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Define the partial derivatives fx(a,b) and fy(a,b).
For f(x,y), a function of two variables:
fx(a,b)=h→0limhf(a+h,b)−f(a,b),fy(a,b)=h→0limhf(a,b+h)−f(a,b)
(The notes’ second formula has a typo, writing fy(a,h). It means fy(a,b).)
What are the names and alternate notations for partial derivatives?
fx is the partial derivative of f with respect to x, or just the x-derivative of f.
Other notations: ∂x∂f, ∂x∂f(a,b), ∂y∂f, ∂y∂f(a,b).
If z=f(x,y), also write ∂x∂z, ∂y∂z.
How do you compute partial derivatives in practice? Work f(x,y)=x2y5.
To compute fx, treat y as a constant and differentiate with respect to x. To compute fy, treat x as a constant.
Example: fx=2xy5,fy=x2⋅5y4=5x2y4.
Compute ∂x∂q and ∂y∂q for q(x,y)=(1+x2)3y2.
x-derivative (treat y2 as constant, use the chain rule):
∂x∂q=y2∂x∂(1+x2)−3=y2(−3)(1+x2)−4(2x)=−6xy2(1+x2)−4
y-derivative (treat (1+x2)31 as constant):
∂y∂q=(1+x2)31∂y∂(y2)=(1+x2)32y
Compute ∂y∂ln(xy−2y2).
Use the chain rule for ln, treating x as constant:
∂y∂ln(xy−2y2)=xy−2y21⋅∂y∂(xy−2y2)=xy−2y2x−4y
What is the geometric meaning of fx(a,b)?
1-D review: for y=f(x) and the point (a,f(a)) on the graph, f′(a) is the slope of the tangent line to the graph.
2-D: for z=f(x,y) and the point (a,b,f(a,b)) on the graph, set y=b to get the trace curve z=f(x,b).
Then fx(a,b) is the slope of the tangent line to the trace curve.
How are partial derivatives defined for more than two variables? Compute fz(0,0,1,1) for f(x,y,z,w)=z2+wexz+y.
Use a similar limit formula, changing only the variable of interest:
∂z∂f(x,y,z,w)=fz=limh→0hf(x,y,z+h,w)−f(x,y,z,w)
Example: by the quotient rule,
fz=(z2+w)21((z2+w)xexz+y−exz+y(2z))=(z2+w)2xz2+xw−2zexz+y
At (0,0,1,1):
fz(0,0,1,1)=(12+1)2(0+0−2)e0=4−2=−21
What are higher-order partial derivatives, and how are they denoted?
Second-order partials are derivatives of derivatives. For f(x,y) there are 4:
fxx=∂x∂(fx),fyy=∂y∂(fy),fxy=∂y∂(fx),fyx=∂x∂(fy)
Other notations: fxx=∂x2∂2f, fxy=∂y∂x∂2f, fyx=∂x∂y∂2f, fyy=∂y2∂2f.
In subscript notation the first letter is the first derivative taken. In ∂y∂x∂2f the order reads right to left.
Order 3: there are 8 partials, e.g. fxyy=∂y∂(fxy).
Compute all first- and second-order partials of f(x,y)=x3+y2ex.
First order: fx=3x2+y2ex,fy=2yex
Second order:
fxx=∂x∂(fx)=6x+y2ex
fxy=∂y∂(fx)=2yex
fyx=∂x∂(fy)=2yex
fyy=∂y∂(fy)=2ex
Note fxy=fyx. This is not a coincidence (see Clairaut’s Theorem).
State Clairaut’s Theorem and its extension to higher orders.
Theorem: if fxy and fyx both exist and are continuous on a disk D, then fxy(a,b)=fyx(a,b) for all (a,b) in D. Equivalently,
∂x∂y∂2f=∂y∂x∂2f(or fxy=fyx).
Higher orders: partial derivatives can be computed in any order, e.g.
fxyxy=fxxyy=fyyxx=fyxyx=fxyyx=fyxxy.
Pitfall: the equality requires the continuity condition.
Compute gzzwx for g(x,y,z,w)=x3w2z2+sin(z2xy). What strategy makes it easier?
Strategy: by Clairaut, reorder the derivatives. Note sin(z2xy) does not depend on w, so take the w-derivative first to kill it.
Steps:
∂w∂sin(z2xy)=0
gw=2x3wz2
gwx=2(3x2)wz2=6x2wz2
gwxz=6x2w(2z)=12x2wz
gwxzz=12x2w
Therefore gzzwx=gwxzz=12x2w.
What is a PDE, and what does this course expect you to do with one?
A Partial Differential Equation (PDE) is a differential equation involving multivariable functions and their partial derivatives.
In this lecture: nothing about solving PDEs. Once a solution is given, you need to know how to check the solution.
Example (Heat equation): for u(x,t), a function of two variables,
∂t∂u=∂x2∂2u is a PDE.
Show that u(x,t)=2πt1e−x2/(4t) (for t>0) satisfies the heat equation.
Compute both sides and compare.
x-derivatives:
∂x∂u=2πt1(−4t2x)e−x2/4t=−4π1xt−3/2e−x2/4t ∂x2∂2u=−4π1t−3/2(e−x2/4t+x(−4t2x)e−x2/4t)=−4π1t−3/2e−x2/4t+8π1x2t−5/2e−x2/4t
t-derivative (product rule on t−1/2 and the exponential):
∂t∂u=2π1(−21t−3/2e−x2/4t+t−1/2e−x2/4t(−4x2)(−t21))=−4π1t−3/2e−x2/4t+8π1t−5/2x2e−x2/4t
The two expressions match, so ∂t∂u=∂x2∂2u.