. 2019 May 24;21(5):525. doi: 10.3390/e21050525

Table A3.

Estimated computational demands.

#	Measure	t(n = 3)	t(n = 4)	t(n = 5)	t(n = 6)	x
	$Φ_{3.0}^{p e a k}$	0.40	1.51	102.67	9397.08	31.13
A	CO $Φ_{3.0}^{p e a k}$	0.39	1.22	26.61	874.54	13.74
B	NN $Φ_{3.0}^{p e a k}$	0.35	1.27	68.61	7070.00	29.06
C	WS $Φ_{3.0}^{p e a k}$	0.32	1.41	91.57	8379.66	32.33
D	IC $Φ_{3.0}^{p e a k}$	0.31	1.18	74.64	8175.50	31.56
E	Est₅Φ_3.0	0.08	0.30	20.53	1879.41	31.13
F	$Φ_{2.0}^{p e a k}$	0.39	1.49	27.60	691.91	12.59
G	$Φ_{2.5}^{p e a k}$	0.37	1.90	33.12	850.35	13.47
H	D1	0.00003	0.00003	0.00004	0.0001	1.43
I	D2	0.000	0.001	0.001	0.002	1.64
J	S	0.005	0.005	0.006	0.007	1.14
K	LZ	0.03	0.02	0.02	0.02	0.99
L	Φ*	0.23	0.29	0.43	0.60	1.38
M	SI	0.20	0.29	0.38	0.38	1.24
N	MI	0.17	0.22	0.18	0.06	0.71
O	AP $Φ_{3.0}^{p e a k}$	0.44	3.98	2021.79	-	67.73

Abbreviations:t(n = i): time in seconds to calculate the relevant measure for a system of size n = 3, 4, 5, 6; x: exponent in a logarithmic regression fit of the form time = bn^x, where n is the system size in nodes, and b is a constant (not reported); Est₅: $Φ_{3.0}^{p e a k}$ estimated from five sample states.