Past exam of the short options paper shared by Parts A and B of the physics course of the University of Oxford / 2019 / S31 / 2

Let the step be $h$. Forward Euler method gives $x_1=x_0+h{v}_0$, $v_1=v_0+hF(x_0)$. Applying the same map with $-h$ gives $x_2=x_1-h{v}_1=x_0-h^{2}F(x_0)$, which generally differs from $x_0$. It is therefore not its own inverse under time reversal.

A kick–drift–kick leapfrog integrator instead hasThe step $-h$ first recovers $v_{1/2}$, then $x_0$, then $v_0$, so $\boxed{{\Phi }_{-h}={\Phi }_h^{-1}}$. This assumes a position-dependent force and the same fixed step. Newtonian mechanics is reversible; respecting that structure helps avoid artificial directional bias and often improves long-term qualitative behaviour. The usual leapfrog also has a structure preserving symplectic geometry, which supports bounded oscillatory energy error, but reversibility by itself does not imply exact conservation of energy. Adaptive stepping requires special care to preserve these properties.

For a second-order scalar partial differential equation, classification refers to its principal second-derivative form. An elliptic partial differential equation has a definite principal form, exemplified by Poisson's equation; it typically determines a spatial field from boundary data. A parabolic partial differential equation has a distinguished first-order evolution direction and diffusive second spatial derivatives, exemplified by $u_t=D{u}_{xx}$. Its initial data relax or spread with time. Thus the pseudo-time equation is parabolic, while its steady-state spatial equation is elliptic.

At a steady state in pseudo-time, ${\partial }_{\tau }\Phi =0$ and the evolution becomes ${\Phi }_{xx}=4\pi G\rho$, the desired Poisson equation. Deviations from a steady solution obey a diffusion equation, so nonconstant error modes decay. This turns an elliptic boundary-value solve into repeated relaxation steps using familiar time-evolution methods. Boundary data and source compatibility still matter; pseudo-time does not remove a nonexistent steady solution.

A backward Euler method with spatial second-order central differences givesThe source is fixed in pseudo-time; if it were evolving, its evaluation would also need specifying. Each pseudo-time step therefore requires a linear system solve rather than a purely local explicit update.

Let $r=\Delta \tau /h^2$ and impose periodic indices modulo $J$. With ${\mathbf{\Phi }}^n=({\Phi }_0^n,\dots ,{\Phi }_{J-1}^n{)}^T$, the linear system iswhere $S$ shifts one grid cell cyclically. For $J\ge 3$, $A$ has diagonal $1+2r$, adjacent and corner entries $-r$, and all other entries zero. It is a cyclic tridiagonal matrix, rather than a nonperiodic tridiagonal one.

The periodic Laplacian annihilates the constant vector, so its steady equation requires $\boxed{\sum _j{\rho }_j=0}$. A strictly positive gravitational density violates this condition: summing the update gives ${\bar{\Phi }}^{n+1}={\bar{\Phi }}^n-4\pi G\Delta \tau \bar{\rho }$, an indefinitely drifting mean. Periodic gravitational calculations normally solve for $\rho -\bar{\rho }$ and fix the arbitrary mean gravitational potential. The per-step matrix $A$ itself remains invertible; the issue is existence of a periodic steady solution of Poisson's equation.

For an error Fourier mode $e_j^n={\hat{e}}^n{e}^{i\theta j}$, the periodic discrete Laplacian has eigenvalue $-4{\sin }^2(\theta /2)/h^2$. The Backward Euler method therefore has amplification factorvon Neumann stability analysis thus imposes no upper limit on positive $\Delta \tau$. The constant mode has $g=1$ and is not damped; compatible forcing and a gauge condition remain necessary as discussed in part (e). Large steps can accelerate relaxation of nonconstant modes, but require a suitably accurate linear solver and can worsen its conditioning. Unconditional linear stability is not a statement about time accuracy or cost.