Let . Using Lagrange multipliers with gives
The third equation fixes . The first two then reduce to and . If , their solution and the constraint give
At , the second equation requires and makes the first inconsistent; at , it requires and gives the same inconsistency. Thus there is no constrained stationary point when . The constraint gradient never vanishes because its vertical component is one, so the multiplier condition has not excluded any regular constrained stationary points.
Eliminate using the constraint: . The restricted objective is the quadratic polynomial , with constant Hessian matrix
Its eigenvalues are and . Hence
For , both eigenvalues are negative and the quadratic polynomial is strictly concave, so the maximum is global on the entire constraint surface. For , the opposite signs give increasing and decreasing directions. At there is no stationary point, as already found, rather than a degenerate extremum to classify. No parameter value produces a constrained local minimum.
Write and use Lagrange multipliers for the particle-number and energy constraints. The stationary equations are
Thus . Finite normalization over infinitely many levels requires . Put , so . The geometric series gives
Therefore
For the energy constraint, use and , obtained by differentiating the geometric series. This yields
Recognizing the hyperbolic cotangent gives
The strict positivity of all occupations requires ; the paper's positivity assumptions alone do not guarantee this feasibility condition. For admissible energy the multiplier is uniquely . Equality is only the limiting state with all occupation in level zero, outside the stipulated strictly positive family; lower energy is impossible.
For rigor beyond formal multiplier equations, has fixed mean . The objective differs from times its information entropy only by the fixed constant . The maximum entropy distribution on the nonnegative integers is uniquely geometric at that mean, confirming the stationary family and its maximum character.

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