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Paper 1
Convolutional neural network based decoders for surface codes
Simone Bordoni, Stefano Giagu
- Year
- 2023
- Journal
- arXiv preprint
- DOI
- arXiv:2312.03508
- arXiv
- 2312.03508
The decoding of error syndromes of surface codes with classical algorithms may slow down quantum computation. To overcome this problem it is possible to implement decoding algorithms based on artificial neural networks. This work reports a study of decoders based on convolutional neural networks, tested on different code distances and noise models. The results show that decoders based on convolutional neural networks have good performance and can adapt to different noise models. Moreover, explainable machine learning techniques have been applied to the neural network of the decoder to better understand the behaviour and errors of the algorithm, in order to produce a more robust and performing algorithm.
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Topical Review: Extracting Molecular Frame Photoionization Dynamics from Experimental Data
Paul Hockett, Varun Makhija
- Year
- 2022
- Journal
- arXiv preprint
- DOI
- arXiv:2209.04301
- arXiv
- 2209.04301
Methods for experimental reconstruction of molecular frame (MF) photoionization dynamics, and related properties - specifically MF photoelectron angular distributions (PADs) and continuum density matrices - are outlined and discussed. General concepts are introduced for the non-expert reader, and experimental and theoretical techniques are further outlined in some depth. Particular focus is placed on a detailed example of numerical reconstruction techniques for matrix-element retrieval from time-domain experimental measurements making use of rotational-wavepackets (i.e. aligned frame measurements) - the ``bootstrapping to the MF" methodology - and a matrix-inversion technique for direct MF-PAD recovery. Ongoing resources for interested researchers are also introduced, including sample data, reconstruction codes (the \textit{Photoelectron Metrology Toolkit}, written in python, and associated \textit{Quantum Metrology with Photoelectrons} platform/ecosystem), and literature via online repositories; it is hoped these resources will be of ongoing use to the community.
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