JPMorgan and Amazon develop quantum tools for finance problems

Investing.com -- JPMorgan Chase and the Amazon Advanced Solutions Lab announced today a research program focused on quantum technologies for complex optimization problems in finance.

The collaboration produced three research papers that provide tools for solving large-scale optimization problems on near-term Rydberg quantum hardware. The researchers developed methods to use quantum devices as co-processors alongside classical solvers.

The first paper addresses portfolio optimization and rebalancing problems. The research team created a decomposition pipeline that reduces the size of real-world portfolio optimization problems by approximately 80% while maintaining solution quality. The pipeline showed a 3x reduction in time-to-solution for large-scale portfolio optimization problems with up to 1,500 variables.

The second paper introduced a quantum compilation toolkit for solving the maximum independent set problem on Rydberg atom arrays. The toolkit reduced qubit requirements for real-world graphs by orders of magnitude. For example, the Cora citation graph with approximately 2,700 nodes previously required about 29 million qubits using earlier methods. The new approach reduced this to tens of qubits.

The third paper presented qReduMIS, a hybrid quantum-classical algorithm where quantum computers serve as co-processors. The algorithm combines exact polynomial-time reduction logic with quantum measurement data. Experiments on QuEra's Aquila device on Amazon Braket showed above 89% average success rates on hard problem instances.

The researchers conducted experiments with up to 231 qubits on QuEra's Aquila quantum device available through Amazon Braket. The tools are designed to work with analog neutral-atom quantum machines based on Rydberg atoms.

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