Problem packetResearch packetR2
Exact additive-cube-free image pools through length 12
Link to a section
Executable material is recorded. Successful replay is a separate check.
Recorded status: available
Recorded scope: every finite word over {0,1,2,3} of lengths 8 through 12, plus the resulting necessary matrix filter for fixed points using all four letters
Complete recorded scope and conditions
{
"kind": "bounded",
"statement": "every finite word over {0,1,2,3} of lengths 8 through 12, plus the resulting necessary matrix filter for fixed points using all four letters",
"bounds": {
"image_length": {
"min": 8,
"max": 12
},
"alphabet_size": {
"min": 4,
"max": 4
}
},
"exhaustive": true
}Originating problem: Additive-cube avoidance on the alphabet zero through three
Authored record and scope
- Authored title
- Exact additive-cube-free image pools through length 12
- Record type
- artifact
- Stored status
- available
- Evidence grade
- executable
- Recorded scope data
- { "kind": "bounded", "statement": "every finite word over {0,1,2,3} of lengths 8 through 12, plus the resulting necessary matrix filter for fixed points using all four letters", "bounds": { "image_length": { "min": 8, "max": 12 }, "alphabet_size": { "min": 4, "max": 4 } }, "exhaustive": true }
2Authored explanation
The Python program grows every word over \(\{0,1,2,3\}\) through length 12 and rejects a prefix as soon as an additive cube ends at its final position. The exact numbers of surviving words at lengths 8 through 12 are 42,070, 150,560, 538,214, 1,924,738, and 6,772,220. It also retains the count for every pair of length and sum, first letter, and symbol-support mask.
A separate C++ program enumerates all \(4^n\) words by two-bit integer code for each \(8\le n\le12\). It scans factors in block-length and start-position order. The five complete sum-count vectors agree exactly with the recursive program.
Consider a fixed point that uses all four letters. Each image \(f(x)\) then occurs as a factor and must itself avoid additive cubes. Applying this necessary condition to the 2,212 expanding matrices leaves 1,146 matrices. Each has at least one letter whose viable image pool contains a word beginning with that letter, so the matrix-level prolongability test makes no further deletion. Complement conjugation reduces the tranche to 588 orbits, with 30 fixed matrices.
The support masks permit an exact incidence-graph filter without enumerating individual image tuples. For each tuple of four support categories, the program tests whether some self-starting image gives a prolongation letter whose reachable component contains all four letters. After this filter, the representative matrix \((8,1,2,2)\), with lengths \((8,9,10,11)\) and sums \((2,4,6,8)\), has the smallest retained pool: 23,298,600 image tuples. Its four unfiltered image-pool sizes are 1, 33, 510, and 5,831. The output records the first twelve orbit representatives under both the prolongability and all-four-reachability rankings. Fixed points that omit a letter lie outside this first tranche and require a separate subalphabet audit.
Files and source
Files embedded in this record. Matching a file hash confirms its identity.
