An Analytically Trained Variational Surrogate for Quantum Phase Estimation on NISQ Hardware
Quantum Phase Estimation (QPE) is a foundational algorithm for molecular ground-state energy estimation, but its deep circuit requirements make direct hardware execution impractical on Noisy Intermediate-Scale Quantum (NISQ) devices. We present an analytically grounded variational surrogate framework in which a shallow Variational Quantum Circuit (VQC) is trained to reproduce the QPE measurement distribution without any quantum circuit simulation. The training target is computed entirely classically via the Dirichlet kernel, evaluated directly from the Full Configuration Interaction (FCI) ground-state energy, the ancilla qubit count, and the time evolution parameter, eliminating the expon...
| Authors | Mousumi Kundu, Ashish Kumar Patra, Anurag K. S. V. et al. |
|---|---|
| Primary category | quant-ph |
| Published | 23 July 2026 |
| Last updated at source | 23 July 2026 |
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