Understanding and mitigating noise in molecular quantum linear response for spectroscopic properties on quantum...

Area of Science:

• Quantum computing
• Quantum chemistry
• Spectroscopy

Background:

• Quantum computing promises to overcome classical computational limits in quantum chemistry.
• Existing quantum algorithms often overlook quantum shot noise and the limitations of current noisy devices.

Purpose of the Study:

• To comprehensively study quantum linear response (qLR) theory for spectroscopic properties on both simulated fault-tolerant and present-day noisy quantum hardware.
• To introduce novel noise analysis metrics and an Ansatz-based error mitigation technique.

Main Methods:

• Simulated fault-tolerant quantum computers and near-term quantum hardware were used to obtain spectroscopic properties via qLR theory.
• Novel metrics were developed to analyze and predict noise origins in quantum algorithms.
• An Ansatz-based error mitigation technique was proposed and tested.
• The impact of Pauli saving on measurement costs and noise in subspace methods was investigated.

Main Results:

• Absorption spectra were obtained on quantum hardware with accuracy comparable to classical multi-configurational methods, using up to a cc-pVTZ basis set.
• Novel metrics and error mitigation techniques were introduced to address noise in quantum algorithms.
• Pauli saving was shown to significantly reduce measurement costs and noise in subspace methods.

Conclusions:

• Quantum linear response theory can achieve classical accuracy for spectroscopic properties on quantum hardware.
• Significant advancements in quantum hardware error rates and measurement speed are crucial for quantum computational chemistry to move beyond a proof-of-concept stage.