Calibration is an important step in the construction of traditional spectrometers to ensure the accuracy of the obtained spectrum. Recent advancements in computational spectroscopy have also spurred the need for calibration with the aid of machine learning to enable the recovery of spectrums, but they generally require large datasets. In this paper, we present an arbitrary spectrum generation engine (ASGE) using a digital micromirror device (DMD) that can be configured to work in a broad wavelength range from visible to the near-infrared. The DMD allows for the independent modulation of spectral elements to output arbitrary spectrums and provide the large datasets required for training and calibration of computational spectrometers. The ASGE can also double as a normal spectrometer if a sampling accessory and a detector are included.
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