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Jianglun Wu

Publications and source records attributed to Jianglun Wu.

3 recordsLinked to original sources

Disorder Thresholds and Free Energy of Brownian Directed Polymers with Product and Radial Spatial Correlations

We study a Brownian directed polymer in a centered Gaussian environment that is white in time and colored in space having long-range spatial correlations. For product-type covariances \(Q(x)\asymp\prod_{j=1}^d(1+|x_j|)^{-α_j}\), with \(α_j\in(0,1)\) and \(κ=\sum_jα_j\), we identify the disorder transition at the marginal value \(κ=2\). For \(κ>2\), weak disorder holds at sufficiently small inverse temperature; for \(κ<2\), the quenched free energy $p(β)$ satisfies \(-p(β)\asympβ^{4/(2-κ)}\) as \(β\downarrow0\). For \(κ=2\), strong disorder holds for every \(β>0\), while \(p(β)=0\) for all sufficiently small \(β\), so \(β_c=0<\barβ_c\). We also consider the radial covariance cases, where $ Q(x)\asymp(1+|x|)^{-\vartheta}$, when \(d\ge3,\vartheta=2\) and \(d=2,\vartheta\ge2\), which was left unanswered in Lacoin~\cite{Lacoin2011}. When $d=2$, we get \(\ln(-p(β))\asymp-β^{-2}\) for \(\vartheta>2\) and \(\ln(-p(β))\asymp-β^{-1}\) for \(\vartheta=2\). The proofs consist of replica coupling, Feynman--Kac variational formula, overlap methods, and continuous-space fractional moments with ordered Wiener-chaos changes of measure.

math.PR

Least squares estimator for path-dependent McKean-Vlasov SDEs via discrete-time observations

In this paper, we are interested in least squares estimator for a class of path-dependent McKean-Vlasov stochastic differential equations (SDEs). More precisely, we investigate the consistency and asymptotic distribution of the least squares estimator for the unknown pa- rameters involved by establishing an appropriate contrast function. Comparing to the existing results in the literature, the innovations of our paper lie in three aspects: (i) We adopt a tamed Euler-Maruyama algorithm to establish the contrast function under the monotone condition, under which the Euler-Maruyama scheme no longer works; (ii) We take the advantage of linear interpolation with respect to the discrete-time observations to approximate the functional solu- tion; (iii) Our model is more applicable and practice as we are dealing with SDEs with irregular coefficients (e.g., H"older continuous) and path-distribution dependent.

math.PR

On the path-independence of the Girsanov transformation for stochastic evolution equations with jumps in Hilbert spaces

Based on a recent result on characterising the path-independence of the Girsanov transformation for non-Lipschnitz stochastic differential equations (SDEs) with jumps on $R^d$, in this paper, we extend our consideration of characterising the path-indpendent property from finite-dimensional SDEs with jumps to stochastic evolution equations with jumps in Hilbert spaces. This is done via Galerkin type finite-dimensional approximations of the infinite-dimensional stochastic evolution equations with jumps in the manner that one could then link the characterisation of the path-independence for finite-dimensional jump type SDEs to that for the infinite-dimensional settings. Our result provides an intrinsic link of infinite-dimensional stochastic evolution equations with jumps to infinite-dimensional partial integro-differential equations.

math.PR