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Solution Manual for Introduction to Partial Differential Equations by Peter J. Olver

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This advanced solution manual offers comprehensive, step-by-step solutions to selected exercises from Introduction to Partial Differential Equations by Peter J. Olver. It covers key topics including first-order equations, linear and nonlinear PDEs, the wave equation, heat equation, Laplace's equation, separation of variables, Fourier analysis, and eigenfunction expansions, as well as modern approaches using differential operators and symmetry methods. Designed for upper-level undergraduate and graduate students in mathematics, physics, and engineering, this manual helps deepen theoretical understanding while reinforcing practical problem-solving skills for applied and pure PDE analysis. partial differential equations solutions, peter olver pde answers, wave equation solved problems, heat equation step-by-step solutions, laplace equation exercises, separation of variables pde, fourier series and transforms, symmetry methods in pdes, linear pde solution manual, mathematical physics textbook solutions, eigenfunction expansion problems, olver introduction to pdes, graduate pde course help, applied mathematics pde workbook, first order nonlinear pde solutions

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SOLUTIONS MANUAL

,Selected Solutions Manual
for Instructors
for

Introduction to Partial
Differential Equations
by
Peter J. Olver

Undergraduate Texts in Mathematics
Springer, 2014
ISBN 978–3–319–02098–3


c 2020 Peter J. Olver

,Table of Contents
Chapter 1. What Are Partial Differential Equations?................................................ 1
Chapter 2. Linear and Nonlinear Waves ............................................................................. 3

Chapter 3. Fourier Series . . . . . . . . . . . . . . . . . . . . . 14

Chapter 4. Separation of Variables . . . . . . . . . . . . . . . . . 29

Chapter 5. Finite Differences . . . . . . . . . . . . . . . . . . . 43

Chapter 6. Generalized Functions and Green’s Functions ............................................... 60
Chapter 7. Fourier Transforms ..................................................................................... 71
Chapter 8. Linear and Nonlinear Evolution Equations ...........................................77
Chapter 9. A General Framework for
Linear Partial Differential Equations ............................... 87

Chapter 10. Finite Elements and WeakSolutions . . . . . . . . . . . 99

Chapter 11. Dynamics of Planar Media . . . . . . . . . . . . . . . 110

Chapter 12. Partial Differential Equations in Space . . . . . . . . . . 126




c 2020 Peter J. Olver

, SelectedSolutionsto
Chapter 1: What Are Partial Differential Equations?
Note: Solutions marked with a ⋆ do not appear in the Student Solutions Manual.

1.1. (a) Ordinary differential equation, equilibrium, order = 1;
(c) partial differential equation, dynamic, order = 2;
(e) partial differential equation, equilibrium, order = 2;
⋆(g) partial differential equation, equilibrium, order = 2;
⋆(i) partial differential equation, dynamic, order = 3;
⋆(k) partial

differential equation, dynamic, order = 4.
u
1.2. (a) (i ) 2u ∂2 = 0, (ii ) u +u
+ = 0;
∂x2 ∂y 2 xx yy
∂u ∂ 2 2
u +u .
⋆ (c) (i ) = u ∂
+
, (ii ) u = u
∂t ∂x2 ∂y2 t xx yy
1.4. (a) independent variables: x, y; dependent variables: u, v; order = 1;
⋆(b) independent variables: x, y; dependent variables: u, v; order = 2;
⋆(d) independent variables: t, x, y; dependent variables: u, v, p; order = 1.

∂ 2 2u
1.5. (a) u ∂ = ex cos y −ex cos y = 0; defined and C∞ on all of R 2 .
2 + 2
∂x2 ∂y
2
∂ u
⋆ (c) u ∂
+
= 6 x − 6 x = 0; defined and C∞ on all of R 2 .
∂x2 2 ∂y2 2 2 2 2 2
∂ u ∂ u 2y − 2x 2x − 2 y
⋆ (d)
∂x2
+
∂y 2
= ∞
2
\ {0}.
2 + y2 ) 2 + 2 + y2 )2 = 0; defined and C on R
h
(x i
(x
1.7. u = log c (x − a)2 + c (y − b)2 , for a, b, c arbitrary constants.
+ c1 x + c2 y + c3 z + c4 (x2 − y 2) + c5 (x2 − z 2) + c6 xy + c7 xz + c8 yz,
⋆ 1.8. (a) c 0
where c0, . . . , c8 are arbitrary constants.
∂ u ∂ u
1.10. (a) 2
u = 8 − 8 = 0; ⋆ (c)
2
u = −4 sin 2 t cos x + 4 sin 2 t cos x = 0.
∂ ∂
2 2
−4 −4
∂t2 ∂x2 ∂t2 ∂x2
2 2
1.11. (a) c0 + c1t + c 2x + c3(t + x ) + c 4 tx, where c0, . . . , c4 are arbitrary constants.
b b , where a, b are arbitrary constants.
⋆ 1.13. u = a + = a +
q
r x2 + y 2 + z 2