- R2.txt7,747 bytes · No SHA-256 recorded
Preview R2.txt
from collections import defaultdict from hashlib import sha256 from itertools import product import json counts = defaultdict(int) first_counts = defaultdict(int) mask_counts = defaultdict(int) first_mask_counts = defaultdict(int) prefixes = [0] * 13 word = [] prefix_sum = [0] def enumerate_words(): length = len(word) if length >= 8: total = prefix_sum[-1] support_mask = sum(1 << letter for letter in set(word)) counts[(length, total)] += 1 first_counts[(length, total, word[0])] += 1 mask_counts[(length, total, support_mask)] += 1 first_mask_counts[(length, total, word[0], support_mask)] += 1 if length == 12: return for letter in range(4): word.append(letter) prefix_sum.append(prefix_sum[-1] + letter) new_length = length + 1 safe = True for block in range(1, new_length // 3 + 1): third = prefix_sum[new_length] - prefix_sum[new_length - block] second = ( prefix_sum[new_length - block] - prefix_sum[new_length - 2 * block] ) first = ( prefix_sum[new_length - 2 * block] - prefix_sum[new_length - 3 * block] ) if first == second == third: safe = False break if safe: prefixes[new_length] += 1 enumerate_words() prefix_sum.pop() word.pop() def expanding_matrix(a, b, c, d): determinant = a * d - b * c trace = a + d return ( determinant != 0 and (determinant - trace + 1) * determinant > 0 and (determinant + trace + 1) * determinant > 0 and (determinant - 1) * determinant > 0 ) def complement_conjugate(matrix): a, b, c, d = matrix return a + 3 * b, -b, 3 * a + 9 * b - c - 3 * d, d - 3 * b def reaches_all(start, masks): reached = 1 << start while True: expanded = reached for letter in range(4): if reached & (1 << letter): expanded |= masks[letter] if expanded == reached: return reached == 15 reached = expanded def reachable_tuple_count(matrix): a, b, c, d = matrix categories = [] for letter in range(4): length = a + b * letter total = c + d * letter letter_categories = [] for mask in range(1, 16): pool = mask_counts[(length, total, mask)] self_start = first_mask_counts[(length, total, letter, mask)] if self_start: letter_categories.append((mask, True, self_start)) if pool > self_start: letter_categories.append((mask, False, pool - self_start)) categories.append(letter_categories) answer = 0 for selected in product(*categories): masks = [item[0] for item in selected] if not any( selected[letter][1] and reaches_all(letter, masks) for letter in range(4) ): continue multiplicity = 1 for item in selected: multiplicity *= item[2] answer += multiplicity return answer enumerate_words() expanding = set() all_images_safe = set() prolongable_pool = set() prolongable_tuple_counts = {} for a in range(8, 13): for b in range(-4, 5): lengths = [a + b * x for x in range(4)] if any(length < 8 or length > 12 for length in lengths): continue for c in range(3 * lengths[0] + 1): for d in range(-36, 37): sums = [c + d * x for x in range(4)] if any(total < 0 or total > 3 * lengths[x] for x, total in enumerate(sums)): continue if not expanding_matrix(a, b, c, d): continue matrix = a, b, c, d expanding.add(matrix) if not all(counts[(lengths[x], sums[x])] for x in range(4)): continue all_images_safe.add(matrix) if any(first_counts[(lengths[x], sums[x], x)] for x in range(4)): prolongable_pool.add(matrix) pool_sizes = [ counts[(lengths[x], sums[x])] for x in range(4) ] missing_start = [ pool_sizes[x] - first_counts[(lengths[x], sums[x], x)] for x in range(4) ] all_tuples = 1 no_prolongable_tuples = 1 for size in pool_sizes: all_tuples *= size for size in missing_start: no_prolongable_tuples *= size prolongable_tuple_counts[matrix] = ( all_tuples - no_prolongable_tuples ) assert all(complement_conjugate(matrix) in prolongable_pool for matrix in prolongable_pool) orbit_counts = {} for matrix, count in