A variational eigenvalue solver on a photonic quantum processor.

Area of Science:

• Quantum computing
• Quantum chemistry
• Computational physics

Background:

• Quantum computers offer solutions to problems intractable for classical computers.
• Finding eigenvalues of operators in large quantum systems is a fundamental challenge.
• Existing quantum algorithms like quantum phase estimation require full coherence.

Purpose of the Study:

• To develop an alternative quantum approach for eigenvalue problems with reduced coherence requirements.
• To combine this method with novel state preparation techniques using ansätze and classical optimization.
• To experimentally validate the approach for a quantum chemistry application.

Main Methods:

• Developed a novel quantum algorithm reducing the need for long coherent evolution.
• Integrated a new state preparation method utilizing ansätze and classical optimization.
• Implemented the algorithm on a reconfigurable photonic quantum processor interfaced with a classical computer.

Main Results:

• Successfully reduced the coherence time requirements for quantum eigenvalue calculations.
• Experimentally demonstrated the feasibility of the approach by calculating the ground-state molecular energy of He-H(+).
• Validated the potential of near-term quantum devices for practical applications.

Conclusions:

• The proposed quantum algorithm significantly lowers coherence demands, making it suitable for current quantum hardware.
• This method broadens the applicability of quantum computation for complex scientific problems, including quantum chemistry.
• Enhances the practical utility of existing and upcoming quantum resources.