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1
(c_0 - x_0 / c_1) / c_2
1
[ [ 0.7, 1.2, 2.31 ] ]
[ [ 10 ], [ 3.54 ] ]
x_0 > 0
c_1 > 0, c_2 > 0
RC-circuit (charging capacitor)
c_0: fixed voltage source, c_1: capacitance, c_2: resistance
x_0: charge
strogatz p.20
[ [ "0.303030303030303 - 0.360750360750361*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
2
c_0 * x_0
1
[ [ 0.23 ] ]
[ [ 4.78 ], [ 0.87 ] ]
x_0 > 0
Population growth (naive)
c_0: growth rate
x_0: population
strogatz p.22
[ [ "0.23*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
3
c_0 * x_0 * (1 - x_0 / c_1)
1
[ [ 0.79, 74.3 ] ]
[ [ 7.3 ], [ 21 ] ]
x_0 > 0
c_1 > 0
Population growth with carrying capacity
c_0: growth rate, c_1: carrying capacity
x_0: population
strogatz p.22
[ [ "0.79*x_0*(1 - 0.0134589502018843*x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
4
1 / (1 + exp(c_0 - x_0 / c_1)) - 0.5
1
[ [ 0.5, 0.96 ] ]
[ [ 0.8 ], [ 0.02 ] ]
x_0 > 0
c_1 > 0
RC-circuit with non-linear resistor (charging capacitor)
c_0: fixed voltage source, c_1: capacitance
x_0: charge
strogatz p.38
[ [ "-0.5 + 1/(1 + 1.64872127070013*exp(-1.04166666666667*x_0))" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
5
c_0 - c_1 * x_0^2
1
[ [ 9.81, 0.0021175 ] ]
[ [ 0.5 ], [ 73 ] ]
c_0 > 0, c_1 > 0
Velocity of a falling object with air resistance
c_0: gravitational acceleration, c_1: overall drag for human: 0.5 * C * rho * A / m, with drag coeff C=0.7, air density rho=1.21, cross-sectional area A=0.25, mass m=50
x_0: velocity
strogatz p.38
[ [ "9.81 - 0.0021175*x_0**2" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
6
c_0 * x_0 - c_1 * x_0^2
1
[ [ 2.1, 0.5 ] ]
[ [ 0.13 ], [ 2.24 ] ]
x_0 > 0
c_0 > 0, c_1 > 0
Autocatalysis with one fixed abundant chemical
c_0: concentration of abundant chemical A times the rate constant of A + X -> 2 X, c_1: rate constant of A + X -> 2X
x_0: concentration of chemical X
strogatz p.39
[ [ "-0.5*x_0**2 + 2.1*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
7
c_0 * x_0 * log(c_1 * x_0)
1
[ [ 0.032, 2.29 ] ]
[ [ 1.73 ], [ 9.5 ] ]
x_0 > 0
c_0 > 0, c_1 > 0
Gompertz law for tumor growth
c_0: growth rate, c_1: tumor carrying capacity
x_0: proportional to number of cells (tumor size)
strogatz p.39
[ [ "0.032*x_0*log(2.29*x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
8
c_0 * x_0 * (1 - x_0 / c_1) * (x_0 / c_2 - 1)
1
[ [ 0.14, 130, 4.4 ] ]
[ [ 6.123 ], [ 2.1 ] ]
x_0 > 0
c_0 > 0, c_1 > 0, c_2 > 0
Logistic equation with Allee effect
c_0: growth rate, c_1: carrying capacity, c_2: Allee effect parameter
x_0: population
strogatz p.39
[ [ "0.14*x_0*(1 - 0.00769230769230769*x_0)*(0.227272727272727*x_0 - 1)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
9
(1 - x_0) * c_0 - x_0 * c_1
1
[ [ 0.32, 0.28 ] ]
[ [ 0.14 ], [ 0.55 ] ]
0 < x_0 < 1
c_0 >= 0, c_1 >= 0
Language death model for two languages
c_0: rate of language 1 speakers switching to language 2, c_1: rate of language 2 speakers switching to language 1
x_0: proportion of population speaking language 1
strogatz p.40
[ [ "0.32 - 0.6*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
10
(1 - x_0) * c_0 * x_0^c_1 - x_0 * (1 - c_0) * (1 - x_0)^c_1
1
[ [ 0.2, 1.2 ] ]
[ [ 0.83 ], [ 0.34 ] ]
0 < x_0 < 1
0 <= c_0 <= 1, c_1 > 1
Refined language death model for two languages
c_0: perceived status of language 1, c_1: adjustable exponent
x_0: proportion of population speaking language 1
