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I want to set up a model/simulation that involves numerically solving a set of coupled differential equations, but at some point in time I want some of the variables to quickly jump to a constant value for the remainder of the simulation.

More explicitly, the ideal scenario would be that each selected differential equation would look like $$\frac{\text dc}{\text dt} = \begin{cases} f(c,\dots), & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=f(c,\dots), & t

where $$f(c,\dots)$$ is a function of the various dependent variables in the model, $$t_0$$ is the time at which the "switch" needs to occur, and $$c_0$$ is the constant value the variable needs to be set to after the "switch".

Of course, I could just make the differential equation look like $$\frac{\text d c}{\text dt}=H(t_0-t)f(c,\dots)+AH(t-t_0)(c_0-c(t))$$ where $$H$$ is the Heaviside step function and $$A$$ is very large so that $$c$$ moves quickly to $$c_0$$ and the derivative quickly decays to $$0$$ when $$t\geq t_0$$. But I didn't know if there was any good machinery in mathematica that could do this better. I know that step functions aren't always the best when numerically solving differential equations, so I feel like there is a faster and more eloquent way to do this.

As a simple example of a differential equation one could use $$\frac{\text dc}{\text dt} = \begin{cases} -c, & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=-c, & t where the initial condition of $$c(t)$$ is not important. Of course this example doesn't require a numeric solution, but an example was requested in the comments. The reason this all needs to be done in the differential equation solver is because in my actual work other equations will depend on versions of this $$c(t)$$ example.

I want to set up a model/simulation that involves numerically solving a set of coupled differential equations, but at some point in time I want some of the variables to quickly jump to a constant value for the remainder of the simulation.

More explicitly, the ideal scenario would be that each selected differential equation would look like $$\frac{\text dc}{\text dt} = \begin{cases} f(c,\dots), & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=f(c,\dots), & t

where $$f(c,\dots)$$ is a function of the various dependent variables in the model, $$t_0$$ is the time at which the "switch" needs to occur, and $$c_0$$ is the constant value the variable needs to be set to after the "switch".

Of course, I could just make the differential equation look like $$\frac{\text d c}{\text dt}=H(t_0-t)f(c,\dots)+AH(t-t_0)(c_0-c(t))$$ where $$H$$ is the Heaviside step function and $$A$$ is very large so that $$c$$ moves quickly to $$c_0$$ and the derivative quickly decays to $$0$$ when $$t\geq t_0$$. But I didn't know if there was any good machinery in mathematica that could do this better. I know that step functions aren't always the best when numerically solving differential equations, so I feel like there is a faster and more eloquent way to do this.

I want to set up a model/simulation that involves numerically solving a set of coupled differential equations, but at some point in time I want some of the variables to quickly jump to a constant value for the remainder of the simulation.

More explicitly, the ideal scenario would be that each selected differential equation would look like $$\frac{\text dc}{\text dt} = \begin{cases} f(c,\dots), & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=f(c,\dots), & t

where $$f(c,\dots)$$ is a function of the various dependent variables in the model, $$t_0$$ is the time at which the "switch" needs to occur, and $$c_0$$ is the constant value the variable needs to be set to after the "switch".

Of course, I could just make the differential equation look like $$\frac{\text d c}{\text dt}=H(t_0-t)f(c,\dots)+AH(t-t_0)(c_0-c(t))$$ where $$H$$ is the Heaviside step function and $$A$$ is very large so that $$c$$ moves quickly to $$c_0$$ and the derivative quickly decays to $$0$$ when $$t\geq t_0$$. But I didn't know if there was any good machinery in mathematica that could do this better. I know that step functions aren't always the best when numerically solving differential equations, so I feel like there is a faster and more eloquent way to do this.

As a simple example of a differential equation one could use $$\frac{\text dc}{\text dt} = \begin{cases} -c, & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=-c, & t where the initial condition of $$c(t)$$ is not important. Of course this example doesn't require a numeric solution, but an example was requested in the comments. The reason this all needs to be done in the differential equation solver is because in my actual work other equations will depend on versions of this $$c(t)$$ example.

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I want to set up a model/simulation that involves numerically solving a set of coupled differential equations, but at some point in time I want some of the variables to quickly jump to a constant value for the remainder of the simulation.

