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The AstroSat mass model: Imaging and flux studies of off-axis sources with CZTI

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Abstract

The Cadmium Zinc Telluride Imager (CZTI) on AstroSat is a hard X-ray coded-aperture mask instrument with a primary field-of-view of \(4.6^\circ \times 4.6^\circ \) (FWHM). The instrument collimators become increasingly transparent at energies above \(\sim \)100 keV, making CZTI sensitive to radiation from the entire sky. While this has enabled CZTI to detect a large number of off-axis transient sources, calculating the source flux or spectrum requires knowledge of the direction and energy dependent attenuation of the radiation incident upon the detector. Here, we present a GEANT4-based mass model of CZTI and AstroSat that can be used to simulate the satellite response to the incident radiation, and to calculate an effective “response file” for converting the source counts into fluxes and spectra. We provide details of the geometry and interaction physics, and validate the model by comparing the simulations of imaging and flux studies with observations. Spectroscopic validation of the mass model is discussed in a companion paper, Chattopadhyay et al. (J. Astrophys. Astr., vol. 42 (2021) https://doi.org/10.1007/s12036-021-09718-2).

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Notes

  1. http://geant4.web.cern.ch/geant4/.

  2. https://github.com/christopherpoole/CADMesh.

  3. http://physics.nist.gov/PhysRefData/Star/Text/method.html.

  4. Note: This criteria forces our sample to consist of long GRBs only. The shortest duration GRB in the sample is \(\sim \)30 s and the longest one is \(\sim \)200 s.

References

  • Agostinelli S., Allison J., Amako K. et al. 2003, Nuclear Instrum. Methods Phys. Res. A, 506, 250

    Article  ADS  Google Scholar 

  • Allison J., Amako K., Apostolakis J. et al. 2006, IEEE Trans. Nucl. Sci., 53, 270

    Article  ADS  Google Scholar 

  • Allison J., Amako K., Apostolakis J. et al. 2016, Nuclear Instruments and Methods in Physics Research A, 835, 186

    Article  ADS  Google Scholar 

  • Antia H. M., Chitinus V. R., Katoch T. V. et al. 2013, GEANT4 simulation of LAXPC background, Tech. Report, Tata Institute of Fundamental Research (TIFR)

    Google Scholar 

  • Band D., Matteson J., Ford L. et al. 1993, APJ, 413, 281

    Article  ADS  Google Scholar 

  • Bhalerao V., Bhattacharya D., Rao A. R., Vadawale S. 2015, GRB Coordinates Network, 18422

  • Bhalerao V., Bhattacharya D., Rao A. R., Vadawale S. 2017, GRB Coordinates Network, 20412

  • Bhalerao V., Kasliwal M., Bhattacharya D. et al. 2017a, Astrophys. J., 845, https://doi.org/10.3847/1538-4357/aa81d2

  • Bhalerao V., Bhattacharya D., Vibhute A. et al. 2017b, J. Astrophys. Astr., 38, 31

  • Bhattacharya D., Dewangan G. C., Antia H. M. et al. 2016, AstroSat Handbook, https://www.iucaa.in/~astrosat/AstroSat_handbook.pdf

  • Bissaldi E., Kocevski D., Omodei N. 2018, GRB Coordinates Network, 23225, 1

    Google Scholar 

  • Bissaldi E., Meegan C. 2019, GRB Coordinates Network, 24692, 1

    Google Scholar 

  • Blackburn J. K. 1995, Astronomical Data Analysis Software and Systems IV, 77

  • Chand V., Chattopadhyay T., Oganesyan G. et al. 2019, Astrophys. J., 874, 70

    Article  ADS  Google Scholar 

  • Chattopadhyay T., Vadawale S. V., Rao A. R., Sreekumar S., Bhattacharya D. 2014, Exp. Astron., 37, 555

    Article  ADS  Google Scholar 

  • Chattopadhyay T., Vadawale S. V., Aarthy E. et al. 2019, Astrophys. J., 884, 123

    Article  ADS  Google Scholar 

  • Chattopadhyay T., Gupta S., Sharma V. et al. 2021, J. Astrophys. Astr., 42, https://doi.org/10.1007/s12036-021-09718-2

  • D’Avanzo P., Evans P. A., Kuin N. P. M. et al. 2017, GRB Coordinates Network, 22053, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2017a, GRB Coordinates Network, 20476, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2017b, GRB Coordinates Network, 21166, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2017c, GRB Coordinates Network, 22003, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2017d, GRB Coordinates Network, 22070, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2018a, GRB Coordinates Network, 22546, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2018b, GRB Coordinates Network, 23061, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2019a, GRB Coordinates Network, 24715, 1

    Google Scholar 

  • Frederiks D., Golenetskii S., Aptekar R. et al. 2019b, GRB Coordinates Network, 23782, 1

