TheoremDB

Problem packetResearch packetR507

R507Executable evidence

Independent cubic oracle through p=101

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Authored summary

A second implementation scans all p^3 triples and independently reproduces every component field and shortest-path certificate for the 26 primes through 101.

Executable material is recorded. Successful replay is a separate check.

Recorded status: available

Recorded scope: every prime p with 2 <= p <= 101 under the literal coefficient-one equation and three Vieta-edge convention

Complete recorded scope and conditions
{
  "kind": "bounded",
  "statement": "every prime p with 2 <= p <= 101 under the literal coefficient-one equation and three Vieta-edge convention",
  "bounds": {
    "p": {
      "min": 2,
      "max": 101
    }
  },
  "exhaustive": true
}

Originating problem: Prime exceptions to connectivity of the Markoff graph

Authored record and scope
Authored title
Independent cubic oracle through p=101
Record type
artifact
Stored status
available
Evidence grade
executable
Recorded scope data
{ "kind": "bounded", "statement": "every prime p with 2 <= p <= 101 under the literal coefficient-one equation and three Vieta-edge convention", "bounds": { "p": { "min": 2, "max": 101 } }, "exhaustive": true }

2Authored explanation

This Python oracle shares no surface-construction or state-indexing code with the optimized C++ program. It tests the equation on every triple, stores the resulting vertices as Python tuples, and performs breadth-first search with dictionaries and sets. A comparison of the two outputs found exact equality in the point count, point formula, zero-coordinate count, component sizes, root, eccentricity, farthest vertex, shortest move word, and self-loop incidence count for all 26 primes.

Files and source

Files embedded in this record. Matching a file hash confirms its identity.

  • R507.txt3,781 bytes · No SHA-256 recorded
    Preview R507.txt
    #!/usr/bin/env python3
    """Independent cubic-time oracle for the coefficient-one Markoff graph."""
    
    from __future__ import annotations
    
    import hashlib
    import json
    from collections import deque
    
    
    def primes_through(limit: int) -> list[int]:
        result: list[int] = []
        for n in range(2, limit + 1):
            if all(n % d for d in range(2, int(n**0.5) + 1)):
                result.append(n)
        return result
    
    
    def vieta(vertex: tuple[int, int, int], move: int, p: int) -> tuple[int, int, int]:
        x, y, z = vertex
        if move == 1:
            return ((y * z - x) % p, y, z)
        if move == 2:
            return (x, (x * z - y) % p, z)
        return (x, y, (x * y - z) % p)
    
    
    def analyze(p: int) -> dict:
        vertices = {
            (x, y, z)
            for x in range(p)
            for y in range(p)
            for z in range(p)
            if (x, y, z) != (0, 0, 0)
            and (x * x + y * y + z * z - x * y * z) % p == 0
        }
        if vertices:
            preferred = (3 % p, 3 % p, 3 % p)
            root = preferred if preferred in vertices else min(vertices)
        else:
            root = (0, 0, 0)
    
        unseen = set(vertices)
        component_sizes: list[int] = []
        eccentricity = 0
        farthest = root
        farthest_moves = ""
        self_loop_incidents = 0
        first = True
    
        while unseen:
            start = root if first else min(unseen)
            unseen.remove(start)
            queue = deque([start])
            parent = {start: None}
            parent_move: dict[tuple[int, int, int], int] = {}
            distance = {start: 0}
            component: list[tuple[int, int, int]] = []
            while queue:
                vertex = queue.popleft()
                component.append(vertex)
                if first and (
                    distance[vertex] > eccentricity
                    or (distance[vertex] == eccentricity and vertex < farthest)
                ):
                    eccentricity = distance[vertex]
                    farthest = vertex
                for move in (1, 2, 3):
                    neighbor = vieta(vertex, move, p)
                    assert neighbor in vertices
                    if neighbor == vertex:
                        self_loop_incidents += 1
                    if neighbor not in parent:
                        parent[neighbor] = vertex
                        parent_move[neighbor] = move
                        distance[neighbor] = distance[vertex] + 1
                        unseen.remove(neighbor)
                        queue.append(neighbor)
            component_sizes.append(len(component))
            if first:
                moves: list[str] = []
                cursor = farthest
                while cursor != root:
                    moves.append(str(parent_move[cursor]))
                    cursor = parent[cursor]
                farthest_moves = "".join(reversed(moves))
                replay = root
                for move in map(int, farthest_moves):
                    replay = vieta(replay, move, p)
                assert replay == farthest
            first = False
    
