Benchmarks

Comprehensive performance results across all ShunyaBar Labs algorithms.

Summary Table#

Algorithm	Domain	Success Rate	Speedup	Key Metric
BAHA	Optimization	84% (26 domains)	4169% vs SA	Spin Glass
NitroSAT	MaxSAT	77% perfect SAT	—	788K vars
Navokoj	3-SAT	99.4%	—	Critical density
Multiplicative PINN	Navier-Stokes	99.64% residual red.	100,000x vs CFD	Monotonicity
Spectral-Multiplicative	Graph partitioning	100%	$1.4M savings	15K nodes
Geometry of Conditional Logic	Incremental repair	100%	847x-12,495x	Sudoku

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BAHA Benchmarks#

Spin Glass (64 spins)#

Solver	Success Rate	Time
Simulated Annealing	6%	—
BAHA	100%	—
Improvement	4169%	—

Graph Isomorphism (N=50)#

Solver	Success Rate
Standard SA	40%
BAHA	100%

26 Problem Domains#

Domain	BAHA Pass	BAHA Mean Score
Random K-SAT	✓	0.91
Graph Coloring	✓	0.89
MaxCut	✓	0.94
Spin Glass	✓	1.00
Graph Isomorphism	✓	1.00
Portfolio (avg)	84%	0.87

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NitroSAT Benchmarks#

Large-Scale Verification#

Instance	Variables	Clauses	Result	Time
Planted Coloring	105,000	232,000	SAT	13.78s
Hardware Check	788,480	—	SAT	5.92s
Random CNF	5,000+ instances	Various	77% perfect	—

Median Satisfaction#

Across 5,000+ random CNF instances:

• Perfect satisfaction: 77%
• Median satisfaction: 99.7%

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Navokoj Benchmarks#

3-SAT at Critical Density (α = 4.27)#

Variables	Clauses	Success Rate
20	~85	100%
50	~215	99.4%
100	~427	98.1%

Graph Coloring#

Nodes	Colors	Success Rate
20	3	100%
50	4	100%

AI Escargot Sudoku#

• Variables: 729
• Clauses: 8,850
• Success Rate: 99.85%

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Multiplicative PINN Benchmarks#

Navier-Stokes Equations#

Metric	Standard (Additive)	Multiplicative PINN
Residual reduction	baseline	99.64%
Monotonicity violations	31.31%	0%
Training time	24 hours (CFD)	0.86 seconds
Speedup	1x	100,000x

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Spectral-Multiplicative Benchmarks#

Cloud Infrastructure Optimization#

Metric	Before	After
Partition balance	60/40	50/50
Constraint violations	Many	0
Cross-region traffic	High	Minimized
Annual cost	baseline	$1.4M savings

15,000-Node Graph#

Metric	Value
Constraint satisfaction	100%
Spectral-Multiplicative correlation	0.996
Runtime	< 1 minute

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Geometry of Conditional Logic#

Sudoku Repair#

Perturbation	Full Restart	CRT Incremental	Speedup
1 cell	baseline	847x	847x
3 cells	baseline	9,234x	9,234x
5 cells	baseline	12,495x	12,495x

Solution Preservation#

k (perturbations)	Preservation Rate
k ≤ 2	100%
k ≤ 5	100%
k > 5	Degrades

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Prime Weighting Ablation#

Weight Scheme	Speedup vs Uniform	Topological Complexity
Uniform	1x (baseline)	High
Random	2x	Medium
Prime	4x	75% reduction

Prime weighting is causal, not decorative — the 4x speedup and 75% complexity reduction are reproduced consistently.

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See Also#

• All Projects — per-project benchmark deep dives
• Prime Weighting — ablation study details
• Limitations — where performance degrades
• Marketing: Results — production benchmark data
• Competition — comparison with other solvers
• Research Report — empirical evaluation methodology