c 2020 Peter J. Olver

, 2 Chapter 1: Selected Solutions


1.15. Example: (b) u2 + u2 + u2 = 0 — the only real solution is u ≡ 0.
x y

⋆ 1.16. When (x, y) 6= (0, 0), a direct4 computation
2 2 4
shows that
4 2 2 4
∂u y (x + 4 x y − y ) ∂u x(x − 4 x y − y )
= , = ,
∂x 2 2
(x + y ) 2 ∂y (x2 + y2) 2
while, from the definition of partial derivative,
∂u
(0, 0) = lim u(h, 0) − u(0, 0) ∂u u(0, k) − u(0, 0)
∂ = 0, (0, 0) = lim = 0.
h→ 0 h ∂y k→ 0 k
x
Thus,
∂2 u ux(0, k) − ux(0, 0) = −1.
∂ 2u uy(h, 0) − uy(0, 0) = 1,
(0, 0) = lim (0, 0) = lim
∂x ∂y h→ 0 h ∂y ∂x k→ 0 k
This does not contradict the equality of mixed partials because the theorem
requires continuity, while
2
∂2u = ∂ u x6 + 9 x 4 y 2 + 9 x 2 y 4 − y 4 , (x, y) 6= (0, 0),
= 2 + y 2 )3
∂x ∂y ∂x ∂y (x
is not continuous at (x, y) = (0, 0). Indeed,
2
lim ∂ u (h, 0) = 1 6= −1 = lim ∂2 u
(0, k).
h → 0 ∂x ∂y k → 0 ∂x ∂y




1.17. (a) homogeneous linear; (d) nonlinear; ⋆
(f ) inhomogeneous linear.
∂ 2u ∂ u2
1.19. (a) (i ) = −4 cos(x − 2 t) = 4 .
∂t2 ∂x2
⋆ 1.20. (a) cos(x − 2 t) + 1 cos x − 5 sin(x − 2 t) − 5 sin x.
4 4
∂ ∂f ∂g
1.21. (a) ∂x[ cf + dg ] = [ cf (x) + dg(x)] = c +d = c∂ x [ f ] + d∂x [ g ]. The same proof
∂x ∂x ∂x
works for ∂y. (b) Linearity requires d = 0, while a, b, c can be arbitrary functions of x, y.
⋆ 1.23. Using standard vector calculus identities:
(b) ∇ × (f + g) = ∇ × f + ∇ × g, ∇ × (c f) = c ∇ × f.
1.24. (a) (L − M )[ u + v ] = L[ u + v ] − M [ u + v ] = L[ u ] + M [ u ] − L[ v ] − M [ v ]
= (L − M)[ u] + (L − M)[ v ],
(L − M)[ cu ] = L[ cu ] − M[ cu ] = cL[ u] − cM[ u] = c(L − M)[ u];
⋆(c) (f L)[ u + v ] = f L[ u + v ] = f L[ u] + f L[ v ] = (f L)[u] + (f L)[ v],
(f L)[ cu ] = f L[ cu ] = f cL[ u] = c(f L)[ u].
1.27. (b) u(x) = 1 ex sin x + c1 e2 x/5 cos 45x + c2 e2 x/5 sin 45x.
16 1 sin x + c e3 x + c
1.28. (b) u(x) = − x − e− 3 x ,
9 10 1 2
⋆(d) u(x) = 1 x ex − 1 ex + 1 e − x + c ex + c e− 2 x .
6 18 4 1 2




c 2020 Peter J. Olver

, SelectedSolutionsto
Chapter 2: Linear and Nonlinear Waves
Note: Solutions marked with a ⋆ do not appear in the Student Solutions Manual.

