Monotonicity conjecture for the optimal grouped MSE constant
Let denote the optimal asymptotic MSE constant within the generalized grouping (GG) family for groups of size . Monotonicity conjecture.
i.e., the optimal asymptotic MSE constant within the GG family is non-increasing in . The conjecture is strongly supported by the numerical evidence and examples described in the paper, but a general proof remains open.
References
Primary source
Neri Merhav, “Grouped Reverse Importance Sampling for the Partition Function”, arXiv:2606.26748 (2026).
Progress summary
The conjecture has only numerical support, while an unverified posted argument claims the optimization may be ill-posed and that a narrower fixed-shape version can fail.
Neri Merhav’s 2026 paper formulates the conjecture that the best asymptotic mean-squared-error constant in the generalized Gaussian family satisfies for every . It explicitly leaves a general proof open.
Known results
- The paper proves that product-form group weights cannot improve ordinary reverse importance sampling (Merhav, 2026).
- It proves that, for non-overlapping groups, it suffices to optimize weights depending on total group energy (Merhav, 2026).
- Numerical examples show the constant decreasing from about at to at , with diminishing returns (Merhav, 2026).
- Power-law energies yield a Gamma representation suggested as a possible route to a proof, but no proof is given (Merhav, 2026).
Posted attempt
An unverified argument claims that, under an unrestricted interpretation, the infimum is for every but is generally unattained; it also claims a three-state example reverses monotonicity when the Gaussian shape is fixed at . These are discussion claims and have not been independently verified.
Current status (as of August 2026): The conjecture remains unproved; the new posted argument is unverified and does not establish a verified counterexample to the stated conjecture.
Solutions 1
ProofThis solution needs a summarySee full solution
The unrestricted optimization has zero infimum and generally no minimum; the meaningful fixed-Gaussian monotonicity statement is false.
Use the definitions in Neri Merhav, Grouped Reverse Importance Sampling for the Partition Function, arXiv:2606.26748, Remark 2, equations (22), (24), and (30), and Conjecture 1. Let , let , and let be the group-energy counting measure or density of states. Assume
The generalized-Gaussian family and its objective are
1. Universal collapse of the unrestricted optimum
Cauchy–Schwarz gives , with equality precisely when almost everywhere. Fix and let . Set
Since for and ,
Dominated convergence consequently yields
Therefore, for every group size,
Moreover, if is supported on at least three distinct energies, equality cannot occur: it would require
on the support, although the left-hand side is strictly convex and can take any fixed value at no more than two points. Hence the minimum in the source's equation (24) does not exist. This includes its own example on .
2. An explicit three-state boundary certificate
Take the source-admissible discrete system
For , choose
Then the one-sample weights are
and exact rational arithmetic gives
Equality would require weights proportional to . The values at energies and force , while the value at energy then forces , which is excluded. Thus the infimum is zero but the minimum is absent.
3. Strict reversal for the fixed Gaussian family
The source's numerical Table 1 fixes and optimizes only . For this distinct substantive interpretation, write
For the same three-state system,
At ,
For two samples, the energy multiplicities are , so
In fact,
where
To certify positivity globally, write . On each interval , use the Bernstein expansion
whose coefficients are explicitly
Exact rational evaluation gives
Since the Bernstein basis is nonnegative and sums to , it follows that throughout . Also . Therefore
Thus the unrestricted infimum formulation is identically zero, the literal minimum formulation is generally undefined, and the practically motivated fixed-Gaussian monotonicity formulation is false.