qvm VS RE2

Quil's semantics are based off of an idea called the "quantum abstract machine". A piece of software which emulates the quantum abstract machine is called the Quantum Virtual Machine or QVM. It's open source and available here.

More interestingly, the QVM repository includes a program called the dqvm which is the QVM but able to be run on an MPI cluster. This doesn't use any advanced state representation (such as matrix product states) and instead just very cleverly arranges for huge wavefunctions to be distributed across a cluster of arbitrary size and worked on in parallel.

and/or in-line assembly code, and still can't optimize specific matrix shapes and structures, or do algebraic simplifications to eliminate work altogether.

The regex library FTA is a great, and clean, example of a long standing practice of compiling regexen, except it doesn't use any fancy VMs or any fancy JITs, just "when you see this regex, automatically turn it into this Common Lisp code, and let the Lisp compiler handle the rest."

[0a] https://github.com/quil-lang/qvm

[0b] COMPILE-OPERATOR: https://github.com/quil-lang/qvm/blob/master/src/compile-gat...

[1] https://www.gnu.org/software/libjit/

quantum computer simulator

Yes, simulator, compiler, paper is some of it.

You can also do this with purely free and open source software like [0].

[0] https://github.com/quil-lang/qvm

I wish I could try running the DQVM, the distributed quantum simulator written in Common Lisp [0], on this thing.

[0] https://github.com/quil-lang/qvm/tree/master/dqvm

Looking at the benchmark where C++ is worst compared to other languages, it's depending on the library used. I would guess if they used Google's re2 Regex library instead of Boost's, the result would be different.

https://github.com/google/re2

https://github.com/greensoftwarelab/Energy-Languages/blob/ma...

That page says it just includes "some of the most common special characters", and following the link to the Examples page in turn includes a link to the full list.

Python uses backtracking, so this probably isn't O(n), especially with the ability to choose the dictionary.

But with there are non-backtracking matchers which would make this O(n). Here's re2 from https://github.com/google/re2 :

  >>> import re2

RE2 is a Google regular expression library

google's regex library: https://github.com/google/re2

I am currently working with Regex, specifically Re2, and was wondering if there is a real difference between the above expressions for repeated sub-regex.

I ported Google RE2, a regular expression library, to SPVM as Resource::Re2, and created SPVM::Regex, a wrapper for it.

I searched for I found that there is a Perl compatible regular expression called Google RE2. It is written in C++, and with Google RE2, I can use Perl-compatible regular expressions as a library.

Yes, but there is an interesting clarification here. RE2 has used the "caching" approach documented in the Ruby bug ticket linked for quite some time (since its birth?): https://github.com/google/re2/blob/954656f47fe8fb505d4818da1...

It is mentioned only briefly in Cox's article on regex matching in the wild. Look for the word "bitstate": https://swtch.com/~rsc/regexp/regexp3.html

I didn't know Perl had implemented this trick too.

The paper[1] cited in the Ruby bug ticket was published very recently. When I first read the Ruby bug ticket, I immediately wondered how they sidestepped the memory use problem. The paper's abstract seems to suggest there is some technique for doing so, as it rebuffs the idea of doing "full" memoization. Alas, I do not have access the paper. (Which is fucking ridiculous.)

[1]: https://ieeexplore.ieee.org/abstract/document/9519427