strogatz p.40
[ [ "-0.8*x_0*(1 - x_0)**1.2 + 0.2*x_0**1.2*(1 - x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
11
- x_0^3
1
[ [] ]
[ [ 3.4 ], [ 1.6 ] ]
Naive critical slowing down (statistical mechanics)
x_0: order parameter
strogatz p.41
[ [ "-x_0**3" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
12
c_0 * x_0 - c_1 * x_0^2
1
[ [ 1.8, 0.1107 ] ]
[ [ 11 ], [ 1.3 ] ]
x_0 > 0
c_0 > 0, c_1 > 0
Photons in a laser (simple)
c_0: G * N0 - k, for G: gain coefficient, N0: initial excited atoms, k: loss rate, c_1: alpha * G, for G: gain coefficient, alpha: rate of atoms dropping back to ground state
x_0: number of photons
strogatz p.55
[ [ "-0.1107*x_0**2 + 1.8*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
13
c_0 * sin(x_0) * (c_1 * cos(x_0) - 1)
1
[ [ 0.0981, 9.7 ] ]
[ [ 3.1 ], [ 2.4 ] ]
c_0 > 0, c_1 > 0
Overdamped bead on a rotating hoop
c_0: m * g, for m: mass, g: gravitational acceleration, c_1: r * omega^2 / g, for r: radius, omega: angular velocity
x_0: angle
strogatz p.63
[ [ "0.0981*(9.7*cos(x_0) - 1)*sin(x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
14
c_0 * x_0 * (1 - x_0 / c_1) - c_3 * x_0^2 / (c_2^2 + x_0^2)
1
[ [ 0.78, 81, 21.2, 0.9 ] ]
[ [ 2.76 ], [ 23.3 ] ]
x_0 > 0
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0
Budworm outbreak model with predation
c_0: growth rate, c_1: carrying capacity, c_2: predation onset, c_3: predation limit
x_0: population
strogatz p.75
[ [ "-0.9*x_0**2/(x_0**2 + 449.44) + 0.78*x_0*(1 - 0.0123456790123457*x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
15
c_0 * x_0 * (1 - x_0 / c_1) - x_0^2 / (1 + x_0^2)
1
[ [ 0.4, 95 ] ]
[ [ 44.3 ], [ 4.5 ] ]
x_0 > 0
c_0 > 0, c_1 > 0
Budworm outbreak with predation (dimensionless)
c_0: growth rate (<0.5 for young forest, 1 for mature), c_1: carrying capacity (~300 for young forest)
x_0: population
strogatz p.76
[ [ "-x_0**2/(x_0**2 + 1) + 0.4*x_0*(1 - 0.0105263157894737*x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
16
c_0 * x_0 - c_1 * x_0^3 - c_2 * x_0^5
1
[ [ 0.1, -0.04, 0.001 ] ]
[ [ 0.94 ], [ 1.65 ] ]
c_0 > 0
Landau equation (typical time scale tau = 1)
c_0: small dimensionless parameter, c_1: constant, c_2: constant; c_1 > 0 for supercritical bifurcation; c_1 < 0 and c_2 > 0 for subcritical bifurcation
x_0: order parameter
strogatz p.87
[ [ "-0.001*x_0**5 + 0.04*x_0**3 + 0.1*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
17
c_0 * x_0 * (1 - x_0 / c_1) - c_2
1
[ [ 0.4, 100, 0.3 ] ]
[ [ 14.3 ], [ 34.2 ] ]
x_0 > 0
c_0 > 0, c_1 > 0, c_2 >= 0
Logistic equation with harvesting/fishing
c_0: growth rate, c_1: carrying capacity, c_2: harvesting rate
x_0: population
strogatz p.89
[ [ "0.4*x_0*(1 - 0.01*x_0) - 0.3" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
18
c_0 * x_0 * (1 - x_0 / c_1) - c_2 * x_0 / (c_3 + x_0)
1
[ [ 0.4, 100, 0.24, 50 ] ]
[ [ 21.1 ], [ 44.1 ] ]
x_0 > 0
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0
Improved logistic equation with harvesting/fishing
c_0: growth rate, c_1: carrying capacity, c_2: harvesting rate, c_3: harvesting onset
x_0: population
strogatz p.90
[ [ "0.4*x_0*(1 - 0.01*x_0) - 0.24*x_0/(x_0 + 50.0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
19
x_0 * (1 - x_0) - c_0 * x_0 / (c_1 + x_0)
1
[ [ 0.08, 0.8 ] ]
[ [ 0.13 ], [ 0.03 ] ]
x_0 > 0
c_0 > 0, c_1 > 0
Improved logistic equation with harvesting/fishing (dimensionless)
c_0: harvesting rate, c_1: harvesting onset
