Computational Chemistry Course - Optimization techniques introduction part 2
This is a video I made for the Computational Chemistry course. It is relative to the Optimization techniques module. It is a simple presentation captured with ScreenFlow and my voice over.
Since no one commented it yet, I will comment my own video. You may have noticed that I listed asymptotes among stationary points. This was the argument of the first question I asked my students about the video: Strictly theoretically speaking, is an asymptote a stationary point? The answer is no, BUT since this video is for a computational chemistry course one has to consider it inside such frame. Stationary points are defined as those structures with zero gradient. Any chemistry software has built in thresholds under which any value is defined as "zero". For example, the gradient of two hydrogen atoms at 5 Å distance is computed as zero, which means it is, in practice, a stationary point! I thought it was important for the students to get the idea of thresholds and the difference between theory and computational practice.
1 comment:
Since no one commented it yet, I will comment my own video. You may have noticed that I listed asymptotes among stationary points. This was the argument of the first question I asked my students about the video: Strictly theoretically speaking, is an asymptote a stationary point? The answer is no, BUT since this video is for a computational chemistry course one has to consider it inside such frame. Stationary points are defined as those structures with zero gradient. Any chemistry software has built in thresholds under which any value is defined as "zero". For example, the gradient of two hydrogen atoms at 5 Å distance is computed as zero, which means it is, in practice, a stationary point! I thought it was important for the students to get the idea of thresholds and the difference between theory and computational practice.
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