1 to 10 of 18 Results
Adobe PDF - 196.7 KB -
MD5: 01650ac972958f9fe0687708d2fb0990
Figure 6: Plot from the generated data. |
Nov 27, 2023 -
Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities
MS Excel Spreadsheet - 18.8 KB -
MD5: e9ae404b4c15cf4db615debfb318510d
List of scenarios found in the Google Scholar literature search. (The original file.) |
Adobe PDF - 70.2 KB -
MD5: 21850b0dc649f6572df2431daf6e5c6f
The average risk after training a 6-qubit QNN for randomly generated target unitaries. For this experiment, data of varying Schmidt rank with average ranks r ∈ {1,2,4,64} and different input sizes t ∈ {1,2,4,8,16,32,64} was used. The markers give the experimentally computed avera... |
Adobe PDF - 158.8 KB -
MD5: e2e6fbb55a2e0cb2f2fd0c46f3086cc4
The average losses at the end of training for QNNs using training data of varying Schmidt ranks with mean Schmidt ranks in {1,2,4,64}. |
Adobe PDF - 165.4 KB -
MD5: 7591bfc8ed33637d989ac57790ccf6a4
Figure 1: The eigenvalues introduced by U†VS after training with four orthogonal inputs for a for a low-risk hypothesis (left) and for a high-risk hypothesis (right). |
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... |
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... |
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. |
Mar 15, 2023 -
Data Repository for a Systematic Mapping Study on Warm-Starting and Quantum Computing
OpenOffice Spreadsheet - 14.2 KB -
MD5: 500fb7b6d37492a75062429df269320d
Spreadsheet containing the data analysis based on properties of techniques distributed across multiple worksheets. Formulas were removed from the spreadsheet to avoid compatibility issues. (OpenDocument Spreadsheet format) |
Mar 15, 2023 -
Data Repository for a Systematic Mapping Study on Warm-Starting and Quantum Computing
MS Excel Spreadsheet - 25.6 KB -
MD5: e2e2931c814a71bad599e80c5a95803b
Spreadsheet containing the data analysis based on properties of techniques distributed across multiple worksheets.
Formulas were removed from the spreadsheet to avoid compatibility issues.
(Excel format) |