Parameter optimization of Josephson parametric amplifiers using a heuristic search algorithm for axion haloscope search
Younggeun Kim, Junu Jeong, SungWoo Youn, Sungjae Bae, Arjan F. van, Loo, Yasunobu Nakamura, Sergey Uchaikin, and Yannis K. Semertzidis

TL;DR
This paper introduces a heuristic search method to optimize Josephson parametric amplifiers, improving their performance for axion dark matter detection by dynamically tuning parameters to maximize signal-to-noise ratio.
Contribution
It applies the Nelder-Mead heuristic algorithm to optimize JPA parameters, enhancing reliability and broadband search capabilities in axion haloscope experiments.
Findings
Optimized JPA parameters increase gain and reduce noise temperature.
The heuristic method adapts to environmental variations for reliable operation.
Enhanced detection sensitivity for axion signals.
Abstract
The cavity haloscope is among the most widely adopted experimental platforms designed to detect dark matter axions with its principle relying on the conversion of axions into microwave photons in the presence of a strong magnetic field. The Josephson parametric amplifier (JPA), known for its quantum-limited noise characteristics, has been incorporated in the detection system to capture the weakly interacting axion signals. However, the performance of the JPA can be influenced by its environment, leading to potential unreliability of a predefined parameter set obtained in a specific laboratory setting. Furthermore, conducting a broadband search requires consecutive characterization of the amplifier across different tuning frequencies. To ensure more reliable measurements, we utilize the Nelder-Mead technique as a numerical search method to dynamically determine the optimal operating…
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