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The reason to do this would to create a quantum computer emulator. I was looking into this myself recently. I believe Iran was doing the same things but on FPGAs:

https://www.tomshardware.com/news/iran-quantum-computer-arm-...



Why would anyone outside of quantum computer research want a quantum computer emulator? On classical machines, classical algorithms beat emulated quantum ones by a very large margin. And Iran apparently claimed "detecting surface vessels using the quantum algorithms", which makes very little sense as there are no high-performance quantum image detection algorithms known, so this is highly likely just some Iranian researchers fooling their government, and making a laughing stock of themselves in the process.


presumably you would want it in order to do research on quantum algorithms, but i don't see what that has to do with fractran


To record the state of a qubit you need fractions and to do quantum math it's mostly multiplying fractions.


someone has a major confusion of levels here. have they ever tried asking gpt-4 to multiply some matrices, i wonder?


I'm guessing that's a joke. The benefit of hardware support for fractions is eliminating rounding errors you get with today's machines. You can do it with libs like PyMath but ultimately you need to do build it from the ground up to completely eliminate type and class abstractions messing up the accuracy, so why not start at the hardware level so potential future chips are automatically supported? Then you can get today's performance without the overhead of legacy software.


it's not a joke. writing a program in fractran to multiply input fractions that are part of the input data is no easier than writing a program in other turing-tarpit esolangs with no built-in arithmetic support, like the λ-calculus. try it. or check out https://stackoverflow.com/questions/1749905/code-golf-fractr... which has a couple of unusably inefficient fractran interpreters in fractran




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