to_text_diagram_drawer
 qid_shape
 all_measurement_key_names
 to_quil
 to_qasm
 save_qasm
 get_independent_qubit_sets
Methods for mutation:
 insert
 append
 insert_into_range
 clear_operations_touching
 batch_insert
 batch_remove
 batch_insert_into
 insert_at_frontier
Circuits can also be iterated over,
for moment in circuit:
...
and sliced,
circuit[1:3]
is a new Circuit made up of two moments, the first beingcircuit[1]
and the second beingcircuit[2]
;circuit[:, qubit]
is a new Circuit with the same moments, but with only those operations which act on the given Qubit;circuit[:, qubits]
, where 'qubits' is list of Qubits, is a new Circuit with the same moments, but only with those operations which touch any of the given qubits;circuit[1:3, qubit]
is equivalent tocircuit[1:3][:, qubit]
;circuit[1:3, qubits]
is equivalent tocircuit[1:3][:, qubits]
;
and concatenated,
circuit1 + circuit2
is a new Circuit made up of the moments in circuit1 followed by the moments in circuit2;
and multiplied by an integer,
circuit * k
is a new Circuit made up of the moments in circuit repeated k times.
and mutated,
circuit[1:7] = [Moment(...)]
and factorized,
circuit.factorize()
returns a sequence of Circuits which represent independent 'factors' of the original Circuit.
Args  

contents

The initial list of moments and operations defining the
circuit. You can also pass in operations, lists of operations,
or generally anything meeting the cirq.OP_TREE contract.
Nonmoment entries will be inserted according to the specified
insertion strategy.

strategy

When initializing the circuit with operations and moments
from contents , this determines how the operations are packed
together. This option does not affect later insertions into the
circuit.

Attributes  

moments

Methods
all_measurement_key_names
all_measurement_key_names() > FrozenSet[str]
Returns the set of all measurement key names in this circuit.
Returns: FrozenSet of strings that are the measurement key names in this circuit.
all_measurement_key_objs
all_measurement_key_objs() > FrozenSet['cirq.MeasurementKey']
all_operations
all_operations() > Iterator['cirq.Operation']
Returns an iterator over the operations in the circuit.
Returns: Iterator over cirq.Operation
elements found in this circuit.
all_qubits
all_qubits() > FrozenSet['cirq.Qid']
Returns the qubits acted upon by Operations in this circuit.
Returns: FrozenSet of cirq.Qid
objects acted on by all operations
in this circuit.
append
append(
moment_or_operation_tree: Union['cirq.Moment', 'cirq.OP_TREE'],
strategy: 'cirq.InsertStrategy' = InsertStrategy.EARLIEST
) > None
Appends operations onto the end of the circuit.
Moments within the operation tree are appended intact.
Args  

moment_or_operation_tree

The moment or operation tree to append. 
strategy

How to pick/create the moment to put operations into. 
are_all_matches_terminal
are_all_matches_terminal(
predicate: Callable[['cirq.Operation'], bool]
) > bool
Check whether all of the ops that satisfy a predicate are terminal.
This method will transparently descend into any CircuitOperations this circuit contains; as a result, it will misbehave if the predicate refers to CircuitOperations. See the tests for an example of this.
Args  

predicate

A predicate on ops.Operations which is being checked. 
Returns  

Whether or not all Operation s in a circuit that satisfy the
given predicate are terminal. Also checks within any CircuitGates
the circuit may contain.

are_all_measurements_terminal
are_all_measurements_terminal() > bool
Whether all measurement gates are at the end of the circuit.
Returns: True iff no measurement is followed by a gate.
are_any_matches_terminal
are_any_matches_terminal(
predicate: Callable[['cirq.Operation'], bool]
) > bool
Check whether any of the ops that satisfy a predicate are terminal.
This method will transparently descend into any CircuitOperations this circuit contains; as a result, it will misbehave if the predicate refers to CircuitOperations. See the tests for an example of this.
Args  

predicate

A predicate on ops.Operations which is being checked. 
Returns  

Whether or not any Operation s in a circuit that satisfy the
given predicate are terminal. Also checks within any CircuitGates
the circuit may contain.

