Oh Emily K, Krogmeier Timothy J, Schlimgen Anthony W, Head-Marsden Kade
Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 61630, United States.
ACS Phys Chem Au. 2024 May 17;4(4):393-399. doi: 10.1021/acsphyschemau.4c00018. eCollection 2024 Jul 24.
There has been a recent interest in quantum algorithms for the modeling and prediction of nonunitary quantum dynamics using current quantum computers. The field of quantum biology is one area where these algorithms could prove to be useful as biological systems are generally intractable to treat in their complete form but amenable to an open quantum systems approach. Here, we present the application of a recently developed singular value decomposition (SVD) algorithm to two systems in quantum biology: excitonic energy transport through the Fenna-Matthews-Olson complex and the radical pair mechanism for avian navigation. We demonstrate that the SVD algorithm is capable of capturing accurate short- and long-time dynamics for these systems through implementation on a quantum simulator and conclude that while the implementation of this algorithm is beyond the reach of current quantum computers, it has the potential to be an effective tool for the future study of systems relevant to quantum biology.
最近，人们对使用当前量子计算机对非酉量子动力学进行建模和预测的量子算法产生了兴趣。量子生物学领域是这些算法可能有用的一个领域，因为生物系统通常难以以完整形式进行处理，但适合采用开放量子系统方法。在这里，我们展示了一种最近开发的奇异值分解（SVD）算法在量子生物学的两个系统中的应用：通过费纳 - 马修斯 - 奥尔森复合体的激子能量传输和鸟类导航的自由基对机制。我们证明，通过在量子模拟器上实现，SVD算法能够捕捉这些系统准确的短期和长期动力学，并得出结论，虽然该算法的实现超出了当前量子计算机的能力范围，但它有可能成为未来研究与量子生物学相关系统的有效工具。
