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Tejaswi Tripathi

Publications and source records attributed to Tejaswi Tripathi.

4 recordsLinked to original sources

One-point fluctuations for exponential last passage percolation under upper-tail conditioning

We study exponential directed last passage percolation conditioned on the last passage time to a specified macroscopic point being atypically large. We determine the one-point fluctuations throughout two of the three spatial regions arising under this conditioning, as well as on the boundaries between these regions, extending the work of Baik-Cordaro-Tripathi. Depending on the location of the observation point, the limiting fluctuations are governed by the GUE Tracy-Widom distribution, a Gaussian distribution, or the one-spike BBP distribution on the boundaries between these regions. Through the correspondence with tandem queues, our results also describe how an atypically late departure at one customer-station pair affects departure epochs elsewhere in the network.

math.PR

A determinant identity for the sum of contour integral matrices

We derive an identity for the determinant of the sum of two $n\times n$ matrices, $U$ and $M$, whose entries are defined via contour integrals. Specifically, we consider $U(i,j)=\frac{1}{2\pi\mathrm{i}}\oint_{\mathrm{C}} \frac{\prod_{\ell=1}^{i-1} (z-\beta_\ell)}{\prod_{\ell=1}^{j} (z-\beta_\ell)} p_i(z)f_j(z)\mathrm{d} z$ and $M(i,j)= \frac{1}{2\pi \mathrm{i}}\int_{\Gamma} q_i(z)g_j(z) \mathrm{d} z$. Under suitable assumptions on the functions $p,q,f,g$, we show that $\det(U+M)$ can be expressed as a Fredholm determinant $\det(\mathrm{I} +K)$, where $K$ is an integral kernel acting on the contour $\Gamma$. The kernel $K$ depends on a function $H$ that solves a system of integral equations. When $f_i$ and $g_i$ are specialized to certain rational functions depending on two sets of parameters $(\alpha_\ell)_{\ell\in \mathbb{Z}}$ and $(\beta_\ell)_{\ell\in \mathbb{Z}}$, $H$ becomes the characteristic function associated with inhomogeneous directed last passage percolation (DLPP) and inhomogeneous totally asymmetric simple exclusion process (TASEP) models. Furthermore, we obtain an explicit random walk hitting expectation representation of this characteristic function. Our work generalizes a recent identity by Baik, Liao, and Liu (2026), which plays an important role in finding the multipoint distribution formula of the periodic KPZ fixed point. Finally, we demonstrate three applications of our general formulas in integrable probability: a new Fredholm determinant formula for the distribution of the path-to-point last passage time in the inhomogeneous DLPP, an indirect proof of a new path-to-line joint distribution formula in the homogeneous DLPP, and a novel proof of the TASEP path-integral formula previously obtained by Matetski, Quastel, and Remenik (2021).

math.CA

Limiting one-point fluctuations of the geodesic in the directed landscape near the endpoints when the geodesic length goes to infinity

We consider the limiting fluctuations of the geodesic in the directed landscape, conditioning on its length going to infinity. It was shown in \cite{Liu22b,Ganguly-Hegde-Zhang23} that when the directed landscape $\mathcal{L}(0,0;0,1) = L$ becomes large, the geodesic from $(0,0)$ to $(0,1)$ lies in a strip of size $O(L^{-1/4})$ and behaves like a Brownian bridge if we zoom in the strip by a factor of $L^{1/4}$. Moreover, the length along the geodesic with respect to the directed landscape fluctuates of order $O(L^{1/4})$ and its limiting one-point distribution is Gaussian \cite{Liu22b}. In this paper, we further zoom in a smaller neighborhood of the endpoints when $\mathcal{L}(0,0;0,1) = L$ or $\mathcal{L}(0,0;0,1) \ge L$, and show that there is a critical scaling window $L^{-3/2}:L^{-1}:L^{-1/2}$ for the time, geodesic location, and geodesic length, respectively. Within this scaling window, we find a nontrivial limit of the one-point joint distribution of the geodesic location and length as $L\to\infty$. This limiting distribution, if we tune the time parameter to infinity, converges to the joint distribution of two independent Gaussian random variables, which is consistent with the results in \cite{Liu22b}. We also find a surprising connection between this limiting distribution and the one-point distribution of the upper tail field of the KPZ fixed point recently obtained in \cite{Liu-Zhang25}.

math.PR

Conditional exponential directed last passage percolation under a one-point upper large deviation event

Under typical scaling, the last passage time field of the directed last passage percolation model with exponential site distributions converges to the KPZ fixed point. In this paper, we consider an atypical scenario in which the last passage time to a specific site is unusually large, and we explore how the last passage time field changes under this one-point upper large deviation event. We prove a conditional law of large numbers and compute the limiting fluctuations in certain regimes. Our proofs rely on an analysis of explicit multi-point distributions.

math.PR