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refactor(Algorithms/WordRAM/Karger): derive contraction survival from Karger.spec through a simulation lemma - #2269
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… Karger.spec `contractDownTo` now simulates the client `Lean.Karger.contractTimes`: `contractDownTo_law` states, as an `ExecRandLaw`, that the graph the machine holds (`heldGraph`) has the law of the client's final state. Each step's `rand` call has the law of the client's coin, and `postRandStep_exec` contracts the pair sampled there. `contractDownTo_spec` keeps its statement. Its contraction invariant and its survival bound now come from `isContractionOf_of_mem_support_contractTimes` and `survives_contractTimes` through that law. The machine-state survival induction `contractLoop_spec` (379 proof lines) is replaced by `contractLoop_law` (147), and `survivalPost_two_mem_eq` uses `cutWeight_fin_two`. `ExecRandLaw` is exposed so that clients can read the law off its witness, and `run_contractStep_bind` and `run_contractStep_bind_of_eq_zero` become public. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG
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Independent reviewer: Claude Code (Opus 5.5), thread No findings. This is the right direction: the machine loop now proves only that it simulates the client, and the probability has one home. Checked:
Limits: I read the whole diff, and the proofs rest on CI. I did not run a local build, repeat the timing or line counts, or re-read the machine-step lemmas, which are unchanged. |
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Add a report-only verifier with independent temporary Git storage, exact reviewed-feature forward/inverse recovery, and ordinary tracked-attribute tree equality. No queue or source mutation by the verifier. Validation: 16 focused real-Git fixtures; check_hygiene.py --check-simp; git diff --cached --check. Historical 2244 reconstruction returned exact d218e3e tree in 3.29s. Full validation and independent review remain before PR integration. No Lean or selected-abstract impact. AI assistance: OpenAI Codex. Refs #2274.
…IME (#2084 M1) (#2086) * feat(Classes/Time): explicit-time verifier characterization of NTIME (#1572) Guess and verify within explicit time (`setOf_exists_mem_NTIME`), through a closed fair-coin composition with the new framed sampler `pairSampler`, and a linear-time verifier for every problem in `NTIME` (`exists_verifier_of_mem_NTIME`). Infrastructure toward the nondeterministic time hierarchy. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(Machines/PTM): make the pair sampler's proof configurations private The induction configurations `PairSampler.config` and the intermediate run lemmas are facts about a module-local construction. Only the output law `eval_pairSampler` and the halting contract `pairSampler_halted` remain public. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(Classes/Promise): PromiseBPTIME with explicit-time sample-and-verify (#2084 M1) Define bounded-error probabilistic time for promise problems (Turing.MultiTapePTM.SolvesWithBoundedErrorInTime, Cslib.Complexity.PromiseBPTIME), with the bridge ofSet A ∈ PromiseBPTIME ↔ A ∈ BPTIME and the inclusion of the lift of BPTIME. Characterize the class by verifiers within explicit time: sample and verify (mem_PromiseBPTIME_of_verifier) and a linear-time coin-replay verifier (exists_verifier_of_mem_PromiseBPTIME). The sample-and-verify machine is extracted from the guess-and-verify proof of #2025 into Classes/Time/SampleVerify (exists_machine_sampleVerify), and setOf_exists_mem_NTIME now uses it. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * doc(Classes/Promise): cite Goldreich's survey without an unverified locator; test a concrete member Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(Foundations): share the two-thirds dyadic fraction lemma `Classes/Time` and `Classes/Promise/Time` each proved the same private `two_thirds_le_div_iff`. Keep one public copy, `ENNReal.two_div_three_le_natCast_div_two_pow_iff`, in a small Foundations companion and use it from both modules. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * docs(PromiseBPTIME): move hierarchy reference past shared link gap --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
…y with cascading cuts) (#2233) * feat(DataStructure/Memory): word-addressed memory oracle and named field arrays Memory.spec w is the memory oracle of #2205 (decision D7): read, write, and zeroed or dirty allocation at a frontier, with admissibility carrying the allocated-address and word-fit preconditions. Field arrays are WordRAM Blocks accessed by Block.get/Block.set programs over the oracle. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * doc(bib): add Guéneau, Charguéraud and Pottier (ESOP 2018) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/StateTransition): refinements by abstraction functions with stacked potentials Refinement D E is a Module whose representation is an invariant plus an abstraction function (#2205 D2). Refinement.Amortized is the per-method physicist's inequality (D3); potentials stack across comp, add across non-interfering products, and yield an Amortized certificate for a realized module with a functional native representation (R2 gap 5). CostIsBigO is the exported asymptotic form (D6). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/StateTransition): weaken and rescale amortized refinements Amortized.mono and Amortized.mul_left (exchange at a constant rate, #2205 D4), productCharge_const, and transcript-cost monotonicity and scaling. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure/StateTransition): place productCharge beside product, outside Refinement Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(DataStructure/StateTransition): make Refinement.Amortized a structure A Prop-valued def whose body starts with an implicit binder is unfolded and auto-introduced during elaboration against an expected type, which broke term-mode uses such as Amortized.prod. A one-field structure, like the existing DataStructure.Amortized, avoids this. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * wip: array stack over memory and queue method lemmas Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(Foundations): affine cost bounds are O(size) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * wip: queue over memory Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(DataStructure/StateTransition): product answer types via Sum.elim With a match, the answer types of product D E mention D and E through the matcher's parameters, so the elaborator cannot identify clients of two products whose components differ only in admissibility (for example the pair of stacks and the pair of bounded stacks). Sum.elim D.Result E.Result depends only on the component answer types. Queue.Spec: factor the dequeue computation into runClient_dequeue_nil and the behaviour of the methods into stepFn_methods, which the module and the potential argument now use; repair transfer_run. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): queue over two array stacks over the memory oracle The M1 slice of #2205. Stack.Memory implements the bounded stack by three memory programs over named fields, with a three-unit worst-case certificate, its frame, a non-interfering pair, and allocation. Queue.Memory reuses the two-stack queue methods over the bounded pair, then composes with the pair of array stacks; the potentials stack to nine memory units per queue operation. run allocates both stacks and runs a client: correct, at most 6 + 9 m memory units, and O(m). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): Fibonacci heap insert over a record of named cells Add Record.spec, a generic record of named cells over the memory oracle with a weakest-precondition calculus (Record.wp) and a one-unit-per-operation refinement into Memory.spec. Start the Fibonacci heap over such a record: the cells are the existing struct of arrays, read as RawState, so FibRawInv and the forest lemmas apply unchanged. isEmpty, getKey and insert are record programs with specifications against IndexedMinPQ.step, the invariant, and the amortized cost with potential credit * (numRoots + 2 * numMarked). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): Fibonacci heap decreaseKey with cascading cuts over a record decreaseKey cuts v from its parent when heap order breaks, cascades up the marked ancestors (fuel bounded by the number of marks), then stores the key and updates the minimum root. Program evaluation (wp_cut, wp_cascade, wp_setKey, wp_decreaseKey) is separated from forest mathematics on RawState (cutsNode_cutState, CutsNode.cascading, Cascading.mark, ...), which reuses ValidSubtree.exists_cut, mark_pending, lower_key_no_cut and CutInv.to_fibRawInv unchanged. Amortized cost: 104 record operations. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure): credit Renfei Zhou in the record Fibonacci heap; test records and insert Retain the original authorship of the native WordRAM Fibonacci heap that Basic.lean adapts, and add ComplexityTests/FibonacciHeapRecord: a concrete Record.Layout with a program run through Record.wp and Record.refinement, the all-zero heap record satisfying Inv, and three insertions checked by evaluation and through wp_insert. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure): credit Renfei Zhou in the record decreaseKey; test a cut and cascading cut Retain the original authorship of the native Cut.lean development that DecreaseKey.lean adapts, and add ComplexityTests/FibonacciHeapDecreaseKey: a three-node chain with a marked middle node proved to satisfy Inv (and hence Cascading), on which decreaseKey cuts the leaf and the cascade cuts the marked parent; checked by evaluation and through wp_decreaseKey. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure): name the adapted module without a slash path Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
