2025/05/27 by Adriel I. Santoso, Santoso, Adriel I., Le Bin Ho +1 · 1 citation
Engineering · #Astrophysics of Galaxies (astro-ph.GA) #CCD and CMOS Imaging Sensors #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Molecular Communication and Nanonetworks #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2505.21188
openalex publication_date 2025/05/27 · openalex created_date 2025/10/18 · openalex updated_date 2026/07/28
Dark matter (DM) remains one of the most compelling unresolved problems in fundamental physics, motivating the search for new detection approaches. We propose a network-based quantum sensor architecture to enhance sensitivity to ultralight DM fields. Each node in the network is a superconducting qubit, interconnected via controlled-Z gates in symmetric topologies such as line, ring, star, and fully connected graphs. We investigate four- and nine-qubit systems, optimizing both state preparation and measurement using a variational quantum metrology framework. This approach minimizes the quantum and classical Cramér-Rao bounds to identify optimal configurations. Bayesian inference is employed to extract the DM-induced phase shift from measurement outcomes. Our results show that optimized network configurations significantly outperform conventional GHZ-based protocols while maintaining shallow circuit depths compatible with noisy intermediate-scale quantum hardware. Sensitivity remains robust under local dephasing noise. These findings highlight the importance of network structure in quantum sensing and point toward scalable strategies for quantum-enhanced DM detection.