are_any_measurements_terminal
are_any_measurements_terminal() > bool
Whether any measurement gates are at the end of the circuit.
Returns: True iff some measurements are not followed by a gate.
batch_insert
batch_insert(
insertions: Iterable[Tuple[int, 'cirq.OP_TREE']]
) > None
Applies a batched insert operation to the circuit.
Transparently handles the fact that earlier insertions may shift the index that later insertions should occur at. For example, if you insert an operation at index 2 and at index 4, but the insert at index 2 causes a new moment to be created, then the insert at "4" will actually occur at index 5 to account for the shift from the new moment.
All insertions are done with the strategy cirq.InsertStrategy.EARLIEST
.
When multiple inserts occur at the same index, the gates from the later inserts end up before the gates from the earlier inserts (exactly as if you'd called list.insert several times with the same index: the later inserts shift the earliest inserts forward).
Args  

insertions

A sequence of (insert_index, operations) pairs indicating operations to add into the circuit at specific places. 
batch_insert_into
batch_insert_into(
insert_intos: Iterable[Tuple[int, 'cirq.OP_TREE']]
) > None
Inserts operations into empty spaces in existing moments.
If any of the insertions fails (due to colliding with an existing operation), this method fails without making any changes to the circuit.
Args  

insert_intos

A sequence of (moment_index, new_op_tree) pairs indicating a moment to add new operations into. 
Raises  

ValueError

One of the insertions collided with an existing operation. 
IndexError

Inserted into a moment index that doesn't exist. 
batch_remove
batch_remove(
removals: Iterable[Tuple[int, 'cirq.Operation']]
) > None
Removes several operations from a circuit.
Args  

removals

A sequence of (moment_index, operation) tuples indicating operations to delete from the moments that are present. All listed operations must actually be present or the edit will fail (without making any changes to the circuit). 
Raises  

ValueError

One of the operations to delete wasn't present to start with. 
IndexError

Deleted from a moment that doesn't exist. 
batch_replace
batch_replace(
replacements: Iterable[Tuple[int, 'cirq.Operation', 'cirq.Operation']]
) > None
Replaces several operations in a circuit with new operations.
Args  

replacements

A sequence of (moment_index, old_op, new_op) tuples indicating operations to be replaced in this circuit. All "old" operations must actually be present or the edit will fail (without making any changes to the circuit). 
Raises  

ValueError

One of the operations to replace wasn't present to start with. 
IndexError

Replaced in a moment that doesn't exist. 
clear_operations_touching
clear_operations_touching(
qubits: Iterable['cirq.Qid'], moment_indices: Iterable[int]
)
Clears operations that are touching given qubits at given moments.
Args  

qubits

The qubits to check for operations on. 
moment_indices

The indices of moments to check for operations within. 
concat_ragged
concat_ragged(
*circuits, align: Union['cirq.Alignment', str] = Alignment.LEFT
) > 'cirq.Circuit'
Concatenates circuits, overlapping them if possible due to ragged edges.
Starts with the first circuit (index 0), then iterates over the other circuits while folding them in. To fold two circuits together, they are placed one after the other and then moved inward until just before their operations would collide. If any of the circuits do not share qubits and so would not collide, the starts or ends of the circuits will be aligned, according to the given align parameter.
Beware that this method is not associative. For example:
a, b = cirq.LineQubit.range(2)
A = cirq.Circuit(cirq.H(a))
B = cirq.Circuit(cirq.H(b))
f = cirq.Circuit.concat_ragged
f(f(A, B), A) == f(A, f(B, A))
False
len(f(f(f(A, B), A), B)) == len(f(f(A, f(B, A)), B))
False
Args  

*circuits

The circuits to concatenate. 
align

When to stop when sliding the circuits together. 'left': Stop when the starts of the circuits align. 'right': Stop when the ends of the circuits align. 'first': Stop the first time either the starts or the ends align. Circuits are never overlapped more than needed to align their starts (in case the left circuit is smaller) or to align their ends (in case the right circuit is smaller) 
Returns  

The concatenated and overlapped circuit. 
copy
copy() > 'Circuit'
Return a copy of this circuit.
earliest_available_moment
earliest_available_moment(
op: 'cirq.Operation', *, end_moment_index: Optional[int] = None
) > int
Finds the index of the earliest (i.e. left most) moment which can accommodate op
.
Note that, unlike circuit.prev_moment_operating_on
, this method also takes care of
implicit dependencies between measurements and classically controlled operations (CCO)
that depend on the results of those measurements. Therefore, using this method, a CCO
op
would not be allowed to move left past a measurement it depends upon.
Args  

op

Operation for which the earliest moment that can accommodate it needs to be found. 
end_moment_index

