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Qiskit 0.15 release notes


Terra 0.12.0


The 0.12.0 release includes several new features and bug fixes. The biggest change for this release is the addition of support for parametric pulses to OpenPulse. These are Pulse commands which take parameters rather than sample points to describe a pulse. 0.12.0 is also the first release to include support for Python 3.8. It also marks the beginning of the deprecation for Python 3.5 support, which will be removed when the upstream community stops supporting it.

New Features

  • The pass qiskit.transpiler.passes.CSPLayout was extended with two new parameters: call_limit and time_limit. These options allow limiting how long the pass will run. The option call_limit limits the number of times that the recursive function in the backtracking solver may be called. Similarly, time_limit limits how long (in seconds) the solver will be allowed to run. The defaults are 1000 calls and 10 seconds respectively.

  • qiskit.pulse.Acquire can now be applied to a single qubit. This makes pulse programming more consistent and easier to reason about, as now all operations apply to a single channel. For example:

    acquire = Acquire(duration=10)
    schedule = Schedule()
    schedule.insert(60, acquire(AcquireChannel(0), MemorySlot(0), RegisterSlot(0)))
    schedule.insert(60, acquire(AcquireChannel(1), MemorySlot(1), RegisterSlot(1)))
  • A new method qiskit.transpiler.CouplingMap.draw() was added to qiskit.transpiler.CouplingMap to generate a graphviz image from the coupling map graph. For example:

    from qiskit.transpiler import CouplingMap
    coupling_map = CouplingMap(
        [[0, 1], [1, 0], [1, 2], [1, 3], [2, 1], [3, 1], [3, 4], [4, 3]])
  • Parametric pulses have been added to OpenPulse. These are pulse commands which are parameterized and understood by the backend. Arbitrary pulse shapes are still supported by the SamplePulse Command. The new supported pulse classes are:

    • qiskit.pulse.ConstantPulse
    • qiskit.pulse.Drag
    • qiskit.pulse.Gaussian
    • qiskit.pulse.GaussianSquare

    They can be used like any other Pulse command. An example:

    from qiskit.pulse import (Schedule, Gaussian, Drag, ConstantPulse,
    sched = Schedule(name='parametric_demo')
    sched += Gaussian(duration=25, sigma=4, amp=0.5j)(DriveChannel(0))
    sched += Drag(duration=25, amp=0.1, sigma=5, beta=4)(DriveChannel(1))
    sched += ConstantPulse(duration=25, amp=0.3+0.1j)(DriveChannel(1))
    sched += GaussianSquare(duration=1500, amp=0.2, sigma=8,
                            width=140)(MeasureChannel(0)) << sched.duration

    The resulting schedule will be similar to a SamplePulse schedule built using qiskit.pulse.pulse_lib, however, waveform sampling will be performed by the backend. The method qiskit.pulse.Schedule.draw() can still be used as usual. However, the command will be converted to a SamplePulse with the qiskit.pulse.ParametricPulse.get_sample_pulse() method, so the pulse shown may not sample the continuous function the same way that the backend will.

    This feature can be used to construct Pulse programs for any backend, but the pulses will be converted to SamplePulse objects if the backend does not support parametric pulses. Backends which support them will have the following new attribute:

    backend.configuration().parametric_pulses: List[str]
    # e.g. ['gaussian', 'drag', 'constant']

    Note that the backend does not need to support all of the parametric pulses defined in Qiskit.

    When the backend supports parametric pulses, and the Pulse schedule is built with them, the assembled Qobj is significantly smaller. The size of a PulseQobj built entirely with parametric pulses is dependent only on the number of instructions, whereas the size of a PulseQobj built otherwise will grow with the duration of the instructions (since every sample must be specified with a value).

  • Added utility functions, qiskit.scheduler.measure() and qiskit.scheduler.measure_all() to qiskit.scheduler module. These functions return a qiskit.pulse.Schedule object which measures qubits using OpenPulse. For example:

    from qiskit.scheduler import measure, measure_all
    measure_q0_schedule = measure(qubits=[0], backend=backend)
    measure_all_schedule = measure_all(backend)
    measure_custom_schedule = measure(qubits=[0],
                                      qubit_mem_slots={0: 1})
  • Pulse qiskit.pulse.Schedule objects now have better representations that for simple schedules should be valid Python expressions.

