The main point of IBM was that by using RAM and Disk storage you could perform computations of the google system that were not as onerous as was put out in the google paper. That said, if you had an extra 10+ qubits…
Can not agree with this more, if people want to plot something that is linear please use a perceptually linear colormap! Just a one second glance at the Mona Lisa in rainbow/Jet is enough to make you gouge your eyes…
Cognitive. Things like having to strip down abstractions and "write it like Fortran". The fact that it can deal with numpy arrays no problem and can actually deal with more common python objects like dicts means that…
I had considered Numba in the past but it just seemed not worth the overhead. A few talks from this year show that they have really expanded the library, to the point where much of the scientific python stack use it…
The main point of IBM was that by using RAM and Disk storage you could perform computations of the google system that were not as onerous as was put out in the google paper. That said, if you had an extra 10+ qubits…
Can not agree with this more, if people want to plot something that is linear please use a perceptually linear colormap! Just a one second glance at the Mona Lisa in rainbow/Jet is enough to make you gouge your eyes…
Cognitive. Things like having to strip down abstractions and "write it like Fortran". The fact that it can deal with numpy arrays no problem and can actually deal with more common python objects like dicts means that…
I had considered Numba in the past but it just seemed not worth the overhead. A few talks from this year show that they have really expanded the library, to the point where much of the scientific python stack use it…