1 to 10 of 18 Results
Adobe PDF - 1.5 MB -
MD5: 2308d08265282378fd4e3335abef9f0c
Qualitative visual analysis of the selected CCSCI approaches. |
Nov 30, 2022 -
Selection, Data Extraction, and Data Synthesis for Cross-chain Smart Contract Invocation Approaches
MS Excel Spreadsheet - 410.7 KB -
MD5: a98239092402fc6514a65dbe7b24bdd8
The data presented in Microsoft Excel format. |
Nov 30, 2022 -
Selection, Data Extraction, and Data Synthesis for Cross-chain Smart Contract Invocation Approaches
OpenOffice Spreadsheet - 281.1 KB -
MD5: 4309c8502bdced6f7ce8ab8ddbd35ed1
The data presented in OpenOffice format. |
Apr 28, 2021 -
MUSE Datenset
Adobe PDF - 126.7 KB -
MD5: 2a9294d6c2bc0b95f11b9bb26def598b
Kurzbeschreibung der Daten und Anleitung zum Importieren der Daten. |
Nov 30, 2022 -
Quality Assurance Forms for Grey Literature Studies Supporting Cross-chain Smart Contract Invocations
MS Excel Spreadsheet - 23.8 KB -
MD5: 5c6f803f1bc18f6b3fb0fa8168e5b8b7
The quality assurance form for grey literature studies in MS Excel format |
Nov 30, 2022 -
Quality Assurance Forms for Grey Literature Studies Supporting Cross-chain Smart Contract Invocations
OpenOffice Spreadsheet - 15.4 KB -
MD5: 035212d37487db785d1341ccbd62fb59
The quality assurance form for grey literature studies in OpenOffice format |
Adobe PDF - 1.5 MB -
MD5: fe7ab8c0df4dcb06431dffceb59a58a2
The protocol document. |
Jul 11, 2023 -
Data repository for: Investigating the effect of circuit cutting in QAOA for the MaxCut problem on NISQ devices
Adobe PDF - 875.6 KB -
MD5: ac0d8290ee7d3aa4bf0f2f554a5ebc27
This document presents five supplementary plots that provide a comprehensive summary of the data across all graphs in all experiments. Please refer to the plots.zip archive for plots specific to each graph. |
Adobe PDF - 68.7 KB -
MD5: 60f2614c7fffce46d724ccc90c2e1a10
The average risk after training a 6-qubit QNN for randomly generated target unitaries using orthogonal data. For each number of training pairs t, the Schmidt rank is chosen as such that r · t = d. The lower bound for the risk for this configuration is shown as a dashed line. The... |
Adobe PDF - 68.6 KB -
MD5: 80bc1f5e3db61210162ddf4b8ffe23d3
The average risk after training a 6-qubit QNN for randomly generated target unitaries using linearly dependent data according. For each number of training pairs t, the Schmidt rank is chosen as such that r · t = d. The lower bound for the risk for this configuration is shown as a... |