Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 29 min ago
PreprintCC BY 4.0arXiv

Partial Information Decomposition When Some Sources Are Known: A Source Chain Rule and a No-Go Theorem

Abstract

Partial information decomposition (PID) splits the information that several sources carry about a target into atoms, distinguished by which collections of sources give access to them. We ask how such a decomposition should behave when some of the sources are already known. The access structure of the atoms suggests one answer: discard the atoms that the known sources provide and regroup the rest according to which further sources unlock them. The classical construction of conditional information suggests another: recompute the decomposition under the conditional distributions and average. We show that the two answers agree, atom by atom, exactly when redundant information obeys a source chain rule, an analogue of the chain rule of mutual information: when the same sources are added to several collections, the enlarged collections share everything the added sources provide and, beyond that, exactly what the original collections share once the added sources are known. The rule divides established measures of redundant information, so that adopting or rejecting it genuinely narrows the choice of measure. Our main result is a no-go theorem: for three or more sources, the source chain rule and local positivity, the requirement that all atoms be nonnegative, cannot hold together in any PID.

Related

  1. Gaussian BROJA Partial Information Decomposition in Closed Form
    Ohad Sheelo, Tal Golan, Ari Pakman
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  2. Interpreting Reasoning of Large Language Models via Partial Information Decomposition
    Barproda Halder, Qiuyi Zhang, Sanghamitra Dutta
    arXivPreprintCC BY 4.0Full textGeneral mathematicsarXiv
  3. Scalable partial information decomposition for symptom networks via supervised embeddings
    Cillian Hourican, Eric Dignum, Rick Quax +1
    arXivPreprintCC BY 4.0Full textGeneral mathematicsarXiv
  4. Between Hi-Fi and MMI: the overlap of redundancy and synergy in partial information decomposition
    Niels Van Santen, Yves Rosseel, Daniele Marinazzo
    arXivPreprintarXiv licenceFull textStatisticsComputational physicsarXiv
  5. Efficient Numerical Evaluation of Arbitrary High-order Partial Derivatives via Algebraic Decomposition
    Shuixin Fang, Hang Zeng
    arXivPreprintarXiv licenceFull textNumerical analysis & scientific computingarXiv
BibTeX
@misc{gutknecht2026partial,
  title = {{Partial Information Decomposition When Some Sources Are Known: A Source Chain Rule and a No-Go Theorem}},
  author = {Aaron J. Gutknecht},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.33743},
  eprint = {2610.33743},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.33743},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Partial Information Decomposition When Some Sources Are Known: A Source Chain Rule and a No-Go Theorem
AU  - Aaron J. Gutknecht
PY  - 2026
DA  - 2026/10/24
PB  - arXiv
DO  - 10.48550/arxiv.2610.33743
UR  - https://arxiv.org/abs/2610.33743
AB  - Partial information decomposition (PID) splits the information that several sources carry about a target into atoms, distinguished by which collections of sources give access to them. We ask how such a decomposition should behave when some of the sources are already known. The access structure of the atoms suggests one answer: discard the atoms that the known sources provide and regroup the rest according to which further sources unlock them. The classical construction of conditional information suggests another: recompute the decomposition under the conditional distributions and average. We show that the two answers agree, atom by atom, exactly when redundant information obeys a source chain rule, an analogue of the chain rule of mutual information: when the same sources are added to several collections, the enlarged collections share everything the added sources provide and, beyond that, exactly what the original collections share once the added sources are known. The rule divides established measures of redundant information, so that adopting or rejecting it genuinely narrows the choice of measure. Our main result is a no-go theorem: for three or more sources, the source chain rule and local positivity, the requirement that all atoms be nonnegative, cannot hold together in any PID.
ER  -