Fall 2021

Ultracold dipolar molecules combine features of ultracold atoms and trapped ions. They promise new research avenues in quantum simulation, quantum computing, and quantum chemistry. But creating and taming ultracold systems of dipolar molecules is not a routine task. For example, Bose-Einstein condensates of dipolar molecules have not been created, yet.

Quantifying quantum states’ complexity is a key problem in various subfields of science, from quantum computing to black-hole physics. We prove a prominent conjecture by Brown and Susskind about how random quantum circuits’ complexity increases. Consider constructing a unitary from Haar-random two-qubit quantum gates. Implementing the unitary exactly requires a circuit of some minimal number of gates - the unitary’s exact circuit complexity.

Interactions between atoms and electromagnetic fields are at the core of nearly all quantum devices, with applications ranging from building quantum computers and networks, communicating quantum information over long distances, and developing quantum sensors of increasing precision. The miniaturization of these systems is critical to increasing their modularity as well as improving the efficacy of light-matter interactions by confining electromagnetic fields in small volumes.

This short talk provides a snapshot of opportunities in quantum science, technology, engineering, and mathematics (qSTEM) at the University of Maryland College Park (UMD). The UMD quantum ecosystem consists of seven quantum institutes, five quantum-adjacent institutes, and approximately 100 faculty, split 55/45 between theory and experiment. I organize the ecosystem into subfields: each subfield is described, and its corresponding faculty is listed.  
(pizza and drinks served after the talk)

The development of spin qubits with long coherence times for quantum information processing requires sources of spin noise to be identified and minimized. Although microwave-based spin control is typically used to extract the noise spectrum, this becomes infeasible when high frequency noise components are stronger than the available microwave power. Here, we introduce an all-optical approach for noise spectroscopy of spin qubits based on Raman spin rotation using Carr-Purcell-Meiboom-Gill (CPMG) pulse sequences.

The quantum circuit model is the de-facto way of designing quantum algorithms. Yet any level of abstraction away from the underlying hardware incurs overhead. In the era of near-term, noisy, intermediate-scale quantum (NISQ) hardware with severely restricted resources, this overhead may be unjustifiable. We develop quantum algorithms for Hamiltonian simulation "one level below" the circuit model, exploiting the underlying control over qubit interactions available in most quantum hardware implementations.

Recent years have seen the development of isolated quantum simulator platforms capable of exploring interesting questions at the frontiers of many-body physics. We describe our platform, based on a chain of Ytterbium ions in a linear trap, and describe its capabilities, which include long-range spin-spin interactions and single-site manipulation and readout. We then describe some recent studies undertaken with this machine, focusing on two.

In this talk, I will discuss chaotic billiard systems subject to a rapid periodic driving force, with driving frequency ω. Classically, the energy of such systems changes by small, effectively random increments associated with collisions with the billiard wall, leading to a random walk in energy space, or “energy diffusion.” I will present a Fokker-Planck description of this process. This model displays several notable features, including a 1/ω² scaling of the energy absorption rate, and (in certain special cases) an exact analytical solution.

We derive a family of optimal protocols, in the sense of saturating the quantum Cramér-Rao bound, for measuring a linear combination of d field amplitudes with quantum sensor networks, a key subprotocol of general quantum sensor networks applications. We demonstrate how to select different protocols from this family under various constraints via linear programming. Focusing on entanglement-based constraints, we prove the surprising result that highly entangled states are not necessary to achieve optimality for many problems.

The typical model for measurement noise in quantum error correction is to randomly flip the binary measurement outcome. In experiments, measurements yield much richer information - e.g., continuous current values, discrete photon counts - which is then mapped into binary outcomes by discarding some of this information. In this work, we consider methods to incorporate all of this richer information, typically called soft information, into the decoding of the surface code.