{"ID":2866255,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.21661","arxiv_id":"2509.21661","title":"Automating Sensor Characterization with Bayesian Optimization","abstract":"The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert's time. In this work, we present a novel technique for automated sensor characterization that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.","short_abstract":"The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bott...","url_abs":"https://arxiv.org/abs/2509.21661","url_pdf":"https://arxiv.org/pdf/2509.21661v2","authors":"[\"J. Cuevas-Zepeda\",\"C. Chavez\",\"J. Estrada\",\"J. Noonan\",\"B. D. Nord\",\"N. Saffold\",\"M. Sofo-Haro\",\"R. Spinola e Castro\",\"S. Trivedi\"]","published":"2025-09-25T22:31:15Z","proceeding":"physics.ins-det","tasks":"[\"physics.ins-det\",\"astro-ph.IM\",\"cs.LG\"]","methods":"[]","has_code":false}