  • The qiskit.circuit.QuantumCircuit methods qiskit.circuit.QuantumCircuit.measure_active(), qiskit.circuit.QuantumCircuit.measure_all(), and qiskit.circuit.QuantumCircuit.remove_final_measurements() now have an addition kwarg inplace. When inplace is set to False the function will return a modified copy of the circuit. This is different from the default behavior which will modify the circuit object in-place and return nothing.

  • Several new constructor methods were added to the qiskit.transpiler.CouplingMap class for building objects with basic qubit coupling graphs. The new constructor methods are:

    For example, to use the new constructors to get a coupling map of 5 qubits connected in a linear chain you can now run:

    from qiskit.transpiler import CouplingMap
    coupling_map = CouplingMap.from_line(5)
  • Introduced a new pass qiskit.transpiler.passes.CrosstalkAdaptiveSchedule. This pass aims to reduce the impact of crosstalk noise on a program. It uses crosstalk characterization data from the backend to schedule gates. When a pair of gates has high crosstalk, they get serialized using a barrier. Naive serialization is harmful because it incurs decoherence errors. Hence, this pass uses a SMT optimization approach to compute a schedule which minimizes the impact of crosstalk as well as decoherence errors.

    The pass takes as input a circuit which is already transpiled onto the backend i.e., the circuit is expressed in terms of physical qubits and swap gates have been inserted and decomposed into CNOTs if required. Using this circuit and crosstalk characterization data, a Z3 optimization(opens in a new tab) is used to construct a new scheduled circuit as output.

    To use the pass on a circuit circ:

    dag = circuit_to_dag(circ)
    pass_ = CrosstalkAdaptiveSchedule(backend_prop, crosstalk_prop)
    scheduled_dag =
    scheduled_circ = dag_to_circuit(scheduled_dag)

    backend_prop is a qiskit.providers.models.BackendProperties object for the target backend. crosstalk_prop is a dict which specifies conditional error rates. For two gates g1 and g2, crosstalk_prop[g1][g2] specifies the conditional error rate of g1 when g1 and g2 are executed simultaneously. A method for generating crosstalk_prop will be added in a future release of qiskit-ignis. Until then you’ll either have to already know the crosstalk properties of your device, or manually write your own device characterization experiments.

  • In the preset pass manager for optimization level 1, qiskit.transpiler.preset_passmanagers.level_1_pass_manager() if qiskit.transpiler.passes.TrivialLayout layout pass is not a perfect match for a particular circuit, then qiskit.transpiler.passes.DenseLayout layout pass is used instead.

  • Added a new abstract method to the abstract BaseOperator class, so it is included for all implementations of that abstract class, including qiskit.quantum_info.Operator and QuantumChannel (e.g., qiskit.quantum_info.Choi) objects. This method returns the right operator multiplication =ab= a \cdot b. This is equivalent to calling the operator qiskit.quantum_info.Operator.compose() method with the kwarg front set to True.

  • Added qiskit.quantum_info.average_gate_fidelity() and qiskit.quantum_info.gate_error() functions to the qiskit.quantum_info module for working with qiskit.quantum_info.Operator and QuantumChannel (e.g., qiskit.quantum_info.Choi) objects.

  • Added the qiskit.quantum_info.partial_trace() function to the qiskit.quantum_info that works with qiskit.quantum_info.Statevector and qiskit.quantum_info.DensityMatrix quantum state classes. For example:

    from qiskit.quantum_info.states import Statevector
    from qiskit.quantum_info.states import DensityMatrix
    from qiskit.quantum_info.states import partial_trace
    psi = Statevector.from_label('10+')
    partial_trace(psi, [0, 1])
    rho = DensityMatrix.from_label('10+')
    partial_trace(rho, [0, 1])
  • When qiskit.circuit.QuantumCircuit.draw() or qiskit.visualization.circuit_drawer() is called with the with_layout kwarg set True (the default) the output visualization will now display the physical qubits as integers to clearly distinguish them from the virtual qubits.

