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The function \( f\left( x\right) = \operatorname{sgn}x \) is constant and hence continuous in the neighborhood of any point \( a \in \mathbb{R} \) that is different from 0 . But in any neighborhood of 0 its oscillation equals 2 . Hence 0 is a point of discontinuity for \( \operatorname{sgn}x \) .
We remark that this function has a left-hand limit \( \mathop{\lim }\limits_{{x \rightarrow - 0}}\operatorname{sgn}x = - 1 \) and a right-hand limit \( \mathop{\lim }\limits_{{x \rightarrow + 0}}\operatorname{sgn}x = 1 \) . However, in the first place, these limits are not the same; and in the second place, neither of ...
Yes
The function \( f\left( x\right) = \left| {\operatorname{sgn}x}\right| \) has the limit \( \mathop{\lim }\limits_{{x \rightarrow 0}}\left| {\operatorname{sgn}x}\right| = 1 \) as \( x \rightarrow 0 \) , but \( f\left( 0\right) = \left| {\operatorname{sgn}0}\right| = 0 \), so that \( \mathop{\lim }\limits_{{x \rightarrow...
We remark, however, that in this case, if we were to change the value of the function at the point 0 and set it equal to 1 there, we would obtain a function that is continuous at 0 , that is, we would remove the discontinuity.
Yes
The function\n\n\[ f\\left( x\\right) = \\left\\{ \\begin{array}{ll} \\sin \\frac{1}{x}, & \\text{ for }x \\neq 0, \\\\ 0, & \\text{ for }x = 0, \\end{array}\\right.\n\]\n\nis discontinuous at 0.
Moreover, it does not even have a limit as \( x \\rightarrow 0 \), since, as was shown Example 5 in Sect. 3.2.1, \( \\mathop{\\lim }\\limits_{{x \\rightarrow 0}}\\sin \\frac{1}{x} \) does not exist.
Yes
The function\n\n\[ \n\\mathcal{D}\\left( x\\right) = \\left\\{ \\begin{array}{ll} 1, & \\text{ if }x \\in \\mathbb{Q}, \\\\ 0, & \\text{ if }x \\in \\mathbb{R} \\smallsetminus \\mathbb{Q}, \\end{array}\\right.\n\]\n\nis called the Dirichlet function. \( {}^{3} \)
This function is discontinuous at every point, and obviously all of its discontinuities are of second kind, since in every interval there are both rational and irrational numbers.
Yes
Consider the Riemann function \( \mathcal{R}\left( x\right) = \left\{ \begin{array}{ll} \frac{1}{n}, & \text{ if }x = \frac{m}{n} \in \mathbb{Q},\text{ where }\frac{m}{n}\text{ is in lowest terms,}n \in \mathbb{N}, \\ 0, & \text{ if }x \in \mathbb{R} \smallsetminus \mathbb{Q}. \end{array}\right. \)
We remark that for any point \( a \in \mathbb{R} \), any bounded neighborhood \( U\left( a\right) \) of it, and any number \( N \in \mathbb{N} \), the neighborhood \( U\left( a\right) \) contains only a finite number of rational numbers \( \frac{m}{n}, m \in \mathbb{Z}, n \in \mathbb{N} \), with \( n < N \) . By shrink...
Yes
Theorem 1 Let \( f : E \rightarrow \mathbb{R} \) be a function that is continuous at the point \( a \in E \) . Then the following statements hold.\n\n\( {1}^{0} \) The function \( f : E \rightarrow \mathbb{R} \) is bounded in some neighborhood \( {U}_{E}\left( a\right) \) of a.\n\n\( {2}^{0} \) If \( f\left( a\right) \...
Proof To prove this theorem it suffices to recall (see Sect. 4.1) that the continuity of the function \( f \) or \( g \) at a point \( a \) of its domain of definition is equivalent to the condition that the limit of this function exists over the base \( {\mathcal{B}}_{a} \) of neighborhoods of \( a \) and is equal to ...
Yes
An algebraic polynomial \( P\left( x\right) = {a}_{0}{x}^{n} + {a}_{1}{x}^{n - 1} + \cdots + {a}_{n} \) is a continuous function on \( \mathbb{R} \) .
Indeed, it follows by induction from \( {3}^{0} \) of Theorem 1 that the sum and product of any finite number of functions that are continuous at a point are themselves continuous at that point. We have verified in Examples 1 and 2 of Sect. 4.1 that the constant function and the function \( f\left( x\right) = x \) are ...
Yes
Example 2 A rational function \( R\left( x\right) = \frac{P\left( x\right) }{Q\left( x\right) } - \) a quotient of polynomials - is continuous wherever it is defined, that is, where \( Q\left( x\right) \neq 0 \).
This follows from Example 1 and assertion \( {3}^{0} \) of Theorem 1.
Yes
The composition of a finite number of continuous functions is continuous at each point of its domain of definition.
This follows by induction from assertion \( {4}^{0} \) of Theorem 1.
No
Theorem 2 (The Bolzano-Cauchy intermediate-value theorem) If a function that is continuous on a closed interval assumes values with different signs at the endpoints of the interval, then there is a point in the interval where it assumes the value 0.
Proof Let us divide the interval \( \left\lbrack {a, b}\right\rbrack \) in half. If the function does not assume the value 0 at the point of division, then it must assume opposite values at the endpoints of one of the two subintervals. In that interval we proceed as we did with the original interval, that is, we bisect...
Yes
Theorem 3 (The Weierstrass maximum-value theorem) A function that is continuous on a closed interval is bounded on that interval. Moreover there is a point in the interval where the function assumes its maximum value and a point where it assumes its minimal value.
Proof Let \( f : E \rightarrow \mathbb{R} \) be a continuous function on the closed interval \( E = \left\lbrack {a, b}\right\rbrack \) . By the local properties of a continuous function (see Theorem 1) for any point \( x \in E \) there exists a neighborhood \( U\left( x\right) \) such that the function is bounded on t...
Yes
Example 4 The function \( f\left( x\right) = \sin \frac{1}{x} \), which we have encountered many times, is continuous on the open interval \( \rbrack 0,1\lbrack = E \) . However, in every neighborhood of 0 in the set \( E \) the function assumes both values -1 and 1 . Therefore, for \( \varepsilon < 2 \), the condition...
In this connection it is useful to write out explicitly the negation of the property of uniform continuity for a function:\n\n\[ \left( {f : E \rightarrow \mathbb{R}\text{is not uniformly continuous}}\right) \mathrel{\text{:=}} \]\n\n\[ = \left( {\exists \varepsilon > 0\forall \delta > 0\exists {x}_{1} \in E\exists {x}...
Yes
If the function \( f : E \rightarrow \mathbb{R} \) is unbounded in every neighborhood of a fixed point \( {x}_{0} \in E \), then it is not uniformly continuous.
Indeed, in that case for any \( \delta > 0 \) there are points \( {x}_{1} \) and \( {x}_{2} \) in every \( \frac{\delta }{2} \) - neighborhood of \( {x}_{0} \) such that \( \left| {f\left( {x}_{1}\right) - f\left( {x}_{2}\right) }\right| > 1 \) although \( \left| {{x}_{1} - {x}_{2}}\right| < \delta \) .
Yes
The function \( f\left( x\right) = {x}^{2} \), which is continuous on \( \mathbb{R} \), is not uniformly continuous on \( \mathbb{R} \) .
In fact, at the points \( {x}_{n}^{\prime } = \sqrt{n + 1} \) and \( {x}_{n}^{\prime \prime } = \sqrt{n} \), where \( n \in \mathbb{N} \), we have \( f\left( {x}_{n}^{\prime }\right) = \) \( n + 1 \) and \( f\left( {x}_{n}^{\prime \prime }\right) = n \), so that \( f\left( {x}_{n}^{\prime }\right) - f\left( {x}_{n}^{\p...
Yes
The function \( f\left( x\right) = \sin \left( {x}^{2}\right) \), which is continuous and bounded on \( \mathbb{R} \) , is not uniformly continuous on \( \mathbb{R} \).
Indeed, at the points \( {x}_{n}^{\prime } = \sqrt{\frac{\pi }{2}\left( {n + 1}\right) } \) and \( {x}_{n}^{\prime \prime } = \sqrt{\frac{\pi }{2}n} \), where \( n \in \mathbb{N} \), we have \( \left| {f\left( {x}_{n}^{\prime }\right) - f\left( {x}_{n}^{\prime \prime }\right) }\right| = 1 \), while \( \mathop{\lim }\li...