prolongable_tuple_counts.items(): representative = min(matrix, complement_conjugate(matrix)) if representative in orbit_counts: assert orbit_counts[representative] == count orbit_counts[representative] = count reachable_counts = {} for matrix in orbit_counts: count = reachable_tuple_count(matrix) assert count == reachable_tuple_count(complement_conjugate(matrix)) reachable_counts[matrix] = count priority_orbits = [] for matrix, count in sorted(orbit_counts.items(), key=lambda item: (item[1], item[0]))[:12]: a, b, c, d = matrix priority_orbits.append({ "all_four_reachable_image_tuples": str( reachable_tuple_count(matrix) ), "lengths": [a + b * x for x in range(4)], "matrix": list(matrix), "prolongable_image_tuples": str(count), "sums": [c + d * x for x in range(4)], }) reachable_priority_orbits = [] for matrix, count in sorted(reachable_counts.items(), key=lambda item: (item[1], item[0]))[:12]: a, b, c, d = matrix reachable_priority_orbits.append({ "all_four_reachable_image_tuples": str(count), "lengths": [a + b * x for x in range(4)], "matrix": list(matrix), "prolongable_image_tuples": str( prolongable_tuple_counts[matrix] ), "sums": [c + d * x for x in range(4)], }) report = { "additive_cube_free_prefixes": prefixes[1:], "image_pools": { str(length): { "sum_counts": [ counts[(length, total)] for total in range(3 * length + 1) ], "total": sum( counts[(length, total)] for total in range(3 * length + 1) ), } for length in range(8, 13) }, "matrix_filter_for_all_four_used_letters": { "expanding_before_image_filter": len(expanding), "every_image_pool_nonempty": len(all_images_safe), "some_prolongable_letter_pool": len(prolongable_pool), "complement_fixed_matrices": sum( complement_conjugate(matrix) == matrix for matrix in prolongable_pool ), "complement_orbits": len({ min(matrix, complement_conjugate(matrix)) for matrix in prolongable_pool }), }, "smallest_all_four_reachable_image_tuple_orbits": reachable_priority_orbits, "smallest_prolongable_image_tuple_orbits": priority_orbits, } payload = json.dumps(report, sort_keys=True, separators=(",", ":")) print(payload) print(sha256((payload + "\n").encode()).hexdigest())File identity
- Recorded filename
- R2.txt
- Download SHA-256
- 54dc2a6de1587110b8addfa3fa64ad5bdbc8f27e305c082487d6df9cebf21cb0
- independent_verifier.txt1,543 bytes · Matches recorded SHA-256
Preview independent_verifier.txt
#include <cstdint> #include <iostream> #include <vector> using u64 = std::uint64_t; int main() { for (int n = 8; n <= 12; ++n) { const u64 words = u64{1} << (2 * n); std::vector<u64> counts(3 * n + 1, 0); for (u64 code = 0; code < words; ++code) { std::vector<int> prefix(n + 1, 0); u64 value = code; for (int i = 0; i < n; ++i) { prefix[i + 1] = prefix[i] + static_cast<int>(value & 3); value >>= 2; } bool safe = true; for (int block = 1; 3 * block <= n && safe; ++block) { for (int start = 0; start + 3 * block <= n; ++start) { const int first = prefix[start + block] - prefix[start]; const int second = prefix[start + 2 * block] - prefix[start + block]; const int third = prefix[start + 3 * block] - prefix[start + 2 * block]; if (first == second && second == third) { safe = false; break; } } } if (safe) ++counts[prefix[n]]; } u64 total = 0; for (u64 count : counts) total += count; std::cout << "n=" << n << " total=" << total << " counts="; for (std::size_t i = 0; i < counts.size(); ++i) { if (i) std::cout << ','; std::cout << counts[i]; } std::cout << '\n'; } }File identity
- Recorded filename
- independent_verifier.txt
- Recorded SHA-256
- 45b0597e5869fad6945edfc8c1c30dfba7bfb41d537865b2a5f3cfa4cbdc205a
- Download SHA-256
- 45b0597e5869fad6945edfc8c1c30dfba7bfb41d537865b2a5f3cfa4cbdc205a
Continue this work
Replay material: complete
4Reproduce
The command, source, environment, and expected result are recorded.
