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tokens: of the code used here is essentially identical to the one employed by Hartlep et al. ( 2013 ). The code has been used over many years to study wave propagation in the solar interior in the presence of both sound-speed perturbations as well as flows, and was used to help improve and validate various helioseismic measurement and inversion techniques. This includes the far-side imaging technique for detecting solar active regions on the side facing away from Earth using observations from the Earth-facing side (Zhao 2007 ; Hartlep et al. 2008 ; Ilonidis et al. 2009 ); measuring the solar meridional flow in the deep interior (e.g., Hartlep et al. 2013 ; Roth et al. 2016 ); detecting sound-speed variation using time–distance helioseismology (Parchevsky et al. 2014 ) and the acoustic holography technique (Braun 2014 ; Díaz Alfaro et al. 2016 ); and studies related to magnetic flux emergence (e.g., Hartlep et al. 2011 ; Ilonidis et al. 2013 ). The code models solar acoustic oscillations in a spherical domain using the Euler equations linearized around a stationary background state, which is characterized by a background density, sound speed and acceleration due to gravity, all taken from a standard solar model. The code also takes into account the effect of mass flows on the propagation of waves. For the governing equations and more details on the code, we refer to Hartlep et al. ( 2013 ). A significant difference between how the code is used in the current study and previous works is the excitation of acoustic waves. In the Sun, turbulent flows near the photosphere act as sources for acoustic perturbations driving waves in a stochastic fashion. However, since this driving mechanism is a nonlinear process, it is lost by linearizing the governing equations. Therefore, for most previous studies, a stochastic term was added in the equations to mimic this excitation. This is not used here, however. Instead, each simulation excites and follows individual waves as described in the next section. 2.1.2. Simulation Setup In order to measure helioseismic travel times accurately, one usually needs many hours of data, for either actual solar observations or numerical simulations that are stochastically driven to mimic solar-like wave excitation. Such numerical simulations are feasible when only one or few sets of them are needed, as for instance in Hartlep et al. ( 2008 , 2013 ). However, for deriving sensitivity kernels, we need to probe many perturbations at many different depths and locations while keeping them spatially separated to avoid travel times to be shifted by multiple perturbations simultaneously. This requires many individual simulations, with only few perturbations in each, which quickly becomes infeasible. The alternative we have chosen here is to simulate not a stochastic Sun-like wavefield but excite individual waves and measure their travel times from their source location to other points on the surface. There is no stochastic noise in this