Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Generating non-gaussian samples from TENDL #41

Open
AnderGray opened this issue Feb 3, 2021 · 4 comments
Open

Generating non-gaussian samples from TENDL #41

AnderGray opened this issue Feb 3, 2021 · 4 comments

Comments

@AnderGray
Copy link

AnderGray commented Feb 3, 2021

Hi,

I'm using sandy to generate some random samples of Fe56 from TENDL 2017, and it's giving me some non-gaussian samples.

Fe56_(n,absorption)_294K_500
Fe56_(n,total)_294K_500

Would you have any clues as to why this is happening?

@AnderGray
Copy link
Author

The blue is the mean, with the red being individual samples

@AnderGray
Copy link
Author

AnderGray commented Feb 4, 2021

n-026_Fe_056.endf.zip

The endf file I began this calculation with, if that's useful.

@vivian-salino
Copy link

vivian-salino commented Feb 23, 2021

Hi @AnderGray,

It is indeed very strange that SANDY does not produce Gaussian samples. I'm afraid I can't help you on this particular point, as I've never looked closely at SANDY's sources.

However, here's my two cents, if it can help you. You have another option: you can start directly from the random files of TENDL. IMHO, this approach is even better: as far as I understand, TENDL's covariances are computed from its random files, which are not necessarily Gaussian. Sampling in TENDL's covariances will produce a degraded (Gaussianized) version of the initial information.

You will (again!) have non-Gaussian distributions, especially in the fast domain, but this time it will be a desirable feature and not a bug-like behavior.

As far as I know, TENDL's covariances are provided for applications that require covariances, such as perturbation approaches.

@AnderGray
Copy link
Author

AnderGray commented Feb 23, 2021

Hi @vivian-salino,

Thanks for your comment, and for sure using the random endf files is a better option, since it requires no sampling and you use the original files (non-gaussian distribution). But unfortunately the variety of nuclides which are currently available from the TENDL website is quite limited, so I've had to use SANDY for most of the nuclides.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants