Unlocking a fast adiabatic CZ gate and exact residual ZZ cancellation between fixed-frequency transmons using a floating tunable coupler
In this work, we demonstrate that a symmetric floating tunable coupler provides a natural platform for fast, high-fidelity adiabatic controlled-Z (CZ) gates. Its favorable energy-level structure eliminates the conventional trade-off between rapid conditional-phase accumulation and adiabatic evolution while preserving exact cancellation of residual ZZ interaction at idling.
Unlocking a fast adiabatic CZ gate and exact residual ZZ cancellation between fixed-frequency transmons using a floating tunable coupler
In this work, we demonstrate that a symmetric floating tunable coupler provides a natural platform for fast, high-fidelity adiabatic controlled-Z (CZ) gates. Its favorable energy-level structure eliminates the conventional trade-off between rapid conditional-phase accumulation and adiabatic evolution while preserving exact cancellation of residual ZZ interaction at idling.
Quantum optimization solvers typically rely on one-variable-to-one-qubit mapping. However, the low qubit count on current quantum computers is a major obstacle in competing against classical methods. Here, we develop a qubit-efficient algorithm that overcomes this limitation by mapping a candidate bit string solution to an entangled wave function of fewer qubits. We propose a variational quantum circuit generalizing the quantum approximate optimization ansatz (QAOA).
We introduce a self-consistent mean-field quantum optimization algorithm that approximates the ground state of classical Ising Hamiltonians. The algorithm decomposes the problem into independent subproblems and treats the interactions between them in a mean-field manner.
Simulating plasma wave propagation on a superconducting quantum chip
Quantum computers may one day enable the efficient simulation of strongly-coupled plasmas that lie beyond the reach of classical computation in regimes where quantum effects are important and the scale separation is large. In this letter, we take the first step towards efficient simulation of quantum plasmas by demonstrating linear plasma wave propagation on a superconducting quantum chip.
State-of-the-art classical optimization solvers set a high bar for quantum computers to deliver utility in this domain. Here, we introduce a quantum preconditioning approach based on the quantum approximate optimization algorithm. It transforms the input problem into a more suitable form for a solver with the level of preconditioning determined by the depth of the quantum circuit. We demonstrate that best-in-class classical heuristics such as simulated annealing and the Burer-Monteiro algorithm can converge more rapidly when given quantum preconditioned input for various problems, including Sherrington-Kirkpatrick spin glasses, random 3-regular graph maximum-cut problems, and a real-world grid energy problem.
Data anonymisation with the Density Matrix Classifier
We propose a new data anonymisation method based on the concept of a quantum feature map. The main advantage of the proposed solution is that a high degree of security is combined with the ability to perform classification tasks directly on the anonymised (encrypted) data resulting in the same or even higher accuracy compared to that obtained when working with the original plain text data.
Coherent control of a superconducting qubit using light
Here, we demonstrate coherent optical control of a superconducting qubit. We achieve this by developing a microwave–optical quantum transducer that operates with up to 1.18% conversion efficiency with low added microwave noise, and we demonstrate optically driven Rabi oscillations in a superconducting qubit.
High-fidelity optical readout of a superconducting qubit using a scalable piezo-optomechanical transducer
Superconducting quantum processors have made significant progress in size and computing potential. As a result, the practical cryogenic limitations of operating large numbers of superconducting qubits are becoming a bottleneck for further scaling. Due to the low thermal conductivity and the dense optical multiplexing capacity of telecommunications fiber, converting qubit signal processing to the optical domain using microwave-to-optics transduction would significantly relax the strain on cryogenic space and thermal budgets. Here, we demonstrate high-fidelity multi-shot optical readout through an optical fiber of a superconducting transmon qubit connected via a coaxial cable to a fully integrated piezo-optomechanical transducer.
Benchmarking quantum optimization for the maximum-cut problem on a superconducting quantum computer
Achieving high-quality solutions faster than classical solvers on computationally hard problems is a challenge for quantum optimization to deliver utility. Using a superconducting quantum computer, we experimentally investigate the performance of a hybrid quantum-classical algorithm inspired by semidefinite programming approaches for solving the maximum-cut problem on 3-regular graphs up to several thousand variables. We leverage the structure of the input problems to address sizes beyond what current quantum machines can naively handle. We attain an average approximation ratio of 99% over a random ensemble of thousands of problem instances.
An ultra-thin aluminum oxide layer is a key component for Josephson junctions in superconducting quantum bits. This layer serves as a barrier layer for Cooper pairs tunneling between the superconducting electrodes and significantly influences the overall performance of the junction. In this study, we investigate the impact of aluminum deposition rates on the microstructure and chemical variation of the aluminum oxide layer, as well as the device's yields and qubits’ lifetimes.
Classical symmetric encryption algorithms use N bits of a shared secret key to transmit N bits of a message over a one-way channel in an information theoretically secure manner. This paper proposes a hybrid quantum-classical symmetric cryptosystem that uses a quantum computer to generate the secret key.
Enhanced superconducting qubit performance through ammonium fluoride etch
The performance of superconducting qubits is often limited by dissipation and two-level systems (TLS) losses. The dominant sources of these losses are believed to originate from amorphous materials and defects at interfaces and surfaces, likely as a result of fabrication processes or ambient exposure. Here, we explore a novel wet chemical surface treatment at the Josephson junction-substrate and the substrate-air interfaces by replacing a buffered oxide etch (BOE) cleaning process with one that uses hydrofluoric acid followed by aqueous ammonium fluoride.
