feat(gui): three research tabs (energy landscape, quantum convergence… - #9
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…, hardness) Replace the dead "live CP-SAT convergence" tab (CP-SAT one-shots these instances in ~20ms / 1 incumbent, so there was nothing to animate) with three research-grade panels, backed by a tested pure-function analysis layer (contrail_env/analysis.py): - Energy landscape: histogram of every feasible solution's cost with the optimum marked, overlaid with the costs GBS and uniform-random samplers actually achieve -- does the quantum sampler concentrate near the optimum? - Quantum convergence: best-cost-so-far vs work for Pasqal QAOA and Xanadu GBS on the current instance, against the CP-SAT optimum -- a curve that actually moves (these iterate). - Hardness sweep: CP-SAT wall time + incumbents vs problem size -- shows the instances are trivially easy for the exact solver (incumbents stays flat). analysis.py is unit-tested (landscape optimum matches CP-SAT; repaired samples never beat the optimum; sweep shapes/effort). GUI plotting slots smoke-tested headless. Tabs renumber to 8; the SolveWorker progress curve is gone.
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…, hardness)
Replace the dead "live CP-SAT convergence" tab (CP-SAT one-shots these instances in ~20ms / 1 incumbent, so there was nothing to animate) with three research-grade panels, backed by a tested pure-function analysis layer (contrail_env/analysis.py):
analysis.py is unit-tested (landscape optimum matches CP-SAT; repaired samples never beat the optimum; sweep shapes/effort). GUI plotting slots smoke-tested headless. Tabs renumber to 8; the SolveWorker progress curve is gone.