…growing structures (#2239) * feat(DataStructure/Memory): word-addressed memory oracle and named field arrays Memory.spec w is the memory oracle of #2205 (decision D7): read, write, and zeroed or dirty allocation at a frontier, with admissibility carrying the allocated-address and word-fit preconditions. Field arrays are WordRAM Blocks accessed by Block.get/Block.set programs over the oracle. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * doc(bib): add Guéneau, Charguéraud and Pottier (ESOP 2018) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/StateTransition): refinements by abstraction functions with stacked potentials Refinement D E is a Module whose representation is an invariant plus an abstraction function (#2205 D2). Refinement.Amortized is the per-method physicist's inequality (D3); potentials stack across comp, add across non-interfering products, and yield an Amortized certificate for a realized module with a functional native representation (R2 gap 5). CostIsBigO is the exported asymptotic form (D6). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/StateTransition): weaken and rescale amortized refinements Amortized.mono and Amortized.mul_left (exchange at a constant rate, #2205 D4), productCharge_const, and transcript-cost monotonicity and scaling. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure/StateTransition): place productCharge beside product, outside Refinement Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(DataStructure/StateTransition): make Refinement.Amortized a structure A Prop-valued def whose body starts with an implicit binder is unfolded and auto-introduced during elaboration against an expected type, which broke term-mode uses such as Amortized.prod. A one-field structure, like the existing DataStructure.Amortized, avoids this. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * wip: array stack over memory and queue method lemmas Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(Foundations): affine cost bounds are O(size) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * wip: queue over memory Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(DataStructure/StateTransition): product answer types via Sum.elim With a match, the answer types of product D E mention D and E through the matcher's parameters, so the elaborator cannot identify clients of two products whose components differ only in admissibility (for example the pair of stacks and the pair of bounded stacks). Sum.elim D.Result E.Result depends only on the component answer types. Queue.Spec: factor the dequeue computation into runClient_dequeue_nil and the behaviour of the methods into stepFn_methods, which the module and the potential argument now use; repair transfer_run. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): queue over two array stacks over the memory oracle The M1 slice of #2205. Stack.Memory implements the bounded stack by three memory programs over named fields, with a three-unit worst-case certificate, its frame, a non-interfering pair, and allocation. Queue.Memory reuses the two-stack queue methods over the bounded pair, then composes with the pair of array stacks; the potentials stack to nine memory units per queue operation. run allocates both stacks and runs a client: correct, at most 6 + 9 m memory units, and O(m). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): products over one memory, and glue charges for hop 3 Products over a shared memory (#2205 hop 3): - `Memory.Framed`: a refinement over `Memory.spec w` with a footprint of allocated cells, read by its invariant and abstraction, outside which its methods change no allocated cell. `Framed.ofStatic` for fixed layouts. - `Framed.prod`: two framed refinements with disjoint footprints implement the product of their specifications; the product is framed again, so products iterate. `Framed.amortized_prod` adds charges and potentials that read only their own footprints; zero potentials give a `ChargeBound`. - `Framed.of_fresh`, `Framed.prod_of_fresh`: allocation preserves structures and sets up products. - `Refinement.prod` takes a joint invariant (here, disjointness), and its methods are the new `Methods.prod`. The array stack is now `Stack.Memory.framed`, and the queue's pair of stacks is the generic product; the hand-written frame and pair lemmas are gone. Glue charges: `Refinement.Amortized.add`, `Amortized.glue` (glue at most `K` times a call's charge plus `K`), `Amortized.glue_of_one_le`, `StateTransitionSpec.totalCost_glue_le` and `Memory.one_le_charge`. `Queue.Memory.run_cost_glue` bounds memory charges and glue together by `(2K + 1)(6 + 9m)`. `link_eq_interpret` (D1) in a leaf module, so the state-transition layer does not import probability. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/StateTransition): instance search for nested products The product instances index their specification with `no_index`, so `product (product D E) F` and deeper products find `HasStepFn`, `Total` and `Deterministic` without a named instance. The test of three stacks in one memory drops its named instance. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/Memory): allocators, and a shared room budget for growing structures `Memory.Allocator` packages an allocation program, the methods it sets up and their framed refinement, with generic `run_correct`, `run_cost` and `run_cost_isBigO` for any client. `Allocator.prod` allocates structures one after the other and `Allocator.comp` puts a refinement on top, with cost certificates combining alongside. `Memory.Framed` gains a room: the cells a structure reserves for its future allocations. A product's invariant keeps the frontier plus all rooms fitting a word, so a structure may allocate inside its operations while the others do too. `Framed.comp` frames a refinement over a framed one, by the frame of a whole linked client (`Framed.modifies_demonic`). The queue over two stacks is restated through the allocator, with no setup proof of its own. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/Memory): structures already in memory, and a growth test An allocator may now take over allocated cells instead of allocating them: `Allocator.owned` names them, `Allocates.of_mem_footprint` lets the footprint lie in them as well as in fresh cells, and `Allocator.ProdPre` asks a product's two structures to take over disjoint cells. Fresh allocators default to taking over none. `Allocator.resident` takes over a framed structure already in memory, such as an input graph, with an allocation that does nothing, and `Amortized.resident` carries its certificate over. `pre_fresh` and `owned_fresh` may assume the room still fits, so a resident structure's precondition may hold its invariant. `Framed.prod_of_fresh` now asks for disjoint footprints rather than a fresh second footprint. The new test `DataStructureMemoryAlloc` checks two write-once cells that each reserve one cell and allocate it inside their first `set`, with the footprints, abstractions and frontier plus room after each step and the tight word-size boundary; and stacks held by the input, taken over beside stacks allocated from scratch in the Dijkstra shape. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/Memory): allocations keep the memory beyond the frontier An admissible run changes no cell at or above its final frontier (`Memory.mem_run_of_frontier_le`, `mem_clientState_of_frontier_le`). `Allocator.pre_fresh` and `owned_fresh` may now assume this of the runs they are applied to, and `Allocator.prod` supplies it from the first allocation's admissibility. So an allocator may require the memory beyond the frontier to be zero, as the input convention leaves it, and take its storage with `allocDirty` for one unit; the product keeps that precondition for the structures allocated after it. The test's write-once cells now take their headers this way, and a test over a nonzero cell shows that the precondition is needed. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure/PriorityQueue): the binary heap's frame keeps the frontier (Framed.ofStatic) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure): migrate the landed memory clients to Framed.ofStatic's frontier_eq and Apart The binary heap (#2237), the adjacency arrays and the direct-address table (#2238) keep the frontier, so each supplies Framed.ofStatic's frontier_eq from its existing run lemma. Dijkstra.Memory.inv_input now assumes that the frontier after allocation fits a word, which the product invariant Memory.Framed.Apart requires; run_triple supplies it from its fitting bound. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG
…domized client, survival proved on the specification (#2241) * feat(DataStructure/Memory): word-addressed memory oracle and named field arrays Memory.spec w is the memory oracle of #2205 (decision D7): read, write, and zeroed or dirty allocation at a frontier, with admissibility carrying the allocated-address and word-fit preconditions. Field arrays are WordRAM Blocks accessed by Block.get/Block.set programs over the oracle. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * doc(bib): add Guéneau, Charguéraud and Pottier (ESOP 2018) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/StateTransition): refinements by abstraction functions with stacked potentials Refinement D E is a Module whose representation is an invariant plus an abstraction function (#2205 D2). Refinement.Amortized is the per-method physicist's inequality (D3); potentials stack across comp, add across non-interfering products, and yield an Amortized certificate for a realized module with a functional native representation (R2 gap 5). CostIsBigO is the exported asymptotic form (D6). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure/StateTransition): weaken and rescale amortized refinements Amortized.mono and Amortized.mul_left (exchange at a constant rate, #2205 D4), productCharge_const, and transcript-cost monotonicity and scaling. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(DataStructure/StateTransition): place productCharge beside product, outside Refinement Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(DataStructure/StateTransition): make Refinement.Amortized a structure A Prop-valued def whose body starts with an implicit binder is unfolded and auto-introduced during elaboration against an expected type, which broke term-mode uses such as Amortized.prod. A one-field structure, like the existing DataStructure.Amortized, avoids this. