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MindQuantum Release Notes

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MindQuantum 0.6.0 Release Notes

Major Features and Improvements

Better iteration supported for QubitOperator and FermionOperator

  • Iterate over a multinomial fermion or boson operator and yield each term
  • When the operator has only one item, each fermion or boson can be obtained through singlet

Add line module

Richer circuit operation supported

  • shift: translation qubit

  • reverse_qubits: flip circuit bit

Feature enhancement

  • MaxCutAnsatz: get_partition, get the max-cut cutting solution
  • MaxCutAnsatz: get_cut_value, get the number of cuts for a cutting solution
  • Circuit: is_measure_end, determine whether the quantum circuit is the end of the measurement gate

SVG drawing mode that supports quantum circuits

  • The quantum circuit build by mindquantum now can be showd by svg in jupyter notebook, just call svg() of any quantum circuits.

Noise simulator supported

MindQuantum adds the following quantum channels for quantum noise simulation

MindQuantum 0.5.0 Release Notes

Major Features and Improvements

API Change

Backwards Incompatible Change

We unified the abbreviations of some nouns in MindQuantum.

  • isparameter property of gate changes to parameterized
0.3.1 0.5.0
>>> from mindquantum import RX
>>> gate = RX('a').on(0)
>>> gate.isparameter
True
>>> from mindquantum import RX
>>> gate = RX('a').on(0)
>>> gate.parameterized
True
  • para_name of a quantum circuit changes to params_name
0.3.1 0.5.0
>>> from mindquantum import Circuit
>>> circ = Circuit().rx('a', 0)
>>> circ.para_name
['a']
>>> from mindquantum import Circuit
>>> circ = Circuit().rx('a', 0)
>>> circ.params_name
['a']

The quantum neural network API was redesigned in this version. From now on, we can easily build a hybrid quantum neural network with the help of Simulator in PYNATIVE_MODE.

The following API was removed.

  1. generate_pqc_operator
  2. PQC
  3. MindQuantumLayer
  4. generate_evolution_operator
  5. Evolution
  6. MindQuantumAnsatzOnlyLayer
  7. MindQuantumAnsatzOnlyOperator

The new API was shown as below.

  1. MQOps
  2. MQN2Ops
  3. MQAnsatzOnlyOps
  4. MQN2AnsatzOnlyOps
  5. MQEncoderOnlyOps
  6. MQN2EncoderOnlyOps
  7. MQLayer
  8. MQN2Layer
  9. MQAnsatzOnlyLayer
  10. MQN2AnsatzOnlyLayer

The above modules are placed in mindquantum.framework.

Removed

Due to the duplication of functions, we deleted some APIs.

  • mindquantum.circuit.StateEvolution

The following APIs have been remoted.

  • mindquantum.core.operators.Hamiltonian.mindspore_data
  • mindquantum.core.operators.Projector.mindspore_data
  • mindquantum.core.circuit.Circuit.mindspore_data
  • mindquantum.core.parameterresolver.ParameterResolver.mindspore_data

New feature

New gates are shown as below.

  • mindquantum.core.gates.SGate
  • mindquantum.core.gates.TGate

Measurement on certain qubits are now supported. The related APIs are shown as below.

  • mindquantum.core.gates.Measure
  • mindquantum.core.gates.MeasureResult

QASM is now supported.

  • mindquantum.io.OpenQASM
  • mindquantum.io.random_hiqasm
  • mindquantum.io.HiQASM

Simulator is now separated from MindSpore backend. Now you can easily to use a simulator.

  • mindquantum.simulator.Simulator

Refactoring

For improving MindQuantum's package structure, we did some refactoring on MindQuantum.

