Tooling: faster ExclusionCircuit and DisjointTensor support masks with identical receipts

certificates/disjoint-tensor-compression.json

@@ -341,8 +341,8 @@
     "scripts/audit_disjoint_tensor.py": "477db540e972b82751fac6a3a6d6e38fb4141e967261b1f9c260e2c686479a78",
     "scripts/binary_phase_frames.py": "4148cfa313cf050ed25296e8db36d35871520b8318fd086c7d1facf0c6af67d7",
     "scripts/complex_compression.py": "9b6f758a5985ba5d9fdd726fe6556b3d3b4bd9d98aaf8ba06a7bb58093c4c504",
-    "scripts/exclusion_circuit.py": "b253f9d7318becda1c1f3b24e2287ed44a9c27fcea00cf9d531afb950d0457a0",
-    "scripts/experiments/disjoint_tensor.py": "102dd59bf96033f96ba0dab4c2aba77b3a7a73b67b0f96929ff8b20a98b91cd8"
+    "scripts/exclusion_circuit.py": "f9fbcd6e85e442cbd0926ac0887414e20735b2dc923d2d5822c803ceb46726d3",
+    "scripts/experiments/disjoint_tensor.py": "085600fc922ae167b5981505e1a5caba4d1c1df15482f61d83d2c086fa89eac1"
   },
   "status": "IMPROVED FINITE COMPLEX NETWORK; NO NEW MULTIPLICATION KAPPA",
   "upstream_commit": "adc7f1241b42e322a6451854ab7e4b4c146bf78a"

certificates/dyadic-central-factor.json

@@ -101,9 +101,9 @@
     "scripts/audit_complex_centers.py": "166b18f560cd0d520d23fa29ee8147e0ea056358c4268a466ec458195a97a960",
     "scripts/binary_phase_frames.py": "4148cfa313cf050ed25296e8db36d35871520b8318fd086c7d1facf0c6af67d7",
     "scripts/complex_compression.py": "9b6f758a5985ba5d9fdd726fe6556b3d3b4bd9d98aaf8ba06a7bb58093c4c504",
-    "scripts/exclusion_circuit.py": "b253f9d7318becda1c1f3b24e2287ed44a9c27fcea00cf9d531afb950d0457a0",
+    "scripts/exclusion_circuit.py": "f9fbcd6e85e442cbd0926ac0887414e20735b2dc923d2d5822c803ceb46726d3",
     "scripts/experiments/complex_centers.py": "3744396587d729253d80980f6310b56e7bf0ea21b165bd178d0d6d4c49faf2e2",
-    "scripts/experiments/disjoint_tensor.py": "102dd59bf96033f96ba0dab4c2aba77b3a7a73b67b0f96929ff8b20a98b91cd8",
+    "scripts/experiments/disjoint_tensor.py": "085600fc922ae167b5981505e1a5caba4d1c1df15482f61d83d2c086fa89eac1",
     "scripts/general_network_guard.py": "790a2064449afdbffd6dbd4adbcf4a28eaf41931ce7134e4a4e8766f3764270c"
   },
   "status": "COMPLEX INTERFACE HEADROOM; RETAINED KAPPA 2^-31",

certificates/parity-side.json

@@ -120,7 +120,7 @@
     "docs/research/parity-side.md": "75de20f8dcd3d1a2e2d19bc087eda50a6cc77027651f48198868426a80cd12f2",
     "scripts/audit_parity_side.py": "7cbdd405ce11fa6f7ffcbef3811174f8685ad4640e9330176601d3b3d3e95390",
     "scripts/binary_phase_frames.py": "4148cfa313cf050ed25296e8db36d35871520b8318fd086c7d1facf0c6af67d7",
-    "scripts/experiments/disjoint_tensor.py": "102dd59bf96033f96ba0dab4c2aba77b3a7a73b67b0f96929ff8b20a98b91cd8",
+    "scripts/experiments/disjoint_tensor.py": "085600fc922ae167b5981505e1a5caba4d1c1df15482f61d83d2c086fa89eac1",
     "scripts/experiments/mixed_point_circuit.py": "f509362b5031976a22af351fd158ae0b4520fa4f286a5176ec37023d672a7ddc",
     "scripts/experiments/parity_phase_repair.py": "1f76f3b96ed556ed901835bd101d0e2588c997d2ed39bdfca097f0187aa86d40",
     "scripts/experiments/parity_side.py": "1363ebf82d4c39e458e7bede8253688271008374db70ed4284df84253c8d092b"

