Energy-Gradient Neural Flow / results.json
Mechanism confirmed, baseline not beaten
1{
2 "seed": 2678,
3 "quadratic_verification": {
4 "predictions": {
5 "boundary": "Euler energy descent is guaranteed for eta*L < 2; with eta=gamma*2/L, transition is gamma=1.",
6 "contraction": "Quadratic mode factor is |1-eta*lambda|; instability begins when eta*lambda_max>2.",
7 "scaling": "The sufficient descent coefficient 1-eta*L/2 depends only on eta*L, not absolute L when eta is scaled by 1/L."
8 },
9 "sweep": [
10 {
11 "gamma": 0.2,
12 "eta": 0.05714285714285715,
13 "eta_L": 0.4,
14 "monotone_energy": true,
15 "max_energy_increase": -0.0018225211027255717,
16 "final_norm": 0.5793798156406682,
17 "observed_contraction_factor": 0.9857142857142858,
18 "predicted_contraction_factor": 0.9857142857142858,
19 "diverged_by_40_steps": false
20 },
21 {
22 "gamma": 0.5,
23 "eta": 0.14285714285714285,
24 "eta_L": 1.0,
25 "monotone_energy": true,
26 "max_energy_increase": -0.000553914262213814,
27 "final_norm": 0.24212844032697112,
28 "observed_contraction_factor": 0.9642857142857143,
29 "predicted_contraction_factor": 0.9642857142857143,
30 "diverged_by_40_steps": false
31 },
32 {
33 "gamma": 0.8,
34 "eta": 0.2285714285714286,
35 "eta_L": 1.6,
36 "monotone_energy": true,
37 "max_energy_increase": -0.00015856319958101233,
38 "final_norm": 0.10078362154379822,
39 "observed_contraction_factor": 0.9428571428571428,
40 "predicted_contraction_factor": 0.9428571428571428,
41 "diverged_by_40_steps": false
42 },
43 {
44 "gamma": 0.99,
45 "eta": 0.28285714285714286,
46 "eta_L": 1.98,
47 "monotone_energy": true,
48 "max_energy_increase": -0.02991478224457711,
49 "final_norm": 0.4583862502349583,
50 "observed_contraction_factor": 0.98,
51 "predicted_contraction_factor": 0.98,
52 "diverged_by_40_steps": false
53 },
54 {
55 "gamma": 1.0,
56 "eta": 0.2857142857142857,
57 "eta_L": 2.0,
58 "monotone_energy": true,
59 "max_energy_increase": -6.165691387405303e-05,
60 "final_norm": 1.0015425167112906,
61 "observed_contraction_factor": 1.0,
62 "predicted_contraction_factor": 1.0,
63 "diverged_by_40_steps": false
64 },
65 {
66 "gamma": 1.01,
67 "eta": 0.2885714285714286,
68 "eta_L": 2.02,
69 "monotone_energy": false,
70 "max_energy_increase": 0.6368284018447827,
71 "final_norm": 2.165416232595698,
72 "observed_contraction_factor": 1.02,
73 "predicted_contraction_factor": 1.02,
74 "diverged_by_40_steps": false
75 },
76 {
77 "gamma": 1.2,
78 "eta": 0.34285714285714286,
79 "eta_L": 2.4,
80 "monotone_energy": false,
81 "max_energy_increase": 428617588905.42065,
82 "final_norm": 500026.9261364795,
83 "observed_contraction_factor": 1.4,
84 "predicted_contraction_factor": 1.4,
85 "diverged_by_40_steps": true
86 },
87 {
88 "gamma": 1.5,
89 "eta": 0.42857142857142855,
90 "eta_L": 3.0,
91 "monotone_energy": false,
92 "max_energy_increase": 7.933575691221004e+23,
93 "final_norm": 549755813888.0,
94 "observed_contraction_factor": 2.0,
95 "predicted_contraction_factor": 2.0,
96 "diverged_by_40_steps": true
97 }
98 ],
99 "scaling_sweep": [
100 {
101 "lambda_max": 1.0,
102 "eta": 1.6,
103 "descent_coefficient": 0.19999999999999996
104 },
105 {
106 "lambda_max": 2.0,
107 "eta": 0.8,
108 "descent_coefficient": 0.19999999999999996
109 },
110 {
111 "lambda_max": 5.0,
112 "eta": 0.32,
113 "descent_coefficient": 0.19999999999999996
114 },
115 {
116 "lambda_max": 10.0,
117 "eta": 0.16,
118 "descent_coefficient": 0.19999999999999996
119 }
120 ],
121 "observed_transition_gamma": 1.0
122 },
123 "mini_experiment": {
124 "device": "cuda",
125 "train_loss_4_steps": {
126 "baseline": 0.23115138709545135,
127 "energy_gradient": 0.22093874216079712
128 },
129 "12_step_mse": {
130 "baseline": 0.408142626285553,
131 "energy_gradient": 0.4640645682811737
132 },
133 "energy_mean_first_last": [
134 -4.184106826782227,
135 -6.150582313537598
136 ],
137 "energy_nonincreasing_fraction": 1.0,
138 "gradient_norm_first_last": [
139 1.1651203632354736,
140 0.499337375164032
141 ],
142 "mean_cumulative_path_length": 2.355754792690277
143 }
144}