x_0: population
strogatz p.90
[ [ "x_0*(1 - x_0) - 0.08*x_0/(x_0 + 0.8)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
20
c_0 - c_1 * x_0 + x_0^2 / (1 + x_0^2)
1
[ [ 0.1, 0.55 ] ]
[ [ 0.002 ], [ 0.25 ] ]
x_0 > 0
c_0 >= 0, c_1 > 0
Autocatalytic gene switching (dimensionless)
c_0: basal production rate, c_1: degradation rate
x_0: gene product
strogatz p.91
[ [ "x_0**2/(x_0**2 + 1) - 0.55*x_0 + 0.1" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
21
c_0 - c_1 * x_0 - exp(-x_0)
1
[ [ 1.2, 0.2 ] ]
[ [ 0 ], [ 0.8 ] ]
x_0 >= 0
c_0 >= 1, c_1 > 0
Dimensionally reduced SIR infection model for dead people (dimensionless)
c_0: death rate, c_1: unknown parameter group
x_0: dead people
strogatz p.92
[ [ "-0.2*x_0 + 1.2 - exp(-x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
22
c_0 + c_1 * x_0^5 / (c_2 + x_0^5) - c_3 * x_0
1
[ [ 1.4, 0.4, 123, 0.89 ] ]
[ [ 3.1 ], [ 6.3 ] ]
x_0 > 0
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0
Hysteretic activation of a protein expression (positive feedback, basal promoter expression)
c_0: basal transcription rate, c_1: maximum transcription rate, c_2: activation coefficient, c_3: decay rate
x_0: protein concentration
strogatz p.93
[ [ "0.4*x_0**5/(x_0**5 + 123.0) - 0.89*x_0 + 1.4" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
23
c_0 - sin(x_0)
1
[ [ 0.21 ] ]
[ [ -2.74 ], [ 1.65 ] ]
-pi <= x_0 <= pi
c_0 > 0
Overdamped pendulum with constant driving torque/fireflies/Josephson junction (dimensionless)
c_0: ratio of driving torque to maximum gravitational torque
x_0: angle
strogatz p.104
[ [ "0.21 - sin(x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
24
x_1 | - c_0 * x_0
2
[ [ 2.1 ] ]
[ [ 0.4, -0.03 ], [ 0, 0.2 ] ]
c_0 > 0
Harmonic oscillator without damping
c_0: spring constant to mass ratio
x_0: position, x_1: velocity
strogatz p.126
[ [ "x_1", "-2.1*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
25
x_1 | - c_0 * x_0 - c_1 * x_1
2
[ [ 4.5, 0.43 ] ]
[ [ 0.12, 0.043 ], [ 0, -0.3 ] ]
c_0 > 0, c_1 > 0
Harmonic oscillator with damping
c_0: spring constant to mass ratio, c_1: damping coefficient to mass ratio
x_0: position, x_1: velocity
strogatz p.144
[ [ "x_1", "-4.5*x_0 - 0.43*x_1" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
26
x_0 * (c_0 - x_0 - c_1 * x_1) | x_1 * (c_2 - x_0 - x_1)
2
[ [ 3, 2, 2 ] ]
[ [ 5, 4.3 ], [ 2.3, 3.6 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0, c_2 > 0
Lotka-Volterra competition model (Strogatz version with sheeps and rabbits)
c_0: growth rate of rabbits, c_1: death rate of rabbits due to sheeps, c_2: growth rate of sheeps
x_0: rabbits, x_1: sheeps
strogatz p.157
[ [ "x_0*(-x_0 - 2.0*x_1 + 3.0)", "x_1*(-x_0 - x_1 + 2.0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
27
x_0 * (c_0 - c_1 * x_1) | - x_1 * (c_2 - c_3 * x_0)
2
[ [ 1.84, 1.45, 3, 1.62 ] ]
[ [ 8.3, 3.4 ], [ 0.4, 0.65 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0
Lotka-Volterra simple (as on Wikipedia)
c_0: growth rate of prey without predators, c_1: killing rate of prey due to predators, c_2: death rate of predators without prey, c_3: growth rate of predators per prey
x_0: prey, x_1: predators
https://en.wikipedia.org/wiki/Lotka-Volterra_equations
[ [ "x_0*(1.84 - 1.45*x_1)", "-x_1*(3.0 - 1.62*x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
28
x_1 | - c_0 * sin(x_0)
2
[ [ 0.9 ] ]
[ [ -1.9, 0 ], [ 0.3, 0.8 ] ]
-pi <= x_0 <= pi
c_0 > 0
