Skip to content
DraconiticResearch
Search Sources API
194,164 studies31 sourcesUpdated 18 min ago
PreprintarXiv licencearXiv

Last-Coverage Probabilities of Random Walks on Cycle Graphs for Symmetric, Biased, and Time-Dependent Walks

Abstract

This paper studies the last-coverage vertex of a nearest-neighbour random walk on a cycle: the vertex most likely to be the final one discovered. We show that the visited vertices always form a single contiguous arc of the ring, a property we call the Connected Arc Property. This lets the walk be replaced by a two-state time-inhomogeneous Markov chain, which we call the interval-expansion representation, in which each expansion step has a probability given by the classical gambler's ruin formula. Within this framework we prove that the last-coverage probability of node k in an n-node cycle is (1-r)r^(n-1-k)/(1-r^(n-1)), where r = (1-p)/p and p is the clockwise transition probability. As p approaches 1/2, we recover the uniform distribution, giving an independent derivation of a classical result. For a walk with a deterministic time-varying bias, we give an exact series representation for the last-coverage probabilities, together with a finite truncation that serves as a computable, error-bounded approximation. All results are validated by Monte Carlo simulation, and we run experiments on sinusoidal time-varying bias. Finally, we compare generalized Petersen graphs with Erdos-Renyi graphs of matching size, finding that structural symmetry is associated with more uniform last-coverage distributions.

Related

  1. Subgraph probabilities in random intersection graphs
    Katarzyna Rybarczyk, Grzegorz Serafin
    arXivPreprintCC BY 4.0Full textCombinatorics & discrete mathematicsarXiv
  2. Stochastic Heterogeneous SIR Model with Infection-Age Dependent Infectivity on Large Random Graphs
    Guodong Pang, Étienne Pardoux, Aurélien Velleret
    Mathematical Physics, Analysis and GeometryPeer-reviewedCC BY-ND 4.0Full text1 citedProbabilityHAL
  3. Convergence of the critical probabilities for stopping near the top of a random walk
    José Ángel Islas
    arXivPreprintarXiv licenceFull textProbabilityarXiv
  4. Critical branching random walks on ℤ2: local survival probabilities and Yaglom limit theorems
    Tianyi Bai, Xinxin Chen, Shen Lin
    arXivPreprintarXiv licenceFull textProbabilityarXiv
  5. Optimal Average Success Probabilities of Binary (n,n−1) and (n,n−2) Quantum Random Access Codes
    Shuo Tan, Syed A. Jafar
    arXivPreprintCC BY 4.0Full textGeneral mathematicsQuantum physics & quantum informationarXiv
BibTeX
@misc{idnani2026lastcoverage,
  title = {{Last-Coverage Probabilities of Random Walks on Cycle Graphs for Symmetric, Biased, and Time-Dependent Walks}},
  author = {Kiyan Idnani and Jad Salem},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.15115},
  eprint = {2610.15115},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.15115},
}
RIS
TY  - UNPB
TI  - Last-Coverage Probabilities of Random Walks on Cycle Graphs for Symmetric, Biased, and Time-Dependent Walks
AU  - Kiyan Idnani
AU  - Jad Salem
PY  - 2026
DA  - 2026/10/10
PB  - arXiv
DO  - 10.48550/arxiv.2610.15115
UR  - https://arxiv.org/abs/2610.15115
AB  - This paper studies the last-coverage vertex of a nearest-neighbour random walk on a cycle: the vertex most likely to be the final one discovered. We show that the visited vertices always form a single contiguous arc of the ring, a property we call the Connected Arc Property. This lets the walk be replaced by a two-state time-inhomogeneous Markov chain, which we call the interval-expansion representation, in which each expansion step has a probability given by the classical gambler's ruin formula. Within this framework we prove that the last-coverage probability of node k in an n-node cycle is (1-r)r^(n-1-k)/(1-r^(n-1)), where r = (1-p)/p and p is the clockwise transition probability. As p approaches 1/2, we recover the uniform distribution, giving an independent derivation of a classical result. For a walk with a deterministic time-varying bias, we give an exact series representation for the last-coverage probabilities, together with a finite truncation that serves as a computable, error-bounded approximation. All results are validated by Monte Carlo simulation, and we run experiments on sinusoidal time-varying bias. Finally, we compare generalized Petersen graphs with Erdos-Renyi graphs of matching size, finding that structural symmetry is associated with more uniform last-coverage distributions.
ER  -