arXiv 2104.063222021-04physics.atom-phphysics.optics

利用高次谐波实现单原子计算

Towards Single Atom Computing via High Harmonic Generation

Gerard McCaul, Kurt Jacobs, Denys I. Bondar

备注：: 5 pages, 6 figures

摘要：

替代计算平台的开发一直是物理学的长期目标，并且随着传统晶体管接近小型化的极限，这是一个特别紧迫的问题。一个潜在的替代范例是水库计算，它利用未知的，但高度非线性的输入数据的转换来执行计算。这样做的好处是，许多物理系统精确地表现出它们作为水库所必需的非线性输入-输出关系。因此，阻碍硅电子学进一步发展的量子效应成为水库计算机的优势。在这里，我们证明，即使是最基本的物质成分-原子-可以作为一个水库的光学计算机，由于高次谐波产生（HHG）的现象。提出了一种用于分类问题的单原子计算机原型，其中分类模型的参数被映射到光学元件。我们数值模拟表明，这种“全光”计算机可以成功地分类数据的准确性，是强烈依赖于动态非线性。这可能会为开发拍赫兹信息处理平台铺平道路。

英文摘要：

The development of alternative platforms for computing has been a longstanding goal for physics, and represents a particularly pressing concern as conventional transistors approach the limit of miniaturization. A potential alternatice paradigm is that of reservoir computing, which leverages unknown, but highly non-linear transformations of input-data to perform computations. This has the advantage that many physical systems exhibit precisely the type of non-linear input-output relationships necessary for them to function as reservoirs. Consequently, the quantum effects which obstruct the further development of silicon electronics become an advantage for a reservoir computer. Here we demonstrate that even the most basic constituents of matter - atoms - can act as a reservoir for optical computers, thanks to the phenomenon of High Harmonic Generation (HHG). A prototype single-atom computer for classification problems is proposed, where parameters of the classification model are mapped to optical elements. We numerically demonstrate that this `all-optical' computer can successfully classify data with an accuracy that is strongly dependent on dynamical non-linearities. This may pave the way for the development of petahertz information processing platforms.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

摘要：

英文摘要：

相关论文