Hamiltonian inverse engineering enables the design of protocols for specific quantum evolutions or target state preparation. Perfect state transfer (PST) and remote entanglement generationare notable examples, as they serve as key primitives in quantum information processing. However, Hamiltonians obtained through conventional methods often lack robustness against noise. Assisted by inverse engineering, we begin with a noise-resilient energy spectrum and construct a class of Hamiltonians, referred to as the dome model, that significantly improves the system’s robustness against noise, as confirmed by numerical simulations. This model introduces a tunable parameter m that modifies the energy-level spacing and gives rise to a well-structured Hamiltonian. It reduces to the conventional PST model at m=0 and simplifies to a SWAP model involving only two end qubits in the large-m regime. To address the challenge of scalability, we propose a cascaded strategy that divides long-distance PST into multiple consecutive PST steps. Our work is particularly suited for demonstration on superconducting qubits with tunable couplers, which enable rapid and flexible Hamiltonian engineering, thereby advancing the experimental potential of robust and scalable quantum information processing.
Spectator-induced leakage poses a fundamental challenge to scalable quantum computing, particularly as frequency collisions become unavoidable in multi-qubit processors. We introducea leakage mitigation strategy based on dynamically reshaping the system Hamiltonian. Our technique utilizes a tunable coupler to enforce a block-diagonal structure on the effective Hamiltonian governing near-resonant spectator interactions, confining the gate dynamics to a two-dimensional invariant subspace and thus preventing leakage by construction. On a multi-qubit superconducting processor, we experimentally demonstrate that this dynamic control scheme suppresses leakage rates to the order of 10−4 across a wide near-resonant detuning range. The method also scales effectively with the number of spectators. With three simultaneous spectators, the total leakage remains below the threshold relevant for surface code error correction. This approach eases the tension between dense frequency packing and high-fidelity gate operation, establishing dynamic Hamiltonian engineering as an essential tool for advancing fault-tolerant quantum computing.
The non-adiabatic geometric quantum computation (NGQC) has attracted a lot of attention for noise-resilient quantum control. However, previous implementations of NGQC require long evolutionpaths that make them more vulnerable to incoherent errors than their dynamical this http URL this work, we experimentally realize a universal short-path non-adiabatic geometric gate set (SPNGQC) with a 2-times shorter evolution path on a superconducting quantum processor. Characterizing with both quantum process tomography and randomized benchmarking methods, we report an average single-qubit gate fidelity of 99.86% and a two-qubit gate fidelity of 97.9%. Additionally, we demonstrate superior robustness of single-qubit SP-NGQC gate to Rabi frequency error in some certain parameter space by comparing their performance to those of the dynamical gates and the former NGQC gates.
Measurement for qubits plays a key role in quantum computation. Current methods for classifying states of single qubit in a superconducting multi-qubit system produce fidelities lowerthan expected due to the existence of crosstalk, especially in case of frequency crowding. Here, We make the digital signal processing (DSP) system used in measurement into a shallow neural network and train it to be an optimal classifier to reduce the impact of crosstalk. The experiment result shows the crosstalk-induced readout error deceased by 100% after a 3-second optimization applied on the 6-qubit superconducting quantum chip.