论文标题
适应性何时有助于量子状态学习?
When Does Adaptivity Help for Quantum State Learning?
论文作者
论文摘要
我们考虑了状态层析成像的经典问题:给定未知量子状态$ρ\ in \ mathbb {c}^{d \ times d} $的副本,输出$ \widehatρ$,在某种意义上接近$ρ$,例如。痕量距离或保真度。当一个允许在所有副本上纠缠的连贯测量值时,$θ(d^2/ε^2)$副本是必要的,足以获得跟踪距离$ε$。不幸的是,达到此速率的协议会产生大量量子内存开销,这些量子内存阻止了近期设备上的实现。另一方面,使用不连贯的(单拷贝)测量的最著名协议使用$ O(d^3/ε^2)$副本,并且多个论文已将其作为一个开放的问题,以了解此速率是否紧张。在这项工作中,我们通过证明任何使用不一致测量的协议(即使适应性地选择)需要$ω(d^3/ε^2)$副本,与最著名的上限匹配。 我们通过一种新的证明技术来做到这一点,该技术直接限制了测量后后部分布的``倾斜'',这产生了我们下限的简短简短证明,我们认为这可能是独立的。 尽管这意味着适应性对于层距离无济于事,但我们表明,它实际上确实有助于层析成像对不忠行为。我们给出了一种自适应算法,该算法仅使用$ \ tilde {o}(d^3/γ)$ copies oble obly copies of $γ$ close的不忠$γ$ copose的状态。相反,众所周知,任何非自适应算法都需要$ω(d^3/γ^2)$副本。虽然民间传说在$ 2 $的尺寸中,据我们所知,人们可以实现$ O(1/γ)$的缩放,但我们的算法是第一个在所有维度上达到最佳速率的算法。
We consider the classic question of state tomography: given copies of an unknown quantum state $ρ\in\mathbb{C}^{d\times d}$, output $\widehatρ$ which is close to $ρ$ in some sense, e.g. trace distance or fidelity. When one is allowed to make coherent measurements entangled across all copies, $Θ(d^2/ε^2)$ copies are necessary and sufficient to get trace distance $ε$. Unfortunately, the protocols achieving this rate incur large quantum memory overheads that preclude implementation on near-term devices. On the other hand, the best known protocol using incoherent (single-copy) measurements uses $O(d^3/ε^2)$ copies, and multiple papers have posed it as an open question to understand whether or not this rate is tight. In this work, we fully resolve this question, by showing that any protocol using incoherent measurements, even if they are chosen adaptively, requires $Ω(d^3/ε^2)$ copies, matching the best known upper bound. We do so by a new proof technique which directly bounds the ``tilt'' of the posterior distribution after measurements, which yields a surprisingly short proof of our lower bound, and which we believe may be of independent interest. While this implies that adaptivity does not help for tomography with respect to trace distance, we show that it actually does help for tomography with respect to infidelity. We give an adaptive algorithm that outputs a state which is $γ$-close in infidelity to $ρ$ using only $\tilde{O}(d^3/γ)$ copies, which is optimal for incoherent measurements. In contrast, it is known that any nonadaptive algorithm requires $Ω(d^3/γ^2)$ copies. While it is folklore that in $2$ dimensions, one can achieve a scaling of $O(1/γ)$, to the best of our knowledge, our algorithm is the first to achieve the optimal rate in all dimensions.