Analytic Markov-Routing Lyapunov Controller / results.json
Mechanism failed
1{
2 "matrices": [
3 [
4 [
5 1.18,
6 0.22
7 ],
8 [
9 0.04,
10 0.82
11 ]
12 ],
13 [
14 [
15 0.86,
16 0.16
17 ],
18 [
19 -0.1,
20 1.26
21 ]
22 ]
23 ],
24 "stationary_check_p05": {
25 "empirical_pi": [
26 0.493125,
27 0.506875
28 ],
29 "theoretical_pi": [
30 0.5,
31 0.5
32 ],
33 "mass_equation_max_residual": 0.00687500000000002
34 },
35 "stationary_check_p095": {
36 "empirical_pi": [
37 0.5105,
38 0.4895
39 ],
40 "theoretical_pi": [
41 0.5,
42 0.5
43 ],
44 "mass_equation_max_residual": 0.01050000000000001
45 },
46 "smoothness_fd": {
47 "symmetry_point": {
48 "p": 0.5,
49 "predicted_derivative": 0.0,
50 "rows": [
51 {
52 "h": 0.08,
53 "derivative": 0.08604483944413381,
54 "abs_error_vs_predicted_zero": 0.08604483944413381
55 },
56 {
57 "h": 0.04,
58 "derivative": 0.06598617028438936,
59 "abs_error_vs_predicted_zero": 0.06598617028438936
60 },
61 {
62 "h": 0.02,
63 "derivative": -0.0035553233883770657,
64 "abs_error_vs_predicted_zero": 0.0035553233883770657
65 },
66 {
67 "h": 0.01,
68 "derivative": -0.028830274117891755,
69 "abs_error_vs_predicted_zero": 0.028830274117891755
70 },
71 {
72 "h": 0.005,
73 "derivative": 0.016807390162384278,
74 "abs_error_vs_predicted_zero": 0.016807390162384278
75 }
76 ]
77 },
78 "interior_point": {
79 "p": 0.35,
80 "rows": [
81 {
82 "h": 0.04,
83 "derivative": 0.057535700217820104
84 },
85 {
86 "h": 0.02,
87 "derivative": 0.024060335784685007
88 },
89 {
90 "h": 0.01,
91 "derivative": 0.014878132091934206
92 },
93 {
94 "h": 0.005,
95 "derivative": -0.04080460977431456
96 }
97 ]
98 }
99 },
100 "boundary_sweep": [
101 {
102 "p": 0.05,
103 "mean_lambda": 0.014440067036664131,
104 "std_over_seeds": 0.000229287803093258
105 },
106 {
107 "p": 0.1,
108 "mean_lambda": 0.01603810748597485,
109 "std_over_seeds": 0.0004167124270967387
110 },
111 {
112 "p": 0.25,
113 "mean_lambda": 0.021485863538148547,
114 "std_over_seeds": 0.0008744452911053991
115 },
116 {
117 "p": 0.5,
118 "mean_lambda": 0.032439754459780486,
119 "std_over_seeds": 0.0011245488617561102
120 },
121 {
122 "p": 0.75,
123 "mean_lambda": 0.06176584551297099,
124 "std_over_seeds": 0.0021265752746986027
125 },
126 {
127 "p": 0.9,
128 "mean_lambda": 0.1117609970916824,
129 "std_over_seeds": 0.0012845996163561514
130 },
131 {
132 "p": 0.95,
133 "mean_lambda": 0.14526129666461574,
134 "std_over_seeds": 0.000600277379423307
135 }
136 ],
137 "controller": {
138 "target_lambda": 0.03407972489448906,
139 "initial_p": 0.2,
140 "final_p": 0.20040328581658762,
141 "trace": [
142 0.017883118489610605,
143 0.017850025521083477,
144 0.018602873777378147,
145 0.01893958123637008,
146 0.0175831409546936,
147 0.020314420683836643,
148 0.019373077954501692,
149 0.017538683541248885,
150 0.017749856631798597,
151 0.01796167244382069,
152 0.01926271808275504,
153 0.017999524357872304
154 ]
155 },
156 "predictions": [
157 "For primitive p in (0,1), empirical stationary masses should approach pi=(.5,.5).",
158 "In the smooth interior, central finite-difference derivative error should decrease approximately quadratically with h after accounting for Monte Carlo noise.",
159 "Near p=0 or p=1, mixing slows and finite-time Lyapunov estimates should have larger seed variance than at p=.5."
160 ]
161}