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Qiskit 0.12 release notes


0.12.0

Terra 0.9

Prelude

The 0.9 release includes many new features and many bug fixes. The biggest changes for this release are new debugging capabilities for PassManagers. This includes a function to visualize a PassManager, the ability to add a callback function to a PassManager, and logging of passes run in the PassManager. Additionally, this release standardizes the way that you can set an initial layout for your circuit. So now you can leverage initial_layout the kwarg parameter on qiskit.compiler.transpile() and qiskit.execute() and the qubits in the circuit will get laid out on the desire qubits on the device. Visualization of circuits will now also show this clearly when visualizing a circuit that has been transpiled with a layout.

New Features

  • A DAGCircuit object (i.e. the graph representation of a QuantumCircuit where operation dependencies are explicit) can now be visualized with the .draw() method. This is in line with Qiskit’s philosophy of easy visualization. Other objects which support a .draw() method are QuantumCircuit, PassManager, and Schedule.

  • Added a new visualization function qiskit.visualization.plot_error_map() to plot the error map for a given backend. It takes in a backend object from the qiskit-ibmq-provider and will plot the current error map for that device.

  • Both qiskit.QuantumCircuit.draw() and qiskit.visualization.circuit_drawer() now support annotating the qubits in the visualization with layout information. If the QuantumCircuit object being drawn includes layout metadata (which is normally only set on the circuit output from transpile() calls) then by default that layout will be shown on the diagram. This is done for all circuit drawer backends. For example:

    from qiskit import ClassicalRegister, QuantumCircuit, QuantumRegister
    from qiskit.compiler import transpile
     
    qr = QuantumRegister(2, 'userqr')
    cr = ClassicalRegister(2, 'c0')
    qc = QuantumCircuit(qr, cr)
    qc.h(qr[0])
    qc.cx(qr[0], qr[1])
    qc.y(qr[0])
    qc.x(qr[1])
    qc.measure(qr, cr)
     
    # Melbourne coupling map
    coupling_map = [[1, 0], [1, 2], [2, 3], [4, 3], [4, 10], [5, 4],
                    [5, 6], [5, 9], [6, 8], [7, 8], [9, 8], [9, 10],
                    [11, 3], [11, 10], [11, 12], [12, 2], [13, 1],
                    [13, 12]]
    qc_result = transpile(qc, basis_gates=['u1', 'u2', 'u3', 'cx', 'id'],
                          coupling_map=coupling_map, optimization_level=0)
    qc.draw(output='text')

    will yield a diagram like:

                      ┌──────────┐┌──────────┐┌───┐┌──────────┐┌──────────────────┐┌─┐
       (userqr0) q0|0>U2(0,pi) ├┤ U2(0,pi) ├┤ X ├┤ U2(0,pi) ├┤ U3(pi,pi/2,pi/2) ├┤M├───
                      ├──────────┤└──────────┘└─┬─┘├──────────┤└─┬─────────────┬──┘└╥┘┌─┐
       (userqr1) q1|0>U2(0,pi) ├──────────────■──┤ U2(0,pi) ├──┤ U3(pi,0,pi) ├────╫─┤M├
                      └──────────┘                 └──────────┘  └─────────────┘    ║ └╥┘
      (ancilla0) q2|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
      (ancilla1) q3|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
      (ancilla2) q4|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
      (ancilla3) q5|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
      (ancilla4) q6|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
      (ancilla5) q7|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
      (ancilla6) q8|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
      (ancilla7) q9|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
     (ancilla8) q10|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
     (ancilla9) q11|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
    (ancilla10) q12|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
    (ancilla11) q13|0>──────────────────────────────────────────────────────────────╫──╫─
                                                                                    ║  ║
              c0_0: 0 ══════════════════════════════════════════════════════════════╩══╬═
    
              c0_1: 0 ═════════════════════════════════════════════════════════════════╩═

    If you do not want the layout to be shown on transpiled circuits (or any other circuits with a layout set) there is a new boolean kwarg for both functions, with_layout (which defaults True), which when set False will disable the layout annotation in the output circuits.

