**10.2**

**First-Order Partial Derivatives**

**Motivating Questions**

In this section, we strive to understand the ideas generated by the following important questions: • How are the first-order partial derivatives of a functionf of the independent variablesx

andydefined?

• Given a function f of the independent variables x and y, what do the first-order partial
derivatives∂f_{∂x}and ∂f_{∂y} tell us aboutf?

**Introduction**

The derivative plays a central role in first semester calculus because it provides important infor- mation about a function. Thinking graphically, for instance, the derivative at a point tells us the slope of the tangent line to the graph at that point. In addition, the derivative at a point also pro- vides the instantaneous rate of change of the function with respect to changes in the independent variable.

Now that we are investigating functions of two or more variables, we can still ask how fast the function is changing, though we have to be careful about what we mean. Thinking graphically again, we can try to measure how steep the graph of the function is in a particular direction. Alternatively, we may want to know how fast a function’s output changes in response to a change in one of the inputs. Over the next few sections, we will develop tools for addressing issues such as these these. Preview Activity10.2explores some issues with what we will come to callpartial derivatives.

**Preview Activity 10.2.** Let’s return to the function we considered in Preview Activity9.1. Suppose
we take out a $18,000 car loan at interest rater and we agree to pay off the loan in tyears. The
monthly payment, in dollars, is

M(r, t) = 1500r

1_{−} 1 +_{12}r−12t.

(a) What is the monthly payment if the interest rate is3%so thatr = 0.03, and we pay the loan off int= 4years?

(b) Suppose the interest rate is fixed at3%. ExpressMas a functionfoftalone usingr= 0.03. That is, letf(t) =M(0.03, t). Sketch the graph off on the left of Figure10.8. Explain the meaning of the functionf.

(c) Find the instantaneous rate of change f0(4) and state the units on this quantity. What information does f0(4) tell us about our car loan? What information does f0(4) tell us about the graph you sketched in (b)?

1 2 3 4 5 6 7 8 9 10 250 500 750 1000 t f(t) 0.02 0.04 0.06 0.08 0.10 250 500 750 1000 r g(r)

Figure 10.8: The graphs off(t) =M(0.03, t)andg(r) =M(r,4).

(d) ExpressM as a function ofr alone, using a fixed time oft= 4. That is, letg(r) =M(r,4). Sketch the graph ofgon the right of Figure10.8. Explain the meaning of the functiong. (e) Find the instantaneous rate of changeg0(0.03)and state the units on this quantity. What

information doesg0(0.03)tell us about our car loan? What information doesg0(0.03)tell us about the graph you sketched in (d)?

./

**First-Order Partial Derivatives**

In Section9.1, we studied the behavior of a function of two or more variables by considering the

tracesof the function. Recall that in one example, we considered the functionf defined by f(x, y) = x

2_{sin(2}_{y}_{)}

32 ,

which measures the range, or horizontal distance, in feet, traveled by a projectile launched with an initial speed ofxfeet per second at an angleyradians to the horizontal. The graph of this function is given again on the left in Figure10.9. Moreover, if we fix the angley = 0.6, we may view the tracef(x,0.6)as a function ofxalone, as seen at right in Figure10.9.

Since the trace is a one-variable function, we may consider its derivative just as we did in the first semester of calculus. Withy= 0.6, we have

f(x,0.6) = sin(1.2)
32 x
2_{,}
and therefore
d
dx[f(x,0.6)] =
sin(1.2)
16 x.

Whenx= 150, this gives

d

dx[f(x,0.6)]|x=150 =

sin(1.2)

10.2. FIRST-ORDER PARTIAL DERIVATIVES 107 0 50 100 150 200 0.5 1.0 1.5 500 1000 1500 x y z 50 100 150 200 200 400 600 800 1000 x f(x,0.6)

Figure 10.9: The trace withy = 0.6.

which gives the slope of the tangent line shown on the right of Figure10.9. Thinking of this deriva- tive as an instantaneous rate of change implies that if we increase the initial speed of the projectile by one foot per second, we expect the horizontal distance traveled to increase by approximately 8.74 feet if we hold the launch angle constant at0.6radians.