    For Example:

    from qiskit import QuantumCircuit
    from qiskit import transpile
    from qiskit.test.mock import FakeVigo
    qc = QuantumCircuit(3)
    qc.h(0), 1), 2)
    transpiled_qc = transpile(qc, FakeVigo())
  • Added new state measure functions to the qiskit.quantum_info module: qiskit.quantum_info.entropy(), qiskit.quantum_info.mutual_information(), qiskit.quantum_info.concurrence(), and qiskit.quantum_info.entanglement_of_formation(). These functions work with the qiskit.quantum_info.Statevector and qiskit.quantum_info.DensityMatrix classes.

  • The decomposition methods for single-qubit gates in qiskit.quantum_info.synthesis.one_qubit_decompose.OneQubitEulerDecomposer have been expanded to now also include the 'ZXZ' basis, characterized by three rotations about the Z,X,Z axis. This now means that a general 2x2 Operator can be decomposed into following bases: U3, U1X, ZYZ, ZXZ, XYX, ZXZ.

Known Issues

  • Running functions that use (for example qiskit.execute.execute(), qiskit.compiler.transpile(), and may not work when called from a script running outside of a if __name__ == '__main__': block when using Python 3.8 on MacOS. Other environments are unaffected by this issue. This is due to changes in how parallel processes are launched by Python 3.8 on MacOS. If RuntimeError or AttributeError are raised by scripts that are directly calling parallel_map() or when calling a function that uses it internally with Python 3.8 on MacOS embedding the script calls inside if __name__ == '__main__': should workaround the issue. For example:

    from qiskit import QuantumCircuit, QiskitError
    from qiskit import execute, BasicAer
    qc1 = QuantumCircuit(2, 2)
    qc1.h(0), 1)
    qc1.measure([0,1], [0,1])
    # making another circuit: superpositions
    qc2 = QuantumCircuit(2, 2)
    qc2.measure([0,1], [0,1])
    execute([qc1, qc2], BasicAer.get_backend('qasm_simulator'))

    should be changed to:

    from qiskit import QuantumCircuit, QiskitError
    from qiskit import execute, BasicAer
    def main():
        qc1 = QuantumCircuit(2, 2)
        qc1.h(0), 1)
        qc1.measure([0,1], [0,1])
        # making another circuit: superpositions
        qc2 = QuantumCircuit(2, 2)
        qc2.measure([0,1], [0,1])
        execute([qc1, qc2], BasicAer.get_backend('qasm_simulator'))
    if __name__ == '__main__':

    if errors are encountered with Python 3.8 on MacOS.

Upgrade Notes

  • The value of the rep_time parameter for Pulse backend’s configuration object is now in units of seconds, not microseconds. The first time a PulseBackendConfiguration object is initialized it will raise a single warning to the user to indicate this.

  • The rep_time argument for qiskit.compiler.assemble() now takes in a value in units of seconds, not microseconds. This was done to make the units with everything else in pulse. If you were passing in a value for rep_time ensure that you update the value to account for this change.

  • The value of the base_gate property of qiskit.circuit.ControlledGate objects has been changed from the class of the base gate to an instance of the class of the base gate.

  • The base_gate_name property of qiskit.circuit.ControlledGate has been removed; you can get the name of the base gate by accessing on the object. For example:

    from qiskit import QuantumCircuit
    from qiskit.extensions import HGate
    qc = QuantumCircuit(3)
    cch_gate = HGate().control(2)
    base_gate_name =
  • Changed qiskit.quantum_info.Operator magic methods so that __mul__ (which gets executed by python’s multiplication operation, if the left hand side of the operation has it defined) implements right matrix multiplication (i.e., and __rmul__ (which gets executed by python’s multiplication operation from the right hand side of the operation if the left does not have __mul__ defined) implements scalar multiplication (i.e. qiskit.quantum_info.Operator.multiply()). Previously both methods implemented scalar multiplciation.

  • The second argument of the qiskit.quantum_info.process_fidelity() function, target, is now optional. If a target unitary is not specified, then process fidelity of the input channel with the identity operator will be returned.

  • qiskit.compiler.assemble() will now respect the configured max_shots value for a backend. If a value for the shots kwarg is specified that exceed the max shots set in the backend configuration the function will now raise a QiskitError exception. Additionally, if no shots argument is provided the default value is either 1024 (the previous behavior) or max_shots from the backend, whichever is lower.

