Despite the significant progress in superconducting quantum computation over the past years, quantum state measurement still lags nearly an order of magnitude behind quantum gate operationsin speed and fidelity. The main challenge is that the strong coupling and readout signal used to probe the quantum state may also introduce additional channels which may cause qubit state transitions. Here, we design a novel architecture to implement the long-sought longitudinal interaction scheme between qubits and resonators. This architecture not only provides genuine longitudinal interaction by eliminating residual transversal couplings, but also introduces proper nonlinearity to the resonator that can further minimize decay error and measurement-induced excitation error. Our experimental results demonstrate a measurement fidelity of 99.8% in 202 ns without the need for any first-stage amplification. After subtracting the residual preparation errors, the pure measurement fidelity is above 99.9%. Our scheme is compatible with the multiplexing readout scheme and can be used for quantum error correction.
Simulations of high-complexity quantum systems, which are intractable for classical computers, can be efficiently done with quantum computers. Similarly, the increasingly complex quantumelectronic circuits themselves will also need efficient simulations on quantum computers, which in turn will be important in quantum-aided design for next-generation quantum processors. Here, we implement variational quantum eigensolvers to simulate a Josephson-junction-array quantum circuit, which leads to the discovery of a new type of high-performance qubit, plasonium. We fabricate this new qubit and demonstrate that it exhibits not only long coherence time and high gate fidelity, but also a shrinking physical size and larger anharmonicity than the transmon, which can offer a number of advantages for scaling up multi-qubit devices. Our work opens the way to designing advanced quantum processors using existing quantum computing resources.
Adiabatic quantum computing enables the preparation of many-body ground states. This is key for applications in chemistry, materials science, and beyond. Realisation poses major experimentalchallenges: Direct analog implementation requires complex Hamiltonian engineering, while the digitised version needs deep quantum gate circuits. To bypass these obstacles, we suggest an adiabatic variational hybrid algorithm, which employs short quantum circuits and provides a systematic quantum adiabatic optimisation of the circuit parameters. The quantum adiabatic theorem promises not only the ground state but also that the excited eigenstates can be found. We report the first experimental demonstration that many-body eigenstates can be efficiently prepared by an adiabatic variational algorithm assisted with a multi-qubit superconducting coprocessor. We track the real-time evolution of the ground and exited states of transverse-field Ising spins with a fidelity up that can reach about 99%.
We report the preparation and verification of a genuine 12-qubit entanglement in a superconducting processor. The processor that we designed and fabricated has qubits lying on a 1Dchain with relaxation times ranging from 29.6 to 54.6 μs. The fidelity of the 12-qubit entanglement was measured to be above 0.5544±0.0025, exceeding the genuine multipartite entanglement threshold by 21 standard deviations. Our entangling circuit to generate linear cluster states is depth-invariant in the number of qubits and uses single- and double-qubit gates instead of collective interactions. Our results are a substantial step towards large-scale random circuit sampling and scalable measurement-based quantum computing.
Superconducting quantum circuits are promising candidate for building scalable quantum computers. Here, we use a four-qubit superconducting quantum processor to solve a two-dimensionalsystem of linear equations based on a quantum algorithm proposed by Harrow, Hassidim, and Lloyd [Phys. Rev. Lett. \textbf{103}, 150502 (2009)], which promises an exponential speedup over classical algorithms under certain circumstances. We benchmark the solver with quantum inputs and outputs, and characterize it by non-trace-preserving quantum process tomography, which yields a process fidelity of 0.837±0.006. Our results highlight the potential of superconducting quantum circuits for applications in solving large-scale linear systems, a ubiquitous task in science and engineering.