By holdingyfixed and differentiating with respect tox, we obtain the first-orderpartial deriva- tive off with respect tox. Denoting this partial derivative asfx, we have seen that

fx(150,0.6) =

d

dxf(x,0.6)|x=150= limh→0

f(150 +h,0.6)_{−}f(150,0.6)

h . More generally, we have

fx(a, b) = lim

h→0

f(a+h, b)_{−}f(a, b)

h , provided this limit exists.

In the same way, we may obtain a trace by setting, say,x= 150as shown in Figure10.10. This gives f(150, y) = 150 2 32 sin(2y), and therefore d dy[f(150, y)] = 1502 16 cos(2y).

If we evaluate this quantity aty = 0.6, we have d

dy[f(150, y)]|y=0.6=

1502

16 cos(1.2)≈509.5feet per radian.

Once again, the derivative gives the slope of the tangent line shown on the right in Figure10.10. Thinking of the derivative as an instantaneous rate of change, we expect that the range of the

0 50 100 150 200 0.5 1.0 1.5 500 1000 1500 x y z 0.25 0.50 0.75 1.00 1.25 200 400 600 800 1000 y f(150, y)

Figure 10.10: The trace withx= 150.

projectile increases by 509.5 feet for every radian we increase the launch angley if we keep the initial speed of the projectile constant at 150 feet per second.

By holdingxfixed and differentiating with respect toy, we obtain the first-orderpartial deriva- tive off with respect toy. As before, we denote this partial derivative asfy and write

fy(150,0.6) =

d

dyf(150, y)|y=0.6 = limh→0

f(150,0.6 +h)_{−}f(150,0.6)

h .

As with the partial derivative with respect tox, we may express this quantity more generally at an arbitrary point(a, b). To recap, we have now arrived at the formal definition of the first-order partial derivatives of a function of two variables.

**Definition 10.3.** The first-order**partial derivatives of**f**with respect to**x**and**yat a point(a, b)

are, respectively,
fx(a, b) = lim
h→0
f(a+h, b)_{−}f(a, b)
h , and
fy(a, b) = lim
h→0
f(a, b+h)_{−}f(a, b)
h ,

provided the limits exist.

**Activity 10.3.**

Consider the functionf defined by

f(x, y) = xy 2

10.2. FIRST-ORDER PARTIAL DERIVATIVES 109 at the point(1,2).

(a) Write the tracef(x,2)at the fixed valuey = 2. On the left side of Figure10.11, draw the graph of the trace withy = 2indicating the scale and labels on the axes. Also, sketch the tangent line at the pointx= 1.

Figure 10.11: Traces off(x, y) = _{x}xy_{+1}2.

(b) Find the partial derivativefx(1,2)and relate its value to the sketch you just made.

(c) Write the tracef(1, y)at the fixed valuex = 1. On the right side of Figure10.11, draw the graph of the trace withx= 1indicating the scale and labels on the axes. Also, sketch the tangent line at the pointy= 2.

(d) Find the partial derivativefy(1,2)and relate its value to the sketch you just made.

C
As these examples show, each partial derivative at a point arises as the derivative of a one-
variable function defined by fixing one of the coordinates. In addition, we may consider each par-
tial derivative as defining a new function of the point(x, y), just as the derivativef0_{(}_{x}_{)}_{defines a}

new function ofxin single-variable calculus. Due to the connection between one-variable deriva- tives and partial derivatives, we will often use Leibniz-style notation to denote partial derivatives by writing

∂f

∂x(a, b) =fx(a, b), and ∂f

∂y(a, b) =fy(a, b).

