Research

What quantum many-body systems feature scalable computational advantages for quantum experiments over classical simulation? Well-established quantum advantages are restricted to highly-structured computer-scientific problems, while recent numerical methods suggest that "typical" quantum many-body dynamics may be classically easier. We proved that uncorrected noise imposes fundamental limits on the magnitude of quantum advantage that experiments can achieve. More recently, I built on these connections to design experimental protocols in which purposefully-inserted perturbations enable a rich dissection of any observable by its complexity with respect to a broad set of classical algorithms. In collaboration with Google Quantum AI on their quantum echoes experiments, we showed how known classical approaches appear to fundamentally break down for certain time-reversed quantum many-body experiments.

Controllable quantum experiments can learn immensely more properties of quantum systems than conventional approaches. Random unitaries are a potent tool for understanding the power and limitations of these abilities. They also serve as models of complex processes in quantum many-body physics and quantum gravity more broadly. We proved that local quantum circuits can become indistinguishable from random unitaries in exponentially shorter times than previously thought, with widespread applications across physics and quantum science. I am currently interested in the intersection of pseudorandom behaviors with physical structure. This has led us to startling subtleties on detecting phases of matter, stronger random unitary constructions for experiments of interest in quantum cryptography and gravity, and several advances and limitations on pseudorandomness in systems with physical constraints.

Quantum experiments are afflicted by error from numerous sources, from environmental decoherence to discretized approximations in simulation algorithms. My work applies fundamental connections with quantum information dynamics to understand and handle uncorrected errors in quantum simulation. I showed that noisy many-body dynamics display universal classes of fidelity decay controlled by their information dynamics. I also applied these ideas to help design novel error mitigation strategies for two recent experiments with Google Quantum AI. Looking forward, I hope to extend these insights to broader physics-informed frameworks for error mitigation, correction, and quantum simulation.

The AdS/CFT correspondence posits that certain quantum Hamiltonians are precisely dual to higher-dimensional theories of quantum gravity. This raises a tantalizing possibility: That quantum simulation experiments may one day realize such Hamiltonians, and assist in our understanding of models of quantum gravity. Despite this promise, several concrete challenges remain. In an earlier work, we showed how a novel "many-body" form of quantum teleportation can be used as an experimental litmus test for detecting gravitational dynamics. We demonstrated a toy example of this teleportation in two experiments, and helped to clarify a third realization. In more recent work, we tackled another challenge, by providing a simple and efficient experimental protocol to cool these Hamiltonians to low temperatures, where the gravitational duality applies.

Estimating the Hamiltonians of quantum systems is a central goal of metrology and device characterization. We introduced a versatile new protocol for quantum-enhanced sensing of an external field, using solely generic quantum many-body dynamics. This opens the door to quantum-enhanced metrology in new platforms, such as solid-state spin defects. In separate work, we showed that learning many-body Hamiltonians at the Heisenberg limit is not possible without a high amount of experimental "control". I also showed that out-of-time-order correlators can exponentially enhance Hamiltonian learning algorithms, which helped motivate a proof-of-concept experiment at Google Quantum AI that used quantum computation to infer molecular geometries from NMR data more accurately than standard methods.

In the past, I also worked on novel topological phenomena in atomic, molecular, and optical quantum systems. These systems provide an entirely new physical context for the realization of topological phases, particularly in out-of-equilibrium settings. We predicted and experimentally observed an analogue of non-Abelian statistics in photonic systems; predicted a new, driven phase of topological matter; and provided a toolkit for realizing topological insulators in polar molecule quantum simulators. In separate work, we introduced a theoretical framework to characterize bulk-boundary correspondences in topological stabilizer codes; this extended known results on 2D stabilizer codes to fracton codes in higher-dimensions.