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!104 verify quantum mep docs

From: @kangyangzc
Reviewed-by: @leonwanghui
Signed-off-by: @leonwanghui
pull/104/MERGE
mindspore-ci-bot Gitee 5 years ago
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      design/meps/mep-quantum/MEP-QUANTUM.md

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@@ -55,7 +55,7 @@ To address the limitations of existing quantum-machine-learning framework, propo
### User Stories

Quantum neural network can be described by quantum circuit model. A quantum circuit is composed of quantum qubits, quantum gates and measurements. The quantum qubits are implemented by different quantum systems, such as Josephson junction, trapped ion, NV center, etc. For a quantum system with $n$ qubits, the quantum state vector is in a
$2^n$-by-$2^n$ dimension Hillbert space. Quantum gates are represented by quantum operators that act on these quantum qubits. There are two kinds of quantum gates, non-parameterized gate and parameterized gate. The Pauli gate $X, Y, Z$, hadamard gate $H$ and CNot gate are commonly used in the non-parameterized gate set. On the other hand, the parameterized gates are trainable in a quantum circuit. Rotation-X gate $\text{Rx}(\theta)$ is one of them, for example, and we can adjust the rotation angle $\theta$ by the expectation value of measurements. The measurements applied on the end of quantum circuit will return the probability of the quantum state collapsed on certain bit strings.
$2^n$ dimension Hillbert space. Quantum gates are represented by quantum operators that act on these quantum qubits. There are two kinds of quantum gates, non-parameterized gate and parameterized gate. The Pauli gate $X, Y, Z$, hadamard gate $H$ and CNot gate are commonly used in the non-parameterized gate set. On the other hand, the parameterized gates are trainable in a quantum circuit. Rotation-X gate $\text{Rx}(\theta)$ is one of them, for example, and we can adjust the rotation angle $\theta$ by the expectation value of measurements. The measurements applied on the end of quantum circuit will return the probability of the quantum state collapsed on certain bit strings.

Figure 1[8] shows a basic structure of parameterized quantum circuit operator in MindSpore. Here we have 8 quantum qubits, and the measurement is applied to the first qubit. The whole quantum circuit is construct by a encoding circuit $U(\rho_{\text{in}})$, which will prepare the quantum system in a certain initial state, and an ansatz circuit combined by CNOT gate and Rotation gate, with rotation angle can be trained by MindSpore.



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