Papers for

network information theorists

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

New improved limits found on four-variable information inequality measure

Improved Bounds on the Ingleton Score of Four Random Variables

Abstract: For four finite discrete random variables, we prove that the negative of the Ingleton expression, divided by the joint entropy, is at most $19/124 \approx 0.15323$, improving the previously reported upper bound $3/19$ by $11/2356$. The proof uses a copy program with four copy steps and six auxiliary variables, certified by exact rational linear-programming certificates. We also show that two published information inequalities, due to Dougherty-Freiling-Zeger and Csirmaz, imply the bound $5/32$ by an explicit nonnegative combination with Shannon inequalities, and that $5/32$ is the exact optimum both of the union of the three published inequality catalogues considered here and of the full copy-lemma extensions of all 213 distinct copy programs occurring in them. The new program is not among these programs, and the bound $19/124$ remains optimal when all of them and all catalogue inequalities are added. Ancillary files provide the parsed catalogues, exact primal and dual certificates, exact extension certificates, and verifiers that use only the Python standard library.

Sun 4 OctInformation Theory
The gist
This paper improves the known maximum limit for a mathematical expression involving four random variables, called the Ingleton score. The researchers used advanced proof techniques involving multiple steps and helper variables to tighten this limit. They also compared their results with previously known inequalities and found that their new limit is the best possible given the known methods. The work includes exact mathematical certificates and verification tools to support their findings.
Open → 2610.05168v1