[RMCProfile-users] Automated weight optimization function

[Krayzman, Victor L. (Assoc)]

RMCProfile uses numerous data sets and restraints of quite different types. Respectively, the residuals for each type of data set and restraint are calculated in different ways. The procedure of computations of each particular residual is important but has no direct relation to the automated weight optimization. Residuals are positive numbers which go to zero when the calculated data approaches to the experimental one.

You are right in general that RMC minimizes the total residual but to be more precise it employs the Metropolis algorithm which accepts all favorable  moves and also may accept some moves which increase the total residual. The probability of acceptance of those moves depends of the value of total residual gain after a move. So, the global weight rescaling parameter T allows to vary this probability and therefore keep the total percentage of accepted move at desired level.

 Victor Krayzman 

-----Original Message-----
From: rmcprofile-users <rmcprofile-users-bounces at shadow.nd.rl.ac.uk> On Behalf Of Tomas Northam via rmcprofile-users
Sent: Wednesday, January 11, 2023 5:00 AM
To: rmcprofile-users at rmcprofile.org
Cc: Tomas Northam <tom.northam at gmail.com>
Subject: [RMCProfile-users] Automated weight optimization function

Dear all,

I have a question regarding the *Automated weight optimization* function.
Two questions:
1. How does it calculate the residual for each data set? And how is the global weight rescaling parameter T chosen?

2. How does the total residual come into the fitting? I understand that RMC works on a chi minimization procedure, so Ido not understand how the * Automated weight optimization* would affect the final fitting.

Thank you for the help.

Kind regards,
Tom.
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