End-to-end resource analysis for quantum interior point methods and portfolio optimization

Understand

We study quantum interior point methods (QIPMs) for second-order cone programming (SOCP), guided by the example use case of portfolio optimization (PO).

• We provide a complete quantum circuit-level description of the algorithm from problem input to problem output, making several improvements to the implementation of the QIPM.
• We report the number of logical qubits and the quantity/depth of non-Clifford T-gates needed to run the algorithm, including constant factors.
• The resource counts we find depend on instance-specific parameters, such as the condition number of certain linear systems within the problem.