passages: memoized exact MC midpoints + wider conservative sweep bounds (L101, exact vs L100)

Off-grid census by caller (MC midpoints, skirts, far shells); all 63.0M sweep misses accounted
(1.9M exact-route fallbacks, 61.1M counted bound skips). Exact MC midpoint queries memoized by
float bits (Unreal enables it too); feature bounds expanded. L100/L101 whole-view hashes equal in
all four strata (v216 unchanged); 0 added/removed crossings; 15 capture pairs pixel-identical.
Near-ready @W12 L100 -> L101: FI 1.77 -> 1.65, TN 1.66 -> 1.54, SW 0.85 -> 0.84, VS 1.03 -> 1.03 s
(L98 2.28/2.23/1.02/1.11). Fast tier PASS; Linux UE host builds. Unreal arrival traces not obtained
(the runner wrongly applied the 6 GiB address-space cap to Unreal).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016dhxM43dnWvUu2B5Ph1iG1

Standalone/Research/WorldAssemblerM3/Linux101/RunL101Readiness.py

@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+"""L80 protocol with balanced, rotating L98/L99/L100/L101 order."""
+from __future__ import annotations
+
+import json
+import re
+import statistics
+import subprocess
+import time
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[4]
+OUT = ROOT / "Saved/Linux/l101/readiness/l98-l99-l100-l101-exact-bounds"
+DATA = ROOT / "Standalone/data/owner_world.json"
+BINARIES = {
+    "L98": ROOT / "Saved/Linux/l98/bin/VoxelForgeCoreHeadless-l98-clang19",
+    "L99": ROOT / "Saved/Linux/l99/bin/VoxelForgeCoreHeadless-l99-clang",
+    "L100": ROOT / "Saved/Linux/l100/bin/VoxelForgeCoreHeadless-l100-clang",
+    "L101": ROOT / "Saved/Linux/l101/bin/VoxelForgeCoreHeadless-l101-clang",
+}
+CAMERAS = {
+    "SW": (8.0, 16.0, -372.2626953125),
+    "FI": (25.8369140625, 3.19921875, -737.0),
+    "TN": (19.166015625, -14.2001953125, -753.3740234375),
+    "VS": (-20.0625, -5.068359375, -900.353515625),
+}
+PIPELINE = re.compile(r"^\[StreamPipeline\] (.*)$", re.M)
+FIELDS = re.compile(r"([a-zA-Z0-9_]+)=([^ ]+)")
+NEAR = re.compile(r"^\[WorldAssemblerNearLODReady\] lods=0-2 tiles=(\d+)/(\d+) "
+                  r"cold_ready_s=([0-9.]+)$", re.M)
+STAMP = re.compile(r"^\[VoxelForgeSourceStamp\] sha256=([0-9a-f]{64})$", re.M)
+
+
+def run(strate: str, workers: int, label: str, phase: str, rep: int) -> dict:
+    OUT.mkdir(parents=True, exist_ok=True)
+    log = OUT / f"w{workers}-{strate.lower()}-{label.lower()}-{phase}{rep}.log"
+    camera = ",".join(f"{value:.12f}" for value in CAMERAS[strate]) + ",0,0"
+    command = [
+        "taskset", "-c", "0-11", "prlimit", "--as=6442450944", "--",
+        "env", "timeout", "1740s", str(BINARIES[label]), str(DATA),
+        "--world-assembler-prototype", "--stream-benchmark", "--stream-pipeline",
+        f"--workers={workers}", "--clip-radius=3", "--max-clip-level=8",
+        "--max-level=8", f"--camera={camera}", "--profile-lod-work",
+        "--stream-scheduler-policy=3",
+    ]
+    start = time.monotonic()
+    with log.open("w", encoding="utf-8") as stream:
+        result = subprocess.run(command, cwd=ROOT, stdout=stream,
+                                stderr=subprocess.STDOUT, check=False, timeout=1740)
+    output = log.read_text(encoding="utf-8", errors="replace")
+    pipeline_match, near_match, stamp_match = (
+        PIPELINE.search(output), NEAR.search(output), STAMP.search(output))
+    if result.returncode or pipeline_match is None or near_match is None or stamp_match is None:
+        raise RuntimeError(f"readiness run failed: exit={result.returncode} {log}")
+    pipeline = dict(FIELDS.findall(pipeline_match.group(1)))
+    row = {
+        "strate": strate, "workers": workers, "binary": label, "phase": phase,
+        "replicate": rep, "exit_code": result.returncode,
+        "source_stamp": stamp_match.group(1), "wall_s": round(time.monotonic() - start, 3),
+        "lod02_tiles": f"{near_match.group(1)}/{near_match.group(2)}",
+        "lod02_ready_s": float(near_match.group(3)),
+        "whole_view_ready_s": float(pipeline["whole_view_ready"].removesuffix("s")),
+        "whole_tiles": pipeline["whole_tiles"].split("/")[0],
+        "log": str(log.relative_to(ROOT)),
+    }
+    print("[L101ReadinessRun] " + json.dumps(row, sort_keys=True), flush=True)
+    return row
+
+
+def main() -> int:
+    for binary in (*BINARIES.values(), DATA):
+        if not binary.is_file():
+            raise SystemExit(f"missing input: {binary}")
+    rows = []
+    labels = tuple(BINARIES)
+    orders = tuple(labels[index:] + labels[:index] for index in range(len(labels)))
+    for workers in (8, 12):
+        for strate in CAMERAS:
+            for label in labels:
+                run(strate, workers, label, "warmup", 0)
+        for strate in CAMERAS:
+            for rep, order in enumerate(orders, 1):
+                for label in order:
+                    rows.append(run(strate, workers, label, "measured", rep))
+                    (OUT / "runs-partial.json").write_text(json.dumps(rows, indent=2) + "\n",
+                                                           encoding="utf-8")
+    summary = []
+    for workers in (8, 12):
+        for strate in CAMERAS:
+            group = [row for row in rows if row["workers"] == workers
+                     and row["strate"] == strate]
+            item = {"workers": workers, "strate": strate, "measured_runs": 3}
+            for label in labels:
+                subset = [row for row in group if row["binary"] == label]
+                for metric in ("lod02_ready_s", "whole_view_ready_s"):
+                    values = [row[metric] for row in subset]
+                    item[f"{label}_{metric}_runs"] = values
+                    item[f"{label}_{metric}_median"] = statistics.median(values)
+                item[f"{label}_process_wall_s_runs"] = [row["wall_s"] for row in subset]
+            summary.append(item)
+    (OUT / "summary.json").write_text(json.dumps(
+        {"comparison_triple": labels, "runs": rows, "summary": summary}, indent=2) + "\n",
+        encoding="utf-8")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())