python3 additive_cube_image_pool.pyVerification source: Inline Python 3 enumerator and independent C++17 verifier prepared and executed on 2026-07-28
Expected output
{
"source_sha256": "21f0530ef09ee3c8833e02fb2d9589578dd6705da00b1b974370c30eaa10944e",
"payload_sha256_including_final_lf": "b634f376e1accef14a8c22e6c92b5d22b66ddd03336d15512384b5dfa23bfb61",
"stdout_sha256": "647c836d17d6fcce497cd133ff6992a2d58028daee67824a0ddc8dff6f9fdc0e",
"additive_cube_free_word_counts": {
"8": 42070,
"9": 150560,
"10": 538214,
"11": 1924738,
"12": 6772220
},
"expanding_matrices_before_image_filter": 2212,
"all_four_image_pools_nonempty": 1146,
"some_prolongable_letter_pool": 1146,
"complement_fixed_matrices": 30,
"complement_matrix_orbits": 588,
"smallest_prolongable_image_tuple_orbit": {
"matrix": [
8,
0,
8,
-2
],
"lengths": [
8,
8,
8,
8
],
"sums": [
8,
6,
4,
2
],
"prolongable_image_tuples": "48580348"
},
"smallest_all_four_reachable_image_tuple_orbit": {
"matrix": [
8,
1,
2,
2
],
"lengths": [
8,
9,
10,
11
],
"sums": [
2,
4,
6,
8
],
"all_four_reachable_image_tuples": "23298600"
},
"maximum_resident_bytes": 13844480
}Recorded artifact fields
5What it produced
Storage bound
6How it connects
Used by
- attempt
Depends on
- artifact
Tested by
- artifact
Recorded for
- problem
Cite this record
Cite the original sources separately.
Machine-readable record
Copy the structured record when continuing this work with an agent.
{
"schema": "theoremdb-agent-record-v1",
"ref": "R2",
"content_hash": null,
"slug": "ac0123-artifact-finite-image-pools",
"type": "artifact",
"title": "Exact additive-cube-free image pools through length 12",
"summary": "Two independent exhaustive programs count every additive-cube-free word of lengths 8 through 12 by sum, reduce the all-four-letters matrix tranche to 588 complement orbits, and rank its smallest incidence-valid image-tuple pools.",
"relevance": "For Additive-cube avoidance on the alphabet zero through three, record ac0123-artifact-finite-image-pools (“Exact additive-cube-free image pools through length 12”) supplies evidence or a replay used to check the packet. The record states: Two independent exhaustive programs count every additive-cube-free word of lengths 8 through 12 by sum, reduce the all-four-letters matrix tranche to 588 complement orbits, and rank its smallest incidence-valid image-tuple pools.",
"relevance_source": "recorded",
"body": "The Python program grows every word over \\(\\{0,1,2,3\\}\\) through length 12 and rejects a prefix as soon as an additive cube ends at its final position. The exact numbers of surviving words at lengths 8 through 12 are 42,070, 150,560, 538,214, 1,924,738, and 6,772,220. It also retains the count for every pair of length and sum, first letter, and symbol-support mask.\n\nA separate C++ program enumerates all \\(4^n\\) words by two-bit integer code for each \\(8\\le n\\le12\\). It scans factors in block-length and start-position order. The five complete sum-count vectors agree exactly with the recursive program.\n\nConsider a fixed point that uses all four letters. Each image \\(f(x)\\) then occurs as a factor and must itself avoid additive cubes. Applying this necessary condition to the 2,212 expanding matrices leaves 1,146 matrices. Each has at least one letter whose viable image pool contains a word beginning with that letter, so the matrix-level prolongability test makes no further deletion. Complement conjugation reduces the tranche to 588 orbits, with 30 fixed matrices.