QSimVerifier: A Zero-Cost AI-Based Framework for Testing, Verification, and Optimization of Qiskit Circuits Using Local Simulators
Jeshik S
Jeshik S, Department of Computer Science and Engineering, R V College of Engineering, Bangalore (Karnataka), India.
Manuscript received on 21 September 2025 | First Revised Manuscript received on 12 November 2025 | Second Revised Manuscript received on 20 November 2025 | Manuscript Accepted on 15 December 2025 | Manuscript published on 30 December 2025 | PP: 32-37 | Volume-14 Issue-1, December 2025 | Retrieval Number: 100.1/ijese.L261813121125 | DOI: 10.35940/ijese.L2618.14011225
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Quantum computing uses qubits that can be in su perposed and entangled states, letting some problems be repre sented and explored differently than with classical bits. It can speed up tasks such as molecular simulations, optimisation, and specific searches when a quantum algorithm matches the prob lem at hand. However, hardware is fragile: qubits decohere, gates are imperfect, crosstalk and noise accumulate, and long circuits often produce incorrect results. QSimVerifier helps by testing quantum programs before they run on real machines. It models device factors (coherence times, gate error rates, crosstalk, tem perature), computes per-gate risk, and generates program vari ants to reveal fragile spots. The tool creates readable reports, visualizations, and hardware-specific recommendations, propos ing mitigations such as simpler gate sequences or error mitigation techniques. By flagging high-risk gates and suggesting fixes, QSimVerifier raises confidence that programs will run correctly on available devices.
Keywords: Quantum Computing, Decoherence, Gate Error, Crosstalk, Mutation Testing, Robustness, Reliability.
Scope of the Article: Artificial Intelligence and Methods