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Data set: A solid-state high harmonic generation spectrometer with cryogenic cooling

Cite this dataset

Zuerch, Michael et al. (2024). Data set: A solid-state high harmonic generation spectrometer with cryogenic cooling [Dataset]. Dryad. https://doi.org/10.5061/dryad.5hqbzkhf0

Abstract

Solid-state high harmonic generation (sHHG) spectroscopy is a promising technique for studying electronic structure, symmetry, and dynamics in condensed matter systems. Here, we report on the implementation of an advanced sHHG spectrometer based on a vacuum chamber and closed-cycle helium cryostat. Using an in situ temperature probe, it is demonstrated that the sample interaction region retains cryogenic temperature during the application of high-intensity femtosecond laser pulses that generate high harmonics. The presented implementation opens the door for temperature-dependent sHHG measurements down to a few Kelvin, which makes sHHG spectroscopy a new tool for studying phases of matter that emerge at low temperatures, which is particularly interesting for highly correlated materials.

README: Data Set: A solid-state high harmonic generation spectrometer with cryogenic cooling

https://doi.org/10.5061/dryad.5hqbzkhf0

This data set contains all raw data and scripts for plotting the data shown in the paper that is open access here: https://doi.org/10.1063/5.0174407

Description of the data and file structure

The repository contains subfolders named after the figures in the published paper which contain measured data. Each subfolder contains a data file (if data is shown in the figure). The primary parameters that are varied in a given experiment are represented in the raw-file name. For example, in Fig. 5 a temperature scan was performed for different fluences. The raw file names are e.g. "105K-0.75uJ.txt" referring to the spectrum measured at 105 K temperature at 0.75 µJ pulse energy.  This naming convention is consistent throughout the repository. The raw data files themselves are encoded in ASCII and contain two columns where the first column is the wavelength in nanometers and the second column is the number of counts. Each line represents a pixel on the spectrometer. The raw data files are otherwise unprocessed spectra as measured by the spectrometer. 

Specific content:

Fig1\b\19K-0.85uJ.txt: ZnO spectrum containing the seventh and ninth harmonics as well as a broad photoluminescence (PL) peak and emerging lasing mode, taken at an intensity of 0.41 ± 0.02 TW/cm^2 and T = 19 K under 3.5 µm wavelength drive.

Fig4\data\xxK-yyuJ.txt: Where xx is a temperature in K and yy is a pulse energy in microjoules. Files contain normalized ZnO thin film spectra collected at different temperatures below the Mott transition under 3.5 µm driving wavelength.

Fig5\data\xxK-yyuJ.txt: Where xx is a temperature in K and yy is a pulse energy in microjoules. Files contain spectra that show temperature-dependent shift of the combined FX-D0X feature from ZnO photoluminescence emission under 3.5 µm driver wavelength.

Fig6\data\xxK-yyuJ.txt: Where xx is a temperature in K and yy is a pulse energy in microjoules. Normalized ZnO thin film spectra at different temperatures show the lasing mode and seventh harmonic signal above the Mott transition under 3.5 µm driver wavelength.

Fig7\data\17K\xxK-yyuJ.txt: Where xx is a temperature in K and yy is a pulse energy in microjoules. Spectra containing intensity-dependent scaling of the seventh and ninth harmonic yields as well as the PL/lasing intensity around the Mott transition for 17 K temperature.

Fig7\data\293K\xxK-yyuJ.txt: Where xx is a temperature in K and yy is a pulse energy in microjoules. Spectra containing intensity-dependent scaling of the seventh and ninth harmonic yields as well as the PL/lasing intensity around the Mott transition for 293 K temperature.

Each base folder contains a python script (see more below) to batch process the data files and create plots that relate to the published paper that is referenced above. 

All contents of this repository are CC0 compatible.

Code/Software:

Codes to analyze the provided raw data including plotting and saving files in the format as represented in the published paper are included in each subfolder. These scripts are written in python and contain comments within the code. All codes were tested on the most recent version of python available in June 2024. Each python script is stand-alone to process the raw data files within the same subfolder. The scripts output PNG or PDF files similar to the published figure panels. 

Funding

German Academic Exchange Service

National Science Foundation, Award: DGE 1752814

Arnold and Mabel Beckman Foundation

Adolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California Berkeley

Alexander von Humboldt Foundation

W. M. Keck Foundation

Office of the President, University of California, Award: M21PL3263

Lawrence Berkeley National Laboratory, Award: 107573

National Science Foundation, Award: DMR 2247363

Lawrence Berkeley National Laboratory, Award: 108232