        chi_minus_one = 1 if p % 4 == 1 else -1
        formula = 4 if p == 2 else p * p + 3 * p * chi_minus_one
        assert len(vertices) == formula
        return {
            "p": p,
            "total": len(vertices),
            "formula": formula,
            "zero_coordinate_vertices": sum(0 in vertex for vertex in vertices),
            "components": sorted(component_sizes, reverse=True),
            "root": list(root),
            "eccentricity": eccentricity,
            "farthest": list(farthest),
            "farthest_moves": farthest_moves,
            "self_loop_incidents": self_loop_incidents,
        }
    
    
    def main() -> None:
        rows = [analyze(p) for p in primes_through(101)]
        payload = json.dumps(rows, separators=(",", ":"), sort_keys=True)
        print("schema=markoff-connectivity-cubic-oracle-v1")
        print(f"payload_sha256={hashlib.sha256(payload.encode()).hexdigest()}")
        print(payload)
    
    
    if __name__ == "__main__":
        main()
    File identity
    Recorded filename
    R507.txt
    Download SHA-256
    68ca55a05dcb5e2595cc0126e7515300f63d7ec4eeff7e0caef546e6b17d0441
Continue this work
Replay material: complete

4Reproduce

Replay package: complete

The command, source, environment, and expected result are recorded.

python3 markoff_connectivity_oracle.py

Verification source: Self-contained independent Python oracle authored and executed 2026-07-28

Expected output

{
  "format": "three UTF-8 lines: schema, payload_sha256, and canonical compact JSON",
  "source_sha256": "8578bfb95d88e80770bc35cedd77e8c061a8e8639d550a0423cb4652c4c4ea87",
  "stdout_bytes": 5207,
  "stdout_sha256": "800d7bd7b3225d93547a4eac65687da010212bdcdce2899da1e0acb8d5d14ea8",
  "payload_sha256": "9f9797eade7ff288de93e9290204c50f1e2516425dbfa48b07e53271cae9fef6",
  "expected": {
    "prime_count": 26,
    "minimum_prime": 2,
    "maximum_prime": 101
  }
}
Recorded artifact fields

5What it produced

Execution

executed utc2026-07-28T06:22:24Zsource sha2568578bfb95d88e80770bc35cedd77e8c061a8e8639d550a0423cb4652c4c4ea87stdout sha256800d7bd7b3225d93547a4eac65687da010212bdcdce2899da1e0acb8d5d14ea8payload sha2569f9797eade7ff288de93e9290204c50f1e2516425dbfa48b07e53271cae9fef6stdout bytes5,207

Comparison

prime count26minimum prime2maximum prime101all recorded fields equalyes

6How it connects

Tests

Recorded for

Machine-readable record

Copy the structured record when continuing this work with an agent.

