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Abbott, T. M. C., Abdalla, F. B., Allam, S., et al. 2018, ApJS, 239, 18

Ahumada, R., Prieto, C. A., Almeida, A., et al. 2020, ApJS, 249, 3

Aihara, H., Arimoto, N., Armstrong, R., et al. 2018a, PASJ, 70, S4

Aihara, H., Armstrong, R., Bickerton, S., et al. 2018b, PASJ, 70, S8

Aihara, H., AlSayyad, Y., Ando, M., et al. 2019, PASJ, 71, 114

Akeson, R., Armus, L., Bachelet, E., et al. 2019, ArXiv e-prints [arXiv:1902.05569]

Arnouts, S., Moscardini, L., Vanzella, E., et al. 2002, MNRAS, 329, 355

Baldry, I. K., Liske, J., Brown, M. J. I., et al. 2018, MNRAS, 474, 3875

Beck, R., Dobos, L., Budavári, T., Szalay, A. S., & Csabai, I. 2016, MNRAS, 460, 1371

Benítez, N. 2000, ApJ, 536, 571

Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393

Bertin, E., Mellier, Y., Radovich, M., et al. 2002, ASP Conf. Ser., 281, 228

Bohlin, R. C., Colina, L., & Finley, D. S. 1995, AJ, 110, 1316

Bosch, J., Armstrong, R., Bickerton, S., et al. 2018, PASJ, 70, S5

Boulade, O., Charlot, X., Abbon, P., et al. 2003, SPIE Conf. Ser., 4841, 72

Bradshaw, E. J., Almaini, O., Hartley, W. G., et al. 2013, MNRAS, 433, 194

Brammer, G. B., van Dokkum, P. G., & Coppi, P. 2008, ApJ, 686, 1503

Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000

Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682

Chabrier, G., & Baraffe, I. 2000, ARA&A, 38, 337

Cheng, C., Huang, J.-S., Willmer, C. N. A., et al. 2021, ApJS, 256, 4

Cohen, J. G., Hogg, D. W., Blandford, R., et al. 2000, ApJ, 538, 29

Coupon, J., Czakon, N., Bosch, J., et al. 2018, PASJ, 70, S7

Dalton, G. B., Caldwell, M., Ward, A. K., et al. 2006, SPIE Conf. Ser., 6269, 62690X

Dawid, A. P. 1984, J. Roy. Stat. Soc. Ser. A (General), 147, 278

D'Isanto, A., & Polsterer, K. L. 2018, A&A, 609, A111

Drinkwater, M. J., Byrne, Z. J., Blake, C., et al. 2018, MNRAS, 474, 4151

Drlica-Wagner, A., Sevilla-Noarbe, I., Rykoff, E. S., et al. 2018, ApJS, 235, 33

Emerson, J. P., Sutherland, W. J., McPherson, A. M., et al. 2004, The Messenger, 117, 27

Euclid Collaboration (Desprez, G., et al.) 2020, A&A, 644, A31

Gaia Collaboration (Brown, et al.) 2016a, A&A, 595, A2

Gaia Collaboration (Prusti, T., et al.) 2016b, A&A, 595, A1

Galametz, A., Saglia, R., Paltani, S., Apostolakos, N., & Dubath, P. 2017, A&A, 598, A20

Garilli, B., McLure, R., Pentericci, L., et al. 2021, A&A, 647, A150

Golob, A., Sawicki, M., Goulding, A. D., & Coupon, J. 2021, MNRAS, 503, 4136

Grogin, N. A., Kocevski, D. D., Faber, S. M., et al. 2011, ApJS, 197, 35

Gwyn, S. D. J. 2008, PASP, 120, 212

Halevi, G., Goulding, A., Greene, J., et al. 2019, ApJ, 885, L3

Harikane, Y., Ono, Y., Ouchi, M., et al. 2022, ApJS, 259, 20

Hartley, W. G., Choi, A., Amon, A., et al. 2022, MNRAS, 509, 3547

Hildebrandt, H., Erben, T., Kuijken, K., et al. 2012, MNRAS, 421, 2355

Hoaglin, D. C., Mosteller, F., & Tukey, J. W. 1983, Understanding Robust and Exploratory Data Analysis (New York: Wiley)

Huang, Y.-J., Urata, Y., Huang, K., et al. 2020, ApJ, 897, 69

Hudelot, P., Cuillandre, J. C., Withington, K., et al. 2012, VizieR Online Data Catalog: II/317

Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841

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Ilbert, O., McCracken, H. J., Le Fèvre, O., et al. 2013, A&A, 556, A55

Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111

Iwata, I., Sawicki, M., Inoue, A. K., et al. 2022, MNRAS, 509, 1820

Iyer, K. G., Gawiser, E., Faber, S. M., et al. 2019, ApJ, 879, 116

Jarvis, M. J., Bonfield, D. G., Bruce, V. A., et al. 2013, MNRAS, 428, 1281

Kawanomoto, S., Uraguchi, F., Komiyama, Y., et al. 2018, PASJ, 70, 66

Kennicutt, Robert C., J. 1998, ARA&A, 36, 189

Kron, R. G. 1980, ApJS, 43, 305

Laigle, C., McCracken, H. J., Ilbert, O., et al. 2016, ApJS, 224, 24

Lang, D., Hogg, D. W., & Mykytyn, D. 2016, The Tractor: Probabilistic Astronomical Source Detection and Measurement Astrophysics Source Code Library, [record ascl:1604.008]

Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, ArXiv e-prints [arXiv:1110.3193]

Le Fèvre, O., Cassata, P., Cucciati, O., et al. 2013, A&A, 559, A14

Le Fèvre, O., Tasca, L. A. M., Cassata, P., et al. 2015, A&A, 576, A79

Lee, K.-G., Krolewski, A., White, M., et al. 2018, ApJS, 237, 31

Masters, D. C., Capak, P., Stern, D., et al. 2015, ApJ, 813, 53

Masters, D. C., Stern, D. K., Cohen, J. G., et al. 2019, ApJ, 877, 81

McCracken, H. J., Milvang-Jensen, B., Dunlop, J., et al. 2012, A&A, 544, A156

McLure, R. J., Pearce, H. J., Dunlop, J. S., et al. 2013, MNRAS, 428, 1088

Miyazaki, S., Komiyama, Y., Kawanomoto, S., et al. 2018, PASJ, 70, S1

Momcheva, I. G., Brammer, G. B., van Dokkum, P. G., et al. 2016, ApJS, 225, 27

Moutard, T., Arnouts, S., Ilbert, O., et al. 2016, A&A, 590, A102

Moutard, T., Sawicki, M., Arnouts, S., et al. 2020, MNRAS, 494, 1894

Newman, J. A., Cooper, M. C., Davis, M., et al. 2013, ApJS, 208, 5

Pacifici, C., Kassin, S. A., Weiner, B. J., et al. 2016, ApJ, 832, 79

Paillassa, M., Bertin, E., & Bouy, H. 2020, A&A, 634, A48

Papovich, C., Dickinson, M., & Ferguson, H. C. 2001, ApJ, 559, 620

Pasquet, J., Bertin, E., Treyer, M., Arnouts, S., & Fouchez, D. 2019, A&A, 621, A26

Pickles, A. J. 1998, PASP, 110, 863

Planck Collaboration XIII. 2016, A&A, 594, A13

Polletta, M., Tajer, M., Maraschi, L., et al. 2007, ApJ, 663, 81

Polsterer, K. L., D'Isanto, A., & Gieseke, F. 2016, ArXiv e-prints [arXiv:1608.08016]

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Sawicki, M. J., Lin, H., & Yee, H. K. C. 1997, AJ, 113, 1

Sawicki, M., Arnouts, S., Huang, J., et al. 2019, MNRAS, 489, 5202

Schechter, P. 1976, ApJ, 203, 297

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Scodeggio, M., Guzzo, L., Garilli, B., et al. 2018, A&A, 609, A84

Scoville, N., Aussel, H., Brusa, M., et al. 2007, ApJS, 172, 1

Skelton, R. E., Whitaker, K. E., Momcheva, I. G., et al. 2014, ApJS, 214, 24

Szalay, A. S., Connolly, A. J., & Szokoly, G. P. 1999, AJ, 117, 68

Tanaka, M., Coupon, J., Hsieh, B.-C., et al. 2018, PASJ, 70, S9

Taniguchi, Y., Scoville, N., Murayama, T., et al. 2007, ApJS, 172, 9

Taniguchi, Y., Kajisawa, M., Kobayashi, M. A. R., et al. 2015, PASJ, 67, 104

Thibert, N., Sawicki, M., Goulding, A., et al. 2021, RNAAS, 5, 144

Weaver, J. R., Kauffmann, O. B., Ilbert, O., et al. 2022, ApJS, 258, 11

Zucca, E., Ilbert, O., Bardelli, S., et al. 2006, A&A, 455, 879
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Abazajian, K., Adelman-McCarthy, J. K., Agüeros, M. A., et al. 2004, AJ, 128, 502

