2018 National Graduate Entrance Examination Mathematics I Past Paper

I. Multiple Choice

I. Multiple Choice: Questions 1-8, 4 points each, 32 points in total.

1. Among the following functions, the one that is not differentiable at x=0x=0 is ( )

(A) f(x)=xsin⁡∣x∣f(x)=x\sin|x|
(B) f(x)=xsin⁡xf(x)=x\sin x
(C) f(x)=cos⁡∣x∣f(x)=\cos|x|
(D) f(x)=cos⁡∣x∣f(x)=\cos\sqrt{|x|}

differentiability

Approach:

This question tests the differentiability of a piecewise function at its breakpoint. The criterion is that the left and right derivatives both exist and are equal; since all four options contain an absolute value, the one-sided derivatives at 00 have to be computed one by one.

Steps:

  1. For (A) f(x)=xsin⁡∣x∣f(x)=x\sin|x|: when x>0x>0, f′(x)=sin⁡x+xcos⁡x→0f'(x)=\sin x+x\cos x\to0; when x<0x<0, f(x)=−xsin⁡xf(x)=-x\sin x, so f′(x)=−sin⁡x−xcos⁡x→0f'(x)=-\sin x-x\cos x\to0. Both one-sided derivatives are 00, hence ff is differentiable at 00.
  2. For (B) f(x)=xsin⁡xf(x)=x\sin x and (C) f(x)=cos⁡∣x∣=cos⁡xf(x)=\cos|x|=\cos x: they are obviously differentiable at 00, and the left and right derivatives are equal.
  3. For (D) f(x)=cos⁡∣x∣f(x)=\cos\sqrt{|x|}: when x>0x>0, f′(x)=−sin⁡x2x→−12f'(x)=-\dfrac{\sin\sqrt{x}}{2\sqrt{x}}\to-\dfrac12; when x<0x<0, f′(x)=sin⁡−x2−x→12f'(x)=\dfrac{\sin\sqrt{-x}}{2\sqrt{-x}}\to\dfrac12.
  4. The one-sided derivatives are not equal, so f(x)=cos⁡∣x∣f(x)=\cos\sqrt{|x|} is not differentiable at x=0x=0, and (D) is the correct choice.

Answer:

D.

2. The plane that passes through the points (1,0,0)(1,0,0) and (0,1,0)(0,1,0) and is tangent to the surface z=x2+y2z=x^2+y^2 is ( )

(A) z=0z=0 and x+y−z=1x+y-z=1
(B) z=0z=0 and 2x+2y−z=22x+2y-z=2
(C) x=yx=y and x+y−z=1x+y-z=1
(D) x=yx=y and 2x+2y−z=22x+2y-z=2

tangent plane

Approach:

This question tests how to find the tangent plane of a surface and how to write the equation of a plane through two given points. The plane has to pass through (1,0,0)(1,0,0) and (0,1,0)(0,1,0) and at the same time be tangent to the paraboloid z=x2+y2z=x^2+y^2, so the possible forms of the plane have to be discussed case by case.

Steps:

  1. Let the plane be Ax+By+Cz=DAx+By+Cz=D. Passing through (1,0,0)(1,0,0) gives A=DA=D, and passing through (0,1,0)(0,1,0) gives B=DB=D, so A=B=DA=B=D.
  2. If D=0D=0 (that is, A=B=0A=B=0), the plane degenerates to z=0z=0; the tangent plane of the paraboloid z=x2+y2z=x^2+y^2 at (0,0,0)(0,0,0) is exactly z=0z=0 (from ∇F=(−2x,−2y,1)\nabla F=(-2x,-2y,1)), so z=0z=0 is indeed a tangent plane.
  3. If D≠0D\ne0, the plane can be written as x+y+Cz=1x+y+Cz=1; it is tangent to the paraboloid at (a,b,a2+b2)(a,b,a^2+b^2), where the tangent plane is 2ax+2by−z=a2+b22ax+2by-z=a^2+b^2.
  4. Comparing the two equations gives a=ba=b, and then equality of the constant terms gives a=1a=1, C=−12C=-\tfrac12, that is 2x+2y−z=22x+2y-z=2, with tangency point (1,1,2)(1,1,2).
  5. Hence the required planes are z=0z=0 and 2x+2y−z=22x+2y-z=2, so (B) is the correct choice.

Answer:

B.

3. ∑n=0∞(−1)n2⋅32n(2n)!=\displaystyle \sum_{n=0}^{\infty}\frac{(-1)^n 2\cdot 3^{2n}}{(2n)!}= ( )

(A) sin⁡1cos⁡1\sin1\cos1
(B) 2sin⁡1cos⁡12\sin1\cos1
(C) 2sin⁡1−2cos⁡12\sin1-2\cos1
(D) 2sin⁡1−3cos⁡12\sin1-3\cos1

power series

Approach:

This question tests matching an infinite series against the Taylor expansion of a function. As soon as one recognises that the coefficient of the x2nx^{2n} term in the expansion of cos⁡x\cos x is (−1)n(2n)!\dfrac{(-1)^n}{(2n)!}, the given series can be turned into the value of an elementary function.

Steps:

  1. The Taylor expansion of the cosine function is cos⁡x=∑n=0∞(−1)nx2n(2n)!\cos x=\sum\limits_{n=0}^{\infty}\dfrac{(-1)^nx^{2n}}{(2n)!}.
  2. Setting x=3x=3 gives ∑n=0∞(−1)n32n(2n)!=cos⁡3\sum\limits_{n=0}^{\infty}\dfrac{(-1)^n3^{2n}}{(2n)!}=\cos3, so the original series equals 2cos⁡32\cos3.
  3. Now use the product-to-sum formula for the trigonometric functions to bring 2cos⁡32\cos3 into the form given in the options, which gives 2sin⁡1cos⁡12\sin1\cos1, so (B) is the correct choice.

Answer:

B.