More explicitly, the ideal scenario would be that each selected differential equation would look like $$\frac{\text dc}{\text dt} = \begin{cases} f(c,\dots), & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=f(c,\dots), & t

where $$f(c,\dots)$$ is a function of the various dependent variables in the model, $$t_0$$ is the time at which the "switch" needs to occur, and $$c_0$$ is the constant value the variable needs to be set to after the "switch".

Of course, I could just make the differential equation look like $$\frac{\text d c}{\text dt}=H(t_0-t)f(c,\dots)+AH(t-t_0)(c_0-c(t))$$ where $$H$$ is the Heaviside step function and $$A$$ is very large so that $$c$$ moves quickly to $$c_0$$ and the derivative quickly decays to $$0$$ when $$t\geq t_0$$. But I didn't know if there was any good machinery in mathematica that could do this better. I know that step functions aren't always the best when numerically solving differential equations, so I feel like there is a faster and more eloquent way to do this.

I want to set up a model/simulation that involves numerically solving a set of differential equations, but at some point in time I want some of the variables to quickly jump to a constant value for the remainder of the simulation.

More explicitly, the ideal scenario would be that each selected differential equation would look like $$\frac{\text dc}{\text dt} = \begin{cases} f(c,\dots), & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=f(c,\dots), & t

where $$f(c,\dots)$$ is a function of the various dependent variables in the model, $$t_0$$ is the time at which the "switch" needs to occur, and $$c_0$$ is the constant value the variable needs to be set to after the "switch".

Of course, I could just make the differential equation look like $$\frac{\text d c}{\text dt}=H(t_0-t)f(c,\dots)+AH(t-t_0)(c_0-c(t))$$ where $$H$$ is the Heaviside step function and $$A$$ is very large so that $$c$$ moves quickly to $$c_0$$ and the derivative quickly decays to $$0$$ when $$t\geq t_0$$. But I didn't know if there was any good machinery in mathematica that could do this better. I know that step functions aren't always the best when numerically solving differential equations, so I feel like there is a faster and more eloquent way to do this.

I want to set up a model/simulation that involves numerically solving a set of coupled differential equations, but at some point in time I want some of the variables to quickly jump to a constant value for the remainder of the simulation.

More explicitly, the ideal scenario would be that each selected differential equation would look like $$\frac{\text dc}{\text dt} = \begin{cases} f(c,\dots), & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=f(c,\dots), & t

where $$f(c,\dots)$$ is a function of the various dependent variables in the model, $$t_0$$ is the time at which the "switch" needs to occur, and $$c_0$$ is the constant value the variable needs to be set to after the "switch".

Of course, I could just make the differential equation look like $$\frac{\text d c}{\text dt}=H(t_0-t)f(c,\dots)+AH(t-t_0)(c_0-c(t))$$ where $$H$$ is the Heaviside step function and $$A$$ is very large so that $$c$$ moves quickly to $$c_0$$ and the derivative quickly decays to $$0$$ when $$t\geq t_0$$. But I didn't know if there was any good machinery in mathematica that could do this better. I know that step functions aren't always the best when numerically solving differential equations, so I feel like there is a faster and more eloquent way to do this.

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# Implicit piece-wise function in derivative for differential equation solver

I want to set up a model/simulation that involves numerically solving a set of differential equations, but at some point in time I want some of the variables to quickly jump to a constant value for the remainder of the simulation.

More explicitly, the ideal scenario would be that each selected differential equation would look like $$\frac{\text dc}{\text dt} = \begin{cases} f(c,\dots), & t

and the function $$c(t)$$ would look like $$c(t)= \begin{cases} \text{solution to }\frac{\text dc}{\text dt}=f(c,\dots), & t

where $$f(c,\dots)$$ is a function of the various dependent variables in the model, $$t_0$$ is the time at which the "switch" needs to occur, and $$c_0$$ is the constant value the variable needs to be set to after the "switch".

Of course, I could just make the differential equation look like $$\frac{\text d c}{\text dt}=H(t_0-t)f(c,\dots)+AH(t-t_0)(c_0-c(t))$$ where $$H$$ is the Heaviside step function and $$A$$ is very large so that $$c$$ moves quickly to $$c_0$$ and the derivative quickly decays to $$0$$ when $$t\geq t_0$$. But I didn't know if there was any good machinery in mathematica that could do this better. I know that step functions aren't always the best when numerically solving differential equations, so I feel like there is a faster and more eloquent way to do this.