Quantum-assisted quantum compiling paper (enrichment)

Discussion (26:04) We'll watch the 1st 4 minutes.

Popular summary (copied from the paper)

Ordinary computers require a compiler that converts one's code into a machine-level language. Quantum computers require a compiler as well. However, a new challenge for such "quantum compilers" is that they should be optimal, i.e., they should return a machine-level program that has as few operations as possible. This optimality is crucial for current noisy quantum devices, where longer programs accumulate more errors while shorter programs avoid errors. In this work, we introduce an algorithm for optimal quantum compiling. The key feature that allows for optimality is that we propose to use quantum computers themselves to assist in the compiling process. Hence, our algorithm is called quantum-assisted quantum compiling (QAQC, pronounced "Quack").

The idea is that one needs to quantify the distance between the original program and the compiled program, with the goal of trying to minimize this distance. We prove that this distance calculation cannot be done efficiently on a classical computer. On the other hand, we provide an efficient quantum circuit for computing it.

In addition to shortening the length of one's quantum program, QAQC can be used to learn algorithms that compensate for a given quantum computer's noise and also to benchmark the noise processes occurring on a quantum computer. We successfully implement QAQC for small programs using currently available quantum computers from IBM and Rigetti, and we use simulators to explore the compilation of larger programs. Overall, QAQC appears to be a promising tool for mitigating errors in the era of noisy intermediate-scale quantum computers.

Using SAT Solvers for Quantum Computing Design: Potential and Challenges (48:03) Oct 25, 2021.

We'll watch the 1st 20 minutes.

Quantum circuit optimisation, verification, and simulation with PyZX, (33:26), by John van de Wetering at: FOSDEM 2020

affiliated sites:

1. https://zxcalculus.com

2. https://github.com/Quantomatic/pyzx Python library for quantum circuit rewriting and optimisation using the ZX-calculus

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Compilers for the NISQ era, Ross Duncan, #QRST (30:12), Oct 6, 2020.

So you have a new quantum computer? What now? I’ll present t|ket⟩, a quantum software development platform produced by Cambridge Quantum Computing Ltd which will help you get the best out of your new machine. The heart of t|ket⟩ is a language-agnostic optimising compiler designed to generate code for a variety of NISQ devices, which has several features designed to minimise the influence of device error. The compiler has been extensively benchmarked and outperforms most competitors in terms of circuit optimisation and qubit routing. This talk will cover roughly the same ground as our recent paper (arXiv:2003.10611) but such is the nature of the field, that paper is already obsolete, so I will cover some of the hot new sh*t we have done since then.