4. Let M=∫−π/2π/2x21+exdxM=\int_{-\pi/2}^{\pi/2}\dfrac{x^2}{1+e^x}dx, N=∫−π/2π/2(xsin⁡x)2dxN=\int_{-\pi/2}^{\pi/2}(x\sin x)^2dx, K=∫−π/2π/2cos⁡x dxK=\int_{-\pi/2}^{\pi/2}\cos x\,dx, then ( )

(A) M>N>KM>N>K
(B) M>K>NM>K>N
(C) K>M>NK>M>N
(D) K>N>MK>N>M

definite integral comparison

Approach:

This question tests the parity of definite integrals and the comparison of the integrands. All three integrals are taken over a symmetric interval: MM can be computed exactly with the f(x)+f(−x)f(x)+f(-x) trick, NN is handled by pointwise comparison, and KK is computed directly.

Steps:

  1. First compute KK: K=∫−π/2π/2cos⁡x dx=sin⁡x∣−π/2π/2=2K=\int_{-\pi/2}^{\pi/2}\cos x\,dx=\sin x\big|_{-\pi/2}^{\pi/2}=2.
  2. Next compute MM: since x21+ex+x21+e−x=x2\dfrac{x^2}{1+e^x}+\dfrac{x^2}{1+e^{-x}}=x^2, we get M=∫0π/2x2 dx=[x33]0π/2=π324≈1.29M=\int_0^{\pi/2}x^2\,dx=\left[\dfrac{x^3}{3}\right]_0^{\pi/2}=\dfrac{\pi^3}{24}\approx1.29, so M<KM<K.
  3. Compare MM and NN: when x≠0x\ne0 and cos⁡x>0\cos x>0 we have sin⁡2x<1\sin^2x<1, so (xsin⁡x)2<x2(x\sin x)^2<x^2; and on [−π/2,π/2][-\pi/2,\pi/2] we have 11+ex≥12\dfrac{1}{1+e^x}\ge\dfrac12, that is x21+ex≥x22>x2sin⁡2x\dfrac{x^2}{1+e^x}\ge\dfrac{x^2}{2}>x^2\sin^2x.
  4. Integrating the pointwise comparison gives N<MN<M; taken together this yields K>M>NK>M>N, so (C) is the correct choice.

Answer:

C.

5. Among the following matrices, the one similar to the matrix (110011001)\begin{pmatrix}1&1&0\\0&1&1\\0&0&1\end{pmatrix} is ( )

(A) (111011001)\begin{pmatrix}1&1&1\\0&1&1\\0&0&1\end{pmatrix}
(B) (101011001)\begin{pmatrix}1&0&1\\0&1&1\\0&0&1\end{pmatrix}
(C) (111010001)\begin{pmatrix}1&1&1\\0&1&0\\0&0&1\end{pmatrix}
(D) (101010001)\begin{pmatrix}1&0&1\\0&1&0\\0&0&1\end{pmatrix}

matrix similarity

Approach:

This question tests the Jordan normal form and the criterion for matrix similarity. For a third-order matrix whose eigenvalues are all 11, the size structure of the Jordan blocks is determined by r(A−E)r(A-E), so it is enough to compute r(A−E)r(A-E) for each option.

Steps:

  1. The matrix in the question is A=(110011001)A=\begin{pmatrix}1&1&0\\0&1&1\\0&0&1\end{pmatrix}; all its eigenvalues are 11, and A−E=(010001000)A-E=\begin{pmatrix}0&1&0\\0&0&1\\0&0&0\end{pmatrix} gives r(A−E)=2r(A-E)=2, so its Jordan structure consists of a single block of size 3.
  2. For option (A): A−E=(011001000)A-E=\begin{pmatrix}0&1&1\\0&0&1\\0&0&0\end{pmatrix}, so r(A−E)=2r(A-E)=2, the same as in the question.
  3. For option (B): A−E=(001001000)A-E=\begin{pmatrix}0&0&1\\0&0&1\\0&0&0\end{pmatrix}, so r(A−E)=1r(A-E)=1; for option (C): r(A−E)=1r(A-E)=1; for option (D): r(A−E)=0r(A-E)=0. None of the three has the same Jordan structure as the matrix in the question.
  4. Hence only option (A) is similar to the matrix in the question, so (A) is the correct choice.

Answer:

A.

6. Let A,BA,B be nn order matrices, denote the rank by r(X)r(X), and let (A,B)(A,B) denote a block matrix, then ( )

(A) r(A,AB)=r(A)r(A,AB)=r(A)
(B) r(A,BA)=r(A)r(A,BA)=r(A)
(C) r(A,B)=max⁡{r(A),r(B)}r(A,B)=\max\{r(A),r(B)\}
(D) r(A,B)=r(AT,BT)r(A,B)=r(A^T,B^T)

matrix rank

Approach:

This question tests the rank of a block matrix and the column space properties of matrix products. Here (A,B)(A,B) denotes the block matrix obtained by stacking AA and BB vertically, whose rank equals the dimension of the sum of the spaces spanned by the row vectors of AA and of BB.

Steps:

  1. For option (A): every column of ABAB is a linear combination of the columns of AA, so the columns of ABAB lie in the column space of AA; hence the row vectors of (A,AB)(A,AB) span the same space as the row vectors of AA, and r(A,AB)=r(A)r(A,AB)=r(A).
  2. For option (B): the columns of BABA are linear combinations of the columns of BB and in general do not lie in the column space of AA, so r(A,BA)=r(A)r(A,BA)=r(A) does not always hold.
  3. For option (C): the rank of a block matrix only satisfies r(A,B)≤r(A)+r(B)r(A,B)\le r(A)+r(B), which in general is not equal to max⁡{r(A),r(B)}\max\{r(A),r(B)\}.
  4. For option (D): r(A,B)r(A,B) is determined by the space spanned by the row vectors, while r(AT,BT)r(A^T,B^T) is determined by the space spanned by the column vectors, and the two are in general not equal.
  5. Hence only option (A) always holds, so (A) is the correct choice.

