Optics: Closing the computation to hardware gap. Yes, it is a 'solved' science, very much so, decades in fact. We still struggle mightily in making anything pra

Optics: Closing the computation to hardware gap. Yes, it is a 'solved' science, very much so, decades in fact. We still struggle mightily in making anything practical out of the equations. It's a bit backwards from most engineering. With bridges and milk-jugs we can get pretty close on paper to the actual product. With optics, we kinda get the theory after we've built it and made the light/photons go all wiggly. It's tough stuff, but would be very useful. Mathematics: A generalized solution to n-order partial differential equations. Laplace, Chebyshev, Hamilton, Wave equations, sure, ok, yes. But I mean any n-order partial differential, not the 'lucky' cases. You get that, and you've solved a great deal of the outstanding problems in other fields (hydrodynamics, optics, economics, turbulence). I'm not sure up to date on this, and it may have been proved that a general solution is actually impossible, but I'm not sure. Physics: Braver grad students. Quantum Gravity is a long was off, we need much bigger machines or a constellation of satellites that use the sky as the particle accelerator. As such, having these brilliant minds labor on obscure portions on some niche interpretation of physics, well, it's useless really. The data will make it all clear as day, whenever the data gets here. Until then, the grad students need to be braver and strike out on their own, leaving the golden age behind. We need them to work on other things. I know that's tough as nails, but I think it's what is needed. Great work has been done in neuroscience by physicists (despite their best efforts :P), and the quants on Wall Street are a meme now. More of that, but in, I dunno, weaving or something.