Quantum-Chiplet: A Novel Python-Based Efficient and Scalable Design Methodology for Quantum Circuit Verification and Implementation

• URL: http://arxiv.org/abs/2503.10054v1
• Date: Thu, 13 Mar 2025 05:12:41 GMT
• Title: Quantum-Chiplet: A Novel Python-Based Efficient and Scalable Design Methodology for Quantum Circuit Verification and Implementation
• Authors: Yu-Ting Kao, Hao-Yu Lu, Yeong-Jar Chang, Darsen Lu,
• Abstract summary: We propose a new quantum representation (QPR) to facilitate the analysis of massively parallel quantum computation.<n>For the verification of quantum circuits, we introduce Quantum-Chiplet, a hierarchical quantum behavior modeling methodology.<n>A quantum amplitude estimation example demonstrates that this method significantly improves the design process, with more than 10x speed-up compared to IBM Qiskit at 14 qubits.
• Score: 5.727672509269657
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Analysis and verification of quantum circuits are highly challenging, given the exponential dependence of the number of states on the number of qubits. For analytical derivation, we propose a new quantum polynomial representation (QPR) to facilitate the analysis of massively parallel quantum computation and detect subtle errors. For the verification of quantum circuits, we introduce Quantum-Chiplet, a hierarchical quantum behavior modeling methodology that facilitates rapid integration and simulation. Each chiplet is systematically transformed into quantum gates. For circuits involving n qubits and k quantum gates, the design complexity is reduced from "greater than O(2^n)" to O(k). This approach provides an open-source solution, enabling a highly customized solution for quantum circuit simulation within the native Python environment, thereby reducing reliance on traditional simulation packages. A quantum amplitude estimation example demonstrates that this method significantly improves the design process, with more than 10x speed-up compared to IBM Qiskit at 14 qubits.

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