Systems and methods for finding quantum binary optimization problems

This invention describes a method for creating specific types of problems that quantum computers can solve. It works by translating problem constraints into a mathematical model (an Ising model) that clearly separates correct answers from incorrect ones, ensuring a distinct "penalty gap." The method also takes into account the specific limitations of the quantum computer's hardware. The claims specify that a first computer sets up these problems for a second, quantum computer, potentially using random selection or a "tabu search" technique.

Why it matters: Since 2015, quantum computing hardware has advanced significantly, offering more accessible platforms and improved performance. This makes the design of hardware-aware optimization problems, as described, more practical and essential for leveraging current quantum capabilities.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedQuantum computing expertise, algorithm design, hardware integration

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