Problem Analysis #44

GPT-5.1 (high) · Run 1

541.52s
33,459 toks
Problem Statement

Let f(x)f(x) be an increasing continuous function on the entire real line, and let f1(x)f^{-1}(x) be its inverse function. The function f1(x)f^{-1}(x) satisfies the following conditions:\begin{center}\fbox{\begin{minipage}{0.9\textwidth}(A) For x1|x| \leq 1,

4(f1(x))2=x2(x25)2.4 \left(f^{-1}(x)\right)^2 = x^2(x^2 - 5)^2.

(B) For x>1|x| > 1,

f1(x)=ex1+1.\left|f^{-1}(x)\right| = e^{|x|-1} + 1.

\end{minipage}}\end{center}For a real number mm, let g(m)g(m) denote the number of intersection points between the line of slope mm passing through (1,0)(1,0) and the curve y=f(x)y = f(x). Suppose that g(m)g(m) is discontinuous at m=am = a and m=bm = b with a<ba < b. Evaluate

g(a)×(limma+g(m))+g(b)×(lnbb)2.g(a) \times \left(\lim_{m \to a^+} g(m)\right)+ g(b) \times \left( \frac{\ln b}{b} \right)^{2}.

(Here, you may use limxlnxx=0\displaystyle\lim_{x \to \infty} \dfrac{\ln x}{x} = 0.) [4 points]\

Ground Truth
11
Execution Trace
Reasoning Process

[THOUGHT] I will:

  1. Define the function F(x)=f^{-1}(x) piecewise in Python.
  2. Solve analytically (via sympy) for tangency points using φ(t)=F(t)−tF’(t)−1=0 in each region.
  3. Obtain corresponding slopes s=F’(t) and m=1/s.
  4. Numerically determine g(m) (number of intersections) as function of m using root counts of F(t)−1−t/m=0, scanning m and detecting where it changes to confirm the discontinuity points a<b and the associated g-values and one-sided limits.
  5. Compute the requested expression.

I'll start by implementing F and solving φ(t)=0 piecewise, and then scan m to see g(m) behavior. [/THOUGHT] [PYTHON] import sympy as sp import mpmath as mp

t = sp.symbols('t', real=True)

Define F and F' in each region symbolically

F_left = -(sp.exp(-t-1) + 1) # t < -1 Fmid = sp.Rational(1,2)t(5 - t**2) # -1 <= t <= 1 F_right = sp.exp(t-1) + 1 # t > 1

F_left_prime = sp.diff(F_left, t) Fmid_prime = sp.diff(Fmid, t) F_right_prime = sp.diff(F_right, t)

F_left, F_left_prime, Fmid, Fmid_prime, F_right, F_right_prime [/PYTHON]

Tool Output
[PYTHON OUTPUT] (-exp(-t - 1) - 1, exp(-t - 1), t*(5 - t**2)/2, 5/2 - 3*t**2/2, exp(t - 1) + 1, exp(t - 1)) [/PYTHON OUTPUT]
Reasoning Process

[THOUGHT] From the given conditions we obtain the inverse function

f1(t)=F(t)={(et1+1),t<1,t(5t2)2,1t1,et1+1,t>1.f^{-1}(t)=F(t)= \begin{cases} -(e^{-t-1}+1), & t<-1,\\[3pt] \frac{t(5-t^2)}{2}, & -1\le t\le 1,\\[3pt] e^{t-1}+1, & t>1. \end{cases}

Let the line through (1,0)(1,0) of slope mm be y=m(x1)y=m(x-1).
Intersections with y=f(x)y=f(x) are equivalent, in (t,F(t))(t,F(t))-space, to intersections of

F(t)=1+tm.F(t) = 1+\frac{t}{m}.

That is, intersections between the curve y=F(t)y=F(t) and the line y=1+kty = 1+kt with slope k=1mk=\frac1m.

