京都大学 情報学研究科 知能情報学専攻 2023年8月実施 情報学基礎 F1-2
Author
Isidore , Casablanca, 祭音Myyura
Description
大学公表の原題
設問1
以下の積分を求めよ。計算過程も明示すること。
(1) ∫ 0 ∞ 1 ( x 2 + 1 ) 2 d x \int_0^{\infty} \frac{1}{(x^2 + 1)^2} \text{d}x ∫ 0 ∞ ( x 2 + 1 ) 2 1 d x
(2) D = { ( x , y ) ∣ x 2 + y 2 4 ≤ 1 } D = \left \{ (x, y) \mid x^2 + \frac{y^2}{4} \leq 1 \right \} D = { ( x , y ) ∣ x 2 + 4 y 2 ≤ 1 } としたときに、
∬ D x 2 y 2 d x d y \iint_D x^2 y^2 \text{d}x \text{d}y ∬ D x 2 y 2 d x d y
設問2
以下の問いに答えよ。計算過程も明示すること。
(1) log e ( 1.02 ) \log_e (1.02) log e ( 1.02 ) の小数第 7 7 7 位を四捨五入し、小数第 6 6 6 位まで求めよ。
(2) x > 0 x > 0 x > 0 に対して、次の不等式が成り立つことを示せ。
x − x 2 2 < log e ( 1 + x ) < 1 − x 2 2 + x 3 3 x - \frac{x^2}{2} < \log_e (1 + x) < 1 - \frac{x^2}{2} + \frac{x^3}{3} x − 2 x 2 < log e ( 1 + x ) < 1 − 2 x 2 + 3 x 3
設問3
3 x 2 + 2 y 2 + z 2 = 1 3x^2 + 2y^2 + z^2 = 1 3 x 2 + 2 y 2 + z 2 = 1 の条件の下で、 x y z xyz x yz の最大値と最小値を求めよ。
题目描述
回答下列三题,并明确写出计算过程。
计算:
计算
∫ 0 ∞ 1 ( x 2 + 1 ) 2 d x ; \int_0^\infty\frac{1}{(x^2+1)^2}\,dx; ∫ 0 ∞ ( x 2 + 1 ) 2 1 d x ;
对椭圆区域
D = { ( x , y ) | x 2 + y 2 4 ≤ 1 } , D=\left\{(x,y)\ \middle|\ x^2+\frac{y^2}{4}\leq1\right\}, D = { ( x , y ) x 2 + 4 y 2 ≤ 1 } ,
计算
∬ D x 2 y 2 d x d y . \iint_Dx^2y^2\,dx\,dy. ∬ D x 2 y 2 d x d y .
完成下列对数近似与不等式问题:
计算 log e ( 1.02 ) \log_e(1.02) log e ( 1.02 ) ,将小数点后第 7 位四舍五入,给出保留 6 位小数的结果。
证明对每个 x > 0 x>0 x > 0 都有
x − x 2 2 < log e ( 1 + x ) < 1 − x 2 2 + x 3 3 . x-\frac{x^2}{2}
<
\log_e(1+x)
<
1-\frac{x^2}{2}+\frac{x^3}{3}. x − 2 x 2 < log e ( 1 + x ) < 1 − 2 x 2 + 3 x 3 .
在约束
3 x 2 + 2 y 2 + z 2 = 1 3x^2+2y^2+z^2=1 3 x 2 + 2 y 2 + z 2 = 1
下,求 x y z xyz x yz 的最大值和最小值。
Kai
設問1
(1)
Let x = tan θ x = \tan \theta x = tan θ , we have d x = d θ cos 2 θ dx=\frac{d\theta}{\cos^{2} \theta} d x = c o s 2 θ d θ . Then
∫ 0 ∞ 1 ( 1 + x 2 ) 2 d x = ∫ 0 π / 2 cos 4 θ d θ cos 2 θ = ∫ 0 π / 2 cos 2 θ d θ = 1 2 ∫ 0 π / 2 ( 1 + cos 2 θ ) d θ = π 4 \begin{aligned}
\int_{0}^{\infty}\frac{1}{(1+x^{2})^{2}}dx
&= \int_{0}^{\pi/2}\cos^{4} \theta~\frac{d\theta}{\cos^{2} \theta}
= \int_{0}^{\pi/2}\cos^{2}\theta~d\theta \\
&= \frac{1}{2} \int_{0}^{\pi/2} (1 + \cos 2\theta) d\theta = \frac{\pi}{4}
\end{aligned} ∫ 0 ∞ ( 1 + x 2 ) 2 1 d x = ∫ 0 π /2 cos 4 θ cos 2 θ d θ = ∫ 0 π /2 cos 2 θ d θ = 2 1 ∫ 0 π /2 ( 1 + cos 2 θ ) d θ = 4 π
