古典的コンピューターが量子コンピューターに追いつき、追い越せることを研究者が示す(Researchers Show Classical Computers Can Keep Up with, and Surpass, Their Quantum Counterparts)

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2024-02-09 ニューヨーク大学 (NYU)

研究者が革新的な手法を採用し、従来のコンピューティングの速度と精度を向上させることに成功しました。量子コンピューティングは、従来のコンピューティングを速度とメモリ使用量の両面で上回る技術として称賛されており、物理現象の予測を可能にする可能性があります。この研究では、量子コンピューティングの長所を最大限に生かすアルゴリズムが開発され、最新の量子コンピュータよりも速く、より精密な計算が可能になりました。

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IBM の Eagle Kicked Ising 実験の効率的な テンソルネットワーク シミュレーション Efficient Tensor Network Simulation of IBM’s Eagle Kicked Ising Experiment

Joseph Tindall, Matthew Fishman, E. Miles Stoudenmire, and Dries Sels
PRX Quantum  Published 23 January 2024
DOI:https://doi.org/10.1103/PRXQuantum.5.010308

Figure 1

ABSTRACT

We report an accurate and efficient classical simulation of a kicked Ising quantum system on the heavy hexagon lattice. A simulation of this system was recently performed on a 127-qubit quantum processor using noise-mitigation techniques to enhance accuracy [Y. Kim et al., Nature, 618, 500–5 (2023)]. Here we show that, by adopting a tensor network approach that reflects the geometry of the lattice and is approximately contracted using belief propagation, we can perform a classical simulation that is significantly more accurate and precise than the results obtained from the quantum processor and many other classical methods. We quantify the treelike correlations of the wave function in order to explain the accuracy of our belief propagation-based approach. We also show how our method allows us to perform simulations of the system to long times in the thermodynamic limit, corresponding to a quantum computer with an infinite number of qubits. Our tensor network approach has broader applications for simulating the dynamics of quantum systems with treelike correlations.

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