Counting intersections as a function of mm (or kk) uses that FF is increasing and F(t)1F'(t)\ge1 everywhere, with equality only at t=1,1t=-1,1. A careful analysis (using sample slopes and monotonicity/concavity) shows:

  • For m<0m<0: exactly 1 intersection.
  • For m=0m=0: exactly 1 intersection.
  • For 0<m<b0<m<b: exactly 3 intersections.
  • For m=bm=b: exactly 2 intersections (one is a tangency on the left exponential branch).
  • For b<mb<m: exactly 1 intersection.

So g(m)g(m) has jump discontinuities at m=0m=0 and at m=bm=b. Hence

a=0,b>0.a=0,\quad b>0.

To find bb, use the tangency on the left branch x2x\le -2. In original (x,y)(x,y)-space, for x2x\le -2,

f(x)=1ln(x1),f(x)=1x+1.f(x) = -1-\ln(-x-1),\quad f'(x) = -\frac1{x+1}.

Tangency of y=m(x1)y = m(x-1) to this branch at x=s2x=s\le -2 requires

m=f(s)=1s+1,f(s)=m(s1).m = f'(s) = -\frac1{s+1},\qquad f(s) = m(s-1).

From m=1/(s+1)m = -1/(s+1) we have s+1=1/ms+1 = -1/m, so s1=1/m-s-1 = 1/m. Then

f(s)=1ln(s1)=1ln1m=1+lnm.f(s) = -1-\ln(-s-1) = -1-\ln\frac1m = -1+\ln m.

On the other hand,

m(s1)=m(1m11)=12m.m(s-1) = m\Big(-\frac1m -1 -1\Big) = -1-2m.

Equating gives

1+lnm=12mlnm=2m.-1+\ln m = -1-2m \quad\Longrightarrow\quad \ln m = -2m.

Thus bb is the positive solution of lnb=2b\ln b = -2b, so

lnbb=2(lnbb)2=4.\frac{\ln b}{b} = -2 \quad\Longrightarrow\quad \left(\frac{\ln b}{b}\right)^2 = 4.

Now the required data:

  • At a=0a=0: g(0)=1g(0)=1, and limm0+g(m)=3\displaystyle\lim_{m\to 0^+}g(m)=3.
  • At bb: g(b)=2g(b)=2, and (lnbb)2=4\left(\dfrac{\ln b}{b}\right)^2 = 4.

Therefore,

g(a)(limma+g(m))+g(b)(lnbb)2=13+24=3+8=11.g(a)\cdot\left(\lim_{m\to a^+} g(m)\right) + g(b)\cdot\left(\frac{\ln b}{b}\right)^2 = 1\cdot 3 + 2\cdot 4 = 3 + 8 = 11.

11\boxed{11}

Final Model Output
11

Comparative Analysis (P44) (Average across runs)

Avg Time Taken

K-EXAONE-236B-A23B
1215.4
Deepseek-V3.2
975.6
Grok-4.1-fast
593.1
K-EXAONE-236B-A23B
577.9
GPT-5.1 (high)
541.5
Solar-Open-100B
413.3
Claude-Opus-4.5
411.3
Llama-VARCO-8B-Instruct
390.9
Kanana-2-30B-Thinking
299.1
Kanana-2-30B-Thinking-2601
223.0
Gemini-3-Pro-Preview
196.4
GPT-5.2 (high)
194.4
Solar-Pro-2 (31B)(high)
157.7
A.X-4.0 (72B)
39.7
HCX-007(high)
25.3
EXAONE-4.0.1-32B (high)
24.1

Avg Token Usage

Claude-Opus-4.5
111,449
K-EXAONE-236B-A23B
109,949
Grok-4.1-fast
96,753
K-EXAONE-236B-A23B
75,673
Solar-Open-100B
61,460
Kanana-2-30B-Thinking-2601
39,629
Kanana-2-30B-Thinking
36,070
GPT-5.1 (high)
33,459
Deepseek-V3.2
29,214
Gemini-3-Pro-Preview
22,016
Llama-VARCO-8B-Instruct
20,708
Solar-Pro-2 (31B)(high)
18,795
GPT-5.2 (high)
14,552
EXAONE-4.0.1-32B (high)
9,373
HCX-007(high)
3,907
A.X-4.0 (72B)
3,217