Quantum Bayesian Networks

October 30, 2018

“Q Entanglement Lab”, using HPC in quantum computing

Filed under: Uncategorized — rrtucci @ 4:52 pm

To paraphrase Mark Twain: “Everyone talks about Quantum Entanglement but no one ever does anything about it“. Q entanglement is at the very heart of quantum computing and quantum information theory. And yet there still doesn’t exist a decent software library for calculating the q entanglement of small to very large quantum systems in either pure or mixed states. In this blog post, I announce that I will soon release such a software library (It’s almost finished. It will be called “Q Entanglement Lab”.)

Our current BayesForge promotion is going very well, thank you. We seem to be making some inroads among users and among investors who want to help us scale our BF up in size. Many more news bulletins about BF will certainly be forthcoming in this blog in the future. This blog post is not about BF, but it’s about an issue that arose in conversations with some potential BF users. Some persons who might have access to HPC ( i.e., classical supercomputers) inquired whether you can use BF as an interface to try to break the existing record for simulating the largest number of qubits. My answer: yes, you could use BF for that purpose, because BF can include heavy duty C++, highly parallelized qc simulators. However, I think it would be wiser to pursue other, kindred records, that haven’t been pursued too vigorously by the qc community yet and would therefore be much easier to break. The record that I have in mind is using HPC for calculating entanglement for the largest number of qubits. Let me explain.

First, a bit of history about the race to use HPC to simulate the largest number of qubits. It’s a very old race. I first wrote about that race in this blog post dated June, 2010. Back then, the record was 42 qubits. It was held by a German supercomputer called Jugene. 7 years later, I reported in this blog post dated Oct 2017 how Google/ProjectQ captured the record with 45 qubits, only to have it snatched away shortly thereafter by IBM with 49 qubits. According to this paper, and also this one, the Chinese have achieved a similar 49 qubit record on their Sunway TaihuLight supercomputer.

An important consideration in pursuing such a record is that it can be quite expensive to pursue. The people at Google have written a paper in which they calculate that Google would charge you more than a million dollars to make such a simulation on their cloud.

To summarize, here are some reasons why trying to break the record for simulating the largest number of qubits might not be a very wise record to pursue.
1. expensive
2. requires access to a supercomputer, which is an extremely limited resource
3. that record has been broken many times before, so it is now very difficult to improve, and, if you do, the improvement will only be by an unsatisfying epsilon
4. improving the record by an epsilon won’t add much light into the underlying physics.

Now let me talk a little bit about my alternative proposal, to pursue the record for using HPC to calculate entanglement for the largest number of qubits.

I believe that as a quantum system evolves, its entanglement changes, sometimes going through phase transition points. This is very interesting stuff, at least to me. I believe in the future we will want to calculate various quantum entanglement measures for very large systems, so the end-product software that arises from pursuing such a record will be very useful for conducting physics studies. Furthermore, such entanglement calculations cannot be done by a qc, they must be done on classical computers, as far as I now, whereas simulations of 49 qubits will someday be done more efficiently on an actual qc.

I like so much the idea of having better software for calculating the quantum entanglement of arbitrary systems, that I have written a software package that does this. My software package is called “Q Entanglement Lab”. (first version already finished, soon to be released). My software package calculates various entanglement measures for pure and mixed states, either exactly or approximately: exactly for small systems, and approximately, using perturbation theory, for larger systems for which exactness is untenable. I have invented several new algorithms for “Q Entanglement Lab”. If you’ve previously used some of my software, you already know that I often have my own, very idiosyncratic way of doing things. Furthermore, the theory of quantum entanglement measures is very diverse. Therefore, I am sure that if others try writing their own version of “Q Entanglement Lab” before looking at what I have done, they will arrive at very different outcomes than mine. That makes this race very exciting. Let many flowers, with different colors and shapes, bloom.

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