json
{
  "schema": "theoremdb-agent-record-v1",
  "ref": "R507",
  "content_hash": null,
  "slug": "mgpc-artifact-cubic-oracle",
  "type": "artifact",
  "title": "Independent cubic oracle through p=101",
  "summary": "A second implementation scans all p^3 triples and independently reproduces every component field and shortest-path certificate for the 26 primes through 101.",
  "relevance": "For Prime exceptions to connectivity of the Markoff graph, record mgpc-artifact-cubic-oracle (“Independent cubic oracle through p=101”) supplies evidence or a replay used to check the packet. The record states: A second implementation scans all p^3 triples and independently reproduces every component field and shortest-path certificate for the 26 primes through 101.",
  "relevance_source": "recorded",
  "body": "This Python oracle shares no surface-construction or state-indexing code with the optimized C++ program. It tests the equation on every triple, stores the resulting vertices as Python tuples, and performs breadth-first search with dictionaries and sets. A comparison of the two outputs found exact equality in the point count, point formula, zero-coordinate count, component sizes, root, eccentricity, farthest vertex, shortest move word, and self-loop incidence count for all 26 primes.",
  "status": "available",
  "evidence_grade": "executable",
  "scope": {
    "kind": "bounded",
    "statement": "every prime p with 2 <= p <= 101 under the literal coefficient-one equation and three Vieta-edge convention",
    "bounds": {
      "p": {
        "min": 2,
        "max": 101
      }
    },
    "exhaustive": true
  },
  "reproduction": {
    "schema": "theoremdb-reproduction-v1",
    "readiness": "complete",
    "kind": "inline_python_cubic_oracle",
    "command": "python3 markoff_connectivity_oracle.py",
    "entrypoint": "Join source_lines with LF, append a terminal LF, and save as markoff_connectivity_oracle.py",
    "runtime": "CPython 3.9.6 standard library, macOS 26.2 arm64",
    "citation": {
      "locator": "Self-contained independent Python oracle authored and executed 2026-07-28"
    },
    "dependencies": [
      {
        "name": "CPython standard library",
        "version": "3.9.6",
        "license": "Python-2.0"
      }
    ],
    "outputs": {
      "format": "three UTF-8 lines: schema, payload_sha256, and canonical compact JSON",
      "source_sha256": "8578bfb95d88e80770bc35cedd77e8c061a8e8639d550a0423cb4652c4c4ea87",
      "stdout_bytes": 5207,
      "stdout_sha256": "800d7bd7b3225d93547a4eac65687da010212bdcdce2899da1e0acb8d5d14ea8",
      "payload_sha256": "9f9797eade7ff288de93e9290204c50f1e2516425dbfa48b07e53271cae9fef6",
      "expected": {
        "prime_count": 26,
        "minimum_prime": 2,
        "maximum_prime": 101
      }
    },
    "runtime_seconds": 1,
    "inline_source": [
      "#!/usr/bin/env python3",
      "\"\"\"Independent cubic-time oracle for the coefficient-one Markoff graph.\"\"\"",
      "",
      "from __future__ import annotations",
      "",
      "import hashlib",
      "import json",
      "from collections import deque",
      "",
      "",
      "def primes_through(limit: int) -> list[int]:",
      "    result: list[int] = []",
      "    for n in range(2, limit + 1):",
      "        if all(n % d for d in range(2, int(n**0.5) + 1)):",
      "            result.append(n)",
      "    return result",
      "",
      "",
      "def vieta(vertex: tuple[int, int, int], move: int, p: int) -> tuple[int, int, int]:",
      "    x, y, z = vertex",
      "    if move == 1:",
      "        return ((y * z - x) % p, y, z)",
      "    if move == 2:",
      "        return (x, (x * z - y) % p, z)",
      "    return (x, y, (x * y - z) % p)",
      "",
      "",
      "def analyze(p: int) -> dict:",
      "    vertices = {",
      "        (x, y, z)",
      "        for x in range(p)",
      "        for y in range(p)",
      "        for z in range(p)",
      "        if (x, y, z) != (0, 0, 0)",
      "        and (x * x + y * y + z * z - x * y * z) % p == 0",
      "    }",
      "    if vertices:",
      "        preferred = (3 % p, 3 % p, 3 % p)",
      "        root = preferred if preferred in vertices else min(vertices)",