To calculate the partial derivative fx, we holdy fixed and thus we treaty as a constant. In

Leibniz notation, observe that ∂

∂x(x) = 1 and

∂

To see the contrast between how we calculate single variable derivatives and partial derivatives,
and the difference between the notations _{dx}d[ ]and _{∂x}∂[ ], observe that

d
dx[3x
2_{−}_{2}_{x}_{+ 3] = 3} d
dx[x
2_{]}_{−}_{2} d
dx[x] +
d
dx[3] = 3·2x−2,
and ∂
∂x[x
2_{y}
−xy+ 2y] =y ∂
∂x[x
2_{]}
−y ∂
∂x[x] +
∂
∂x[2y] =y·2x−y

Thus, computing partial derivatives is straightforward: we use the standard rules of single vari- able calculus, but do so while holding one (or more) of the variables constant.

**Activity 10.4.**

(a) If we have the functionfof the variablesxandyand we want to find the partial deriva- tivefx, which variable do we treat as a constant? When we find the partial derivative

fy, which variable do we treat as a constant?

(b) Iff(x, y) = 3x3_{−}_{2}_{x}2_{y}5_{, find the partial derivatives}_{f}

xandfy.

(c) Iff(x, y) = xy 2

x+ 1, find the partial derivativesfxandfy.

(d) Ifg(r, s) =rscos(r), find the partial derivativesgrandgs.

(e) Assumingf(w, x, y) = (6w+ 1) cos(3x2_{+ 4}_{xy}3_{+}_{y}_{)}_{, find the partial derivatives}_{f}

w,fx,

andfy.

(f) Find all possible first-order partial derivatives ofq(x, t, z) = x2

t_{z}3

1 +x2.

C

**Interpretations of First-Order Partial Derivatives**

Recall that the derivative of a single variable function has a geometric interpretation as the slope of the line tangent to the graph at a given point. Similarly, we have seen that the partial derivatives measure the slope of a line tangent to a trace of a function of two variables as shown in Figure

10.12.

Now we consider the first-order partial derivatives in context. Recall that the difference quo-
tient f(a+h_{h})−f(a) for a functionf of a single variablexat a point wherex=atells us the average
rate of change off over the interval[a, a+h], while the derivativef0(a)tells us the instantaneous
rate of change offatx=a. We can use these same concepts to explain the meanings of the partial
derivatives in context.

**Activity 10.5.**

The speed of soundCtraveling through ocean water is a function of temperature, salinity and depth. It may be modeled by the function

10.2. FIRST-ORDER PARTIAL DERIVATIVES 111 0 50 100 150 200 0.5 1.0 1.5 500 1000 1500 x y z 0 50 100 150 200 0.5 1.0 1.5 500 1000 1500 x y z

Figure 10.12: Tangent lines to two traces of the range function.

HereC is the speed of sound in meters/second, T is the temperature in degrees Celsius,S is the salinity in grams/liter of water, andDis the depth below the ocean surface in meters.

(a) State the units in which each of the partial derivatives,CT, CS andCD, are expressed

and explain the physical meaning of each. (b) Find the partial derivativesCT,CSandCD.

(c) Evaluate each of the three partial derivatives at the point whereT = 10,S = 35and

D= 100. What does the sign of each partial derivatives tell us about the behavior of the

functionCat the point(10,35,100)?

C

**Using tables and contours to estimate partial derivatives**

Remember that functions of two variables are often represented as either a table of data or a con- tour plot. In single variable calculus, we saw how we can use the difference quotient to approxi- mate derivatives if, instead of an algebraic formula, we only know the value of the function at a few points. The same idea applies to partial derivatives.

**Activity 10.6.**

The wind chill, as frequently reported, is a measure of how cold it feels outside when the wind is blowing. In Table10.1, the wind chillw, measured in degrees Fahrenheit, is a function of the wind speedv, measured in miles per hour, and the ambient air temperatureT, also measured in degrees Fahrenheit. We thus viewwas being of the formw=w(v, T).

