Fermilab Leads Quantum Sensor Project to Detect Dark Matter Using Spin Qubits

Fermilab is leading the Quandarum project in collaboration with Diraq, the University of Wisconsin-Madison, the University of Chicago, and Manchester University. The goal is to develop a quantum sensor capable of detecting axions, hypothetical particles considered candidates for dark matter. Funded by the U.S. Department of Energy’s QuantISED program as part of a $71 million initiative across 25 projects, Quandarum aims to integrate silicon spin qubits with cryogenic readout circuits on a single chip, creating a scalable platform for advanced dark matter detection.

The Quandarum project focuses on integrating spin qubits with cryogenic readout technology to create advanced quantum sensors. Spin qubits leverage the spin state of electrons in silicon, offering high stability and scalability, making them ideal for large-scale quantum sensing arrays. Cryogenic readout technology is essential for accurately detecting the fragile states of these qubits, as it operates at extremely low temperatures to minimize noise and preserve quantum coherence.

Diraq’s role in manufacturing silicon spin qubits involves embedding them into a cryogenic environment where they can be precisely monitored. This setup allows for the detection of subtle changes in the qubit states, which are critical for identifying particles like axions. The project employs Application-Specific Integrated Circuits (ASICs) designed to enhance performance and reduce interference, ensuring reliable data acquisition under challenging conditions.

Fermilab contributes expertise in managing extreme environment electronics, crucial for the cryogenic infrastructure necessary for these sensors. Diraq’s role is pivotal in manufacturing silicon spin qubits at scale, utilizing established CMOS fabrication processes to ensure consistency and quality. This collaboration enables the development of scalable quantum sensing platforms with potential applications beyond dark matter detection, including other high-energy physics research areas.

The project addresses technical challenges such as maintaining qubit coherence and improving readout accuracy through iterative development of ASICs, which are custom-designed to enhance performance and reduce interference. The collaboration also involves universities developing algorithms and physics models to interpret data effectively, potentially using advanced techniques like machine learning.

Beyond dark matter detection, the sensors have potential applications in other high-energy physics research areas. The project’s success hinges on overcoming challenges like qubit decoherence and environmental noise, with plans to scale up qubit numbers for higher sensitivity while managing complexity. Overall, Quandarum represents a comprehensive approach combining hardware development, cryogenic technology, and advanced data processing to advance quantum sensing capabilities.