Overcoming the order barrier in the numerical approximation of stochastic partial differential equations with additive space–time noise

By Arnulf Jentzen, Peter E. Kloeden. Proceedings of the Royal Society A, 2009

155 citations recorded by the source corpus.

Subfields: Atmospheric Science, Control and Systems Engineering, Finance

View Paper: https://www.semanticscholar.org/paper/add001d51f51a01a7d057d1dbce68f327c80779c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Arnulf Jentzen
2. Peter E. Kloeden

In Control and Systems Engineering

1. Arnulf Jentzen
2. Peter E. Kloeden
3. Giuseppe Da Prato
4. M. Roeckner
5. Bixiang Wang
6. Tomás Caraballo
7. Feng-Yu Wang
8. Michael Röckner

In Finance

1. Arnulf Jentzen
2. Peter E. Kloeden
3. M. Roeckner
4. Giuseppe Da Prato
5. Xuerong Mao
6. Sotirios Sabanis
7. Martin Hairer
8. Michael Röckner

Citations in the corpus

• TAYLOR EXPANSIONS OF SOLUTIONS OF STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS WITH ADDITIVE NOISE (2010, methodology): “An idea used in [24] to derive what was called the exponential Euler scheme for the SPDE (1), that has a better convergence rate than hitherto analyzed schemes, can be exploited here.”
• The Numerical Approximation of Stochastic Partial Differential Equations (2009, methodology): “for t ∈ [0 ,T ]. This motivated what is in [ 67 ] called the exponential Euler scheme and given by”
• A mild Itô formula for SPDEs (2010, background): “Therefore, the accelerated exponential Euler approximations (140) can in the case of additive noise be simulated quite efficiently (see Section 3 in [53] and, particularly, see Figure 2 in [55] for details).”