Pith. sign in

REVIEW

Mumott -- a Python package for the analysis of multi-modal tensor tomography data

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2504.16446 v1 pith:SBO3ZPHX submitted 2025-04-23 cond-mat.mtrl-sci cond-mat.mes-hallcond-mat.soft

classification cond-mat.mtrl-scicond-mat.mes-hallcond-mat.soft
keywords packagemumotttensortomographyadoptionanalysisavailablecomputational
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Small and wide angle x-ray scattering tensor tomography are powerful methods for studying anisotropic nanostructures in a volume-resolved manner, and are becoming increasingly available to users of synchrotron facilities. The analysis of such experiments requires, however, advanced procedures and algorithms, which creates a barrier for the wider adoption of these techniques. Here, in response to this challenge, we introduce the mumott package. It is written in Python with computationally demanding tasks handled via just-in-time compilation using both CPU and GPU resources. The package is being developed with a focus on usability and extensibility, while achieving a high computational efficiency. Following a short introduction to the common workflow, we review key features, outline the underlying object-oriented framework, and demonstrate the computational performance. By developing the mumott package and making it generally available, we hope to lower the threshold for the adoption of tensor tomography and to make these techniques accessible to a larger research community.

Discussion (0). Continue with ORCID to comment.

Pith tools