{
  "patent_number": "US 12008436",
  "country": "US",
  "title": "Solving Big Math Problems with Small Quantum Computers",
  "original_title": "Machine learning mapping for quantum processing units",
  "summary": "This patent describes how a classical computer can break down large mathematical problems into smaller pieces that even limited quantum computers can solve, then combine the results.",
  "what_it_does": "This patent describes a method for solving complex mathematical problems, called 'objective functions,' that are too large for current quantum computers. First, a classical computer obtains an objective function that has more variables than the quantum computer has 'logical qubits' (Claim 1). Next, the classical computer uses machine learning to break down this big problem into several smaller 'sub-problems,' each small enough for the quantum computer to handle (Abstract, Claim 1). The quantum computer then solves each sub-problem by initializing its qubits, applying changes (perturbations), and measuring the results multiple times ('shots') (Claim 1). From these measurements, an 'expectation value' is determined for each sub-problem, leading to its solution (Claim 1). Finally, the classical computer gathers all the sub-problem solutions to find the overall solution to the original big problem and stores it (Claim 1). For example, if you have a complex optimization problem with 100 variables, but your quantum computer only has 10 logical qubits, this method would break the 100-variable problem into several 10-variable sub-problems.",
  "what_it_does_not_cover": [
    "Does not cover solving mathematical problems that involve fewer variables than the quantum computer has logical qubits, meaning the problem fits directly on the quantum computer (Claim 1).",
    "Does not cover methods that solve the entire objective function directly on a quantum computer without first decomposing it into smaller sub-problems (Claim 1).",
    "Does not cover purely classical computer systems solving large problems without involving a quantum computing system for sub-problem solutions (Claim 1).",
    "Does not cover determining sub-problem solutions without using an 'expectation value' derived from a set of raw outputs from multiple 'shots' (Claim 1).",
    "Does not cover decomposition methods that do not involve machine learning, as described in the abstract."
  ],
  "filed": "2022-06-30",
  "granted": "2024-06-11",
  "expires": "2042-06-30",
  "status": "active",
  "holder": "Quantum Computing",
  "holder_url": "https://patentbrief.org/company/quantum-computing",
  "inventors": [
    {
      "name": "Jesse Berwald",
      "url": "https://patentbrief.org/inventor/jesse-berwald"
    },
    {
      "name": "Raouf Dridi",
      "url": "https://patentbrief.org/inventor/raouf-dridi"
    },
    {
      "name": "Uchenna Chukwu",
      "url": "https://patentbrief.org/inventor/uchenna-chukwu"
    }
  ],
  "times_cited": 0,
  "tags": [
    "quantum_computing",
    "software",
    "ai_ml",
    "telecommunications",
    "semiconductors"
  ],
  "abstract": "Some embodiments include a process, including obtaining, with a classical computer system, a mathematical problem to be solved by a quantum computing system, wherein: the quantum computing system comprises one or more quantum computers, the mathematical problem involves more variables than any of the one or more quantum computers have logical qubits, and solving the mathematical problem entails determining values of the variables; decomposing, with the classical computer system, the mathematical problem into a plurality of sub-problems, wherein decomposing the mathematical problem into the plurality of sub-problems comprises decomposing the mathematical problem with machine learning into quantum circuits; causing, with the classical computer system, the quantum computing system to solve each of the sub-problems and aggregate solutions to the sub-problems to determine a solution to the mathematical problem; and storing, with the classical computer system, the solution to the mathematical problem in memory.",
  "url": "https://patentbrief.org/patent/us/12008436/machine-learning-mapping-for-quantum-processing-units",
  "markdown_url": "https://patentbrief.org/patent/us/12008436/machine-learning-mapping-for-quantum-processing-units/md",
  "google_patents_url": "https://patents.google.com/patent/US12008436",
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}