Energy Inference of Black-Box Quantum Computers Using Quantum Speed Limit

TL;DR

This paper introduces a method to estimate the energy scales of black-box quantum computers using only operational data and quantum speed limits, revealing fundamental energetic properties from execution times.

Contribution

It proposes a novel approach to infer Hamiltonian energy scales of cloud-based quantum processors solely from measured execution times, without hardware access.

Findings

Estimated energy scales align with typical drive energies in superconducting qubits.

Current gate operations are close to the quantum speed limit.

Method successfully applied to IBM's quantum processor.

Abstract

Cloud-based quantum computers do not provide users with access to hardware-level information such as the underlying Hamiltonians, which obstructs the characterization of their physical properties. We propose a method to infer the energy scales of gate Hamiltonians in such black-box quantum processors using only user-accessible data, by exploiting quantum speed limits. Specifically, we reinterpret the Margolus-Levitin and Mandelstam-Tamm bounds as estimators of the energy expectation value and variance, respectively, and relate them to the shortest time for the processor to orthogonalize a quantum state. This shortest gate time, expected to lie on the nanosecond scale, is inferred from job execution times measured in seconds by employing gate-time amplification. We apply the method to IBM's superconducting quantum processor and estimate the energy scales associated with single-, two-, and three-qubit gates. The order of estimated energy is consistent with typical drive energies in superconducting qubit systems, suggesting that current gate operations approach the quantum speed limit. Our results demonstrate that fundamental energetic properties of black-box quantum computers can be quantitatively accessed through operational time measurements, reflecting the conjugate relationship between time and energy imposed by the uncertainty principle.