## 1 Introduction  
To optimize the plasma parameters and the design of scenarios for tokamak operations, significant scientific efforts have been focused on experimental and theoretical studies of the tokamak power exhaust. One of the main challenges in this domain lays in the harsh tokamak environment for direct measurements and in simplifying the hypotheses made for the numerical simulations of plasma. In this context, synthetic diagnostics are the main tool able to confront plasma transport codes and experimental data from the full set of plasma diagnostics. Numerous studies have been conducted in the field of plasma modeling for the description, prediction, and understanding of the evolution of plasma. The most common 2D transport codes use field-aligned meshes, as in SolEdge2D-Eirene [1] and SOLPS [2]. Despite the remarkable level of development, this approach still has several problems. First of all, it is not a straightforward way to describe the complex details of the tokamak vessel and plasma-facing components (PFCs). To deal with this issue, 3D SOL codes using Monte Carlo methods can be employed, such as in EMC3-Eirene [3]. In addition, singularitiesoccur in the vicinity of X-points of the magnetic field and, more importantly, in the center of the plasma column. Therefore, it is not possible to perform simulations for the whole plasma domain, and such codes as SOLPS do not consider the center region at all. The key plasma parameters at the last closed magnetic flux surface are matched with other simulations, for example, by using the ASTRA [4] simulation. Moreover, if there is a need to change the magnetic field configuration, one should redefine the mesh, which is extremely time-consuming. Consequently, it is almost impossible to perform 2D simulations for full discharges with evolving magnetic equilibrium. Recently, a novel approach was introduced for fusion plasma modeling by using the hybridized discontinous Galerkin (HDG) method [5]. It employs non-aligned, non-structured meshes which allow us to not only precisely describe the PFCs geometry and the evolving magnetic field, but also to refine some mesh domains locally. This approach provides a better plasma description together with good time performance. The application of the HDG code led to the state-of-the-art 2D simulation of the entire discharge in the VEST tokamak from the plasma start-up to its ramp-down [6]. It also demonstrated the difference of such an approach compared with the usual steady-state ones. The plasma density in the latter case is shown to be lower than in a full discharge simulation, which cannot be covered by the commonly used codes. However, despite the promising qualitative agreement of the evolving plasma parameters with the experimental values, quantitative comparison with the integrated electron density from interferometry measurements shows discrepancies [6]. This means that the HDG code still needs more improvements and investigations, as well as benchmarking with both experiments and other existing codes. The tokamak environment with its high temperatures (of the order of \(10^{7}\)-\(10^{8}\) K) and low pressures (few Pa) usually leads to indirect measurements of macroscopic plasma parameters, which are typically compared with the outputs of the transport codes. Each measurement then needs to be interpreted, applying a set of assumptions in the physical model of a diagnostic and often using hypotheses on the plasma state and its equillibrium. For example, the phase shift of a passing laser beam can stand for the line-integrated density, supposing that electron temperature does not affect the measurement, or the intensity and the wavelength spectrum of the light can give information about density and temperature of radiating plasma species if we assume a certain model for the ionization states distribution [7], etc. Synthetic diagnostics are used to verify such relations. In addition to the evaluation of the fidelity of the imposed simplifications, it can also be employed for the benchmarking of the transport codes.