Pendulum without friction
c_0: gravitational acceleration to length ratio
x_0: angle, x_1: angular velocity
strogatz p.169
[ [ "x_1", "-0.9*sin(x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
29
c_0 * x_0 * x_1 | x_1^2 - x_0^2
2
[ [ 0.65 ] ]
[ [ 3.2, 1.4 ], [ 1.3, 0.2 ] ]
c_0 > 0
Dipole fixed point
c_0: constant
x_0: x, x_1: y
strogatz p.181
[ [ "0.65*x_0*x_1", "-x_0**2 + x_1**2" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
30
x_0 * (x_1 - c_0 * x_0 * x_1) | x_1 * (x_0 - c_0 * x_0 * x_1)
2
[ [ 1.61 ] ]
[ [ 0.3, 0.04 ], [ 0.1, 0.21 ] ]
x_0 > 0, x_1 > 0
c_0 > 0
RNA molecules catalyzing each others replication
c_0: catalytic rate
x_0: concentration of molecule 1, x_1: concentration of molecule 2
strogatz p.187
[ [ "x_0*(-1.61*x_0*x_1 + x_1)", "x_1*(-1.61*x_0*x_1 + x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
31
- c_0 * x_0 * x_1 | c_0 * x_0 * x_1 - c_1 * x_1
2
[ [ 0.4, 0.314 ] ]
[ [ 7.2, 0.98 ], [ 20, 12.4 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0
SIR infection model only for healthy and sick
c_0: recovery rate, c_1: infection rate
x_0: healthy, x_1: sick
strogatz p.188
[ [ "-0.4*x_0*x_1", "0.4*x_0*x_1 - 0.314*x_1" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
32
x_1 | - c_0 * x_1 + x_0 - x_0^3
2
[ [ 0.18 ] ]
[ [ -1.8, -1.8 ], [ 5.8, 0 ] ]
c_0 > 0
Damped double well oscillator
c_0: damping coefficient
x_0: position, x_1: velocity
strogatz p.190
[ [ "x_1", "-x_0**3 + x_0 - 0.18*x_1" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
33
- sin(x_1) - c_0 * x_0^2 | x_0 - cos(x_1) / x_0
2
[ [ 0.08 ] ]
[ [ 5, 0.7 ], [ 9.81, -0.8 ] ]
x_0 > 0
c_0 > 0
Glider (dimensionless)
c_0: drag coefficient
x_0: speed, x_1: angle to horizontal
strogatz p.190
[ [ "-0.08*x_0**2 - sin(x_1)", "x_0 - cos(x_1)/x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
34
x_1 | sin(x_0) * (cos(x_0) - c_0)
2
[ [ 0.93 ] ]
[ [ 2.1, 0 ], [ -1.2, -0.2 ] ]
c_0 > 0
Frictionless bead on a rotating hoop (dimensionless)
c_0: gravitational acceleration over radius times omega^2
x_0: angle, x_1: angular velocity
strogatz p.191
[ [ "x_1", "(cos(x_0) - 0.93)*sin(x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
35
cot(x_1) * cos(x_0) | sin(x_0) * (cos(x_1)^2 + c_0 * sin(x_1)^2)
2
[ [ 4.2 ] ]
[ [ 1.13, -0.3 ], [ 2.4, 1.7 ] ]
-pi < x_0 <= pi, -pi / 2 <= x_1 <= pi / 2
c_0 > 0
Rotational dynamics of an object in a shear flow
c_0: shape dependent parameter
x_0: longitude (angle around z-axis), x_1: latitue (angle from north)
strogatz p.194
[ [ "cos(x_0)*cot(x_1)", "(4.2*sin(x_1)**2 + cos(x_1)**2)*sin(x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
36
x_1 | - sin(x_0) - x_1 - c_0 * cos(x_0) * x_1
2
[ [ 0.07 ] ]
[ [ 0.45, 0.9 ], [ 1.34, -0.8 ] ]
-pi < x_o < pi
c_0 > 0
Pendulum with non-linear damping, no driving (dimensionless)
c_0: Damping coefficient
x_0: angle, x_1: angular velocity
strogatz p.195
[ [ "x_1", "-0.07*x_1*cos(x_0) - x_1 - sin(x_0)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
37
x_1 | - x_0 - c_0 * (x_0^2 - 1) * x_1
2
[ [ 0.43 ] ]
[ [ 2.2, 0 ], [ 0.1, 3.2 ] ]
c_0 > 0
Van der Pol oscillator (standard form)
c_0: damping parameter for nonlinear damping term
x_0: position, x_1: velocity
strogatz p.200
[ [ "x_1", "-x_0 - 0.43*x_1*(x_0**2 - 1)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
38
c_0 * (x_1 - x_0^3 / 3 + x_0) | - x_0 / c_0
2
[ [ 3.37 ] ]
[ [ 0.7, 0 ], [ -1.1, -0.7 ] ]
c_0 > 0
