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pith:VZCLPQBZ

pith:2026:VZCLPQBZMRXXJFPPB5JWX3NSNF
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Relationship Between Controllability Scoring and Optimal Experimental Design

Kazuhiro Sato

Finite-time controllability scores in linear networks match D- and A-optimality criteria from optimal experimental design via additive Gramian decomposition.

arxiv:2602.11921 v3 · 2026-02-12 · math.OC

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Claims

C1strongest claim

We establish a structural connection between finite-time controllability scoring and approximate optimal experimental design (OED): the finite-time controllability Gramian decomposes additively across nodes, yielding an affine matrix model of the same form as the information-matrix model in OED.

C2weakest assumption

The finite-time controllability Gramian admits an additive decomposition across nodes for linear networked systems, and source-like nodes without negative self-loops exhibit the stated long-horizon downweighting under AECS.

C3one line summary

Finite-time controllability scoring matches approximate OED, with VCS corresponding to D-optimality and AECS to A-optimality, plus a unique optimizer and long-horizon node downweighting.

References

16 extracted · 16 resolved · 1 Pith anchors

[1] On the role of network centrality in the controllability of complex networks, 2017
[2] Controllability of complex networks, 2011
[3] Controllability metrics, limitations and algorithms for complex networks, 2014
[4] On submodularity and controllability in complex dynamical networks, 2016
[5] Controllability of large-scale networks: The control energy exponents, 2024
Receipt and verification
First computed 2026-05-18T02:45:05.281048Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

ae44b7c039646f7495ef0f536bedb2694644c5dc5533c8c81c09b08a448794d7

Aliases

arxiv: 2602.11921 · arxiv_version: 2602.11921v3 · doi: 10.48550/arxiv.2602.11921 · pith_short_12: VZCLPQBZMRXX · pith_short_16: VZCLPQBZMRXXJFPP · pith_short_8: VZCLPQBZ
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/VZCLPQBZMRXXJFPPB5JWX3NSNF \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ae44b7c039646f7495ef0f536bedb2694644c5dc5533c8c81c09b08a448794d7
Canonical record JSON
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    "primary_cat": "math.OC",
    "submitted_at": "2026-02-12T13:20:53Z",
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