Method and device for processing quantum data

A method for processing quantum data, comprising:

• determining a quantum data set and category information characterizing a data type of the quantum data set;
• applying a local quantum circuit to a quantum data point contained in the quantum data set, wherein the local quantum circuit is obtained after part of qubits are selected from a plurality of qubits contained in a parameterized quantum circuit;
• acquiring state information of qubits in the local quantum circuit after being applied to the quantum data point through measurement, and taking the state information and the category information as training data for training a classical neural network;
• and
• inputting the training data into the classical neural network to train the classical neural network and obtain a trained classical neural network, wherein a data type of a quantum data set to be processed can be identified by the trained classical neural network.

A quantum device, comprising:

• an information determination unit configured for determining a quantum data set and category information characterizing a data type of the quantum data set;
• a circuit processing unit configured for applying a local quantum circuit to a quantum data point contained in the quantum data set, wherein the local quantum circuit is obtained after part of qubits are selected from a plurality of qubits contained in a parameterized quantum circuit;
• and
• a measurement unit configured for acquiring state information of qubits in the local quantum circuit after being applied to the quantum data point through measurement, and taking the state information and the category information as training data for training a classical neural network to obtain a trained classical neural network, wherein a data type of a quantum data set to be processed can be identified by the trained classical neural network.

A quantum device for processing quantum data, comprising:

• a quantum data processing unit configured for determining a quantum data set and category information characterizing a data type of the quantum data set;
• applying a local quantum circuit to a quantum data point contained in the quantum data set, wherein the local quantum circuit is obtained after part of qubits are selected from a plurality of qubits contained in a parameterized quantum circuit;
• a quantum circuit measuring unit configured for acquiring state information of qubits in the local quantum circuit after being applied to the quantum data point through measurement, and taking the state information and the category information as training data for training a classical neural network;
• and
• a classical data processing unit configured for inputting the training data into the classical neural network to train the classical neural network and obtain a trained classical neural network, wherein a data type of a quantum data set to be processed can be identified by the trained classical neural network.