(2)
Let x = r cos θ , y = 2 r sin θ x = r \cos \theta, y = 2r \sin \theta x = r cos θ , y = 2 r sin θ , the Jacobian determinant
J = ∣ cos θ − r sin θ 2 sin θ 2 r cos θ ∣ = 2 r cos 2 θ + 2 r sin 2 θ = 2 r \begin{aligned}
J &=
\begin{vmatrix}
\cos\theta & -r\sin\theta\\
2\sin\theta & 2r\cos\theta
\end{vmatrix}
= 2r\cos^{2}\theta+2r\sin^{2}\theta = 2r
\end{aligned} J = cos θ 2 sin θ − r sin θ 2 r cos θ = 2 r cos 2 θ + 2 r sin 2 θ = 2 r
Then we have
∬ D x 2 y 2 d x d y = ∫ 0 1 ∫ 0 2 π 4 r 4 sin 2 θ cos 2 θ ( ∣ 2 r ∣ d r ) d θ = ∫ 0 1 2 r 5 d r ∫ 0 2 π sin 2 2 θ d θ = ∫ 0 1 2 r 5 d r 1 2 ∫ 0 2 π ( 1 − cos 4 θ ) d θ = [ r 6 3 ] 0 1 ⋅ 1 2 [ θ − 1 4 sin 4 θ ] 0 2 π = π 3 \begin{aligned}
\iint_{D}x^{2}y^{2}dxdy
&= \int_{0}^{1}\int_{0}^{2\pi}4r^{4}\sin^{2}\theta\cos^{2}\theta~(|2r|dr)d\theta
= \int_{0}^{1}2r^{5}~dr\int_{0}^{2\pi}\sin^{2}2\theta~d\theta\\[0.7em]
&= \int_{0}^{1}2r^{5}~dr\frac{1}{2}\int_{0}^{2\pi}(1-\cos 4\theta)~d\theta
= \left[\frac{r^{6}}{3}\right]_{0}^{1}\cdot \frac{1}{2}\left[\theta-\frac{1}{4}\sin 4\theta\right]_{0}^{2\pi}
= \frac{\pi}{3}
\end{aligned} ∬ D x 2 y 2 d x d y = ∫ 0 1 ∫ 0 2 π 4 r 4 sin 2 θ cos 2 θ ( ∣2 r ∣ d r ) d θ = ∫ 0 1 2 r 5 d r ∫ 0 2 π sin 2 2 θ d θ = ∫ 0 1 2 r 5 d r 2 1 ∫ 0 2 π ( 1 − cos 4 θ ) d θ = [ 3 r 6 ] 0 1 ⋅ 2 1 [ θ − 4 1 sin 4 θ ] 0 2 π = 3 π
設問2
(1)
Using log ( 1 + t ) = ∑ k = 1 ∞ ( − 1 ) k + 1 t k / k \log(1+t)=\sum_{k=1}^{\infty}(-1)^{k+1}t^k/k log ( 1 + t ) = ∑ k = 1 ∞ ( − 1 ) k + 1 t k / k with t = 0.02 t=0.02 t = 0.02 ,
∑ k = 1 5 ( − 1 ) k + 1 0.02 k k = 0.019802627306 … . \sum_{k=1}^{5}(-1)^{k+1}\frac{0.02^k}{k}
=0.019802627306\ldots . k = 1 ∑ 5 ( − 1 ) k + 1 k 0.0 2 k = 0.019802627306 … .
The alternating-series remainder is less than 0.02 6 / 6 < 1.1 × 10 − 11 0.02^6/6<1.1\times10^{-11} 0.0 2 6 /6 < 1.1 × 1 0 − 11 , so the required value is 0.019803 0.019803 0.019803 .
(2)
(solution by Isidore)
For the lower bound, let
g ( x ) = log ( 1 + x ) − x + x 2 2 . g(x)=\log(1+x)-x+\frac{x^2}{2}. g ( x ) = log ( 1 + x ) − x + 2 x 2 .
Then g ( 0 ) = 0 g(0)=0 g ( 0 ) = 0 and g ′ ( x ) = x 2 / ( 1 + x ) > 0 g'(x)=x^2/(1+x)>0 g ′ ( x ) = x 2 / ( 1 + x ) > 0 for x > 0 x>0 x > 0 , so x − x 2 / 2 < log ( 1 + x ) x-x^2/2<\log(1+x) x − x 2 /2 < log ( 1 + x ) .
