কোনো ফাংশনের অন্তরজ সবসময় শুণ্য হওয়ার মানে কী?

Before this, knowক্রমবর্ধমান আর ক্রমহ্রাসমান ফাংশনের ক্যালকুলাস

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Suppose a function f(x)f(x) is continuous on [a,b][a,b] and differentiable on (a,b)(a,b). If f′(x)=0f'(x)=0 for all xx in (a,b)(a,b), what would that mean for f(x)f(x) graphically?

First, what does the derivative of a function at a point represent graphically?

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Steven Kwon already gave a nice explanation with good intuition. Here we'll give a (nonstandard?) proof avoiding the mean value theorem, inspired by a blog post of Tim Gowers.

Suppose ff is differentiable on [0,1][0,1], with f′(t)=0f'(t) = 0 for all t∈[0,1]t\in[0,1]. We want to show +f(1)−f(0)=0+f(1)-f(0) = 0. (The same reasoning will show that ff is constant on [0,1][0,1]: do you see why?)

The difficulty (and also why this fact is interesting) is that the condition "f′(t)=0f'(t) = 0" (always-zero derivative) is local, while the desired statement +f(1)−f(0)=0+f(1)-f(0) = 0 is a more global expression.

Note that the "global" change in ff has a nice "telescoping" property: for example, [+f(1)−f(0)]=[+f(0.5)−f(0)]+[+f(1)−f(0.5)].[+f(1)-f(0)] = [+f(0.5)-f(0)] + [+f(1)-f(0.5)].

The opposite +,−+,- signs of the f(0.5)f(0.5) terms cancel each other out. So this leads to a natural idea: if we keep breaking up larger intervals (like [0,1][0,1]) into smaller intervals (like [0,0.5][0,0.5] and [0.5,1][0.5,1]), then "eventually" we'll be able to use the local zero-change/sensitivity/derivative condition f′(t)=0f'(t)=0 "better and better".

OK, so for any x,yx,y in the big interval [0,1][0,1], let's write Δ(x,y)=+f(y)−f(x)\Delta(x,y) = +f(y) - f(x) for convenience. Then we can nicely rewrite the "telescoping" property above as Δ(a,b)=Δ(a,c)+Δ(c,b).\Delta(a,b) = \Delta(a,c)+ \Delta(c,b). We want to keep splitting into smaller and smaller intervals like this, until we can use the always-00-derivative condition. For example, if we had a=0a=0, b=1b=1, then we could decompose Δ(0,1)=Δ(0.0,0.1)+Δ(0.1,0.2)+⋯+Δ(0.9,1.0).\Delta(0,1) = \Delta(0.0,0.1)+\Delta(0.1,0.2)+\cdots+\Delta(0.9,1.0).

We want to be able to say that each of these 1010 (or however many we end up decomposing into) terms are small, and this is where the derivative condition comes into play.

The technical details

"Smallness" is relative, so let's fix a concrete threshold ϵ>0\epsilon>0 that we can refer to. Recall that f′(t)=0f'(t) = 0 just means that Δ([t,x])=o(∣x−t∣)\Delta([t,x]) = o(|x-t|), so for our ϵ>0\epsilon>0, there exists δ>0\delta>0 such that ∣Δ([t,x])∣<ϵ∣x−t∣|\Delta([t,x])| < \epsilon|x-t| for all xx within δ=δ(t)\delta = \delta(t) of tt. (Here δ\delta may depend on tt and ϵ\epsilon.)

Let BtB_t be the interval ("ball") where we can apply the inequality in the previous paragraph: that is, Bt=(t−δ(t),t+δ(t))B_t = (t-\delta(t),t+\delta(t)). Of course, as we vary over all t∈[0,1]t\in[0,1], all of [0,1][0,1] is "covered" by the BtB_t. In fact, the "completeness/compactness" (this is technical: don't worry about it) of the reals tells us that we only need finitely many of these balls: the interval [0,1][0,1] can be covered by finitely many balls Bt1,Bt2,…,BtnB_{t_1},B_{t_2},\ldots,B_{t_n}, say with 0≤t1<t2<⋯<tn≤10 \le t_1 < t_2 < \cdots < t_n \le 1, and BtiB_{t_i} having radius ri=δ(ti)r_i = \delta(t_i).

In other words, every point in [0,1][0,1] is now under the control/jurisdiction (in the territory of) one of these nn balls.

Now we can assume without loss of generality that these balls form a "chain from 00 to 11" going from left to right, so that 00 lies in Bt1B_{t_1}, Bt1B_{t_1} intersects Bt2B_{t_2} somewhere between t1t_1 and t2t_2, Bt2B_{t_2} intersect Bt3B_{t_3} somewhere between t2t_2 and t3t_3, etc., and 11 lies in BtnB_{t_n}. This is hopefully intuitive, so don't worry about the details, but the idea is that the only way two neighboring balls could ever not intersect is if one of the balls were "redundant" (contained in a larger ball, so then we could remove the redundant/smaller ball).

