Fig. 3: Temperature extraction and evolution.

a Density profile near the interface for the isochorically heated target at two times. The solid lines show the same best-fit density profiles from Fig. 2 for 2.3 ns (red) and 4.0 ns (blue). A Bayesian sampling process was used to determine the range of profiles that accurately recreate the diffraction patterns of Fig. 2, shown here as the shaded regions. A second Bayesian process is used to evolve the 2.3 ns best-fit data to 4.0 ns, resulting in a subset of density profiles given by the dark-shaded band. b Temperature profiles inferred from the density profiles (same color scheme). The temperature profiles show a steep discontinuity at the interface, providing evidence of interfacial thermal resistance. c–e Probability density functions of the main parameters in our Bayesian analysis of the propagation of the system from 2.3 ns to 4.0 ns: thermal conductivity coefficients for (c) tungsten and (d) plastic, and (e) the thermal resistance across the interface.