old new

mindquantum.gate.Hamiltonian

mindquantum.core.operators.Hamiltonian

mindquantum.gate.Projector

mindquantum.core.operators.Projector

mindquantum.circuit.qft

mindquantum.algorithm.library.qft

mindquantum.circuit.generate_uccsd

mindquantum.algorithm.nisq.chem.generate_uccsd

mindquantum.circuit.TimeEvolution

mindquantum.core.operators.TimeEvolution

mindquantum.utils.count_qubits

mindquantum.core.operators.count_qubits

mindquantum.utils.commutator

mindquantum.core.operators.commutator

mindquantum.utils.normal_ordered

mindquantum.core.operators.normal_ordered

mindquantum.utils.get_fermion_operator

mindquantum.core.operators.get_fermion_operator

mindquantum.utils.number_operator

mindquantum.core.operators.number_operator

mindquantum.utils.hermitian_conjugated

mindquantum.core.operators.hermitian_conjugated

mindquantum.utils.up_index

mindquantum.core.operators.up_index

mindquantum.utils.down_index

mindquantum.core.operators.down_index

mindquantum.utils.sz_operator

mindquantum.core.operators.sz_operator

mindquantum.ansatz.Ansatz

mindquantum.algorithm.nisq.Ansatz

mindquantum.ansatz.MaxCutAnsatz

mindquantum.algorithm.nisq.qaoa.MaxCutAnsatz

mindquantum.ansatz.Max2SATAnsatz

mindquantum.algorithm.nisq.qaoa.Max2SATAnsatz

mindquantum.ansatz.HardwareEfficientAnsatz

mindquantum.algorithm.nisq.chem.HardwareEfficientAnsatz

mindquantum.ansatz.QubitUCCAnsatz

mindquantum.algorithm.nisq.chem.QubitUCCAnsatz

mindquantum.ansatz.UCCAnsatz

mindquantum.algorithm.nisq.chem.UCCAnsatz

mindquantum.hiqfermion.Transform

mindquantum.algorithm.nisq.chem.Transform

mindquantum.hiqfermion.get_qubit_hamiltonian

mindquantum.algorithm.nisq.chem.get_qubit_hamiltonian

mindquantum.hiqfermion.uccsd_singlet_generator

mindquantum.algorithm.nisq.chem.uccsd_singlet_generator

mindquantum.hiqfermion.uccsd_singlet_get_packed_amplitudes

mindquantum.algorithm.nisq.chem.uccsd_singlet_get_packed_amplitudes

mindquantum.hiqfermion.uccsd0_singlet_generator

mindquantum.algorithm.nisq.chem.uccsd0_singlet_generator

mindquantum.hiqfermion.quccsd_generator

mindquantum.algorithm.nisq.chem.quccsd_generator

mindquantum.utils.bprint

mindquantum.io.bprint

mindquantum.circuit

mindquantum.core.circuit

mindquantum.gate

mindquantum.core.gates

mindquantum.ops

mindquantum.core.operators

mindquantum.parameterresolver

mindquantum.core.parameterresolver

Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, Damien Ngyuen, zhouxu, wangzidong, yangkang, lujiale, zhangzhenghai, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

MindQuantum 0.3.1 Release Notes

Major Features and Improvements

  • Three tutorials have been rewritten to make them easier to read
  • Circuit information such as qubit number, parameters will update immediately after you add gate
  • The UN operator now support parameterized gate
  • New ansatz that solving max 2 sat problem now are supported

Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wangzidong, yangkang, lujiale, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

MindQuantum 0.2.0 Release Notes

Major Features and Improvements

  1. Parameterized FermionOperator and QubitOperator for quantum chemistry
  2. Different kinds of transformation between FermionOperator and QubitOperator
  3. UCCSD, QAOA and hardware efficient ansatz supported
  4. MindQuantumAnsatzOnlyLayer for simulating circuit with ansatz only circuit
  5. TimeEvolution with first order Trotter decomposition
  6. High level operations for modifying quantum circuit

Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wangzidong, yangkang, lujiale, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

MindQuantum 0.1.0 Release Notes

Initial release of MindQuantum.

Major Features and Improvements

  1. Easily build parameterized quantum circuit.
  2. Effectively simulate quantum circuit.
  3. Calculating the gradient of parameters of quantum circuit.
  4. PQC (parameterized quantum circuit) operator that naturally compatible with other operators in mindspore framework.
  5. Evolution operator that evaluate a quantum circuit and return the quantum state.
  6. Data parallelization for PQC operator.

Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wangzidong, yangkang, lujiale, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng. MindQuantum adds the following quantum channels for quantum noise simulation

Contributions of any kind are welcome!

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