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Charge collection parameterization of MALTA2, a depleted monolithic active pixel sensor

L. Fasselt, P. Behera, D. V. Berlea, D. Bortoletto, C. Buttar, T. Chembakan, V. Dao, G. Dash, S. Haberl, T. Inada, F. K. Isik, P. Jana, X. Li, L. Li, H. Pernegger, P. Riedler, W. Snoeys, C. A. Solans Sánchez, A. Swoboda, I. Turk Cakir, M. van Rijnbach, M. Vázquez Núñez, A. Vijay, J. Weick, S. Worm

Abstract

A fast simulation method is presented for a depleted monolithic active pixel sensor, which uses a data driven parameterization of the charge collection and propagation. This approach provides an efficient alternative to TCAD simulations, particularly for sensors whose proprietary process details - such as doping profiles or implant geometries - are unavailable. Data was obtained with a MALTA2 sensor fabricated in a 180 nm CMOS imaging technology on 30 μm epitaxial silicon using the MALTA beam telescope at CERN SPS. The model reproduces the measured inpixel efficiency with high accuracy and enables a realistic yet computationally lightweight analog pixel simulation. This method will be further employed in optimizing the digital sensor design for applications in high-rate particle tracking and high-granularity calorimetry.

Charge collection parameterization of MALTA2, a depleted monolithic active pixel sensor

Abstract

A fast simulation method is presented for a depleted monolithic active pixel sensor, which uses a data driven parameterization of the charge collection and propagation. This approach provides an efficient alternative to TCAD simulations, particularly for sensors whose proprietary process details - such as doping profiles or implant geometries - are unavailable. Data was obtained with a MALTA2 sensor fabricated in a 180 nm CMOS imaging technology on 30 μm epitaxial silicon using the MALTA beam telescope at CERN SPS. The model reproduces the measured inpixel efficiency with high accuracy and enables a realistic yet computationally lightweight analog pixel simulation. This method will be further employed in optimizing the digital sensor design for applications in high-rate particle tracking and high-granularity calorimetry.
Paper Structure (6 sections, 3 equations, 5 figures)

This paper contains 6 sections, 3 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Charge collection measurement
  3. Charge collection model
  4. Parametric fast simulation
  5. Data to simulation comparison
  6. Conclusion

Figures (5)

  • Figure 1: Cross-section through the center of a MALTA2 pixel on 30µm epitaxial silicon.
  • Figure 2: Data of the tracking efficiency for different in-pixel regions (a) from which the most probable value (MPV) of the charge deposition is reconstructed on a $2\times2$ pixel matrix (b).
  • Figure 3: Most probable value of the energy loss (MPV) along an X-projection in (a). Shown is the one-dimensional charge collection model (red dashed) that is convoluted with a gaussian (blue line) to parameterize the data. The $2\times2$ pixel design in (b) explains the distribution of the two-dimensional residuals in (c).
  • Figure 4: In-pixel efficiency for simulation and data at a threshold of $1400\,\mathrm{e^-}$. The simulation matches the data when considering the tracking uncertainty of the telescope $\sigma_{\mathrm{gauss}}=4.6µm$.
  • Figure 5: Simulation results (boxes) are compared to data (blue stars). The model as determined in section \ref{['sec:ChargeModel']} with $\sigma_{\mathrm{erf}}=4.3µm$ best describes the data.