Extremal statistics for first-passage trajectories of drifted Brownian motion under stochastic resetting

We study the extreme value statistics of first-passage trajectories generated from a one-dimensional drifted Brownian motion subject to stochastic resetting to the starting point with a constant rate r . Each stochastic trajectory starts from a positive position x 0 and terminates whenever the particle hits the origin for the first time. We obtain an exact expression for the marginal distribution <?CDATA Pᵣ(M|x₀)?> P r ( M | x 0 ) of the maximum displacement M . We find that stochastic resetting has a profound impact on <?CDATA Pᵣ(M|x₀)?> P r ( M | x 0 ) and the expected value <?CDATA M?> ⟨ M ⟩ of M . Depending on the drift velocity v , <?CDATA M?> ⟨ M ⟩ shows three distinct trends of change with r . For <?CDATA v x2A7E 0?> v ⩾ 0 , <?CDATA M?> ⟨ M ⟩ decreases monotonically with r , and tends to <?CDATA 2x₀?> 2 x 0 as <?CDATA r → ∞?> r → ∞ . For <?CDATA vc< v<0?> v c < v < 0 , <?CDATA M?> ⟨ M ⟩ shows a nonmonotonic dependence on r , in which a minimum <?CDATA M?> ⟨ M ⟩ exists for an intermediate level of r . For <?CDATA vx2A7D vc?> v ⩽ v c , <?CDATA M?> ⟨ M ⟩ increases monotonically with r . Moreover, by deriving the propagator and using a path decomposition technique, we obtain, in the Laplace domain, the joint distribution of M and the time t m at which the maximum M is reached. Interestingly, the dependence of the expected value <?CDATA tₘ?> ⟨ t m ⟩ of t m on r is either monotonic or nonmonotonic, depending on the value of v . For <?CDATA v> vₘ?> v > v m , there is a nonzero resetting rate at which <?CDATA tₘ?> ⟨ t m ⟩ attains its minimum. Otherwise, <?CDATA tₘ?> ⟨ t m ⟩ increases monotonically with r . We provide an analytical determination of two critical values of v , <?CDATA vc≈ -1.694\,15 D/x₀?> v c ≈ − 1.694 15 D / x 0 and <?CDATA vₘ≈ -1.661\,02 D/x₀?> v m ≈ − 1.661 02 D / x 0 , where D is the diffusion constant. Finally, numerical simulations are performed to support our theoretical results.