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Dataset results
3 results for “quantum noise limited”
Experimental data for Quantum noise limited microwave amplification using a graphene Josephson junction
<p>This dataset was used in our study of "Quantum noise limited microwave amplification using a graphene Josephson junction".</p>
Data for LIGO operates with quantum noise below the Standard Quantum Limit
<p>This repository hosts data sets used to create all the figures in the paper "LIGO operates with quantum noise below the Standard Quantum Limit". </p> <p> </p> <p>Version 1: initial upload</p> <p>Version 2: Add README.txt and MCMC set-up code</p>
Data repository of the paper "Quantum-noise-limited optical neural networks operating at a few quanta per activation"
<p>This data repository includes the requisite data and code for deriving the primary results from the paper, "Quantum-noise-limited optical neural networks operating at a few quanta per activation". The repository is structured to provide everything needed to reproduce the figures included in the main manuscript, along with the source code for training the neural network models and the collected experimental data mentioned in the paper.</p> <p>The code in this repository is primarily intended for reproducing the results discussed in the paper. Those interested in developing their own applications may refer to our Github repository: https://github.com/mcmahon-lab/Single-Photon-Detection-Neural-Networks.</p> <p><strong>Where to Start</strong></p> <p>The directory 'main_figures' includes Jupyter notebooks to generate each panel in Figure 3 and Figure 4 in the main text, using the data from the directory 'results', which can be generated by notebooks in the directory 'test'. </p> <p>The simulations, experiments, and figure generation were all conducted in Python. As certain parts of the code require specific versions of Python packages, the necessary packages are listed in the 'requirements.txt' file.</p> <p>For more information, please refer to 'README.txt'.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.