In htis post, I’ll discuss a simulation technique for generating statistically exact jump times when the rate is state-dependent, $\lambda(X_t)$.

My research centers around using mathematics to understand how biological systems function *because* of **randomness**, rather than *in spite* of it.

Within this realm, I have particular interests in

- molecular motors and intracellular transport
- cytoskeletal dynamics
- noise in ligand-receptor signaling

How receptor surface diffusion and cell rotation enhance association rates.
submitted,
2018.

Analysis of non-processive molecular motor transport using renewal reward theory.
accepted, SIAP,
2017.

Complex nearly immotile behavior of microtubule-associated cargos.
submitted,
2017.

MATH-UA.0123-004: Calculus 3

In htis post, I’ll discuss a simulation technique for generating statistically exact jump times when the rate is state-dependent, $\lambda(X_t)$.

I’ll discuss the use of operator splitting as the basis for numerically solving ODEs or PDEs with some concrete examples. Along the way, we’ll stumble into a lot of linear algebra and a teensy bit of Lie theory.

- christopher.miles@cims.nyu.edu
- 251 Mercer Street, New York, NY