certificates/positive-side-core.json

@@ -23101,7 +23101,7 @@
   "source_sha256": {
     "docs/research/positive-side-core.md": "fab9ff0ed8de56cb9c4c1587b65f956f706ab8f3b8afcb9212366218e227f49d",
     "scripts/audit_positive_side.py": "b021aad944d8a6c023e57b1b48937854803bbb370240c93e0fe359d831c838c9",
-    "scripts/exclusion_circuit.py": "b253f9d7318becda1c1f3b24e2287ed44a9c27fcea00cf9d531afb950d0457a0",
+    "scripts/exclusion_circuit.py": "f9fbcd6e85e442cbd0926ac0887414e20735b2dc923d2d5822c803ceb46726d3",
     "scripts/experiments/positive_side_core.py": "0d453ab7e869d2cf6a43d6865de82583edb390d3c75038271f0fc09e0f3828ba",
     "scripts/experiments/rank_product_core.py": "7a91c1188c5d42e864a5d2e42397b09c435b526ae4f4210c44bf615de488708e",
     "scripts/experiments/shared_core.py": "d3c59b61229956cb54ae1ef9145ed213abdf1ae743929de145a77c43656f01a8",

certificates/ternary-side.json

@@ -1563,8 +1563,8 @@
     "notes/ternary-five-subsets.tex": "f8553a7ad7da9fcd85def67360f7c070ec6c15911c3310fca360d821e1ed1ccd",
     "scripts/audit_ternary_side.py": "5e86566eee32031e1829d26ea17a7372e4802e2f7d76a2caa3ae16de3ab072c1",
     "scripts/certify.py": "2348d95008276c5d5764f7e028c3918e484582cd589bd4d9b82919161745e53e",
-    "scripts/exclusion_circuit.py": "b253f9d7318becda1c1f3b24e2287ed44a9c27fcea00cf9d531afb950d0457a0",
-    "scripts/experiments/disjoint_tensor.py": "102dd59bf96033f96ba0dab4c2aba77b3a7a73b67b0f96929ff8b20a98b91cd8",
+    "scripts/exclusion_circuit.py": "f9fbcd6e85e442cbd0926ac0887414e20735b2dc923d2d5822c803ceb46726d3",
+    "scripts/experiments/disjoint_tensor.py": "085600fc922ae167b5981505e1a5caba4d1c1df15482f61d83d2c086fa89eac1",
     "scripts/experiments/prime_core.py": "080a89a2c91505b509068698542843c9d7af3cdec01b5c88972107dc9c688c62",
     "scripts/experiments/rank_product_core.py": "7a91c1188c5d42e864a5d2e42397b09c435b526ae4f4210c44bf615de488708e",
     "scripts/experiments/shared_core.py": "d3c59b61229956cb54ae1ef9145ed213abdf1ae743929de145a77c43656f01a8",

research/disjoint-tensor-support-masks/NOTICE.md

@@ -0,0 +1,11 @@
+# Notice — disjoint-tensor support masks
+
+Douglas R. Colkitt authored the disjoint-tensor compression screen, the
+`DisjointTensor` recurrence and embedding, and the original expected-support
+coefficient checks consumed by this tooling package.
+
+This package adds an equivalence-preserving closed-form rewrite of the
+historical leave-intersecting-inputs expected-support genexpr inside
+`DisjointTensor.verify`, with identical receipts and updated source pins only.
+
+Prepared by Wentao Li with substantial AI assistance, under Apache-2.0.