  • A new analysis pass CountOpsLongest was added to retrieve the number of operations on the longest path of the DAGCircuit. When used it will add a count_ops_longest_path key to the property set dictionary. You can add it to your a passmanager with something like:

    from qiskit.transpiler.passes import CountOpsLongestPath
    from qiskit.transpiler.passes import CxCancellation
    from qiskit.transpiler import PassManager
     
    pm = PassManager()
    pm.append(CountOpsLongestPath())

    and then access the longest path via the property set value with something like:

    pm.append(
        CxCancellation(),
        condition=lambda property_set: property_set[
            'count_ops_longest_path'] < 5)

    which will set a condition on that pass based on the longest path.

  • Two new functions, sech() and sech_deriv() were added to the pulse library module qiskit.pulse.pulse_lib for creating an unnormalized hyperbolic secant SamplePulse object and an unnormalized hyperbolic secant derviative SamplePulse object respectively.

  • A new kwarg option vertical_compression was added to the QuantumCircuit.draw() method and the qiskit.visualization.circuit_drawer() function. This option only works with the text backend. This option can be set to either high, medium (the default), or low to adjust how much vertical space is used by the output visualization.

  • A new kwarg boolean option idle_wires was added to the QuantumCircuit.draw() method and the qiskit.visualization.circuit_drawer() function. It works for all drawer backends. When idle_wires is set False in a drawer call the drawer will not draw any bits that do not have any circuit elements in the output quantum circuit visualization.

  • A new PassManager visualizer function qiskit.visualization.pass_mamanger_drawer() was added. This function takes in a PassManager object and will generate a flow control diagram of all the passes run in the PassManager.

  • When creating a PassManager you can now specify a callback function that if specified will be run after each pass is executed. This function gets passed a set of kwargs on each call with the state of the pass manager after each pass execution. Currently these kwargs are:

    • pass_ (Pass): the pass being run
    • dag (DAGCircuit): the dag output of the pass
    • time (float): the time to execute the pass
    • property_set (PropertySet): the property set
    • count (int): the index for the pass execution

    However, it’s worth noting that while these arguments are set for the 0.9 release they expose the internals of the pass manager and are subject to change in future release.

    For example you can use this to create a callback function that will visualize the circuit output after each pass is executed:

    from qiskit.transpiler import PassManager
     
    def my_callback(**kwargs):
        print(kwargs['dag'])
     
    pm = PassManager(callback=my_callback)

    Additionally you can specify the callback function when using qiskit.compiler.transpile():

    from qiskit.compiler import transpile
     
    def my_callback(**kwargs):
        print(kwargs['pass'])
     
    transpile(circ, callback=my_callback)
  • A new method filter() was added to the qiskit.pulse.Schedule class. This enables filtering the instructions in a schedule. For example, filtering by instruction type:

    from qiskit.pulse import Schedule
    from qiskit.pulse.commands import Acquire
    from qiskit.pulse.commands import AcquireInstruction
    from qiskit.pulse.commands import FrameChange
     
    sched = Schedule(name='MyExperiment')
    sched.insert(0, FrameChange(phase=-1.57)(device))
    sched.insert(60, Acquire(5))
    acquire_sched = sched.filter(instruction_types=[AcquireInstruction])
  • Additional decomposition methods for several types of gates. These methods will use different decomposition techniques to break down a gate into a sequence of CNOTs and single qubit gates. The following methods are added:

    MethodDescription
    QuantumCircuit.iso()Add an arbitrary isometry from m to n qubits to a circuit. This allows for attaching arbitrary unitaries on n qubits (m=n) or to prepare any state of n qubits (m=0)
    QuantumCircuit.diag_gate()Add a diagonal gate to the circuit
    QuantumCircuit.squ()Decompose an arbitrary 2x2 unitary into three rotation gates and add to a circuit
    QuantumCircuit.ucg()Attach an uniformly controlled gate (also called a multiplexed gate) to a circuit
    QuantumCircuit.ucx()Attach a uniformly controlled (also called multiplexed) Rx rotation gate to a circuit
    QuantumCircuit.ucy()Attach a uniformly controlled (also called multiplexed) Ry rotation gate to a circuit
    QuantumCircuit.ucz()Attach a uniformly controlled (also called multiplexed) Rz rotation gate to a circuit
  • Addition of Gray-Synth and Patel–Markov–Hayes algorithms for synthesis of CNOT-Phase and CNOT-only linear circuits. These functions allow the synthesis of circuits that consist of only CNOT gates given a linear function or a circuit that consists of only CNOT and phase gates given a matrix description.