⋆ 2.1.1. u(t, x) = t x + f(x), where f is an arbitrary C1 function.

2.1.3. (a) u(t, x) = f(t); ⋆
(c) u(t, x) = tx − 1 t22 + f(x); (e) u(t, x) = e− tx f(t).
2.1.5. u(t, x, y) = f (x, y) where f is an arbitrary C1 function of two variables. This is valid pro-
vided each slice Da,b = D ∩ { (t, a, b) | t ∈ R }, for fixed (a, b) ∈ R 2, is either empty or a
connected interval.
⋆ ♥ 2.1.8. (a) The partial differential equation is really an autonomous first-order ordinary differen-
tial equation in t, with x as a parameter. Solving this ordinary differential equation
by standard methods, [20, 23], the solution to the initial value problem is
f (x) . Thus, if f(x) > 0, then the denominator does not vanish for t ≥ 0,
u(t, x) =
tf (x) + 1
and, moreover, goes to ∞ as t → ∞. Therefore, u(t, x) → 0 as t → ∞.
(b) If f(x) < 0, then the denominator in the preceding solution formula vanishes when
t = τ = −1/f(x). Moreover, for t < τ, the numerator is negative, while the denominator
is positive, and so lim u(t, x) = −∞.
t→ τ


(c) The solution is defined for 0 < t < t⋆, where t⋆ = −1/ min f(x). In particular, if
min f(x) = −∞, then the solution is not defined for all x ∈ R for any t > 0.
♦ 2.1.9. It suffices to show that, given two points (t1, x), (t2, x) ∈ D, then u(t1, x) = u(t2, x). By
the assumption, (t, x) ∈ D for t1 ≤ t ≤ t2, and so u(t, x) is defined and continuously
differentiable at such points. Thus, by the Fundamental Theorem of Calculus,
Z t
2 ∂u

u(t2, x) − u(t1, x) = (s, x) ds = 0. Q.E.D.
t 1 ∂t




2.2.2. (a) u(t, x) = e − (x+3 t) 2




t= 1 t= 2 t= 3




c 2020 Peter J. Olver

, 4 Chapter 2: Selected Solutions



⋆(c) u(t, x) = e − t/2 tan−1(x − t)




t= 1 t= 2 t= 3
2.2.3. (b) Characteristic lines: x = 5 t + c; general solution: u(t,x) = f(x −5t);
x




t



⋆(d) Characteristic lines: x = −4 t + c; general solution: u(t, x) = e −t f (x + 4 t);
x




t



⋆ 2.2.4. u(t, x) = t + e − (x−2 t) .
2


♦ 2.2.6. By the chain rule
∂v ∂u ∂v ∂u , x) ,
(t, x) = (t − t , x) , (t, x) = (t − t
0
∂t ∂t ∂x ∂x
and hence
0
∂v ∂v ∂u ∂u , x) = 0.
(t, x) + c (t, x) = (t − t , x) + c (t − t
∂t ∂x 0
∂t ∂x

0
Moreover, v(t0, x) = u(0,x) = f(x). Q.E.D.
⋆ 2.2.9. (a) | u(t, x) | = | f(x − ct) | e− at ≤ M e− at → 0 as t → ∞ since a > 0.
(b) For example, if c ≥ a, then the solution u(t, x) = e(c−a) t−x −6 → 0 as t → ∞.




c 2020 Peter J. Olver

, Chapter 2: Selected Solutions 5
1 1
⋆ ♥ 2.2.11. (a) u(t, x) = , where h(ξ) is an arbitrary C function.
t + h(x − t)
(b) The solution to the initial value problem is
f(x − t)
u(t, x) = .
1 + t f(x − t)
If f(x) ≥ 0, then the denominator does not vanish for t ≥ 0, and hence the solution
y is strictly
exists for t > 0. Moreover, for fixed t > 0, the function g(y) =
1 + ty
M
increasing for y ≥ 0. Therefore, 0 ≤ u(t, x) ≤ −→ 0 as t → ∞.
(c) Using the preceding solution formula, if 1f(x) + M< t 0, then, at the point x = x − 1/f(x),