\n\nThe support masks permit an exact incidence-graph filter without enumerating individual image tuples. For each tuple of four support categories, the program tests whether some self-starting image gives a prolongation letter whose reachable component contains all four letters. After this filter, the representative matrix \\((8,1,2,2)\\), with lengths \\((8,9,10,11)\\) and sums \\((2,4,6,8)\\), has the smallest retained pool: 23,298,600 image tuples. Its four unfiltered image-pool sizes are 1, 33, 510, and 5,831. The output records the first twelve orbit representatives under both the prolongability and all-four-reachability rankings. Fixed points that omit a letter lie outside this first tranche and require a separate subalphabet audit.",
"status": "available",
"evidence_grade": "executable",
"scope": {
"kind": "bounded",
"statement": "every finite word over {0,1,2,3} of lengths 8 through 12, plus the resulting necessary matrix filter for fixed points using all four letters",
"bounds": {
"image_length": {
"min": 8,
"max": 12
},
"alphabet_size": {
"min": 4,
"max": 4
}
},
"exhaustive": true
},
"reproduction": {
"schema": "theoremdb-reproduction-v1",
"readiness": "complete",
"kind": "inline_exact_finite_word_pool_enumerator_with_independent_verifier",
"command": "python3 additive_cube_image_pool.py",
"entrypoint": "Join source_lines with LF characters and append one terminal LF as additive_cube_image_pool.py; source_sha256 includes that terminal LF",
"runtime": "Python 3.9.6 standard library; independent Apple clang 21.0.0 C++17 verifier",
"citation": {
"locator": "Inline Python 3 enumerator and independent C++17 verifier prepared and executed on 2026-07-28"
},
"dependencies": [
{
"name": "CPython",
"version": "3.9.6",
"license": "PSF-2.0"
},
{
"name": "Python standard library",
"version": "3.9.6",
"license": "PSF-2.0"
},
{
"name": "Apple clang and libc++ for the independent verifier",
"version": "21.0.0, arm64-apple-darwin25.2.0",
"license": "Apache-2.0 WITH LLVM-exception"
}
],
"outputs": {
"source_sha256": "21f0530ef09ee3c8833e02fb2d9589578dd6705da00b1b974370c30eaa10944e",
"payload_sha256_including_final_lf": "b634f376e1accef14a8c22e6c92b5d22b66ddd03336d15512384b5dfa23bfb61",
"stdout_sha256": "647c836d17d6fcce497cd133ff6992a2d58028daee67824a0ddc8dff6f9fdc0e",
"additive_cube_free_word_counts": {
"8": 42070,
"9": 150560,
"10": 538214,
"11": 1924738,
"12": 6772220
},
"expanding_matrices_before_image_filter": 2212,
"all_four_image_pools_nonempty": 1146,
"some_prolongable_letter_pool": 1146,
"complement_fixed_matrices": 30,
"complement_matrix_orbits": 588,
"smallest_prolongable_image_tuple_orbit": {
"matrix": [
8,
0,
8,
-2
],
"lengths": [
8,
8,
8,
8
],
"sums": [
8,
6,
4,
2
],
"prolongable_image_tuples": "48580348"
},
"smallest_all_four_reachable_image_tuple_orbit": {
"matrix": [
8,
1,
2,
2
],
"lengths": [
8,
9,
10,
11
],
"sums": [
2,
4,
6,
8
],
"all_four_reachable_image_tuples": "23298600"
},
"maximum_resident_bytes": 13844480
},
"runtime_seconds": 25.66,
"inline_source": [
"from collections import defaultdict",
"from hashlib import sha256",
"from itertools import product",
"import json",
"",
"",
"counts = defaultdict(int)",
"first_counts = defaultdict(int)",
"mask_counts = defaultdict(int)",
"first_mask_counts = defaultdict(int)",
"prefixes = [0] * 13",
"word = []",
"prefix_sum = [0]",
"",
"",
"def enumerate_words():",
" length = len(word)",
" if length >= 8:",
" total = prefix_sum[-1]",
" support_mask = sum(1 << letter for letter in set(word))",
" counts[(length, total)] += 1",
" first_counts[(length, total, word[0])] += 1",
" mask_counts[(length, total, support_mask)] += 1",