(a) Estimate the partial derivative wv(20,−10). What are the units on this quantity and

v\T -30 -25 -20 -15 -10 -5 0 5 10 15 20 5 -46 -40 -34 -28 -22 -16 -11 -5 1 7 13 10 -53 -47 -41 -35 -28 -22 -16 -10 -4 3 9 15 -58 -51 -45 -39 -32 -26 -19 -13 -7 0 6 20 -61 -55 -48 -42 -35 -29 -22 -15 -9 -2 4 25 -64 -58 -51 -44 -37 -31 -24 -17 -11 -4 3 30 -67 -60 -53 -46 -39 -33 -26 -19 -12 -5 1 35 -69 -62 -55 -48 -41 -34 -27 -21 -14 -7 0 40 -71 -64 -57 -50 -43 -36 -29 -22 -15 -8 -1 Table 10.1: Wind chill as a function of wind speed and temperature.

(b) Estimate the partial derivative wT(20,−10). What are the units on this quantity and

what does it mean?

(c) Use your results to estimate the wind chillw(18,−10).
(d) Use your results to estimate the wind chillw(20,_{−}12).
(e) Use your results to estimate the wind chillw(18,_{−}12).

C

**Activity 10.7.**

Shown below in Figure10.13is a contour plot of a functionf. The value of the function along a few of the contours is indicated to the left of the figure.

-3 -2 -1 1 2 3 -3 -2 -1 1 2 3 6 5 4 3 2 1 0 -1 x y

Figure 10.13: A contour plot off. (a) Estimate the partial derivativefx(−2,−1).

(b) Estimate the partial derivativefy(−2,−1).

10.2. FIRST-ORDER PARTIAL DERIVATIVES 113 (d) Locate one point(x, y)where the partial derivativefx(x, y) = 0.

(e) Locate one point(x, y)wherefx(x, y)<0.

(f) Locate one point(x, y)wherefy(x, y)>0.

(g) Suppose you have a different functiong, and you know thatg(2,2) = 4,gx(2,2)> 0,

andgy(2,2)>0. Using this information, sketch a possibility for the contourg(x, y) = 4

passing through(2,2)on the left side of Figure10.14. Then include possible contours

g(x, y) = 3andg(x, y) = 5. 1 2 3 4 1 2 3 4 x y 1 2 3 4 1 2 3 4 x y

Figure 10.14: Plots for contours ofgandh.

(h) Suppose you have yet another functionh, and you know thath(2,2) = 4,hx(2,2)<0,

andhy(2,2)>0. Using this information, sketch a possible contourh(x, y) = 4passing

through(2,2)on the right side of Figure10.14. Then include possible contoursh(x, y) =

3andh(x, y) = 5.

C

**Summary**

• Iff =f(x, y)is a function of two variables, there are two first order partial derivatives off: the partial derivative off with respect tox,

∂f

∂x(x, y) =fx(x, y) = limh→0

f(x+h, y)_{−}f(x, y)

h , and the partial derivative off with respect toy,

∂f

∂y(x, y) =fy(x, y) = limh→0

f(x, y+h)_{−}f(x, y)

h ,

where each partial derivative exists only at those points(x, y)for which the limit exists.

• The partial derivativefx(a, b)tells us the instantaneous rate of change off with respect toxat

(x, y) = (a, b)whenyis fixed atb. Geometrically, the partial derivativefx(a, b)tells us the slope

• The partial derivativefy(a, b)tells us the instantaneous rate of change off with respect toyat

(x, y) = (a, b)whenxis fixed ata. Geometrically, the partial derivativefy(a, b)tells us the slope

of the line tangent to thex=atrace of the functionf at the point(a, b, f(a, b)).

