Preface
This section studies some first order nonlinear ordinary differential equations describing the time evolution (or “motion”) of those hamiltonian systems provided with a first integral linking implicitly both variables to a motion constant. An application has been performed on the Lotka--Volterra predator-prey system, turning to a strongly nonlinear differential equation in the phase variables.
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Introduction to Linear Algebra with Mathematica
Glossary
Pendulum numerical simulation
portrait =
StreamPlot[{fx[x, y], fy[x, y]}, {x, -6, 6}, {y, -3, 3},
AspectRatio -> Automatic]
solution =
Function[point, Function @@ {t, ({x[t], y[t]} /.
NDSolve[{x'[t] == fx[x[t], y[t]], y'[t] == fy[x[t], y[t]],
Thred[{x[time], y[time]} == point]}, {x, y}, {t, time,
time + 40}])[[1]]}]
Function[point, Function @@ {t, ({x[t], y[t]} /.
NDSolve[{Derivative[1][x][t] == fx[x[t], y[t]],
Derivative[1][y][t] == fy[x[t], y[t]],
Thred[{x[time], y[time]} == point]}, {x, y}, {t, time, time + 40}])[[1]]}]
sol1
contains the two interpolating functions (Mathematica uses cubic splines) that represent x(t) and v(t). We can evaluate them or plot
them. For example, the values at t = 3 are
PlotStyle -> {Dashing[{}], Dashing[{0.02, 0.02}]}]
ysol1[t_] := Last[sol1]
sol1
contains the two interpolating functions (Mathematica uses cubic splines) that represent x(t) and v(t). We can evaluate them or plot
them. For example, the values at t = 3 are
PlotStyle -> {Dashing[{}], Dashing[{0.02, 0.02}]}]
ysol1[t_] := Last[sol1]
xsol1
and ysol1
.
Now we turn to plotting solutions of the pendulum equation subject to distinct initial conditions. Actually, we define three solutions:
sol3 = ans[0.25, 1, 3, 0, 15]
PlotRange -> {{-1.6, 3.1}, {-1.9, 1.4}}, AxesLabel -> {"x", "v"}, PlotStyle -> {{Thick, Red}, {Thick, Blue}, {Thick, Green}}]
PlotRange -> {-2, 3}, PlotStyle -> {{Thick, Red}, {Thick, Blue}, {Thick, Green}}]
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