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docs/src/catalyst_applications/nonlinear_solve.md

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(k1,k2), X1 <--> X2
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end
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```
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It has an infinite number of steady states. To make steady state finding possible, information of the system's conserved quantities (here $C=X1+X2$) must be provided. Since these can be computed from system initial conditions (`u0`, i.e. those provided when performing ODE simulations), designating an `u0` is often the best way. There are two ways to do this. First, one can perform [ODE simulation-based steady state finding](@ref), using the initial condition as the initial `u` guess. Alternatively, any conserved quantities can be eliminated when the `NonlinearProblem` is created. This feature is supported by Catalyst's [conservation law finding and elimination feature](@ref network_analysis_deficiency).
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It has an infinite number of steady states. To make steady state finding possible, information of the system's conserved quantities (here $C=X1+X2$) must be provided. Since these can be computed from system initial conditions (`u0`, i.e. those provided when performing ODE simulations), designating an `u0` is often the best way. There are two ways to do this. First, one can perform [ODE simulation-based steady state finding](@ref nonlinear_solve_ode_simulation_based), using the initial condition as the initial `u` guess. Alternatively, any conserved quantities can be eliminated when the `NonlinearProblem` is created. This feature is supported by Catalyst's [conservation law finding and elimination feature](@ref network_analysis_deficiency).
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To eliminate conservation laws we simply provide the `remove_conserved = true` argument to `NonlinearProblem`:
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```@example nonlinear_solve2
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If you use this functionality in your research, [in addition to Catalyst](@ref catalyst_citation), please cite the following papers to support the authors of the NonlinearSolve.jl package:
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```
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A NonlinearSolve. jl-related publication is in preparation, once it is available, its details will be added here.
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```
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```

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