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HiGHS Optimization: - qubo_highs.py: QUBO→MIP reformulation via highspy (exact, not approximate) - solve_route_lp: TSP/VRP assignment relaxation for RouteCost 39-node graph - scale_space_solver.py: multi-scale optimization (coarse LP → fine MIP) - Gaussian kernels in Q16_16, voltage↔scale mapping - alphaproof_loop.py: Ollama → lake build → feedback proof search Lean Formalization: - AdjugateMatrix.lean: division-free matrix inversion (291 lines, 3300 jobs, 0 errors) - det2/det4/det8 via cofactor expansion, all Q16_16 - adjugate, matrixInverse, cayleyTransform - 7 #eval witnesses all pass FPGA (Tang Nano 9K): - voltage_mode_controller.v: 4-mode BRAM (STORE/COMPUTE/APPROX/MORPHIC) - scale_space_bram.v: 4 Gaussian kernel banks (σ=0.25/0.50/0.75/1.00) - highs_pivot_accelerator.v: 3-stage pipeline, Q16_16 division, 64-element columns - blitter_memory_map.v: 8-bit CPU ↔ 32-bit Q16 bridge, full I/O map at $8000
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10 lines
194 B
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# Braid VCN Encoder Pipeline dependencies
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reedsolo>=1.7.0
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cryptography>=41.0.0
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numpy>=1.24.0
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# QUBO-to-MIP bridge (HiGHS solver)
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highspy>=1.7.0
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# AlphaProof loop (Ollama API)
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requests>=2.31.0
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