The moment index just after the starting point of the reverse search. Defaults to the length of the list of moments. 
Returns  

Index of the earliest matching moment. Returns end_moment_index if no moment on left
is available.

factorize
factorize() > Iterable[Self]
Factorize circuit into a sequence of independent circuits (factors).
Factorization is possible when the circuit's qubits can be divided into two or more independent qubit sets. Preserves the moments from the original circuit. If this is not possible, returns the set consisting of the single circuit (this one).
q0, q1, q2 = cirq.LineQubit.range(3)
circuit = cirq.Circuit()
circuit.append(cirq.Moment(cirq.H(q2)))
circuit.append(cirq.Moment(cirq.CZ(q0,q1)))
circuit.append(cirq.H(q0))
print(circuit)
0: ───────@───H───
│
1: ───────@───────
<BLANKLINE>
2: ───H───────────
for i, f in enumerate(circuit.factorize()):
print("Factor {}".format(i))
print(f)
Factor 0
0: ───────@───H───
│
1: ───────@───────
Factor 1
2: ───H───────────
Returns  

The sequence of circuits, each including only the qubits from one independent qubit set. 
final_state_vector
final_state_vector(
*,
initial_state: 'cirq.STATE_VECTOR_LIKE' = 0,
qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT,
ignore_terminal_measurements: bool = False,
dtype: Type[np.complexfloating] = np.complex128,
param_resolver: 'cirq.ParamResolverOrSimilarType' = None,
seed: 'cirq.RANDOM_STATE_OR_SEED_LIKE' = None
) > np.ndarray
Returns the state vector resulting from acting operations on a state.
This is equivalent to calling cirq.final_state_vector with the same arguments and this circuit as the "program".
Args  

initial_state

If an int, the state is set to the computational basis state corresponding to this state. Otherwise if this is a np.ndarray it is the full initial state. In this case it must be the correct size, be normalized (an L2 norm of 1), and be safely castable to an appropriate dtype for the simulator. 
qubit_order

Determines the canonical ordering of the qubits. This is often used in specifying the initial state, i.e. the ordering of the computational basis states. 
qubits_that_should_be_present

Qubits that may or may not appear in operations within the circuit, but that should be included regardless when generating the matrix. 
ignore_terminal_measurements

When set, measurements at the end of the circuit are ignored instead of causing the method to fail. Defaults to False. 
dtype

The numpy.dtype used by the simulation. Typically one of
numpy.complex64 or numpy.complex128 .

param_resolver

Parameters to run with the program. 
seed

The random seed to use for this simulator. 
Returns  

The state vector resulting from applying the given unitary operations to the desired initial state. Specifically, a numpy array containing the amplitudes in np.kron order, where the order of arguments to kron is determined by the qubit order argument (which defaults to just sorting the qubits that are present into an ascending order). 
Raises  

ValueError

If the program doesn't have a well defined final state because it has nonunitary gates. 
findall_operations
findall_operations(
predicate: Callable[['cirq.Operation'], bool]
) > Iterable[Tuple[int, 'cirq.Operation']]
Find the locations of all operations that satisfy a given condition.
This returns an iterator of (index, operation) tuples where each operation satisfies op_cond(operation) is truthy. The indices are in order of the moments and then order of the ops within that moment.
Args  

predicate

A method that takes an Operation and returns a Truthy value indicating the operation meets the find condition. 
Returns  

An iterator (index, operation)'s that satisfy the op_condition. 
findall_operations_between
findall_operations_between(
start_frontier: Dict['cirq.Qid', int],
end_frontier: Dict['cirq.Qid', int],
omit_crossing_operations: bool = False
) > List[Tuple[int, 'cirq.Operation']]
Finds operations between the two given frontiers.
If a qubit is in start_frontier
but not end_frontier
, its end index
defaults to the end of the circuit. If a qubit is in end_frontier
but
not start_frontier
, its start index defaults to the start of the
circuit. Operations on qubits not mentioned in either frontier are not
included in the results.
Args  

start_frontier

Just before where to start searching for operations, for each qubit of interest. Start frontier indices are inclusive. 
end_frontier

Just before where to stop searching for operations, for each qubit of interest. End frontier indices are exclusive. 
omit_crossing_operations

