Let SS be the set of all twice differentiable functions ff from R\mathbb{R} to R\mathbb{R} such that d2fdx2(x)>0\frac{d^2 f}{dx^2}(x) > 0 for all x(1,1)x \in (-1, 1). For fSf \in S, let XfX_f be the number of points x(1,1)x \in (-1, 1) for which f(x)=xf(x) = x. Then, which of the following statements is (are) true? (a) There exists a function fSf \in S such that Xf=0X_f = 0 (b) For every function fSf \in S, we have Xf2X_f \leq 2 (c) There exists a function fSf \in S such that Xf=2X_f = 2 (d) There does not exist any function fSf \in S such that Xf=1X_f = 1

4 min read
62 views
Published July 22, 2025
Mathematics
Calculus
Functions
Real Analysis
Convexity & Fixed-points

💡 Want to ask your own questions?

Get instant explanations with AI • Free trial

Detailed Explanation

1. Turning the problem into a standard form

Take g(x)=f(x)x.g(x)=f(x)-x. Because g(x)=f(x)>0for all x(1,1),g''(x)=f''(x)>0\quad\text{for all }x\in(-1,1), the function gg is strictly convex in (1,1)(-1,1).

2. Geometry of a strictly convex curve

For any strictly convex gg on an interval:

  1. The graph lies below the straight line joining any two points on it.
  2. Therefore, if gg has two distinct zeros, say at x=ax=a and x=bx=b with a<ba<b, then
    g(x)<0  for all x(a,b).g(x)<0 \;\text{for all }x\in(a,b).
  3. A strictly convex function cannot have more than two real zeros in a connected interval; three would contradict the property in (2).

3. Consequences for the number of fixed points XfX_f

Because the fixed points of ff are precisely the zeros of gg:

  • Upper bound: Xf2.X_f\le 2.
  • Possibilities: XfX_f can be 0,1,20,1,2.

4. Constructing explicit examples

  1. Xf=0X_f=0:
    f(x)=x+2+x2.f(x)=x + 2 + x^2.
    Then g(x)=2+x2>0  x,g(x)=2+x^2>0\;\forall x, so no fixed points.
  2. Xf=1X_f=1:
    f(x)=x2.f(x)=x^2.
    Here g(x)=x2x=x(x1),g(x)=x^2-x=x(x-1), which vanishes only at x=0x=0 inside (1,1)(-1,1).
  3. Xf=2X_f=2:
    f(x)=x+x214.f(x)=x + x^2 - \tfrac14.
    Then g(x)=x214=(x12)(x+12),g(x)=x^2-\tfrac14=(x-\tfrac12)(x+\tfrac12), giving zeros at x=±12x=\pm\tfrac12. All examples satisfy f(x)=2>0f''(x)=2>0 within (1,1)(-1,1).

5. Verifying the options

  • (a) True – example 1.
  • (b) True – proven upper bound Xf2X_f\le2.
  • (c) True – example 3.
  • (d) False – example 2 contradicts it.

Simple Explanation (ELI5)

What is the question?

We are looking at very smooth curves f(x)f(x) on the number line such that the curve always bends upwards between x=1x=-1 and x=1x=1.

What do we count?

We count how many times that curve meets the diagonal line y=xy = x inside the window (1,1)(-1,1). Every meeting point is called a "fixed point" because there f(x)=xf(x)=x.

Why does the curve always bend up?

Because f(x)>0f''(x)>0 in (1,1)(-1,1). A positive second derivative means the curve is strictly convex – picture a bowl that always opens upward.

Important facts of a bowl-shaped curve minus the diagonal

Define another curve g(x)=f(x)xg(x)=f(x)-x. Because f(x)>0f''(x)>0 and d2(x)/dx2=0d^2(x)/dx^2=0, we have
g(x)=f(x)>0.g''(x)=f''(x)>0.
So g(x)g(x) is also strictly convex.

A strictly convex curve can:

  • cross the xx-axis zero, one, or two times (never three or more). Think of a smile that may stay above the axis, touch it once at its lowest dip, or cut it twice.

What the choices really ask

  • (a) Is a bowl that never touches the diagonal possible? (Yes.)
  • (b) Can we ever get 3 or more touch points? (No.)
  • (c) Can we design a curve that touches exactly twice? (Yes.)
  • (d) Is it impossible to touch exactly once? (No, it is possible.)

So the correct statements are (a), (b), (c).

👆 Found this helpful? Get personalized explanations for YOUR questions!

Step-by-Step Solution

Step 1: Reformulate with g(x)=f(x)xg(x)=f(x)-x

g(x)=f(x)x,g(x)=f(x)>0 on (1,1).g(x)=f(x)-x, \qquad g''(x)=f''(x)>0 \text{ on }(-1,1). So gg is strictly convex.

Step 2: Prove an upper bound on zeros of a strictly convex function

Assume, for contradiction, that gg has three distinct zeros a<b<ca<b<c in (1,1)(-1,1). By convexity, g(a+c2)<12(g(a)+g(c))=0,g\bigl(\tfrac{a+c}{2}\bigr)<\tfrac12\bigl(g(a)+g(c)\bigr)=0, which contradicts g(b)=0g(b)=0 because the curve would cross the axis more than twice. Hence Xf=#{x(1,1):g(x)=0}2.X_f=\#\{x\in(-1,1):g(x)=0\}\le2. This proves statement (b).

Step 3: Produce explicit examples

  1. No fixed point (Xf=0)(X_f=0)
    Choose f(x)=x+2+x2.f(x)=x+2+x^2.
    Then g(x)=2+x2>0,  x(1,1)Xf=0.g(x)=2+x^2>0,\;\forall x\in(-1,1)\Rightarrow X_f=0.
    Hence (a) is true.

  2. Exactly two fixed points (Xf=2)(X_f=2)
    Choose f(x)=x+x214.f(x)=x+x^2-\tfrac14.
    Here g(x)=x214=(x12)(x+12),g(x)=x^2-\tfrac14=(x-\tfrac12)(x+\tfrac12), so zeros at x=±12x=\pm\tfrac12. Therefore Xf=2X_f=2, proving (c) is true.

  3. Exactly one fixed point exists, so statement (d) is false
    Take f(x)=x2.f(x)=x^2.
    Then g(x)=x(x1)g(x)=x(x-1) vanishes only at x=0x=0 in (1,1)(-1,1), giving Xf=1X_f=1. Hence (d) is false.

Step 4: Final verdict

True statements: (a), (b), (c) False statement: (d)

Examples

Example 1

Parabolic mirrors rely on strict convexity to focus light; they never intersect a straight line more than twice in a small region.

Example 2

Cost functions in economics are often convex; their difference with linear pricing shows how many equilibrium points (fixed points) the market can have.

Example 3

In optimization, strictly convex loss functions guarantee at most one minimizer, similar to how our g(x) has limited zeros.

Visual Representation

References

🤔 Have Your Own Question?

Get instant AI explanations in multiple languages with diagrams, examples, and step-by-step solutions!

AI-Powered Explanations
🎯Multiple Languages
📊Interactive Diagrams

No signup required • Try 3 questions free