Circuit Quantum Electrodynamics with Carbon-Nanotube-Based Superconducting Quantum Circuits
PHYSICAL REVIEW APPLIED 15:6 (2021) 64050
Abstract:Hybrid circuit QED involves the study of coherent quantum physics in solid-state systems via their interactions with superconducting microwave circuits. Here we present a crucial step in the implementation of a hybrid superconducting qubit that employs a carbon nanotube as a Josephson junction. We realize the junction by contacting a carbon nanotube with a superconducting Pd/Al bilayer, and implement voltage tunability of the quantum circuit's frequency using a local electrostatic gate. We demonstrate a strong dispersive coupling to a coplanar waveguide resonator by investigating the gate-tunable resonator frequency. We extract qubit parameters from spectroscopy using dispersive readout and find qubit relaxation and coherence times in the range of 10-200ns.
Critical slowing down in circuit quantum electrodynamics
Science Advances American Association for the Advancement of Science 7:21 (2021) eabe9492
Abstract:Critical slowing down of the time it takes a system to reach equilibrium is a key signature of bistability in dissipative first-order phase transitions. Understanding and characterizing this process can shed light on the underlying many-body dynamics that occur close to such a transition. Here, we explore the rich quantum activation dynamics and the appearance of critical slowing down in an engineered superconducting quantum circuit. Specifically, we investigate the intermediate bistable regime of the generalized Jaynes-Cummings Hamiltonian (GJC), realized by a circuit quantum electrodynamics (cQED) system consisting of a transmon qubit coupled to a microwave cavity. We find a previously unidentified regime of quantum activation in which the critical slowing down reaches saturation and, by comparing our experimental results with a range of models, we shed light on the fundamental role played by the qubit in this regime.
Efficient Hamiltonian programming in qubit arrays with nearest-neighbor couplings
Physical Review A American Physical Society 102:3 (2020) 32405
Abstract:We consider the problem of selectively controlling couplings in a practical quantum processor with always-on interactions that are diagonal in the computational basis, using sequences of local not gates. This methodology is well known in nuclear magnetic resonance implementations, but previous approaches do not scale efficiently for the general fully connected Hamiltonian, where the complexity of finding time-optimal solutions makes them only practical up to a few tens of qubits. Given the rapid growth in the number of qubits in cutting-edge quantum processors, it is of interest to investigate the applicability of this control scheme to much larger-scale systems with realistic restrictions on connectivity. Here we present an efficient scheme to find near time-optimal solutions that can be applied to engineered qubit arrays with local connectivity for any number of qubits, indicating the potential for practical quantum computing in such systems.
Modeling Enclosures for Large-Scale Superconducting Quantum Circuits
PHYSICAL REVIEW APPLIED 14:2 (2020) 24061
Abstract:© 2020 American Physical Society. Superconducting quantum circuits are typically housed in conducting enclosures in order to control their electromagnetic environment. As devices grow in physical size, the electromagnetic modes of the enclosure come down in frequency and can introduce unwanted long-range cross-talk between distant elements of the enclosed circuit. Incorporating arrays of inductive shunts such as through-substrate vias or machined pillars can suppress these effects by raising these mode frequencies. Here, we derive simple, accurate models for the modes of enclosures that incorporate such inductive-shunt arrays. We use these models to predict that cavity-mediated interqubit couplings and drive-line cross-talk are exponentially suppressed with distance for arbitrarily large quantum circuits housed in such enclosures, indicating the promise of this approach for quantum computing. We find good agreement with a finite-element simulation of an example device containing more than 400 qubits.
Cost-function embedding and dataset encoding for machine learning with parametrized quantum circuits
PHYSICAL REVIEW A 101:5 (2020) 52309