research/disjoint-tensor-support-masks/README.md

@@ -0,0 +1,107 @@
+# Faster DisjointTensor.verify output supports with identical receipts
+
+**Tooling improvement; no new kappa.**
+Landed with open [CrocSwap/integer-mult-bounds#2001](https://github.com/CrocSwap/integer-mult-bounds/pull/2001) so shared certificate JSON files carry both the `exclusion_circuit.py` and `disjoint_tensor.py` source pins without a merge conflict.
+ At base
+`0b1cccf86e2f5132ed286a26ef0a681a495740ea`, the historical disjoint-tensor
+checker (`scripts/experiments/disjoint_tensor.py:DisjointTensor.verify`) spends
+most of its wall time on the leave-intersecting-inputs expected-support genexpr
+
+```text
+sum(1<<i for i,S in enumerate(self.inputs) if not S&T)
+```
+
+for every triple output `T` on the certificate circuit (`h=26`, 2600 inputs).
+
+This change replaces that genexpr with an equivalent closed-form point-incidence
+mask `full ^ OR_{p in T} vertex[p]`, keeps every support and embedding
+`require`, and leaves `dag_sha256` unchanged. Only the source pin for
+`scripts/experiments/disjoint_tensor.py` changes inside the four certificates
+that bind that file.
+
+## Reproduce
+
+Python **3.12**, standard library only, from the repository root:
+
+```sh
+python3.12 -I -B research/disjoint-tensor-support-masks/verify.py
+python3.12 -I -O -B research/disjoint-tensor-support-masks/verify.py
+python3.12 -B scripts/research_package.py --package research/disjoint-tensor-support-masks
+python3.12 -I -B research/disjoint-tensor-support-masks/benchmark.py --rounds 5
+```
+
+Expected:
+
+```text
+PASS_DISJOINT_TENSOR_SUPPORT_MASKS verify_cases=6 mask_cases=7416 certs=4 no_new_kappa
+PASS_REGISTERED_RESEARCH_PACKAGE research/disjoint-tensor-support-masks outcome=completed
+PASS_IDENTICAL_DISJOINT_TENSOR_SUPPORT_MASK_RECEIPTS
+```
+
+Default verify is read-only. Full `make verify`, selected cold replay, Lean, and
+multiplication-theorem obligations were not rerun for this isolated
+historical-checker change.
+
+## Result
+
+On Linux / CPython 3.12.3 (Linux-6.12.94+-x86_64-with-glibc2.39), five
+alternating fresh-process pairs timing only `DisjointTensor(26).verify`
+(construction excluded) gave median wall time **1.101 → 0.606 seconds (1.82×)**.
+Timing is host-descriptive and is not a correctness gate; all samples and
+environment pins are in [RESULT.json](RESULT.json). Every verify receipt matches
+the baseline checker fieldwise (`roles`, `additions`, `dag_sha256`, flags).
+
+## Equivalence
+
+Precompute `vertex[p] = OR { 1<<i : input i contains point p }` and
+`full = (1<<len(inputs))-1`. For each output mask `T`,
+
+- historical: bits of inputs `S` with `S&T == 0`
+- closed form: `full ^ OR_{p in T} vertex[p]`
+
+An input that meets `T` in one or more points is cleared exactly once by the
+OR, matching the Boolean filter. An XOR-of-vertex mutant cancels inputs that
+meet `T` twice and is rejected by the package controls. Embedding, recurrence
+and `dag_sha256` paths are unchanged. Support checks use `require`, so admission
+stays enforced under `-O`.
+
+## Open next questions
+
+1. **Question:** Is `DisjointTensor.verify_frames` / `frame_data` worth a
+   separate identical-receipt rewrite?
+   **Why it matters:** On `h=26`, `verify_frames` dominates the full certificate
+   wall time via point-union loops; it is a different object from the verify
+   expected-support path measured here.
+   **First step:** Profile `DisjointTensor(26).verify_frames` alone and check
+   whether ancestor/target-union construction can reuse precomputed incidence
+   without changing transition receipts.
+   **Blocked by:** Out of this session’s stop rule.
+
+2. **Question:** Should `DisjointTensor.verify`'s `dag_sha256` `json.dumps` path
+   get a hand-rolled formatter like the mixed-point / SharedPoint digests?
+   **Why it matters:** `json.dumps` is a secondary share of verify after the
+   support genexpr; a byte-identical encoder would be a different object.
+   **First step:** Profile the post-mask verify residual and compare a
+   hand-rolled `[[i,args,str(support)]]` encoder against the committed digest.
+   **Blocked by:** Out of this session’s stop rule.
+
+## Overlap and credit
+
+Closest priors (different objects):
+[CrocSwap/integer-mult-bounds#756](https://github.com/CrocSwap/integer-mult-bounds/pull/756),
+[CrocSwap/integer-mult-bounds#1793](https://github.com/CrocSwap/integer-mult-bounds/pull/1793),
+[CrocSwap/integer-mult-bounds#1861](https://github.com/CrocSwap/integer-mult-bounds/pull/1861),
+[CrocSwap/integer-mult-bounds#1922](https://github.com/CrocSwap/integer-mult-bounds/pull/1922),
+[CrocSwap/integer-mult-bounds#1984](https://github.com/CrocSwap/integer-mult-bounds/pull/1984),
+[CrocSwap/integer-mult-bounds#1994](https://github.com/CrocSwap/integer-mult-bounds/pull/1994),
+[CrocSwap/integer-mult-bounds#2001](https://github.com/CrocSwap/integer-mult-bounds/pull/2001)
+(ExclusionCircuit leave-two-out / embedding masks on `scripts/exclusion_circuit.py`;
+this package rewrites the triple-disjoint expected-support path inside
+`scripts/experiments/disjoint_tensor.py` only). No competing open PR on the
+`DisjointTensor.verify` support-mask object at refresh.
+
+Douglas R. Colkitt authored the disjoint-tensor compression screen and original
+checker. Prepared by Wentao Li
+([VictorLiwentao](https://github.com/VictorLiwentao),
+[@Is__Victor](https://x.com/Is__Victor)) with substantial AI assistance, under
+Apache-2.0.

