• Qualia. What is this subjective experience that I know as consciousness? I've gone through Wiki, SEP and a fair number of books on philosophy and a few on neuroscience but I still don't understand what it is that I experience as the color "red" when in reality it's just a bunch of electric fields (photons). Why can't I get the same experience — i.e., color — when I look at UV or IR photons? These too are the very same electric fields as the red, blue, green I see all the time.
• Photographic composition. I'm a designer. I know them. I use them. But only empirically. I just do not understand them at a neuroscientific level. Why does rule-of-thirds feel pleasing? Is the golden ration bullshit? My gut says yes but I'm unable to come up with a watertight rebuttal. Why do anamorphic ultra-widescreen shoots feel so dramatic/cinematic? Yet to see an online exposition on the fundamental reasons underlying the experience. Any questions to artists are deflected with the standard "It's art, not science" reply.
• Wave-Particle duality. "It's a probability wave that determines when a particle will pop into existence out of nothingness." okay, where exactly does this particle come from? If enough energy accumulates in a region of empty space, a particle pops into existence? What is this "energy"? What is it made of? What even is an electron, really? I've followed quite a few rabbit holes and come out none the wiser for it.
• Convolution. It's disappointing how little I understand it given how wide its applications are. Convolution of two gaussians is a gaussian? Convolution in time domain is multiplication in frequency domain and vice-versa? How do these come out of the definition which is "convolution is sliding a flipped kernel over a signal"?
I think this was a pretty neat explanation:
https://sites.google.com/site/butwhymath/m/convolution
The problem with convolutions, like many things in science, is that how you learn it, depends on what you're studying. Same theory, but with N different explanations, which can cause confusion if some of them are very different and tough to connect (i.e learning convolutions in a physics class vs leaning one in a statistics class)