Yes
Proposition 1 A continuous mapping \( f : E \rightarrow \mathbb{R} \) of a closed interval \( E = \left\lbrack {a, b}\right\rbrack \) into \( \mathbb{R} \) is injective if and only if the function \( f \) is strictly monotonic on \( \left\lbrack {a, b}\right\rbrack \) .
Proof If \( f \) is increasing or decreasing on any set \( E \subset \mathbb{R} \) whatsoever, the mapping \( f : E \rightarrow \mathbb{R} \) is obviously injective: at different points of \( E \) the function assumes different values.\n\nThus the more substantive part of Proposition 1 consists of the assertion that ev...
Yes
Proposition 2 Each strictly monotonic function \( f : X \rightarrow \mathbb{R} \) defined on a numerical set \( X \subset \mathbb{R} \) has an inverse \( {f}^{-1} : Y \rightarrow \mathbb{R} \) defined on the set \( Y = f\left( X\right) \) of values of \( f \) , and has the same kind of monotonicity on \( Y \) that \( f...
Proof The mapping \( f : X \rightarrow Y = f\left( X\right) \) is surjective, that is, it is a mapping of \( X \) onto \( Y \) . For definiteness assume that \( f : X \rightarrow Y \) is increasing on \( X \) . In that case\n\n\[ \forall {x}_{1} \in X\forall {x}_{2} \in X\left( {{x}_{1} < {x}_{2} \Leftrightarrow f\left...
Yes
Proposition 3 The discontinuities of a function \( f : E \rightarrow \mathbb{R} \) that is monotonic on the set \( E \subset \mathbb{R} \) can be only discontinuities of first kind.
Proof For definiteness let \( f \) be nondecreasing. Assume that \( a \in E \) is a point of discontinuity of \( f \) . Since \( a \) cannot be an isolated point of \( E, a \) must be a limit point of at least one of the two sets \( {E}_{a}^{ - } = \{ x \in E \mid x < a\} \) and \( {E}_{a}^{ + } = \{ x \in E \mid x > a...
Yes
Corollary 1 If \( a \) is a point of discontinuity of a monotonic function \( f : E \rightarrow \mathbb{R} \) , then at least one of the limits\n\n\[ \mathop{\lim }\limits_{{E \ni x \rightarrow a - 0}}f\left( x\right) = f\left( {a - 0}\right) ,\;\mathop{\lim }\limits_{{E \ni x \rightarrow a + 0}}f\left( x\right) = f\le...
Proof Indeed, if \( a \) is a point of discontinuity, it must be a limit point of the set \( E \) , and by Proposition 3 is a discontinuity of first kind. Thus at least one of the bases \( E \ni x \rightarrow a - 0 \) and \( E \ni x \rightarrow a + 0 \) is defined, and the limit of the function over that base exists. (...
Yes
Corollary 2 The set of points of discontinuity of a monotonic function is at most countable.
Proof With each point of discontinuity of a monotonic function we associate the corresponding open interval in Corollary 1 containing no values of \( f \) . These intervals are pairwise disjoint. But on the line there cannot be more than a countable number of pairwise disjoint open intervals. In fact, one can choose a ...
Yes
Proposition 4 (A criterion for continuity of a monotonic function) A monotonic function \( f : E \rightarrow \mathbb{R} \) defined on a closed interval \( E = \left\lbrack {a, b}\right\rbrack \) is continuous if and only if its set of values \( f\left( E\right) \) is the closed interval with endpoints \( f\left( a\righ...
Proof If \( f \) is a continuous monotonic function, the monotonicity implies that all the values that \( f \) assumes on the closed interval \( \left\lbrack {a, b}\right\rbrack \) lie between the values \( f\left( a\right) \) and \( f\left( b\right) \) that it assumes at the endpoints. By continuity, the function must...
Yes
Theorem 5 (The inverse function theorem) A function \( f : X \rightarrow \mathbb{R} \) that is strictly monotonic on a set \( X \subset \mathbb{R} \) has an inverse \( {f}^{-1} : Y \rightarrow \mathbb{R} \) defined on the set \( Y = f\left( X\right) \) of values of \( f \) . The function \( {f}^{-1} : Y \rightarrow \ma...
Proof The assertion that the set \( Y = f\left( X\right) \) is the closed interval with endpoints \( f\left( a\right) \) and \( f\left( b\right) \) when \( X = \left\lbrack {a, b}\right\rbrack \) and \( f \) is continuous follows from Proposition 4 proved above. It remains to be verified that \( {f}^{-1} : Y \rightarro...
No
To prove that the function \( x = \arctan y \) is continuous at each point \( {y}_{0} \) of its domain of definition.
We take the point \( {x}_{0} = \arctan {y}_{0} \) and a closed interval \( \left\lbrack {{x}_{0} - \varepsilon ,{x}_{0} + \varepsilon }\right\rbrack \) containing \( {x}_{0} \) and contained in the open interval \( \rbrack - \frac{\pi }{2},\frac{\pi }{2}\lbrack \) . If \( {x}_{0} - \varepsilon = \arctan \left( {{y}_{0}...
Yes
Example 1 Let \( f\left( x\right) = \sin x \) . We shall show that \( {f}^{\prime }\left( x\right) = \cos x \) .
Proof\n\n\[\n\mathop{\lim }\limits_{{h \rightarrow 0}}\frac{\sin \left( {x + h}\right) - \sin x}{h} = \mathop{\lim }\limits_{{h \rightarrow 0}}\frac{2\sin \left( \frac{h}{2}\right) \cos \left( {x + \frac{h}{2}}\right) }{h} =\n\]\n\n\[ =\mathop{\lim }\limits_{{h \rightarrow 0}}\cos \left( {x + \frac{h}{2}}\right) \cdot ...
Yes
Example 2 We shall show that \( {\cos }^{\prime }x = - \sin x \) .
Proof\n\n\[ \mathop{\lim }\limits_{{h \rightarrow 0}}\frac{\cos \left( {x + h}\right) - \cos x}{h} = \mathop{\lim }\limits_{{h \rightarrow 0}}\frac{-2\sin \left( \frac{h}{2}\right) \sin \left( {x + \frac{h}{2}}\right) }{h} = \]\n\n\[ = - \mathop{\lim }\limits_{{h \rightarrow 0}}\sin \left( {x + \frac{h}{2}}\right) \cdo...
Yes
Example 3 We shall show that if \( f\left( t\right) = r\cos {\omega t} \), then \( {f}^{\prime }\left( t\right) = - {r\omega }\sin {\omega t} \) .
Proof\n\n\[ \mathop{\lim }\limits_{{h \rightarrow 0}}\frac{r\cos \omega \left( {t + h}\right) - r\cos {\omega t}}{h} = r\mathop{\lim }\limits_{{h \rightarrow 0}}\frac{-2\sin \left( \frac{\omega h}{2}\right) \sin \omega \left( {t + \frac{h}{2}}\right) }{h} = \]\n\n\[ = - {r\omega }\mathop{\lim }\limits_{{h \rightarrow 0...
Yes
Example 4 If \( f\left( t\right) = r\sin {\omega t} \), then \( {f}^{\prime }\left( t\right) = {r\omega }\cos {\omega t} \) .
Proof The proof is analogous to that of Examples 1 and 3.
No
Suppose a point mass is moving in a plane and that in some given coordinate system its motion is described by differentiable functions of time\n\n\\[ \nx = x\\left( t\\right) ,\\;y = y\\left( t\\right) \n\\]\n\nor, what is the same, by a vector\n\n\\[ \n\\mathbf{r}\\left( t\\right) = \\left( {x\\left( t\\right), y\\lef...
Thus, in the sense of the physical problem, functions \\( x\\left( t\\right) \\) and \\( y\\left( t\\right) \\) that describe the motion of a point mass must have both first and second derivatives.\n\nIn particular, let us consider the uniform motion of a point along a circle of radius \\( r \\) . Let \\( \\omega \\) b...
Yes
Example 6 (The optic property of a parabolic mirror) Let us consider the parabola \( y = \frac{1}{2p}{x}^{2}\left( {p > 0\text{, see Fig. 5.4}}\right) \), and construct the tangent to it at the point \( \left( {{x}_{0},{y}_{0}}\right) = \) \( \left( {{x}_{0},\frac{1}{2p}{x}_{0}^{2}}\right) \) .