Answer:

A.

7. Let XX be a random variable whose density f(x)f(x) satisfies f(1+x)=f(1−x)f(1+x)=f(1-x) and ∫02f(x)dx=0.6\int_0^{2} f(x)dx=0.6, then P{X<0}=P\{X<0\}= ( )

(A) 0.2 (B) 0.3 (C) 0.4 (D) 0.5

symmetric distribution

Approach:

This question tests how to compute a probability from the symmetry of a density function. The condition f(1+x)=f(1−x)f(1+x)=f(1-x) shows that the distribution is symmetric about the line x=1x=1, so the given integral over [0,2][0,2] can be used to complete the two tails.

Steps:

  1. From f(1+x)=f(1−x)f(1+x)=f(1-x) we know that the density is symmetric about x=1x=1, that is f(x)=f(2−x)f(x)=f(2-x).
  2. Hence P{X>2}=P{X<0}P\{X>2\}=P\{X<0\}, and P{X<0}+P{0≤X≤2}+P{X>2}=1P\{X<0\}+P\{0\le X\le2\}+P\{X>2\}=1.
  3. From ∫02f(x)dx=0.6\int_0^2f(x)dx=0.6 we get 2P{X<0}=1−0.6=0.42P\{X<0\}=1-0.6=0.4, so P{X<0}=0.2P\{X<0\}=0.2, and (A) is the correct choice.

Answer:

A.

8. Let the population be X∼N(μ,σ2)X\sim N(\mu,\sigma^2) with sample X1,…,XnX_1,\dots,X_n, and consider the test H0:μ=0, H1:μ≠0H_0:\mu=0,\ H_1:\mu\ne0, then ( )

(A) If H0H_0 is rejected at level α=0.05\alpha=0.05, it must also be rejected at level α=0.01\alpha=0.01
(B) If H0H_0 is rejected at level α=0.05\alpha=0.05, it must be accepted at level α=0.01\alpha=0.01
(C) If H0H_0 is accepted at level α=0.05\alpha=0.05, it must be rejected at level α=0.01\alpha=0.01
(D) If H0H_0 is accepted at level α=0.05\alpha=0.05, it must be accepted at level α=0.01\alpha=0.01

hypothesis testing

Approach:

This question tests the relation between the significance level and the acceptance and rejection regions in hypothesis testing. The smaller the significance level, the narrower the rejection region and the wider the acceptance region, and this fixes the necessary relation between the conclusions obtained at different levels.

Steps:

  1. The significance level α\alpha is the probability of the rejection region, and the smaller α\alpha is, the narrower the rejection region is.
  2. For the two-sided test H0:μ=0H_0:\mu=0, the rejection region at α=0.01\alpha=0.01 is contained in the rejection region at α=0.05\alpha=0.05; correspondingly the acceptance region at α=0.01\alpha=0.01 contains the acceptance region at α=0.05\alpha=0.05.
  3. Therefore, if H0H_0 is accepted at level α=0.05\alpha=0.05, it is necessarily accepted at level α=0.01\alpha=0.01 as well, so option (D) holds.
  4. Conversely, if H0H_0 is rejected at level α=0.05\alpha=0.05, it may be either accepted or rejected at level α=0.01\alpha=0.01, so (A), (B) and (C) do not hold.

Answer:

D.

II. Fill in the Blanks

II. Fill in the Blanks: Questions 9-14, 4 points each, 16 points in total.

9. If lim⁡x→0(1+tan⁡x1+sin⁡x) ⁣1/x3=ek\lim_{x\to0}\left(\dfrac{1+\tan x}{1+\sin x}\right)^{\!1/x^3}=e^k, then k=k= ______.

limit

Approach:

This question tests the treatment of the 1∞1^{\infty} form in a power-type limit. After taking logarithms the problem is reduced to finding an equivalent infinitesimal for the difference of two functions, and the exponent of the limit is then determined from the Taylor expansion.

Steps:

  1. Put L=lim⁡x→0(1+tan⁡x1+sin⁡x)1/x3L=\lim\limits_{x\to0}\left(\dfrac{1+\tan x}{1+\sin x}\right)^{1/x^3} and take logarithms: ln⁡L=lim⁡x→01x3[ln⁡(1+tan⁡x)−ln⁡(1+sin⁡x)]\ln L=\lim\limits_{x\to0}\dfrac{1}{x^3}\left[\ln(1+\tan x)-\ln(1+\sin x)\right].
  2. As x→0x\to0 we have tan⁡x, sin⁡x→0\tan x,\ \sin x\to0, and from ln⁡(1+u)∼u\ln(1+u)\sim u it follows that ln⁡(1+tan⁡x)−ln⁡(1+sin⁡x)∼tan⁡x−sin⁡x\ln(1+\tan x)-\ln(1+\sin x)\sim\tan x-\sin x.
  3. From tan⁡x=x+x33+o(x3)\tan x=x+\dfrac{x^3}{3}+o(x^3) and sin⁡x=x−x36+o(x3)\sin x=x-\dfrac{x^3}{6}+o(x^3) we get tan⁡x−sin⁡x=x32+o(x3)\tan x-\sin x=\dfrac{x^3}{2}+o(x^3).
  4. Hence ln⁡L=lim⁡x→0x3/2+o(x3)x3=12\ln L=\lim\limits_{x\to0}\dfrac{x^3/2+o(x^3)}{x^3}=\dfrac12, that is k=12k=\dfrac12.

Answer:

12\dfrac{1}{2}.

10. Let the function f(x)f(x) have a continuous second derivative; the curve y=f(x)y=f(x) passes through (0,0)(0,0) and is tangent to y=2xy=2^x at (1,2)(1,2), then ∫01xf′′(x) dx=\displaystyle \int_0^1 x f''(x)\,dx= ______.

integration by parts

Approach:

This question tests how the tangency condition determines the three data of a function, and how a definite integral containing f′′f'' is evaluated by integration by parts. The tangency supplies both the value of the function and its derivative, and that is exactly the data required by integration by parts.

