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科学家研制出原子玻色子采样器
作者:小柯机器人 发布时间:2024/5/11 22:10:22

近日,美国科罗拉多大学的Adam M. Kaufman&Aaron W. Young及其研究团队取得一项新进展。经过不懈努力,他们研制出原子玻色子采样器。相关研究成果已于2024年5月8日在国际权威学术期刊《自然》上发表。

据悉,玻色子采样器为量子计算提供了一种受限模型,它基于可编程、非相互作用的动力学传播中相同玻色子干涉所产生的分布采样能力。尽管目前普遍认为,有效且精确的经典玻色子采样模拟并不存在,这激发了光子学领域在玻色子采样实验上取得了一系列突破。然而,由于难以产生和稳定地操控特定数量的低损耗光子,传统方法通常采用概率技术来进行后选择或标记,从而改变标准玻色子采样的过程。

该研究团队通过在二维隧道耦合光学晶格中,使用超冷原子实现玻色子采样来解决上述挑战。研究人员运用了前所未有的技术组合,融合了高精度的光学冷却技术、晶格中原子的成像技术,以及通过光镊实现的对原子的可编程控制。当将其扩展至相互作用系统时,这项研究展示了在各种哈伯德模型模拟中直接构建基态和激发态的核心能力。

附:英文原文

Title: An atomic boson sampler

Author: Young, Aaron W., Geller, Shawn, Eckner, William J., Schine, Nathan, Glancy, Scott, Knill, Emanuel, Kaufman, Adam M.

Issue&Volume: 2024-05-08

Abstract: A boson sampler implements a restricted model of quantum computing. It is defined by the ability to sample from the distribution resulting from the interference of identical bosons propagating according to programmable, non-interacting dynamics. An efficient exact classical simulation of boson sampling is not believed to exist, which has motivated ground-breaking boson sampling experiments in photonics with increasingly many photons. However, it is difficult to generate and reliably evolve specific numbers of photons with low loss, and thus probabilistic techniques for postselection or marked changes to standard boson sampling are generally used. Here, we address the above challenges by implementing boson sampling using ultracold atoms in a two-dimensional, tunnel-coupled optical lattice. This demonstration is enabled by a previously unrealized combination of tools involving high-fidelity optical cooling and imaging of atoms in a lattice, as well as programmable control of those atoms using optical tweezers. When extended to interacting systems, our work demonstrates the core abilities required to directly assemble ground and excited states in simulations of various Hubbard models.

DOI: 10.1038/s41586-024-07304-4

Source: https://www.nature.com/articles/s41586-024-07304-4

期刊信息

Nature:《自然》,创刊于1869年。隶属于施普林格·自然出版集团,最新IF:69.504
官方网址:http://www.nature.com/
投稿链接:http://www.nature.com/authors/submit_manuscript.html