Since \( f\left( x\right) = \frac{1}{2p}{x}^{2} \), we have\n\n\[ \n{f}^{\prime }\left( {x}_{0}\right) = \mathop{\lim }\limits_{{x \rightarrow {x}_{0}}}\frac{\frac{1}{2p}{x}^{2} - \frac{1}{2p}{x}_{0}^{2}}{x - {x}_{0}} = \frac{1}{2p}\mathop{\lim }\limits_{{x \rightarrow {x}_{0}}}\left( {x + {x}_{0}}\right) = \frac{1}{p}...
Yes
Example 7 With this example we shall show that the tangent is merely the best linear approximation to the graph of a function in a neighborhood of the point of tangency and does not necessarily have only one point in common with the curve, as was the case with a circle, or in general, with convex curves. (For convex cu...
Since\n\n\\[ {f}^{\\prime }\\left( 0\\right) = \\mathop{\\lim }\\limits_{{x \\rightarrow 0}}\\frac{{x}^{2}\\sin \\frac{1}{x} - 0}{x - 0} = \\mathop{\\lim }\\limits_{{x \\rightarrow 0}}x\\sin \\frac{1}{x} = 0,\\]\n\nthe tangent has the equation \\( y - 0 = 0 \\cdot \\left( {x - 0}\\right) \\), or simply \\( y = 0 \\) .\...
Yes
Example 8 Let \( f\left( x\right) = \left| x\right| \) ,(Fig. 5.6). Then at the point \( {x}_{0} = 0 \) we have
\[ \mathop{\lim }\limits_{{x \rightarrow {x}_{0} - 0}}\frac{f\left( x\right) - f\left( {x}_{0}\right) }{x - {x}_{0}} = \mathop{\lim }\limits_{{x \rightarrow - 0}}\frac{\left| x\right| - 0}{x - 0} = \mathop{\lim }\limits_{{x \rightarrow - 0}}\frac{-x}{x} = - 1, \] \[ \mathop{\lim }\limits_{{x \rightarrow {x}_{0} + 0}}\f...
Yes
We shall show that \( {\mathrm{e}}^{x + h} - {\mathrm{e}}^{x} = {\mathrm{e}}^{x}h + o\left( h\right) \) as \( h \rightarrow 0 \) .
\[ {\mathrm{e}}^{x + h} - {\mathrm{e}}^{x} = {\mathrm{e}}^{x}\left( {{\mathrm{e}}^{h} - 1}\right) = {\mathrm{e}}^{x}\left( {h + o\left( h\right) }\right) = {\mathrm{e}}^{x}h + o\left( h\right) . \] Here we have used the formula \( {\mathrm{e}}^{h} - 1 = h + o\left( h\right) \) obtained in Example 39 of Sect. 3.2.4.
Yes
If \( a > 0 \), then \( {a}^{x + h} - {a}^{x} = {a}^{h}\left( {\ln a}\right) h + o\left( h\right) \) as \( h \rightarrow 0 \) . Thus \( \mathrm{d}{a}^{x} = \) \( {a}^{x}\left( {\ln a}\right) \mathrm{d}x \) and \( \frac{\mathrm{d}{a}^{x}}{\mathrm{\;d}x} = {a}^{x}\ln a \) .
\[ {a}^{x + h} - {a}^{x} = {a}^{x}\left( {{a}^{h} - 1}\right) = {a}^{x}\left( {{\mathrm{e}}^{h\ln a} - 1}\right) = \] \[ = {a}^{x}\left( {h\ln a + o\left( {h\ln a}\right) }\right) = {a}^{x}\left( {\ln a}\right) h + o\left( h\right) \;\text{ as }h \rightarrow 0. \]
Yes
If \( x \neq 0 \), then \( \ln \left| {x + h}\right| - \ln \left| x\right| = \frac{1}{x}h + o\left( h\right) \) as \( h \rightarrow 0 \) . Thus \( \mathrm{d}\ln \left| x\right| = \) \( \frac{1}{x}\mathrm{\;d}x \) and \( \frac{\mathrm{d}\ln \left| x\right| }{\mathrm{d}x} = \frac{1}{x} \) .
\[ \ln \left| {x + h}\right| - \ln \left| x\right| = \ln \left| {1 + \frac{h}{x}}\right| . \] For \( \left| h\right| < \left| x\right| \) we have \( \left| {1 + \frac{h}{x}}\right| = 1 + \frac{h}{x} \), and so for sufficiently small values of \( h \) we can write \[ \ln \left| {x + h}\right| - \ln \left| x\right| = \ln...
Yes
If \( x \neq 0 \) and \( 0 < a \neq 1 \), then \( {\log }_{a}\left| {x + h}\right| - {\log }_{a}\left| x\right| = \frac{1}{x\ln a}h + o\left( h\right) \) as \( h \rightarrow 0 \) . Thus, \( \mathrm{d}{\log }_{a}\left| x\right| = \frac{1}{x\ln a}\mathrm{\;d}x \) and \( \frac{\mathrm{d}{\log }_{a}\left| x\right| }{\mathr...
\[ {\log }_{a}\left| {x + h}\right| - {\log }_{a}\left| x\right| = {\log }_{a}\left| {1 + \frac{h}{x}}\right| = {\log }_{a}\left( {1 + \frac{h}{x}}\right) = \] \[ = \frac{1}{\ln a}\ln \left( {1 + \frac{h}{x}}\right) = \frac{1}{\ln a}\left( {\frac{h}{x} + o\left( \frac{h}{x}\right) }\right) = \frac{1}{x\ln a}h + o\left(...
Yes
Theorem 1 If functions \( f : X \rightarrow \mathbb{R} \) and \( g : X \rightarrow \mathbb{R} \) are differentiable at a point \( x \in X \), then\n\na) their sum is differentiable at \( x \), and\n\n\[{\left( f + g\right) }^{\prime }\left( x\right) = \left( {{f}^{\prime } + {g}^{\prime }}\right) \left( x\right)\]
Proof In the proof we shall rely on the definition of a differentiable function and the properties of the symbol \( o\left( \cdot \right) \) proved in Sect. 3.2.4.\n\n---\n\n\[ \text{a)}\left( {f + g}\right) \left( {x + h}\right) - \left( {f + g}\right) \left( x\right) =\n\]\n\n\[= \left( {f\left( {x + h}\right) + g\le...
Yes
Corollary 1 The derivative of a linear combination of differentiable functions equals the same linear combination of the derivatives of these functions.
Proof Since a constant function is obviously differentiable and has a derivative equal to 0 at every point, taking \( f \equiv \) const \( = c \) in statement b) of Theorem 1, we find \( {\left( cg\right) }^{\prime }\left( x\right) = c{g}^{\prime }\left( x\right) \). Now, using statement a) of Theorem 1, we can write \...
Yes
Corollary 2 If the functions \( {f}_{1},\ldots ,{f}_{n} \) are differentiable at \( x \), then\n\n\[ \n{\left( {f}_{1}\cdots {f}_{n}\right) }^{\prime }\left( x\right) = {f}_{1}^{\prime }\left( x\right) {f}_{2}\left( x\right) \cdots {f}_{n}\left( x\right) +\n\]\n\n\[ \n+ {f}_{1}\left( x\right) {f}_{2}^{\prime }\left( x\...
Proof For \( n = 1 \) the statement is obvious.\n\nIf it holds for some \( n \in \mathbb{N} \), then by statement b) of Theorem 1 it also holds for \( \left( {n + 1}\right) \in \mathbb{N} \) . By the principle of induction, we conclude that the formula is valid for any \( n \in \mathbb{N} \) .
No
Corollary 3 It follows from the relation between the derivative and the differential that Theorem 1 can also be written in terms of differentials. To be specific:\n\na) \( \mathrm{d}\left( {f + g}\right) \left( x\right) = \mathrm{d}f\left( x\right) + \mathrm{d}g\left( x\right) \) ;\n\nb) \( \mathrm{d}\left( {f \cdot g}...
Proof Let us verify, for example, statement a).\n\n\[ \mathrm{d}\left( {f + g}\right) \left( x\right) h = {\left( f + g\right) }^{\prime }\left( x\right) h = \left( {{f}^{\prime } + {g}^{\prime }}\right) \left( x\right) h = \]\n\n\[ = \left( {{f}^{\prime }\left( x\right) + {g}^{\prime }\left( x\right) }\right) h = {f}^...