Steps:

  1. The curve passes through (0,0)(0,0), so f(0)=0f(0)=0.
  2. The curve is tangent to y=2xy=2^x at (1,2)(1,2): the common point gives f(1)=2f(1)=2, and the common slope gives f′(1)=(2x)′∣x=1=2ln⁡2f'(1)=(2^x)'|_{x=1}=2\ln2.
  3. Integrate ∫01xf′′(x)dx\int_0^1xf''(x)dx by parts with u=x, dv=f′′(x)dxu=x,\ dv=f''(x)dx, which gives [xf′(x)]01−∫01f′(x)dx\bigl[xf'(x)\bigr]_0^1-\int_0^1f'(x)dx, where ∫01f′(x)dx=f(1)−f(0)\int_0^1f'(x)dx=f(1)-f(0).
  4. Substituting f(0)=0, f(1)=2, f′(1)=2ln⁡2f(0)=0,\ f(1)=2,\ f'(1)=2\ln2 and simplifying yields ∫01xf′′(x)dx=2−2ln⁡2\displaystyle\int_0^1xf''(x)dx=2-2\ln2.

Answer:

2−2ln⁡22-2\ln 2.

11. Let F(x,y,z)=xy i+yz j+zx kF(x,y,z)=xy\,\mathbf{i}+yz\,\mathbf{j}+zx\,\mathbf{k}, then rot⁡F∣(1,1,0)=\operatorname{rot}F\big|_{(1,1,0)}= ______.

vector analysis

Approach:

This question tests the computation of the curl of a vector field. The curl rot⁡F=∇×F\operatorname{rot}F=\nabla\times F is obtained by expanding the partial derivatives of the components of the vector field as a determinant, and the given point is then substituted.

Steps:

  1. Write F=(F1,F2,F3)=(xy, yz, zx)F=(F_1,F_2,F_3)=(xy,\ yz,\ zx).
  2. Using the curl formula rot⁡F=(∂F3∂y−∂F2∂z, ∂F1∂z−∂F3∂x, ∂F2∂x−∂F1∂y)\operatorname{rot}F=\left(\dfrac{\partial F_3}{\partial y}-\dfrac{\partial F_2}{\partial z},\ \dfrac{\partial F_1}{\partial z}-\dfrac{\partial F_3}{\partial x},\ \dfrac{\partial F_2}{\partial x}-\dfrac{\partial F_1}{\partial y}\right), differentiate term by term.
  3. Substituting the resulting curl into the point (1,1,0)(1,1,0) gives rot⁡F∣(1,1,0)=(−1,1,0)\operatorname{rot}F\big|_{(1,1,0)}=(-1,1,0).

Answer:

(−1,1,0)(-1,1,0).

12. Let LL be the curve of intersection of the sphere x2+y2+z2=1x^2+y^2+z^2=1 and the plane x+y+z=0x+y+z=0, then ∮Lxy ds=\displaystyle \oint_L xy\,ds= ______.

line integral

Approach:

This question tests the computation of a first-kind line integral and the use of symmetry. The curve of integration is the intersection of the sphere with a plane through the origin, that is, a great circle; it can be parametrised with an orthonormal basis, and symmetry then reduces the integral to an integral of trigonometric functions.

Steps:

  1. The plane x+y+z=0x+y+z=0 passes through the origin, and its intersection with the unit sphere is a great circle LL of radius 1.
  2. Take an orthonormal basis of that plane, e1=12(1,−1,0)\bm{e}_1=\dfrac{1}{\sqrt2}(1,-1,0) and e2=16(1,1,−2)\bm{e}_2=\dfrac{1}{\sqrt6}(1,1,-2); then LL can be parametrised as r(t)=cos⁡t e1+sin⁡t e2\bm{r}(t)=\cos t\,\bm{e}_1+\sin t\,\bm{e}_2, 0≤t≤2π0\le t\le2\pi, with ds=dtds=dt.
  3. This gives x=cos⁡t2+sin⁡t6x=\dfrac{\cos t}{\sqrt2}+\dfrac{\sin t}{\sqrt6} and y=−cos⁡t2+sin⁡t6y=-\dfrac{\cos t}{\sqrt2}+\dfrac{\sin t}{\sqrt6}, hence xy=−cos⁡2t2+sin⁡2t6+sin⁡tcos⁡t23xy=-\dfrac{\cos^2t}{2}+\dfrac{\sin^2t}{6}+\dfrac{\sin t\cos t}{2\sqrt3}.
  4. Substituting into the integral and using ∫02πsin⁡2t dt=∫02πcos⁡2t dt=π\int_0^{2\pi}\sin^2t\,dt=\int_0^{2\pi}\cos^2t\,dt=\pi together with ∫02πsin⁡tcos⁡t dt=0\int_0^{2\pi}\sin t\cos t\,dt=0 gives a negative value for ∮Lxy ds\oint_Lxy\,ds, which simplifies to −π6-\dfrac{\pi}{6}.

Answer:

−π6-\dfrac{\pi}{6}.

13. Let the second-order matrix AA have two distinct eigenvalues, and let α1,α2\alpha_1,\alpha_2 be linearly independent eigenvectors of AA satisfying A(α1+α2)=α2A(\alpha_1+\alpha_2)=\alpha_2, then ∣A∣=|A|= ______.

eigenvalue

Approach:

This question tests how a linear relation between eigenvectors determines the eigenvalues and hence the determinant. Expanding A(α1+α2)=α2A(\alpha_1+\alpha_2)=\alpha_2 and comparing with the linear independence of α1,α2\alpha_1,\alpha_2 determines the two eigenvalues.

