{"id":8442,"date":"2022-01-27T09:00:00","date_gmt":"2022-01-27T17:00:00","guid":{"rendered":"https:\/\/azure.microsoft.com\/en-us\/blog\/quantum\/?p=8442"},"modified":"2025-01-15T14:42:59","modified_gmt":"2025-01-15T22:42:59","slug":"nasas-jpl-uses-microsofts-azure-quantum-to-manage-communication-with-space-missions","status":"publish","type":"post","link":"https:\/\/azure.microsoft.com\/en-us\/blog\/quantum\/2022\/01\/27\/nasas-jpl-uses-microsofts-azure-quantum-to-manage-communication-with-space-missions\/","title":{"rendered":"NASA\u2019s JPL uses Microsoft\u2019s Azure Quantum to manage communication with space missions"},"content":{"rendered":"\n

Effective 10\/13\/2023, we\u2019re pleased to share that the Microsoft Quantum Inspired Optimization (QIO) solver is now available on GitHub under the MIT license in collaboration with KPMG. We\u2019re excited for vibrant, community based QIO innovation to continue and generate progress and applications. Access here on GitHub<\/a>.<\/em><\/p>\n\n\n

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As NASA launches more frequent and complex missions into space, managing communications with the growing number of spacecraft is becoming increasingly challenging. NASA\u2019s Jet Propulsion Laboratory (JPL) has turned to Azure Quantum to explore ways to communicate more efficiently with spacecraft exploring our solar system and beyond.<\/p>\n\n\n\n

JPL communicates with space missions through the Deep Space Network (DSN)<\/a>, a global network of large radio antennae located in California, Spain, and Australia that allows constant communication with spacecraft as the earth rotates.<\/p>\n\n\n\n

Scheduling requests to use the DSN antennae from the space missions come with a large number of constraints and require intensive computing resources. All missions require access for key communication, resulting in several hundred weekly requests when each spacecraft is visible to the antenna. Recent space missions like the Mars 2020 Perseverance Rover<\/a> and the James Webb Space Telescope<\/a> also require higher-fidelity data operations that significantly increase the load on the DSN.<\/p>\n\n\n\n

Taking a Quantum-inspired approach to scheduling optimization<\/h2>\n\n\n\n

For highly complex, multivariate problems like this, quantum-inspired optimization algorithms<\/a> that take learnings and advancements from our key research in quantum technology and implement them in classical algorithms provide a key advantage over traditional optimization algorithms. The Azure Quantum team developed a solution for a version of JPL\u2019s scheduling problem with a limited feature set with the eventual goal to incorporate a broader set of requirements. This is intended to reduce the need for lengthy negotiations and speed up the overall process.<\/p>\n\n\n\n

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