Determines whether or not operations that cross from a location between the two frontiers to a location outside the two frontiers are included or excluded. (Operations completely inside are always included, and operations completely outside are always excluded.) 
Returns  

A list of tuples. Each tuple describes an operation found between the two frontiers. The first item of each tuple is the index of the moment containing the operation, and the second item is the operation itself. The list is sorted so that the moment index increases monotonically. 
findall_operations_until_blocked
findall_operations_until_blocked(
start_frontier: Dict['cirq.Qid', int],
is_blocker: Callable[['cirq.Operation'], bool] = (lambda op: False)
) > List[Tuple[int, 'cirq.Operation']]
Finds all operations until a blocking operation is hit.
An operation is considered blocking if both of the following hold:
 It is in the 'light cone' of start_frontier.
is_blocker
returns a truthy value, or it acts on a blocked qubit
Every qubit acted on by a blocking operation is thereafter itself blocked.
The notion of reachability here differs from that in reachable_frontier_from in two respects:
 An operation is not considered blocking only because it is in a moment before the start_frontier of one of the qubits on which it acts.
 Operations that act on qubits not in start_frontier are not automatically blocking.
For every (moment_index, operation) returned:
 moment_index >= min((start_frontier[q] for q in operation.qubits if q in start_frontier), default=0)
 set(operation.qubits).intersection(start_frontier)
Below are some examples, where on the left the opening parentheses show
start_frontier
and on the right are the operations included (with
their moment indices) in the output. F
and T
indicate that
is_blocker
return False
or True
, respectively, when applied to
the gates; M
indicates that it doesn't matter.
─(─F───F─────── ┄(─F───F─)┄┄┄┄┄
│ │ │ │
─(─F───F───T─── => ┄(─F───F─)┄┄┄┄┄
│ ┊
───────────T─── ┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
───M─────(─F─── ┄┄┄┄┄┄┄┄┄(─F─)┄┄
│ │ ┊ │
───M───M─(─F─── ┄┄┄┄┄┄┄┄┄(─F─)┄┄
│ => ┊
───────M───M─── ┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
│ ┊
───────────M─── ┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
───M─(─────M─── ┄┄┄┄┄()┄┄┄┄┄┄┄┄
│ │ ┊ ┊
───M─(─T───M─── ┄┄┄┄┄()┄┄┄┄┄┄┄┄
│ => ┊
───────T───M─── ┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
│ ┊
───────────M─── ┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
─(─F───F─── ┄(─F───F─)┄
│ │ => │ │
───F─(─F─── ┄(─F───F─)┄
─(─F─────────── ┄(─F─)┄┄┄┄┄┄┄┄┄
│ │
───F───F─────── ┄(─F─)┄┄┄┄┄┄┄┄┄
│ => ┊
───────F───F─── ┄┄┄┄┄┄┄┄┄(─F─)┄
│ │
─(─────────F─── ┄┄┄┄┄┄┄┄┄(─F─)┄
Args  

start_frontier

A starting set of reachable locations. 
is_blocker

A predicate that determines if operations block
reachability. Any location covered by an operation that causes
is_blocker to return True is considered to be an unreachable
location.

Returns  

A list of tuples. Each tuple describes an operation found between the start frontier and a blocking operation. The first item of each tuple is the index of the moment containing the operation, and the second item is the operation itself. 
findall_operations_with_gate_type
findall_operations_with_gate_type(
gate_type: Type[_TGate]
) > Iterable[Tuple[int, 'cirq.GateOperation', _TGate]]
Find the locations of all gate operations of a given type.
Args  

gate_type

The type of gate to find, e.g. XPowGate or MeasurementGate. 
Returns  

An iterator (index, operation, gate)'s for operations with the given gate type. 
freeze
freeze() > 'cirq.FrozenCircuit'
Gets a frozen version of this circuit.
Repeated calls to .freeze()
will return the same FrozenCircuit
instance as long as this circuit is not mutated.
from_moments
@classmethod
from_moments( *moments ) > CIRCUIT_TYPE
Create a circuit from moment op trees.
Args  

*moments

Op tree for each moment. If an op tree is a moment, it
will be included directly in the new circuit. If an op tree is
a circuit, it will be frozen, wrapped in a CircuitOperation, and
included in its own moment in the new circuit. Otherwise, the
op tree will be passed to cirq.Moment to create a new moment
which is then included in the new circuit. Note that in the
latter case we have the normal restriction that operations in a
moment must be applied to disjoint sets of qubits.