Abbott, T. M. C., Abdalla, F. B., Allam, S., et al. 2018, ApJS, 239, 18

Ahumada, R., Prieto, C. A., Almeida, A., et al. 2020, ApJS, 249, 3

Aihara, H., Arimoto, N., Armstrong, R., et al. 2018a, PASJ, 70, S4

Aihara, H., Armstrong, R., Bickerton, S., et al. 2018b, PASJ, 70, S8

Aihara, H., AlSayyad, Y., Ando, M., et al. 2019, PASJ, 71, 114

Akeson, R., Armus, L., Bachelet, E., et al. 2019, ArXiv e-prints [arXiv:1902.05569]

Arnouts, S., Moscardini, L., Vanzella, E., et al. 2002, MNRAS, 329, 355

Baldry, I. K., Liske, J., Brown, M. J. I., et al. 2018, MNRAS, 474, 3875

Beck, R., Dobos, L., Budavári, T., Szalay, A. S., & Csabai, I. 2016, MNRAS, 460, 1371

Benítez, N. 2000, ApJ, 536, 571

Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393

Bertin, E., Mellier, Y., Radovich, M., et al. 2002, ASP Conf. Ser., 281, 228

Bohlin, R. C., Colina, L., & Finley, D. S. 1995, AJ, 110, 1316

Bosch, J., Armstrong, R., Bickerton, S., et al. 2018, PASJ, 70, S5

Boulade, O., Charlot, X., Abbon, P., et al. 2003, SPIE Conf. Ser., 4841, 72

Bradshaw, E. J., Almaini, O., Hartley, W. G., et al. 2013, MNRAS, 433, 194

Brammer, G. B., van Dokkum, P. G., & Coppi, P. 2008, ApJ, 686, 1503

Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000

Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682

Chabrier, G., & Baraffe, I. 2000, ARA&A, 38, 337

Cheng, C., Huang, J.-S., Willmer, C. N. A., et al. 2021, ApJS, 256, 4

Cohen, J. G., Hogg, D. W., Blandford, R., et al. 2000, ApJ, 538, 29

Coupon, J., Czakon, N., Bosch, J., et al. 2018, PASJ, 70, S7

Dalton, G. B., Caldwell, M., Ward, A. K., et al. 2006, SPIE Conf. Ser., 6269, 62690X

Dawid, A. P. 1984, J. Roy. Stat. Soc. Ser. A (General), 147, 278

D'Isanto, A., & Polsterer, K. L. 2018, A&A, 609, A111

Drinkwater, M. J., Byrne, Z. J., Blake, C., et al. 2018, MNRAS, 474, 4151

Drlica-Wagner, A., Sevilla-Noarbe, I., Rykoff, E. S., et al. 2018, ApJS, 235, 33

Emerson, J. P., Sutherland, W. J., McPherson, A. M., et al. 2004, The Messenger, 117, 27

Euclid Collaboration (Desprez, G., et al.) 2020, A&A, 644, A31

Gaia Collaboration (Brown, et al.) 2016a, A&A, 595, A2

Gaia Collaboration (Prusti, T., et al.) 2016b, A&A, 595, A1

Galametz, A., Saglia, R., Paltani, S., Apostolakos, N., & Dubath, P. 2017, A&A, 598, A20

Garilli, B., McLure, R., Pentericci, L., et al. 2021, A&A, 647, A150

Golob, A., Sawicki, M., Goulding, A. D., & Coupon, J. 2021, MNRAS, 503, 4136

Grogin, N. A., Kocevski, D. D., Faber, S. M., et al. 2011, ApJS, 197, 35

Gwyn, S. D. J. 2008, PASP, 120, 212

Halevi, G., Goulding, A., Greene, J., et al. 2019, ApJ, 885, L3

Harikane, Y., Ono, Y., Ouchi, M., et al. 2022, ApJS, 259, 20

Hartley, W. G., Choi, A., Amon, A., et al. 2022, MNRAS, 509, 3547

Hildebrandt, H., Erben, T., Kuijken, K., et al. 2012, MNRAS, 421, 2355

Hoaglin, D. C., Mosteller, F., & Tukey, J. W. 1983, Understanding Robust and Exploratory Data Analysis (New York: Wiley)

