Question

$$ \begin{array}{l} \text { 23. Prove that if } \lim _{x \rightarrow c} f(x)=L \text { and } \lim _{x \rightarrow c} f(x)=M, \text { then }\\\ L=M \end{array} $$

Short answer

If two limits exist as \( x \to c \) for a function \( f(x) \), they must be equal, thus \( L = M \).

Step-by-step solution

Understanding the Limit Definition

The problem states that \( \lim_{x \to c} f(x) = L \) and \( \lim_{x \to c} f(x) = M \). By definition of the limit, this means for any \( \epsilon > 0 \), there exists a \( \delta > 0 \) such that for all \( x \) where \( 0 < |x - c| < \delta \), we have \( |f(x) - L| < \epsilon \) and \( |f(x) - M| < \epsilon \).

Applying the Definition to Both Limits

For the given \( \epsilon > 0 \), there exists a \( \delta_1 > 0 \) for \( |f(x) - L| < \epsilon \) and a \( \delta_2 > 0 \) for \( |f(x) - M| < \epsilon \) whenever \( 0 < |x - c| < \delta_1 \) and \( 0 < |x - c| < \delta_2 \).

Finding a Common Interval

Let \( \delta = \min(\delta_1, \delta_2) \). Then for all \( x \) such that \( 0 < |x - c| < \delta \), both \( |f(x) - L| < \epsilon \) and \( |f(x) - M| < \epsilon \) hold. Thus, for the same \( x \), \( |L - M| = |(f(x) - L) - (f(x) - M)| \leq |f(x) - L| + |f(x) - M| < \epsilon + \epsilon = 2\epsilon \).

Concluding the Proof

Since \( |L - M| < 2\epsilon \) for any arbitrary \( \epsilon > 0 \), and \( \epsilon \) can be made arbitrarily small, it follows that \( |L - M| = 0 \), hence \( L = M \). Therefore, if \( \lim_{x \to c} f(x) = L \) and \( \lim_{x \to c} f(x) = M \), then \( L = M \).

Key concepts

Limit of a Function

The limit of a function is a foundational concept in calculus. It refers to the value that a function approaches as the input (or x-value) approaches a specific point. When we express this mathematically, we write \( \lim_{x \to c} f(x) = L \). This statement says that as \( x \) gets closer and closer to \( c \), the value of the function \( f(x) \) gets closer and closer to \( L \).
This concept helps in understanding the behavior of functions, especially when they might not be traditionally defined at a particular point, such as in the case of division by zero.
When studying limits, it's crucial to recognize that the actual value at \( x = c \) is irrelevant; rather, what matters is how the function behaves as \( x \) approaches \( c \). This makes limits extremely powerful in defining and analyzing the continuity and differentiability of functions, facilitating deeper insights into their behavior.

Epsilon-Delta Definition

The epsilon-delta definition provides a formal way to define limits. It's a precise mathematical framework to demonstrate how limits work. According to this definition, for a limit \( \lim_{x \to c} f(x) = L \), for every possible small number \( \epsilon > 0 \), there is a corresponding small distance \( \delta > 0 \), such that whenever the distance between \( x \) and \( c \) is less than \( \delta \), the distance between \( f(x) \) and the limit \( L \) will be less than \( \epsilon \).
To summarize, the epsilon-delta definition tells us:

• We can get \( f(x) \) as close to \( L \) as we desire, by choosing \( x \) values sufficiently close to \( c \).
• It provides a rigorous way to prove that a limit exists and has a specific value.
• This concept is essential in proving advanced theorems and understanding continuity on a deeper level.

This definition is fundamental in calculus as it moves from an intuitive understanding of limits to a precise and logical formulation.

Uniqueness of Limits

The uniqueness of limits theorem states that if a function \( f(x) \) approaches two different limits \( L \) and \( M \) as \( x \) approaches a particular point \( c \), then \( L \) must equal \( M \). This theorem may sound simple, but it has profound implications.
Mathematically, this is proved using the epsilon-delta definition. If both \( \lim_{x \to c} f(x) = L \) and \( \lim_{x \to c} f(x) = M \), we can choose \( \epsilon > 0 \) and find \( \delta \) values for both limits, ensuring that \( |f(x) - L| < \epsilon \) and \( |f(x) - M| < \epsilon \). By defining \( \delta = \min(\delta_1, \delta_2) \), it can be shown that \( |L - M| < 2\epsilon \).
Since \( \epsilon \) can be made arbitrarily small, this leads to \( |L - M| = 0 \), thus proving that \( L = M \).
This practical proof ensures that a function can have at most one limit as the input approaches a particular value, reinforcing consistency and stability in the assessment of limits across calculus.