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11 to 20 of 2,436 Results
plot.ipynb
Dec 16, 2024 - Data repository for "Joint Wire Cutting with Non-Maximally Entangled States"
Jupyter Notebook - 58.7 KB - MD5: dddcc6cf6126e960de35b77316a6c9dd
The main entry point to plot generated data. Requires the data as CSV file.
README.md
Dec 16, 2024 - Data repository for "Joint Wire Cutting with Non-Maximally Entangled States"
Markdown Text - 2.1 KB - MD5: e578ebbd1e188030418ecb9c26adc624
Readme file with additional information on the data and code.
requirements.txt
Dec 16, 2024 - Data repository for "Joint Wire Cutting with Non-Maximally Entangled States"
Plain Text - 2.1 KB - MD5: f5d9b3247d64823beabb16315090f872
Python requirements for reproduction.
states.py
Dec 16, 2024 - Data repository for "Joint Wire Cutting with Non-Maximally Entangled States"
Python Source Code - 1.3 KB - MD5: a0cdda6de40f11db533b691699e3ec80
Functions to generate entangled states
test_cut.py
Dec 16, 2024 - Data repository for "Joint Wire Cutting with Non-Maximally Entangled States"
Python Source Code - 2.7 KB - MD5: b244c0ef8c8a9c58576370ae90a79590
Tests for functions in "cut.py".
test_mubs.py
Dec 16, 2024 - Data repository for "Joint Wire Cutting with Non-Maximally Entangled States"
Python Source Code - 1.2 KB - MD5: 2f60a0784ca977a192382cfa97dd44d3
Tests for functions in "mubs.py".
test_operators.py
Dec 16, 2024 - Data repository for "Joint Wire Cutting with Non-Maximally Entangled States"
Python Source Code - 3.4 KB - MD5: 28071dfefba2ca9109976f6142dc7378
Tests for functions in "operators.py".
code.zip
Dec 9, 2024 - Replication Data for: Advanced System Integration: Analyzing OpenAPI Chunking for Retrieval-Augmented Generation
ZIP Archive - 253.7 KB - MD5: 12d770635f5681c5fae70fe48159d570
results.zip
Dec 9, 2024 - Replication Data for: Advanced System Integration: Analyzing OpenAPI Chunking for Retrieval-Augmented Generation
ZIP Archive - 210.5 MB - MD5: 427613443f5e68f44d561e7c1d7b64fe
cuda_qnn.py
Oct 8, 2024 - Data repository for "Minimial-Risk Training Samples for QNN Training from Measurements"
Python Source Code - 24.6 KB - MD5: de37947e29cd064e381011cfc7b1f24d
Collection of various QNN implementations. For the paper the implementation UnitaryParametrization is used.
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