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With the improvements in hardware, sample environment, and new data packets/storage of events we require new software for the production, distribution, caching, saving, histograming, reducing, fitting, monitoring, and feedback to users/NICE.
CHRNS Computing resources are available via ORCiD login within NIST
DAVE and Mslice for MACS
SASView for VSANS
Refl1D for CANDOR
Developing necessary web-based tools to perform all other tasks
New rebinning API and web interface for event mode data
Built around the newest data management tools from the CHRNS-FAIR initiative, we have designed a web interface that allows inspection and rebinning (<1 second!) of time-stammped neutron data. The API allows for automated data binning. The code is located here.
Web interface to rebin event-mode data
Refl1D/CANDOR data fitting
Enabled remote (web-based) access to a 'live' fitting server for interactive fitting sessions, or static fit results for batch fits for the Refl1D analysis software, which is used for analysis of data from the CHRNS CANDOR instrument.
The interface is detachable and re-attachable to the fitting session at any time
Parameter error bars are determined with MCMC, correlations, fit history etc. visually represented
Necessary for Autonomous Experiments
Low-code fitting development:
Simple web app lets users build physical models
Compare model to data directly in-app
Code is generated from the visual model representation and piped to Refl1D
A low code app to make models and code for advanced fitting
Experimental optimization of the neutron instrument, measurement, and sample to greatly reduce measurement times and increase data quality.
Remote Execution of CANDOR experimental optimizations
Jupyter Notebook data fitting using Refl1D
Feature-complete experimental optimization for bio-materials
C++ classes wrapped in Python for speed and compatibility
Intelligent experiment-design and experiment-planning tools using predictions of information content based on user-supplied models (bio/soft materials initially)
Remote Execution of SANS experimental optimizations
Feature-complete experimental optimization
lipid vesicle molecular model
Any SASView model
Monte Carlo Markov Chain fitting of SANS data
Instrument resolution
We have implemented Autonomous Reflectivity measurements on CANDOR, and once we gain experience and user feedback through hot-testing, we will use that understanding to provide intelligent, automated determinations of how to efficiently complete VSANS measurements. The ‘immediate’ feedback to the user on the information content of a measurement and statistical error analysis for a given model(s) can be used to reduce overcounting in SANS. This does not require a time-resolved experiment to leverage the capability.
DAVE and Mslice
Used for reducing MACS data and has been adapted to visualize time-slice data, taking special care of the error bar due to low count rate of the event mode. (DAVE)