Seminar

Spins associated to defects in solids are promising qubits for quantum information processing. We have developed novel control gates for an electron spin coupled to nuclear spins, and applied this scheme to realise a universally connected 10-qubit register using an NV-centre in diamond [1].  Moreover, we employed dynamical decoupling of the register to realise coherence times up to 63(2) seconds. Building upon these techniques, we have also recently demonstrated the 3D imaging of a system of 27 coupled nuclear spins with atomic scale resolution [2].

We theoretically study the Hofstadter butterfly of a triangular network model in minimally twisted bilayer graphene. The band structure manifests periodicity in energy, mimicking that of Floquet systems. The butterfly diagrams provide fingerprints of the model parameters and reveal the hidden band topology. In a strong magnetic field, we establish that minimally twisted bilayer graphene realizes low-energy Floquet topological insulators (FTIs) carrying zero Chern number, while hosting chiral edge states in bulk gaps.

Based on the recent breakthrough of Huang (2019), we show that for any total Boolean function f, deg(f) = O(~deg(f)^2): The degree of f is at most quadratic in the approximate degree of f.

Machine learning (ML) provides the potential to solve challenging quantum many-body problems in physics and chemistry. Yet, this prospect has not been fully justified. In this work, we establish rigorous results to understand the power of classical ML and the potential for quantum advantage in an important example application: predicting outcomes of quantum mechanical processes.

We develop approximations to a perturbed quantum dynamics beyond the standard approximation based on quantum Zeno dynamics and adiabatic elimination. The effective generators describing the approximate evolutions are endowed with the same block structure as the unperturbed part of the generator, and their adiabatic error is “eternal” - it does not accumulate over time. We show how this gives rise to Schrieffer-Wolff generators in open systems.

This talk will introduce generalized Jordan–Wigner transformation on arbitrary triangulation of any simply connected manifold in 2d, 3d and general dimensions. This gives a duality between all fermionic systems and a new class of lattice gauge theories. This map preserves the locality and has an explicit dependence on the second Stiefel–Whitney class and a choice of spin structure on the manifold.

Applying a periodic Hamiltonian to a system of particles allows us to study out-of-equilibrium matter, like the prethermal discrete time crystal (PDTC). One can define a time-independent Hamiltonian that describes the dynamics of the driven system not continuously, but in a stroboscopic manner. This implies energy conservation during the validity window of this approximation.

In this work we explore the energy spectrum of a superconducting circuit consisting of a single fluxonium atom coupled to a long section of 1-D transmission line. Owing to the strong anharmonicity of the fluxonium we uncover a new many-body effect, dressing of photons by photons. Specifically, fluxonium's local non-linearity leads to hybridization between one-photon states and nearly resonant multi-photon states.  Accounting for this effect requires deriving the correct multi-mode light matter coupling model of our circuit.

Caroline Figgatt is an atomic physicist working to develop ion trap quantum computers at Honeywell Quantum Systems. She completed her PhD in physics at the University of Maryland in 2018, where she built a programmable ion trap quantum computer and demonstrated a variety of quantum algorithms on it. For her dissertation, she performed the first parallel 2-qubit operations in a single chain of trapped ion qubits. She will talk about quantum research at the company, highlight what it's like to work at Honeywell, and hold a Q&A.

Matrix syntax is a formal model of syntactic relations, based on a conservative and a radical assumption. The conservative assumption dates back to antiquity: that the fundamental divide in human language is between nouns and verbs, which are “conceptually at right angles” (as different as substantive words can be). The radical assumption is that such a conceptual orthogonality could be treated as a formal orthogonality in a vector space, with all its consequences.