    Google Scholar 

  • Hunter J. D. 2007, Computing in Science & Engineering, 9, 90

    Article  ADS  Google Scholar 

  • Hurley K., Mitrofanov I. G., Golovin D. et al. 2017, GRB Coordinates Network, 21164, 1

    Google Scholar 

  • Hurley K., Mitrofanov I. G., Golovin D. et al. 2018, GRB Coordinates Network, 22679, 1

    Google Scholar 

  • Hurley K., Mitrofanov I. G., Golovin D. et al. 2019, GRB Coordinates Network, 23764, 1

    Google Scholar 

  • Kasliwal M., Nakar E., Singer L. et al. 2017, Science, 358, 1559

    Article  ADS  Google Scholar 

  • Kozlova A., Golenetskii S., Aptekar R. et al. 2016, GRB Coordinates Network, 19842, 1

    Google Scholar 

  • Kozlova A., Golenetskii S., Aptekar R. et al. 2017, GRB Coordinates Network, 21926, 1

    Google Scholar 

  • Kozlova A., Golenetskii S., Aptekar R. et al. 2018, GRB Coordinates Network, 22680, 1

    Google Scholar 

  • Landsman W. B. 1993, Astronomical Data Analysis Software and Systems II, 52

    Google Scholar 

  • Marcinkowski R., Xiao H., Hajdas W. 2017, GRB Coordinates Network, 20387

  • Melandri A., D’Avanzo P., Page K. L. et al. 2017, GRB Coordinates Network, 21640, 1

    Google Scholar 

  • Moss M. J., Barthelmy S. D., D’Elia V. et al. 2018, GRB Coordinates Network, 23105, 1

    Google Scholar 

  • Palit S., Anumarlapudi A., Bhalerao V. 2021, J. Astrophys. Astr., 42, https://doi.org/10.1007/s12036-021-09759-7

  • Poole C. M., Cornelius I., Trapp J. V., Langton C. M. 2012, Australas. Phys. Engg. Sci. Med., 35, 329

  • Rao A., Bhattacharya D., Bhalerao V., Vadawale S., Sreekumar, S. 2017, Curr. Sci., 113, https://doi.org/10.18520/cs/v113/i04/595-598

  • Rao A. R., Chand V., Hingar M. K. et al. 2016, APJ, 833, 86

    Article  ADS  Google Scholar 

  • Robitaille T. P., Tollerud E. J., Greenfield P. et al. 2013, A&A, 558, A33

    Article  ADS  Google Scholar 

  • Sbarufatti B., Burrows D. N., Beardmore A. P. et al. 2017, GRB Coordinates Network, 20510, 1

    Google Scholar 

  • Sharma V., Bhalerao V., Bhattacharya D., Rao A. R., Vadawale S. 2017, GRB Coordinates Network, 20389

  • Sharma Y., Marathe A., Bhalerao V. et al. 2021, J. Astrophys. Astr., 42, https://doi.org/10.1007/s12036-021-09714-6

  • Singh K. P., Tandon S. N., Agrawal P. C. et al. 2014, in Proc. SPIE Vol. 9144, Space Telescopes and Instrumentation 2014: Ultraviolet to Gamma Ray, 91441S

  • Singhal A., Srinivasan R., Bhalerao V. et al 2021, J. Astrophys. Astr., 42, https://doi.org/10.1007/s12036-021-09743-1

  • Svinkin D., Golenetskii S., Aptekar R. et al. 2016a, GRB Coordinates Network, 19476, 1

    Google Scholar 

  • Svinkin D., Golenetskii S., Aptekar R. et al. 2016b, GRB Coordinates Network, 19477, 1

    Google Scholar 

  • Svinkin D., Golenetskii S., Aptekar R. et al. 2016c, GRB Coordinates Network, 19727, 1

    Google Scholar 

  • Svinkin D., Golenetskii S., Aptekar R. et al. 2017, GRB Coordinates Network, 21679, 1

    Google Scholar 

  • Svinkin D., Golenetskii S., Aptekar R. et al. 2018, GRB Coordinates Network, 23128, 1

    Google Scholar 

  • Troja E., D’Ai A., D’Elia V. et al. 2018, GRB Coordinates Network, 22532, 1

    Google Scholar 

  • Tsvetkova A., Golenetskii S., Aptekar R. et al. 2016a, GRB Coordinates Network, 19244, 1

    Google Scholar 

  • Tsvetkova A., Golenetskii S., Aptekar R. et al. 2016b, GRB Coordinates Network, 19511, 1

    Google Scholar 

  • Tsvetkova A., Golenetskii S., Aptekar R. et al. 2017, GRB Coordinates Network, 20806, 1

    Google Scholar 

  • Tsvetkova A., Golenetskii S., Aptekar R. et al. 2018a, GRB Coordinates Network, 22513, 1