get_independent_qubit_sets
get_independent_qubit_sets() > List[Set['cirq.Qid']]
Divide circuit's qubits into independent qubit sets.
Independent qubit sets are the qubit sets such that there are no entangling gates between qubits belonging to different sets. If this is not possible, a sequence with a single factor (the whole set of circuit's qubits) is returned.
q0, q1, q2 = cirq.LineQubit.range(3)
circuit = cirq.Circuit()
circuit.append(cirq.Moment(cirq.H(q2)))
circuit.append(cirq.Moment(cirq.CZ(q0,q1)))
circuit.append(cirq.H(q0))
print(circuit)
0: ───────@───H───
│
1: ───────@───────
<BLANKLINE>
2: ───H───────────
[sorted(qs) for qs in circuit.get_independent_qubit_sets()]
[[cirq.LineQubit(0), cirq.LineQubit(1)], [cirq.LineQubit(2)]]
Returns  

The list of independent qubit sets. 
has_measurements
has_measurements()
Returns whether or not this circuit has measurements.
Returns: True if cirq.is_measurement(self)
is True otherwise False.
insert
insert(
index: int,
moment_or_operation_tree: Union['cirq.Operation', 'cirq.OP_TREE'],
strategy: 'cirq.InsertStrategy' = InsertStrategy.EARLIEST
) > int
Inserts operations into the circuit.
Operations are inserted into the moment specified by the index and 'InsertStrategy'. Moments within the operation tree are inserted intact.
Args  

index

The index to insert all the operations at. 
moment_or_operation_tree

The moment or operation tree to insert. 
strategy

How to pick/create the moment to put operations into. 
Returns  

The insertion index that will place operations just after the operations that were inserted by this method. 
Raises  

ValueError

Bad insertion strategy. 
insert_at_frontier
insert_at_frontier(
operations: 'cirq.OP_TREE',
start: int,
frontier: Optional[Dict['cirq.Qid', int]] = None
) > Dict['cirq.Qid', int]
Inserts operations inline at frontier.
Args  

operations

The operations to insert. 
start

The moment at which to start inserting the operations. 
frontier

frontier[q] is the earliest moment in which an operation acting on qubit q can be placed. 
Raises  

ValueError

If the frontier given is after start. 
insert_into_range
insert_into_range(
operations: 'cirq.OP_TREE', start: int, end: int
) > int
Writes operations inline into an area of the circuit.
Args  

start

The start of the range (inclusive) to write the given operations into. 
end

The end of the range (exclusive) to write the given operations into. If there are still operations remaining, new moments are created to fit them. 
operations

An operation or tree of operations to insert. 
Returns  

An insertion index that will place operations after the operations that were inserted by this method. 
Raises  

IndexError

Bad inline_start and/or inline_end. 
map_operations
map_operations(
func: Callable[['cirq.Operation'], 'cirq.OP_TREE']
) > Self
Applies the given function to all operations in this circuit.
Args  

func

a mapping function from operations to OP_TREEs. 
Returns  

A circuit with the same basic structure as the original, but with
each operation op replaced with func(op) .

next_moment_operating_on
next_moment_operating_on(
qubits: Iterable['cirq.Qid'],
start_moment_index: int = 0,
max_distance: Optional[int] = None
) > Optional[int]
Finds the index of the next moment that touches the given qubits.
Args  

qubits

We're looking for operations affecting any of these qubits. 
start_moment_index

The starting point of the search. 
max_distance

The number of moments (starting from the start index and moving forward) to check. Defaults to no limit. 
Returns  

None if there is no matching moment, otherwise the index of the earliest matching moment. 
Raises  

ValueError

negative max_distance. 
next_moments_operating_on
next_moments_operating_on(
qubits: Iterable['cirq.Qid'], start_moment_index: int = 0
) > Dict['cirq.Qid', int]
Finds the index of the next moment that touches each qubit.
Args  

qubits

The qubits to find the next moments acting on. 
start_moment_index

The starting point of the search. 
Returns  

The index of the next moment that touches each qubit. If there is no such moment, the next moment is specified as the number of moments in the circuit. Equivalently, can be characterized as one plus the index of the last moment after start_moment_index (inclusive) that does not act on a given qubit. 
operation_at
operation_at(
qubit: 'cirq.Qid', moment_index: int
) > Optional['cirq.Operation']
Finds the operation on a qubit within a moment, if any.
Args  

qubit

The qubit to check for an operation on. 
moment_index

The index of the moment to check for an operation within. Allowed to be beyond the end of the circuit. 
Returns  

