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Programming Quantum Oscillators: Computation and Simulation with Random-Access Memory

Date and Time: Wednesday, September 09, 2026, 03:30pm -
Location: 330W/Zoom
 

Speaker: Srivatsan Chakram

Abstract:  Over the past five decades, rapid progress in controlling individual quantum systems has transformed foundational gedanken experiments in quantum mechanics into laboratory reality. This second quantum revolution has enabled fundamental tests of quantum mechanics while opening new paradigms for computation, communication, and sensing. I will trace two strands of this history: the development of cavity quantum electrodynamics, recognized by the 2012 Nobel Prize, and the observation of macroscopic quantum tunneling and energy quantization in electrical circuits, recognized by the 2025 Nobel Prize. Their convergence in circuit quantum electrodynamics informs my group’s effort to build quantum processors with random-access memory, an essential component of classical computers that is notably absent from most quantum processors. I will describe several generations of these processors, built by coupling superconducting circuits to long-lived microwave cavities, including our recently demonstrated cascaded architecture for random-access quantum memory. Separating processing from memory can improve connectivity and reduce control complexity. The harmonic-oscillator modes of the cavities offer long coherence times, large local Hilbert spaces, and comparatively simple error models, providing a hardware-efficient route to quantum error correction. Using microwave drives to induce the coherent exchange of photons between an auxiliary qubit and a selected cavity mode, we have also demonstrated arbitrary unitary control on any finite-dimensional subspace of the oscillator. This resolves a long-standing challenge for exchange-based oscillator control dating to the early days of the second quantum revolution. I will conclude by describing ongoing experiments that harness these devices for quantum simulation, sensing, and machine learning.

Host: Jed Pixley