Coalescence in Markov Chains

Abstract A Markov chain $$X^i$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>X</mml:mi> <mml:mi>i</mml:mi> </mml:msup> </mml:math> on a finite state space S has transition matrix P and initial state i . We may run the chains $$(X^i: i\in S)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:msup> <mml:mi>X</mml:mi> <mml:mi>i</mml:mi> </mml:msup> <mml:mo>:</mml:mo> <mml:mi>i</mml:mi> <mml:mo>∈</mml:mo> <mml:mi>S</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> in parallel, while insisting that any two such chains coalesce whenever they are simultaneously at the same state. There are | S | trajectories which evolve separately, but not necessarily independently, prior to coalescence. What can be said about the number $$k(\mu )$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo>(</mml:mo> <mml:mi>μ</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> of coalescence classes of the process, and what is the set K ( P ) of such numbers $$k(\mu )$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo>(</mml:mo> <mml:mi>μ</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> , as the coupling $$\mu $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> of the chains ranges over couplings that are consistent with P ? We continue earlier work of Grimmett and Holmes (In: In and out of equilibrium 3, Birkhäuser/Springer, Cham, 2021) on these two fundamental questions, which have special importance for the “coupling from the past” algorithm. We concentrate partly on a family of couplings termed block measures, which may be viewed as couplings of lumpable chains with coalescing lumps. Constructions of such couplings are presented and also of non-block measure with similar properties.

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Journal
Journal of Theoretical Probability
Published
2026-05-11
DOI
https://doi.org/10.1007/s10959-026-01500-w
Primary Topic
Markov Chains and Monte Carlo Methods
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article
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article

Coalescence in Markov Chains

Mark J. Holmes, Geoffrey Grimmett
Journal of Theoretical Probability
Markov Chains and Monte Carlo Methods
article

Coalescence in Markov Chains

Mark J. Holmes, Geoffrey Grimmett
article en

Abstract

Abstract A Markov chain $$X^i$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>X</mml:mi> <mml:mi>i</mml:mi> </mml:msup> </mml:math> on a finite state space S has transition matrix P and initial state i . We may run the chains $$(X^i: i\in S)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:msup> <mml:mi>X</mml:mi> <mml:mi>i</mml:mi> </mml:msup> <mml:mo>:</mml:mo> <mml:mi>i</mml:mi> <mml:mo>∈</mml:mo> <mml:mi>S</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> in parallel, while insisting that any two such chains coalesce whenever they are simultaneously at the same state. There are | S | trajectories which evolve separately, but not necessarily independently, prior to coalescence. What can be said about the number $$k(\mu )$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo>(</mml:mo> <mml:mi>μ</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> of coalescence classes of the process, and what is the set K ( P ) of such numbers $$k(\mu )$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo>(</mml:mo> <mml:mi>μ</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> , as the coupling $$\mu $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> of the chains ranges over couplings that are consistent with P ? We continue earlier work of Grimmett and Holmes (In: In and out of equilibrium 3, Birkhäuser/Springer, Cham, 2021) on these two fundamental questions, which have special importance for the “coupling from the past” algorithm. We concentrate partly on a family of couplings termed block measures, which may be viewed as couplings of lumpable chains with coalescing lumps. Constructions of such couplings are presented and also of non-block measure with similar properties.

Journal of Theoretical ProbabilityVol. 39(3)
The University of Melbourne (AU), University of Cambridge (GB)
Openalex Percentile: Top 99%
Markov Chains and Monte Carlo Methods
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Coalescence in Markov Chains — Mark J. Holmes, Geoffrey Grimmett · Journal of Theoretical Probability (2026) | TGRS Research Map | TGRS