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Slope Fields - Logistic Growth - 2 dP dt = kP (L - P ) For what values of P is the function kP (L - P ) largest? (a) P =0 (b) P = L (c) P =2L (d) P = L 2

dP kP L P dt P is the function L P largestmath121/Notes/Annotated_Online/... · 2017. 12. 15. · dt = kP (L P): On the slope eld, draw several solutions using di erent initial conditions

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  • Slope Fields - Logistic Growth - 2

    dP

    dt= k P (L− P )

    For what values of P is the function k P (L− P ) largest?

    (a) P = 0

    (b) P = L

    (c) P = 2L

    (d) P =L

    2

  • Slope Fields - Logistic Growth - 3

    Sketch the slope field associated with the differential equation

    dP

    dt= k P (L− P ).

    On the slope field, draw several solutions using different initial conditions.

  • Euler’s Method - 1

    Euler’s Method

    We can extend the idea of a slope field (a visual technique) to Euler’s method (anumerical technique). Euler’s method can be used to produce approximations ofthe curve y(x) that satisfy a particular differential equation. Here is the idea:

    Knowing where you are in x and y, you look at the slope field at yourlocation, set off in that direction for a small distance, look again and adjustyour direction, set off in that direction for a small distance, etc.

  • Euler’s Method - 2

    Algorithmically,

    • Start at a point (xi, yi)

    • Compute the slope there, using the DE dydx

    = f (xi, yi)

    • Follow the slope for a step of ∆x:– xi+1 = xi + ∆x

    – yi+1 = yi +dy

    dx∆x︸ ︷︷ ︸

    ∆y

  • Euler’s Method - 3

    Follow this procedure for the differential equationdy

    dx= x + y with initial con-

    dition y(0) = 0.1. Use ∆x = 0.1.

    x y slope ∆y = slope ·∆x

    0 0.1 0.1 (0.1)(0.1) = 0.01

    0.1 0.11

    0.2

    0.3

    0.4

  • Euler’s Method - 4

    Here is a picture of the slope field fordy

    dx= x + y. On this slope field, sketch

    what you have done in creating the table of values. From the picture, wouldyou say the values for y(x) in your table are over-estimates or under-estimatesof the real y values?

    0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

    −1

    −0.8

    −0.6

    −0.4

    −0.2

    0

    0.2

    0.4

    0.6

    0.8

    1

  • Separation of Variables - 1

    Separation of Variables

    We have now considered both visual and approximate techniques for solving dif-ferential equations, which can be obtained with no calculus. The problem withthose approaches is that they do not result in formulas for the function y that wewant to identify.We (at last!) proceed to calculus-based techniques for finding a formula for y.

    Consider the differential equationdy

    dx= k y.

    Treating dx and dy as separable units, transform the equation so that onlyterms with y are on the left, and only terms with x are on the right.

    Place an integral sign in front of each side.

  • Separation of Variables - 2

    Evaluate the integrals.

    Solve for y.

    The solution gives a family of functions, one for each value of the integrationconstant. k is also a parameter, of course, but it is presumed to be specified in thedifferential equation.

  • Separation of Variables - 3

    As soon as we are given an initial value, say y(0) = 10, the solution becomesunique.Find the specific solution with initial value y(0) = 10.

    If y0 > 0, this function describes exponential growth (k > 0) or decay (k < 0).

  • Separation of Variables - 4

    Use the method of separation of variables to solve the differential equation

    dR

    dx= 2R + 3,

    and find the particular solution for which R(0) = 0.

  • Classifying Differential Equations - 1

    Classifying Differential EquationsFor any differential equation which is separable, we can at least attempt to find asolution using anti-derivatives. For equations which are not separable, we’ll needother techniques. It is important, as a result, to be able to tell the difference!Indicate which of the following differential equations are separable. For thosewhich are separable, set up the appropriate integrals to start solving for y.

    • dydx

    = x2

    • dydx

    =ey

    x

  • Classifying Differential Equations - 2

    • dydx

    = x + y

    • dydx

    = cos(x) cos(y)

  • Classifying Differential Equations - 3

    • dydx

    = cos(xy) A. Separable B. Not separable

    • dydx

    = ex + ey A. Separable B. Not separable

    • dydx

    = e(x+y) A. Separable B. Not separable

  • Classifying Differential Equations - 4

    Note: all the original anti-derivatives we studied in first term are of the formdy

    dx= f (x) and so y = F (x) =

    ∫f (x) dx.

    E.g.dy

    dx= x2

    dy

    dx= x cos(5x)

    dy

    dx=

    x

    1 + x2

    These are all immediately separable.

    The challenge is that most interesting scientific laws expressed in differential equa-tion form aren’t that easy to work with.