Noise Analysis and Mitigation for Scalable Quantum Computation

量子计算机有望在现有计算能力上实现前所未有的提升，从而提高从医学、生物学和寻找新材料到改进机器学习和更准确的金融预测等一系列应用的性能。在过去的十年里，我们已经进入了“量子技术时代”，这一理论前景正在成为现实。量子计算机在尺寸和“质量”方面都在迅速改进，我们现在已经超越了这些设备可以用经典机器模拟的极限。然而，在实际应用中使用量子计算机的主要障碍是它们对环境的不完美和不期望的影响非常敏感。有两种方法来解决这个问题。第一种方法是以一种自动“纠正”不需要的错误的方式构建计算。虽然这个想法看起来很吸引人，但它是有代价的。对于使用的每一个“真正的”量子信息单位，人们需要操作更多的物理单位。这种情况的直接后果是，对于有用的应用，我们需要的量子计算机要比我们希望在不久的将来拥有的大得多。第二种方法是我们在这里采用的方法，它被认为是短期内最有希望应用的方法。而不是纠正错误，可以尝试减轻它们并减少它们对计算的影响。这可以通过将大型计算分解为较小的部分（其中一些由经典计算机运行）来实现，在经典处理结果时消除一些不希望的影响，确保计算的量子部分以一种累积较小可能错误的方式完成。要做到这一点，深入了解所使用的量子硬件的内部工作原理至关重要。这种理解的一个主要障碍是使量子计算首先变得强大的相同现象，即它的“整体”性质，即总体大于各部分的总和。在这项可行性研究中，我们将以可扩展的方式对最有前途的量子硬件方法之一（超导量子比特）的缺陷进行抽象描述和建模。使用这种新的理解，我们将开发能够意识到其运行的硬件的详细缺陷的软件，并反过来提供减轻给定应用程序不希望出现的错误的最佳方法。

Quantum computers promise an unprecedented increase in the existing computational power, enabling improved performance to a range of applications from medicine, biology and search for new materials to improved machine learning and more accurate predictions in finance. During the last decade, we have entered the "quantum technology era", where this theoretical prospect is becoming a reality. Quantum computers improve rapidly both in terms of size and "quality", and we have now crossed the limit where these devices can be simulated by classical machines.However, the main obstacle in using quantum computers for practical applications is the fact that they are very sensitive to imperfections and undesired effects of their environment. There are two approaches to this issue. The first is to construct the computations in a way that unwanted errors are "corrected" automatically and in general. While this idea seems very appealing, it comes with a cost. For each "true" unit of quantum information used, one needs to manipulate many more physical units. The direct consequence of this is that for useful applications we would require quantum computers that are much bigger than those we can hope to have in the near-future.The second approach is the one we take here, and that is considered the most promising for near-term applications. Instead of correcting the errors, one can try to mitigate them and reduce the effect they have on the computation. This can be done by breaking a large computation to smaller parts (some run by classical computers), cancelling some undesired effects while classically processing the results, ensure that the quantum part of the computation is done in a way that accumulates the smaller possible errors. To do this it is crucial to understand in depth the inner workings of the quantum hardware that is used. A major obstacle in this understanding is the same phenomenon that makes quantum computing powerful in the first place, namely its "holistic" nature, i.e. the total is more than the sum of its parts.In this feasibility study we will characterise and model abstractly the imperfections of one of the most promising quantum hardware approaches (superconducting qubits) in a scalable way. Using this new understanding, we will develop software that is aware of the detailed imperfections of the hardware it runs, and in return provides the best way to mitigate the undesired errors for a given application.