  • A new function random_circuit was added to the qiskit.circuit.random module. This function will generate a random circuit of a specified size by randomly selecting different gates and adding them to the circuit. For example, you can use this to generate a 5-qubit circuit with a depth of 10 using:

    from qiskit.circuit.random import random_circuit
     
    circ = random_circuit(5, 10)
  • A new kwarg output_names was added to the qiskit.compiler.transpile() function. This kwarg takes in a string or a list of strings and uses those as the value of the circuit name for the output circuits that get returned by the transpile() call. For example:

    from qiskit.compiler import transpile
    my_circs = [circ_a, circ_b]
    tcirc_a, tcirc_b = transpile(my_circs,
                                 output_names=['Circuit A', 'Circuit B'])

    the name attribute on tcirc_a and tcirc_b will be 'Circuit A' and 'Circuit B' respectively.

  • A new method equiv() was added to the qiskit.quantum_info.Operator and qiskit.quantum_info.Statevector classes. These methods are used to check whether a second Operator object or Statevector is equivalent up to global phase.

  • The user config file has several new options:

    • The circuit_drawer field now accepts an auto value. When set as the value for the circuit_drawer field the default drawer backend will be mpl if it is available, otherwise the text backend will be used.
    • A new field circuit_mpl_style can be used to set the default style used by the matplotlib circuit drawer. Valid values for this field are bw and default to set the default to a black and white or the default color style respectively.
    • A new field transpile_optimization_level can be used to set the default transpiler optimization level to use for calls to qiskit.compiler.transpile(). The value can be set to either 0, 1, 2, or 3.
  • Introduced a new pulse command Delay which may be inserted into a pulse Schedule. This command accepts a duration and may be added to any Channel. Other commands may not be scheduled on a channel during a delay.

    The delay can be added just like any other pulse command. For example:

    from qiskit import pulse
     
    drive_channel = pulse.DriveChannel(0)
    delay = pulse.Delay(20)
     
    sched = pulse.Schedule()
    sched += delay(drive_channel)

Upgrade Notes

  • The previously deprecated qiskit._util module has been removed. qiskit.util should be used instead.

  • The QuantumCircuit.count_ops() method now returns an OrderedDict object instead of a dict. This should be compatible for most use cases since OrderedDict is a dict subclass. However type checks and other class checks might need to be updated.

  • The DAGCircuit.width() method now returns the total number quantum bits and classical bits. Before it would only return the number of quantum bits. If you require just the number of quantum bits you can use DAGCircuit.num_qubits() instead.

  • The function DAGCircuit.num_cbits() has been removed. Instead you can use DAGCircuit.num_clbits().

  • Individual quantum bits and classical bits are no longer represented as (register, index) tuples. They are now instances of Qubit and Clbit classes. If you’re dealing with individual bits make sure that you update any usage or type checks to look for these new classes instead of tuples.

  • The preset passmanager classes qiskit.transpiler.preset_passmanagers.default_pass_manager and qiskit.transpiler.preset_passmanagers.default_pass_manager_simulator (which were the previous default pass managers for qiskit.compiler.transpile() calls) have been removed. If you were manually using this pass managers switch to the new default, qiskit.transpile.preset_passmanagers.level1_pass_manager.

  • The LegacySwap pass has been removed. If you were using it in a custom pass manager, it’s usage can be replaced by the StochasticSwap pass, which is a faster more stable version. All the preset passmanagers have been updated to use StochasticSwap pass instead of the LegacySwap.

  • The following deprecated qiskit.dagcircuit.DAGCircuit methods have been removed:

    • DAGCircuit.get_qubits() - Use DAGCircuit.qubits() instead

    • DAGCircuit.get_bits() - Use DAGCircuit.clbits() instead

    • DAGCircuit.qasm() - Use a combination of qiskit.converters.dag_to_circuit() and QuantumCircuit.qasm(). For example:

      from qiskit.dagcircuit import DAGCircuit
      from qiskit.converters import dag_to_circuit
      my_dag = DAGCircuit()
      qasm = dag_to_circuit(my_dag).qasm()
    • DAGCircuit.get_op_nodes() - Use DAGCircuit.op_nodes() instead. Note that the return type is a list of DAGNode objects for op_nodes() instead of the list of tuples previously returned by get_op_nodes().

    • DAGCircuit.get_gate_nodes() - Use DAGCircuit.gate_nodes() instead. Note that the return type is a list of DAGNode objects for gate_nodes() instead of the list of tuples previously returned by get_gate_nodes().