    Google Scholar 

  • Tsvetkova A., Golenetskii S., Aptekar R. et al. 2018b, GRB Coordinates Network, 23254, 1

    Google Scholar 

  • Tsvetkova A., Golenetskii S., Aptekar R. et al. 2019, GRB Coordinates Network, 24652, 1

    Google Scholar 

  • Ukwatta T. N., Beardmore A. P., Evans P. A. et al. 2016, GRB Coordinates Network, 19502, 1

    Google Scholar 

  • Vadawale S., Chattopadhyay T., Mithun N. et al. 2018, Nature Astron., 2, 50

    Article  ADS  Google Scholar 

  • Vadawale S. V., Chattopadhyay T., Rao A. R. et al. 2015, A&A, 578, A73

    Article  ADS  Google Scholar 

  • van der Walt S., Colbert S. C., Varoquaux G. 2011, Computing in Science & Engineering, 13(2), 22

    Article  Google Scholar 

  • Veres P., Meegan C., Mailyan B. 2018, GRB Coordinates Network, 23053, 1

    Google Scholar 

  • von Kienlin A. 2019, GRB Coordinates Network, 24596, 1

    Google Scholar 

  • von Kienlin A., Meegan C. A., Paciesas W. S. et al. 2020, APJ, 893, 46

    Article  ADS  Google Scholar 

  • Wanderman D., Piran T. 2010, MNRAS, 406, 1944

    ADS  Google Scholar 

  • Wanderman D., Piran T. 2015, MNRAS, 448, 3026

    Article  ADS  Google Scholar 

Download references

Acknowledgements

CZT–Imager is built by a consortium of Institutes across India. The Tata Institute of Fundamental Research, Mumbai, led the effort with instrument design and development. Vikram Sarabhai Space Centre, Thiruvananthapuram provided the electronic design, assembly and testing. ISRO Satellite Centre (ISAC), Bengaluru provided the mechanical design, quality consultation and project management. The Inter University Centre for Astronomy and Astrophysics (IUCAA), Pune did the Coded Mask design, instrument calibration, and Payload Operation Centre. Space Application Centre (SAC) at Ahmedabad provided the analysis software. Physical Research Laboratory (PRL) Ahmedabad, provided the polarisation detection algorithm and ground calibration. A vast number of industries participated in the fabrication and the University sector pitched in by participating in the test and evaluation of the payload. The Indian Space Research Organisation funded, managed and facilitated the project. We thank the satellite and instrument teams for sharing their design details, and engineers at ISAC, ISITE, ISRO for providing CAD files that could be used in the mass model. In particular, we thank Prof. Shyam Tandon (IUCAA, Pune), Prof. H.M. Anitia (TIFR, Mumbai), Mr. Harshit Shah (TIFR, Mumbai), and Mr. Nagabhushana S. (IIA, Bangalore) for their assistance. We thank Mr. Dhanraj Borgaonkar (IUCAA, Pune) for the help in profiling the mass model. We thank Gaurav Waratkar (IIT Bombay) and Vedant Shenoy (IIT Bombay) for assisting in the data analysis. We acknowledge the use of Vikram-100 HPC at the Physical Research Laboratory (PRL), Ahmedabad and Pegasus HPC at the Inter University Centre for Astronomy and Astrophysics (IUCAA), Pune. This work utilised various software including Python, AstroPy (Robitaille et al. 2013), NumPy (van der Walt et al 2011), Matplotlib (Hunter 2007), IDL Astrolib (Landsman 1993), FTOOLS (Blackburn 1995), C, and C++.

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Correspondence to Varun Bhalerao.

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This article is part of the Special Issue on "AstroSat: Five Years in Orbit".

Appendices

Appendices

1.1 Appendix A: Visual impact of residual Poisson noise

For a few GRBs, we see that the scatter plots of module-wise observed versus simulated counts show a good correlation, but the DPHs are visually discrepant. A key factor in this is Poisson noise present in the observed data. We illustrate this with the example of GRB 160607A. In Fig. A1, the upper left and right panels show the observed and simulated DPH for the GRB. These DPHs appear quite distinct. However, Fig. A2 shows that there is a modest correlation between the observed and simulated module-wise count rates. In particular, the modules with high simulated counts (\(\gtrsim \)25) also have high observed counts (\(\gtrsim \)40).

Figure A1
figure 9

Upper left: Background-subtracted source DPH for GRB 160607A. Lower left: Simulated DPH including a residual Poisson noise component. For both these panels, the colour bar ranges from first to 99th percentile values. Upper right: Simulated mass model DPH, with the maximum set at 99th percentile value. Lower right: Simulated Poisson background noise, with the mean value subtracted. The range of the colour bar is the actual range for this residual Poisson noise.

