I worked in that field doing numerical many-body simulations of electron dynamics interacting with their environment in solid state devices like quantum dots, graphene, photonic waveguides & cavities , etc.
You would start from a Lagrangian formulation of the classical interaction, let's say Light-Matter, that would yield for example the Schrodinger and Maxwell equations. Following a Legendre transformation (there a post on the HN front page the other day on that) you end up with a so-called Hamilton operator from which you can derive a (huge) set of coupled differential equations which you then solve.
Here, if you wanted to increase temporal accuracy, it typically leads simply to longer calculation times.
We also tried a different approach using Feynman's path integrals and boy did that explode numerically. We optimized our programs to the point where everything was reduced to work on bits, but to no avail it was numerically unstable and the memory consumption when through the roof the longer or more accurate you wanted to make the simulation.
So, I would argue that NO, Feynman does not make it easier per se.
However, other groups made it work somehow.
As a starting point you can check that paper and it's references from the introduction section.
For writing documentation: AsciiDoc [1] as fileformat.
For publishing documentation / to build the web site: Antora [2].
AsciiDoc has a bit more features compared to Markdown which allows for a richer and more pleasant presentation of the docs.
Antora allows you to have the project documentation in the actual project repositories. It then pulls the docs from all the different repos together to build the site. This also allows you to have the released product versions go in-synch with the docs versions. Antora builds each version of the product as part of one site. The reader can explore different product versions or navigate between pages across versions.
IBM did research back in the 90s on perceptually-based colormaps and how to best represent various types of data within the color dimensions of luminescence, saturation and hue [1]. For example, they found that,
(1) Hue was not a good dimension for encoding magnitude information, i.e. rainbow color maps are bad.
(2) The mechanisms in human vision responsible for high spatial frequency information processing are luminance channels. If the data to be represented have high spatial frequency, use a color map which has a strong luminance variation across the data range.
(3) For interval and ratio data, both luminance- and saturation-varying color maps should produce the effect of having equal steps in data value correspond to equal perceptual steps, but the first will be most effective for high spatial frequency data variations and the second will be most effective for low spatial frequency variations.
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[1] the original link got removed from IBMs website. Back in the day it was under
In total, yes it was. Working for some years in a field, having the time afforded to emerse yourself into a subject and deeply think about it, calculating yourself into frustrating dead ends and also
into successes, writing papers, going to conferences presenting your results, have scientific exchanges with peers, write applications for research grants, sit in committees, work as a referee for scientific journals, teaching students, then writing a coherent and compelling thesis and finally defending it against & having a scientific discussion on eye-to-eye level with your supervisors will shape your character... a lot.
You might wanna skip that postdoc thing though if you know you don't wanna stay in academia (and trust me, you don't).
Exactly my experience back in the days doing the mandatory "advanced experimental physics laboratory semester" where you had to do like 14 vastly different experiment of the caliber described in that post in the course of one semester on old equipment that would break during the experiment, with less than motivated PhD students or post grads as teachers. Of the 14 experiments only two worked and we got the expected results.
This experience drove me right into theoretical physics and writing computer simulations of electron dynamics and light-matter interactions in confined semiconductors (quantum dots, graphene and the like). That was fun.
Now I am working on medical device software development, as the other stuff does not pay the bills.
Great article on the topic.
Biggest takeaway is how they added linters and link checkers to the toolchain.
We currently try to establish something similar on our end using AsciiDoc [1] as fileformat, Antora [2] to build the site and hosting on Azure storage.
AsciiDoc has a bit more features compared to Markdown which allows for a richer presentation of the docs.
Biggest difference is that Linode has the docs in a separate repository. Not sure if it is a limitation of their toolchain or a deliberate decision.
Antora allows you to have the project documentation in the actual project repositories. It then pulls the docs from all the different repos together to build the site. This also allows you to have the released product versions go in-synch with the docs versions. Antora builds each version of the product as part of one site. The reader can explore different product versions or navigate between pages across versions.
Mentioned in the text is IBM, which did research back in the 90s on perceptually-based colormaps and how to best represent various types of data within the color dimensions of luminescence, saturation and hue [1]. For example, they found that,
(1) Hue was not a good dimension for encoding magnitude information, i.e. rainbow color maps are bad.
(2) The mechanisms in human vision responsible for high spatial frequency information processing are luminance channels. If the data to be represented have high spatial frequency, use a color map which has a strong luminance variation across the data range.
(3) For interval and ratio data, both luminance- and saturation-varying color maps should produce the effect of having equal steps in data value correspond to equal perceptual steps, but the first will be most effective for high spatial frequency data variations and the second will be most effective for low spatial frequency variations.
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[1] the original link got removed from IBMs website. Back in the day it was under
Decreasing the total energy exposure of the complete biosphere to reduce temperature rise sounds risky to me.
Yes, it might not become as warm, but especially plants need sunlight for photosynthesis / oxygen production. If we deny the plants that energy the ripple effect throughout the biosphere will be huge.
> You can load models from your computer. In this case the model won't be uploaded to any web server, the entire process happens in your browser.
Could I somehow embed this as a preview feature in an other application (which is completely under my control)?
Let's say I am working on a gallery application, but not for photos/image files, but for 3D files. Could I ember a browser/html page render and use this online 3D viewer there?
https://www.australiangeographic.com.au/news/2024/08/high-co...