Cellular automata are interacting classical bits that d isplay diverse emergent behaviors\, from fractals to random-number gen erators to Turing-complete computation. We discover that quantum cellu lar automata (QCA) can exhibit complexity in the sense of the complexi ty science that describes biology\, sociology\, and economics. QCA exh ibit complexity when evolving under 'Goldilocks rules' that we define by balancing activity and stasis. Our Goldilocks rules generate robust dynamical features (entangled breathers)\, network structure and dyna mics consistent with complexity\, and persistent entropy fluctuations. Present-day experimental platformsâ€”Rydberg arrays\, trapped ions\, and superconducting qubitsâ€”can implement our Goldilocks protocols\, making testable the link between complexity science and quantum comput ation exposed by our QCA. \nThe inability of classical computers to si mulate large quantum systems is a hindrance to understanding the physi cs of QCA\, but quantum computers offer an ideal simulation platform. I will discuss our recent experimental realization of QCA on a digital quantum processor\, simulating a one-dimensional Goldilocks QCA rule on chains of up to 23 superconducting qubits. Employing low-overhead c alibration and error mitigation techniques\, we calculate population d ynamics and complex network measures indicating the formation of small -world mutual information networks. Unlike random states\, these netwo rks decohere at fixed circuit depth independent of system size\, the l argest of which corresponds to 1\,056 two-qubit gates. This quantum c ircuit depth result presents a strong contrast to the quantum volume c oncept used to characterize many current quantum computers in industry . Such computations may open the door to the employment of QCA in appl ications like the simulation of strongly-correlated matter or beyond-c lassical computational demonstrations.

\n \nThis event starts a t 3:30pm with refreshments\, followed at 3:45pm by a short presentatio n by Linipun Phuttitarn (PhD student Saffman group) titled "Enhanced M easurement of Neutral Atom Qubits with Machine Learning". The invited presentation starts at 4pm.

\n URL:https://www.physics.wisc.edu/events/?id=8098 END:VEVENT END:VCALENDAR