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RRLS: relations, rewrites & phase / Note

RRLS: lift, learn, loop, and decode

Reference05 Sept 2026 · saved

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01 / THE QUESTION

Editorial guide

Can an exact complementary-coordinate lift plus conflict-driven clause learning give reusable, independently checkable reasoning on captured cores and fresh SAT cases?

02 / WHAT THE RECORD SAYS

Source passage

All 40 selected inputs received independently checked decisions: 16 captured cores and 24 fresh or specified-family inputs.

03 / LIMITS & OPEN POINTS

Source passage

This is a faster finite execution, not an elimination of search.

04 / THE NEXT QUESTION

Source passage

Future structural primitives would need their own soundness, coverage, recognition, representation-size, and total-cost arguments.

05 / CHECKS IN THE RECORD

Source passage

The 19 passing test groups include the previous twelve regression groups and seven new groups. New checks cover 300 deterministic small random formulas against exhaustive truth assignments, every learned lemma against all models of those small formulas, all 256 subsets of a three-variable forbidden-assignment cube, sparse identifiers, empty and tautological formulas, budget refusal and resume, corrupted proofs and assignments, lift corruption, and rechecked proof slicing.

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Not recorded
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Origin
d0re research collection (snapshot 1 October 2026)
Original path
/The Theory of Reality/RRLS_LIFT_LOOP_PROOF.md
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Title basis
From the source
Date
05 Sept 2026 · saved
Status basis
Its scan-based checker is reused, not replaced, by r-01881573f5be: "SAT models and generic UNSAT RUP proofs use the separate scan-based checker."
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20,871 bytes
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3,046 words
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9be766ae72f64bf2a076ce78a911cfe7992367147383ac8ecbb70732f1b4b796

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RRLS: lift, learn, loop, and decode
2026-09-05
d0re research record r-9be766ae72f6
https://www.d0re.com/library/records/r-9be766ae72f6.html
Authorship basis: Collection attribution; original record retains its own credits
Date basis: saved
Source SHA-256: 9be766ae72f64bf2a076ce78a911cfe7992367147383ac8ecbb70732f1b4b796

Independent research by Anthony Michael Collado.
Original credits remain with each source.