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The HMC Algorithm with Overrelaxation and Adaptive--Step ...

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1.7<br />

1.5<br />

1.3<br />

1.1<br />

0.9<br />

0.7<br />

0.5<br />

Background<br />

Aim of Talk<br />

<strong>The</strong> Hamiltonian Monte Carlo (<strong>HMC</strong>) <strong>Algorithm</strong><br />

Improving Performance of <strong>HMC</strong> <strong>Algorithm</strong><br />

Numerical Experiments & Results<br />

Comparing OSV<strong>HMC</strong> vs SV<strong>HMC</strong><br />

Example results from the improved <strong>HMC</strong> algorithm<br />

Graphical Illustration<br />

Numerical Results (n=64, N=2000)<br />

OSV<strong>HMC</strong> SV<strong>HMC</strong> Ideal<br />

Accept. rate 0.92 0.94 1<br />

P(0) 1.02 1.11 1<br />

κ ∗ 4.15 3.19<br />

CPU time[sec] 639.58 669.40<br />

E 0.98 0.90 1<br />

r 5.1e − 4 5.6e − 4 < 0.01<br />

τ int 0.71 0.94 0.5<br />

N eff 1400 1059 2000<br />

P(κ)<br />

ρ int<br />

(τ)<br />

3.1623<br />

2.5119<br />

1.9953<br />

1.5849<br />

1.2589<br />

1<br />

0.7943<br />

0.631<br />

0.5012<br />

0.3981<br />

0.3162<br />

10 −3 10 −2 10 −1 10 0 10 1<br />

κ<br />

OSV<strong>HMC</strong><br />

SV<strong>HMC</strong><br />

iacf OSV<strong>HMC</strong><br />

(τ,τ int<br />

) OSV<strong>HMC</strong><br />

iacf SV<strong>HMC</strong><br />

(τ*,τ* int<br />

) SV<strong>HMC</strong><br />

0.3<br />

0 1 2 3 4 5 6 7 8<br />

τ<br />

M. Alfaki, S. Subbey, <strong>and</strong> D. Haugl<strong>and</strong> <strong>The</strong> Hamiltonian Monte Carlo (<strong>HMC</strong>) <strong>Algorithm</strong>

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