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    IB Math AIHL
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    Differential Equations
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    Differential Equations

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    Solving Differential Equations

    2 skills
    Separable Variables
    AHL AI 5.14

    When you have a differential equation in the form

    dxdy​=f(x)g(y)🚫

    you can bring all the y's to one side and all the x's to the other:

    g(y)1​dy=f(x)dx🚫
    ∫g(y)1​dy=∫f(x)dx🚫


    Watch video explanation →
    Particular Solutions
    AHL AI 5.14

    The solutions to differential equations will usually contain a constant of integration +C. These are called general solutions.


    Often, we are given an initial condition, ie the value of y for a specific x, which we can use to solve for C. The result is the particular solution.

    Watch video explanation →

    Euler's Method

    1 skill
    Performing Euler's Method
    AHL AI 5.16

    Mathematically Euler's Method works as follows:

    1. Start at a known point (x0​,y0​)

    2. Pick a step size h such that x0​+nh=xfinal​ for some integer n.

    Repeat the following steps for each n until the desired x-value is reached:

    1. Find the slope dxdy​=f(xn​,yn​)

    2. Find the next x value xn+1​=xn​+h📖.

    3. Find the next y-value yn+1​=yn​+h×f(xn​,yn​)📖

    Watch video explanation →

    Coupled systems

    6 skills
    Coupled systems of differential equations
    AHL AI 5.17

    A system of differential equations is said to be coupled if the variables and their derivatives are interrelated, meaning knowledge of one variable depends on knowledge of another.


    Coupled systems of differential equations can be written in the form

    dtdx​=f1​(x,y,t),dtdy​=f2​(x,y,t)
    Euler's method for coupled systems
    AHL AI 5.17

    Let a coupled system of differential equations be given by the formulas

    dtdx​=f1​(x,y,t),dtdy​=f2​(x,y,t)


    We can use Euler's method to find how the x and y values change when t moves in steps of size h by using the equations:

    tn+1​xn+1​yn+1​​=tn​+h=xn​+hf1​(xn​,yn​,tn​)=yn​+hf2​(xn​,yn​,tn​)​
    Finding eigenvector solutions of linear systems
    AHL AI 5.17

    If a coupled system of differential equations involves strictly linear equations of x and y, i.e. is of the form

    ⎩⎪⎪⎨⎪⎪⎧​dtdx​=ax+bydtdy​=cx+dy​

    for real numbers a,b,c, and d, then the system can be written in matrix form as

    (x˙y˙​​)=M(xy​),M=(ac​bd​)


    If M has real and distinct eigenvalues λ1​ and λ2​ that produce the corresponding eigenvectors p1​ and p2​, the general solution of the system is given by

    (xy​)=Aeλ1​tp1​+Beλ2​tp2​
    Stable, unstable and saddle points
    AHL AI 5.17

    If as t increases the solution curves move

    • all towards the equilibrium point, then the point is stable

    • all away from the equilibrium point, then the point is unstable

    • some towards and some away from the equilibrium point, then the point is a saddle point

    Phase portraits for real distinct eigenvalues
    AHL AI 5.17

    For a coupled system whose matrix M has real and distinct eigenvalues, the phase portrait will have stream lines that approach the direction of the eigenvector with the larger eigenvalue. The process for sketching is as follows:

    1. Draw the eigenvectors as straight lines through the origin (or other equilibrium point)

    2. Consider which case the eigenvalues satisfy:

      <ul>
<li>The figure has three side-by-side panels, each with a black background, orange headings, orange straight lines through the origin, and purple curved streamlines with arrowheads.</li>
<li>Panel titles (left to right): “λ1 &gt; λ2 &gt; 0”, “λ1 &gt; 0 &gt; λ2”, “0 &gt; λ1 &gt; λ2”.</li>
<li>In each panel, two orange rays labeled v1 and v2 pass through the origin at different angles; they form the only straight lines in the diagrams.</li>
<li>Purple trajectories curve around these lines and include small directional arrows indicating flow along the curves.</li>
<li>Left panel (λ1 &gt; λ2 &gt; 0): arrows on the purple curves point away from the origin; many curves bend to become nearly parallel to the v1 direction, while others pass near and bend away from the v2 line.</li>
<li>Middle panel (λ1 &gt; 0 &gt; λ2): trajectories show arrows both approaching and leaving the origin; some curves align with v2 near the origin and bend to align with v1 farther out.</li>
<li>Right panel (0 &gt; λ1 &gt; λ2): arrows on the purple curves point toward the origin; curves far from the origin tend to align with v2, and near the origin several curves run close to the v1 line; small white tags mark v1 and v2 labels on the orange rays.</li>
</ul>
      • The sign of the eigenvalues determines whether we have an unstable node, stable node or saddle point.

      • The solution curves start in the direction of v2​, the eigenvector with the smaller eigenvalue, and end in the direction of v1​ with the larger eigenvalue.

    3. Draw at least one solution curve in each quadrant generated by the intersecting eigenvectors.

    Phase portraits for complex eigenvalues
    AHL AI 5.17

    When the eigenvalues of a coupled system are complex, say

    λ=a±bi,

    the solution curves follow 3 possible shapes in a phase portrait:

    <ul>
<li>Three side-by-side phase portraits on a black background, separated by vertical borders; no axes or grid.</li>
<li>Each panel shows purple trajectories with small arrowheads marking flow direction.</li>
<li>Left panel (labeled “a &gt; 0” in orange): a multi-turn spiral centered near the middle whose radius increases as it winds outward.</li>
<li>Middle panel (labeled “a = 0”): two nested, tilted closed orbits with elliptical shape.</li>
<li>Right panel (labeled “a &lt; 0”): a multi-turn spiral centered near the middle whose radius decreases as it winds inward.</li>
</ul>

    a>0: an unstable spiral,

    a=0: an ellipse,

    a<0: a stable spiral.

    Once the shape is known, we can determine whether the trajectories are clockwise or counterclockwise by evaluating dtdx​ at (0,1):

    • dtdx​<0, spiral is counterclockwise

    • dtdx​<0. spiral is clockwise

    This is equivalent to looking at the top right of the matrix:

    ⎩⎪⎪⎨⎪⎪⎧​dtdx​=ax+by dtdy​=cx+dy​⇔x˙=(ac​bd​)x⟹dtdx​=b

    Second Order Differential Equations

    1 skill
    Second order differential equations
    AHL AI 5.18

    A second order differential equation is a differential equation of the form

    dtd2x​=f(x,dtdx​,t)

    To solve these equations, we rewrite it as a system of coupled first order equations. Using the fact that dtd2x​=dtd​(dtdx​) and substituting dtdx​=y,

    ⎩⎪⎨⎪⎧​dtdx​=ydtdy​=f(x,y,t)​


    This equation can be solved with the usual techniques for coupled systems. On exams, questions involving second-order differential equations are usually set in a real-world context such as movement.