Apple's new ARM CPUs vs, classic x86 for physics?

AI Thread Summary
In this discussion, a second-year student seeks advice on whether to purchase a Mac with M-series chips or a Windows laptop for coding and lab reports using MacTeX. Concerns about software compatibility with ARM architecture are raised, particularly regarding physics software and Python libraries like Matplotlib, Pandas, and NumPy. It is noted that the current version of MacTeX runs natively on ARM, and many developers have likely updated their software for Apple Silicon. However, specific compatibility issues with Anaconda and Qt are highlighted, indicating that some tools may not be available on M1 Macs. The conversation also suggests considering the cost-effectiveness of a refurbished desktop for better screen real estate while retaining a laptop for portability. Overall, the discussion emphasizes the importance of checking software compatibility and weighing the benefits of different hardware options for academic needs.
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ARM vs x86. Which is more compatible with Physics software?
Hi it's my first post here!
I'm in my second year of my degree and looking to replace my computer. The new M-series chips seem like a better deal, however I am nervous that some software that might not be compatible with the ARM architecture. For more context on my workflow I do quite a bit of coding and use MacTeX for my lab reports.

Should I go with the Macs or buy a Windows laptop?
 
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What "physics software" are you looking at, and what does it say about requirements?
 
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When I upgraded to Apple Silicon awhile back, I didn't have to abandon any software due to compatibility. The current version of MacTeX runs natively on ARM, and I'm pretty sure the previous one did too. The only software I stopped using was DropBox since they still hadn't bothered to release an ARM client at the time and I didn't really use DropBox anymore anyway. The ARM-based systems have been out for a while now, so I would expect most developers who support macOS have already ported their software to Apple Silicon.
 
@Vanadium 50 I'm still an undergraduate so I've not used a lot of the heavy programs. The ones I use right now are python libraries such at matplot, pandas, astropy and numpy obviously. Our university uses the Anaconda distribution, but my computer can't handle it so I am forced to use Spyder and download some of the libraries myself. Other than python, we have used MATLAB before and I regularly have to use SAOImageDS9.
 
Dex_ said:
Our university uses the Anaconda distribution, but my computer can't handle it so I am forced to use Spyder and download some of the libraries myself.
You might want to check out compatibility of all of Anaconda on M1 https://www.anaconda.com/blog/new-release-anaconda-distribution-now-supporting-m1
Please note that macOS M1 does not support Qt yet – Anaconda Navigator and Spyder will not be available. Please check back for updates.
Support for other Python things on Apple Silicon (e.g. TensorFlow) is also more complicated.

As an alternative have you looked at what the price of an M1 Mac would get you in (possibly refurbished) desktop hardware with as much screen real estate as you can afford (possibly starting small and upgrading later)? You can still use your laptop for taking notes in class etc, or if it is really dying get a chromebook.

IME expensive laptops suck for coding, writing documents, spreadsheets, just about everything apart from showing off in coffee shops next to a power outlet.
 
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