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https://github.com/cqcl/architecture-aware-phasepoly-synth

This repository contains the source code to replicate the results from the paper "Architecture-aware phase polynomial synthesis for NISQ devices" by Arianne Meijer - van de Griend and Ross Duncan.

https://github.com/cqcl/architecture-aware-phasepoly-synth

Science Score: 13.0%

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Last synced: 10 months ago · JSON representation

Repository

This repository contains the source code to replicate the results from the paper "Architecture-aware phase polynomial synthesis for NISQ devices" by Arianne Meijer - van de Griend and Ross Duncan.

Basic Info
  • Host: GitHub
  • Owner: CQCL
  • Language: OpenQASM
  • Default Branch: master
  • Size: 3 MB
Statistics
  • Stars: 4
  • Watchers: 4
  • Forks: 2
  • Open Issues: 1
  • Releases: 0
Created over 6 years ago · Last pushed about 4 years ago
Metadata Files
Readme

README.md

Architecture aware phase polynomial synthesis for NISQ devices.

This repository contains the source code to replicate the results from the paper "Architecture-aware phase polynomial synthesis for NISQ devices" by Arianne Meijer - van de Griend and Ross Duncan.

Installation

To run our experiments, make a python 3.6 environment and install the packages from the requirements.txt.

Installing Staq

Retrieve the Staq source code from https://github.com/softwareQinc/staq and build it as instructed. Then copy the executable to this folder such that the python file can find it.

Replicating results

Our results can be replicated using the jupyter notebook. It also contains our script for generating phase polynomials and to analyse the raw metrics from the synthesised circuits.

The proposed algorithm

The code of our proposed algorithm can be found in phase_poly.py the corresponding method in the PhasePoly class is called Ariannes_synth().

Owner

  • Name: Cambridge Quantum
  • Login: CQCL
  • Kind: organization
  • Location: Cambridge, UK

Quantum Software and Technologies

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Dependencies

requirements.txt pypi
  • jupyter ==1.0.0
  • matplotlib ==3.2.1
  • networkx ==2.4
  • numpy ==1.18.1
  • pandas ==1.0.2
  • pytket ==0.5
  • pytket-pyzx ==0.2.1