research/disjoint-tensor-support-masks/RESULT.json

@@ -0,0 +1,50 @@
+{
+  "environment": {
+    "executable": "/usr/bin/python3.12",
+    "platform": "Linux-6.12.94+-x86_64-with-glibc2.39",
+    "python": "3.12.3 (main, Aug 31 2026, 10:18:26) [GCC 13.3.0]"
+  },
+  "fixture": "DisjointTensor(26).verify only (construction excluded)",
+  "median_baseline_seconds": 1.100771291000001,
+  "median_optimized_seconds": 0.606201886000008,
+  "median_ratio": 1.8158493340616007,
+  "no_new_kappa": true,
+  "rounds": 5,
+  "samples": [
+    {
+      "baseline_seconds": 1.0696186399999874,
+      "optimized_seconds": 0.6307327730000338,
+      "ratio": 1.6958348856876826,
+      "round": 0
+    },
+    {
+      "baseline_seconds": 1.1055623980000178,
+      "optimized_seconds": 0.632604850000007,
+      "ratio": 1.747635033149059,
+      "round": 1
+    },
+    {
+      "baseline_seconds": 1.0914323959999592,
+      "optimized_seconds": 0.606201886000008,
+      "ratio": 1.8004437485368443,
+      "round": 2
+    },
+    {
+      "baseline_seconds": 1.100771291000001,
+      "optimized_seconds": 0.5845005470000046,
+      "ratio": 1.8832681964966445,
+      "round": 3
+    },
+    {
+      "baseline_seconds": 1.1040789429999904,
+      "optimized_seconds": 0.5881630169999994,
+      "ratio": 1.8771648524102826,
+      "round": 4
+    }
+  ],
+  "source_sha256": {
+    "baseline": "102dd59bf96033f96ba0dab4c2aba77b3a7a73b67b0f96929ff8b20a98b91cd8",
+    "production": "085600fc922ae167b5981505e1a5caba4d1c1df15482f61d83d2c086fa89eac1"
+  },
+  "status": "PASS_IDENTICAL_DISJOINT_TENSOR_SUPPORT_MASK_RECEIPTS"
+}