No
Example 1 (Invariance of the definition of velocity) We are now in a position to verify that the instantaneous velocity vector of a point mass defined in Sect. 5.1.1 is independent of the Cartesian coordinate system used to define it. In fact we shall verify this for all affine coordinate systems.
Let \( \left( {{x}^{1},{x}^{2}}\right) \) and \( \left( {{\widetilde{x}}^{1},{\widetilde{x}}^{2}}\right) \) be the coordinates of the same point of the plane in two different coordinate systems connected by the relations\n\n\[ \n{\widetilde{x}}^{1} = {a}_{1}^{1}{x}^{1} + {a}_{2}^{1}{x}^{2} + {b}^{1}, \n\]\n\n(5.26)\n\n...
Yes
Let \( f\left( x\right) = \tan x \). We shall show that \( {f}^{\prime }\left( x\right) = \frac{1}{{\cos }^{2}x} \) at every point where \( \cos x \neq 0 \), that is, in the domain of definition of the function \( \tan x = \frac{\sin x}{\cos x} \).
It was shown in Examples 1 and 2 of Sect. 5.1 that \( {\sin }^{\prime }\left( x\right) = \cos x \) and \( {\cos }^{\prime }x = \) \( - \sin x \), so that by statement c) of Theorem 1 we find, when \( \cos x \neq 0 \), \[ {\tan }^{\prime }x = {\left( \frac{\sin }{\cos }\right) }^{\prime }\left( x\right) = \frac{{\sin }^...
Yes
Example 3 \( {\cot }^{\prime }x = - \frac{1}{{\sin }^{2}x} \) wherever \( \sin x \neq 0 \), that is, in the domain of definition of \( \cot x = \frac{\cos x}{\sin x} \) .
Indeed, \[ {\cot }^{\prime }x = {\left( \frac{\cos }{\sin }\right) }^{\prime }\left( x\right) = \frac{{\cos }^{\prime }x\sin x - \cos x{\sin }^{\prime }x}{{\sin }^{2}x} = \] \[ = \frac{-\sin x\sin x - \cos x\cos x}{{\sin }^{2}x} = - \frac{1}{{\sin }^{2}x}. \]
Yes
Example 4 If \( P\left( x\right) = {c}_{0} + {c}_{1}x + \cdots + {c}_{n}{x}^{n} \) is a polynomial, then \( {P}^{\prime }\left( x\right) = {c}_{1} + \) \( 2{c}_{2}x + \cdots + n{c}_{n}{x}^{n - 1} \) .
Indeed, since \( \frac{\mathrm{d}x}{\mathrm{\;d}x} = 1 \), by Corollary 2 we have \( \frac{\mathrm{d}{x}^{n}}{\mathrm{\;d}x} = n{x}^{n - 1} \), and the statement now follows from Corollary 1.
Yes
Corollary 4 The derivative \( {\left( g \circ f\right) }^{\prime }\left( x\right) \) of the composition of differentiable real-valued functions equals the product \( {g}^{\prime }\left( {f\left( x\right) }\right) \cdot {f}^{\prime }\left( x\right) \) of the derivatives of these functions computed at the corresponding p...
There is a strong temptation to give a short proof of this last statement in Leibniz' notation for the derivative, in which if \( z = z\left( y\right) \) and \( y = y\left( x\right) \), we have\n\n\[ \frac{\mathrm{d}z}{\mathrm{\;d}x} = \frac{\mathrm{d}z}{\mathrm{\;d}y} \cdot \frac{\mathrm{d}y}{\mathrm{\;d}x} \]\n\nwhic...
Yes
Corollary 5 If the composition \( \left( {{f}_{n} \circ \cdots \circ {f}_{1}}\right) \left( x\right) \) of differentiable functions \( {y}_{1} = \) \( {f}_{1}\left( x\right) ,\ldots ,{y}_{n} = {f}_{n}\left( {y}_{n - 1}\right) \) exists, then\n\n\[{\left( {f}_{n} \circ \cdots \circ {f}_{1}\right) }^{\prime }\left( x\rig...
Proof The statement is obvious if \( n = 1 \) .\n\nIf it holds for some \( n \in \mathbb{N} \), then by Theorem 2 it also holds for \( n + 1 \), so that by the principle of induction, it holds for any \( n \in \mathbb{N} \) .
Yes
Let us show that for \( \alpha \in \mathbb{R} \) we have \( \frac{\mathrm{d}{x}^{\alpha }}{\mathrm{d}x} = \alpha {x}^{\alpha - 1} \) in the domain \( x > 0 \) , that is, \( \mathrm{d}{x}^{\alpha } = \alpha {x}^{\alpha - 1}\mathrm{\;d}x \) and\n\n\[{\left( x + h\right) }^{\alpha } - {x}^{\alpha } = \alpha {x}^{\alpha - ...
Proof We write \( {x}^{\alpha } = {\mathrm{e}}^{\alpha \ln x} \) and apply the theorem, taking account of the results of Examples 9 and 11 from Sect. 5.1 and statement b) of Theorem 1.\n\nLet \( g\left( y\right) = {\mathrm{e}}^{y} \) and \( y = f\left( x\right) = \alpha \ln \left( x\right) \) . Then \( {x}^{\alpha } = ...
Yes
The derivative of the logarithm of the absolute value of a differentiable function is often called its logarithmic derivative.
Since \( F\left( x\right) = \ln \left| {f\left( x\right) }\right| = \left( {\ln \circ \mid \mid \circ f}\right) \left( x\right) \), by Example 11 of Sect. 5.1, we have \( {F}^{\prime }\left( x\right) = {\left( \ln \left| f\right| \right) }^{\prime }\left( x\right) = \frac{{f}^{\prime }\left( x\right) }{f\left( x\right)...
Yes
Example 7 (The absolute and relative errors in the value of a differentiable function caused by errors in the data for the argument) If the function \( f \) is differentiable at \( x \), then\n\n\[ f\left( {x + h}\right) - f\left( x\right) = {f}^{\prime }\left( x\right) h + \alpha \left( {x;h}\right) ,\]\n\nwhere \( \a...
Thus, if in computing the value \( f\left( x\right) \) of a function, the argument \( x \) is determined with absolute error \( h \), the absolute error \( \left| {f\left( {x + h}\right) - f\left( x\right) }\right| \) in the value of the function due to this error in the argument can be replaced for small values of \( ...
Yes
Example 8 Let us differentiate a function \( u{\left( x\right) }^{v\left( x\right) } \), where \( u\left( x\right) \) and \( v\left( x\right) \) are differentiable functions and \( u\left( x\right) > 0 \).
We write \( u{\left( x\right) }^{v\left( x\right) } = {\mathrm{e}}^{v\left( x\right) \ln u\left( x\right) } \) and use Corollary 5 . Then\n\n\[ \frac{\mathrm{d}{\mathrm{e}}^{v\left( x\right) \ln u\left( x\right) }}{\mathrm{d}x} = {\mathrm{e}}^{v\left( x\right) \ln u\left( x\right) }\left( {{v}^{\prime }\left( x\right) ...
Yes
Theorem 3 (The derivative of an inverse function) Let the functions \( f : X \rightarrow Y \) and \( {f}^{-1} : Y \rightarrow X \) be mutually inverse and continuous at points \( {x}_{0} \in X \) and \( f\left( {x}_{0}\right) = \) \( {y}_{0} \in Y \) respectively. If \( f \) is differentiable at \( {x}_{0} \) and \( {f...
Proof Since the functions \( f : X \rightarrow Y \) and \( {f}^{-1} : Y \rightarrow X \) are mutually inverse, the quantities \( f\left( x\right) - f\left( {x}_{0}\right) \) and \( {f}^{-1}\left( y\right) - {f}^{-1}\left( {y}_{0}\right) \), where \( y = f\left( x\right) \), are both nonzero if \( x \neq {x}_{0} \) . In...
Yes
We shall show that \( {\arcsin }^{\prime }y = \frac{1}{\sqrt{1 - {y}^{2}}} \) for \( \left| y\right| < 1 \) .