    • DAGCircuit.get_named_nodes() - Use DAGCircuit.named_nodes() instead. Note that the return type is a list of DAGNode objects for named_nodes() instead of the list of node_ids previously returned by get_named_nodes().

    • DAGCircuit.get_2q_nodes() - Use DAGCircuit.twoQ_gates() instead. Note that the return type is a list of DAGNode objects for twoQ_gates() instead of the list of data_dicts previously returned by get_2q_nodes().

    • DAGCircuit.get_3q_or_more_nodes() - Use DAGCircuit.threeQ_or_more_gates() instead. Note that the return type is a list of DAGNode objects for threeQ_or_more_gates() instead of the list of tuples previously returned by get_3q_or_more_nodes().

  • The following qiskit.dagcircuit.DAGCircuit methods had deprecated support for accepting a node_id as a parameter. This has been removed and now only DAGNode objects are accepted as input:

    • successors()
    • predecessors()
    • ancestors()
    • descendants()
    • bfs_successors()
    • quantum_successors()
    • remove_op_node()
    • remove_ancestors_of()
    • remove_descendants_of()
    • remove_nonancestors_of()
    • remove_nondescendants_of()
    • substitute_node_with_dag()
  • The qiskit.dagcircuit.DAGCircuit method rename_register() has been removed. This was unused by all the qiskit code. If you were relying on it externally you’ll have to re-implement is an external function.

  • The qiskit.dagcircuit.DAGCircuit property multi_graph has been removed. Direct access to the underlying networkx multi_graph object isn’t supported anymore. The API provided by the DAGCircuit class should be used instead.

  • The deprecated exception class qiskit.qiskiterror.QiskitError has been removed. Instead you should use qiskit.exceptions.QiskitError.

  • The boolean kwargs, ignore_requires and ignore_preserves from the qiskit.transpiler.PassManager constructor have been removed. These are no longer valid options.

  • The module qiskit.tools.logging has been removed. This module was not used by anything and added nothing over the interfaces that Python’s standard library logging module provides. If you want to set a custom formatter for logging use the standard library logging module instead.

  • The CompositeGate class has been removed. Instead you should directly create a instruction object from a circuit and append that to your circuit. For example, you can run something like:

    custom_gate_circ = qiskit.QuantumCircuit(2)
    custom_gate_circ.x(1)
    custom_gate_circ.h(0)
    custom_gate_circ.cx(0, 1)
    custom_gate = custom_gate_circ.to_instruction()
  • The previously deprecated kwargs, seed and config for qiskit.compiler.assemble() have been removed use seed_simulator and run_config respectively instead.

  • The previously deprecated converters qiskit.converters.qobj_to_circuits() and qiskit.converters.circuits_to_qobj() have been removed. Use qiskit.assembler.disassemble() and qiskit.compiler.assemble() respectively instead.

  • The previously deprecated kwarg seed_mapper for qiskit.compiler.transpile() has been removed. Instead you should use seed_transpiler

  • The previously deprecated kwargs seed, seed_mapper, config, and circuits for the qiskit.execute() function have been removed. Use seed_simulator, seed_transpiler, run_config, and experiments arguments respectively instead.

  • The previously deprecated qiskit.tools.qcvv module has been removed use qiskit-ignis instead.

  • The previously deprecated functions qiskit.transpiler.transpile() and qiskit.transpiler.transpile_dag() have been removed. Instead you should use qiskit.compiler.transpile. If you were using transpile_dag() this can be replaced by running:

    circ = qiskit.converters.dag_to_circuit(dag)
    out_circ = qiskit.compiler.transpile(circ)
    qiskit.converters.circuit_to_dag(out_circ)
  • The previously deprecated function qiskit.compile() has been removed instead you should use qiskit.compiler.transpile() and qiskit.compiler.assemble().

  • The jupyter cell magic %%qiskit_progress_bar from qiskit.tools.jupyter has been changed to a line magic. This was done to better reflect how the magic is used and how it works. If you were using the %%qiskit_progress_bar cell magic in an existing notebook, you will have to update this to be a line magic by changing it to be %qiskit_progress_bar instead. Everything else should behave identically.

  • The deprecated function qiskit.tools.qi.qi.random_unitary_matrix() has been removed. You should use the qiskit.quantum_info.random.random_unitary() function instead.