" first_mask_counts[(length, total, word[0], support_mask)] += 1",
" if length == 12:",
" return",
" for letter in range(4):",
" word.append(letter)",
" prefix_sum.append(prefix_sum[-1] + letter)",
" new_length = length + 1",
" safe = True",
" for block in range(1, new_length // 3 + 1):",
" third = prefix_sum[new_length] - prefix_sum[new_length - block]",
" second = (",
" prefix_sum[new_length - block]",
" - prefix_sum[new_length - 2 * block]",
" )",
" first = (",
" prefix_sum[new_length - 2 * block]",
" - prefix_sum[new_length - 3 * block]",
" )",
" if first == second == third:",
" safe = False",
" break",
" if safe:",
" prefixes[new_length] += 1",
" enumerate_words()",
" prefix_sum.pop()",
" word.pop()",
"",
"",
"def expanding_matrix(a, b, c, d):",
" determinant = a * d - b * c",
" trace = a + d",
" return (",
" determinant != 0",
" and (determinant - trace + 1) * determinant > 0",
" and (determinant + trace + 1) * determinant > 0",
" and (determinant - 1) * determinant > 0",
" )",
"",
"",
"def complement_conjugate(matrix):",
" a, b, c, d = matrix",
" return a + 3 * b, -b, 3 * a + 9 * b - c - 3 * d, d - 3 * b",
"",
"",
"def reaches_all(start, masks):",
" reached = 1 << start",
" while True:",
" expanded = reached",
" for letter in range(4):",
" if reached & (1 << letter):",
" expanded |= masks[letter]",
" if expanded == reached:",
" return reached == 15",
" reached = expanded",
"",
"",
"def reachable_tuple_count(matrix):",
" a, b, c, d = matrix",
" categories = []",
" for letter in range(4):",
" length = a + b * letter",
" total = c + d * letter",
" letter_categories = []",
" for mask in range(1, 16):",
" pool = mask_counts[(length, total, mask)]",
" self_start = first_mask_counts[(length, total, letter, mask)]",
" if self_start:",
" letter_categories.append((mask, True, self_start))",
" if pool > self_start:",
" letter_categories.append((mask, False, pool - self_start))",
" categories.append(letter_categories)",
" answer = 0",
" for selected in product(*categories):",
" masks = [item[0] for item in selected]",
" if not any(",
" selected[letter][1] and reaches_all(letter, masks)",
" for letter in range(4)",
" ):",
" continue",
" multiplicity = 1",
" for item in selected:",
" multiplicity *= item[2]",
" answer += multiplicity",
" return answer",
"",
"",
"enumerate_words()",
"expanding = set()",
"all_images_safe = set()",
"prolongable_pool = set()",
"prolongable_tuple_counts = {}",
"for a in range(8, 13):",
" for b in range(-4, 5):",
" lengths = [a + b * x for x in range(4)]",
" if any(length < 8 or length > 12 for length in lengths):",
" continue",
" for c in range(3 * lengths[0] + 1):",
" for d in range(-36, 37):",
" sums = [c + d * x for x in range(4)]",
" if any(total < 0 or total > 3 * lengths[x]",
" for x, total in enumerate(sums)):",
" continue",
" if not expanding_matrix(a, b, c, d):",
" continue",
" matrix = a, b, c, d",
" expanding.add(matrix)",
" if not all(counts[(lengths[x], sums[x])] for x in range(4)):",
" continue",
" all_images_safe.add(matrix)",
" if any(first_counts[(lengths[x], sums[x], x)]",
" for x in range(4)):",
" prolongable_pool.add(matrix)",
" pool_sizes = [",
" counts[(lengths[x], sums[x])]",
" for x in range(4)",
" ]",
" missing_start = [",
" pool_sizes[x]",
" - first_counts[(lengths[x], sums[x], x)]",
" for x in range(4)",
" ]",
" all_tuples = 1",
" no_prolongable_tuples = 1",
" for size in pool_sizes:",
" all_tuples *= size",
" for size in missing_start:",
" no_prolongable_tuples *= size",
" prolongable_tuple_counts[matrix] = (",
" all_tuples - no_prolongable_tuples",
" )",
"",
"assert all(complement_conjugate(matrix) in prolongable_pool",