**Exercises**

**1.** The Heat Index,I, (measured inapparent degrees F) is a function of the actual temperatureT
outside (in degrees F) and the relative humidityH (measured as a percentage). A portion of
the table which gives values for this function,I =I(T, H), is reproduced below:

T↓ \H→ 70 75 80 85

90 106 109 112 115

92 112 115 119 123

94 118 122 127 132

96 125 130 135 141

(a) State the limit definition of the value IT(94,75). Then, estimate IT(94,75), and write

one complete sentence that carefully explains the meaning of this value, including its units.

(b) State the limit definition of the value IH(94,75). Then, estimateIH(94,75), and write

one complete sentence that carefully explains the meaning of this value, including its units.

(c) Suppose you are given thatIT(92,80) = 3.75 andIH(92,80) = 0.8. Estimate the val-

ues ofI(91,80)andI(92,78). Explain how the partial derivatives are relevant to your thinking.

(d) On a certain day, at 1 p.m. the temperature is 92 degrees and the relative humidity is 85%. At 3 p.m., the temperature is 96 degrees and the relative humidity 75%. What is the average rate of change of the heat index over this time period, and what are the units on your answer? Write a sentence to explain your thinking.

**2.** Let f(x, y) = 1_{2}xy2 _{represent the kinetic energy in Joules of an object of mass} _{x}_{in kilograms}

with velocityyin meters per second. Let(a, b)be the point(4,5)in the domain off. (a) Calculatefx(a, b).

(b) Explain as best you can in the context of kinetic energy what the partial derivative

fx(a, b) = lim

h→0

f(a+h, b)−f(a, b)

h tells us about kinetic energy.

10.2. FIRST-ORDER PARTIAL DERIVATIVES 115 (d) Explain as best you can in the context of kinetic energy what the partial derivative

fy(a, b) = lim

h→0

f(a, b+h)_{−}f(a, b)

h tells us about kinetic energy.

(e) Often we are given certain graphical information about a function instead of a rule. We can use that information to approximate partial derivatives. For example, suppose that we are given a contour plot of the kinetic energy function (as in Figure10.15) instead of a formula. Use this contour plot to approximatefx(4,5)andfy(4,5)as best you can.

Compare to your calculations from earlier parts of this exercise.

1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 x y 10 20 3040 50 60 70 80

Figure 10.15: The graph off(x, y) = 1_{2}xy2_{.}

**3.** The temperature on an unevenly heated metal plate positioned in the first quadrant of thex-y
plane is given by

C(x, y) = 25xy+ 25

(x_{−}1)2_{+ (}_{y}_{−}_{1)}2_{+ 1}.

Assume that temperature is measured in degrees Celsius and thatxandyare each measured
in inches. (**Note:** At no point in the following questions should you expand the denominator
ofC(x, y).)

(a) Determine ∂C_{∂x}|(x,y)and ∂C∂y|(x,y).

(b) If an ant is on the metal plate, standing at the point(2,3), and starts walking in a direc- tion parallel to theyaxis, at what rate will the temperature he is experiencing change? Explain, and include appropriate units.

(c) If an ant is walking along the liney= 3, at what instantaneous rate will the temperature he is experiencing change when he passes the point(1,3)?

(d) Now suppose the ant is stationed at the point(6,3)and walks in a straight line towards the point(2,0). Determine theaveragerate of change in temperature (per unit distance

traveled) the ant encounters in moving between these two points. Explain your reason- ing carefully. What are the units on your answer?

**4.** Consider the functionf defined byf(x, y) = 8−x2_{−}_{3}_{y}2_{.}

(a) Determinefx(x, y)andfy(x, y).

(b) Find parametric equations inR3for the tangent line to the tracef(x,1)atx= 2. (c) Find parametric equations inR3for the tangent line to the tracef(2, y)aty= 1. (d) State respective direction vectors for the two lines determined in (b) and (c).

(e) Determine the equation of the plane that passes through the point(2,1, f(2,1))whose
normal vector is orthogonal to the direction vectors of the two lines found in (b) and (c).
(f) Use a graphing utility to plot both the surfacez = 8−x2_{−}_{3}_{y}2_{and the plane from (e)}