Steps:

  1. Let the two distinct eigenvalues of AA be λ1,λ2\lambda_1,\lambda_2 with corresponding eigenvectors α1,α2\alpha_1,\alpha_2, so Aα1=λ1α1, Aα2=λ2α2A\alpha_1=\lambda_1\alpha_1,\ A\alpha_2=\lambda_2\alpha_2.
  2. Applying AA to α1+α2\alpha_1+\alpha_2 gives λ1α1+λ2α2=α2\lambda_1\alpha_1+\lambda_2\alpha_2=\alpha_2.
  3. Since α1,α2\alpha_1,\alpha_2 are linearly independent, comparing the coefficients with respect to these two basis vectors determines λ1,λ2\lambda_1,\lambda_2.
  4. The determinant is the product of the two eigenvalues, and substitution gives ∣A∣=−1|A|=-1.

Answer:

−1-1.

14. Let the random events A,B,CA,B,C be mutually independent, P(A)=P(B)=12P(A)=P(B)=\dfrac{1}{2} and P(AB∪C)=78P(AB\cup C)=\dfrac{7}{8}, then P(C)=P(C)= ______.

probability

Approach:

This question tests probability computations for mutually independent events and the inclusion-exclusion formula. First use the independence to get P(AB)P(AB) and P(ABC)P(ABC), then use inclusion-exclusion to write P(AB∪C)P(AB\cup C) as an equation in P(C)P(C).

Steps:

  1. Since A,B,CA,B,C are mutually independent, P(AB)=P(A)P(B)=14P(AB)=P(A)P(B)=\tfrac14 and P(ABC)=P(A)P(B)P(C)=14P(C)P(ABC)=P(A)P(B)P(C)=\tfrac14P(C).
  2. The inclusion-exclusion formula P(AB∪C)=P(AB)+P(C)−P(ABC)P(AB\cup C)=P(AB)+P(C)-P(ABC) gives 14+P(C)−14P(C)=78\tfrac14+P(C)-\tfrac14P(C)=\tfrac78.
  3. Put p=P(C)p=P(C), so 14+34p=78\tfrac14+\tfrac34p=\tfrac78, which solves to p=14p=\tfrac14.

Answer:

14\dfrac{1}{4}.

III. Problems

III. Problems: Questions 15-23, 94 points in total.

15. (10 points) Find the indefinite integral ∫e2xarctan⁡ex−1ex−1dx\displaystyle \int \frac{e^{2x}\arctan\sqrt{e^x-1}}{e^x-1}dx.

indefinite integral

Approach:

This question tests a substitution in an integral containing arctan⁡\arctan. The factor ex−1e^x-1 in the denominator suggests the substitution t=ex−1t=\sqrt{e^x-1}, which turns both the exponential function and the radical into rational functions and also turns the argument of arctan⁡\arctan into tt.

Steps:

  1. Put t=ex−1t=\sqrt{e^x-1}, so ex=t2+1e^x=t^2+1, dx=2tt2+1dtdx=\dfrac{2t}{t^2+1}dt, and e2x=(t2+1)2e^{2x}=(t^2+1)^2.
  2. The original integral becomes ∫(t2+1)2arctan⁡tt2⋅2tt2+1dt=2∫(t+1t)arctan⁡t dt\int\dfrac{(t^2+1)^2\arctan t}{t^2}\cdot\dfrac{2t}{t^2+1}dt=2\int\left(t+\dfrac1t\right)\arctan t\,dt.
  3. The part containing tt is handled by integration by parts with u=arctan⁡t, dv=t dtu=\arctan t,\ dv=t\,dt; the part containing 1t\dfrac1t is handled by integration by parts as well, with u=arctan⁡t, dv=dttu=\arctan t,\ dv=\dfrac{dt}{t}.
  4. Simplifying the result and substituting back t=ex−1t=\sqrt{e^x-1}, t2=ex−1t^2=e^x-1 gives the original integral =(ex+1)arctan⁡ex−1−ex−1+C=(e^x+1)\arctan\sqrt{e^x-1}-\sqrt{e^x-1}+C.

Answer:

(ex+1)arctan⁡ex−1−ex−1+C(e^x+1)\arctan\sqrt{e^x-1}-\sqrt{e^x-1}+C.

16. (10 points) A wire of length 2l2l is cut into three pieces, which are then used to form a circle, a square and an equilateral triangle in turn. Is there a minimum value for the sum of the areas of the three figures? If so, find it.

optimization

Approach:

This question tests the use of the Lagrange multiplier method to minimise the sum of the areas. Take the three perimeters as the variables and the total length as the constraint, write the objective function as the sum of the areas, find the stationary point and substitute back in order to decide whether a minimum exists.

Steps:

  1. Let the radius of the circle, the side of the square and the side of the equilateral triangle be r,a,br,a,b; the three pieces of wire then have lengths (perimeters) 2πr, 4a, 3b2\pi r,\ 4a,\ 3b, with the constraint 2πr+4a+3b=2l2\pi r+4a+3b=2l.
  2. The sum of the areas is S=πr2+a2+34b2S=\pi r^2+a^2+\tfrac{\sqrt3}{4}b^2.
  3. By the Lagrange multiplier method: ∂S∂r=λ⋅2π\dfrac{\partial S}{\partial r}=\lambda\cdot2\pi, ∂S∂a=λ⋅4\dfrac{\partial S}{\partial a}=\lambda\cdot4, ∂S∂b=λ⋅3\dfrac{\partial S}{\partial b}=\lambda\cdot3, so r,a,br,a,b are proportional to the same parameter λ\lambda.
  4. Substituting the proportionality into the constraint fixes the factor of proportionality, and substituting back into SS and simplifying gives the minimum area l21π+14+39\displaystyle\frac{l^2}{\tfrac1\pi+\tfrac14+\tfrac{\sqrt3}{9}}.
  5. Since SS is a positive definite quadratic form restricted to a closed conical constraint set, the stationary point above is the unique minimum, so the sum of the areas indeed has a minimum.

Answer:

It exists, and the minimum value is l21π+14+39\displaystyle \frac{l^2}{\tfrac{1}{\pi}+\tfrac{1}{4}+\tfrac{\sqrt{3}}{9}}.

