import numpy as np import scipy.interpolate as interp from scipy.integrate import solve_ivp def calc_null_curves(times, spatial_coords, gXX, gXt, gtt, reverse = False): """ Compute null curves along a given axis. Shoot a null ray from each point in spatial_coords, in the positive and negative direction and compute its trajectory. :param array_like times: 1D array of coordinate times at which the spacetime curvature is provided :param array_like spatial_coords: 1D array of spatial coordinates :param array_like gXX: 2D array containing the values of the XX component of the spacetime metric, where X is the spatial coordinate along which the rays are traced. gXX[i, j] is the value at spacetime point (t=times[i], X=spatial_coords[j]). :param array_like gXt: same as gXX, but for the Xt component of the metric :param array_like gtt: same as gXX, but for the tt component of the metric :param bool reverse: when true, the null curves are traced from the last time coordinate backwards in time :return: Tuple of (ray_times, rays_pos, rays_neg). rays_*[i, j] contains the X-coordinate of the ray shot from (t=ray_times[0], X=spatial_coords[i]) at time t=ray_times[j]. """ gXX_interp = interp.RectBivariateSpline(times, spatial_coords, gXX) gXt_interp = interp.RectBivariateSpline(times, spatial_coords, gXt) gtt_interp = interp.RectBivariateSpline(times, spatial_coords, gtt) if reverse: ray_times = times[::-1] else: ray_times = times # terminate integration on reaching the outer boundaries def event_x_bound_upper(t, x, sign): return x[0] - spatial_coords[-1] event_x_bound_upper.terminal = True event_x_bound_upper.direction = 1.0 def event_x_bound_lower(t, x, sign): return x[0] - spatial_coords[0] event_x_bound_lower.terminal = True event_x_bound_lower.direction = -1.0 events = [event_x_bound_upper, event_x_bound_lower] # null geodesic equation RHS: # gXX dX^2 + 2 gXt dX dt - gtt dt^2 = 0 # => dx / dt = (-gXt ± √(gXt^2 - gXX gtt)) / gXX def dXdt(t, coord, sign, gXX = gXX_interp, gtt = gtt_interp, gXt = gXt_interp): gXt_val = gXt(t, coord) gXX_val = gXX(t, coord) gtt_val = gtt(t, coord) return ((-gXt_val + sign * np.sqrt((gXt_val ** 2) - gtt_val * gXX_val)) / gXX_val).flatten()[0] rays_pos = np.empty((spatial_coords.shape[0], times.shape[0])) rays_neg = np.empty_like(rays_pos) for j, X0 in enumerate(spatial_coords): for tgt, sign in ((rays_pos, 1.0), (rays_neg, -1.0)): ret = solve_ivp(dXdt, (ray_times[0], ray_times[-1]), (X0,), method = 'RK45', t_eval = ray_times, args = (sign,), dense_output = True, events = events, rtol = 1e-6, atol = 1e-8) t, x = ret.t, ret.y[0] if len(t) < len(ray_times): x_ext = np.empty_like(ray_times) x_ext[:x.shape[0]] = x x_ext[x.shape[0]:] = x[-1] + sign * (ray_times[x.shape[0]:] - t[-1]) x = x_ext tgt[j] = x return (ray_times, rays_pos, rays_neg) def calc_null_coordinates(times, spatial_coords, u_rays, v_rays, gXX, gXt, gtt): """ Compute double-null coordinates (u, v) as functions of position and time. :param array_like times: 1D array of coordinate times at which the spacetime curvature is provided :param array_like spatial_coords: 1D array of spatial coordinates :param array_like u_rays: 1D array assigning the values of u on the initial time slice. u_rays[i] is the value of u at X=spatial_coords[i]. :param array_like v_rays: same as u_rays, but for v. :param array_like gXX: 2D array containing the values of the XX component of the spacetime metric, where X is the spatial coordinate along which the rays are traced. gXX[i, j] is the value at spacetime point (t=times[i], X=spatial_coords[j]). :param array_like gXt: same as gXX, but for the Xt component of the metric :param array_like gtt: same as gXX, but for the tt component of the metric :return: tuple containing two 2D arrays with, respectively, values of u and v as functions of t and X. u/v[i, j] is the value of u/v at t=times[i], X=spatial_coords[j]. """ _, X_of_ut, X_of_vt = calc_null_curves(times, spatial_coords, gXX, gXt, gtt) u_of_tx = np.empty((times.shape[0], spatial_coords.shape[0])) v_of_tx = np.empty_like(u_of_tx) for i, t in enumerate(times): Xu = X_of_ut[:, i] Xv = X_of_vt[:, i] u_of_tx[i] = interp.interp1d(Xu, u_rays)(spatial_coords) v_of_tx[i] = interp.interp1d(Xv, v_rays)(spatial_coords) return (u_of_tx, v_of_tx)