论文标题
用于蛋白质折叠的数字化 - 隔热量子算法
Digitized-Counterdiabatic Quantum Algorithm for Protein Folding
论文作者
论文摘要
我们提出了一种混合经典的量子数字化 - 苏绝热算法，以解决四面体晶格上的蛋白质折叠问题。数字化 - 苏绝热量子计算是一种通过数字化来压缩量子算法的范式，该量子通过数字化给定绝热量子计算的反糖化加速度。找到氨基酸序列的最低能量构型是NP-硬化的优化问题，在化学，生物学和药物设计中起着重要作用。使用问题启发和硬件有效的变分量子电路，我们胜过最先进的量子算法。我们将我们的方法应用于最多9个氨基酸的蛋白质，在量子硬件上最多使用17 QUAT。具体而言，我们使用Quantinuum的被困离子，Google和IBM的超导电路基准测试了量子算法，在NISQ时代获得了低深度电路的高成功概率。
We propose a hybrid classical-quantum digitized-counterdiabatic algorithm to tackle the protein folding problem on a tetrahedral lattice. Digitized-counterdiabatic quantum computing is a paradigm developed to compress quantum algorithms via the digitization of the counterdiabatic acceleration of a given adiabatic quantum computation. Finding the lowest energy configuration of the amino acid sequence is an NP-hard optimization problem that plays a prominent role in chemistry, biology, and drug design. We outperform state-of-the-art quantum algorithms using problem-inspired and hardware-efficient variational quantum circuits. We apply our method to proteins with up to 9 amino acids, using up to 17 qubits on quantum hardware. Specifically, we benchmark our quantum algorithm with Quantinuum's trapped ions, Google's and IBM's superconducting circuits, obtaining high success probabilities with low-depth circuits as required in the NISQ era.
