Speaker
Description
Contour-based extrapolation of thermodynamic observables to finite chemical potential is known to overcome the shortcomings of Taylor series extrapolation and to extend the reach in the finite density region. Two such schemes are the T-prime expansion, which uses contours of constant baryon density, and a recently proposed scheme using contours of constant entropy. However, a detailed comparison of these schemes has not yet been performed. Using large-statistics data on a $16^3 \times 8$ lattice, we push these expansions to higher orders than those explored in the original works. One of the difficulties in doing so is the accurate computation of higher-order temperature derivatives of the defining observables, namely baryon density and the entropy density. To this end, we employ a Bayesian approach to spline fitting with free knots to obtain the required derivatives. In this talk, we present a systematic comparison of the two schemes to assess their relative performance for future extrapolation studies.