TY - JOUR
T1 - Fast initial conditions for Glauber dynamics
AU - Lubetzky, Eyal
AU - Sly, Allan
N1 - Publisher Copyright:
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2021/11
Y1 - 2021/11
N2 - In the study of Markov chain mixing times, analysis has centered on the performance from a worst-case starting state. Here, in the context of Glauber dynamics for the one-dimensional Ising model, we show how new ideas from information percolation can be used to establish mixing times from other starting states. At high temperatures we show that the alternating initial condition is asymptotically the fastest one, and, surprisingly, its mixing time is faster than at infinite temperature, accelerating as the inverse-temperature β ranges from 0 to β0=12arctanh(13). Moreover, the dominant test function depends on the temperature: at β< β it is autocorrelation, whereas at β> β it is the Hamiltonian.
AB - In the study of Markov chain mixing times, analysis has centered on the performance from a worst-case starting state. Here, in the context of Glauber dynamics for the one-dimensional Ising model, we show how new ideas from information percolation can be used to establish mixing times from other starting states. At high temperatures we show that the alternating initial condition is asymptotically the fastest one, and, surprisingly, its mixing time is faster than at infinite temperature, accelerating as the inverse-temperature β ranges from 0 to β0=12arctanh(13). Moreover, the dominant test function depends on the temperature: at β< β it is autocorrelation, whereas at β> β it is the Hamiltonian.
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U2 - 10.1007/s00440-020-01015-3
DO - 10.1007/s00440-020-01015-3
M3 - Article
AN - SCOPUS:85096389121
SN - 0178-8051
VL - 181
SP - 647
EP - 667
JO - Probability Theory and Related Fields
JF - Probability Theory and Related Fields
IS - 1-3
ER -