Van der Pol oscillator (simplified form from Strogatz)
c_0: damping parameter for nonlinear damping term
x_0: position, x_1: velocity
strogatz p.214
[ [ "-1.12333333333333*x_0**3 + 3.37*x_0 + 3.37*x_1", "-0.29673590504451*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
39
- x_0 + c_0 * x_1 + x_0^2 * x_1 | c_1 - c_0 * x_0 - x_0^2 * x_1
2
[ [ 2.4, 0.07 ] ]
[ [ 0.4, 0.31 ], [ 0.2, -0.7 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0
Glycolytic oscillator, e.g., ADP and F6P in yeast (dimensionless)
c_0: kinetic parameter, c_1: kinetic parameter
x_0: concentration of ADP, x_1: concentration of F6P
strogatz p.207
[ [ "x_0**2*x_1 - x_0 + 2.4*x_1", "-x_0**2*x_1 - 2.4*x_0 + 0.07" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
40
x_1 | - x_0 + c_0 * x_1 * (1 - x_0^2)
2
[ [ 0.886 ] ]
[ [ 0.63, -0.03 ], [ 0.2, 0.2 ] ]
c_0 > 0
Duffing equation (weakly non-linear oscillation)
c_0: parameter for cubic nonlinearity
x_0: position, x_1: velocity
strogatz p.217
[ [ "x_1", "-x_0 + 0.886*x_1*(1 - x_0**2)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
41
c_0 * (x_1 - x_0) * (c_1 + x_0^2) - x_0 | c_2 - x_0
2
[ [ 15.3, 0.001, 0.3 ] ]
[ [ 0.8, 0.3 ], [ 0.02, 1.2 ] ]
x_0 > 0, x_1 > 0
c_0 > 1, 0 < c_1 < 1, c_2 > 0, 8 * c_0 * c_1 < 1
Cell cycle model by Tyson for interaction between protein cdc2 and cyclin (dimensionless)
c_0: parameter >> 1, c_1: parameter << 1, c_2: adjustable parameter
x_0: concentration of cdc2, x_1: concentration of cyclin
strogatz p.238
[ [ "-x_0 + 15.3*(-x_0 + x_1)*(x_0**2 + 0.001)", "0.3 - x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
42
c_0 - x_0 - c_1 * x_0 * x_1 / (1 + x_0^2) | c_2 * x_0 * (1 - x_1 / (1 + x_0^2))
2
[ [ 8.9, 4, 1.4 ] ]
[ [ 0.2, 0.35 ], [ 3, 7.8 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0, c_2 > 0
Reduced model for chlorine dioxide-iodine-malonic acid rection (dimensionless)
c_0: empirical rate parameter, c_1: fixed to 4 by strogatz, c_2: empirical rate parameter
x_0: dimensionless I- concentration, x_1: dimensionless ClO2 concentration
strogatz p.260
[ [ "-4.0*x_0*x_1/(x_0**2 + 1) - x_0 + 8.9", "1.4*x_0*(-x_1/(x_0**2 + 1) + 1)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
43
x_1 | c_0 - sin(x_0) - c_1 * x_1
2
[ [ 1.67, 0.64 ] ]
[ [ 1.47, -0.2 ], [ -1.9, 0.03 ] ]
c_0 > 0, c_1 > 0
Driven pendulum with linear damping / Josephson junction (dimensionless)
c_0: driving force/current, c_1: damping parameter
x_0: angle, x_1: angular velocity
strogatz p.269
[ [ "x_1", "-0.64*x_1 - sin(x_0) + 1.67" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
44
x_1 | c_0 - sin(x_0) - c_1 * x_1 * abs(x_1)
2
[ [ 1.67, 0.64 ] ]
[ [ 1.47, -0.2 ], [ -1.9, 0.03 ] ]
c_0 > 0, c_1 > 0
Driven pendulum with quadratic damping (dimensionless)
c_0: driving torque, c_1: damping parameter
x_0: angle, x_1: angular velocity
strogatz p.300
[ [ "x_1", "-0.64*x_1*Abs(x_1) - sin(x_0) + 1.67" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
45
c_0 * (1 - x_0) - x_0 * x_1^2 | x_0 * x_1^2 - c_1 * x_1
2
[ [ 0.5, 0.02 ] ]
[ [ 1.4, 0.2 ], [ 0.32, 0.64 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0
Isothermal autocatalytic reaction model by Gray and Scott 1985 (dimensionless)
c_0: rate constant, c_1: rate constant
x_0: concentration 1, x_1: concentration 2
strogatz p.288
[ [ "-x_0*x_1**2 - 0.5*x_0 + 0.5", "x_0*x_1**2 - 0.02*x_1" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
46
