Natural dynamical reduction of the three-body problem

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ملخص

The three-body problem is a fundamental long-standing open problem, with applications in all branches of physics, including astrophysics, nuclear physics and particle physics. In general, conserved quantities allow to reduce the formulation of a mechanical problem to fewer degrees of freedom, a process known as dynamical reduction. However, extant reductions are either non-general, or hide the problem’s symmetry or include unexplained definitions. This paper presents a general and natural dynamical reduction, which avoids these issues. Any three-body configuration defines a triangle, and its orientation in space. Accordingly, we decompose the dynamical variables into the geometry (shape + size) and orientation of the triangle. The geometry variables are shown to describe the motion of an abstract point in a curved 3d space, subject to a potential-derived force and a magnetic-like force with a monopole charge. The orientation variables are shown to obey a dynamics analogous to the Euler equations for a rotating rigid body; only here the moments of inertia depend on the geometry variables, rather than being constant. The reduction rests on a novel symmetric solution to the center of mass constraint inspired by Lagrange’s solution to the cubic. The formulation of the orientation variables is novel and rests on a partially known generalization of the Euler–Lagrange equations to non-coordinate velocities. Applications to global features, to the statistical solution, to special exact solutions and to economized simulations are presented. A generalization to the four-body problem is presented.

اللغة الأصليةإنجليزيّة أمريكيّة
رقم المقال29
دوريةCelestial Mechanics and Dynamical Astronomy
مستوى الصوت135
رقم الإصدار3
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - يونيو 2023

All Science Journal Classification (ASJC) codes

  • !!Computational Mathematics
  • !!Astronomy and Astrophysics
  • !!Applied Mathematics
  • !!Mathematical Physics
  • !!Space and Planetary Science
  • !!Modeling and Simulation

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