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Le Chen

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Publications associées (7)

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We consider nonlinear parabolic stochastic PDEs on a bounded Lipschitz domain driven by a Gaussian noise that is white in time and colored in space, with Dirichlet or Neumann boundary condition. We establish existence, uniqueness and moment bounds of the r ...

New York2023

Moment bounds and asymptotics for the stochastic wave equation

Robert Dalang, Le Chen

We consider the stochastic wave equation on the real line driven by space time white noise and with irregular initial data. We give bounds on higher moments and, for the hyperbolic Anderson model, explicit formulas for second moments. These bounds imply we ...

Elsevier Science Bv2015

We study the nonlinear stochastic heat equation in the spatial domain R, driven by space-time white noise. A central special case is the parabolic Anderson model. The initial condition is taken to be a measure on R, such as the Dirac delta function, but th ...

Inst Mathematical Statistics2015

BiVO4 thin film photoanodes grown by chemical vapor deposition

Esther Alarcon Llado, Le Chen

BiVO4 thin film photoanodes were grown by vapor transport chemical deposition on FTO/glass substrates. By controlling the flow rate, the temperatures of the Bi and V sources (Bi metal and V2O5 powder, respectively), and the temperature of the deposition zo ...

Royal Soc Chemistry2014

Moments, Intermittency, and Growth Indices for Nonlinear Stochastic PDE's with Rough Initial Conditions

Le Chen

In this thesis, we study several stochastic partial differential equations (SPDE’s) in the spatial domain R, driven by multiplicative space-time white noise. We are interested in how rough and unbounded initial data affect the random field solution and the ...

EPFL2013

Bismuth vanadate (BiVO4) has attracted increasing attention as a photoanode for photoelectrochemical (PEC) water splitting. It has a band gap in the visible light range (2.4-2.5 eV) and a valence band position suitable for driving water oxidation under ill ...

Amer Chemical Soc2013

In this report, we propose a statistical model to deal with the discrete-distribution data varying over time. The proposed model -- HMM+DM -- extends the Dirichlet mixture model to the dynamic case: Hidden Markov Model with Dirichlet mixture output. Both t ...

IDIAP2007