the solution u(t, x⋆ ) → −∞ as t → τ = −1/f(x).
(d) If m = min f(x) < 0, then, by part (c), the minimal blow-up time is τ⋆ = −1/m.
(
f(x − ct), x ≥ c t,
2.2.14. (a) u(t, x) = g(t − x/c), x ≤ c t, defines a classical C1 solution provided the
compatibility conditions g(0) = f(0), g′(0) = −cf(0), hold.
(b) The initial condition affects the solution for x ≥ c t, whereas the boundary
condition affects the solution for x ≤ c t. Apart from the compatibility condition
along the characteristic line x = ct, they do not affect each other.



2.2.17. (a) u(t, x) =
1 e− 2 t
= .
(b) (xet )2 + 1 2
x +e − 2 t
t = 0: t = 1:




t = 2: t = 3:




(
1, x = 0,
(c) The limit is discontinuous: lim u(t, x) = 0, otherwise.
t→ ∞

0, x < −1, f f(−1), x < 1,
⋆ 2.2.18. (a) lim
(−1), x = −1, (b) lim f(1), x = 1,
t→ ∞ u(t, x) = t→ − ∞
u(t, x) =
f(1), x > −1. 0, x > 1.




c 2020 Peter J. Olver

, 6 Chapter 2: Selected Solutions

2.2.20. (a) The characteristic curves are given by x = tan(t + k) for k ∈ R.
x




t




(b) The general solution is u(t, x) = g(tan−1 x − t), where g(ξ) is an arbitrary C1 function of
the characteristic variable.
(c) The solution is u(t, x) = f tan(tan−1 x − t) . Observe that the solution is not defined
for x < tan t − 1 π for 0 < t < π, nor at any value of x after t ≥ π. As t increases up
to π, the wave moves
2 rapidly off to +∞ at an ever accelerating rate, and the solution
effectively disappears.
⋆ 2.2.22. If u(t, x) = v(β(x) − t), then, by the chain rule, ut = −v′(β(x) − t), while
ux = v′(β(x) − t) β′(x) = v′ (β(x) − t)/c(x), and hence ut + c(x) ux = 0. Q.E.D.
⋆ 2.2.24. If | c(x) | ≤ c⋆, then each characteristic curve exists for all t ∈ R; indeed, if | dx/dt | ≤ c⋆,
then | x(t) − x(0) | ≤ c⋆ | t |, and hence, by the existence and uniqueness theorem for
first-order ordinary differential equations, the solution x(t) is uniquely defined for all
t.
Thus, the characteristic curve through a point (t,x) ∈ R 2 intersects the x axis at,
say, the point x = x⋆. Since the solution must be constant along the characteristic,
its value u(t,x) equals the initial value f(x⋆).
⋆ ♥ 2.2.25. (a) The characteristic curves are solutions to the first-order ordinary differential equation
dx
= c(x). They cannot cross each other because of uniqueness of solutions to the
dt
initial value problem. Indeed, uniqueness says that, since c(x) ∈ C1, there is
exactly one solution x = g(t) to the initial value problem x(t0) = x0, and hence
exactly one characteristic curve going through any point (t0, x 0).
dx
(b) If x(t) = x⋆ is constant, = 0 = c(x )⋆solves the characteristic ordinary differential
dt
then
equation, and hence, by uniqueness, its graph, which is a horizontal line, is the
characteristic curve going through the point (t, x⋆).
(e) Suppose x = g(t) is not monotone, so g′(t1) = c(g(t1)) > 0 and g′(t 2) = c(g(t2)) < 0,
say. Then, by continuity, 0 = g′(t 0) = c(g(t0)) for some t0 between t1 and t2, and
hence x0 = g(t0) is a fixed point. But, this would violate uniqueness: the non-
horizontal char- acteristic curve x = g(t) would cross the horizontal characteristic
line at the fixed point
(t0, x0) = (t0, x(t0)). We conclude that each non-horizontal characteristic curve
must be the graph of a monotone function.
(f ) Because the individual points on the wave follow the monotone characteristic curves
x(t), and hence the wave speed c(x(t)) has the same sign at all times t.


c 2020 Peter J. Olver

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