Quantum computing and simulation with multimode superconducting random-access memories
Abstract: Superconducting quantum processors have advanced rapidly in recent decades, yet remain constrained by limited coherence, restricted connectivity, and the large overheads required for control and quantum error correction. I will describe an alternative architecture that attempts to address these challenges by harnessing multiple harmonic modes of an ultra-coherent multimode cavity, all controlled by a single nonlinear superconducting circuit. This architecture separates processing (in the nonlinear circuit) from memory (in long-lived cavity modes), yielding high connectivity and hardware efficiency while exploiting the long coherence times and bosonic nature of the microwave cavity modes. I will present recent progress on fast, universal cavity control via sideband interactions; encoders that map qubit states into bosonic error-correcting codes; mitigation of ancilla-induced errors using cascaded random-access memory architectures; and the control of cavities with tens of millisecond coherence times. I will also discuss applications of such multimode random-access memories to quantum simulation, including prospects for realizing measurement-induced phase transitions in multimode bosonic systems.
Bio: Srivatsan Chakram is an Assistant Professor of Physics & Astronomy at Rutgers University. His group develops hardware-efficient superconducting quantum processors centered on low-loss multimode superconducting cavities, leveraging them for advanced quantum control, bosonic quantum error correction, and quantum simulation. He is also a Principal Investigator in the Device Thrust of the SQMS Center at Fermilab. He received his Integrated M.Sc. from the Indian Institute of Technology Kanpur (IIT Kanpur), completed his Ph.D. at Cornell University on cavity optomechanics and ultracold atomic physics, and conducted postdoctoral research in superconducting quantum information in Prof. David Schuster’s lab at the University of Chicago.
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