Problem Analysis #1

32.48s
8,267 toks
Problem Statement

For a square matrix AA, the matrix exponential eAe^{A} is defined byeA=E+k=11k!Ak,e^{A} = E + \sum_{k=1}^{\infty} \frac{1}{k!}A^{k},where EE is the identity matrix.

  • [(1)] Let A=(1445810335). A= \begin{pmatrix} -1 & 4 & 4 \\ -5 & 8 & 10 \\ 3 & -3 & -5 \end{pmatrix}. Compute the matrix exponential eAe^{A}.
  • [(2)] Consider the matrices Ax=(0x0x00001),B=(100010001), A_x= \begin{pmatrix} 0 & -x & 0 \\ x & 0 & 0 \\ 0 & 0 & 1 \end{pmatrix},\qquad B= \begin{pmatrix} 1 & 0 & 0 \\ 0 & -1 & 0 \\ 0 & 0 & 1 \end{pmatrix}, where xx is a real number, and define the vector a=(11e). a= \begin{pmatrix} 1 \\[2mm] 1 \\[2mm] e \end{pmatrix}. Let C=BeAxC = B e^{A_x}. Determine the minimum and maximum values of yTCyyTy \frac{y^{T} C y}{y^{T}y} over all nonzero real vectors yR3y\in\mathbb{R}^{3}.
  • [(3)] Let f(z)=12zTCzaTz,z=(z1z2z3), f(z)=\frac{1}{2}z^{T} C z - a^{T}z, \qquad z= \begin{pmatrix} z_{1}\\ z_{2}\\ z_{3} \end{pmatrix}, where CC is the matrix from part (2). Find the value of z12+z22+z32 \sqrt{z_1^2+z_2^2+z_3^2} for the vector zz satisfying fz1=fz2=fz3=0. \frac{\partial f}{\partial z_{1}} = \frac{\partial f}{\partial z_{2}} = \frac{\partial f}{\partial z_{3}} =0. Let λ1,λ2,λ3\lambda_1,\lambda_2,\lambda_3 be the eigenvalues of the matrix AA in part {\rm (1)}. Let mm and MM be the minimum and maximum values, respectively, obtained in part {\rm (2)}, and letR=z12+z22+z32R = \sqrt{z_1^2+z_2^2+z_3^2}be the value obtained in part {\rm (3)}. Computeλ1λ2λ3mR2(λ12+λ22+λ32).\lambda_1\lambda_2\lambda_3 \cdot m \cdot R^2 \cdot \bigl(\lambda_1^2+\lambda_2^2+\lambda_3^2\bigr).\
Ground Truth
252
Execution Trace
Reasoning Process

[THOUGHT] I need to compute the matrix exponential (e^{A}) for the given matrix (A), then find its eigenvalues (\lambda_1,\lambda_2,\lambda_3).
The Rayleigh quotient for (C=B e^{A_x}) simplifies because (C) is symmetric and its eigenvalues are always ({1,-1,e}), so the minimum (m=-1) and the norm (R^2=3).
Finally, the required product is (-3\cdot\det(A)\cdot\operatorname{tr}(A^2)).
I will use SymPy to compute (e^{A}), its eigenvalues, determinant, and trace of (A^2), then evaluate the product. [/THOUGHT] [PYTHON] import sympy as sp

Define matrix A

A = sp.Matrix([[-1, 4, 4], [-5, 8, 10], [3, -3, -5]])

Compute matrix exponential e^A

expA = A.exp()

Compute eigenvalues of A

eigvals = A.eigenvals() # returns a dict {eigenvalue: algebraic multiplicity}

Extract the three eigenvalues (they may be complex)

lam1, lam2, lam3 = list(eigvals.keys())

Compute determinant of A

detA = A.det()

Compute trace of A^2

traceA2 = (A**2).trace()

Compute the final expression: -3 * det(A) * trace(A^2)

final_product = -3 * detA * traceA2

Print results

print("e^A:") sp.pprint(expA) print("\nEigenvalues of A:", lam1, lam2, lam3) print("det(A):", detA) print("tr(A^2):", traceA2) print("Final product:", final_product) [/PYTHON]

Tool Output
[PYTHON OUTPUT] e^A: ⎡ 3 3 3 ⎤ ⎢- ℯ + 2⋅ℯ -2⋅ℯ + 2⋅ℯ -2⋅ℯ + 2⋅ℯ ⎥ ⎢ ⎥ ⎢ 3 -2 -2 3 -2 3⎥ ⎢- ℯ + ℯ - ℯ + 2⋅ℯ - 2⋅ℯ + 2⋅ℯ ⎥ ⎢ ⎥ ⎢ -2 -2 -2 ⎥ ⎣ ℯ - ℯ -ℯ + ℯ -ℯ + 2⋅ℯ ⎦ Eigenvalues of A: 3 1 -2 det(A): -6 tr(A^2): 14 Final product: 252 [/PYTHON OUTPUT]
Reasoning Process

[THOUGHT] The Python output provides the eigenvalues of (A) as (3, 1, -2), determinant (-6), and trace of (A^2) as (14). The minimum (m) of the Rayleigh quotient is (-1) (from eigenvalues of (C)), and (R^2 = 3) (from the norm of the minimizer (z)). The product is ((-6) \cdot (-1) \cdot 3 \cdot 14 = 252). [/THOUGHT] \boxed{252}

Final Model Output
252

Comparative Analysis (P1) (Average across runs)

Avg Time Taken

K-EXAONE-236B-A23B
575.7
GPT-5.1 (high)
150.0
Llama-VARCO-8B-Instruct
141.2
Deepseek-V3.2
124.1
A.X-4.0 (72B)
99.6
Gemini-3-Pro-Preview
97.2
Kanana-2-30B-Thinking
84.0
Kanana-2-30B-Thinking-2601
55.4
Claude-Opus-4.5
43.6
Solar-Pro-2 (31B)(high)
40.8
K-EXAONE-236B-A23B
40.2
HCX-007(high)
39.6
Grok-4.1-fast
34.8
GPT-5.2 (high)
34.3
Solar-Open-100B
32.5
axk1
13.5
EXAONE-4.0.1-32B (high)
6.3

Avg Token Usage

K-EXAONE-236B-A23B
59096.7
Claude-Opus-4.5
19293.0
Gemini-3-Pro-Preview
14285.0
Kanana-2-30B-Thinking
13812.0
Llama-VARCO-8B-Instruct
13418.0
Kanana-2-30B-Thinking-2601
12936.0
K-EXAONE-236B-A23B
11127.0
Deepseek-V3.2
9555.0
GPT-5.1 (high)
9506.0
Grok-4.1-fast
9320.0
Solar-Pro-2 (31B)(high)
8677.0
Solar-Open-100B
8267.0
HCX-007(high)
5746.0
A.X-4.0 (72B)
5358.0
GPT-5.2 (high)
5281.0
EXAONE-4.0.1-32B (high)
5236.0
axk1
4605.0