I totally agree that having a decent personal machine is of utmost importance for a matter modeling researcher, but this doesn't mean you have to buy a very expensive and/or powerful laptop, especially for (most of) the reasons you provided after this part of your question:
"Though most matter modelling researchers, run the bulk of their calculations on computing clusters, the need for a powerful personal computing machine still seems unavoidable. For a few reasons like..."
I'll go through your reasons one by one:
- "Run some back-of-the-envelope-style quick numerics/computations"
By definition, a "back-of-the-envelope-style calculation" does not need a very expensive computer. I guess you mean medium-scale calculations. I agree that it's nice to be able to run some fairly serious calculations in MATLAB on a laptop (even with a laptop GPU) but laptops are not meant for doing heavy calculations or even medium-scale calculations (except for laptops like TensorBook, which is extremely overpriced). The vast majority of laptops and laptop users do web browsing and word processing. A server-grade compute node in a proper cluster can run at 100% CPU capacity for days and not get dangerously overheated, but laptops were never meant to be safe for that type of usage, nor resilient to doing it without burning out.
I'm also assuming that you're paying for this yourself rather than getting it for free, or on a budget that can only be spent on a single laptop (since most people reading this answer will be in the former situation). Laptops are overpriced (spec-for-spec) compared to bigger computers (meaning a laptop with 16GB of RAM will typically cost far more than a desktop with 16GB of RAM or putting a 16GB compute node into an existing cluster), and the only reason for getting a laptop rather than a desktop is portability/travel, which causes wear and tear and risk of dropping/losing it, which is just another reason why getting a very expensive one with 32GB of RAM is not the best idea.
A laptop with 16GB of RAM is quite ideal: not too expensive (especially if you buy it with 8GB and an extra DIMM slot where you can add the other 8GB yourself, but unfortunately a lot of them these days don't allow that because they come with all slots filled with RAM that's soldered into the MOBO), and would rarely go over RAM capacity (especially with a good operating system and smart usage, such as browser tab suspenders). However, I say this more because researchers often like to have lots of tabs open in their web browser (lots of research papers that they "must read later but don't yet have time"!), not because it's great for doing back-of-the-envelope or medium-scale calculations. If you want to do calculations involving 16GB of RAM or more, seriously consider doing it on a server meant for calculations, even if your laptop has (for some reason) 128GB of RAM: such calculations will almost always be heavy in CPU usage too, and do you really want to burn out your expensive laptop CPU rather than the comparatively much cheaper server-grade CPU that's designed for calculations?
- "Post-simulation analysis with scripting tools"
Except for high-performance graphics (HPG?) which is addressed in your next point, I'm not sure what post-simulation analysis using scripting tools, you could be doing which needs more than 16GB of RAM and yet can't be done relatively easily on a compute cluster that's meant for doing such "heavier" calculations.
- "Plotting, Creating illustrations (for example with Blender or something similar) etc."
Most "plotting" is on a 2D grid (x-axis and y-axis) and doesn't need much computing power, but creating illustrations (or nowadays, also videos!) can be very demanding on computer resources. Is there a reason why you need a laptop to do these? If you're doing a lot of video editing, I'd recommend a desktop since one with 32GB of RAM could easily cost the same as an equally powerful laptop with 16GB of RAM (for example). I'm assuming that you're not doing a lot of serious video rendering while on a train anyways, but I appreciate that everyone has their own way of doing things.
- "Code Development (especially for people contributing to various packages across the board)"
I totally agree that this requires a lot of debugging and testing, for which decent computing power is often needed, but it's again unlikely that you need something with more than 16GB of RAM.
So now I'll answer the rest of your questions:
- Intel (usually seemed to be the preferred ones due to Intel MKl and oneAPI)
- AMD (though not the default choice, they seem to be getting better)
- Apple silicon (They seem promising, but I am not sure if people in the community are already adopting these new architectures)
Other relevant Hardware specs"
Intel. It's true that AMD is getting better, but it's much easier and safer to just stick with Intel for now. You'll already have millions of options available to you, so filtering your search results for only Intel will also help save you time, among many other advantages (some which you seem to already know!).
"Other relevant Hardware specs
I mentioned my recommendations earlier :)
They are very helpful indeed, but unfortunately it's also easy to get this "wrong". Having an SSD can certainly make a noticeable speed difference in your experience with booting the computer and opening software, but almost everybody has fewer than 128GB of software while the rest are personal files/data for which it's usually actually better to have an HDD drive since for the same price you can get far, far, far more storage space with not much less functionality. I'd recommend 128-256GB of SSD and 1-2TB of HDD (I personally like to have a lot of storage space, but you might not need that much, so it's your call, but 512GB of SSD space is a bit overkill in my opinion since it's extremely unlikely that you're actually using all that data often).
It's very convenient to have one if you're developing code that is meant to run on GPUs, or if you're testing or doing some simple calculations that use GPUs, but GPUs are expensive and you won't be able to compete with what supercomputing clusters have, so I wouldn't spend too much money on this part (1-2GB of RAM at the most, for example). If you do get a GPU, for many things, it absolutely needs to be an NVIDIA GPU (many things in scientific computing only work with NVIDIA GPUs).
Final recommendation: If you get a laptop with an Intel CPU and 16GB of RAM , a 128-256GB SDD, a 1-2TB HDD and a 1-2GB NVIDIA GPU (only if you really do need it, because otherwise it can actually be harmful, which I can explain in another answer if you want to ask!), then you'll be getting something very decent for your work as a matter modeling researcher with access to larger supercomputing facilities, without entering the realm of the "overpriced" and without risking walking around with something ultra-expensive (which can be stressful).