Huang, Y.-J., Urata, Y., Huang, K., et al. 2020, ApJ, 897, 69

Hudelot, P., Cuillandre, J. C., Withington, K., et al. 2012, VizieR Online Data Catalog: II/317

Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841

Ilbert, O., Capak, P., Salvato, M., et al. 2009, ApJ, 690, 1236

Ilbert, O., McCracken, H. J., Le Fèvre, O., et al. 2013, A&A, 556, A55

Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111

Iwata, I., Sawicki, M., Inoue, A. K., et al. 2022, MNRAS, 509, 1820

Iyer, K. G., Gawiser, E., Faber, S. M., et al. 2019, ApJ, 879, 116

Jarvis, M. J., Bonfield, D. G., Bruce, V. A., et al. 2013, MNRAS, 428, 1281

Kawanomoto, S., Uraguchi, F., Komiyama, Y., et al. 2018, PASJ, 70, 66

Kennicutt, Robert C., J. 1998, ARA&A, 36, 189

Kron, R. G. 1980, ApJS, 43, 305

Laigle, C., McCracken, H. J., Ilbert, O., et al. 2016, ApJS, 224, 24

Lang, D., Hogg, D. W., & Mykytyn, D. 2016, The Tractor: Probabilistic Astronomical Source Detection and Measurement Astrophysics Source Code Library, [record ascl:1604.008]

Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, ArXiv e-prints [arXiv:1110.3193]

Le Fèvre, O., Cassata, P., Cucciati, O., et al. 2013, A&A, 559, A14

Le Fèvre, O., Tasca, L. A. M., Cassata, P., et al. 2015, A&A, 576, A79

Lee, K.-G., Krolewski, A., White, M., et al. 2018, ApJS, 237, 31

Masters, D. C., Capak, P., Stern, D., et al. 2015, ApJ, 813, 53

Masters, D. C., Stern, D. K., Cohen, J. G., et al. 2019, ApJ, 877, 81

McCracken, H. J., Milvang-Jensen, B., Dunlop, J., et al. 2012, A&A, 544, A156

McLure, R. J., Pearce, H. J., Dunlop, J. S., et al. 2013, MNRAS, 428, 1088

Miyazaki, S., Komiyama, Y., Kawanomoto, S., et al. 2018, PASJ, 70, S1

Momcheva, I. G., Brammer, G. B., van Dokkum, P. G., et al. 2016, ApJS, 225, 27

Moutard, T., Arnouts, S., Ilbert, O., et al. 2016, A&A, 590, A102

Moutard, T., Sawicki, M., Arnouts, S., et al. 2020, MNRAS, 494, 1894

Newman, J. A., Cooper, M. C., Davis, M., et al. 2013, ApJS, 208, 5

Pacifici, C., Kassin, S. A., Weiner, B. J., et al. 2016, ApJ, 832, 79

Paillassa, M., Bertin, E., & Bouy, H. 2020, A&A, 634, A48

Papovich, C., Dickinson, M., & Ferguson, H. C. 2001, ApJ, 559, 620

Pasquet, J., Bertin, E., Treyer, M., Arnouts, S., & Fouchez, D. 2019, A&A, 621, A26

Pickles, A. J. 1998, PASP, 110, 863

Planck Collaboration XIII. 2016, A&A, 594, A13

Polletta, M., Tajer, M., Maraschi, L., et al. 2007, ApJ, 663, 81

Polsterer, K. L., D'Isanto, A., & Gieseke, F. 2016, ArXiv e-prints [arXiv:1608.08016]

Prevot, M. L., Lequeux, J., Maurice, E., Prevot, L., & Rocca-Volmerange, B. 1984, A&A, 132, 389