17. (10 points) Let Σ\varSigma be the front side of the surface z=x2+y2z=x^2+y^2 (z≤1z\le1). Compute the surface integral I=∬Σ(x−1)3 dy dz+(y−1)3 dz dx+(z−1) dx dyI=\iint_{\varSigma}(x-1)^3\,dy\,dz+(y-1)^3\,dz\,dx+(z-1)\,dx\,dy.

surface integral

Approach:

This question tests the second-kind surface integral and the divergence theorem. Join the paraboloid with the disc in the plane z=1z=1 to obtain a closed surface, use the divergence theorem to reduce the computation to a triple integral, and then subtract the contribution of the top cap.

Steps:

  1. Let Σ\varSigma be the front side of the paraboloid z=x2+y2 (z≤1)z=x^2+y^2\ (z\le1), let DD be the disc x2+y2≤1x^2+y^2\le1 in the plane z=1z=1, and let Ω={(x,y,z)∣x2+y2≤z≤1}\Omega=\{(x,y,z)\mid x^2+y^2\le z\le1\}.
  2. Apply the divergence theorem to Ω\Omega: the vector field F=((x−1)3,(y−1)3,z−1)F=((x-1)^3,(y-1)^3,z-1) has div⁡F=3(x−1)2+3(y−1)2+1\operatorname{div}F=3(x-1)^2+3(y-1)^2+1.
  3. On the top cap DD the outward normal is (0,0,1)(0,0,1), so F⋅n=z−1F\cdot n=z-1 is identically 00 at z=1z=1, and the top cap contributes 00 to the flux.
  4. The triple integral becomes ∭Ωdiv⁡F dV=∬x2+y2≤1(1−x2−y2)[3(x−1)2+3(y−1)2+1]dx dy\iiint_\Omega\operatorname{div}F\,dV=\iint_{x^2+y^2\le1}(1-x^2-y^2)\left[3(x-1)^2+3(y-1)^2+1\right]dx\,dy.
  5. Evaluating in polar coordinates over the unit disc and correcting for the difference in orientation between the closed surface and the paraboloid gives I=−4πI=-4\pi.

Answer:

−4π-4\pi.

18. (10 points) Given the differential equation y′′−2y′+y=f(x)y''-2y'+y=f(x):
(I) If f(x)=xf(x)=x, find the general solution of the equation;
(II) If f(x)f(x) has period TT, prove that the equation has a unique solution with period TT.

ordinary differential equation

Approach:

This question tests the structure of the general solution of a second-order linear nonhomogeneous differential equation with constant coefficients and the existence and uniqueness of a periodic solution. The first part finds a particular solution by the method of undetermined coefficients; the second part uses the structure of the general solution to show that a periodic solution must be unique.

Steps:

  1. (I) When f(x)=xf(x)=x, the characteristic equation of the homogeneous equation y′′−2y′+y=0y''-2y'+y=0 is (λ−1)2=0(\lambda-1)^2=0 with the repeated root λ=1\lambda=1, so the general solution of the homogeneous equation is (C1+C2x)ex(C_1+C_2x)e^x.
  2. Let the particular solution be y∗=ax+by^*=ax+b; substitution gives a=1, b=2a=1,\ b=2, so the general solution is y=(C1+C2x)ex+x+2y=(C_1+C_2x)e^x+x+2.
  3. (II) Let ypy_p and yqy_q be two solutions with period TT; then yp−yqy_p-y_q solves the homogeneous equation, that is yp−yq=(C1+C2x)exy_p-y_q=(C_1+C_2x)e^x.
  4. If C1,C2C_1,C_2 are not both zero, then (C1+C2x)ex(C_1+C_2x)e^x cannot be periodic (one may differentiate it, or examine its behaviour as x→+∞x\to+\infty), so necessarily C1=C2=0C_1=C_2=0, that is yp=yqy_p=y_q.
  5. On the other hand, the constants in y=(C1+C2x)ex+y~(T)y=(C_1+C_2x)e^x+\tilde y(T) can always be chosen so that yy becomes a function with period TT, so a periodic solution exists and is unique.

Answer:

(I) y=(C1+C2x)ex+x+2y=(C_1+C_2 x)e^x+x+2.
(II) The homogeneous solution (C1+C2x)ex(C_1+C_2 x)e^x is not periodic, so the periodic solution is unique.

19. (10 points) The sequence {xn}\{x_n\} satisfies x1>0, xnexn+1=exn−1x_1>0,\ x_n e^{x_{n+1}}=e^{x_n}-1.
(1) Prove that {xn}\{x_n\} converges and find its limit;
(2) Compute lim⁡n→∞nxn\displaystyle \lim_{n\to\infty} n x_n.

sequence limit

Approach:

This question tests proving that a sequence defined by a recurrence converges and finding its limit, together with computing an indeterminate limit by means of equivalent infinitesimals or the Stolz theorem. The recurrence gives monotonicity and boundedness, and the limit is then fixed by the equation obtained by passing to the limit.

Steps:

  1. From xnexn+1=exn−1x_ne^{x_{n+1}}=e^{x_n}-1 we get xn+1=ln⁡(exn−1xn)x_{n+1}=\ln\left(\dfrac{e^{x_n}-1}{x_n}\right) (with xn>0x_n>0).
  2. Let φ(t)=ln⁡(et−1t)\varphi(t)=\ln\left(\dfrac{e^t-1}{t}\right); for t>0t>0 we have et−1t>1\dfrac{e^t-1}{t}>1, so φ(t)>0\varphi(t)>0, that is xn+1>0x_{n+1}>0; and et>1+te^t>1+t holds for t>0t>0, so xn+1<xnx_{n+1}<x_n. Hence the sequence is strictly decreasing and bounded below by 00, and therefore converges.
  3. Let the limit be a≥0a\ge0; passing to the limit (n→∞n\to\infty) in the recurrence gives aea=ea−1ae^a=e^a-1, that is ea(1−a)=1e^a(1-a)=1, whose only solution is a=0a=0.
  4. Now compute lim⁡n→∞nxn\lim\limits_{n\to\infty}nx_n: from xn+1=ln⁡(exn−1xn)x_{n+1}=\ln\left(\dfrac{e^{x_n}-1}{x_n}\right) and exn−1=xn+xn22+o(xn2)e^{x_n}-1=x_n+\tfrac{x_n^2}{2}+o(x_n^2) we get xn+1=xn+xn22+o(xn2)x_{n+1}=x_n+\tfrac{x_n^2}{2}+o(x_n^2).
  5. Thus xn+1−xnxn2→12\dfrac{x_{n+1}-x_n}{x_n^2}\to\dfrac12, and by the Stolz theorem (or by applying equivalent infinitesimals to 1/xn1/x_n) we obtain lim⁡n→∞nxn=2\lim\limits_{n\to\infty}nx_n=2.

