Sigma Percentile
JEE Main 2018 (Paper 1)
LEVELJEE Advanced

Animated Solution for Mathematics - Limits, Continuity and Differentiability: Let . Then the set is equal to :

Select Answer:

Visualized Solution

and Critical Points

  • Given:
  • Modulus functions and create sharp corners at their roots.
  • Potential points of non-differentiability: and .

Behavior Near

  • Let's analyze the behavior of as .
  • The term approaches .
  • This is a non-zero constant, so it doesn't cause any sharp corners here.

Approximating Near

  • For , we use standard limits:

The Magic of

  • Substituting these approximations back into :
  • Since , the sharp corner disappears!

Differentiability at

  • The function locally behaves like a smooth parabola .
  • The derivative at is exactly .
  • Conclusion: is differentiable at .

Behavior Near

  • Now, let's shift our focus to .
  • The term approaches , a non-zero constant.
  • The critical terms are and .

Trigonometric Transformation

  • Near , , so .
  • Using trigonometry:

Approximating Near

  • Let . As , .
  • The product becomes:

Differentiability at

  • This behaves like , which is smooth and has a derivative of .
  • Conclusion: is differentiable at .

Final Conclusion: Set

  • is differentiable at both critical points, and .
  • Everywhere else, it is a product of smooth functions.
  • The set of non-differentiable points is empty: .

The Sigma Insight: Differentiability of a Function

Solution Diagram

The Illusion of Sharpness

A Calculus Journey
Welcome, fellow traveler of the mathematical landscape. Today, we are going to dissect a function that, at first glance, looks like a nightmare of sharp corners and jagged edges.
We are looking at the function:
When you see modulus signs, your instinct might be to panic, expecting a graph full of V-shaped kinks. But in JEE Advanced, we don't panic; we investigate. Let's peel back the layers of this function and discover the hidden smoothness beneath.

Phase 1

Identifying the Suspects
Calculus is a detective game. We are looking for points where the function fails to be differentiable.
A function is non-differentiable where it has a 'kink'—a point where the slope changes abruptly. In our function, the modulus terms and are the prime suspects.
They are defined differently on either side of their roots, and . These are the only two points where the 'DNA' of our function changes. Everywhere else, it is a product of smooth, well-behaved functions.
So, our mission is clear: we must investigate the behavior of specifically at and .

Phase 2

The Origin ()
Let's stand at the origin. As approaches , the term is perfectly well-behaved; it just approaches . It is a constant, a silent observer that doesn't affect the differentiability.
The real action happens with and . Recall your standard limits: for small , and .
If we substitute these into our function, we get:
And here is the magic: is exactly . The sharp corner of the first is perfectly neutralized by the second .
The function locally behaves like a smooth parabola . A parabola is the definition of smoothness! Its derivative at is . The suspect is cleared; the function is differentiable at .

Phase 3

The Point ()
Now, let's move to our second suspect, . As approaches , the term approaches , which is just a non-zero constant. Again, it is harmless.
The troublemakers are and . Since we are near , is positive, so .
Using the trigonometric identity , we can see that as , behaves like . Now, look at the product: .
Let . The expression becomes . Just like , the function is smooth at the origin with a derivative of .
It creates a beautiful, inverted, smooth curve with a horizontal tangent. The sharp corner of is once again smoothed out by the linear behavior of the sine term. The second suspect is cleared!

Conclusion

The Empty Set
We have interrogated both suspects. At , the function behaves like a parabola. At , it behaves like a smooth cubic-like curve.
Everywhere else, it is a product of smooth functions. There are no points of non-differentiability.
The set of points where is non-differentiable is, quite elegantly, the empty set, .
Isn't that beautiful? What looked like a jagged, broken path was actually a perfectly smooth journey all along. Keep this intuition in your toolkit: multiplication can be a powerful tool for smoothing out the sharpest of corners. Happy problem solving!

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