Compressed Sensing for Multidimensional Spectroscopy Experiments
详细信息 查看全文
- 作者：Jacob N. Sanders ; Semion K. Saikin ; Sarah Mostame ; Xavier Andrade ; Julia R. Widom ; Andrew H. Marcus ; Al谩n Aspuru-Guzik
- 刊名：The Journal of Physical Chemistry Letters
- 出版年：2012
- 出版时间：September 20, 2012
- 年：2012
- 卷：3
- 期：18
- 页码：2697-2702
- 全文大小：322K
- 年卷期：v.3,no.18(September 20, 2012)
- ISSN：1948-7185
文摘
Compressed sensing is a processing method that significantly reduces the number of measurements needed to accurately resolve signals in many fields of science and engineering. We develop a two-dimensional variant of compressed sensing for multidimensional spectroscopy and apply it to experimental data. For the model system of atomic rubidium vapor, we find that compressed sensing provides an order-of-magnitude (about 10-fold) improvement in spectral resolution along each dimension, as compared to a conventional discrete Fourier transform, using the same data set. More attractive is that compressed sensing allows for random undersampling of the experimental data, down to less than 5% of the experimental data set, with essentially no loss in spectral resolution. We believe that by combining powerful resolution with ease of use, compressed sensing can be a powerful tool for the analysis and interpretation of ultrafast spectroscopy data.