qsimcirq.QSimCircuit

A mutable list of groups of operations to apply to some qubits.

qsimcirq.QSimCircuit(
    cirq_circuit: cirq.Circuit,
    device: cirq.devices = cirq.devices.UNCONSTRAINED_DEVICE,
    allow_decomposition: bool = False
)

Methods returning information about the circuit (inherited from AbstractCircuit):

next_moment_operating_on
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_keys
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 being circuit[1] and the second being circuit[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 to circuit[1:3][:, qubit];
circuit[1:3, qubits] is equivalent to circuit[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. Non-moment 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.
`device`	Hardware that the circuit should be able to run on.

Attributes
`device`
`moments`

Attributes

device

moments

Methods

`all_measurement_keys`

all_measurement_keys() -> AbstractSet[str]

`all_operations`

all_operations() -> Iterator[ops.Operation]

Iterates over the operations applied by this circuit.

Operations from earlier moments will be iterated over first. Operations within a moment are iterated in the order they were given to the moment's constructor.

`all_qubits`

all_qubits() -> FrozenSet['cirq.Qid']

Returns the qubits acted upon by Operations in this circuit.

`append`

append(
    moment_or_operation_tree: Union['cirq.Moment', 'cirq.OP_TREE'],
    strategy: "cirq.InsertStrategy" = InsertStrategy.EARLIEST
)

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.

`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.

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.

`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 '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.

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).

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).

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.

`copy`

copy() -> "Circuit"

`factorize`

factorize() -> Iterable[CIRCUIT_TYPE]

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,
    qubits_that_should_be_present: Iterable['cirq.Qid'] = (),
    ignore_terminal_measurements: bool = True,
    dtype: Type[np.number] = np.complex128
) -> np.ndarray

Left-multiplies a state vector by the circuit's unitary effect.

A circuit's "unitary effect" is the unitary matrix produced by multiplying together all of its gates' unitary matrices. A circuit with non-unitary gates (such as measurement or parameterized gates) does not have a well-defined unitary effect, and the method will fail if such operations are present.

For convenience, terminal measurements are automatically ignored instead of causing a failure. Set the ignore_terminal_measurements argument to False to disable this behavior.

This method is equivalent to left-multiplying the input state by cirq.unitary(circuit) but it's computed in a more efficient way.

Args
`initial_state`	The input state for the circuit. This can be a list of qudit values, a big endian int encoding the qudit values, a vector of amplitudes, or a tensor of amplitudes. When this is an int, it refers to a computational basis state (e.g. 5 means initialize to `\|5⟩ = \|...000101⟩`). If this is a vector of amplitudes (a flat numpy array of the correct length for the system) or a tensor of amplitudes (a numpy array whose shape equals this circuit's `qid_shape`), it directly specifies the initial state's amplitudes. The vector type must be convertible to the given `dtype` argument.
`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) numpy array storing the superposition that came out of the circuit for the given input 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.

`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, ops.Operation]]

Finds all operations until a blocking operation is hit.

An operation is considered blocking if

a) It is in the 'light cone' of start_frontier.

AND

(

1) is_blocker returns a truthy value.

OR

2) 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:

1) 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. 2) Operations that act on qubits not in start_frontier are not automatically blocking.

For every (moment_index, operation) returned:

1) moment_index >= min((start_frontier[q] for q in operation.qubits if q in start_frontier), default=0) 2) 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[T_DESIRED_GATE_TYPE]
) -> Iterable[Tuple[int, ops.GateOperation, T_DESIRED_GATE_TYPE]]

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"

Creates a FrozenCircuit from this circuit.

If 'self' is a FrozenCircuit, the original object is returned.

`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()

`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 of 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: 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.

`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.

`next_moment_operating_on`

next_moment_operating_on(
    qubits: Iterable['cirq.Qid'],
    start_moment_index: int = 0,
    max_distance: 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 next 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, ...]

`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:

a) There is not a blocking operation covering L.

AND

[
    b1) qubit is in start frontier and moment_index =
        max(start_frontier[qubit], 0).

    OR

    b2) There is no operation at L and prev(L) = (qubit,
        moment_index-1) is reachable.

