Optimize bridge-orbit engine (int-bitmask states, ~5x faster); measure feasibility

- fast_bridge.py: states as 210-bit integer edge-bitmasks (compact memory,
  O(1) set ops); build a NetworkX graph only once per state for the planar
  embedding; parity-subgraph bridges via one iterative DFS per state instead
  of per-edge subgraph copies. Validated identical orbits to the slow version;
  throughput ~5170 states/s vs ~1100 (graph.copy was 66% of old runtime).
- fast_decide.py: integrated, gated ELG-witness check (only even-class
  sources with all-opposite-class neighbourhoods are tested with the
  ground-truth is_even_level_graph, then parity match). Witness detection
  validated (ELGs -> True, T*_9 -> False).
- Feasibility finding: bridge orbits are ~100x smaller than full E/O orbits
  but still 1e5-1e6 states per labelling (partitions 0,1 of dual 0 exceed
  310k and 685k without exhausting), x ~150 valid parity partitions per dual.
  Exhausting every orbit -- required for a conclusive NEGATIVE -- is
  computationally infeasible. A conclusive POSITIVE (witness ELG) remains
  reachable; none found so far.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
2026-05-22 02:10:52 -04:00
parent 79bfd8e588
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"""Fast bridge-orbit machinery.
States are integer bitmasks over the 210 possible edges of a 21-vertex
graph (edge (i,j), i<j -> a fixed bit). This makes the `seen` set and
frontier compact and the set-difference/union O(1) int ops, eliminating
all NetworkX graph copies. A NetworkX graph is built only once per state
(needed for the planar embedding); parity-subgraph bridges are found with
one iterative DFS per state instead of per-edge subgraph copies.
"""
import sys
import os
sys.path.insert(0, '/Users/didericis/Code/math-research/papers/'
'level_resolutions_of_maximal_planar_graphs/experiments')
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
import networkx as nx
class EdgeCode:
"""Bijection edge <-> bit index for a fixed vertex set."""
def __init__(self, nodes):
self.nodes = sorted(nodes)
self.idx = {}
self.edges = []
b = 0
n = len(self.nodes)
for a in range(n):
for c in range(a + 1, n):
e = (self.nodes[a], self.nodes[c])
self.idx[e] = b
self.edges.append(e)
b += 1
self.nbits = b
def bit(self, u, v):
return self.idx[(u, v)] if u < v else self.idx[(v, u)]
def state_of(self, G):
s = 0
for u, v in G.edges():
s |= 1 << self.bit(u, v)
return s
def edges_of(self, state):
out = []
s = state
while s:
b = (s & -s).bit_length() - 1
out.append(self.edges[b])
s &= s - 1
return out
def graph_of(self, state):
G = nx.Graph()
G.add_nodes_from(self.nodes)
G.add_edges_from(self.edges_of(state))
return G
def parity_bridges(adj_by_node):
"""adj_by_node: dict node -> set(neighbors) for ONE parity subgraph.
Return set of frozenset({u,v}) bridges (edges on no cycle). Iterative
DFS lowlink."""
bridges = set()
visited = set()
disc = {}
low = {}
timer = [0]
for root in adj_by_node:
if root in visited:
continue
# iterative DFS
stack = [(root, None, iter(adj_by_node[root]))]
visited.add(root)
disc[root] = low[root] = timer[0]
timer[0] += 1
while stack:
node, parent, it = stack[-1]
advanced = False
for nb in it:
if nb == parent:
continue
if nb not in visited:
visited.add(nb)
disc[nb] = low[nb] = timer[0]
timer[0] += 1
stack.append((nb, node, iter(adj_by_node[nb])))
advanced = True
break
else:
low[node] = min(low[node], disc[nb])
if not advanced:
stack.pop()
if stack:
pnode = stack[-1][0]
low[pnode] = min(low[pnode], low[node])
if low[node] > disc[pnode]:
bridges.add(frozenset((pnode, node)))
return bridges
def backward_bridge_states(state, code, labels):
"""Yield neighbor STATES (ints) s' with s' -> state a bridge switch."""
