## ./

# poten_tree.pro

## Routines

`result = poten_tree(pos, mass [, theta=theta])`

This function computes the potential energy of a mass distribution.

`test`

`test2`

`test3`

## Routine details

## toppoten_tree

`result = poten_tree(pos, mass [, theta=theta])`

This function computes the potential energy of a mass distribution. It uses a divide and conquer algorithm based on the Barnes-Hut algorithm, and scales as N(log(N)). The poten_slow program is more accurate, but scales as N^2. Generally, this procedure will calculate energies accurate to 1%

### Return value

The potential energy of the system. It is assumed that G=1, so that PE = sum_i (sum j > i (m_i * m_j / r_ij) )

### Parameters

- pos in required
A [3, n] array of 3D particle locations

- mass in required
A n element vector of masses

### Keywords

- theta in optional
A precision pramater which controls the algorithm. Higher values translate to faster run time and larger errors. A value of 1 is recommended, and usually achieves 1% accuracy. A value of 1.5 achieves 1% accuracy for >100 evenly distributed particles. Default is 1

## toptest

`test`

## toptest2

`test2`

## toptest3

`test3`

## File attributes

Modifcation date: | Mon Jul 26 19:29:01 2010 |

Lines: | 163 |