Description Usage Arguments Details Value Author(s) See Also
determines pion mass and pcac mass from online measured correlator of the HMC code
1 2 3 4 
data 
data to be fitted to as e.g. the output of

t1 
lower bound for the fitrange in time (t1,t2). Counting starts with 0. 
t2 
upper bound for the fitrange in time (t1,t2). Counting starts with 0. 
stat_range 
range of data to be included in the analysis. 
S 
passed to 
pl 
logical: if set to TRUE the function produces plots 
skip 
number of measurements to be discarded at the beginning of the
time series. 
iobs 
if there are several operators available (locallocal, localsmeared, etc.), then this labels these (for cmi format) 
ind.vec 
index vector indexing the column numbers in cmicor to be used 
mu 
twisted mass parameter. 
kappa 
hopping parameter. 
boot.R 
number of bootstrap samples for bootstrap analysis 
boot.l 
average block size for blocking analysis with tsboot 
tsboot.sim 
The type of simulation required to generate the replicate
time series. See 
method 
the type of error analysis to be used. Can be either “uwerr”, “boot”, “all” or “no”. For “no” (or any other string) no error analysis is performed. This might be helpful for a first impression and also to test different initial values for the fitting parameters. The latter is in particular needed for more than one state in the fit. 
fit.routine 
The fit routine to be used. Default is “gsl”, which uses the gnu scientific library “gsl_multifit_fdfsolver” solver to minimise the chisquare. All other values lead to the usage of R's optim function. The latter choice might be significantly slower. 
nrep 
vector (N1, N2, ...) of replica length N1, N2. If missing it is
assumed that there is only one ensemble. If there are two or more replica
the parameter 
oldnorm 
If set to “TRUE”, the old online measurement normalisation of “tmLQCD” prior to version 5.2.0 is used in order to get correct values for the pion decay constant. 
The online measurements in the HMC code compute the PP and PA correlation functions summed over spatial x for all t. We analyse these correlators in different ways:
First, only the PP correlator is analysed and fitted by p1*p1*cosh(m(tT/2)) for m and p1.
Second, PP and PA correlators are fitted together with three parameters as C_PP = p1*p1*cosh(m(tT/2)) and C_PA = p1*p2*cosh(m(tT/2))C_PA = p1*p2*cosh(m(tT/2)) in a simultaneous fit. m is then the pseudo scalar mass and the pcac mass is determined from
p_1)
Finally, the PCAC mass can also be determined computing
C_PP(t))
(C_PA(t+1)C_PA(t1))/(4 C_PP(t))
using the symmetric finite difference operator.
returns an object of class
ofit
with the following
items
fitresult 
result from the fit as returned by 
fitresultpp 
Fit result of the PP correlator only 
t1 
lower bound for the fitrange in time (t1,t2). Counting starts with 0. 
t2 
upper bound for the fitrange in time (t1,t2). Counting starts with 0. 
N 
number of measurements found in the data 
Time 
Time extent found in the data 
fitdata 

uwerrresultmps 
the
result of the time series analysis for the lowest mass as carried out by

uwerrresultmpcac 
the result of the time series
analysis for the PCAC mass carried out by 
effmass 
effective masses in the pion channel 
matrix.size 
size of the data matrix, copied from input 
boot 
object returned by
the call to 
tsboot 
object returned by the call to

method 
error analysis method as copied from input 
fit.routine 

nrep 

dpaopp 

Carsten Urbach, curbach@gmx.de
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