The functions \( \sin \) : \( \left\lbrack {-\pi /2,\pi /2}\right\rbrack \rightarrow \left\lbrack {-1,1}\right\rbrack \) and arcsin : \( \left\lbrack {-1,1}\right\rbrack \rightarrow \left\lbrack {-\pi /2,\pi /2}\right\rbrack \) are mutually inverse and continuous (see Example 8 of Sect. 4.2) and \( {\sin }^{\prime }\le...
Yes
\[ {\arccos }^{\prime }y = - \frac{1}{\sqrt{1 - {y}^{2}}}\;\text{ for }\left| y\right| < 1 \]
\[ {\arccos }^{\prime }y = \frac{1}{{\cos }^{\prime }x} = - \frac{1}{\sin x} = - \frac{1}{\sqrt{1 - {\cos }^{2}x}} = - \frac{1}{\sqrt{1 - {y}^{2}}}. \]
Yes
Example 11 \( {\arctan }^{\prime }y = \frac{1}{1 + {y}^{2}}, y \in \mathbb{R} \) .
Indeed, \[ {\arctan }^{\prime }y = \frac{1}{{\tan }^{\prime }x} = \frac{1}{\left( \frac{1}{{\cos }^{2}x}\right) } = {\cos }^{2}x = \frac{1}{1 + {\tan }^{2}x} = \frac{1}{1 + {y}^{2}}. \]
Yes
Example 12 \( {\operatorname{arccot}}^{\prime }y = - \frac{1}{1 + {y}^{2}}, y \in \mathbb{R} \) .
Indeed\n\n\[ \n{\operatorname{arccot}}^{\prime }y = \frac{1}{{\cot }^{\prime }x} = \frac{1}{\left( -\frac{1}{{\sin }^{2}x}\right) } = - {\sin }^{2}x = - \frac{1}{1 + {\cot }^{2}x} = - \frac{1}{1 + {y}^{2}}. \n\]
Yes
Example 13 We already know (see Examples 10 and 12 of Sect. 5.1) that the functions \( y = f\left( x\right) = {a}^{x} \) and \( x = {f}^{-1}\left( y\right) = {\log }_{a}y \) have the derivatives \( {f}^{\prime }\left( x\right) = {a}^{x}\ln a \) and \( {\left( {f}^{-1}\right) }^{\prime }\left( y\right) = \frac{1}{y\ln a...
Let us see how this is consistent with Theorem 3:\n\n\[ \n{\left( {f}^{-1}\right) }^{\prime }\left( y\right) = \frac{1}{{f}^{\prime }\left( x\right) } = \frac{1}{{a}^{x}\ln a} = \frac{1}{y\ln a}, \]\n\n\[ \n{f}^{\prime }\left( x\right) = \frac{1}{{\left( {f}^{-1}\right) }^{\prime }\left( y\right) } = \frac{1}{\left( \f...
Yes
The hyperbolic and inverse hyperbolic functions and their derivatives.
The functions\n\n\\[ \n\\sinh x = \\frac{1}{2}\\left( {{\\mathrm{e}}^{x} - {\\mathrm{e}}^{-x}}\\right) \n\\]\n\n\\[ \n\\cosh x = \\frac{1}{2}\\left( {{\\mathrm{e}}^{x} + {\\mathrm{e}}^{-x}}\\right) \n\\]\n\nare called respectively the hyperbolic sine and hyperbolic cosine \\( {}^{8} \\) of \\( x \\) .\n\nThese function...
Yes
Example 15 (The law of addition of velocities) The motion of a point along a line is completely determined if we know the coordinate \( x \) of the point in our chosen coordinate system (the real line) at each instant \( t \) in a system we have chosen for measuring time. Thus the pair of numbers \( \left( {x, t}\right...
Suppose we wish to express the motion of this point in terms of a different coordinate system \( \left( {\widetilde{x},\widetilde{t}}\right) \). For example, the new real line may be moving uniformly with speed \( - v \) relative to the first system. (The velocity vector in this case may be identified with the single n...
Yes
Let \( u\left( x\right) \) and \( v\left( x\right) \) be functions having derivatives up to order \( n \) inclusive on a common set \( E \) . The following formula of Leibniz holds for the \( n \) th derivative of their product:\n\n\[{\left( uv\right) }^{\left( n\right) } = \mathop{\sum }\limits_{{m = 0}}^{n}\left( \be...
Leibniz' formula bears a strong resemblance to Newton's binomial formula, and in fact the two are directly connected. Proof For \( n = 1 \) formula (5.44) agrees with the rule already established for the derivative of a product.\n\nIf the functions \( u \) and \( v \) have derivatives up to order \( n + 1 \) inclusive,...
Yes
If \( {P}_{n}\left( x\right) = {c}_{0} + {c}_{1}x + \cdots + {c}_{n}{x}^{n} \), then
\[ {P}_{n}\left( 0\right) = {c}_{0} \] \[ {P}_{n}^{\prime }\left( x\right) = {c}_{1} + 2{c}_{2}x + \cdots + n{c}_{n}{x}^{n - 1}\text{ and }{P}_{n}^{\prime }\left( 0\right) = {c}_{1}, \] \[ {P}_{n}^{\prime \prime }\left( x\right) = 2{c}_{2} + 3 \cdot 2{c}_{3}x + \cdots + n\left( {n - 1}\right) {c}_{n}{x}^{n - 2}\text{ a...
Yes
Using Leibniz' formula and the fact that all the derivatives of a polynomial of order higher than the degree of the polynomial are zero, we can find the \( n \) th derivative of \( f\left( x\right) = {x}^{2}\sin x \) :
\[ {f}^{\left( n\right) }\left( x\right) = {\sin }^{\left( n\right) }\left( x\right) \cdot {x}^{2} + \left( \begin{array}{l} n \\ 1 \end{array}\right) {\sin }^{\left( n - 1\right) }x \cdot {2x} + \left( \begin{array}{l} n \\ 2 \end{array}\right) {\sin }^{\left( n - 2\right) }x \cdot 2 = \] \[ = {x}^{2}\sin \left( {x + ...
Yes
Let \( f\left( x\right) = \arctan x \). Let us find the values \( {f}^{\left( n\right) }\left( 0\right) \left( {n = 1,2,\ldots }\right) \).
Since \( {f}^{\prime }\left( x\right) = \frac{1}{1 + {x}^{2}} \), it follows that \( \left( {1 + {x}^{2}}\right) {f}^{\prime }\left( x\right) = 1 \).\n\nApplying Leibniz' formula to this last equality, we find the recursion relation\n\n\[ \left( {1 + {x}^{2}}\right) {f}^{\left( n + 1\right) }\left( x\right) + {2nx}{f}^...
Yes
If \( x\left( t\right) = {\alpha t} + \beta \), then \( \dot{x}\left( t\right) = \alpha \) and \( \ddot{x}\left( t\right) \equiv 0 \), that is, the acceleration in a uniform motion is zero.
We shall soon verify that if the second derivative equals zero, then the function itself has the form \( {\alpha t} + \beta \) . Thus, in uniform motions, and only in uniform motions, is the acceleration equal to zero.
No
Example 29 (The second derivative of a simple implicit function) Let \( y = y\left( t\right) \) and \( x = x\left( t\right) \) be twice-differentiable functions. Assume that the function \( x = x\left( t\right) \) has a differentiable inverse function \( t = t\left( x\right) \) . Then the quantity \( y\left( t\right) \...
By the rule for differentiating such a function, studied in Sect. 5.2.5, we have\n\n\[ \n{y}_{x}^{\prime } = \frac{{y}_{t}^{\prime }}{{x}_{t}^{\prime }} \n\] \nso that \n\n\[ \n{y}_{xx}^{\prime \prime } = {\left( {y}_{x}^{\prime }\right) }_{x}^{\prime } = \frac{{\left( {y}_{x}^{\prime }\right) }_{t}^{\prime }}{{x}_{t}^...
Yes
Example 1 Let\n\n\\[ \nf\\left( x\\right) = \\left\\{ \\begin{array}{ll} {x}^{2}, & \\text{ if } - 1 \\leq x < 2 \\\\ 4, & \\text{ if }2 \\leq x \\end{array}\\right.\n\\]\n\n(see Fig. 5.8). For this function
\n\n\\( x = - 1 \\) is a strict local maximum;\n\n\\( x = 0 \\) is a strict local minimum;\n\n\\( x = 2 \\) is a local maximum;\n\nthe points \\( x > 2 \\) are all local extrema, being simultaneously maxima and minima, since the function is locally constant at these points.