G = code.graph_of(state)
ok, emb = nx.check_planarity(G)
if not ok:
return
# parity adjacency for the two parity classes
even_adj = {v: set() for v in code.nodes if labels[v] == 0}
odd_adj = {v: set() for v in code.nodes if labels[v] == 1}
for u, v in G.edges():
pu, pv = labels[u], labels[v]
if pu == 0 and pv == 0:
even_adj[u].add(v); even_adj[v].add(u)
elif pu == 1 and pv == 1:
odd_adj[u].add(v); odd_adj[v].add(u)
bridges = parity_bridges(even_adj) | parity_bridges(odd_adj)
for u, v in G.edges():
f1 = emb.traverse_face(u, v)
if len(f1) != 3:
continue
f2 = emb.traverse_face(v, u)
if len(f2) != 3:
continue
w = f1[0] if f1[0] != u and f1[0] != v else (f1[1] if f1[1] != u and f1[1] != v else f1[2])
x = f2[0] if f2[0] != u and f2[0] != v else (f2[1] if f2[1] != u and f2[1] != v else f2[2])
if w == x or G.has_edge(w, x):
continue
if labels[w] != labels[x]:
continue # wx must be same-parity (flippable in predecessor)
# uv is the NEW edge of switch s'->state; if same-parity it must be
# a bridge of state's parity subgraph:
if labels[u] == labels[v] and frozenset((u, v)) not in bridges:
continue
ns = state & ~(1 << code.bit(u, v))
ns |= 1 << code.bit(w, x)
yield ns
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"""Fast exhaustive bridge-derivability decision for a dual.
For each valid parity partition L, exhaust the backward bridge-orbit
(integer states) and look for an ELG witness with BFS-parity L. The ELG
check is gated by a cheap filter: an ELG source s lies in one parity
class and ALL its neighbours lie in the other (they are level 1), so only
such candidate sources are fully tested.
YES (bridge-derived) as soon as any partition yields a witness; NO
(conclusive) if all partitions' orbits are fully exhausted with no
witness; INCONCLUSIVE if any orbit hits the cap.
"""
import sys
import os
import time
sys.path.insert(0, '/Users/didericis/Code/math-research/papers/'
'level_resolutions_of_maximal_planar_graphs/experiments')
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
import networkx as nx
from collections import deque
from load_holton_mckay import parse_planar_code
from tutte_dual_treecolor import dual_triangulation
from exhaustive_bridge import valid_parity_partitions
from fast_bridge import EdgeCode, parity_bridges
from test_conjecture import is_even_level_graph
def _bfs_parity(adj, s, n):
"""BFS distance parity from s over adjacency dict; returns dict v->parity
or None if graph (restricted to reached) doesn't cover all n nodes."""
par = {s: 0}
dq = deque([s])
while dq:
u = dq.popleft()
for w in adj[u]:
if w not in par:
par[w] = par[u] ^ 1
dq.append(w)
if len(par) != n:
return None
return par
def expand_and_check(state, code, labels, n):
"""Build G once; return (is_witness, list_of_neighbor_states)."""
G = code.graph_of(state)
