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Reynolds Earns $5,000 Martinis Grant for Qubit Control

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October 31, 2026 by Ivy Delaney

Mia Reynolds, a doctoral student at Florida A&M University, has earned a $5,000 research grant from Qolab through the John Martinis Grants for Experimental Superconducting Device Physics. Awarded in October 2026 at the Adaptive Quantum Circuits Conference, the grant recognizes Reynolds’ work on radio-frequency microwave pulse engineering for multi-scale qubit control.

Selected by 2025 Nobel Prize winner John Martinis as one of only two recipients this year, Reynolds says she is “humbled to be awarded the grant knowing that my proposal was chosen over other researchers in the field.” Her project aims to improve the precision and efficiency of qubit control, a key challenge in developing practical quantum computers.

Microwave Pulse Engineering for Enhanced Multi-Scale Qubit Control

Reynolds’ research focuses on the precise application of microwave pulses to manipulate qubits, the fundamental building blocks of quantum computers. This work aims to improve qubit control across multiple scales, addressing a key limitation in current quantum processor development. The $5,000 John Martinis Grant will provide access to Qolab’s cloud computing platform, a resource Reynolds states will be “very useful for our experimentation.” The core of Reynolds’ approach lies in optimizing how microwave signals interact with qubits.

“My research is about finding better ways to use microwave technology to manage the tiny parts that make quantum computers work,” she explained, highlighting the need for refined control mechanisms. Unlike classical computers that store information as bits representing 0 or 1, quantum computers use qubits existing in a superposition of both states simultaneously.

Reynolds clarified this distinction, stating, “Classical computation stores information in the form of bits as 0s and 1s while quantum computing stores information in the form of qubits as a superposition of both 0 and 1 simultaneously.” The potential impact of this work extends beyond incremental improvements in qubit control; Reynolds hopes her research will contribute to the development of truly fault-tolerant quantum computing. “I hope our work helps make quantum processing units more reliable and brings us closer to truly fault-tolerant quantum computing,” she said.

Reynolds also acknowledged the growing momentum within the quantum field, noting the influx of new talent and researchers. “As the field continues to grow, I am very excited about the new talent and researchers entering the field,” Reynolds observed, adding that the support of Professor Arigong and colleague Jonathan Casamayor has been instrumental to her progress. This collaborative environment, combined with the resources provided by the grant, positions Reynolds to contribute meaningfully to the advancement of quantum technologies.

My research is about finding better ways to use microwave technology to manage the tiny parts that make quantum computers work.

Mia Reynolds, Doctoral Student at Florida A&M University

John Martinis Grant Fuels Reynolds’ Quantum Computing Research

Reynolds’ work focuses on optimizing the precision of microwave signals used to manipulate qubits, a critical step toward building more stable and powerful quantum processors. She added, “It motivates me to want to produce good work and represent both my lab and the college well.” Reynolds works in the lab of Bayaner Arigong, an associate professor in the Department of Electrical and Computer Engineering at the college.

Reynolds said Arigong and other members of the lab, including Jonathan Casamayor, another doctoral student in the lab, have been a great help since she first arrived at the college. Reynolds’ project addresses the challenge of reliably managing qubits, which limits the development of quantum computers. “By improving the control and reliability of qubits, we hope to help make quantum computing a practical reality,” Reynolds said, emphasizing the potential for this technology to revolutionize fields like cybersecurity and drug discovery.

Classical computation stores information in the form of bits as 0s and 1s while quantum computing stores information in the form of qubits as a superposition of both 0 and 1 simultaneously.

Mia Reynolds, Doctoral Student at Florida A&M University
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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