Séminaire du LPTMS: Shlomi Reuveni


11:00 - 12:00

LPTMS, salle 201, 2ème étage, Bât 100, Campus d'Orsay
15 Rue Georges Clemenceau, Orsay, 91405

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First Passage Under Restart

Shlomi Reuveni (Department of Systems Biology, Harvard Medical School, Boston)

Stopping a process in its midst—only to start it all over again—may prolong, leave unchanged, or even shorten the time taken for its completion. Among these three possibilities the latter is particularly interesting as it suggests that restart can be used to expedite the completion of complex processes involving strong elements of chance. This turned out to be important in computer science where restart drastically improves performance of randomized algorithms, but is not less relevant to many physical, chemical, and biological processes since restart is inherent to the stochastic Michaelis-Menten reaction scheme and this is ubiquitous throughout the sciences. I will introduce the problem of first passage under restart using the example of simple diffusion, but will then explain why many unknowns compel us to generalize to arbitrary first passage processes and restart mechanisms. This has recently led us to discover universal features of the problem which I will derive and describe, and the framework developed will also serve to make the case for a much required paradigm shift in our understanding of enzymatic catalysis and inhibition at the single-molecule level.

References :

  1. S. Reuveni, M. Urbakh and J. Klafter, Role of Substrate Unbinding in Michaelis–Menten Enzymatic Reactions, PNAS 111 (12), 4391 (2014).
  2. T. Rotbart, S. Reuveni and M. Urbakh, Michaelis-Menten Reaction Scheme as a Unified Approach Towards the Optimal Restart Problem, Phys. Rev. E 92, 060101(R) (2015).
  3. S. Reuveni, Optimal Stochastic Restart Renders Fluctuations in First Passage Times Universal, Phys. Rev. Lett. 116, 170601 (2016).
  4. A. Pal and S. Reuveni, First Passage Under Restart, Phys. Rev. Lett. 118, 030603 (2017).
  5. T. Rotbart, S. Reuveni and M. Urbakh, Single-enzyme approach predicts natural emergence of inhibitor-activator duality, bioRxiv 095562.
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