5.2. Experimental hyper-nuclei with 2 Lambda

In this tutorial, you will learn how to get experimental data associated to hyper-nuclei.

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Import the libraries that will be employed in this tutorial.

# Import numpy
import numpy as np
# Import matplotlib
import matplotlib.pyplot as plt
# Import nucleardatapy package
import nucleardatapy as nuda

You can simply print out the properties of the nuda’s function that we will use:

# Explore the nucleardatapy module to find the correct attribute
print(dir(nuda.hnuc.setupRE2LExp))

['__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', 'print_latex', 'print_outputs']

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Set the experimental tables for 1-Lambda hyper-nuclei:

tables, tables_lower = nuda.hnuc.re2L_exp_tables()
print('tables:',tables)

tables: ['2013-2L-Ahn']

Select a table:

table2L = '2013-2L-Ahn'

Instantiate hnuc:

hnuc = nuda.hnuc.setupRE2LExp( table = table2L )
hnuc.print_outputs()

- Print output:
   table: 2013-2L-Ahn
   ref: J. K. Ahn, H. Akikawa, S. Aoki, K. Arai, Phys. Rev. C 88, 014003 (2013)
   key: JKAhn:2013
   label: []
   note: write here notes about this table.
   A: [6]
   Z: [2]
   N: [2]
   S: [-2]
   Q: [2]
 symb: ['He']
 be: [6.91]
 be_err: [0.16]
 dbe: [0.67]
 dbe_err: [0.17]