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * wip: array stack over memory and queue method lemmas Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(Foundations): affine cost bounds are O(size) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * wip: queue over memory Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * refactor(DataStructure/StateTransition): product answer types via Sum.elim With a match, the answer types of product D E mention D and E through the matcher's parameters, so the elaborator cannot identify clients of two products whose components differ only in admissibility (for example the pair of stacks and the pair of bounded stacks). Sum.elim D.Result E.Result depends only on the component answer types. Queue.Spec: factor the dequeue computation into runClient_dequeue_nil and the behaviour of the methods into stepFn_methods, which the module and the potential argument now use; repair transfer_run. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): queue over two array stacks over the memory oracle The M1 slice of #2205. Stack.Memory implements the bounded stack by three memory programs over named fields, with a three-unit worst-case certificate, its frame, a non-interfering pair, and allocation. Queue.Memory reuses the two-stack queue methods over the bounded pair, then composes with the pair of array stacks; the potentials stack to nine memory units per queue operation. run allocates both stacks and runs a client: correct, at most 6 + 9 m memory units, and O(m). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): distributional refinements and a random table over memory `RandomizedSpec` gives each operation a law, a stateful `PMF` handler. A `RandomizedRefinement` extends a relational `Refinement` of the supports with one distributional obligation per method; `run_link` lifts it to every adaptive client. The identical-until-bad step reuses `OracleComp.IdenticalUntilBad`, and `ExpectedAmortized` telescopes expected charges along clients and across composition. `withCoins` adds private coins (`ProbOracleComp`) to a lower interface. Pilot: a random table stored in a field array over `Memory.spec w` with coins refines the seed-level hash-family spec `HashFamily.seedSpec`; its run from allocation has transcript law `HashFamily.evalOps` (decision D10 of #2205). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(DataStructure): stack coin-using distributional hops; deterministic hops as distributional Follow-ups to #2232 for #2205. - `RandomizedRefinement.withCoins`: coins pass through a refinement unchanged. - `RandomizedRefinement.mergeCoins`: two layers of private coins are one. - `RandomizedRefinement.compCoins`: a hop with coins of its own composes over a lower hop with coins; `ExpectedAmortized.withCoins`/`.compCoins` stack expected potentials across it. - `Refinement.toRandomized`, `Refinement.Amortized.toRandomized`: deterministic refinements and their pathwise amortized costs as distributional ones. - `Probability.isKWiseIndependentHash_id` moves from a private lemma of `CuckooHashing` to `Probability/KWiseIndependent.lean`; the memory random table gets its `kWiseSpec` contract (`RandomTable.kWiseSpec_contract_run`). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * feat(Algorithms/Lean/Karger): Karger's contraction algorithm as a randomized client, with its survival bound on the specification For #2205 (decision D10). Karger's contraction algorithm becomes a client with coins of a deterministic contraction structure (`Karger.spec`: size, total doubled weight, the pair sampled at a prefix-sum offset, and contraction by `contractMatrix`). Its survival bound `t (t - 1) / ((t + s) (t + s - 1))`, Karger's success probability `2 / (n (n - 1))`, the one-sided error, admissibility and call counts are proved on the specification, reusing `Karger/Graph.lean` and the `Probability.PMF` event-composition bounds unchanged. Supporting lemmas: `RandomizedSpec.withCoins_run_sample_bind`, `StateTransitionSpec.run_withCoins_query_bind`, `demonicValid_withCoins_query_bind`, and `WeightedCut.cutWeight_fin_two`, `totalDoubledWeight_fin_two`. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG * fix(StateTransition): use OracleComp.sumHandler after #2201 #2201 retired `ProbOracleComp.handler` and `handler_eq_sumHandler`. The coin interface `withCoins` now uses the canonical `OracleComp.sumHandler`, which `ProbOracleComp.handler` was equal to. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Karger/Contraction.lean: main's copy is byte-identical to the approved parent #2241 head a944aee, so this branch's side is kept. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG
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Independent reviewer: Claude Code (Opus 5.5), thread I confirmed the carry-forward record. All three of this PR's files are byte-identical between the two heads, and against |
worker-claude-015dlg8k-kargerbridge(Claude Code, Opus), for #2205: the first bridge-and-delete under the policy of 2026-11-02 (item 3). Stacked on #2241; the base isfeat/karger-spec, so the diff shows only this change. Retarget it when #2241 lands.Change
Karger's word-RAM contraction loop no longer proves its survival probability on machine states. It is shown to simulate the spec-level client of #2241, and the probability is taken from there.
