26.2 g1600 hadron
first we read the header
= file("../g1600/G2t_T64_L20_msq0-1.160000_msq1-0.700000_l00.000000_l10.000000_mu0.000000_g1600.000000_rep0_bin1000_merged_bin100", "rb")
to.read if(!exists("foo", mode="function")) source("read_header.R")
<-read_header(to.read) header
## Warning in readChar(to.read, nchars = 100, useBytes = 100): truncating string
## with embedded nuls
#header
26.2.1 Reading the configuration
We read the configuration from the file in to the three dimensional array d[correlator, time, configuration]
<- list()
configurations <-array(dim = c(header$ncorr, header$L[1], header$confs) )
d
for (iconf in c(1:header$confs)){
<-append(configurations, readBin(to.read, integer(),n = 1, endian = "little"))
configurationsfor(t in c(1:header$L[1] ) ){
for (corr in c(1:header$ncorr)){
<-readBin(to.read, double(),n = 1, endian = "little")
d[corr, t, iconf]
}
} }
26.2.2 GEVP
first we define the correlator number that correspond to the correlator we want in the GEVP
###########
<-0+1 # <phi0 phi0 >
n_00<-129+1 # <phi0^3 phi0 >
n_01<-127+1 # <phi0 phi1 >
n_02
<-5+1 # <phi0^3 phi0^3 >
n_11<-128+1 # <phi0^3 phi1 >
n_12
<-1+1 # <phi1 phi1 >
n_22#######
<-188+1 # <phi0 phi0^2phi1 >
n_03<-189+1 # <phi0^3 phi0^2phi1 >
n_13<-190+1 # <phi1^3 phi0^2phi1 >
n_23<-187+1 # <phi0^2phi1 phi0^2phi1 > n_33
with the above correlator we build the GEVP between the operators \(\phi_0\), \(\phi_0^3\) and \(\phi_1\)
<- cf()
mycffor (n in c(n_00,n_01,n_02,
n_01,n_11,n_12,
n_02,n_12,n_22)){
# for (n in c(
# n_11,n_12,
# n_12,n_22)){
<- cf_meta(nrObs =1, Time = header$L[1], nrStypes = 1)
cf_tmp <- cf_orig(cf_tmp, cf = t(d[n, ,]))
cf_tmp <- symmetrise.cf(cf_tmp, sym.vec = c(1))
cf_tmp <- c(mycf, cf_tmp)
mycf
}# Bootstrap cf
<- 150
boot.R <- 1
boot.l <- 1433567
seed <- bootstrap.cf(cf=mycf, boot.R=boot.R, boot.l=boot.l, seed=seed) cfb
26.2.3 Effective mass
<- extractSingleCor.cf(cf=cfb, id=1)
cor1 <- bootstrap.effectivemass(cf=cor1)
cor1.effmass <- extractSingleCor.cf(cf=cfb, id=5)
cor2 <- bootstrap.effectivemass(cf=cor2)
cor2.effmass <- extractSingleCor.cf(cf=cfb, id=9)
cor3 <- bootstrap.effectivemass(cf=cor3)
cor3.effmass plot(cor1.effmass, ylab="a Meff", xlab="t/a", xlim=c(0,20),ylim=c(0,0.2))
plot(cor2.effmass, rep=TRUE, col="red")
plot(cor3.effmass, rep=TRUE, col="blue")
26.2.4 correlators
<- extractSingleCor.cf(cf=cfb, id=1)
cor1 #cor1.effmass <- bootstrap.effectivemass(cf=cor1)
<- extractSingleCor.cf(cf=cfb, id=5)
cor2 # cor2.effmass <- bootstrap.effectivemass(cf=cor2)
<- extractSingleCor.cf(cf=cfb, id=9)
cor3 # cor3.effmass <- bootstrap.effectivemass(cf=cor3)
plot(cor1, ylab="a Meff", xlab="t/a", col="black", xlim=c(0,20),ylim=c(-2e-6,3e-2))
plot(cor2, rep=TRUE, col="red",pch=2)
plot(cor3, rep=TRUE, col="blue",pch=3)