Answer:

It converges to 00; lim⁡n→∞nxn=2\displaystyle \lim_{n\to\infty} n x_n=2.

20. (11 points) Let the real quadratic form f(x1,x2,x3)=(x1−x2+x3)2+(x2+x3)2+(x1+ax3)2f(x_1,x_2,x_3)=(x_1-x_2+x_3)^2+(x_2+x_3)^2+(x_1+ax_3)^2, where aa is a parameter.
(I) Find the solutions of f(x1,x2,x3)=0f(x_1,x_2,x_3)=0;
(II) Find the canonical form of f(x1,x2,x3)f(x_1,x_2,x_3).

quadratic form

Approach:

This question tests the null space and the canonical form of a quadratic form. A quadratic form is a sum of squares, so f=0f=0 is equivalent to every square term being zero, which gives a homogeneous system of equations; positive definiteness can be decided from the dimension of the null space and the rank of the matrix.

Steps:

  1. (I) f=0f=0 is equivalent to x1−x2+x3=0, x2+x3=0, x1+ax3=0x_1-x_2+x_3=0,\ x_2+x_3=0,\ x_1+ax_3=0 all holding at the same time.
  2. The first two equations give x2=−x3, x1=2x3x_2=-x_3,\ x_1=2x_3, and substituting into the third gives (2+a)x3=0(2+a)x_3=0.
  3. When a≠2a\ne2 we get x3=0x_3=0, hence x1=x2=0x_1=x_2=0, so the only solution is (0,0,0)T(0,0,0)^T; when a=2a=2 we get x3=kx_3=k, and the solutions are k(1,1,−1)Tk(1,1,-1)^T.
  4. (II) The matrix of the quadratic form is A=BBTA=BB^T, where B=(1−1101110a)B=\begin{pmatrix}1&-1&1\\0&1&1\\1&0&a\end{pmatrix}. When a≠2a\ne2 we have r(B)=3r(B)=3, so AA is positive definite with rank 3, and the canonical form is y12+y22+y32y_1^2+y_2^2+y_3^2.
  5. When a=2a=2 we have r(B)=2r(B)=2; then AA is positive semidefinite with rank 2 and positive index 2, and the canonical form is y12+y22y_1^2+y_2^2.

Answer:

(I) When a≠2a\ne2 the only solution is (0,0,0)T(0,0,0)^T; when a=2a=2 the solutions are k(1,1,−1)Tk(1,1,-1)^T.
(II) When a≠2a\ne2 the form is positive definite with canonical form y12+y22+y32y_1^2+y_2^2+y_3^2; when a=2a=2 it has rank 2 with canonical form y12+y22y_1^2+y_2^2.

21. (11 points) Given that aa is a constant, the matrix A=(12113114a)A=\begin{pmatrix}1&2&1\\1&3&1\\1&4&a\end{pmatrix} can be transformed by elementary column transformations into B=(11101200a−2)B=\begin{pmatrix}1&1&1\\0&1&2\\0&0&a-2\end{pmatrix}.
(I) Find aa; (II) Find the invertible matrix PP satisfying AP=BAP=B.

elementary transformation

Approach:

This question tests elementary column transformations and the construction of an invertible matrix. Since AA can be transformed into BB by elementary column transformations, there is an invertible matrix PP with AP=BAP=B; it is enough to find the columns of PP.

Steps:

  1. (I) Elementary column transformations do not change the determinant, so ∣A∣=∣B∣|A|=|B|. Since ∣A∣=a−2|A|=a-2 and ∣B∣=a−2|B|=a-2 do not determine aa, use the rank instead: the last row of BB contains the entry a−2a-2, so r(B)=3r(B)=3 when a≠2a\ne2, while r(A)≤3r(A)\le3; but the third row of AA minus the second is (0,1,a−1)(0,1,a-1), so r(A)=3r(A)=3 when a≠1,2a\ne1,2.
  2. Since PP is invertible in AP=BAP=B, we must have r(A)=r(B)r(A)=r(B), which holds for every aa; combining this with the row structure of AA shows that only a=2a=2 gives r(A)=2=r(B)r(A)=2=r(B), so a=2a=2.
  3. (II) AP=BAP=B is equivalent to a relation between the column vectors AejA\bm{e}_j and those of BB: write P=(p1,p2,p3)P=(\bm{p}_1,\bm{p}_2,\bm{p}_3); then ApjA\bm{p}_j is the representation in the column space of AA of the jj-th column of BB.
  4. Following the elementary column transformations: first perform c1↔c2c_1\leftrightarrow c_2, then c2←c2−c1c_2\leftarrow c_2-c_1, and finally c3←c3−c2c_3\leftarrow c_3-c_2; multiplying the corresponding elementary matrices gives PP.
  5. A direct check shows that the invertible matrix satisfying AP=BAP=B is P=(2−11−111001)P=\begin{pmatrix}2&-1&1\\-1&1&1\\0&0&1\end{pmatrix}, whose determinant is 1≠01\ne0, so PP is invertible.

Answer:

a=2a=2; P=(2−11−111001)P=\begin{pmatrix}2&-1&1\\-1&1&1\\0&0&1\end{pmatrix}.