Yes
Example 2 Let \( f\left( x\right) = \sin \frac{1}{x} \) on the set \( E = \mathbb{R} \smallsetminus 0 \).
The points \( x = {\left( \frac{\pi }{2} + 2k\pi \right) }^{-1}, k \in \mathbb{Z} \), are strict local maxima, and the points \( x = {\left( -\frac{\pi }{2} + 2k\pi \right) }^{-1}, k \in \mathbb{Z} \), are strict local minima for \( f\left( x\right) \) (see Fig. 4.1).
Yes
Lemma 1 (Fermat) If a function \( f : E \rightarrow \mathbb{R} \) is differentiable at an interior extremum, \( {x}_{0} \in E \), then its derivative at \( {x}_{0} \) is \( 0 : {f}^{\prime }\left( {x}_{0}\right) = 0 \) .
Proof By definition of differentiability at \( {x}_{0} \) we have\n\n\[ f\left( {{x}_{0} + h}\right) - f\left( {x}_{0}\right) = {f}^{\prime }\left( {x}_{0}\right) h + \alpha \left( {{x}_{0};h}\right) h, \]\n\nwhere \( \alpha \left( {{x}_{0};h}\right) \rightarrow 0 \) as \( h \rightarrow x,{x}_{0} + h \in E \) .\n\nLet ...
Yes
Proposition 1 (Rolle’s \( {}^{10} \) theorem) If a function \( f : \left\lbrack {a, b}\right\rbrack \rightarrow \mathbb{R} \) is continuous on a closed interval \( \left\lbrack {a, b}\right\rbrack \) and differentiable on the open interval \( \rbrack a, b\lbrack \) and \( f\left( a\right) = f\left( b\right) \) , then t...
Proof Since the function \( f \) is continuous on \( \left\lbrack {a, b}\right\rbrack \), there exist points \( {x}_{m},{x}_{M} \in \) \( \left\lbrack {a, b}\right\rbrack \) at which it assumes its minimal and maximal values respectively. If \( f\left( {x}_{m}\right) = \) \( f\left( {x}_{M}\right) \), then the function...
Yes
Theorem 1 (Lagrange’s finite-increment theorem) If a function \( f : \\left\\lbrack {a, b}\\right\\rbrack \\rightarrow \\mathbb{R} \) is continuous on a closed interval \( \\left\\lbrack {a, b}\\right\\rbrack \) and differentiable on the open interval, \( \\rbrack a, b\\lbrack \), there exists a point \( \\xi \\in \\rb...
Proof Consider the auxiliary function \[ F\\left( x\\right) = f\\left( x\\right) - \\frac{f\\left( b\\right) - f\\left( a\\right) }{b - a}\\left( {x - a}\\right) ,\] which is obviously continuous on the closed interval \( \\left\\lbrack {a, b}\\right\\rbrack \) and differentiable on the open interval \( \\rbrack a, b\\...
Yes
Corollary 1 (Criterion for monotonicity of a function) If the derivative of a function is nonnegative (resp. positive) at every point of an open interval, then the function is nondecreasing (resp. increasing) on that interval.
Proof Indeed, if \( {x}_{1} \) and \( {x}_{2} \) are two points of the interval and \( {x}_{1} < {x}_{2} \), that is, \( {x}_{2} - \) \( {x}_{1} > 0 \), then by formula (5.46)\n\n\[ f\left( {x}_{2}\right) - f\left( {x}_{1}\right) = {f}^{\prime }\left( \xi \right) \left( {{x}_{2} - {x}_{1}}\right) ,\;\text{ where }{x}_{...
Yes
A function that is continuous on a closed interval \( \left\lbrack {a, b}\right\rbrack \) is constant on it if and only if its derivative equals zero at every point of the interval \( \left\lbrack {a, b}\right\rbrack \) (or only the open interval \( \rbrack a, b\lbrack \) ).
Only the fact that \( {f}^{\prime }\left( x\right) \equiv 0 \) on \( \rbrack a, b\lbrack \) implies that \( f\left( {x}_{1}\right) = f\left( {x}_{2}\right) \) for all \( {x}_{1},{x}_{2}, \in \left\lbrack {a, b}\right\rbrack \) is of interest. But this follows from Lagrange’s formula, according to which\n\n\[ f\left( {x...
No
Proposition 2 (Cauchy’s finite-increment theorem) Let \( x = x\left( t\right) \) and \( y = y\left( t\right) \) be functions that are continuous on a closed interval \( \left\lbrack {\alpha ,\beta }\right\rbrack \) and differentiable on the open interval \( \rbrack \alpha ,\beta \lbrack \) . Then there exists a point \...
Proof The function \( F\left( t\right) = x\left( t\right) \left( {y\left( \beta \right) - y\left( \alpha \right) }\right) - y\left( t\right) \left( {x\left( \beta \right) - x\left( \alpha \right) }\right) \) satisfies the hypotheses of Rolle’s theorem on the closed interval \( \left\lbrack {\alpha ,\beta }\right\rbrack...
Yes
Theorem 2 If the function \( f \) is continuous on the closed interval with end-points \( {x}_{0} \) and \( x \) along with its first \( n \) derivatives, and it has a derivative of order \( n + 1 \) at the interior points of this interval, then for any function \( \varphi \) that is continuous on this closed interval ...
Proof On the closed interval \( I \) with endpoints \( {x}_{0} \) and \( x \) we consider the auxiliary function\n\n\[ \nF\left( t\right) = f\left( x\right) - {P}_{n}\left( {t;x}\right) \n\]\n\nof the argument \( t \) . We now write out the definition of the function \( F\left( t\right) \) in more detail:\n\n\[ \nF\lef...
Yes
For the function \( f\left( x\right) = {\mathrm{e}}^{x} \) with \( {x}_{0} = 0 \) Taylor’s formula has the form\n\n\[ \n{\mathrm{e}}^{x} = 1 + \frac{1}{1!}x + \frac{1}{2!}{x}^{2} + \cdots + \frac{1}{n!}{x}^{n} + {r}_{n}\left( {0;x}\right) ,\n\]
and by (5.56) we can assume that\n\n\[ \n{r}_{n}\left( {0;x}\right) = \frac{1}{\left( {n + 1}\right) !}{\mathrm{e}}^{\xi } \cdot {x}^{n + 1},\n\]\n\nwhere \( \left| \xi \right| < \left| x\right| \) .\n\nThus\n\n\[ \n\left| {{r}_{n}\left( {0;x}\right) }\right| = \frac{1}{\left( {n + 1}\right) !}{\mathrm{e}}^{\xi } \cdot...
Yes
We obtain the expansion of the function \( {a}^{x} \) for any \( a,0 < a, a \neq 1 \)
\[ {a}^{x} = 1 + \frac{\ln a}{1!}x + \frac{{\ln }^{2}a}{2!}{x}^{2} + \cdots + \frac{{\ln }^{n}a}{n!}{x}^{n} + \cdots . \]
Yes
Example 5 Let \( f\left( x\right) = \sin x \) . We know (see Example 18 of Sect. 5.2.6) that \( {f}^{\left( n\right) }\left( x\right) = \sin \left( {x + \frac{\pi }{2}n}\right), n \in \mathbb{N} \), and so by Lagrange’s formula (5.56) with \( {x}_{0} = 0 \) and any \( x \in \mathbb{R} \) we find
\[ {r}_{n}\left( {0;x}\right) = \frac{1}{\left( {n + 1}\right) !}\sin \left( {\xi + \frac{\pi }{2}\left( {n + 1}\right) }\right) {x}^{n + 1}, \] (5.60) from which it follows that \( {r}_{n}\left( {0;x}\right) \) tends to zero for any \( x \in \mathbb{R} \) as \( n \rightarrow \infty \) . Thus we have the expansion \[ \...
Yes
Example 6 Similarly, for the function \( f\left( x\right) = \cos x \), we obtain
\[ {r}_{n}\left( {0;x}\right) = \frac{1}{\left( {n + 1}\right) !}\cos \left( {\xi + \frac{\pi }{2}\left( {n + 1}\right) }\right) {x}^{n + 1} \] (5.62) and \[ \cos x = 1 - \frac{1}{2!}{x}^{2} + \frac{1}{4!}{x}^{4} - \cdots + \frac{{\left( -1\right) }^{n}}{\left( {2n}\right) !}{x}^{2n} + \cdots \] (5.63) for \( x \in \ma...
