Pc18 - Coupled first order equations
When two changing quantities affect one another, their differential equations must be solved together. Pc18 turns a coupled pair of first-order linear equations into one second-order equation, recovers the other variable and applies consistent initial data. You will also interpret population-rate models and explain the long-term behaviour of a coupled system.
Two quantities sharing two rate equations
Two processing compartments contain amounts and of a chemical. Their model is , . If they start at , , can the second amount initially rise even though both amounts eventually settle below their starting values? We will solve the model and find out.
The first rate is not determined by alone; it also depends on . The same is true in reverse. Population models work in a similar way: a species' own growth may be reduced by the presence of a competitor.
Coupled first-order linear equations
A coupled system uses the same independent variable, here time , with dependent variables and influencing the rate equations together. A constant-coefficient first-order linear system has the form
where are constants and are specified functions of time. Terms such as or would make the system non-linear. A dot means differentiation with respect to .
Translate each rate statement separately. Growth proportional to the same population gives a positive self-term; a competitor reducing that growth gives a negative term involving the other population. Do not confuse a rate with the population itself.
Worked example 1: competition and initial rates
Question. In a model, each of two species would grow at a rate times its population per year if alone. Competition reduces the growth rate of species X by and that of species Y by . Form the rate equations and find the initial rates when , .
Plan. Write each independent growth term, subtract its competition term and substitute the starting populations.
Why this step? The competition term involves the other species, not the species whose rate is being calculated.
Answer. The displayed equations model the competition. Initially X increases by animals per year and Y decreases by animal per year.
Check. Without competition the rates would be and . The reductions are and , giving the calculated net rates.
Worked example 2 changes only the initial Y population, from to . Both rate signs reverse even though the model's coefficients are unchanged.
Worked example 2: a different starting balance
Question. For the same model, find the initial rates when , .
Plan. Retain both rate equations and substitute the new initial state.
Why this step? A system's behaviour depends on its starting state as well as its coefficients. A change in one population can change both rates.
Answer. X initially decreases by animals per year and Y increases by animal per year.
Check. Raising by changes by and by , matching the changes from the first example.
These equations are mathematical approximations to competing populations. If a solution later predicts a negative population, it has left the physically meaningful range; do not interpret negative values as actual animals.
Watch out
Wrong: from , conclude that . Right: a negative derivative means the population is decreasing at that instant; the population itself can still be positive.
The next model uses different growth and competition coefficients.
Eliminate one variable, then recover it
Differentiating one first-order equation introduces a second derivative; the other equation then lets you eliminate the unwanted variable.
You already know
A constant-coefficient second-order equation is solved using its auxiliary equation, with a particular integral when the right side is non-zero. The resulting two constants must describe the whole coupled system, not two unrelated solutions.
If the first equation is , with , it also gives a way back to . Keep that rearrangement before differentiating: you will need it both for elimination and for recovery.
Elimination and recovery
From
write
Differentiate the first equation, substitute the given equation for , then substitute this expression for . Solve the resulting second-order equation for , and recover from the original first-order equation. If , use the other equation for elimination when possible, or solve the resulting one-way system in sequence.
Not in the formula booklet: learn it.
Recovering the second variable from an original equation ensures the constants remain linked. It also gives a useful check against the other original equation.
Worked example 3: two distinct exponential modes
Question. Find the general solution of
Plan. Eliminate using , solve for , then recover .
Why this step? Differentiation alone does not eliminate ; both original equations are needed before the second-order equation contains only .
Answer. , .
Check. Differentiating gives , while gives exactly the same expression.
Worked example 4 changes only the coefficient of in the second equation from to . One auxiliary root becomes zero, so the corresponding term is a constant.
Worked example 4: a zero auxiliary root
Question. Find the general solution of , .
Plan. Use the same recovery relation but repeat the elimination with the changed coefficient.
Why this step? A zero root supplies a constant solution mode. Omitting it would leave only one arbitrary constant for a system needing two.
Answer. , .
Check. ; the constant terms cancel.
Under “Show that”, the eliminated differential equation and its auxiliary equation must be visible. Jumping directly to a supplied exponential expression does not establish it.
Exam tip
Show the differentiation, both substitutions and the second-order equation before solving it. After recovery, simplify the expression for the second variable rather than leaving an avoidable unsimplified derivative.
The next system changes the diagonal coefficients as well as the coupling, so repeat the elimination.
Watch out
Wrong: after , take with independent . The original equations link the constants. The correct recovery is , so and .
Use an original equation to recover the second variable with the same constants.
Initial data must describe one shared state
Giving and already determines both initial derivatives through the original equations.
For , , the general solution found above gives
These are two equations for the same two constants. Alternatively, use the original system to calculate , then apply and to the second-order solution.
Key idea
There are two arbitrary constants for the coupled pair as a whole. The recovered must use the same constants as ; it does not introduce two new independent constants.
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