Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC) method for studying state-to-state dynamics in a wide range of material systems. A MSM contains a list of atomic processes and their rate constants for different states of the system. In many situations, only few of the possible atomic processes are included in the MSM. The use of an incomplete MSM with the KMC method can lead to an error in the dynamics. In this work, we develop an error measure to assess the accuracy of a MSM generated using dynamical basin escape pathway searches. We show that the error associated with an incomplete MSM depends on the rate constants missing from the MSM. A procedure to estimate the missing rate constants ...
We consider a continuous-time, ergodic Markov process on a large continuous or discrete state space...
This paper extends Hodgson's methods to the more familiar and physically realistic class of hid...
We consider a continuous-time Markov process on a large continuous or discrete state space. The proc...
Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC)...
The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials len...
The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials len...
Markov state models (MSMs) and other related kinetic network models are frequently used to study the...
Kinetic Monte Carlo (KMC) models of complex materials and biomolecules are increasingly being constr...
The parameters of a discrete stationary Markov model are transition probabilities between states. Tr...
In calculating the time evolution of an atomic system on diffusive timescales, off-lattice kinetic M...
This section reviews the relation between the continuous dynamics of a molecular system in thermal e...
In many applications one is interested to compute transition probabilities of a Markov chain. This c...
This dissertation deals with four important aspects of model checking Markov chains: the development...
The Markov chain Monte Carlo method is an important tool to estimate the average properties of syste...
This dissertation deals with four important aspects of model checking Markov chains: the development...
We consider a continuous-time, ergodic Markov process on a large continuous or discrete state space...
This paper extends Hodgson's methods to the more familiar and physically realistic class of hid...
We consider a continuous-time Markov process on a large continuous or discrete state space. The proc...
Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC)...
The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials len...
The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials len...
Markov state models (MSMs) and other related kinetic network models are frequently used to study the...
Kinetic Monte Carlo (KMC) models of complex materials and biomolecules are increasingly being constr...
The parameters of a discrete stationary Markov model are transition probabilities between states. Tr...
In calculating the time evolution of an atomic system on diffusive timescales, off-lattice kinetic M...
This section reviews the relation between the continuous dynamics of a molecular system in thermal e...
In many applications one is interested to compute transition probabilities of a Markov chain. This c...
This dissertation deals with four important aspects of model checking Markov chains: the development...
The Markov chain Monte Carlo method is an important tool to estimate the average properties of syste...
This dissertation deals with four important aspects of model checking Markov chains: the development...
We consider a continuous-time, ergodic Markov process on a large continuous or discrete state space...
This paper extends Hodgson's methods to the more familiar and physically realistic class of hid...
We consider a continuous-time Markov process on a large continuous or discrete state space. The proc...