Salvato, M., Hasinger, G., Ilbert, O., et al. 2009, ApJ, 690, 1250

Salvato, M., Ilbert, O., Hasinger, G., et al. 2011, ApJ, 742, 61

Sawicki, M., & Yee, H. K. C. 1998, AJ, 115, 1329

Sawicki, M. J., Lin, H., & Yee, H. K. C. 1997, AJ, 113, 1

Sawicki, M., Arnouts, S., Huang, J., et al. 2019, MNRAS, 489, 5202

Schechter, P. 1976, ApJ, 203, 297

Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525

Scodeggio, M., Guzzo, L., Garilli, B., et al. 2018, A&A, 609, A84

Scoville, N., Aussel, H., Brusa, M., et al. 2007, ApJS, 172, 1

Skelton, R. E., Whitaker, K. E., Momcheva, I. G., et al. 2014, ApJS, 214, 24

Szalay, A. S., Connolly, A. J., & Szokoly, G. P. 1999, AJ, 117, 68

Tanaka, M., Coupon, J., Hsieh, B.-C., et al. 2018, PASJ, 70, S9

Taniguchi, Y., Scoville, N., Murayama, T., et al. 2007, ApJS, 172, 9

Taniguchi, Y., Kajisawa, M., Kobayashi, M. A. R., et al. 2015, PASJ, 67, 104

Thibert, N., Sawicki, M., Goulding, A., et al. 2021, RNAAS, 5, 144

Weaver, J. R., Kauffmann, O. B., Ilbert, O., et al. 2022, ApJS, 258, 11

Zucca, E., Ilbert, O., Bardelli, S., et al. 2006, A&A, 455, 879
## Appendix A: HSC-SSP PDR2 photometry

We compare here the photometry we obtain with the `hscPipe` on the HSC bands to the HSC PDR2 photometry. The comparison is made in the ultraDeep region of the E-COSMOS field. This field is one of the deepest in the *U*-band and is the only field observed across all bands. Thus it could be the most sensitive to any problem caused by considering the extra bands in the `hscPipe` source detection phase and the forced extraction.

Figure A.1 shows the comparison of the magnitudes in the *grizy* bands. The distributions show nearly no deviations and an extremely tight scatter between our photometry and the HSC PDR2 one, down to the faintest magnitudes. As the data from which the photometry is extracted are exactly the same in both cases, the few differences can only be due to the addition of the CLAUDS and NIR bands in the source detection process. The effect can be the new detection of close-by sources or deblending of new sources, resulting in a slightly different allocation of the flux in the two versions of the photometry.

## Appendix B: COSMOS2020 SExtractor photometry

The `Classic` configuration of COSMOS2020 photometry extraction is extremely similar to our `SExtractor` configuration. Indeed, the same code is applied to the same data. However, there are a few differences in the settings of the two extractions, for instance, the bands on which the detection is made. `SExtracor` uses mostly the bluest bands, *Ugrizy* (+$K_s$ when available), for the detection, whereas `Classic` uses the reddest bands, *izYJHKs*, to build its detection map. Another difference is the step of PSF homogenization of the images that is made with

<figure><img src="image_19.png" /><figcaption>**Fig. A.1.** Comparison between our `hscPipe` photometry and that of HSC PDR2. The dashed lines encompass 68% of the distributions.</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>**Fig. B.1.** Comparison of COSMOS2020 `Classic` and `SExtractor` 2" aperture magnitudes.</figcaption></figure>

the COSMOS2020 `Classic` methods but not our `SExtractor` one.

A comparison of the obtained photometry in both cases, like the one presented in Fig. B.1, shows the differences induced by these configuration choices. The figure presents the comparison of the 2" photometry between `Classic` and `SExtractor`. As expected, the relation between the two photometry catalogs is tight. However, we can observe strong biases, as large as ~0.07mag (e.g., for the *z* or the *Y* bands). This effect is due to PSF homogenization.

## Appendix C: SExtractor-hscPipe 2" photometry

The 2" aperture photometry is the one used in both configurations to compute photometric redshifts. In Fig. C.1, we present the direct comparison of the 2" aperture photometry from `SExtractor` and `hscPipe`. We note a tight relation between the measurements obtained with these two codes; however, an
# Appendix A: HSC-SSP PDR2 photometry

We compare here the photometry we obtain with the *hscPipe* on the HSC bands to the HSC PDR2 photometry. The comparison is made in the ultraDeep region of the E-COSMOS field. This field is one of the deepest in the *U*-band and is the only field observed across all bands. Thus it could be the most sensitive to any problem caused by considering the extra bands in the *hscPipe* source detection phase and the forced extraction.