  • The deprecated function qiskit.tools.qi.qi.random_density_matrix() has been removed. You should use the qiskit.quantum_info.random.random_density_matrix() function instead.

  • The deprecated function qiskit.tools.qi.qi.purity() has been removed. You should the qiskit.quantum_info.purity() function instead.

  • The deprecated QuantumCircuit._attach() method has been removed. You should use QuantumCircuit.append() instead.

  • The qiskit.qasm.Qasm method get_filename() has been removed. You can use the return_filename() method instead.

  • The deprecated qiskit.mapper module has been removed. The list of functions and classes with their alternatives are:

    • qiskit.mapper.CouplingMap: qiskit.transpiler.CouplingMap should be used instead.
    • qiskit.mapper.Layout: qiskit.transpiler.Layout should be used instead
    • qiskit.mapper.compiling.euler_angles_1q(): qiskit.quantum_info.synthesis.euler_angles_1q() should be used instead
    • qiskit.mapper.compiling.two_qubit_kak(): qiskit.quantum_info.synthesis.two_qubit_cnot_decompose() should be used instead.

    The deprecated exception classes qiskit.mapper.exceptions.CouplingError and qiskit.mapper.exceptions.LayoutError don’t have an alternative since they serve no purpose without a qiskit.mapper module.

  • The qiskit.pulse.samplers module has been moved to qiskit.pulse.pulse_lib.samplers. You will need to update imports of qiskit.pulse.samplers to qiskit.pulse.pulse_lib.samplers.

  • seaborn(opens in a new tab) is now a dependency for the function qiskit.visualization.plot_state_qsphere(). It is needed to generate proper angular color maps for the visualization. The qiskit-terra[visualization] extras install target has been updated to install seaborn>=0.9.0 If you are using visualizations and specifically the plot_state_qsphere() function you can use that to install seaborn or just manually run pip install seaborn>=0.9.0

  • The previously deprecated functions qiksit.visualization.plot_state and qiskit.visualization.iplot_state have been removed. Instead you should use the specific function for each plot type. You can refer to the following tables to map the deprecated functions to their equivalent new ones:

    Qiskit Terra 0.6Qiskit Terra 0.7+
    plot_state(rho)plot_state_city(rho)
    plot_state(rho, method=’city’)plot_state_city(rho)
    plot_state(rho, method=’paulivec’)plot_state_paulivec(rho)
    plot_state(rho, method=’qsphere’)plot_state_qsphere(rho)
    plot_state(rho, method=’bloch’)plot_bloch_multivector(rho)
    plot_state(rho, method=’hinton’)plot_state_hinton(rho)
  • The pylatexenc and pillow dependencies for the latex and latex_source circuit drawer backends are no longer listed as requirements. If you are going to use the latex circuit drawers ensure you have both packages installed or use the setuptools extras to install it along with qiskit-terra:

    pip install qiskit-terra[visualization]
  • The root of the qiskit namespace will now emit a warning on import if either qiskit.IBMQ or qiskit.Aer could not be setup. This will occur whenever anything in the qiskit namespace is imported. These warnings were added to make it clear for users up front if they’re running qiskit and the qiskit-aer and qiskit-ibmq-provider packages could not be found. It’s not always clear if the packages are missing or python packaging/pip installed an element incorrectly until you go to use them and get an empty ImportError. These warnings should make it clear up front if there these commonly used aliases are missing.

    However, for users that choose not to use either qiskit-aer or qiskit-ibmq-provider this might cause additional noise. For these users these warnings are easily suppressable using Python’s standard library warnings. Users can suppress the warnings by putting these two lines before any imports from qiskit:

    import warnings
    warnings.filterwarnings('ignore', category=RuntimeWarning,
                            module='qiskit')

    This will suppress the warnings emitted by not having qiskit-aer or qiskit-ibmq-provider installed, but still preserve any other warnings emitted by qiskit or any other package.

Deprecation Notes

  • The U and CX gates have been deprecated. If you’re using these gates in your code you should update them to use u3 and cx instead. For example, if you’re using the circuit gate functions circuit.u_base() and circuit.cx_base() you should update these to be circuit.u3() and circuit.cx() respectively.

