PennyLaneAI / catalyst

A JIT compiler for hybrid quantum programs in PennyLane
https://docs.pennylane.ai/projects/catalyst
Apache License 2.0
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openjournals/joss-reviews#6720 #887

Closed pmcao closed 3 months ago

pmcao commented 3 months ago

openjournals/joss-reviews#6720

Comment:

On balance, the paper has motivated the need, described three critical pillars of the JIT compiler infrastructure, and made significant open-source contributions.

My takeaway from reviewing this paper is that fault-tolerant quantum computing has to be supported end-to-end in both hardware, mid-circuit, and classical processing because the fault can manifest at any part of the pipeline, for example, Silent Data Corruption in the classical processing part. As the author mentioned, "becoming clear that we cannot separate classical and quantum parts of the program".

This JOSS paper would benefit from a Discussion / Future Work in which the authors, with their expertise, could point to future directions in this area.

pmcao commented 3 months ago

This is a minor issue that would need a few sentences to be resolved.

After that, the submission can be published.

This comment finalizes my review.

josh146 commented 3 months ago

Hi @pmcao, thank you for your review comments!

This JOSS paper would benefit from a Discussion / Future Work in which the authors, with their expertise, could point to future directions in this area.

I have added a new section to the manuscript, detailing future directions for the catalyst hybrid compilation stack:

# Discussion and future work

The Catalyst hybrid compilation stack as presented here provides an end-to-end infrastructure
to explore next-generation dynamic hybrid quantum-classical algorithms, by allowing for 
workflows that support compressed representation of large, highly structured quantum 
algorithms, as well as mid-circuit measurements with arbitrary classical processing and 
feedforward.

The Catalyst software stack will continue to be developed alongside research, algorith, and 
hardware needs, with potential future work including support for quantum hardware control 
systems, building out a library of MLIR quantum compilation passes for optimizing quantum 
circuits (without unrolling classical control structure), and explorations of dynamic quantum 
error mitigation and proof-of-concept error correction experiments.

Quantum software is driving many new results and ideas in quantum computing research, and the 
PennyLane framework has already been used in a number of scientific publications 
[@delgado2021variational; @wierichs2021general] and educational materials [@demos]. By enabling 
researchers to scale up their ideas and algorithms, and execute on both near-term and future 
quantum hardware, the software presented here will help drive future research in quantum 
computing.