MindQuantum 0.6.0

MindQuantum 0.6.0 Release Notes

Major Features and Improvements

Better iteration supported for QubitOperator and FermionOperator

The following example will be demonstrated with QubitOperator

• Iter multiple terms QubitOperator

>>> from mindquantum.core.operators import QubitOperator
>>> ops = QubitOperator('X0 Y1', 1) + QubitOperator('Z2 X3', {'a': 3})

>>> for idx, o in enumerate(ops):
>>>     print(f'Term {idx}: {o}')

You will get each term of this operator,

Term 0: 1 [X0 Y1]
Term 1: 3*a [Z2 X3]

• Iter single term QubitOperator

>>> ops = QubitOperator('X0 Y1', 2)

>>> for idx, o in enumerate(ops.singlet()):
>>>     print(f'Word {idx}: {o}')

You will get each word of this operator with coefficient set to identity,

Word 0: 1 [X0]
Word 1: 1 [Y1]

More built-in circuit supported

• general_w_state: circuit that can prepare a w state.
• general_ghz_state: circuit that can prepare a ghz state.
• bitphaseflip_operator: circuit that can flip the sign of one or multiple calculation base.
• amplitude_encoder: circuit that can encode classical number into quantum amplitude.

Richer circuit operation supported

For origin circuit,

>>> from mindquantum.core.circuit import Circuit
>>> circuit = Circuit().z(0).rx('a', 1, 0).y(1)

q0: ──Z──────●─────────
             │
q1: ───────RX(a)────Y──

• shift operator will shift the qubit index.

from mindquantum.core.circuit import shift
>>> shift(circuit, 2)

q2: ──Z──────●─────────
             │
q3: ───────RX(a)────Y──

• Reverse circuit qubits, the circuit will be flipped upside down.

>>> circuit.reverse_qubits()

q0: ───────RX(a)────Y──
             │
q1: ──Z──────●─────────

Feature enhancement

• MaxCutAnsatz: get_partition
• MaxCutAnsatz: get_cut_value
• Circuit: is_measure_end

SVG supported

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

>>> from mindquantum import *

>>> circuit = (qft(range(3)) + BarrierGate(True)).measure_all()
>>> circuit.svg()

Noise simulator supported

In This version, we can simulate a quantum circuit in noise simulator just by adding different noise channels. The following are supported channels:

• PauliChannel
• BitFlipChannel
• PhaseFlipChannel
• BitPhaseFlipChannel
• DepolarizingChannel

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 0.5.0 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

>>> 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

>>> 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.

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.

Contributions of any kind are welcome!