Given the starting positions, velocities, and masses of three objects interacting via gravity, the classical three-body problem involves determining the motions of the three particles throughout time.

What’s cool about the three-body system is that it’s impossible to solve for the motions of the objects exactly. That is, we can’t write down an equation that describes the system. Instead of finding an exact solution, we solve the system numerically, which amounts to finding an accurate approximation.

The three-body problem is an example of a chaotic system, meaning that even a slight change in the starting conditions drastically changes the time-evolution of the system.

The GIF above shows a planar (i.e., two-dimensional) three-body system.

Mathematica code:

``````G = 1; time = 30;
mA = 1; xA0 = 0; yA0 = 0; vxA0 = 0; vyA0 = 0;
mB = 1; xB0 = 1; yB0 = 0; vxB0 = 0; vyB0 = 0;
mC = 1; xC0 = 0; yC0 = 0.8; vxC0 = 0; vyC0 = 0;
soln1 = NDSolve[
{mA*Derivative[xA][t] ==
-((G*mA*mB*(xA[t] - xB[t]))/((xA[t] - xB[t])^2 +
(yA[t] - yB[t])^2)^(3/2)) -
(G*mA*mC*(xA[t] - xC[t]))/((xA[t] - xC[t])^2 +
(yA[t] - yC[t])^2)^(3/2),
mA*Derivative[yA][t] ==
-((G*mA*mB*(yA[t] - yB[t]))/((xA[t] - xB[t])^2 +
(yA[t] - yB[t])^2)^(3/2)) -
(G*mA*mC*(yA[t] - yC[t]))/((xA[t] - xC[t])^2 +
(yA[t] - yC[t])^2)^(3/2),
mB*Derivative[xB][t] ==
-((G*mB*mC*(xB[t] - xC[t]))/((xB[t] - xC[t])^2 +
(yB[t] - yC[t])^2)^(3/2)) -
(G*mB*mA*(xB[t] - xA[t]))/((xB[t] - xA[t])^2 +
(yB[t] - yA[t])^2)^(3/2),
mB*Derivative[yB][t] ==
-((G*mB*mC*(yB[t] - yC[t]))/((xB[t] - xC[t])^2 +
(yB[t] - yC[t])^2)^(3/2)) -
(G*mB*mA*(yB[t] - yA[t]))/((xB[t] - xA[t])^2 +
(yB[t] - yA[t])^2)^(3/2),
mC*Derivative[xC][t] ==
-((G*mC*mA*(xC[t] - xA[t]))/((xC[t] - xA[t])^2 +
(yC[t] - yA[t])^2)^(3/2)) -
(G*mC*mB*(xC[t] - xB[t]))/((xC[t] - xB[t])^2 +
(yC[t] - yB[t])^2)^(3/2),
mC*Derivative[yC][t] ==
-((G*mC*mA*(yC[t] - yA[t]))/((xC[t] - xA[t])^2 +
(yC[t] - yA[t])^2)^(3/2)) -
(G*mC*mB*(yC[t] - yB[t]))/((xC[t] - xB[t])^2 +
(yC[t] - yB[t])^2)^(3/2),
xA == xA0, yA == yA0,
Derivative[xA] == vxA0, Derivative[yA] == vyA0,
xB == xB0, yB == yB0,
Derivative[xB] == vxB0, Derivative[yB] == vyB0,
xC == xC0, yC == yC0,
Derivative[xC] == vxC0, Derivative[yC] == vyC0
},
{xA, yA, xB, yB, xC, yC},{t, 0, time}, MaxSteps -> 100000]
x1[t_] := Evaluate[xA[t] /. soln1[[1,1]]]
y1[t_] := Evaluate[yA[t] /. soln1[[1,2]]]
x2[t_] := Evaluate[xB[t] /. soln1[[1,3]]]
y2[t_] := Evaluate[yB[t] /. soln1[[1,4]]]
x3[t_] := Evaluate[xC[t] /. soln1[[1,5]]]
y3[t_] := Evaluate[yC[t] /. soln1[[1,6]]]
Manipulate[Show[
{ParametricPlot[
{{x1[t], y1[t]}, {x2[t], y2[t]}, {x3[t], y3[t]}},
{t, tmax - 0.5, tmax},
Axes -> False, PlotRange -> {{-0.55, 1.45},
{-0.55, 1.08}}, PlotStyle -> {Red, Green, Blue},
GridLines -> {Table[0.25*x + 0.07, {x, -100, 100}],
Table[0.25*y + 0.01, {y, -100, 100}]},
GridLinesStyle -> Directive[LightGray]]},
{Graphics[{Opacity[0.7], EdgeForm[Directive[Black]], Red,
Disk[{x1[tmax], y1[tmax]}, 0.03], Green,
Disk[{x2[tmax], y2[tmax]}, 0.03], Blue,
Disk[{x3[tmax], y3[tmax]}, 0.03]}]}, ImageSize -> 600],
{tmax, 6.05, 16.05}]
``````