None if there is no operation on the qubit at the given moment, or else the operation. 
prev_moment_operating_on
prev_moment_operating_on(
qubits: Sequence['cirq.Qid'],
end_moment_index: Optional[int] = None,
max_distance: Optional[int] = None
) > Optional[int]
Finds the index of the previous moment that touches the given qubits.
Args  

qubits

We're looking for operations affecting any of these qubits. 
end_moment_index

The moment index just after the starting point of the reverse search. Defaults to the length of the list of moments. 
max_distance

The number of moments (starting just before from the end index and moving backward) to check. Defaults to no limit. 
Returns  

None if there is no matching moment, otherwise the index of the latest matching moment. 
Raises  

ValueError

negative max_distance. 
qid_shape
qid_shape(
qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT
) > Tuple[int, ...]
Get the qubit shapes of all qubits in this circuit.
Returns: A tuple containing the dimensions (shape) of all qudits
found in this circuit according to qubit_order
.
reachable_frontier_from
reachable_frontier_from(
start_frontier: Dict['cirq.Qid', int],
*,
is_blocker: Callable[['cirq.Operation'], bool] = (lambda op: False)
) > Dict['cirq.Qid', int]
Determines how far can be reached into a circuit under certain rules.
The location L = (qubit, moment_index) is reachable if and only if the following all hold true:
 There is not a blocking operation covering L.
 At least one of the following holds:
 qubit is in start frontier and moment_index = max(start_frontier[qubit], 0).
 There is no operation at L and prev(L) = (qubit, moment_index1) is reachable.
 There is an (nonblocking) operation P covering L such that (q', moment_index  1) is reachable for every q' on which P acts.
An operation in moment moment_index is blocking if at least one of the following hold:
is_blocker
returns a truthy value. The operation acts on a qubit not in start_frontier.
 The operation acts on a qubit q such that start_frontier[q] > moment_index.
In other words, the reachable region extends forward through time along each qubit in start_frontier until it hits a blocking operation. Any location involving a qubit not in start_frontier is unreachable.
For each qubit q in start_frontier
, the reachable locations will
correspond to a contiguous range starting at start_frontier[q] and
ending just before some index end_q. The result of this method is a
dictionary, and that dictionary maps each qubit q to its end_q.
Examples:
If start_frontier
is
{
cirq.LineQubit(0): 6,
cirq.LineQubit(1): 2,
cirq.LineQubit(2): 2
}
then the reachable wire locations in the following circuit are highlighted with '█' characters:
0 1 2 3 4 5 6 7 8 9 10 11 12 13
0: ───H───@─────────────────█████████████████████─@───H───
│ │
1: ───────@─██H███@██████████████████████─@───H───@───────
│ │
2: ─────────██████@███H██─@───────@───H───@───────────────
│ │
3: ───────────────────────@───H───@───────────────────────
And the computed end_frontier
is
{
cirq.LineQubit(0): 11,
cirq.LineQubit(1): 9,
cirq.LineQubit(2): 6,
}
Note that the frontier indices (shown above the circuit) are best thought of (and shown) as happening between moment indices.
If we specify a blocker as follows:
is_blocker=lambda: op == cirq.CZ(cirq.LineQubit(1),
cirq.LineQubit(2))
and use this start_frontier
:
{
cirq.LineQubit(0): 0,
cirq.LineQubit(1): 0,
cirq.LineQubit(2): 0,
cirq.LineQubit(3): 0,
}
Then this is the reachable area:
0 1 2 3 4 5 6 7 8 9 10 11 12 13
0: ─██H███@██████████████████████████████████████─@───H───
│ │
1: ─██████@███H██─@───────────────────────@───H───@───────
│ │
2: ─█████████████─@───H───@───────@───H───@───────────────
│ │
3: ─█████████████████████─@───H───@───────────────────────
and the computed end_frontier
is:
{
cirq.LineQubit(0): 11,
cirq.LineQubit(1): 3,
cirq.LineQubit(2): 3,
cirq.LineQubit(3): 5,
}
Args  

start_frontier

A starting set of reachable locations. 
is_blocker

A predicate that determines if operations block
reachability. Any location covered by an operation that causes
is_blocker to return True is considered to be an unreachable
location.

