MACON-QC: Many-Body Phases In Continuous-Time Quantum Computation

量子计算（QC）的连续时间方法在系统堆栈的所有级别上，特别是在软件级别上，都与基于门的QC有着根本的不同。在一般情况下，连续时间的方法可以更强大的消相干，虽然目前的错误校正的艺术落后于基于门的QC。然而，多量子位连续时间工程量子系统和自然界中的凝聚态系统之间的明显相似性允许软件设计者开发算法，这些算法的灵感来自并借鉴了上世纪积累的凝聚态物理学中量子相变的大量知识。在MACON-QC中，我们将开发直接受到凝聚态多体相变启发的连续时间算法。这些算法将利用目前无法在硬件中实现的哈密顿算子，即使是在两个量子比特的水平上。这项研究的最终目标是确定需要哪些新的硬件元件，以使未来的凝聚态连续时间量子计算机能够在现实世界的应用中展示量子加速。与此同时，将开发在连续进化过程中验证真正量子行为的方法，以便可以证明该算法经过真正的量子状态。还将探索通过机器学习优化新添加的元素和算法。

Continuous-time approaches to quantum computation (QC) are fundamentally different from gate-based QC at all levels of the system stack, particularly at the software level. In general continuous-time approaches can be more robust with respect to decoherence, though at present the state of art of error-correction lags behind that of gate-based QC. Nevertheless the clear analogies between many-qubit continuous-time engineered quantum systems and condensed-matter systems in nature allow software designers to develop algorithms which are inspired by and draw on the vast knowledge of quantum phase-transitions in condensed-matter physics accumulated over the last century.In MACON-QC we will develop continuous-time algorithms which are directly inspired by many-body phase transitions in condensed matter. These algorithms will utilise Hamiltonians which cannot currently be implemented in hardware, even at the two-qubit level. The ultimate goal of the research is to establish which qualitatively new hardware elements are required so as to enable future condensed-matter-inspired continuous-time quantum computers to demonstrate quantum speedup in real-world applications. In tandem with this task, approaches to certifying truly quantum behaviour during the continuous evolution will be developed so that it can be demonstrated that the algorithm goes through truly quantum states. Optimization of the newly-added elements and the algorithms via machine learning will also be explored.