Fig. 1 | Scientific Reports

Fig. 1

From: A Flexible Hybrid Quantum-classical Training Framework of Organ-at-Risk and Tumor Segmentation Models for Radiation Therapy Planning

Fig. 1The alt text for this image may have been generated using AI.

The Illustration of the Quantum Circuit We Designed. Like neural networks, the variational part of the quantum circuit consists of repeated blocks; as the number of blocks increases, both the representational capacity and the parameter count of the circuit increase accordingly. Longitudinally, the circuit is composed of N qubits, while transversely, the variational structure consists of K repeated strongly-entangled blocks. Qubits are all initialized to zeros. RX and RY all carry parameters, representing rotations around the X-axis and Y-axis respectively. The H gate is the Hadamard gate, which puts qubits into a superposition state. The CNOT gate is the controlled NOT gate, used for entangling qubits. Measurement operations are used to obtain the state of qubits.

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