    OR

    b3) There is an (non-blocking) 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

a) `is_blocker` returns a truthy value.

OR

b) The operation acts on a qubit not in start_frontier.

OR

c) 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

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: q in start_frontier and start_frontier[q] <= i < end_frontier[q] where i is the moment index, q is the qubit, and end_frontier is the result of this method.

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:

q in start_frontier and start_frontier[q] <= i < end_frontier[q]

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 multi-line 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.

`tetris_concat`

tetris_concat(
    *circuits,
    align: Union['cirq.Alignment', str] = Alignment.LEFT
) -> "cirq.Circuit"

Concatenates circuits while overlapping them if possible.

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, acording 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.tetris_concat
    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.

`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 multi-line 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_quil`

to_quil(
    qubit_order: "cirq.QubitOrderOrList" = ops.QubitOrder.DEFAULT
) -> str

`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 ascii-only 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
) -> TextDiagramDrawer

Returns a TextDiagramDrawer with the circuit drawn into it.

Args
`use_unicode_characters`	Determines if unicode characters are allowed (as opposed to ascii-only diagrams).
`qubit_namer`	Names qubits in diagram. Defaults to str.
`transpose`	Arranges qubit wires vertically instead of horizontally.
`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']],
    *,
    new_device: "cirq.Device" = None
) -> "cirq.Circuit"

Returns the same circuit, but with different qubits.

Note that this method does essentially the same thing as cirq.Circuit.with_device. It is included regardless because there are also transform_qubits methods on cirq.Operation and cirq.Moment.

Args
`qubit_map`	A function or a dict mapping each current qubit into a desired new qubit.
`new_device`	The device to use for the new circuit, if different. If this is not set, the new device defaults to the current device.

Returns
The receiving circuit but with qubits transformed by the given function, and with an updated device (if specified).

`translate_cirq_to_qsim`

View source

translate_cirq_to_qsim(
    qubit_order: cirq.ops.QubitOrderOrList = cirq.ops.QubitOrder.DEFAULT
) -> qsimcirq.qsim.Circuit

Translates this Cirq circuit to the qsim representation. :qubit_order: Ordering of qubits :return: a C++ qsim Circuit object

`translate_cirq_to_qtrajectory`

View source

translate_cirq_to_qtrajectory(
    qubit_order: cirq.ops.QubitOrderOrList = cirq.ops.QubitOrder.DEFAULT
) -> qsimcirq.qsim.NoisyCircuit

Translates this noisy Cirq circuit to the qsim representation. :qubit_order: Ordering of qubits :return: a C++ qsim NoisyCircuit object

`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.number] = 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_device`

with_device(
    new_device: "cirq.Device",
    qubit_mapping: Callable[['cirq.Qid'], 'cirq.Qid'] = (lambda e: e)
) -> "Circuit"

Maps the current circuit onto a new device, and validates.

Args
`new_device`	The new device that the circuit should be on.
`qubit_mapping`	How to translate qubits from the old device into qubits on the new device.

Returns
The translated circuit.

`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 moment-by-moment 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 built-in 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.

Returns
The merged circuit.

Raises
`ValueError`	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))

* <b>`0`</b>: ───H───@───────
          │
* <b>`1`</b>: ───────X───────
<BLANKLINE>
* <b>`2`</b>: ───X───Y───Z───
print(circuit1.zip(circuit2, circuit3))
* <b>`0`</b>: ───H───@───────
          │
* <b>`1`</b>: ───────X───────
<BLANKLINE>
* <b>`2`</b>: ───X───Y───Z───
<BLANKLINE>
* <b>`3`</b>: ───────S───────
print(cirq.Circuit.zip(circuit3, circuit2, circuit1))
* <b>`0`</b>: ───H───@───────
          │
* <b>`1`</b>: ───────X───────
<BLANKLINE>
* <b>`2`</b>: ───X───Y───Z───
<BLANKLINE>
* <b>`3`</b>: ───────S───────

`add`

__add__(
    other
)

`bool`

__bool__()

`eq`

View source

__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
) -> "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
)