arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2407.00749math.PR
收藏

关于连续状态马尔可夫链混合时间的谱轮廓界的精度研究

On the Precision of the Spectral Profile Bound for the Mixing Time of Continuous State Markov Chains

Elnaz Karimian Sichani, Aaron Smith

AI总结:

本研究拓展有限状态马尔可夫链相关结论,证明连续状态下Chen等人的谱轮廓混合时间界精度达初始密度的log log因子,该结果可作为比较界用于马尔可夫链对比分析。

摘要:

我们研究了Goel等人与Chen等人提出的、针对连续状态空间马尔可夫链$L^2$混合时间的谱轮廓界的精确性。我们证明,Chen等人给出的界的精确性可达初始密度的$\text{log}\text{log}$因子量级。该结果拓展了Kozma的研究发现——Kozma曾针对有限状态空间马尔可夫链,证明了Goel等人提出的原始谱轮廓界的类似结论。Kozma的研究表明,谱轮廓界的精确性可达乘积因子$\text{log}(\text{log}(\boldsymbol{\u03c0}_{\text{min}}))$,其中$\boldsymbol{\u03c0}_{\text{min}}$是平稳分布概率质量函数的最小值。我们讨论了核心发现在马尔可夫链比较中的应用:我们的主要结果可作为比较界,表明当已知链仅存在非谱界时,仍可实现不同链之间的比较。

英文摘要:

We investigate the sharpness of the spectral profile bound presented by Goel et al. and Chen et al. on the $L^{2}$ mixing time of Markov chains on continuous state spaces. We show that the bound provided by Chen et al. is sharp up to a factor of $\log\log$ of the initial density. This result extends the findings of Kozma, which showed the analogous result for the original spectral profile bound of Goel et al. for Markov chains on finite state spaces. Kozma shows that the spectral profile bound is sharp up to a multiplicative factor of $\log(\log(π_{min}))$, where $π_{\min}$ is the smallest value of the probability mass function of the stationary distribution. We discuss the application of our primary finding to the comparison of Markov chains. Our main result can be used as a comparison bound, indicating that it is possible to compare chains even when only non-spectral bounds exist for a known chain.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