research/disjoint-tensor-support-masks/SOURCES.json

@@ -0,0 +1,78 @@
+{
+  "schema_version": 1,
+  "base_commit": "0b1cccf86e2f5132ed286a26ef0a681a495740ea",
+  "files": [
+    {
+      "path": "docs/research/agent-task-catalog.json",
+      "usage": "provenance",
+      "git_blob": "06c96f5579bb67ed1b86d334e78fbed7da6945f1",
+      "sha256": "6686ad58f1fbdbc87134a78901b60fd53a20d3984355e91defbbebc9e9fa8075"
+    },
+    {
+      "path": "certificates/selected-result.json",
+      "usage": "provenance",
+      "git_blob": "ae6a99f28aa468649eb66a361e764d769363bf11",
+      "sha256": "10b9e340fd8e354a37a0c4813c90e5de1dd42044b5f6aca4a3fc5a42b685fa32"
+    },
+    {
+      "path": "certificates/disjoint-tensor-compression.json",
+      "usage": "provenance",
+      "git_blob": "323a46ad8fe77f3d70747b97ce5a0d0fcffaaac5",
+      "sha256": "3f2b37542f9581f9d3238cccfce19fd3e2964c89ec4af4ff047fb8041f5c3cd1"
+    },
+    {
+      "path": "certificates/ternary-side.json",
+      "usage": "provenance",
+      "git_blob": "2c5c9f6ea8ba3200c39283bc7e0059d802268c71",
+      "sha256": "a01961cf95a3da641302bce643bdb9f2bfbff5094358c7029e0104a90d8a374f"
+    },
+    {
+      "path": "certificates/dyadic-central-factor.json",
+      "usage": "provenance",
+      "git_blob": "a85cb8a395065fffc985ead49cb0362532909c97",
+      "sha256": "ffae0f0a22863718e3134a924592dcf4b05e919223323ba536c587c592bfe6a1"
+    },
+    {
+      "path": "certificates/parity-side.json",
+      "usage": "provenance",
+      "git_blob": "afbbf2d3b7c21526853f7db7860071c4a63c475d",
+      "sha256": "4533d0123659fe7917fbab169e5f4abdbca27510335451feb84b87bea8b668d5"
+    },
+    {
+      "path": "docs/research/disjoint-tensor-compression.md",
+      "usage": "provenance",
+      "git_blob": "5c6f8f52f79e4c56f47d5e9cd26d5549f02b60fc",
+      "sha256": "d7d59f70653b8fbb3cb31fbe6466f73ae48a6b79852f2fe649a9d38e1b9763d1"
+    },
+    {
+      "path": "notes/disjoint-tensor-compression.tex",
+      "usage": "provenance",
+      "git_blob": "0e3cad1b933f532cd83d6a3e93114c4c9361e65c",
+      "sha256": "528cba56872313b8cd63ff11f523a399dfb3c85cae1a764110ae9d26ac9151ac"
+    },
+    {
+      "path": "scripts/experiments/disjoint_tensor.py",
+      "usage": "provenance",
+      "git_blob": "dd196e67162c349d9b6f7aa27edbed2b1b0b601f",
+      "sha256": "102dd59bf96033f96ba0dab4c2aba77b3a7a73b67b0f96929ff8b20a98b91cd8"
+    },
+    {
+      "path": "scripts/audit_disjoint_tensor.py",
+      "usage": "provenance",
+      "git_blob": "08cb8184abcb7f81434395871152e4902df8cf84",
+      "sha256": "477db540e972b82751fac6a3a6d6e38fb4141e967261b1f9c260e2c686479a78"
+    },
+    {
+      "path": "scripts/exclusion_circuit.py",
+      "usage": "provenance",
+      "git_blob": "aaa99986c4b81c5d4fbe016fd216a4818940bb95",
+      "sha256": "b253f9d7318becda1c1f3b24e2287ed44a9c27fcea00cf9d531afb950d0457a0"
+    },
+    {
+      "path": "scripts/binary_phase_frames.py",
+      "usage": "provenance",
+      "git_blob": "c8e4fa71fe60550324f9e43c1dd5ad6d9bf4e2f4",
+      "sha256": "4148cfa313cf050ed25296e8db36d35871520b8318fd086c7d1facf0c6af67d7"
+    }
+  ]
+}