Returns  

An end_frontier dictionary, containing an end index for each qubit q
mapped to a start index by the given start_frontier dictionary.
To determine if a location (q, i) was reachable, you can use this expression:
where i is the moment index, q is the qubit, and end_frontier is the result of this method. 
save_qasm
save_qasm(
file_path: Union[str, bytes, int],
header: Optional[str] = None,
precision: int = 10,
qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT
) > None
Save a QASM file equivalent to the circuit.
Args  

file_path

The location of the file where the qasm will be written. 
header

A multiline string that is placed in a comment at the top of the QASM. Defaults to a cirq version specifier. 
precision

Number of digits to use when representing numbers. 
qubit_order

Determines how qubits are ordered in the QASM register. 
to_qasm
to_qasm(
header: Optional[str] = None,
precision: int = 10,
qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT
) > str
Returns QASM equivalent to the circuit.
Args  

header

A multiline string that is placed in a comment at the top of the QASM. Defaults to a cirq version specifier. 
precision

Number of digits to use when representing numbers. 
qubit_order

Determines how qubits are ordered in the QASM register. 
to_text_diagram
to_text_diagram(
*,
use_unicode_characters: bool = True,
transpose: bool = False,
include_tags: bool = True,
precision: Optional[int] = 3,
qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT
) > str
Returns text containing a diagram describing the circuit.
Args  

use_unicode_characters

Determines if unicode characters are allowed (as opposed to asciionly diagrams). 
transpose

Arranges qubit wires vertically instead of horizontally. 
include_tags

Whether tags on TaggedOperations should be printed 
precision

Number of digits to display in text diagram 
qubit_order

Determines how qubits are ordered in the diagram. 
Returns  

The text diagram. 
to_text_diagram_drawer
to_text_diagram_drawer(
*,
use_unicode_characters: bool = True,
qubit_namer: Optional[Callable[['cirq.Qid'], str]] = None,
transpose: bool = False,
include_tags: bool = True,
draw_moment_groups: bool = True,
precision: Optional[int] = 3,
qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT,
get_circuit_diagram_info: Optional[Callable[['cirq.Operation', 'cirq.CircuitDiagramInfoArgs'],
'cirq.CircuitDiagramInfo']] = None
) > 'cirq.TextDiagramDrawer'
Returns a TextDiagramDrawer with the circuit drawn into it.
Args  

use_unicode_characters

Determines if unicode characters are allowed (as opposed to asciionly diagrams). 
qubit_namer

Names qubits in diagram. Defaults to using _circuit_diagraminfo or str. 
transpose

Arranges qubit wires vertically instead of horizontally. 
include_tags

Whether to include tags in the operation. 
draw_moment_groups

Whether to draw moment symbol or not 
precision

Number of digits to use when representing numbers. 
qubit_order

Determines how qubits are ordered in the diagram. 
get_circuit_diagram_info

Gets circuit diagram info. Defaults to protocol with fallback. 
Returns  

The TextDiagramDrawer instance. 
transform_qubits
transform_qubits(
qubit_map: Union[Dict['cirq.Qid', 'cirq.Qid'], Callable[['cirq.Qid'], 'cirq.Qid']]
) > 'cirq.Circuit'
Returns the same circuit, but with different qubits.
Args  

qubit_map

A function or a dict mapping each current qubit into a desired new qubit. 
Returns  

The receiving circuit but with qubits transformed by the given function. 
Raises  

TypeError

If qubit_function is not a function or a dict.

translate_cirq_to_qsim
translate_cirq_to_qsim(
qubit_order: cirq.QubitOrderOrList = cirq.QubitOrder.DEFAULT
) > qsimcirq.qsim.Circuit
Translates this Cirq circuit to the qsim representation. :qubit_order: Ordering of qubits :return: a tuple of (C++ qsim Circuit object, moment boundary gate indices)
translate_cirq_to_qtrajectory
translate_cirq_to_qtrajectory(
qubit_order: cirq.QubitOrderOrList = cirq.QubitOrder.DEFAULT
) > qsimcirq.qsim.NoisyCircuit
Translates this noisy Cirq circuit to the qsim representation. :qubit_order: Ordering of qubits :return: a tuple of (C++ qsim NoisyCircuit object, moment boundary gate indices)
unfreeze
unfreeze(
copy: bool = True
) > 'cirq.Circuit'
Creates a Circuit from this circuit.
Args  

copy

If True and 'self' is a Circuit, returns a copy that circuit. 
unitary
unitary(
qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT,
qubits_that_should_be_present: Iterable['cirq.Qid'] = (),
ignore_terminal_measurements: bool = True,
dtype: Type[np.complexfloating] = np.complex128
) > np.ndarray
Converts the circuit into a unitary matrix, if possible.
Returns the same result as cirq.unitary
, but provides more options.
Args  

qubit_order

Determines how qubits are ordered when passing matrices into np.kron. 
qubits_that_should_be_present

