Schedules and Devices

Schedule and Circuit are the two major container classes for quantum circuits. In contrast to Circuit, a Schedule includes detailed information about the timing and duration of the gates.

Conceptually a Schedule is made up of a set of ScheduledOperations as well as a description of the Device on which the schedule is intended to be run. Each ScheduledOperation is made up of a time when the operation starts and a duration describing how long the operation takes, in addition to the Operation itself (like in a Circuit an Operation is made up of a Gate and the QubitIds upon which the gate acts.)


The Device class is an abstract class which encapsulates constraints (or lack thereof) that come when running a circuit on actual hardware. For instance, most hardware only allows certain gates to be enacted on qubits. Or, as another example, some gates may be constrained to not be able to run at the same time as neighboring gates. Further the Device class knows more about the scheduling of Operations.

Here for example is a Device made up of 10 qubits on a line:

import cirq
from cirq.devices import GridQubit
class Xmon10Device(cirq.Device):

  def __init__(self):
      self.qubits = [GridQubit(i, 0) for i in range(10)]

  def duration_of(self, operation):
      # Wouldn't it be nice if everything took 10ns?
      return cirq.Duration(nanos=10)

  def validate_operation(self, operation):
      if not isinstance(operation, cirq.GateOperation):
          raise ValueError('{!r} is not a supported operation'.format(operation))
      if not isinstance(operation.gate, (cirq.CZPowGate,
          raise ValueError('{!r} is not a supported gate'.format(operation.gate))
      if len(operation.qubits) == 2:
          p, q = operation.qubits
          if not p.is_adjacent(q):
            raise ValueError('Non-local interaction: {}'.format(repr(operation)))

  def validate_scheduled_operation(self, schedule, scheduled_operation):

  def validate_circuit(self, circuit):
      for moment in circuit:
          for operation in moment.operations:

  def validate_schedule(self, schedule):
      for scheduled_operation in schedule.scheduled_operations:
          self.validate_scheduled_operation(schedule, scheduled_operation)

This device, for example, knows that two qubit gates between next-nearest-neighbors is not valid:

device = Xmon10Device()
circuit = cirq.Circuit()
circuit.append([cirq.CZ(device.qubits[0], device.qubits[2])])
except ValueError as e:
# prints something like
# ValueError: Non-local interaction: Operation(cirq.CZ, (GridQubit(0, 0), GridQubit(2, 0)))


A Schedule contains more timing information above and beyond that which is provided by the Moment structure of a Circuit. This can be used both for fine grained timing control, but also to optimize a circuit for a particular device. One can work directly with Schedules or, more common, use a custom scheduler that converts a Circuit to a Schedule. A simple example of such a scheduler is the moment_by_moment_schedule method of This scheduler attempts to keep the Moment structure of the underlying Circuit as much as possible: each Operation in a Moment is scheduled to start at the same time (such a schedule may not be possible, in which case this method raises an exception.)

Here, for example, is a simple Circuit on the Xmon10Device defined above

circuit = cirq.Circuit()
circuit.append([cirq.CZ(device.qubits[0], device.qubits[1]), cirq.X(device.qubits[0])])
# prints:
# (0, 0): ───@───X───
#            │
# (1, 0): ───@───────

This can be converted over into a schedule using the moment by moment schedule

schedule = cirq.moment_by_moment_schedule(device, circuit)

Schedules have an attributed scheduled_operations which contains all the scheduled operations in a SortedListWithKey, where the key is the start time of the SortedOperation. Schedules support nice helpers for querying about the time-space layout of the schedule. For instance, the Schedule behaves as if it has an index corresponding to time. So, we can look up which operations occur at a specific time

# prints something like 
# [ScheduledOperation(Timestamp(picos=10000), Duration(picos=10000),...)]

or even a start and end time using slicing notation

slice = schedule[cirq.Timestamp(nanos=5):cirq.Timestamp(nanos=15)]
slice_schedule = cirq.Schedule(device, slice)
print(slice_schedule == schedule)
# prints True

More complicated queries across Schedules can be done using the query.

Schedules are usually built by converting from Circuits, but one can also directly manipulate the schedule using the include and exclude methods. include will check if there are any collisions with other schedule operations.