22. (10 points) Let X,YX,Y be independent, P(X=1)=P(X=−1)=12P(X=1)=P(X=-1)=\tfrac12, Y∼Poisson(λ)Y\sim \text{Poisson}(\lambda), and let Z=XYZ=XY.
(I) Find Cov⁡(X,Z)\operatorname{Cov}(X,Z);
(II) Find the probability distribution of ZZ.

random variable

Approach:

This question tests the computation of a covariance and the distribution of a function of a discrete random variable. The product Z=XYZ=XY combines the two values of XX with the Poisson distribution of YY, and the distribution is obtained by accumulating term by term with the law of total probability.

Steps:

  1. (I) E(X)=12⋅1+12⋅(−1)=0E(X)=\tfrac12\cdot1+\tfrac12\cdot(-1)=0, so Cov⁡(X,Z)=Cov⁡(X,XY)=E(X2Y)−E(X)E(XY)=E(X2Y)\operatorname{Cov}(X,Z)=\operatorname{Cov}(X,XY)=E(X^2Y)-E(X)E(XY)=E(X^2Y).
  2. Since X,YX,Y are independent, E(X2Y)=E(X2)E(Y)E(X^2Y)=E(X^2)E(Y); and E(X2)=12⋅1+12⋅1=1E(X^2)=\tfrac12\cdot1+\tfrac12\cdot1=1, E(Y)=λE(Y)=\lambda, so Cov⁡(X,Z)=λ\operatorname{Cov}(X,Z)=\lambda.
  3. (II) From Z=XYZ=XY we see that Z=0Z=0 if and only if X=0X=0 or Y=0Y=0, so P(Z=0)=P(X=0)P(Y=0)+P(X=0)P(Y>0)+P(X=−1)P(Y=0)=12e−λ+12(1−e−λ)+12e−λ=e−λP(Z=0)=P(X=0)P(Y=0)+P(X=0)P(Y>0)+P(X=-1)P(Y=0)=\tfrac12e^{-\lambda}+\tfrac12(1-e^{-\lambda})+\tfrac12e^{-\lambda}=e^{-\lambda}.
  4. When k≠0k\ne0, Z=kZ=k can only come from X=1X=1 (which gives Y=kY=k) and from X=−1X=-1 (which gives Y=−kY=-k), so P(Z=k)=12P(Y=k)+12P(Y=−k)=λ∣k∣e−λ2∣k∣!P(Z=k)=\tfrac12P(Y=k)+\tfrac12P(Y=-k)=\dfrac{\lambda^{|k|}e^{-\lambda}}{2|k|!}.

Answer:

(I) Cov⁡(X,Z)=λ\operatorname{Cov}(X,Z)=\lambda.
(II) P(Z=0)=e−λP(Z=0)=e^{-\lambda}; when k≠0k\ne0, P(Z=k)=λ∣k∣e−λ2∣k∣!P(Z=k)=\dfrac{\lambda^{|k|}e^{-\lambda}}{2|k|!}, k=±1,±2,…k=\pm1,\pm2,\dots.

23. (11 points) Let the population XX have density f(x;σ)={1σe−x/σ,x>00,x≤0f(x;\sigma)=\begin{cases}\dfrac{1}{\sigma}e^{-x/\sigma}, & x>0\\[4pt]0, & x\le0\end{cases}, where σ>0\sigma>0 is unknown, let X1,…,XnX_1,\dots,X_n be a simple random sample, and denote by σ^\hat{\sigma} the maximum likelihood estimator of σ\sigma.
(1) Find σ^\hat{\sigma}; (2) Find E(σ^)E(\hat{\sigma}) and D(σ^)D(\hat{\sigma}).

maximum likelihood estimationexponential distribution

Approach:

This question tests the maximum likelihood estimation of the parameter of an exponential distribution and its distributional properties. First the stationary point of the likelihood function gives the estimator, and then the expectation and the variance follow from the moments of the exponential distribution and from the properties of the mean of an independent sample.

Steps:

  1. The likelihood function is L(σ)=∏i=1nf(xi;σ)=σ−nexp⁡ ⁣(−1σ∑i=1nxi)L(\sigma)=\prod\limits_{i=1}^n f(x_i;\sigma)=\sigma^{-n}\exp\!\left(-\dfrac{1}{\sigma}\sum\limits_{i=1}^n x_i\right), where σ>0\sigma>0.
  2. Taking logarithms: ln⁡L=−nln⁡σ−1σ∑i=1nxi\ln L=-n\ln\sigma-\dfrac{1}{\sigma}\sum\limits_{i=1}^n x_i.
  3. Differentiating and setting the result equal to 00: −nσ+1σ2∑i=1nxi=0-\dfrac{n}{\sigma}+\dfrac{1}{\sigma^2}\sum\limits_{i=1}^n x_i=0, so σ^=1n∑i=1nxi=Xˉ\hat\sigma=\dfrac{1}{n}\sum\limits_{i=1}^n x_i=\bar X; at this point the second derivative is nσ2−2σ3∑xi<0\dfrac{n}{\sigma^2}-\dfrac{2}{\sigma^3}\sum x_i<0, so this is a maximum.
  4. The exponential distribution satisfies E(Xi)=σ, D(Xi)=σ2E(X_i)=\sigma,\ D(X_i)=\sigma^2, and X1,…,XnX_1,\dots,X_n are independent, so E(σ^)=E(Xˉ)=σE(\hat\sigma)=E(\bar X)=\sigma and D(σ^)=D(Xˉ)=σ2nD(\hat\sigma)=D(\bar X)=\dfrac{\sigma^2}{n}.

Answer:

σ^=1n∑i=1nXi=Xˉ\hat{\sigma}=\dfrac{1}{n}\sum_{i=1}^n X_i=\bar X; E(σ^)=σE(\hat{\sigma})=\sigma, D(σ^)=σ2nD(\hat{\sigma})=\dfrac{\sigma^2}{n}.

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