  • The u0 gate has been deprecated in favor of using multiple iden gates and it will be removed in the future. If you’re using the u0 gate in your circuit you should update your calls to use iden. For example, f you were using circuit.u0(2) in your circuit before that should be updated to be:

    circuit.iden()
    circuit.iden()

    instead.

  • The qiskit.pulse.DeviceSpecification class is deprecated now. Instead you should use qiskit.pulse.PulseChannelSpec.

  • Accessing a qiskit.circuit.Qubit, qiskit.circuit.Clbit, or qiskit.circuit.Bit class by index is deprecated (for compatibility with the (register, index) tuples that these classes replaced). Instead you should use the register and index attributes.

  • Passing in a bit to the qiskit.QuantumCircuit method append as a tuple (register, index) is deprecated. Instead bit objects should be used directly.

  • Accessing the elements of a qiskit.transpiler.Layout object with a tuple (register, index) is deprecated. Instead a bit object should be used directly.

  • The qiskit.transpiler.Layout constructor method qiskit.transpiler.Layout.from_tuplelist() is deprecated. Instead the constructor qiskit.transpiler.Layout.from_qubit_list() should be used.

  • The module qiskit.pulse.ops has been deprecated. All the functions it provided:

    • union
    • flatten
    • shift
    • insert
    • append

    have equivalent methods available directly on the qiskit.pulse.Schedule and qiskit.pulse.Instruction classes. Those methods should be used instead.

  • The qiskit.qasm.Qasm method get_tokens() is deprecated. Instead you should use the generate_tokens() method.

  • The qiskit.qasm.qasmparser.QasmParser method get_tokens() is deprecated. Instead you should use the read_tokens() method.

  • The as_dict() method for the Qobj class has been deprecated and will be removed in the future. You should replace calls to it with to_dict() instead.

Bug Fixes

  • The definition of the CU3Gate has been changed to be equivalent to the canonical definition of a controlled U3Gate.

  • The handling of layout in the pass manager has been standardized. This fixes several reported issues with handling layout. The initial_layout kwarg parameter on qiskit.compiler.transpile() and qiskit.execute() will now lay out your qubits from the circuit onto the desired qubits on the device when transpiling circuits.

  • Support for n-qubit unitaries was added to the BasicAer simulator and unitary (arbitrary unitary gates) was added to the set of basis gates for the simulators

  • The qiskit.visualization.plost_state_qsphere() has been updated to fix several issues with it. Now output Q Sphere visualization will be correctly generated and the following aspects have been updated:

    • All complementary basis states are antipodal

    • Phase is indicated by color of line and marker on sphere’s surface


    • Probability is indicated by translucency of line and volume of marker on

      sphere’s surface

Other Notes

  • The default PassManager for qiskit.compiler.transpile() and qiskit.execute() has been changed to optimization level 1 pass manager defined at qiskit.transpile.preset_passmanagers.level1_pass_manager.

  • All the circuit drawer backends now will express gate parameters in a circuit as common fractions of pi in the output visualization. If the value of a parameter can be expressed as a fraction of pi that will be used instead of the numeric equivalent.

  • When using qiskit.assembler.assemble_schedules() if you do not provide the number of memory_slots to use the number will be inferred based on the number of acquisitions in the input schedules.

  • The deprecation warning on the qiskit.dagcircuit.DAGCircuit property node_counter has been removed. The behavior change being warned about was put into effect when the warning was added, so warning that it had changed served no purpose.

  • Calls to PassManager.run() now will emit python logging messages at the INFO level for each pass execution. These messages will include the Pass name and the total execution time of the pass. Python’s standard logging was used because it allows Qiskit-Terra’s logging to integrate in a standard way with other applications and libraries. All logging for the transpiler occurs under the qiskit.transpiler namespace, as used by logging.getLogger('qiskit.transpiler). For example, to turn on DEBUG level logging for the transpiler you can run:

    import logging
     
    logging.basicConfig()
    logging.getLogger('qiskit.transpiler').setLevel(logging.DEBUG)

    which will set the log level for the transpiler to DEBUG and configure those messages to be printed to stderr.