Deprecation Notes

  • Methods for adding gates to a qiskit.circuit.QuantumCircuit with abbreviated keyword arguments (e.g. ctl, tgt) have had their keyword arguments renamed to be more descriptive (e.g. control_qubit, target_qubit). The old names have been deprecated. A table including the old and new calling signatures for the QuantumCircuit methods is included below.

    Instruction TypeFormer SignatureNew Signature
    qiskit.extensions.HGateqc.h(q)qc.h(qubit), tgt), target_qubit))
    qiskit.extensions.RGateqc.r(theta, phi, q)qc.r(theta, phi, qubit)
    qiskit.extensions.RXGateqc.rx(theta, q)qc.rx(theta, qubit)
    qiskit.extensions.CrxGateqc.crx(theta, ctl, tgt)qc.crx(theta, control_qubit, target_qubit)
    qiskit.extensions.RYGateqc.ry(theta, q)qc.ry(theta, qubit)
    qiskit.extensions.CryGateqc.cry(theta, ctl, tgt)qc.cry(theta, control_qubit, target_qubit)
    qiskit.extensions.RZGateqc.rz(phi, q)qc.rz(phi, qubit)
    qiskit.extensions.CrzGateqc.crz(theta, ctl, tgt)qc.crz(theta, control_qubit, target_qubit)
    qiskit.extensions.FredkinGateqc.cswap(ctl, tgt1, tgt2)qc.cswap(control_qubit, target_qubit1, target_qubit2)
    qiskit.extensions.U1Gateqc.u1(theta, q)qc.u1(theta, qubit)
    qiskit.extensions.Cu1Gateqc.cu1(theta, ctl, tgt)qc.cu1(theta, control_qubit, target_qubit)
    qiskit.extensions.U2Gateqc.u2(phi, lam, q)qc.u2(phi, lam, qubit)
    qiskit.extensions.U3Gateqc.u3(theta, phi, lam, q)qc.u3(theta, phi, lam, qubit)
    qiskit.extensions.Cu3Gateqc.cu3(theta, phi, lam, ctl, tgt)qc.cu3(theta, phi, lam, control_qubit, target_qubit)
    qiskit.extensions.XGateqc.x(q)qc.x(qubit), tgt), target_qubit)
    qiskit.extensions.ToffoliGateqc.ccx(ctl1, ctl2, tgt)qc.ccx(control_qubit1, control_qubit2, target_qubit)
    qiskit.extensions.YGateqc.y(q)qc.y(qubit), tgt), target_qubit)
    qiskit.extensions.ZGateqc.z(q)qc.z(qubit), tgt), target_qubit)
  • Running qiskit.pulse.Acquire on multiple qubits has been deprecated and will be removed in a future release. Additionally, the qiskit.pulse.AcquireInstruction parameters mem_slots and reg_slots have been deprecated. Instead reg_slot and mem_slot should be used instead.

  • The attribute of the qiskit.providers.models.PulseDefaults class circuit_instruction_map has been deprecated and will be removed in a future release. Instead you should use the new attribute instruction_schedule_map. This was done to match the type of the value of the attribute, which is an InstructionScheduleMap.

  • The qiskit.pulse.PersistentValue command is deprecated and will be removed in a future release. Similar functionality can be achieved with the qiskit.pulse.ConstantPulse command (one of the new parametric pulses). Compare the following:

    from qiskit.pulse import Schedule, PersistentValue, ConstantPulse, \
    # deprecated implementation
    sched_w_pv = Schedule()
    sched_w_pv += PersistentValue(value=0.5)(DriveChannel(0))
    sched_w_pv += PersistentValue(value=0)(DriveChannel(0)) << 10
    # preferred implementation
    sched_w_const = Schedule()
    sched_w_const += ConstantPulse(duration=10, amp=0.5)(DriveChannel(0))
  • Python 3.5 support in qiskit-terra is deprecated. Support will be removed in the first release after the upstream Python community’s end of life date for the version, which is 09/13/2020.

  • The require_cptp kwarg of the qiskit.quantum_info.process_fidelity() function has been deprecated and will be removed in a future release. It is superseded by two separate kwargs require_cp and require_tp.

  • Setting the scale parameter for qiskit.circuit.QuantumCircuit.draw() and qiskit.visualization.circuit_drawer() as the first positional argument is deprecated and will be removed in a future release. Instead you should use scale as keyword argument.