For the upper bound, first note that
h ( x ) = x − x 2 2 + x 3 3 − log ( 1 + x ) h(x)=x-\frac{x^2}{2}+\frac{x^3}{3}-\log(1+x) h ( x ) = x − 2 x 2 + 3 x 3 − log ( 1 + x )
satisfies h ( 0 ) = 0 h(0)=0 h ( 0 ) = 0 and h ′ ( x ) = x 3 / ( 1 + x ) > 0 h'(x)=x^3/(1+x)>0 h ′ ( x ) = x 3 / ( 1 + x ) > 0 . Thus, for 0 < x ≤ 1 0<x\le1 0 < x ≤ 1 ,
log ( 1 + x ) < x − x 2 2 + x 3 3 ≤ 1 − x 2 2 + x 3 3 . \log(1+x)<x-\frac{x^2}{2}+\frac{x^3}{3}
\le1-\frac{x^2}{2}+\frac{x^3}{3}. log ( 1 + x ) < x − 2 x 2 + 3 x 3 ≤ 1 − 2 x 2 + 3 x 3 .
For x ≥ 1 x\ge1 x ≥ 1 , write y = x − 1 ≥ 0 y=x-1\ge0 y = x − 1 ≥ 0 . Concavity gives
log ( 1 + x ) ≤ log 2 + y / 2 \log(1+x)\le\log2+y/2 log ( 1 + x ) ≤ log 2 + y /2 , so
1 − x 2 2 + x 3 3 − log ( 1 + x ) ≥ 5 6 − log 2 + y 2 − y 2 + y 3 3 ≥ 17 24 − log 2 > 1 120 > 0. \begin{aligned}
1-\frac{x^2}{2}+\frac{x^3}{3}-\log(1+x)
&\ge\frac56-\log2+\frac{y^2-y}{2}+\frac{y^3}{3}\\
&\ge\frac{17}{24}-\log2>\frac1{120}>0.
\end{aligned} 1 − 2 x 2 + 3 x 3 − log ( 1 + x ) ≥ 6 5 − log 2 + 2 y 2 − y + 3 y 3 ≥ 24 17 − log 2 > 120 1 > 0.
Here log 2 < 7 / 10 \log2<7/10 log 2 < 7/10 , since
e 7 / 10 > ∑ k = 0 4 ( 7 / 10 ) k / k ! > 2 e^{7/10}>\sum_{k=0}^4(7/10)^k/k!>2 e 7/10 > ∑ k = 0 4 ( 7/10 ) k / k ! > 2 .
(solution by Casablanca)
Easy to see that we only need to prove that:
1 + x < e 1 − x 2 2 + x 3 3 1+x < e^{1- \frac{x^2}{2}+ \frac{x^3}{3}} 1 + x < e 1 − 2 x 2 + 3 x 3
Let f ( x ) = e 1 − x 2 2 + x 3 3 f(x) = e^{1- \frac{x^2}{2}+ \frac{x^3}{3}} f ( x ) = e 1 − 2 x 2 + 3 x 3 . Then we have f ( x ) ≥ f ( 1 ) = e 5 6 f(x) \geq f(1) = e^{\frac 56} f ( x ) ≥ f ( 1 ) = e 6 5 .
(i) for x ∈ ( 0 , 1 ] , x + 1 ≤ 2 < e 5 6 ≤ f ( x ) x \in (0, 1], x+1 \leq 2 < e^{\frac 56} \leq f(x) x ∈ ( 0 , 1 ] , x + 1 ≤ 2 < e 6 5 ≤ f ( x ) \quad (note: e x > 1 + x + x 2 2 , e 5 6 > 157 72 > 2 e^x > 1+ x + \frac{x^2}{2}, e^{\frac 56} > \frac{157}{72}>2 e x > 1 + x + 2 x 2 , e 6 5 > 72 157 > 2 )
(ii) for x ∈ ( 1 , + ∞ ) x \in (1, + \infty) x ∈ ( 1 , + ∞ ) , f ′ ( x ) = ( x 2 − x ) f ( x ) > 0 f'(x) = (x^2 - x)f(x) > 0 f ′ ( x ) = ( x 2 − x ) f ( x ) > 0 , f ( x ) f(x) f ( x ) increases
and we consider the point ( 3 2 , e ) (\frac{3}{2},e) ( 2 3 , e ) on ( x , f ( x ) ) (x,f(x)) ( x , f ( x )) , f ′ ( 3 2 ) = 3 4 e f'(\frac 32) = \frac 34 e f ′ ( 2 3 ) = 4 3 e .