Figure A.1 shows the comparison of the magnitudes in the *grizy* bands. The distributions show nearly no deviations and an extremely tight scatter between our photometry and the HSC PDR2 one, down to the faintest magnitudes. As the data from which the photometry is extracted are exactly the same in both cases, the few differences can only be due to the addition of the CLAUDS and NIR bands in the source detection process. The effect can be the new detection of close-by sources or deblending of new sources, resulting in a slightly different allocation of the flux in the two versions of the photometry.

# Appendix B: COSMOS2020 SExtractor photometry

The *Classic* configuration of COSMOS2020 photometry extraction is extremely similar to our *SExtractor* configuration. Indeed, the same code is applied to the same data. However, there are a few differences in the settings of the two extractions, for instance, the bands on which the detection is made. *SExtracor* uses mostly the bluest bands, *Ugrizy* (+*K*<sub>s</sub> when available), for the detection, whereas *Classic* uses the reddest bands, izYJHK<sub>s</sub>, to build its detection map. Another difference is the step of PSF homogenization of the images that is made with

<figure><img src="image_19.png" /><figcaption>**Fig. A.1.** Comparison between our *hscPipe* photometry and that of HSC PDR2. The dashed lines encompass 68% of the distributions.</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>**Fig. B.1.** Comparison of COSMOS2020 *Classic* and *SExtractor* 2" aperture magnitudes.</figcaption></figure>

the COSMOS2020 *Classic* methods but not our *SExtractor* one.

A comparison of the obtained photometry in both cases, like the one presented in Fig. B.1, shows the differences induced by these configuration choices. The figure presents the comparison of the 2" photometry between *Classic* and *SExtractor*. As expected, the relation between the two photometry catalogs is tight. However, we can observe strong biases, as large as ~0.07mag (e.g., for the *z* or the *Y* bands). This effect is due to PSF homogenization.

# Appendix C: SExtractor-hscPipe 2" photometry

The 2" aperture photometry is the one used in both configurations to compute photometric redshifts. In Fig. C.1, we present the direct comparison of the 2" aperture photometry from *SExtractor* and *hscPipe*. We note a tight relation between the measurements obtained with these two codes; however, an
<figure><img src="image_21.png" /><figcaption>**Fig. C.1.** Comparison of SExtractor and the hscPipe 2" aperture magnitudes.</figcaption></figure>

asymmetric scatter is present. This asymmetry seems to indicate that the hscPipe fluxes are lower than the SExtractor ones, and this effect is stronger for fainter sources. As these sources are more sensitive to background noise, we interpret the increase in asymmetry toward fainter magnitudes as a sign of stronger subtraction of the background by hscPipe compared to SExtractor. The same conclusion was reached when analyzing Fig. 5, 4 and 7 in Sect. 3.3.

## Appendix D: Phosphoros results on SExtractor photometry

Throughout the paper, the results that are presented are those of Phosphoros/hscPipe and Le Phare/SExtractor. This choice makes it difficult to attribute the differences observed in the photo-zs to the codes or to the photometry. To address this problem, we apply here Phosphoros to the SExtractor photometry to create a version of the photo-zs for which only

the photo-z codes differ. The configuration used to compute these photo-zs is the same as that presented in Sect. 4.1. We use SExtractor 2" aperture photometry uncorrected for galactic extinction, that we fit with the templates, extinction law, and priors described in Sect. 4.1. As a result, PDZs are produced, from which the point estimates (median) are computed.

Figure D.1 presents a comparison of the results of SExtractor/Phosphoros (middle panels) with both hscPipe/Phosphoros (top panels) and SExtractor/Le Phare (bottom panels). In all three cases, *Ugrizy* photo-zs are compared with the spectroscopic sample. In these plots, we can see that the two sets of photo-zs computed from the SExtractor photometry have the same quality when comparing the scatter and the outlier fractions. The scatter from the Phosphoros results is still larger in the bright bins, whereas for the fainter sources the Phosphoros results present a better scatter and outlier fraction than Le Phare photo-zs. This is probably due to the choices in the priors applied by both codes.

These results show that the majority of the differences observed between the photo-zs presented in this work are due to the differences in photometry. Outside of the effect of the priors, there are a few differences between Phosphoros and Le Phare photo-zs, which is expected due to the strong similarities between the two template-fitting codes. All these comparisons thus validate that Phosphoros is able to provide sensible results and is ready to be used by the community.

