advanced28 min studyLesson 274 in Mathematics

Epigraphs and lower semicontinuity

Use closed epigraphs and sublevel compactness to explain when a convex infimum is attained.

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What you’ll understand

  • Translate lower semicontinuity into epigraph and sublevel closedness.
  • Distinguish closed functions from functions with closed effective domains.
  • Prove existence from a nonempty compact sublevel set and identify failed hypotheses.

A numerical sequence can approach a promising location while the objective suddenly becomes worse at the limit. Lower semicontinuity rules out that upward jump in cost. It is exactly the direction of continuity needed for minimization: limits of good candidates remain at least as good as their limiting costs. Drawing the epigraph makes the idea geometric. A function may have an open effective domain and still have a closed epigraph, because finite-height sequences might never approach its missing boundary. This distinction is central to reliable existence arguments.

Put the graph under a roof

The epigraph of f is the set of pairs (x,t) with real height t at least f(x). An infinite value contributes no vertical fiber. The function is convex exactly when this set is convex. In finite-dimensional Euclidean space, f is lower semicontinuous when every sequence converging to x has lower limiting cost at least f(x). Equivalently, its epigraph is closed; equivalently, every finite sublevel set is closed. The sequential formulation remains valid for extended values, including the requirement that costs diverge to infinity near a point assigned infinity.

For the epigraph equivalence, if (x_n,t_n) converges and f(x_n)≤t_n, lower semicontinuity gives f(x)≤liminf f(x_n)≤t. Conversely, a failure of lower semicontinuity supplies a sequence with costs bounded below f(x) by a fixed gap. Passing to a suitable finite height constructs epigraph points converging outside the epigraph. This is why convex analysts call a lower semicontinuous proper convex function closed: the closed object is its epigraph, not necessarily its ordinary graph or its effective domain.

epi⁡f={(x,t):f(x)≤t},f(x)≤lim inf⁡n→∞f(xn)whenever xn→x\operatorname{epi}f=\{(x,t):f(x)\le t\},\qquad f(x)\le\liminf_{n\to\infty}f(x_n)\quad\text{whenever }x_n\to x
The inequality prevents an upward jump in the objective at a candidate limit. For minimization it allows the limit to improve the cost.↔ Scroll wide equations horizontally.

Boundary values decide closedness

Consider f(x)=1/x for x>0 and infinity otherwise. Its finite part is convex, and it tends to infinity as x approaches zero from the right. Its epigraph is therefore closed even though its domain (0,∞) is not. By contrast, the indicator of the open ray (0,∞) is not lower semicontinuous at zero: points approaching from the right have cost zero, while the assigned value at zero is infinity. Closing that epigraph adds the vertical fiber above zero and yields the indicator of [0,∞).

A less obvious failure occurs when a boundary value is too high but finite. Define h(0)=1, h(x)=0 for x>0, and h(x)=infinity for x<0. This function is convex: mixtures involving zero have right-side cost at least zero. It is not lower semicontinuous at zero because nearby positive points have cost zero. Replacing h(0) by zero closes the epigraph. Checking convexity alone would miss this defect. Closing a proper convex function with an affine lower bound preserves the supporting affine information while repairing such missing limit points.

h‾(x)={0x≥0,+∞x<0,epi⁡h‾=epi⁡h‾\overline h(x)=\begin{cases}0&x\ge0,\\+\infty&x<0,\end{cases}\qquad \operatorname{epi}\overline h=\overline{\operatorname{epi}h}
Here h(0)=1 and h(x)=0 for x>0. Closing the epigraph lowers the exceptional endpoint value; it does not alter the positive side.↔ Scroll wide equations horizontally.

Existence needs compactness as well

Let f be proper and lower semicontinuous, with some nonempty compact sublevel set at a finite height. Restrict f to that set and take a minimizing sequence there. Compactness produces a convergent subsequence, and lower semicontinuity gives a minimizer. All points outside that sublevel have larger cost than its defining height, so the minimizer is global. Convexity is not needed for this existence argument, although it adds useful geometry afterward. If all finite sublevels are bounded, lower semicontinuity makes them compact in finite dimensions.

