Hi! I have been using your videos for years ever since I first had to install heasoft back in 2020 haha. I wanted to reach out to see if you would be interested in collaborating on a project related to machine learning and quasi-periodic oscillations in neutron stars. I published an initial concept paper in MNRAS on this topic but I need some help with data processing to scale the project up!
In numerical recipes is routine for it but if we want to write it from scratch i found reduction to Hessenberg by Gaussian elimination (Householder reflections would be better but I havent found how to effectively multiply matrix by Householder reflections) I derived multiplication by rotation matrices G from the left and G^{T} from the right which allowed to write QR decomposition But which shifts should I use How to use deflation QR metod can be done in place but how to do it
My major is general physics and I plan to do a PhD in physics related to quantum mechanics. I’m eager to learn anything related to my future career. Luckily the YT algorithm recommended a video of this series to me this morning! Thank you!
Thank you so much dude. My professor somewhat went over how to do this in his lecture with the 1st degree equation of a line, but there was basically 0 material on how to do it with polynomials. This makes a ton of sense and helped me out.
Thanks for the information, but I have a question , is possible obtain with the software Heasoft he values of Nh(density column) for a big data, could you explain it ? please, Thank you so much!.
Is it a bad idea to let the curve C be a function of the form r = a(t) + i * b(t), a<=t<=b. And then integrate the real and imaginary integrals from t = a to t = a, because of it being closed, and then using the fundamental theorem to argue that the result should be zero.
Also the Green's theorem says that the integration over a boundary is equal to the integral over the domain, given some conditions. So should we not make the assumption that the contour can be continously deformed so its boundary perfectly fits with the boundary of the analytic domain, D. Since the original integration is done over the boundary of the domain C which is obviously a subset of D. So C would have to be made equal to D in order for Greens theorem to apply for the domain D.
my configure failed and it says scipy version is older and need v1.5. my scipy version is v1.3 and when i tried to upgrade it it says its the latest version. . what shoild i do ?
Very helpful, thank you! Bounding the integral on the upper arc of the semicircle to show that it goes to 0 in the limit takes some extra work, though.
What about the convergence or real integral in the disk where we convert and integrate? If real integral doesn't convergence in the disk, it's impossible to do next steps.