c_0 * sin(x_0 - x_1) - sin(x_0) | c_0 * sin(x_1 - x_0) - sin(x_1)
2
[ [ 0.33 ] ]
[ [ 0.54, -0.1 ], [ 0.43, 1.21 ] ]
c_0 > 0
Interacting bar magnets
c_0: coupling constant
x_0: angle of magnet 1, x_1: angle of magnet 2
strogatz p.289
[ [ "-sin(x_0) + 0.33*sin(x_0 - x_1)", "-sin(x_1) - 0.33*sin(x_0 - x_1)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
47
- x_0 + 1 / (1 + exp(c_0 * x_1 - c_1)) | - x_1 + 1 / (1 + exp(c_0 * x_0 - c_1))
2
[ [ 4.89, 1.4 ] ]
[ [ 0.65, 0.59 ], [ 3.2, 10.3 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0
Binocular rivalry model (no oscillations)
c_0: strength of mutual antagonism, c_1: strength of input stimulus
x_0: perception of left eye stimulus, x_1: perception of right eye stimulus
strogatz p.290
[ [ "-x_0 + 1/(0.246596963941606*exp(4.89*x_1) + 1)", "-x_1 + 1/(0.246596963941606*exp(4.89*x_0) + 1)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
48
c_0 - x_0 - x_0 * x_1 / (1 + c_1 * x_0^2) | c_2 - x_0 * x_1 / (1 + c_1 * x_0^2)
2
[ [ 18.3, 0.48, 11.23 ] ]
[ [ 0.1, 30.4 ], [ 13.2, 5.21 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0, c_2 > 0
Bacterial respiration model for nutrients and oxygen levels
c_0: parameter, c_1: parameter, c_2: parameter
x_0: concentration of nutrients, x_1: concentration of oxygen
strogatz p.293
[ [ "-x_0*x_1/(0.48*x_0**2 + 1) - x_0 + 18.3", "-x_0*x_1/(0.48*x_0**2 + 1) + 11.23" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
49
1 - (c_0 + 1) * x_0 + c_1 * x_0^2 * x_1 | c_0 * x_0 - c_1 * x_0^2 * x_1
2
[ [ 3.03, 3.1 ] ]
[ [ 0.7, -1.4 ], [ 2.1, 1.3 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0
Brusselator: hypothetical chemical oscillation model (dimensionless)
c_0: parameter, c_1: parameter
x_0: concentration of X, x_1: concentration of Y
strogatz p.296
[ [ "3.1*x_0**2*x_1 - 4.03*x_0 + 1", "-3.1*x_0**2*x_1 + 3.03*x_0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
50
c_0 - x_0 + x_0^2 * x_1 | c_1 - x_0^2 * x_1
2
[ [ 0.24, 1.43 ] ]
[ [ 0.14, 0.6 ], [ 1.5, 0.9 ] ]
x_0 > 0, x_1 > 0
c_0 > 0, c_1 > 0
Chemical oscillator model by Schnackenberg 1979 (dimensionless)
c_0: parameter, c_1: parameter
x_0: concentration of X, x_1: concentration of Y
strogatz p.296
[ [ "x_0**2*x_1 - x_0 + 0.24", "-x_0**2*x_1 + 1.43" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
51
c_0 + sin(x_1) * cos(x_0) | c_1 + sin(x_1) * cos(x_0)
2
[ [ 1.432, 0.972 ] ]
[ [ 2.2, 0.67 ], [ 0.03, -0.12 ] ]
-pi < x_0 < pi, -pi < x_1 < pi
c_0 > 0, c_1 > 0
Oscillator death model by Ermentrout and Kopell 1990
c_0: driving torque 1, c_1: driving torque 2
x_0: angle 1, x_1: angle 2
strogatz p.301
[ [ "sin(x_1)*cos(x_0) + 1.432", "sin(x_1)*cos(x_0) + 0.972" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
52
c_0 * (x_1 - x_0) | c_1 * (x_0 * x_2 - x_1) | c_2 * (c_3 + 1 - x_2 - c_3 * x_0 * x_1)
3
[ [ 0.1, 0.21, 0.34, 3.1 ] ]
[ [ 1.3, 1.1, 0.89 ], [ 0.89, 1.3, 1.1 ] ]
x_0 > 0, x_1 > 0, x_2 > 0
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0
Maxwell-Bloch equations (laser dynamics)
c_0: decay rate in cavity, c_1: decay rate atomic polarization, c_2: decay rate population inversion, c_3: pumping energy parameter
x_0: E, x_1: P, x_2: D
strogatz p.82
[ [ "-0.1*x_0 + 0.1*x_1", "0.21*x_0*x_2 - 0.21*x_1", "-1.054*x_0*x_1 - 0.34*x_2 + 1.394" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
53
