Self-consistent Quantum Linear Response with a Polarizable Embedding Environment.

Area of Science:

• Quantum Computing
• Computational Chemistry
• Quantum Information Science

Background:

• Quantum computing offers potential for complex problem-solving, especially in quantum chemistry.
• Calculating molecular properties and excited states is computationally intensive for classical computers.

Purpose of the Study:

• To compute excitation energies using hybrid quantum-classical algorithms for near-term quantum devices.
• To combine quantum linear response (qLR) with polarizable embedding (PE) for accurate molecular simulations.

Main Methods:

• Employed self-consistent operator manifold of quantum linear response (q-sc-LR) with unitary coupled cluster (UCC) wave functions.
• Utilized a Davidson solver to improve computational efficiency by avoiding full electronic Hessian construction.
• Introduced a novel superposition-state-based technique for computing Hessian-vector products, enhancing noise resilience.

Main Results:

• The PE-UCCSD model demonstrated accuracy comparable to classical PE-CCSD methods for closed-shell systems like butadiene and para-nitroaniline in water.
• The new superposition-state method proved more resilient to hardware noise than previous gradient-based approaches.
• Explored challenges of hardware noise and proposed error mitigation techniques for noisy quantum computations.

Conclusions:

• Hybrid quantum-classical methods, like PE-UCCSD, are viable for accurate excitation energy calculations.
• The developed methods show promise for advancing quantum chemistry simulations on current and future quantum hardware.
• Error mitigation is crucial for obtaining reliable results from noisy quantum computers.