Accurate dynamics from self-consistent memory in stochastic chemical reactions with small copy numbers
From MaRDI portal
Publication:6063359
DOI10.1088/1751-8121/acfd6azbMath1526.92062arXiv2303.00029OpenAlexW4387041071MaRDI QIDQ6063359
Publication date: 7 November 2023
Published in: Journal of Physics A: Mathematical and Theoretical (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2303.00029
path integralchemical reactionsout of equilibrium dynamicsmemorydemographic noiseDoi-Peliti field theorynon equilibrium statistical physics
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Path integral methods for stochastic differential equations
- Solving the chemical master equation for monomolecular reaction systems analytically
- Strong approximation theorems for density dependent Markov chains
- Solving the chemical master equation for monomolecular reaction systems and beyond: a Doi-Peliti path integral view
- Memory effects in biochemical networks as the natural counterpart of extrinsic noise
- System size expansion using Feynman rules and diagrams
- Path integral methods for the dynamics of stochastic and disordered systems
- Approximation and inference methods for stochastic biochemical kinetics—a tutorial review
- Inference for dynamics of continuous variables: the extended Plefka expansion with hidden nodes
- Critical scaling in hidden state inference for linear Langevin dynamics
- Effective action for composite operators
- Two Langevin equations in the Doi–Peliti formalism
- Conservation Laws and Correlation Functions
- Solving moment hierarchies for chemical reaction networks
- Applications of field-theoretic renormalization group methods to reaction–diffusion problems
- WKB theory of large deviations in stochastic populations
- Stochastic approach to chemical kinetics
- Brownian motion in a field of force and the diffusion model of chemical reactions
- Particle entity in the Doi–Peliti and response field formalisms
- Reaction diffusion systems and extensions of quantum stochastic processes