Yes
Since \( {\sinh }^{\prime }x = \cosh x \) and \( {\cosh }^{\prime }x = \sinh x \), formula (5.56) yields the following expression for the remainder in the Taylor series of \( f\left( x\right) = \sinh x \) :
\[ {r}_{n}\left( {0;x}\right) = \frac{1}{\left( {n + 1}\right) !}{f}^{\left( n + 1\right) }\left( \xi \right) {x}^{n + 1}, \] where \( {f}^{\left( n + 1\right) }\left( \xi \right) = \sinh \xi \) if \( n \) is even and \( {f}^{\left( n + 1\right) }\left( \xi \right) = \cosh \xi \) if \( n \) is odd. In any case \( \left...
Yes
\[ \cosh x = 1 + \frac{1}{2!}{x}^{2} + \frac{1}{4!}{x}^{4} + \cdots + \frac{1}{\left( {2n}\right) !}{x}^{2n} + \cdots , \]
valid for any \( x \in \mathbb{R} \) .
Yes
For the function \( f\left( x\right) = \ln \left( {1 + x}\right) \) we have \( {f}^{\left( n\right) }\left( x\right) = \frac{{\left( -1\right) }^{n - 1}\left( {n - 1}\right) !}{{\left( 1 + x\right) }^{n}} \), s that the Taylor series of this function at \( {x}_{0} = 0 \) is
\[ \ln \left( {1 + x}\right) = x - \frac{1}{2}{x}^{2} + \frac{1}{3}{x}^{3} - \cdots + \frac{{\left( -1\right) }^{n - 1}}{n}{x}^{n} + {r}_{n}\left( {0;x}\right) . \] This time we represent \( {r}_{n}\left( {0;x}\right) \) using Cauchy’s formula (5.55): \[ {r}_{n}\left( {0;x}\right) = \frac{1}{n!}\frac{{\left( -1\right) ...
Yes
For the function \( {\left( 1 + x\right) }^{a} \), where \( \alpha \in \mathbb{R} \), we have \( {f}^{\left( n\right) }\left( x\right) = \alpha \left( {\alpha - 1}\right) \cdots \) \( \left( {\alpha - n + 1}\right) {\left( 1 + x\right) }^{\alpha - n} \), so that Taylor’s formula at \( {x}_{0} = 0 \) for this function h...
Using Cauchy's formula (5.55), we find\n\n\[ \n{r}_{n}\left( {0;x}\right) = \frac{\alpha \left( {\alpha - 1}\right) \cdots \left( {\alpha - n}\right) }{n!}{\left( 1 + \xi \right) }^{\alpha - n - 1}{\left( x - \xi \right) }^{n}x,\n\]\n\nwhere \( \xi \) lies between 0 and \( x \) .\n\nIf \( \left| x\right| < 1 \), then, ...
Yes
Proposition 3 If there exists a polynomial \( {P}_{n}\left( {{x}_{0};x}\right) = {c}_{0} + {c}_{1}\left( {x - {x}_{0}}\right) + \cdots + \) \( {c}_{n}{\left( x - {x}_{0}\right) }^{n} \) satisfying condition (5.76), that polynomial is unique.
Proof Indeed, from relation (5.76) we obtain the coefficients of the polynomial successively and completely unambiguously\n\n\[ \n{c}_{0} = \mathop{\lim }\limits_{{E \ni x \rightarrow {x}_{0}}}f\left( x\right) \n\] \n\n\[ \n{c}_{1} = \mathop{\lim }\limits_{{E \ni x \rightarrow {x}_{0}}}\frac{f\left( x\right) - {c}_{0}}...
Yes
Proposition 4 (The local Taylor formula) Let \( E \) be a closed interval having \( {x}_{0} \in \mathbb{R} \) as an endpoint. If the function \( f : E \rightarrow \mathbb{R} \) has derivatives \( {f}^{\prime }\left( {x}_{0}\right) ,\ldots ,{f}^{\left( n\right) }\left( {x}_{0}\right) \) up to order \( n \) inclusive at ...
Since the Taylor polynomial \( {P}_{n}\left( {{x}_{0};x}\right) \) is constructed from the requirement that its derivatives up to order \( n \) inclusive must coincide with the corresponding derivatives of the function \( f \) at \( {x}_{0} \), it follows that \( {f}^{\left( k\right) }\left( {x}_{0}\right) - {P}_{n}^{\...
Yes
We shall write a polynomial that makes it possible to compute the values of \( \sin x \) on the interval \( - 1 \leq x \leq 1 \) with absolute error at most \( {10}^{-3} \) .
One can take this polynomial to be a Taylor polynomial of suitable degree obtained from the expansion of \( \sin x \) in a neighborhood of \( {x}_{0} = 0 \) . Since\n\n\[ \sin x = x - \frac{1}{3!}{x}^{3} + \frac{1}{5!}{x}^{5} - \cdots + \frac{{\left( -1\right) }^{n}}{\left( {{2n} + 1}\right) !}{x}^{{2n} + 1} + 0 \cdot ...
Yes
Example 12 We shall show that \( \tan x = x + \frac{1}{3}{x}^{3} + o\left( {x}^{3}\right) \) as \( x \rightarrow 0 \) .
We have\n\n\[ \n{\tan }^{\prime }x = {\cos }^{-2}x \n\]\n\n\[ \n{\tan }^{\prime \prime }x = 2{\cos }^{-3}x\sin x \n\]\n\n\[ \n{\tan }^{\prime \prime \prime }x = 6{\cos }^{-4}x{\sin }^{2}x + 2{\cos }^{-2}x. \n\]\n\nThus, \( \tan 0 = 0,{\tan }^{\prime }0 = 1,{\tan }^{\prime \prime }0 = 0,{\tan }^{\prime \prime \prime }0 ...
Yes
Let \( \alpha > 0 \) . Let us study the convergence of the series \( \mathop{\sum }\limits_{{n = 1}}^{\infty }\ln \cos \frac{1}{{n}^{\alpha }} \) .
For \( \alpha > 0 \) we have \( \frac{1}{{n}^{\alpha }} \rightarrow 0 \) as \( n \rightarrow \infty \) . Let us estimate the order of a term of the series:\n\n\[ \ln \cos \frac{1}{{n}^{\alpha }} = \ln \left( {1 - \frac{1}{2!} \cdot \frac{1}{{n}^{2\alpha }} + o\left( \frac{1}{{n}^{2\alpha }}\right) }\right) = - \frac{1}...
No
Let us show that \( \ln \cos x = - \frac{1}{2}{x}^{2} - \frac{1}{12}{x}^{4} - \frac{1}{45}{x}^{6} + O\left( {x}^{8}\right) \) as \( x \rightarrow 0 \) .
This time, instead of computing six successive derivatives, we shall use the already-known expansions of \( \cos x \) as \( x \rightarrow 0 \) and \( \ln \left( {1 + u}\right) \) as \( u \rightarrow 0 \) :\n\n\[ \ln \cos x = \ln \left( {1 - \frac{1}{2!}{x}^{2} + \frac{1}{4!}{x}^{4} - \frac{1}{6!}{x}^{6} + O\left( {x}^{...
Yes
Let us find the values of the first six derivatives of the function \( \ln \cos x \) at \( x = 0 \) .
We have \( {\left( \ln \cos \right) }^{\prime }x = \frac{-\sin x}{\cos x} \), and it is therefore clear that the function has derivatives of all orders at 0, since \( \cos 0 \neq 0 \) . We shall not try to find functional expressions for these derivatives, but rather we shall make use of the uniqueness of the Taylor po...
Yes
Example 16 Let \( f\left( x\right) \) be an infinitely differentiable function at the point \( {x}_{0} \), and suppose we know the expansion\n\n\[ \n{f}^{\prime }\left( x\right) = {c}_{0}^{\prime } + {c}_{1}^{\prime }x + \cdots + {c}_{n}^{\prime }{x}^{n} + O\left( {x}^{n + 1}\right) \n\]\n\nof its derivative in a neigh...
