Gain-Weighted Cluster Co-Design / results.json

Mechanism confirmed, baseline not beaten

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  1{
  2  "cluster_sweep": [
  3    {
  4      "c": 0.5,
  5      "cycle_product_predicted": 0.125,
  6      "greedy_boundary_cycle_gain": 0.0,
  7      "greedy_internal": true,
  8      "greedy_partition": [
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 21      "random_internal": false,
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 23      "singleton_boundary_cycle_gain": 0.125,
 24      "singleton_internal": false
 25    },
 26    {
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 29      "greedy_boundary_cycle_gain": 0.0,
 30      "greedy_internal": true,
 31      "greedy_partition": [
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 37        [
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 70      "singleton_internal": false
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 72    {
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 75      "greedy_boundary_cycle_gain": 0.0,
 76      "greedy_internal": true,
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 98      "greedy_boundary_cycle_gain": 0.0,
 99      "greedy_internal": true,
100      "greedy_partition": [
101        [
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103          1,
104          2
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106        [
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108          4,
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113      "random_internal": false,
114      "rho": 2.970539996088122,
115      "singleton_boundary_cycle_gain": 3.375,
116      "singleton_internal": false
117    }
118  ],
119  "imbalance_sweep": [
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122      "mu_optimized": 0.7000000000000018,
123      "mu_unscaled": 0.7,
124      "predicted_optimized": 0.7
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126    {
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130      "predicted_optimized": 0.7
131    },
132    {
133      "imbalance": 4.0,
134      "mu_optimized": 0.7000000041261014,
135      "mu_unscaled": 2.8,
136      "predicted_optimized": 0.7
137    },
138    {
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140      "mu_optimized": 0.7000000092680518,
141      "mu_unscaled": 5.6,
142      "predicted_optimized": 0.7
143    }
144  ],
145  "normalization_sweep": [
146    {
147      "c": 0.25,
148      "mu_optimized": 0.2500000014736077,
149      "mu_q0": 1.0,
150      "predicted_optimum": 0.25,
151      "q": [
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155      "rho": 0.25,
156      "stable_by_certificate": true
157    },
158    {
159      "c": 0.5,
160      "mu_optimized": 0.5000000029472154,
161      "mu_q0": 2.0,
162      "predicted_optimum": 0.5,
163      "q": [
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167      "rho": 0.5000000000000001,
168      "stable_by_certificate": true
169    },
170    {
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173      "mu_q0": 3.6,
174      "predicted_optimum": 0.9,
175      "q": [
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179      "rho": 0.9000000000000002,
180      "stable_by_certificate": true
181    },
182    {
183      "c": 1.0,
184      "mu_optimized": 1.0000000058944307,
185      "mu_q0": 4.0,
186      "predicted_optimum": 1.0,
187      "q": [
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191      "rho": 1.0,
192      "stable_by_certificate": false
193    },
194    {
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196      "mu_optimized": 1.1000000064838737,
197      "mu_q0": 4.4,
198      "predicted_optimum": 1.1,
199      "q": [
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203      "rho": 1.1,
204      "stable_by_certificate": false
205    },
206    {
207      "c": 1.5,
208      "mu_optimized": 1.5000000088416459,
209      "mu_q0": 6.0,
210      "predicted_optimum": 1.5,
211      "q": [
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213        -0.6931471835071606
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215      "rho": 1.5000000000000004,
216      "stable_by_certificate": false
217    },
218    {
219      "c": 2.0,
220      "mu_optimized": 2.0000000117888614,
221      "mu_q0": 8.0,
222      "predicted_optimum": 2.0,
223      "q": [
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227      "rho": 2.0000000000000004,
228      "stable_by_certificate": false
229    }
230  ],
231  "predictions": {
232    "boundary_confirmed": true,
233    "boundary_predicted_c": 1.0,
234    "cluster_transition_confirmed": true,
235    "imbalance_max_abs_error": 9.268051881505812e-09,
236    "mechanism_scope": "clustering removes the dominant channel from the boundary graph; it does not reduce full spectral radius",
237    "normalization_max_abs_error": 1.1788861442596499e-08
238  }
239}