{"id":19141,"date":"2024-07-24T22:45:56","date_gmt":"2024-07-24T22:45:56","guid":{"rendered":"https:\/\/liquidinstruments.com\/?p=19141"},"modified":"2025-10-13T00:26:50","modified_gmt":"2025-10-13T00:26:50","slug":"streamlining-experimental-control-stacks-with-flexible-fpga-based-instrumentation-and-python","status":"publish","type":"post","link":"https:\/\/liquidinstruments.com\/webinars\/streamlining-experimental-control-stacks-with-flexible-fpga-based-instrumentation-and-python\/","title":{"rendered":"Streamlining experimental control stacks with flexible, FPGA-based instrumentation and Python","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

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Webinar details<\/b><\/span><\/h2>\n

Date:<\/strong> July 24, 2024<\/span><\/p>\n

Speaker:<\/strong> Jason Ball<\/span><\/p>\n\n <\/div>\n <\/div>\n

\n Watch now<\/span><\/a>\n \n \n \n <\/div>\n <\/div>\n <\/div>[vc_column_text css=””]<\/p>\n

Overview<\/span><\/h2>\n

Automating control of experiments is critical for efficient data taking and repeatable results. To this end, Python has become the programming language of choice for an expansive list of research fields, including bioinformatics, machine learning, and experimental physics, owing to its ease of use and abundant supporting resources.<\/p>\n

During this presentation, we explain how to use Python<\/a> to implement an experimental control stack with Moku<\/a>, a family of reconfigurable, FPGA-based instruments, to maximize efficiency and speed.<\/p>\n

Join us to:<\/span><\/h2>\n