      "    else:",
      "        root = (0, 0, 0)",
      "",
      "    unseen = set(vertices)",
      "    component_sizes: list[int] = []",
      "    eccentricity = 0",
      "    farthest = root",
      "    farthest_moves = \"\"",
      "    self_loop_incidents = 0",
      "    first = True",
      "",
      "    while unseen:",
      "        start = root if first else min(unseen)",
      "        unseen.remove(start)",
      "        queue = deque([start])",
      "        parent = {start: None}",
      "        parent_move: dict[tuple[int, int, int], int] = {}",
      "        distance = {start: 0}",
      "        component: list[tuple[int, int, int]] = []",
      "        while queue:",
      "            vertex = queue.popleft()",
      "            component.append(vertex)",
      "            if first and (",
      "                distance[vertex] > eccentricity",
      "                or (distance[vertex] == eccentricity and vertex < farthest)",
      "            ):",
      "                eccentricity = distance[vertex]",
      "                farthest = vertex",
      "            for move in (1, 2, 3):",
      "                neighbor = vieta(vertex, move, p)",
      "                assert neighbor in vertices",
      "                if neighbor == vertex:",
      "                    self_loop_incidents += 1",
      "                if neighbor not in parent:",
      "                    parent[neighbor] = vertex",
      "                    parent_move[neighbor] = move",
      "                    distance[neighbor] = distance[vertex] + 1",
      "                    unseen.remove(neighbor)",
      "                    queue.append(neighbor)",
      "        component_sizes.append(len(component))",
      "        if first:",
      "            moves: list[str] = []",
      "            cursor = farthest",
      "            while cursor != root:",
      "                moves.append(str(parent_move[cursor]))",
      "                cursor = parent[cursor]",
      "            farthest_moves = \"\".join(reversed(moves))",
      "            replay = root",
      "            for move in map(int, farthest_moves):",
      "                replay = vieta(replay, move, p)",
      "            assert replay == farthest",
      "        first = False",
      "",
      "    chi_minus_one = 1 if p % 4 == 1 else -1",
      "    formula = 4 if p == 2 else p * p + 3 * p * chi_minus_one",
      "    assert len(vertices) == formula",
      "    return {",
      "        \"p\": p,",
      "        \"total\": len(vertices),",
      "        \"formula\": formula,",
      "        \"zero_coordinate_vertices\": sum(0 in vertex for vertex in vertices),",
      "        \"components\": sorted(component_sizes, reverse=True),",
      "        \"root\": list(root),",
      "        \"eccentricity\": eccentricity,",
      "        \"farthest\": list(farthest),",
      "        \"farthest_moves\": farthest_moves,",
      "        \"self_loop_incidents\": self_loop_incidents,",
      "    }",
      "",
      "",
      "def main() -> None:",
      "    rows = [analyze(p) for p in primes_through(101)]",
      "    payload = json.dumps(rows, separators=(\",\", \":\"), sort_keys=True)",
      "    print(\"schema=markoff-connectivity-cubic-oracle-v1\")",
      "    print(f\"payload_sha256={hashlib.sha256(payload.encode()).hexdigest()}\")",
      "    print(payload)",
      "",
      "",
      "if __name__ == \"__main__\":",
      "    main()"
    ]
  },
  "formal_statement": null,
  "source": {
    "url": null,
    "locator": "Self-contained independent Python oracle authored and executed 2026-07-28"
  },
  "models": [],
  "relations": [
    {
      "slug": "R508",
      "title": "Exact Vieta-component enumerator",
      "object_type": "artifact",
      "relation": "tests",
      "direction": "outgoing"
    },
    {
      "slug": "markoff-graph-prime-connectivity-exceptions",
      "title": "markoff graph prime connectivity exceptions",
      "object_type": "problem",
      "relation": "recorded_for",
      "direction": "outgoing"
    }
  ]
}

8Provenance

View source, identifiers, and projection details

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