Data for paper Designing Quantum Networks Using Preexisting Infrastructure
doi:10.4121/14914806.v1
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doi: 10.4121/14914806
doi: 10.4121/14914806
Datacite citation style:
Avis, Guus; Julian Rabbie; Wehner, S.D.C. (Stephanie); Chakraborty, Kaushik (2021): Data for paper Designing Quantum Networks Using Preexisting Infrastructure. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/14914806.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
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This is the data corresponding to the paper Designing Quantum Networks Using Preexisting Infrastructure. It contains data for parameter scans over different parameters that go into our method for solving the Repeater Allocation Problem and for the computation duration as a function of network size. In both cases, sample networks were generated as random geometric graphs. More information about the methodology can be found in the paper.
All data is in CSV format. Additionally, one python file is included that can be used to create plots based on the parameter-scan data (i.e. scan_D-(...).csv, scan_Lmax-(...).csv and scan_K-(...).csv).
The python code used to generate the data can be found in the this GitHub repository: https://github.com/jtrabbie/RepAlloc .
All data is in CSV format. Additionally, one python file is included that can be used to create plots based on the parameter-scan data (i.e. scan_D-(...).csv, scan_Lmax-(...).csv and scan_K-(...).csv).
The python code used to generate the data can be found in the this GitHub repository: https://github.com/jtrabbie/RepAlloc .
history
- 2021-07-13 first online, published, posted
publisher
4TU.ResearchData
references
funding
- Quantum Internet Alliance (grant code 820445) [more info...] European Commission
- Quantum Software Consortium (grant code 024.003.037) [more info...] Dutch Research Council
organizations
QuTech, Delft University of TechnologyKavli Institute of Nanoscience, Delft University of Technology
DATA
files (6)
- 5,329 bytesMD5:
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README - 446 bytesMD5:
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computation_times_data.csv - 1,657 bytesMD5:
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plot_csv_data_parameter_scans_on_random_geometric_graphs.py - 61,590 bytesMD5:
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scan_D-num_nodes_25_L_max_0,9_N_max_6_K_6_radius_0,9.csv - 51,329 bytesMD5:
e270392281309df36e77de5942b94c71
scan_K-num_nodes_25_Lmax_0,9_N_max_6_D_4_radius_0,9.csv - 69,433 bytesMD5:
2e56a89a785dd5eba615adae8f928a5b
scan_Lmax-num_nodes_25_N_max_6_D_4_K_6_radius_0,9.csv -
download all files (zip)
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