One simulation lemma.
contractDownTo_law(WordRAM/Karger/Contract.lean) states, as anExecRandLaw, thatcontractDownTorun from aContractStateholding a multigraphWonksupervertices has these properties:k - trandcalls;36 (k² - t²) + 4instructions;tsupervertices;heldGraph wb str(activeKand the matrix read from memory), has the law ofLean.Karger.contractTimes (k - t)run on⟨k, W⟩.Each positive-weight step makes one
randcall, uniform on[0, S - 1], which has the law of the client's coinunifFin (S - 1).postRandStep_execthen contracts the pair sampled there (sampledPair_eq,contractGraph_fin). A weightless step, which drops the last supervertex, is the client'scontract 0 (k - 1)of a zero matrix. The composition usesExecRandLaw.loop_iter,rand_seqandseq_det(the Schöning/PPZ precedent). The machine-step lemmas (postRandStep_exec,mergeLoop_exec,compactPhase_exec, …) are untouched.Derived, not reproved.
contractDownTo_speckeeps its statement word for word. Its parts come from these sources:contractDownTo_law;IsContractionOf W₀:isContractionOf_of_mem_support_contractTimes;t(t-1)/(k(k-1))onSurvivalPost:survives_contractTimes.The last two are carried through the law, and on a final state the spec graph is the held matrix.
survivalPost_two_mem_eqnow usescutWeight_fin_twofrom #2241.contractDownToAt_spec,KargerMinCut,KargerSteinandFastCutare unchanged and inherit the derived bound. No abstract statement changes:KargerMinCutAbstractand its bridge build unchanged.Deleted. These go:
contractLoop_spec, which interleaved the telescoping bound, theIsContractionOftracking and the support bookkeeping with register steps;eval_map_snd_toOuterMeasure.contractLoop_lawreplacescontractLoop_specwith no probability argument.Small API changes.
ExecRandLaw(Randomized/Law.lean) becomes@[expose], likeExecRandWithin, so that a client can read the law off its witness.contractDownTo_specneeds this to rebuild its∃ mstatement.Lean.Karger.run_contractStep_bindandrun_contractStep_bind_of_eq_zerobecome public. They are the one-step runs that the simulation matches; they are not copied.Size
Proof-body lines (
scripts/proof_lengths.py):Karger/Contract.leancontractLoop_spec379 →compactPhase_exec339KargerMinCut.leanKargerStein.leanKarger/FastCut.leanChanged proofs:
contractLoop_spec379 is replaced bycontractLoop_law147. Of those 147 lines, about 55 are the existing weightless-step machine reasoning, kept as it was, and none is probability.contractDownTo_specgoes from 49 to 26, andsurvivalPost_two_mem_eqfrom 14 to 4.contractDownTo_law(22) andContractState.heldGraph_eq(3) are new. The diff is +224 / −417. ElaboratingContract.leantakes 12.5 s instead of 16.2 s; the other three files are within noise (8.8 s against 9.9 s, 18.8 s against 20.1 s, and 4.4 s against 4.3 s).Existing notions considered. These are reused:
ExecRandLawand its rules, for the law of an observation of a randomized program;Lean.Karger.Graph,specandcontractTimes, for the abstract state and the client;ContractStateandHoldsMatrix, for the representation.heldGraphis new: it is the abstraction function from machine states toLean.Karger.Graph. No existing reader of the workspace returns aGraph. The abstraction of #2253 reads aMemorylayout, notData 16.Validation
scripts/check.sh --quick --base origin/feat/karger-specpasses. It builds 26 targets: the changed modules and their clients, including Schöning, PPZ and PPSZ (clients ofLaw.lean), the Karger tests andComplexityAbstracts.KargerMinCutBridge.lake build --wfailpasses on the four Karger modules,ComplexityTests.{WordRAMKargerMinCut, WordRAMKargerStein, KargerContraction, Abstracts.KargerMinCutTests}andComplexityAbstracts.{KargerMinCutBridge, KargerMinCutAbstract}.check_hygiene.py --check-simp,check_tidy_surface.py,check_changed_files.py(against the base),lint-styleand the Batteries linters on the three changed modules pass.contractDownTo_spec,contractDownToAt_spec,SurvivalPost,survivalPost_two_mem_eqandpostRandStep_execwith the base; they are unchanged.Hosted CI runs the six gates.
Not in scope. These remain:
singleCode_specandampTrialBody_specinKargerMinCut.leanstill compose the (now derived) survival bound with the readout. Rederiving them fromtwo_div_le_toOuterMeasure_kargerwould need a readout law and would not shorten them.abstracts/…/KargerMinCutBridge.leanhas its own copy of the loop induction for the exact basis (contractLoop_exact). It does no probability.AI assistance
Written by Claude Code (Opus) as worker
worker-claude-015dlg8k-kargerbridge; not yet reviewed.🤖 Generated with Claude Code
https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG