Quantum critical dynamics in a 5000-qubit programmable spin glass

التفاصيل البيبلوغرافية
العنوان: Quantum critical dynamics in a 5000-qubit programmable spin glass
المؤلفون: King, Andrew D., Raymond, Jack, Lanting, Trevor, Harris, Richard, Zucca, Alex, Altomare, Fabio, Berkley, Andrew J., Boothby, Kelly, Ejtemaee, Sara, Enderud, Colin, Hoskinson, Emile, Huang, Shuiyuan, Ladizinsky, Eric, MacDonald, Allison J. R., Marsden, Gaelen, Molavi, Reza, Oh, Travis, Poulin-Lamarre, Gabriel, Reis, Mauricio, Rich, Chris, Sato, Yuki, Tsai, Nicholas, Volkmann, Mark, Whittaker, Jed D., Yao, Jason, Sandvik, Anders W., Amin, Mohammad H.
المصدر: Nature, 2023
سنة النشر: 2022
المجموعة: Condensed Matter
Quantum Physics
مصطلحات موضوعية: Quantum Physics, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics
الوصف: Experiments on disordered alloys suggest that spin glasses can be brought into low-energy states faster by annealing quantum fluctuations than by conventional thermal annealing. Due to the importance of spin glasses as a paradigmatic computational testbed, reproducing this phenomenon in a programmable system has remained a central challenge in quantum optimization. Here we achieve this goal by realizing quantum critical spin-glass dynamics on thousands of qubits with a superconducting quantum annealer. We first demonstrate quantitative agreement between quantum annealing and time-evolution of the Schr\"odinger equation in small spin glasses. We then measure dynamics in 3D spin glasses on thousands of qubits, where simulation of many-body quantum dynamics is intractable. We extract critical exponents that clearly distinguish quantum annealing from the slower stochastic dynamics of analogous Monte Carlo algorithms, providing both theoretical and experimental support for a scaling advantage in reducing energy as a function of annealing time.
نوع الوثيقة: Working Paper
DOI: 10.1038/s41586-023-05867-2
الوصول الحر: http://arxiv.org/abs/2207.13800Test
رقم الانضمام: edsarx.2207.13800
قاعدة البيانات: arXiv