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T=SQL Engine — Temporal-to-Structured Query Language
Maps Vacuum Fluctuation timestamps -> Worm Chain indices.
Authors: Ahmad Ali Parr, Jessica L. Williams (SNAPKITTYWEST)
Evidence boundary
-----------------
"Worm Chain" is a data structure (dictionary).
T=SQL is a human-designed software/hardware wrapper around SHA-256 hashing.
Vacuum fluctuations are used as entropy seeds, NOT as an energy source.
Collisions are mathematically inevitable (Pigeonhole; 64->32 bit).
The P4 settler resolves them via monotone sequence counter.
"""
import hashlib
import struct
from dataclasses import dataclass
from typing import Dict, List, Optional, Tuple
# ── Types ──────────────────────────────────────────────────────────────────
@dataclass
class WormEvent:
t_coord: int # Raw vacuum-derived timestamp (64-bit)
sql_idx: int # T=SQL hashed index (32-bit)
entropy_seed: bytes # Normalized 256-bit seed from ANu
p3q_state: str # Quantum circuit state snapshot label
settlement_id: int # P4 settlement sequence number (monotone)
# ── T=SQL Engine ───────────────────────────────────────────────────────────
class TSQLEngine:
"""
T=SQL Engine: maps temporal vacuum fluctuation coordinates to
structured Worm Chain indices, supporting SQL-like queries.
Formal properties (see lean/TSQLFormal.lean):
- Deterministic: same t_coord always yields same sql_idx
- Collision-inevitable: Pigeonhole, |UInt64| > |UInt32|
- Ordered: collision resolution via monotone settlement_id
"""
def __init__(self):
# The "Worm Chain": non-linear event store keyed by sql_idx
self.worm_chain: Dict[int, WormEvent] = {}
self.settlement_seq: int = 0
self.salt = b"DEADBEEF_VACUUM_SALT"
# ── Core hash ──────────────────────────────────────────────────────────
def _compute_t_sql_index(self, t_coord: int) -> int:
"""
T=SQL Mapping: T -> SQL
Deterministic SHA-256 hash of the temporal coordinate.
Returns first 4 bytes as the 32-bit SQL index.
"""
t_bytes = struct.pack(">Q", t_coord & 0xFFFFFFFFFFFFFFFF)
digest = hashlib.sha256(t_bytes + self.salt).digest()
return struct.unpack(">I", digest[:4])[0]
# ── Write path ─────────────────────────────────────────────────────────
def ingest_event(
self,
t_coord: int,
seed: bytes,
state: str,
settlement: Optional[int] = None,
) -> WormEvent:
"""
Write a vacuum fluctuation event into the Worm Chain.
settlement_id is automatically assigned if not provided.
"""
self.settlement_seq += 1
sid = settlement if settlement is not None else self.settlement_seq
idx = self._compute_t_sql_index(t_coord)
event = WormEvent(t_coord, idx, seed, state, sid)
self.worm_chain[idx] = event
print(f"[T=SQL] Ingested T={t_coord:#018x} -> SQL_IDX={idx:#010x} SID={sid}")
return event
# ── Query: by timestamp ────────────────────────────────────────────────
def query_by_time(self, t_coord: int) -> Optional[WormEvent]:
"""
T=SQL SELECT: retrieve state by temporal coordinate.
SELECT * FROM WormChain WHERE t_coord = t;
"""
idx = self._compute_t_sql_index(t_coord)
return self.worm_chain.get(idx)
# ── Query: by sql_idx range ────────────────────────────────────────────
def query_manifold(self, lo: int, hi: int) -> List[WormEvent]:
"""
T=SQL RANGE: retrieve events within an index manifold.
SELECT * FROM WormChain WHERE sql_idx BETWEEN lo AND hi;
"""
return [
e for idx, e in self.worm_chain.items()
if lo <= idx <= hi
]
# ── Query: all events ordered by settlement ────────────────────────────
def query_ordered(self) -> List[WormEvent]:
"""
Return all events sorted by monotone settlement_id.
Equivallent to: SELECT * FROM WormChain ORDER BY settlement_id;
"""
return sorted(self.worm_chain.values(), key=lambda e: e.settlement_id)
# ── Diagnostics ────────────────────────────────────────────────────────
def stats(self) -> dict:
return {
"events": len(self.worm_chain),
"settlement_seq": self.settlement_seq,
"collision_probability": 1.0 / (2**32),
}
# ── Self-test ──────────────────────────────────────────────────────────────
if __name__ == "__main__":
engine = TSQLEngine()
# Simulated vacuum events: (timestamp, seed, state, settlement_id)
events = [
(1692834001, b"\xaa" * 32, "S_0", 1001),
(1692834005, b"\xbb" * 32, "S_1", 1002),
(1692834010, b"\xcc" * 32, "S_2", 1003),
]
for t, seed, state, sid in events:
engine.ingest_event(t, seed, state, sid)
print()
# Query by time
target = 1692834005
result = engine.query_by_time(target)
if result:
print(f"[T=SQL Query] T={target} -> state={result.p3q_state} idx={result.sql_idx:#010x}")
# Ordered query
print("\n[T=SQL Ordered]")
for e in engine.query_ordered():
print(f" SID={e.settlement_id} T={e.t_coord} state={e.p3q_state}")
# Stats
print("\n[T=SQL Stats]", engine.stats())
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