  • The module is deprecated and will be removed in a future release. The legacy functions in the module have all been superseded by functions and classes in the qiskit.quantum_info module. A table of the deprecated functions and their replacement are below:

    DeprecatedReplacement and quantum_info.PTM
  • The qiskit.quantum_info.states.states module is deprecated and will be removed in a future release. The legacy functions in the module have all been superseded by functions and classes in the qiskit.quantum_info module.

  • The scaling parameter of the draw() method for the Schedule and Pulse objects was deprecated and will be removed in a future release. Instead the new scale parameter should be used. This was done to have a consistent argument between pulse and circuit drawings. For example:

    #The consistency in parameters is seen below
    #For circuits
    circuit = QuantumCircuit()
    #For pulses
    pulse = SamplePulse()
    #For schedules
    schedule = Schedule()

Bug Fixes

Other Notes

  • The transpiler passes in the qiskit.transpiler.passes directory have been organized into subdirectories to better categorize them by functionality. They are still all accessible under the qiskit.transpiler.passes namespace.

Aer 0.4.0


  • Added NoiseModel.from_backend for building a basic device noise model for an IBMQ backend (#569)
  • Added multi-GPU enabled simulation methods to the QasmSimulator, StatevectorSimulator, and UnitarySimulator. The qasm simulator has gpu version of the density matrix and statevector methods and can be accessed using "method": "density_matrix_gpu" or "method": "statevector_gpu" in backend_options. The statevector simulator gpu method can be accessed using "method": "statevector_gpu". The unitary simulator GPU method can be accessed using "method": "unitary_gpu". These backends use CUDA and require an NVidia GPU.(#544)
  • Added PulseSimulator backend (#542)
  • Added PulseSystemModel and HamiltonianModel classes to represent models to be used in PulseSimulator (#496, #493)
  • Added duffing_model_generators to generate PulseSystemModel objects from a list of parameters (#516)
  • Migrated ODE function solver to C++ (#442, #350)
  • Added high level pulse simulator tests (#379)
  • CMake BLAS_LIB_PATH flag to set path to look for BLAS lib (#543)


  • Changed the structure of the src directory to organise simulator source code. Simulator controller headers were moved to src/controllers and simulator method State headers are in src/simulators (#544)
  • Moved the location of several functions (#568): * Moved contents of qiskit.provider.aer.noise.errors into the qiskit.providers.noise module * Moved contents of qiskit.provider.aer.noise.utils into the qiskit.provider.aer.utils module.
  • Enabled optimization to aggregate consecutive gates in a circuit (fusion) by default (#579).


  • Deprecated utils.qobj_utils functions (#568)
  • Deprecated qiskit.providers.aer.noise.device.basic_device_noise_model. It is superseded by the NoiseModel.from_backend method (#569)


  • Removed NoiseModel.as_dict, QuantumError.as_dict, ReadoutError.as_dict, and QuantumError.kron methods that were deprecated in 0.3 (#568).

Ignis 0.2

No Change

Aqua 0.6

No Change

IBM Q Provider 0.4.6


  • Several new methods were added to IBMQBackend:

    • wait_for_final_state() blocks until the job finishes. It takes a callback function that it will invoke after every query to provide feedback.
    • active_jobs() returns the jobs submitted to a backend that are currently in an unfinished status.
    • job_limit() returns the job limit for a backend.
    • remaining_jobs_count() returns the number of jobs that you can submit to the backend before job limit is reached.
  • QueueInfo now has a new format() method that returns a formatted string of the queue information.

  • IBMQJob now has three new methods: done(), running(), and cancelled() that are used to indicate job status.

  • now accepts an optional job_tags parameter. If specified, the job_tags are assigned to the job, which can later be used as a filter in

  • IBMQJobManager now has a new method retrieve_job_set() that allows you to retrieve a previously submitted job set using the job set ID.


  • The Exception hierarchy has been refined with more specialized classes. You can, however, continue to catch their parent exceptions (such as IBMQAccountError). Also, the exception class IBMQApiUrlError has been replaced by IBMQAccountCredentialsInvalidUrl and IBMQAccountCredentialsInvalidToken.


  • The use of proxy urls without a protocol (e.g. http://) is deprecated due to recent Python changes.
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