Aer 0.3

  • There’s a new high-performance Density Matrix Simulator that can be used in conjunction with our noise models, to better simulate real world scenarios.
  • We have added a Matrix Product State (MPS) simulator. MPS allows for efficient simulation of several classes of quantum circuits, even under presence of strong correlations and highly entangled states. For cases amenable to MPS, circuits with several hundred qubits and more can be exactly simulated, e.g., for the purpose of obtaining expectation values of observables.
  • Snapshots can be performed in all of our simulators.
  • Now we can measure sampling circuits with read-out errors too, not only ideal circuits.
  • We have increased some circuit optimizations with noise presence.
  • A better 2-qubit error approximations have been included.
  • Included some tools for making certain noisy simulations easier to craft and faster to simulate.
  • Increased performance with simulations that require less floating point numerical precision.

Ignis 0.2

New Features

Bug Fixes

  • Fixed a bug in RB fit error
  • Fixed a bug in the characterization fitter when selecting a qubit index to fit

Other Notes

  • Measurement mitigation now operates in parallel when applied to multiple results
  • Guess values for RB fitters are improved

Aqua 0.6

Added

  • Relative-Phase Toffoli gates rccx (with 2 controls) and rcccx (with 3 controls).

  • Variational form RYCRX

  • A new 'basic-no-ancilla' mode to mct.

  • Multi-controlled rotation gates mcrx, mcry, and mcrz as a general u3 gate is not supported by graycode implementation

  • Chemistry: ROHF open-shell support

    • Supported for all drivers: Gaussian16, PyQuante, PySCF and PSI4
    • HartreeFock initial state, UCCSD variational form and two qubit reduction for parity mapping now support different alpha and beta particle numbers for open shell support
  • Chemistry: UHF open-shell support

    • Supported for all drivers: Gaussian16, PyQuante, PySCF and PSI4
    • QMolecule extended to include integrals, coefficients etc for separate beta
  • Chemistry: QMolecule extended with integrals in atomic orbital basis to facilitate common access to these for experimentation

    • Supported for all drivers: Gaussian16, PyQuante, PySCF and PSI4
  • Chemistry: Additional PyQuante and PySCF driver configuration

    • Convergence tolerance and max convergence iteration controls.
    • For PySCF initial guess choice
  • Chemistry: Processing output added to debug log from PyQuante and PySCF computations (Gaussian16 and PSI4 outputs were already added to debug log)

  • Chemistry: Merged qiskit-chemistry into qiskit-aqua

  • Add MatrixOperator, WeightedPauliOperator and TPBGroupedPauliOperator class.

  • Add evolution_instruction function to get registerless instruction of time evolution.

  • Add op_converter module to unify the place in charge of converting different types of operators.

  • Add Z2Symmetries class to encapsulate the Z2 symmetries info and has helper methods for tapering an Operator.

  • Amplitude Estimation: added maximum likelihood postprocessing and confidence interval computation.

  • Maximum Likelihood Amplitude Estimation (MLAE): Implemented new algorithm for amplitude estimation based on maximum likelihood estimation, which reduces number of required qubits and circuit depth.

  • Added (piecewise) linearly and polynomially controlled Pauli-rotation circuits.

  • Add q_equation_of_motion to study excited state of a molecule, and add two algorithms to prepare the reference state.

Changed

  • Improve mct’s 'basic' mode by using relative-phase Toffoli gates to build intermediate results.
  • Adapt to Qiskit Terra’s newly introduced Qubit class.
  • Prevent QPE/IQPE from modifying input Operator objects.
  • The PyEDA dependency was removed; corresponding oracles’ underlying logic operations are now handled by SymPy.
  • Refactor the Operator class, each representation has its own class MatrixOperator, WeightedPauliOperator and TPBGroupedPauliOperator.
  • The power in evolution_instruction was applied on the theta on the CRZ gate directly, the new version repeats the circuits to implement power.
  • CircuitCache is OFF by default, and it can be set via environment variable now QISKIT_AQUA_CIRCUIT_CACHE.

Bug Fixes

  • A bug where TruthTableOracle would build incorrect circuits for truth tables with only a single 1 value.
  • A bug caused by PyEDA’s indeterminism.
  • A bug with QPE/IQPE’s translation and stretch computation.
  • Chemistry: Bravyi-Kitaev mapping fixed when num qubits was not a power of 2
  • Setup initial_layout in QuantumInstance via a list.

Removed

  • General multi-controlled rotation gate mcu3 is removed and replaced by multi-controlled rotation gates mcrx, mcry, and mcrz

Deprecated

  • The Operator class is deprecated, in favor of using MatrixOperator, WeightedPauliOperator and TPBGroupedPauliOperator.

IBM Q Provider 0.3

No change

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