TROPIC: A program for calculating reduced transition probabilities

Measurements of level lifetimes and the extracted transition probabilities are one of the cornerstones of nuclear structure physics. The reduced transition probabilities, $B(\pi \lambda ;J_i\to J_f)$ yield information about the structure, wavefunctions, and matrix elements of excited states connected by electromagnetic transitions in a given nucleus. The arsenal of techniques for measuring lifetimes continues to expand and presently includes a wide range of values from femtoseconds to microseconds. While lifetime measurement techniques vary, the extraction of transition probabilities remains the same. RULER is the program used by the National Nuclear Data Center (NNDC) and ENDSF evaluations, while TRANSNUCLEAR was developed at the University of Cologne and modified by a variety of groups. This paper presents a new program TROPIC (TRansitiOn ProbabIlity Calculator), which is the most modern and efficient way to extract transition probabilities $B\left(\pi \lambda \right)$. TROPIC is a program written in Python 3 with the NumPy and SciPy libraries. This is in line with the advances that ENSDF and NNDC are making in moving away from the 80-character card punch input formats. Several design features were implemented to provide a streamlined process for the user and mitigate drawbacks that were present in other programs. The results from TROPIC have been compared with TRANSNUCLEAR and RULER. The answers are as expected identical, but the investment of input to output time is significantly reduced. TROPIC will be made available for public domain use, along with a user guide and example files.

Program summary

Program Title: TROPIC

CPC Library link to program files: https://doi.org/10.17632/958ygp2sb4.1

Developer's repository link: https://github.com/ND-fIREBall/TROPIC

Licensing provisions: GPLv3

Programming language: Python 3

Nature of problem: An efficient way to calculate multiple reduced transition probabilities with minimal effort invested from the user.

Solution method: A Python 3 script has been developed to read in a CSV file containing all necessary input parameters, calculate the transition probabilities listed in the CSV file, and export the results in three different output formats.