Year: 2023
Type: article
Abstract: State-of-the-art noisy digital quantum computers can only execute short-depth quantum circuits. Variational algorithms are a promising route to unlock the potential of noisy quantum computers since the depth of the corresponding circuits can be kept well below hardware-imposed limits. Typically, the variational parameters correspond to virtual ${R}_{Z}$ gate angles, implemented by phase changes of calibrated pulses. By encoding the variational parameters directly as hardware pulse amplitudes and durations, we succeed in further shortening the pulse schedule and overall circuit duration. This decreases the impact of qubit decoherence and gate noise. As a demonstration, we apply our pulse-based variational algorithm to the calculation of the ground state of different hydrogen-based systems (${\mathrm{H}}_{2}, {\mathrm{H}}_{3}$, and ${\mathrm{H}}_{4}$) using IBM cross-resonance-based hardware. We observe a reduction in schedule duration of up to $5\ifmmode\times\else\texttimes\fi{}$ compared to cnot-based Ans\"atze, while also reducing the measured energy. In particular, we observe a sizable improvement of the minimal energy configuration of ${\mathrm{H}}_{3}$ compared to a cnot-based variational form. Finally, we discuss possible future developments including error-mitigation schemes and schedule optimizations, which will enable further improvements of our approach, paving the way towards the simulation of larger systems on noisy quantum devices.
Source: Physical Review Research
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,625
Funders: National Science Foundation, International Business Machines Corporation, European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Horizon 2020 Framework Programme, National Center of Competence in Research Materials’ Revolution: Computational Design and Discovery of Novel Materials, NCCR Catalysis
OpenAlex ID: W4386443796
