quasi_newton() -- optimize atoms with quasi-Newton minimization

edat = <energy_data>		objective function parameters
schedule_scale = <physical.values>	1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1	factors for physical restraint types in scaling the schedule
residue_span_range = <int:2>	0 99999	range of residues spanning the allowed distances; for MAKE_RESTRAINTS, PICK_RESTRAINTS, non-bonded dynamic pairs
max_iterations = <int:1>	200	maximal iterations in optimization
output = <str:1>	'LONG'	'NO_REPORT' | 'REPORT'
min_atom_shift = <float:1>	0.010	minimal atomic shift for the optimization convergence test
actions = []		list of periodic actions

Output:

molpdf

Requirements:

restraints

This functions in a very similar way to conjugate_gradients(), but uses a variable metric (quasi-Newton) method instead to find the minimum. The algorithm implemented in MODELLER is the BFGS or Broyden-Fletcher-Goldfarb-Shanno method [Press et al., 1992].