Update docs/src/model_simulation/finite_state_projection_simulation.md

Co-authored-by: Sam Isaacson <isaacsas@users.noreply.github.com>

Author: TorkelE

docs/src/model_simulation/finite_state_projection_simulation.md

@@ -57,7 +57,7 @@ As previously discussed, [*stochastic chemical kinetics*](@ref math_models_in_ca
 
 One can study the dynamics of stochastic chemical kinetics models by simulating the stochastic processes using Monte Carlo methods. For example, they can be [exactly sampled](@ref simulation_intro_jumps) using [Stochastic Simulation Algorithms](https://en.wikipedia.org/wiki/Gillespie_algorithm) (SSAs), which are also often referred to as Gillespie's method. To gain a good understanding of a system's dynamics, one typically has to carry out a large number of jump process simulations to minimize sampling error. To avoid such sampling error, an alternative approach is to solve ODEs for the *full probability distribution* that these processes have a given value at each time. Knowing this distribution, one can then calculate any statistic of interest that can be sampled via running many SSA simulations.
 
-[*The chemical master equation*](https://en.wikipedia.org/wiki/Master_equation) (CME) describes the time development of this probability distribution[^1], and is given by a (possibly infinite) coupled system of ODEs (with one ODE for each possible chemical state, i.e. number configuration, of the system). For a simple [birth-death model](@ref basic_CRN_library_bd) (`(p,d), 0 <--> X`) the CME looks like
+[*The chemical master equation*](https://en.wikipedia.org/wiki/Master_equation) (CME) describes the time development of this probability distribution[^1], and is given by a (possibly infinite) coupled system of ODEs (with one ODE for each possible chemical state, i.e. number configuration, of the system). For a simple [birth-death model](@ref basic_CRN_library_bd) ($\varnothing \xrightleftharpoons[d]{p} X$) the CME looks like
 ```math
 \begin{aligned}
 \frac{dP(X=0)}{dt} &= d \cdot P(X=1) - p \cdot P(X=0) \\