Coercivity means f(x) tends to infinity as the norm of x tends to infinity. For a proper lower semicontinuous function on finite-dimensional space, it provides the bounded sublevels needed for existence. Without coercivity, existence may still hold, but cannot be inferred from closedness alone: exp(x) is continuous convex and has unattained infimum zero as x tends to negative infinity. In an infinite-dimensional Hilbert space, closed bounded sets need not be norm compact; weak compactness and weak lower semicontinuity require a distinct argument rather than reusing the finite-dimensional proof word for word.

An attained minimum on an open domain

Analyze f(x)=x²+1/x for x>0, extended by infinity otherwise. Show its minimum is attained and compute it.

  1. As x approaches zero from the right, 1/x diverges. As x tends to positive infinity, x² diverges. Thus every nonempty finite sublevel stays in a closed bounded interval strictly inside the positive ray.

  2. The extended function is lower semicontinuous, and f′′(x)=2+2/x3>0f''(x)=2+2/x^3>0 on its domain. Existence follows from compact sublevels, and strict convexity gives uniqueness.

  3. Set f′(x)=2x−1/x2=0f'(x)=2x-1/x^2=0. The positive solution is x=2−1/3x=2^{-1/3}. Substitution gives 2−2/3+21/3=3 2−2/32^{-2/3}+2^{1/3}=3\,2^{-2/3}.

The result

An open effective domain does not prevent attainment. The blow-up at its missing boundary keeps all finite-cost minimizing sequences away from that boundary.

Explore the model

Interactive lab

Interactive lab · function

Inspect finite sublevels of a coercive quadratic

Pause and Reset, then set a=1,x=2. Predict y=4, so the sublevel y≤4 of the full quadratic is [−2,2]. For a fresh comparison Reset and set a=0,x=2; every real input now has cost zero and the zero sublevel is unbounded. The display window is finite even when the true sublevel is unbounded. This finite quadratic instrument does not render infinity-valued boundary fibers.

Inspect finite sublevels of a coercive quadraticThis lab uses only y = ax². Playback traces the curve within the fixed integration interval from 0 to x; it does not estimate numerical error or change the chosen point. Current readings: y at chosen x: 0.608; Tangent slope · 2ax: 1.35; Signed area · ax³/3: 0.182. All parameters are adjustable with the labeled controls below.−2.4−1.201.22.4−9−4.504.59xy(x, ax²)
y = ax²TangentSigned integral
y at chosen x
0.608
Tangent slope · 2ax
1.35
Signed area · ax³/3
0.182
t = 0 s

This lab uses only y = ax². Playback traces the curve within the fixed integration interval from 0 to x; it does not estimate numerical error or change the chosen point. Parameter changes pause playback and recompute the model at the current elapsed time. Reset restores both parameters and returns time to zero. Playback starts paused. Adjust either parameter, then choose Play or Step.

Look forA bounded plotting window is not evidence that an objective has bounded sublevel sets.

Check your understanding

Which claim is valid in finite-dimensional Euclidean space?

Try it yourself

Let f(x)=exp(x) on R. Are its epigraph and domain closed? Does it attain its infimum? Identify the missing existence ingredient.

Take a moment to make a prediction or work it out on paper. Open a hint when you need one.

Give me a hint

Examine the sublevel f≤1 and the sequence x_n=−n.

Compare with the solution

The domain is R and is closed. The function is continuous, hence lower semicontinuous, so its epigraph is closed as well. Nevertheless its infimum is zero and no finite x has exp(x)=0. The sublevel f≤1 is (−∞,0], closed but unbounded and therefore not compact. The minimizing sequence −n escapes every bounded set. Thus closedness controls finite candidate limits but cannot stop minimizing sequences from escaping to infinity.

Take it with you

  • Closed convex functions have closed epigraphs, possibly open effective domains.
  • Lower semicontinuity passes a minimizing cost to a convergent candidate limit.
  • In finite dimensions, compact sublevels give existence; closedness alone does not.

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