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 preconditioning for constrained optimization problems
We study the effect of quantum preconditioning on constrained combinatorial optimization problems, focusing on balanced graph bi-partitioning. The proposed approach uses two-point correlations between decision variables derived from the Quantum Approximate Optimization Algorithm (QAOA) to construct a modified objective function that is subsequently provided to mixed-integer programming (MIP) solvers. The results support a hybrid optimization framework in which quantum algorithms provide problem-specific information to guide classical exact MIP solvers.
Scaling Alternating-Bias-Assisted Annealing for precision transmon frequency targeting on superconducting quantum processors
Here, we characterize ABAA tuning performance within a 150-mm wafer process flow and extend this technique to simultaneous, multi-channel tuning, demonstrating that a wafer-scale JJ resistance tuning precision of σ=0.50±0.05% alongside a component-level yield of ≥98.8% can be achieved. These results confirm the efficacy and scalability of ABAA for high-precision Hamiltonian targeting, a critical enabler for modular superconducting quantum processor technology.
Localized thermometry via Dayem bridges integrated on superconducting qubit chips
Here we demonstrate a complementary on-chip thermometry method based on superconducting Dayem bridges that are integrated on the same chip as transmon qubits. By extracting the critical current of the Dayem bridge from I-V measurements, we obtain a local, quantitative measure of the chip temperature without the need for microwave calibration or qubit-specific control sequences.
Demonstrating real-time and low-latency quantum error correction with superconducting qubits
Quantum error correction will be essential for quantum computers to realize their full potential. As quantum computers advance towards demonstrating a universal fault-tolerant logical gate set, implementing scalable and low-latency real-time decoding will be crucial to avoid an exponential slowdown and maintain a fast logical clock rate. Here, we demonstrate low-latency feedback with a scalable FPGA decoder integrated into the control system of a superconducting quantum processor.
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.