c_0 - c_5 * x_1 * x_0 / (c_9 + x_0) - c_4 * x_0 | c_1 * x_2 * (c_8 + x_1) - c_2 * x_1 / (c_6 + x_1) - c_3 * x_0 * x_1 / (c_7 + x_1) | - c_1 * x_2 * (c_8 + x_1) + c_2 * x_1 / (c_6 + x_1) + c_3 * x_0 * x_1 / (c_7 + x_1)
3
[ [ 0.1, 0.6, 0.2, 7.95, 0.05, 0.4, 0.1, 2, 0.1, 0.1 ] ]
[ [ 0.005, 0.26, 2.15 ], [ 0.248, 0.0973, 0.0027 ] ]
x_0 > 0, x_1 > 0, x_2 > 0
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0, c_4 > 0, c_5 > 0, c_6 > 0, c_7 > 0, c_8 > 0, c_9 > 0
Model for apoptosis (cell death)
c_0: parameter, c_1: parameter, c_2: parameter, c_3: parameter, c_4: parameter, c_5: parameter, c_6: parameter, c_7: parameter, c_8: parameter, c_9: parameter
x_0: x, x_1: y, x_2: z
https://epubs.siam.org/doi/10.1137/20M1318043
[ [ "-0.4*x_0*x_1/(x_0 + 0.1) - 0.05*x_0 + 0.1", "-7.95*x_0*x_1/(x_1 + 2.0) - 0.2*x_1/(x_1 + 0.1) + 0.6*x_2*(x_1 + 0.1)", "7.95*x_0*x_1/(x_1 + 2.0) + 0.2*x_1/(x_1 + 0.1) - 0.6*x_2*(x_1 + 0.1)" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
54
c_0 * (x_1 - x_0) | c_1 * x_0 - x_1 - x_0 * x_2 | x_0 * x_1 - c_2 * x_2
3
[ [ 5.1, 12, 1.67 ] ]
[ [ 2.3, 8.1, 12.4 ], [ 10, 20, 30 ] ]
x_0 > 0, x_1 > 0, x_2 > 0
c_0 > 0, c_1 > 0, c_2 > 0
Lorenz equations in well-behaved periodic regime
c_0: Prandtl number (sigma), c_1: Rayleigh number (r), c_2: unnamed parameter (b)
x_0: x, x_1: y, x_2: z
strogatz p.319
[ [ "-5.1*x_0 + 5.1*x_1", "-x_0*x_2 + 12.0*x_0 - x_1", "x_0*x_1 - 1.67*x_2" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
55
c_0 * (x_1 - x_0) | c_1 * x_0 - x_1 - x_0 * x_2 | x_0 * x_1 - c_2 * x_2
3
[ [ 10, 99.96, 2.6666666667 ] ]
[ [ 2.3, 8.1, 12.4 ], [ 10, 20, 30 ] ]
x_0 > 0, x_1 > 0, x_2 > 0
c_0 > 0, c_1 > 0, c_2 > 0
Lorenz equations in complex periodic regime
c_0: Prandtl number (sigma), c_1: Rayleigh number (r), c_2: unnamed parameter (b)
x_0: x, x_1: y, x_2: z
strogatz p.319
[ [ "-10.0*x_0 + 10.0*x_1", "-x_0*x_2 + 99.96*x_0 - x_1", "x_0*x_1 - 2.66666666666667*x_2" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
56
c_0 * (x_1 - x_0) | c_1 * x_0 - x_1 - x_0 * x_2 | x_0 * x_1 - c_2 * x_2
3
[ [ 10, 28, 2.6666666667 ] ]
[ [ 2.3, 8.1, 12.4 ], [ 10, 20, 30 ] ]
x_0 > 0, x_1 > 0, x_2 > 0
c_0 > 0, c_1 > 0, c_2 > 0
Lorenz equations standard parameters (chaotic)
c_0: Prandtl number (sigma), c_1: Rayleigh number (r), c_2: unnamed parameter (b)
x_0: x, x_1: y, x_2: z
strogatz p.319
[ [ "-10.0*x_0 + 10.0*x_1", "-x_0*x_2 + 28.0*x_0 - x_1", "x_0*x_1 - 2.66666666666667*x_2" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
57
c_3 * (- x_1 - x_2) | c_3 * (x_0 + c_0 * x_1) | c_3 * (c_1 + x_2 * (x_0 - c_2))
3
[ [ -0.2, 0.2, 5.7, 5 ] ]
[ [ 2.3, 1.1, 0.8 ], [ -0.1, 4.1, -2.1 ] ]
c_1 > 0, c_2 > 0
Rössler attractor (stable fixed point)
c_0: parameter, c_1: parameter, c_2: parameter, c_3: just for time scaling
x_0: x, x_1: y, x_2: z
https://en.wikipedia.org/wiki/Rössler_attractor
[ [ "-5.0*x_1 - 5.0*x_2", "5.0*x_0 - 1.0*x_1", "5.0*x_2*(x_0 - 5.7) + 1.0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
58
c_3 * (- x_1 - x_2) | c_3 * (x_0 + c_0 * x_1) | c_3 * (c_1 + x_2 * (x_0 - c_2))
3
[ [ 0.1, 0.2, 5.7, 5 ] ]
[ [ 2.3, 1.1, 0.8 ], [ -0.1, 4.1, -2.1 ] ]
c_1 > 0, c_2 > 0
Rössler attractor (periodic)
c_0: parameter, c_1: parameter, c_2: parameter, c_3: just for time scaling
x_0: x, x_1: y, x_2: z
https://en.wikipedia.org/wiki/Rössler_attractor
[ [ "-5.0*x_1 - 5.0*x_2", "5.0*x_0 + 0.5*x_1", "5.0*x_2*(x_0 - 5.7) + 1.0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
59
c_3 * (- x_1 - x_2) | c_3 * (x_0 + c_0 * x_1) | c_3 * (c_1 + x_2 * (x_0 - c_2))
