论文标题
近期量子设备的自适应POVM实施和测量误差缓解策略
Adaptive POVM implementations and measurement error mitigation strategies for near-term quantum devices
论文作者
论文摘要
我们提出了针对近期小型和嘈杂设备的变异量子算法量身定制的自适应测量技术。特别是，我们以两种方式概括了早期的“学习来衡量”策略。首先，通过考虑一类自适应阳性算子的有价值措施（POVM），可以通过简单的投影测量值模拟而无需辅助矩形，我们减少了所需的Qubits和两个Qubit Gates的量。其次，通过引入基于量子检测器断层扫描的方法来减轻噪声的效果，我们可以优化POVM，并在当前可用的嘈杂量子设备中可靠地推断预期值。我们的数值模拟清楚地表明，所提出的策略可以显着减少所需的镜头数量，以达到变异量子本质体的化学精度，从而有助于解决近期量子计算的瓶颈之一。
We present adaptive measurement techniques tailored for variational quantum algorithms on near-term small and noisy devices. In particular, we generalise earlier "learning to measure" strategies in two ways. First, by considering a class of adaptive positive operator valued measures (POVMs) that can be simulated with simple projective measurements without ancillary qubits, we decrease the amount of required qubits and two-qubit gates. Second, by introducing a method based on Quantum Detector Tomography to mitigate the effect of noise, we are able to optimise the POVMs as well as to infer expectation values reliably in the currently available noisy quantum devices. Our numerical simulations clearly indicate that the presented strategies can significantly reduce the number of needed shots to achieve chemical accuracy in variational quantum eigensolvers, thus helping to solve one of the bottlenecks of near-term quantum computing.