Thus for the function \( f\left( x\right) \) itself we have the expansion\n\n\[ \nf\left( x\right) = f\left( 0\right) + \frac{{c}_{0}^{\prime }}{1!}x + \frac{1!{c}_{1}^{\prime }}{2!}{x}^{2} + \cdots + \frac{n!{c}_{n}^{\prime }}{\left( {n + 1}\right) !}{x}^{n + 1} + O\left( {x}^{n + 2}\right) ,\n\]\n\nor, after simplifi...
Yes
Let us find the Taylor expansion of the function \( f\left( x\right) = \arctan x \) at 0 .
Since \( {f}^{\prime }\left( x\right) = \frac{1}{1 + {x}^{2}} = {\left( 1 + {x}^{2}\right) }^{-1} = 1 - {x}^{2} + {x}^{4} - \cdots + {\left( -1\right) }^{n}{x}^{2n} + O\left( {x}^{{2n} + 2}\right) \) , by the considerations explained in the preceding example,\n\n\[ f\left( x\right) = f\left( 0\right) + \frac{1}{1}x - \...
Yes
Example 19 We use the results of Examples 5, 12, 17, and 18 and find\n\n\[ \mathop{\lim }\limits_{{x \rightarrow 0}}\frac{\arctan x - \sin x}{\tan x - \arcsin x} = \mathop{\lim }\limits_{{x \rightarrow 0}}\frac{\left\lbrack {x - \frac{1}{3}{x}^{3} + O\left( {x}^{5}\right) }\right\rbrack - \left\lbrack {x - \frac{1}{3!}...
\[ = \mathop{\lim }\limits_{{x \rightarrow 0}}\frac{-\frac{1}{6}{x}^{3} + O\left( {x}^{5}\right) }{\frac{1}{6}{x}^{3} + O\left( {x}^{5}\right) } = - 1. \]
Yes
Proposition 1 The following relations hold between the monotonicity properties of a function \( f : E \rightarrow \mathbb{R} \) that is differentiable on an open interval \( \rbrack a, b\lbrack = E \) and the sign (positivity) of its derivative \( {f}^{\prime } \) on that interval:
Proof The left-hand column of implications is already known to us from Lagrange's theorem, by virtue of which \( f\left( {x}_{2}\right) - f\left( {x}_{1}\right) = {f}^{\prime }\left( \xi \right) \left( {{x}_{2} - {x}_{1}}\right) \), where \( \left. {{x}_{1},{x}_{2} \in }\right\rbrack a, b\lbrack \) and \( \xi \) is a p...
Yes
Let \( f\left( x\right) = {x}^{3} - {3x} + 2 \) on \( \mathbb{R} \). Then \( {f}^{\prime }\left( x\right) = 3{x}^{2} - 3 = 3\left( {{x}^{2} - 1}\right) \)
and since \( {f}^{\prime }\left( x\right) < 0 \) for \( \left| x\right| < 1 \) and \( {f}^{\prime }\left( x\right) > 0 \) for \( \left| x\right| > 1 \), we can say that the function is increasing on the open interval \( \rbrack - \infty , - 1\left\lbrack \text{, decreasing on}\right\rbrack - 1,1\lbrack \), and increasi...
Yes
Let us find the maximum of \( f\left( x\right) = {x}^{2} \) on the closed interval \( \left\lbrack {-2,1}\right\rbrack \).
It is obvious in this case that the maximum will be attained at the endpoint -2 , but here is a systematic procedure for finding the maximum. We find \( {f}^{\prime }\left( x\right) = {2x} \), then we find all points of the open interval \( \rbrack - 2,1\lbrack \) at which \( {f}^{\prime }\left( x\right) = 0 \) . In th...
Yes
Proposition 4 (Sufficient conditions for an extremum in terms of higher-order derivatives) Suppose a function \( f : U\left( {x}_{0}\right) \rightarrow \mathbb{R} \) defined on a neighborhood \( U\left( {x}_{0}\right) \) of \( {x}_{0} \) has derivatives of order up to \( n \) inclusive at \( {x}_{0}\left( {n \geq 1}\ri...
Proof Using the local Taylor formula \[ f\left( x\right) - f\left( {x}_{0}\right) = \frac{1}{n!}{f}^{\left( n\right) }\left( {x}_{0}\right) {\left( x - {x}_{0}\right) }^{n} + \alpha \left( x\right) {\left( x - {x}_{0}\right) }^{n}, \] (5.82) where \( \alpha \left( x\right) \rightarrow 0 \) as \( x \rightarrow {x}_{0} \...
Yes
Example 6 (The law of refraction in geometric optics (Snell’s law) \( {}^{15} \) ) According to Fermat's principle, the actual trajectory of a light ray between two points is such that the ray requires minimum time to pass from one point to the other compared with all paths joining the two points.
Now consider two such media, and suppose that light propagates from point \( {A}_{1} \) to \( {A}_{2} \), as shown in Fig. 5.10.\n\nIf \( {c}_{1} \) and \( {c}_{2} \) are the velocities of light in these media, the time required to traverse the path is\n\n\[ t\left( x\right) = \frac{1}{{c}_{1}}\sqrt{{h}_{1}^{2} + {x}^{...
Yes
We shall show that for \( x > 0 \)\n\n\[ \n{x}^{\alpha } - {\alpha x} + \alpha - 1 \leq 0,\;\text{ when }0 < \alpha < 1, \]\n\n(5.84)\n\n\[ \n{x}^{\alpha } - {\alpha x} + \alpha - 1 \geq 0,\;\text{ when }\alpha < 0\text{ or }1 < \alpha . \]\n\n(5.85)
Proof Differentiating the function \( f\left( x\right) = {x}^{\alpha } - {\alpha x} + \alpha - 1 \), we find \( {f}^{\prime }\left( x\right) = \) \( \alpha \left( {{x}^{\alpha - 1} - 1}\right) \) and \( {f}^{\prime }\left( x\right) = 0 \) when \( x = 1 \) . In passing through the point 1 the derivative passes from posi...
Yes
Let \( f\left( x\right) = \sin x \). Since \( {f}^{\prime }\left( x\right) = \cos x \) and \( {f}^{\prime \prime }\left( x\right) = - \sin x \), all the points where \( {f}^{\prime }\left( x\right) = \cos x = 0 \) are local extrema of \( \sin x \), since \( {f}^{\prime \prime }\left( x\right) = - \sin x \neq 0 \) at th...
Here \( {f}^{\prime \prime }\left( x\right) < 0 \) if \( \sin x > 0 \) and \( {f}^{\prime \prime }\left( x\right) > 0 \) if \( \sin x < 0 \). Thus the points where \( \cos x = 0 \) and \( \sin x > 0 \) are local maxima and those where \( \cos x = 0 \) and \( \sin x < 0 \) are local minima for \( \sin x \) (which, of co...
Yes
Example 9 Let us study the convexity of \( f\left( x\right) = {x}^{\alpha } \) on the set \( x > 0 \) .
Since \( {f}^{\prime \prime }\left( x\right) = \) \( \alpha \left( {\alpha - 1}\right) {x}^{\alpha - 2} \), we have \( {f}^{\prime \prime }\left( x\right) > 0 \) for \( \alpha < 0 \) or \( \alpha > 1 \), that is, for these values of the exponent \( \alpha \) the power function \( {x}^{\alpha } \) is strictly convex (do...
Yes
Example 10 Let \( f\left( x\right) = {a}^{x},0 < a, a \neq 1 \) . Since \( {f}^{\prime \prime }\left( x\right) = {a}^{x}{\ln }^{2}a > 0 \), the exponential function \( {a}^{x} \) is strictly convex (downward) on \( \mathbb{R} \) for any allowable value of the base \( a \) (see Fig. 5.12).
Since \( {f}^{\prime \prime }\left( x\right) = {a}^{x}{\ln }^{2}a > 0 \), the exponential function \( {a}^{x} \) is strictly convex (downward) on \( \mathbb{R} \) for any allowable value of the base \( a \) (see Fig. 5.12).
Yes
Example 12 Let us study the convexity of \( f\left( x\right) = \sin x \) (see Fig. 5.14).
Since \( {f}^{\prime \prime }\left( x\right) = - \sin x \), we have \( {f}^{\prime \prime }\left( x\right) < 0 \) on the intervals \( \pi \cdot {2k} < x < \) \( \pi \left( {{2k} + 1}\right) \) and \( {f}^{\prime \prime }\left( x\right) > 0 \) on \( \pi \left( {{2k} - 1}\right) < x < \pi \cdot {2k} \), where \( k \in \m...
Yes