Let
F ( x ) = f ( x ) − ( 3 4 e ( x − 3 2 ) + e ) = f ( x ) − 3 4 e x + e 8 , F(x) = f(x) - (\frac 34 e(x - \frac 32) + e) = f(x) - \frac 34 ex + \frac e8, F ( x ) = f ( x ) − ( 4 3 e ( x − 2 3 ) + e ) = f ( x ) − 4 3 e x + 8 e ,
where
x ∈ ( 1 , + ∞ ) x \in (1, +\infty) x ∈ ( 1 , + ∞ )
and we know that: F ( 3 2 ) = 0 , F ′ ( x ) = ( x 2 − x ) f ( x ) − 3 4 e F(\frac 32) = 0, F'(x) = (x^2-x)f(x) - \frac 34 e F ( 2 3 ) = 0 , F ′ ( x ) = ( x 2 − x ) f ( x ) − 4 3 e , it's obvious that F ′ ( x ) F'(x) F ′ ( x ) increases for x > 1 x > 1 x > 1 , and F ′ ( 3 2 ) = 0 F'(\frac 32) = 0 F ′ ( 2 3 ) = 0 .
Hence F ( x ) ≥ F ( 3 2 ) = 0 F(x) \geq F(\frac 32 ) = 0 F ( x ) ≥ F ( 2 3 ) = 0 for x > 1 x > 1 x > 1 .
Thus
f ( x ) ≥ 3 4 e x − e 8 , x ∈ ( 1 , + ∞ ) f(x) \geq \frac 34 ex - \frac e8, x \in (1,+\infty) f ( x ) ≥ 4 3 e x − 8 e , x ∈ ( 1 , + ∞ )
Consider the intersection ( x 0 , y 0 ) (x_0,y_0) ( x 0 , y 0 ) of y = x + 1 y = x+1 y = x + 1 and y = 3 4 e x − e 8 y = \frac 34 ex - \frac e8 y = 4 3 e x − 8 e . We have
x 0 = 8 + e 6 e − 8 ≈ 1.290. x_0 = \frac{8+e}{6e-8}\approx1.290. x 0 = 6 e − 8 8 + e ≈ 1.290.
Since e > 65 / 24 > 46 / 17 e>65/24>46/17 e > 65/24 > 46/17 , we have x 0 < 13 / 10 x_0<13/10 x 0 < 13/10 . Also e 5 / 6 > ∑ k = 0 6 ( 5 / 6 ) k / k ! > 23 / 10 e^{5/6}>\sum_{k=0}^6(5/6)^k/k!>23/10 e 5/6 > ∑ k = 0 6 ( 5/6 ) k / k ! > 23/10 . Thus, for 1 < x ≤ x 0 1<x\leq x_0 1 < x ≤ x 0 , f ( x ) ≥ f ( 1 ) = e 5 / 6 > x 0 + 1 ≥ x + 1 f(x)\geq f(1)=e^{5/6}>x_0+1\geq x+1 f ( x ) ≥ f ( 1 ) = e 5/6 > x 0 + 1 ≥ x + 1 . For x > x 0 x>x_0 x > x 0 , the tangent bound gives
f ( x ) ≥ 3 4 e x − e 8 > x + 1 f(x) \geq \frac 34 ex - \frac e8 > x+1 f ( x ) ≥ 4 3 e x − 8 e > x + 1
and from (i) and (ii), finally ,we know that f ( x ) > 1 + x f(x) > 1+x f ( x ) > 1 + x
設問3
Perform the Lagrange multipliers method, we get
L ( x , y , z ; λ ) = x y z − λ ( 3 x 2 + 2 y 2 + z 2 − 1 ) L(x,y,z;\lambda) = xyz - \lambda(3x^2+2y^2+z^2-1) L ( x , y , z ; λ ) = x yz − λ ( 3 x 2 + 2 y 2 + z 2 − 1 )
At a nonzero extremum, the stationary equations give
3 x 2 = 2 y 2 = z 2 = 1 3 . 3x^2=2y^2=z^2=\frac13. 3 x 2 = 2 y 2 = z 2 = 3 1 .
Thus ∣ x ∣ = 1 / 3 |x|=1/3 ∣ x ∣ = 1/3 , ∣ y ∣ = 1 / 6 |y|=1/\sqrt6 ∣ y ∣ = 1/ 6 , ∣ z ∣ = 1 / 3 |z|=1/\sqrt3 ∣ z ∣ = 1/ 3 , and both signs of the product occur. Therefore,
min { x y z } = − 1 18 2 , max { x y z } = 1 18 2 \min \{xyz\} = -\frac{1}{18}\sqrt{2}, \quad \max \{xyz\} = \frac{1}{18}\sqrt{2} min { x yz } = − 18 1 2 , max { x yz } = 18 1 2