Now that we know all the balls "interweave" in this nice fashion, let u1u_1 be any point in both the neighboring balls Bt1,Bt2B_{t_1},B_{t_2} (between t1t_1 and t2t_2). Similarly define u2,u3,…,un−1u_2,u_3,\ldots,u_{n-1}. Also, for convenience, let u0=0u_0 = 0 and un=1u_n = 1; by assumption we know u0u_0 lies in Bt1B_{t_1} and unu_n lies in BtnB_{t_n}.

Implementing the key "telescoping" idea

Instead of breaking up the interval [0,1][0,1] at the points 0.1,0.2,…,0.90.1,0.2,\ldots,0.9, we'll break it up at the points we just constructed: 0=u0,t1,u1,t2,u2,t3,…,tn−1,un−1,tn,un=1.0=u_0,t_1,u_1,t_2,u_2,t_3,\ldots,t_{n-1},u_{n-1},t_n,u_n=1. Then neighboring points are either of the form ui−1,tiu_{i-1},t_i or ti,uit_i,u_i. In the former case, we have ∣Δ(ui−1,ti)∣<ϵ∣ui−1−ti∣=ϵ(ti−ui−1),|\Delta(u_{i-1},t_i)| < \epsilon|u_{i-1} - t_i| = \epsilon(t_i - u_{i-1}), since ui−1u_{i-1} lies in the territory BtiB_{t_i} of tit_i, and ui−1<tiu_{i-1} < t_i. Similarly, in the latter case, we have ∣Δ(ti,ui)∣<ϵ∣ui−ti∣=ϵ(ui−ti),|\Delta(t_i,u_i)| < \epsilon|u_i - t_i| = \epsilon(u_i - t_i), since uiu_i also lies in the territory BtiB_{t_i} of tit_i, and ti<uit_i < u_i.

But we also have the telescoping property Δ(0,1)=Δ(0=u0,t1)+Δ(t1,u1)+⋯+Δ(un−1,tn)+Δ(tn,un=1).\Delta(0,1) = \Delta(0=u_0,t_1) + \Delta(t_1,u_1) + \cdots + \Delta(u_{n-1},t_n) + \Delta(t_n,u_n=1). Finally, by the triangle inequality, we have ∣Δ(0,1)∣≤∣Δ(0=u0,t1)∣+∣Δ(t1,u1)∣+⋯+∣Δ(un−1,tn)∣+∣Δ(tn,un=1)∣<ϵ(t1−u0)+ϵ(u1−t1)+⋯+ϵ(tn−un−1)+ϵ(un−tn)=ϵ(un−tn+tn−un−1+⋯+u1−t1+t1−u0)=ϵ(un−u0)=ϵ(1−0)=ϵ.\begin{align*} \small{|\Delta(0,1)|} & \le |\Delta(0=u_0,t_1)| + |\Delta(t_1,u_1)| + \cdots + |\Delta(u_{n-1},t_n)| + |\Delta(t_n,u_n=1)| \\ & < \epsilon(t_1-u_0) + \epsilon(u_1-t_1) + \cdots + \epsilon(t_n-u_{n-1}) + \epsilon(u_n-t_n) \\ & = \epsilon(u_n - t_n + t_n - u_{n-1} + \cdots + u_1 - t_1 + t_1 - u_0) \\ &= \epsilon (u_n - u_0) = \epsilon (1-0) = \epsilon. \end{align*}

(Intuition: the t1−u0t_1-u_0, u1−t1u_1-t_1, etc. terms are just the lengths of the intervals we broke up [0,1][0,1] into, so their total length is just the length 1−01-0 of [0,1][0,1]. In fact, this is another "telescoping" sum, with the t1,u1,…,un−1,tnt_1,u_1,\ldots,u_{n-1},t_n all canceling out: everything but the endpoints un=1u_n=1 and u0=0u_0=0.)

So ∣Δ(0,1)∣<ϵ|\Delta(0,1)| < \epsilon. But remember how we said smallness was relative? Well, ϵ>0\epsilon>0 was an arbitrary reference threshold: we can make it as small as we like, so Δ(0,1)=0\Delta(0,1) = 0, as desired.

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Here is an interesting problem in elementary calculus:(taken from a problem solving group on Facebook.)

f:[0,1]→Rf:[0,1]\rightarrow \textbf{R} is continuous on [0,1][0,1] and differentiable on (0,1)(0,1) so that f(0)=0f(0)=0 and 0≤f′(x)≤kf(x)0\leq f'(x)\leq k f(x), where k∈R+, ∀x∈(0,1)k\in \textbf{R}^{+}, \ \forall x \in (0,1).

Prove that f(x)=0 ∀x∈(0,1)f(x)=0 \ \forall x \in (0,1).

Type a concept, like “slope” or “photosynthesis”.

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