### Time Parameters in IACTs: State of the Art  
Beyond the information derived from light intensity, the arrival time of Cherenkov photons on the camera represents another valuable data dimension. This temporal information depends on the geometry of the particle shower, the impact distance of the telescope, and the altitude of photon emission. The incorporation of time information enhances the overall performance of Cherenkov telescopes, improving sensitivity, resolution, and energy threshold capabilities. Here, we delve into various applications of time information in the analysis of Cherenkov telescope data.  
* Image Cleaning. **In the case of the MAGIC telescopes, the standard image cleaning procedure has been enhanced by incorporating temporal constraints alongside the traditional intensity-based selection. This refined approach exploits the expectation that pixels belonging to the shower image light up within a few tens of nanoseconds, thereby effectively suppressing contributions from night sky background fluctuations and other spurious signals [16]. The adoption of this method, particularly after the introduction of a 2 GS/s digitization system capable of recording the full waveform of pixel signals, resulted in a significant background reduction by a factor of two and an improvement in sensitivity by a factor of 1.4 for point-source observations [7; 17].
* Time Parameters. Quantities characterizing the temporal profile of the image, such as time gradient and time RMS, serve as additional inputs (independent of the purely morphological features) for discriminating hadron-generated signals and estimating energy and impact distance. Integration of these parameters into the analysis of the MAGIC telescope data led to a halving of the residual hadronic background while maintaining the same number of excess events compared to an analysis using only standard parameters [7].
* Deep Learning Techniques. The use of deep learning, an artificial intelligence technique employing convolutional neural networks, presents a promising avenue for classifying Cherenkov telescope images based on both charge and time information. This approach involves creating two-dimensional maps of pixels containing various waveform parameters, which, alongside the intensity map, significantly improves event classification. Tested on simulated data for the future Cherenkov Telescope Array (CTA), this method exhibited promising results for discriminating proton and electron backgrounds [18].  
Apart from MAGIC, other notable Cherenkov telescopes, such as VERITAS (Very Energetic Radiation Imaging Telescope Array System) [19] and HESS [20], have also demonstrated the efficacy of incorporating time information into their data analyses. These telescopes, like MAGIC, have explored the implementation of advanced algorithms for image cleaning and the extraction of time parameters, contributing to the refinement of background discrimination and sensitivity.  
The integration of time information into Cherenkov telescopes' data reconstruction proves to be a versatile and advantageous technique. Its implementation across various telescopes showcases its adaptability and potential for enhancing the precision and reliability of astrophysical observations. This technique, particularly beneficial for single telescopes lacking stereoscopic vision of particle showers, underscores the significance of time as an additional parameter for reconstructing events.  
In this paper, we focus on the definition, evaluation, and application of time-derived parameters for Gamma/Hadron separation in the context of the ASTRI Mini-Array.