Description
Scaling silicon spin qubits requires hybrid quantum–classical integration to accommodate ultra fast qubit operations and limited coherence times.
We present Diraq’s roadmap using the NVIDIA DGX Quantum system, where Nvidia’s GraceHopper superchip and Quantum Machines’ OPX1000 enable real-time feedback for tasks with varying latency requirements; ranging from machine-learning-based autocalibration, to heralded initialization within relaxation times, and ultimately mid-circuit measurement faster than decoherence.
Complementing this, we introduce the DGXQ-alpha reinforcement learning software framework, highlighted through the example of GHZ state-fidelity optimization, and discuss its path toward broader usability in hybrid quantum–classical workflows.
Speaker
Dr. André Saraiva
Head of Theory
André Saraiva is Head of Theory at Diraq, leading the design and modelling of large-scale silicon-based quantum processors. A solidstate physicist specialising in spin qubits, quantum dots, and scalable semiconductor architectures, Saraiva is focused on advancing the theoretical foundations required to scale quantum systems to the millions, and ultimately billions, of qubits needed for practical commercial applications. Before joining Diraq in 2022, he held senior research roles at UNSW Sydney and Silicon Quantum Computing, and served as Professor of Physics at the Federal University of Rio de Janeiro. He has also held postdoctoral fellowships at the University of Wisconsin–Madison and UFRJ. Saraiva holds a PhD in Physics from UFRJ and has authored numerous scientific publications that have shaped the development of silicon-based quantum computing.
Dean Poulos
Customer Success Physicist for Australia
Overview of the current software framework for programming the DGXQ-alpha for reinforcement learning, referencing the example of GHZ state fidelity optimization. Explore future directions for enhancing the functionality and usability of the framework going forward.
Host
Lorenzo Leandro
Product Solutions Physicist
Dr. Lorenzo Leandro is a Product Solutions Physicist at Quantum Machines, where he leads product outreach and solutions for the photonics market. With a Ph.D. in Experimental Quantum Optics from the Technical University of Denmark and years of experience in scientific communication, he strives to connect scientific endeavor and results with the vision of quantum computing technologies, engaging and inspiring the current and next generations of scientists.