Qubits that may or may not appear in operations within the circuit, but that should be included regardless when generating the matrix. 
ignore_terminal_measurements

When set, measurements at the end of the circuit are ignored instead of causing the method to fail. 
dtype

The numpy dtype for the returned unitary. Defaults to
np.complex128. Specifying np.complex64 will run faster at the
cost of precision. dtype must be a complex np.dtype, unless
all operations in the circuit have unitary matrices with
exclusively real coefficients (e.g. an H + TOFFOLI circuit).

Returns  

A (possibly gigantic) 2d numpy array corresponding to a matrix equivalent to the circuit's effect on a quantum state. 
Raises  

ValueError

The circuit contains measurement gates that are not ignored. 
TypeError

The circuit contains gates that don't have a known unitary matrix, e.g. gates parameterized by a Symbol. 
with_noise
with_noise(
noise: 'cirq.NOISE_MODEL_LIKE'
) > 'cirq.Circuit'
Make a noisy version of the circuit.
Args  

noise

The noise model to use. This describes the kind of noise to add to the circuit. 
Returns  

A new circuit with the same moment structure but with new moments inserted where needed when more than one noisy operation is generated for an input operation. Emptied moments are removed. 
zip
zip(
*circuits, align: Union['cirq.Alignment', str] = Alignment.LEFT
) > 'cirq.Circuit'
Combines operations from circuits in a momentbymoment fashion.
Moment k of the resulting circuit will have all operations from moment k of each of the given circuits.
When the given circuits have different lengths, the shorter circuits are implicitly padded with empty moments. This differs from the behavior of python's builtin zip function, which would instead truncate the longer circuits.
The zipped circuits can't have overlapping operations occurring at the same moment index.
Args  

*circuits

The circuits to merge together. 
align

The alignment for the zip, see cirq.Alignment .

Returns  

The merged circuit. 
Raises  

ValueError

If the zipped circuits have overlapping operations occurring at the same moment index. 
Examples:
import cirq
a, b, c, d = cirq.LineQubit.range(4)
circuit1 = cirq.Circuit(cirq.H(a), cirq.CNOT(a, b))
circuit2 = cirq.Circuit(cirq.X(c), cirq.Y(c), cirq.Z(c))
circuit3 = cirq.Circuit(cirq.Moment(), cirq.Moment(cirq.S(d)))
print(circuit1.zip(circuit2))
0: ───H───@───────
│
1: ───────X───────
<BLANKLINE>
2: ───X───Y───Z───
print(circuit1.zip(circuit2, circuit3))
0: ───H───@───────
│
1: ───────X───────
<BLANKLINE>
2: ───X───Y───Z───
<BLANKLINE>
3: ───────S───────
print(cirq.Circuit.zip(circuit3, circuit2, circuit1))
0: ───H───@───────
│
1: ───────X───────
<BLANKLINE>
2: ───X───Y───Z───
<BLANKLINE>
3: ───────S───────
__add__
__add__(
other
)
__bool__
__bool__() > bool
__eq__
__eq__(
other
)
Return self==value.
__getitem__
__getitem__(
key
)
__iter__
__iter__() > Iterator['cirq.Moment']
__len__
__len__() > int
__mul__
__mul__(
repetitions: _INT_TYPE
)
__ne__
__ne__(
other
) > bool
Return self!=value.
__pow__
__pow__(
exponent: int
) > 'cirq.Circuit'
A circuit raised to a power, only valid for exponent 1, the inverse.
This will fail if anything other than 1 is passed to the Circuit by returning NotImplemented. Otherwise this will return the inverse circuit, which is the circuit with its moment order reversed and for every moment all the moment's operations are replaced by its inverse. If any of the operations do not support inverse, NotImplemented will be returned.
__radd__
__radd__(
other
)
__rmul__
__rmul__(
repetitions: _INT_TYPE
)