adj = {v: set(G.neighbors(v)) for v in code.nodes}
# --- ELG witness check (gated) ---
# Necessary condition for BFS-parity(s)==L: s's whole neighbourhood is
# the opposite class (level 1). Only such s are fully tested with the
# ground-truth ELG check (all level subgraphs bipartite) + parity match.
witness = False
for s in code.nodes:
cs = labels[s]
nbrs = adj[s]
if not nbrs or any(labels[w] == cs for w in nbrs):
continue
ok, lvls = is_even_level_graph(G, frozenset({s}))
if not ok:
continue
if all((lvls[v] % 2 == 0) == (labels[v] == cs) for v in code.nodes):
witness = True
break
# --- neighbours (backward bridge switches) ---
neigh = []
ok, emb = nx.check_planarity(G)
if ok:
even_adj = {v: set() for v in code.nodes if labels[v] == 0}
odd_adj = {v: set() for v in code.nodes if labels[v] == 1}
for u in code.nodes:
for v in adj[u]:
if u < v and labels[u] == labels[v]:
if labels[u] == 0:
even_adj[u].add(v); even_adj[v].add(u)
else:
odd_adj[u].add(v); odd_adj[v].add(u)
bridges = parity_bridges(even_adj) | parity_bridges(odd_adj)
for u, v in G.edges():
f1 = emb.traverse_face(u, v)
if len(f1) != 3:
continue
f2 = emb.traverse_face(v, u)
if len(f2) != 3:
continue
w = next(a for a in f1 if a != u and a != v)
x = next(b for b in f2 if b != u and b != v)
if w == x or G.has_edge(w, x):
continue
if labels[w] != labels[x]:
continue
if labels[u] == labels[v] and frozenset((u, v)) not in bridges:
continue
ns = (state & ~(1 << code.bit(u, v))) | (1 << code.bit(w, x))
neigh.append(ns)
return witness, neigh
def decide_partition(code, labels, n, cap):
s0 = code.state0
seen = {s0}
frontier = [s0]
while frontier and len(seen) < cap:
new = []
for st in frontier:
wit, neigh = expand_and_check(st, code, labels, n)
if wit:
return 'found', len(seen)
for ns in neigh:
if ns not in seen:
seen.add(ns)
new.append(ns)
frontier = new
return ('exhausted' if not frontier else 'capped'), len(seen)
def decide_dual(i, cap=4_000_000, log=print):
graphs = parse_planar_code('experiments/nonham38m4.pc')
G, _ = dual_triangulation(graphs[i][0])
n = G.number_of_nodes()
code = EdgeCode(G.nodes())
code.state0 = code.state_of(G)
parts = list(valid_parity_partitions(G))
log(f'dual {i}: {len(parts)} partitions, n={n}', flush=True)
t0 = time.time()
any_capped = False
max_orbit = 0
for j, labels in enumerate(parts):
st, sz = decide_partition(code, labels, n, cap)
if st == 'found':
log(f' partition {j}: WITNESS -> dual {i} IS bridge-derived '
f'(orbit>={sz}, {time.time()-t0:.0f}s)', flush=True)
return 'bridge-derived'
if st == 'capped':
any_capped = True
log(f' partition {j}: CAP {sz} (inconclusive)', flush=True)
else:
max_orbit = max(max_orbit, sz)
if (j + 1) % 10 == 0:
log(f' ...{j+1}/{len(parts)} done, max_orbit={max_orbit}, '
f'{time.time()-t0:.0f}s', flush=True)
verdict = 'INCONCLUSIVE (cap hit)' if any_capped else 'NOT bridge-derived'
log(f' dual {i}: {verdict} (max_orbit={max_orbit}, {time.time()-t0:.0f}s)',
flush=True)
return verdict
if __name__ == '__main__':
for idx in sys.argv[1:]:
decide_dual(int(idx))
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"""Measure the per-partition bridge-orbit size distribution for a dual,
with a modest cap, logging each partition's orbit size and time. Tells us
whether the slowness is a few giant orbits or uniformly heavy."""