Figure A2
figure 10

The observed and simulated module-wise count rates of GRB 160607 show a reasonable correlation. The best-fit line gives a scaling factor of 1.3.

The key cause of this visual discrepancy is residual Poisson noise. For all of our GRBs, source DPH is obtained by creating a DPH for the GRB interval and subtracting a background DPH estimated from pre– and post–GRB intervals. These intervals are selected to be much longer than the GRB, and the count rates are scaled to the GRB duration to suppress uncertainty in the estimate of the background. However, this removes only the mean background from the actual GRB data, leaving residual noise.

To demonstrate this, we create a simulated background DPH using a Poisson distribution with the expected background count rate. We then subtract the mean from this DPH to leave only the Poisson-induced noise (Fig. A1, lower right panel). Adding this residual noise component to the simulation results in the DPH shown in the lower left panel: the prominent contrast from the simulation has been lost due to the high variations added by the residual noise.

1.2 Appendix B: Comparisons for the full GRB sample

In Sections 5.3 and 5.4 we have discussed the comparisons between the observed and simulated data for eight selected GRBs. Here, we discuss twenty more GRBs that were studied in this work.

The observed and simulated DPHs of the on-axis GRB 160325A show good agreement, including vertical and horizontal patterns caused by shadows of the collimators (Fig. B1(a)). The DPHs for GRB 170726A, located just outside the primary field of view, is more discrepant: but in reasonable agreement in terms of counts per detector (Fig. B1(b)). In Section 5.3 we had pointed out that the observed DPH of GRB 170527A shows two bright spots caused due to scattering from the alpha detector holders (Fig. 6(d)), an effect we could not replicate in our simulations. A similar effect is seen at the bottom of the observed DPH for GRB 171010A which is incident from \(\phi =242^\circ \) (Fig. 7(c)), GRB 180605A with \(\phi =277^\circ \) (Fig. B1(d)), GRB 180914A with \(\phi =217^\circ \) (Fig. B2(a)), and GRB 180427A with \(\phi =251^\circ \) (Fig. B2(b)).

Figure B1
figure 11

(a)–(d) Observed and simulated DPHs for GRBs incident from above the detector plane, \(\theta \le 60^\circ \). Details are as in Fig. 6.

Figure B2
figure 12

(a)–(d) Observed and simulated DPHs for GRBs incident from above the detector plane, \(\theta \le 60^\circ \). Details are as in Fig. 6.

Figures B3 and B4 compare the observed and simulated DPHs for GRBs incident at oblique angles, \(60^\circ < \theta \le 120^\circ \). The observed DPHs are relatively featureless here, owing to the oblique angle of incidence. In Section 5.3, we discussed GRB 170511A (Fig. 7(b)) as an example of how the edge pixels of a quadrant can get significantly higher counts in such oblique cases: an effect slightly overestimated in our simulations. This effect is also seen at the bottom edges of GRB 160106A (Fig. B4(b)), and the top edge of GRB 160530A (Fig. B3(c)). Even the visually discrepant GRB 171027A (Fig. B3(a)) shows a good correlation in the module-wise count rates, with slope close to unity. Such visual discrepancy is discussed in Appendix A.

Figure B5 shows comparisons for GRBs incident from below the focal plane (\(\theta > 120^\circ \)). Here we see greater discrepancies between observations and simulations. This is an unsurprising effect, as the satellite body has not been modelled very accurately. As discussed in Section 5.3, a common discrepancy seen here is the presence of “hotspots” in the simulation: a certain region of the DPH is disproportionately brighter than the rest. Such an effect is seen in the top right modules of GRB 170614A (Fig. B5(b)) and two detector modules along the top row of GRB 190530A (Fig. B5(c)). There is still broad agreement in the observations and simulations: the bright lower edge, right side, and middle “spike” in the simulations of GRB 170921B can be discerned in the observed data (Fig. B5(a)). Overall, it appears as if the observed DPHs are “blurred” versions of the simulations, the sharper simulated DPHs are likely an artefact of our choice of clumping several satellite components into compact boxes and sheets.

Figure B3
figure 13

(a)–(d) Observed and simulated DPHs for GRBs incident at oblique angles, \(60^\circ < \theta \le 120^\circ \). Details are as in Fig. 6.

Figure B4
figure 14

(a)–(d) Observed and simulated DPHs for GRBs incident at oblique angles, \(60^\circ < \theta \le 120^\circ \). Details are as in Fig. 6.

Figure B5
figure 15

(a)–(d) Observed and simulated DPHs for GRBs incident from below the detector plane, \(\theta > 120^\circ \). Details are as in Fig. 6.

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Mate, S., Chattopadhyay, T., Bhalerao, V. et al. The AstroSat mass model: Imaging and flux studies of off-axis sources with CZTI. J Astrophys Astron 42, 93 (2021). https://doi.org/10.1007/s12036-021-09763-x

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