Lists
Lists
Redwan, Kazi, Ahmed, Mustakim, Al Sohan, Md. Faruk Abdullah, Islam, Sajedul, Tamang, Birbal, Lama, Rasmila, Shrestha, Ruja and Shufian, Abu (2026) Design and optimization of complex quantum circuits targeting near-term Quantum processors using custom algorithms and Qiskit Transpiler. In: TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON), 27-30 October 2025, Kota Kinabalu, Malaysia.
Quantum computing faces challenges such as noise, short coherence time, and limited qubit connections. These challenges worsen as quantum circuits become more complex. One major issue is the increasing depth of quantum circuits. This research proposes an optimization framework targeting depth and gate count reduction in quantum circuits, specifically for Noisy Intermediate-Scale Quantum (NISQ) devices. The proposed approach combines unitary merging of single-qubit gates, CNOT cancellation, gate commuting, and rotation gate rewriting strategies. Consecutive gates acting on the same qubit, such as Rx(θ1)⋅Rx(θ2), are algebraically merged into a single rotation, while pairs of redundant CNOT gates are eliminated based on gate identity relations. The technique is implemented using Qiskit and validated across five diverse circuits including complex, random, and multi-qubit configurations. Experimental results show an average depth reduction of 33.33% and gate count reduction of 32.14%, with runtime improvement of up to 25%. For instance, an input circuit with a depth of 7 and gate count of 11 was reduced to a depth of 2 and 4 gates. All optimized circuits preserve functional correctness with a fidelity F≥0.99. High-resolution circuit diagrams are presented to visually demonstrate improvements before and after optimization. Additionally, global phase shifts such as eiπ/4 are preserved or analytically characterized where relevant. This work enhances the viability of quantum computations on near-term hardware and opens pathways for future AI-driven quantum optimizations.
 |
View Item |