import sys
import os
sys.path.insert(0, '/Users/didericis/Code/math-research/papers/'
'level_resolutions_of_maximal_planar_graphs/experiments')
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
import time
from load_holton_mckay import parse_planar_code
from tutte_dual_treecolor import dual_triangulation
from bridge_derived_test import sig, backward_bridge_neighbors
from exhaustive_bridge import valid_parity_partitions
def orbit_size(G, labels, cap, time_cap):
t0 = time.time()
seen = {sig(G)}
frontier = [G]
while frontier and len(seen) < cap:
if time.time() - t0 > time_cap:
return len(seen), time.time() - t0, 'timecap'
new = []
for H in frontier:
for Hp in backward_bridge_neighbors(H, labels):
s = sig(Hp)
if s not in seen:
seen.add(s)
new.append(Hp)
frontier = new
return len(seen), time.time() - t0, ('exhausted' if not frontier else 'cap')
def main(i, cap=400000, time_cap=30):
graphs = parse_planar_code('experiments/nonham38m4.pc')
G, _ = dual_triangulation(graphs[i][0])
parts = list(valid_parity_partitions(G))
print(f'dual {i}: {len(parts)} partitions; cap={cap} time_cap={time_cap}s',
flush=True)
sizes = []
for j, labels in enumerate(parts):
n, dt, st = orbit_size(G, labels, cap, time_cap)
sizes.append((n, st))
print(f' [{j}] orbit={n} {st} {dt:.1f}s', flush=True)
exhausted = [n for n, st in sizes if st == 'exhausted']
unfinished = [(n, st) for n, st in sizes if st != 'exhausted']
print(f'\nexhausted: {len(exhausted)}/{len(parts)}; '
f'largest exhausted={max(exhausted) if exhausted else 0}; '
f'unfinished={len(unfinished)}', flush=True)
if __name__ == '__main__':
main(int(sys.argv[1]) if len(sys.argv) > 1 else 0)
@@ -0,0 +1,72 @@
"""Diagnostic: per-partition bridge-orbit size distribution for a dual,
logging EVERY partition. Separates BFS time from witness-check time, and
records whether each orbit exhausted below the cap. Also reports if any
witness is found (early YES)."""
import sys
import os
import time
sys.path.insert(0, '/Users/didericis/Code/math-research/papers/'
'level_resolutions_of_maximal_planar_graphs/experiments')
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from load_holton_mckay import parse_planar_code
from tutte_dual_treecolor import dual_triangulation
from exhaustive_bridge import valid_parity_partitions
from fast_bridge import EdgeCode
from fast_decide import expand_and_check
def run(i, cap, time_cap):
graphs = parse_planar_code('experiments/nonham38m4.pc')
G, _ = dual_triangulation(graphs[i][0])
n = G.number_of_nodes()
code = EdgeCode(G.nodes())
code.state0 = code.state_of(G)
parts = list(valid_parity_partitions(G))
print(f'dual {i}: {len(parts)} partitions, cap={cap}, time_cap={time_cap}s',
flush=True)
sizes = []
for j, labels in enumerate(parts):
t0 = time.time()
seen = {code.state0}
frontier = [code.state0]
wit = False
capped = False
while frontier and len(seen) < cap:
if time.time() - t0 > time_cap:
capped = True
break
new = []
for st in frontier:
w, neigh = expand_and_check(st, code, labels, n)
if w:
wit = True
break
for ns in neigh:
if ns not in seen:
seen.add(ns)
new.append(ns)
if wit:
break
frontier = new
if len(seen) >= cap:
capped = True
st_tag = 'WITNESS' if wit else ('cap' if capped else 'exhausted')
sizes.append((len(seen), st_tag))
print(f' [{j}] {st_tag} orbit={len(seen)} {time.time()-t0:.1f}s',
flush=True)
if wit:
print(f'dual {i}: BRIDGE-DERIVED (witness at partition {j})',
flush=True)
return
exh = [s for s, t in sizes if t == 'exhausted']
capped_ct = sum(1 for s, t in sizes if t == 'cap')
print(f'\ndual {i}: no witness. exhausted={len(exh)}/{len(parts)}, '
f'capped={capped_ct}, largest_exhausted={max(exh) if exh else 0}',
flush=True)
if __name__ == '__main__':
i = int(sys.argv[1]) if len(sys.argv) > 1 else 0
cap = int(sys.argv[2]) if len(sys.argv) > 2 else 500000
tcap = int(sys.argv[3]) if len(sys.argv) > 3 else 60
run(i, cap, tcap)