SU(2) torelon correlator data ------------------------------------ Improved anisotropic action: beta = 3.4000 anisotropy a_s / a_t = 4.0000 input u_t = 1.0000 input u_s = 0.9260 Individual term couplings: spatial plaquette 1.9267 temporal plaquette 21.1473 spatial 2x1 rectangle -0.1123 2s x 1t rectangle -1.5414 2t x 1s rectangle 0.0000 Lattice size (32 x 8) x 112 ------------------------------------ Configuration updating parameters: number of bins 1440 number of measurements per bin 30 number of updates between measurements 30 number of Cabibbo-Marinari sweeps per update 1 number of over-relaxation sweeps per update 6 ------------------------------------ APE fuzzing parameters: Smearing scheme: alpha = 0.1500 initial fuzzing levels = 3 increment in fuzzing levels = 3 number of fuzzings = 6 ------------------------------------ CORRELATOR information: Maximum time separation measured 15 Number of torelon momenta to use 6 (px,py) = ( 0, 0 ) (px,py) = ( 1, 0 ) (px,py) = ( 2, 0 ) (px,py) = ( 3, 0 ) (px,py) = ( 4, 0 ) (px,py) = ( 5, 0 ) Optimized on time slices 1/0 ------------------------------------ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (px,py)=(0,0) FIT RESULTS tmin tmax chisq/dof Q energy 2 10 1.35 0.22 0.22343(54) Energy: ------- best = 0.22343475 plus_error = 0.00053230 minus_error = -0.00053997 boot_avg = 0.22343933 boot_med = 0.22345769 boot_upp = 0.22396705 boot_low = 0.22289479 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (px,py)=(1,0) FIT RESULTS tmin tmax chisq/dof Q energy 2 10 0.53 0.82 0.22808(39) Energy: ------- best = 0.22808098 plus_error = 0.00038576 minus_error = -0.00038888 boot_avg = 0.22807834 boot_med = 0.22808712 boot_upp = 0.22846673 boot_low = 0.22769210 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (px,py)=(2,0) FIT RESULTS tmin tmax chisq/dof Q energy 2 10 1.44 0.19 0.24558(42) Energy: ------- best = 0.24557787 plus_error = 0.00040728 minus_error = -0.00042673 boot_avg = 0.24556953 boot_med = 0.24557894 boot_upp = 0.24598515 boot_low = 0.24515113 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (px,py)=(3,0) FIT RESULTS tmin tmax chisq/dof Q energy 2 10 0.49 0.84 0.27047(47) Energy: ------- best = 0.27047252 plus_error = 0.00046921 minus_error = -0.00046615 boot_avg = 0.27047780 boot_med = 0.27046589 boot_upp = 0.27094173 boot_low = 0.27000636 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (px,py)=(4,0) FIT RESULTS tmin tmax chisq/dof Q energy 2 10 0.73 0.65 0.30217(53) Energy: ------- best = 0.30216614 plus_error = 0.00051313 minus_error = -0.00055553 boot_avg = 0.30214096 boot_med = 0.30213527 boot_upp = 0.30267928 boot_low = 0.30161061 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (px,py)=(5,0) FIT RESULTS tmin tmax chisq/dof Q energy 2 10 0.91 0.50 0.33793(65) Energy: ------- best = 0.33793449 plus_error = 0.00069548 minus_error = -0.00060267 boot_avg = 0.33797009 boot_med = 0.33795687 boot_upp = 0.33862997 boot_low = 0.33733182 ################################################################### Computation of the Renormalization of the Anisotropy ---------------------------------------------------- Continuum dispersion relation Correlators fit using 1 exponential(s) Momenta orientations included in fit: (px,py) t_start t_stop (0,0) 2 10 (1,0) 2 10 (2,0) 2 10 (3,0) 2 10 (4,0) 2 10 (5,0) 2 10 Chi-square per degree of freedom = 0.988714 Goodness of fit Q = 0.493892 Z_xi = 0.9642(28) Z_xi: ---- best = 0.96416764 plus_error = 0.00302480 minus_error = -0.00266462 boot_avg = 0.96441005 boot_med = 0.96447551 boot_upp = 0.96719244 boot_low = 0.96150302 1/Z_xi = 1.0372(31) 1 / Z_xi: -------- best = 1.03716404 plus_error = 0.00286519 minus_error = -0.00324686 boot_avg = 1.03691227 boot_med = 1.03683296 boot_upp = 1.04002922 boot_low = 1.03391718 E_0 = 0.13689(52) E_0: --- best = 0.13688604 plus_error = 0.00053997 minus_error = -0.00049428 boot_avg = 0.13692296 boot_med = 0.13693017 boot_upp = 0.13742600 boot_low = 0.13639176 Some details of the other fit parameters: ---------------------------------------- (px,py) a_t E(px,py) (0,0) 0.22301(28) (1,0) 0.22875(26) (2,0) 0.24516(20) (3,0) 0.27030(21) (4,0) 0.30200(33) (5,0) 0.33843(47)