3
[ [ 0.2, 0.2, 5.7, 5 ] ]
[ [ 2.3, 1.1, 0.8 ], [ -0.1, 4.1, -2.1 ] ]
c_1 > 0, c_2 > 0
Rössler attractor (chaotic)
c_0: parameter, c_1: parameter, c_2: parameter, c_3: just for time scaling
x_0: x, x_1: y, x_2: z
https://en.wikipedia.org/wiki/Rössler_attractor
[ [ "-5.0*x_1 - 5.0*x_2", "5.0*x_0 + 1.0*x_1", "5.0*x_2*(x_0 - 5.7) + 1.0" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
60
x_0 * (x_2 - c_1) - c_3 * x_1 | c_3 * x_0 + x_1 * (x_2 - c_1) | c_2 + c_0 * x_2 - x_2^3 / 3. - (x_0^2 + x_1^2) * (1 + c_4 * x_2) + c_5 * x_2 * x_0^3
3
[ [ 0.95, 0.7, 0.65, 3.5, 0.25, 0.1 ] ]
[ [ 0.1, 0.05, 0.05 ], [ -0.3, 0.2, 0.1 ] ]
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0, c_4 > 0
Aizawa attractor (chaotic)
c_0: parameter, c_1: parameter, c_2: parameter, c_3: parameter, c_4: parameter
x_0: x, x_1: y, x_2: z
https://analogparadigm.com/downloads/alpaca_17.pdf
[ [ "x_0*(x_2 - 0.7) - 3.5*x_1", "3.5*x_0 + x_1*(x_2 - 0.7)", "0.1*x_0**3*x_2 - 0.333333333333333*x_2**3 + 0.95*x_2 - (x_0**2 + x_1**2)*(0.25*x_2 + 1) + 0.65" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
61
c_0 * x_0 - x_1 * x_2 | c_1 * x_1 + x_0 * x_2 | c_2 * x_2 + x_0 * x_1 / c_3
3
[ [ 5, -10, -3.8, 3 ] ]
[ [ 15, -15, -15 ], [ 8, 14, -10 ] ]
Chen-Lee attractor; system for gyro motion with feedback control of rigid body (chaotic)
c_0: parameter, c_1: parameter, c_2: parameter, c_3: fixed constant; parameters relate to principal moments of inertia
x_0: omega_x, x_1: omega_y, x_2: omega_z; variables are essentially angular velocities
https://doi.org/10.1016/j.chaos.2003.12.034
[ [ "5.0*x_0 - x_1*x_2", "x_0*x_2 - 10.0*x_1", "0.333333333333333*x_0*x_1 - 3.8*x_2" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
62
- x_0 + 1 / (1 + exp(c_0 * x_2 + c_1 * x_1 - c_2)) | c_3 * (x_0 - x_1) | - x_2 + 1 / (1 + exp(c_0 * x_0 + c_1 * x_3 - c_2)) | c_3 * (x_2 - x_3)
4
[ [ 0.89, 0.4, 1.4, 1 ] ]
[ [ 2.25, -0.5, -1.13, 0.4 ], [ 0.342, -0.431, -0.86, 0.041 ] ]
x_0 > 0, x_1 > 0, x_2 > 0, x_3 > 0
c_0 > 0, c_1 > 0, c_2 > 0, c_3 > 0
Binocular rivalry model with adaptation (oscillations)
c_0: strength of mutual antagonism, c_1: influence of adaptation, c_2: strength of input stimulus, c_3: time scale of adaptation
x_0: perception of left eye stimulus, x_1: adaptation of left eye stimulus, x_2: perception of right eye stimulus, x_3: adaptation of right eye stimulus
strogatz p.295
[ [ "-x_0 + 1/(0.246596963941606*exp(0.4*x_1 + 0.89*x_2) + 1)", "1.0*x_0 - 1.0*x_1", "-x_2 + 1/(0.246596963941606*exp(0.89*x_0 + 0.4*x_3) + 1)", "1.0*x_2 - 1.0*x_3" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...
63
- c_1 * x_0 * x_2 | c_1 * x_0 * x_2 - c_0 * x_1 | c_0 * x_1 - c_2 * x_2 | c_2 * x_2
4
[ [ 0.47, 0.28, 0.3 ] ]
[ [ 0.6, 0.3, 0.09, 0.01 ], [ 0.4, 0.3, 0.25, 0.05 ] ]
0 < x_0 < 1, 0 < x_1 < 1, 0 < x_2 < 1, 0 < x_3 < 1, x_1 + x_2 + x_3 + x_4 = 1
c_0 > 0, c_1 > 0, c_2 > 0
SEIR infection model (proportions)
c_0: transfer rate rate, c_1: transmission rate, c_2: recovery rate
x_0: susceptible, x_1: exposed, x_2: infected, x_3: recovered
https://de.wikipedia.org/wiki/SEIR-Modell
[ [ "-0.28*x_0*x_2", "0.28*x_0*x_2 - 0.47*x_1", "0.47*x_1 - 0.3*x_2", "0.3*x_2" ] ]
[ [ { "success": true, "message": "The solver successfully reached the end of the integration interval.", "t": [ 0, 0.0195694716, 0.0391389432, 0.0587084149, 0.0782778865, 0.0978473581, 0.1174168297, 0.1369863014, 0.15655577...