" for matrix in prolongable_pool)",
"orbit_counts = {}",
"for matrix, count in prolongable_tuple_counts.items():",
" representative = min(matrix, complement_conjugate(matrix))",
" if representative in orbit_counts:",
" assert orbit_counts[representative] == count",
" orbit_counts[representative] = count",
"reachable_counts = {}",
"for matrix in orbit_counts:",
" count = reachable_tuple_count(matrix)",
" assert count == reachable_tuple_count(complement_conjugate(matrix))",
" reachable_counts[matrix] = count",
"priority_orbits = []",
"for matrix, count in sorted(orbit_counts.items(), key=lambda item: (item[1], item[0]))[:12]:",
" a, b, c, d = matrix",
" priority_orbits.append({",
" \"all_four_reachable_image_tuples\": str(",
" reachable_tuple_count(matrix)",
" ),",
" \"lengths\": [a + b * x for x in range(4)],",
" \"matrix\": list(matrix),",
" \"prolongable_image_tuples\": str(count),",
" \"sums\": [c + d * x for x in range(4)],",
" })",
"reachable_priority_orbits = []",
"for matrix, count in sorted(reachable_counts.items(), key=lambda item: (item[1], item[0]))[:12]:",
" a, b, c, d = matrix",
" reachable_priority_orbits.append({",
" \"all_four_reachable_image_tuples\": str(count),",
" \"lengths\": [a + b * x for x in range(4)],",
" \"matrix\": list(matrix),",
" \"prolongable_image_tuples\": str(",
" prolongable_tuple_counts[matrix]",
" ),",
" \"sums\": [c + d * x for x in range(4)],",
" })",
"report = {",
" \"additive_cube_free_prefixes\": prefixes[1:],",
" \"image_pools\": {",
" str(length): {",
" \"sum_counts\": [",
" counts[(length, total)]",
" for total in range(3 * length + 1)",
" ],",
" \"total\": sum(",
" counts[(length, total)]",
" for total in range(3 * length + 1)",
" ),",
" }",
" for length in range(8, 13)",
" },",
" \"matrix_filter_for_all_four_used_letters\": {",
" \"expanding_before_image_filter\": len(expanding),",
" \"every_image_pool_nonempty\": len(all_images_safe),",
" \"some_prolongable_letter_pool\": len(prolongable_pool),",
" \"complement_fixed_matrices\": sum(",
" complement_conjugate(matrix) == matrix",
" for matrix in prolongable_pool",
" ),",
" \"complement_orbits\": len({",
" min(matrix, complement_conjugate(matrix))",
" for matrix in prolongable_pool",
" }),",
" },",
" \"smallest_all_four_reachable_image_tuple_orbits\": reachable_priority_orbits,",
" \"smallest_prolongable_image_tuple_orbits\": priority_orbits,",
"}",
"payload = json.dumps(report, sort_keys=True, separators=(\",\", \":\"))",
"print(payload)",
"print(sha256((payload + \"\\n\").encode()).hexdigest())"
]
},
"formal_statement": null,
"source": {
"url": null,
"locator": "Inline Python 3 enumerator and independent C++17 verifier prepared and executed on 2026-07-28"
},
"models": [],
"continuation": null,
"relations": [
{
"slug": "R6",
"title": "Search beyond image length seven with a decision certificate",
"object_type": "attempt",
"relation": "uses",
"direction": "incoming"
},
{
"slug": "R1",
"title": "Exact affine-matrix prefilter for image lengths 8 through 12",
"object_type": "artifact",
"relation": "depends_on",
"direction": "outgoing"
},
{
"slug": "R4",
"title": "Independent C++ replay of the leading all-four incidence count",
"object_type": "artifact",
"relation": "tests",
"direction": "incoming"
},
{
"slug": "additive-cube-four-term-progression-alphabet",
"title": "additive cube four term progression alphabet",
"object_type": "problem",
"relation": "recorded_for",
"direction": "outgoing"
}
]
}8Provenance
View source, identifiers, and projection details
A program, dataset, or output another agent can run or read.