## Appendix E: Description of the released catalogs

The current release (Sect. 5) consists of a set of catalogs for the four HSC-CLAUDS regions. Several versions are available depending on the adopted photometry (based on the HSC pipeline (Sect. 3.1) or SExtractor run (Sect. 3.2)), the photometric code used (Phosphoros (Sect. 4.1) or Le Phare (Sect. 4.2)) and the number of photometric bands considered for the photometric redshift runs (*Ugrizy* and all-bands). Only subregions in the XMM-LSS and E-COSMOS fields are covered with the near-infrared VISTA imaging.

The description of the catalog outputs is given in Tab E.1 for the SExtractor -Le Phare catalogs and in Tab E.2 for the hscPipe -Phosphoros catalogs<fnref n="9" />.

As the footprints of the different surveys are different, the keyword FLAG_FIELD_BINARY allows the user to restrict the data to a specific dataset by combining its 7 boolean elements (described in Tab E.1). A version defined with a single integer is also available (FLAG_FIELD for Le Phare catalogs). To guarantee the selection of clean objects, the flags MASK and ST_TRAIL must be set to 0 (for SExtractor catalogs) or ISOUTSIDEMASK to "True" (for hscPipe catalogs).

All the catalogs include a stellar classification based on $\chi^2$ estimates between the Pickles stellar templates (Pickles 1998) and the galaxy templates. If the sources are compact and better fitted by a stellar template they are flagged as stars (OBJ_TYPE=2 or ISSTAR=True). In addition the Le Phare code also performs a classification using a QSO library (Salvato et al. 2011). If the sources are compact and better fitted by a QSO template, they are flagged as QSO (OBJ_TYPE=1).

For the catalogs based on the Phosphoros code, the PDZs of all sources are provided in separate catalogs for each tract of the

<footnote n="9">⁹ the catalogs do not contain all the information produced by the hscPipe output, but the raw photometry file are available through the HSC collaboration distribution portal. https://hsc-release.mtk.nao.ac.jp/doc/index.php/data-access__pdr3/</footnote>
<figure><img src="image_21.png" /><figcaption>**Fig. C.1.** Comparison of SExtractor and the hscPipe 2" aperture magnitudes.</figcaption></figure>

asymmetric scatter is present. This asymmetry seems to indicate that the hscPipe fluxes are lower than the SExtractor ones, and this effect is stronger for fainter sources. As these sources are more sensitive to background noise, we interpret the increase in asymmetry toward fainter magnitudes as a sign of stronger subtraction of the background by hscPipe compared to SExtractor. The same conclusion was reached when analyzing Fig. 5, 4 and 7 in Sect. 3.3.

## Appendix D: Phosphoros results on SExtractor photometry

Throughout the paper, the results that are presented are those of Phosphoros/hscPipe and Le Phare/SExtractor. This choice makes it difficult to attribute the differences observed in the photo-zs to the codes or to the photometry. To address this problem, we apply here Phosphoros to the SExtractor photometry to create a version of the photo-zs for which only

the photo-z codes differ. The configuration used to compute these photo-zs is the same as that presented in Sect. 4.1. We use SExtractor 2" aperture photometry uncorrected for galactic extinction, that we fit with the templates, extinction law, and priors described in Sect. 4.1. As a result, PDZs are produced, from which the point estimates (median) are computed.

Figure D.1 presents a comparison of the results of SExtractor/Phosphoros (middle panels) with both hscPipe/Phosphoros (top panels) and SExtractor/Le Phare (bottom panels). In all three cases, *Ugrizy* photo-zs are compared with the spectroscopic sample. In these plots, we can see that the two sets of photo-zs computed from the SExtractor photometry have the same quality when comparing the scatter and the outlier fractions. The scatter from the Phosphoros results is still larger in the bright bins, whereas for the fainter sources the Phosphoros results present a better scatter and outlier fraction than Le Phare photo-zs. This is probably due to the choices in the priors applied by both codes.

These results show that the majority of the differences observed between the photo-zs presented in this work are due to the differences in photometry. Outside of the effect of the priors, there are a few differences between Phosphoros and Le Phare photo-zs, which is expected due to the strong similarities between the two template-fitting codes. All these comparisons thus validate that Phosphoros is able to provide sensible results and is ready to be used by the community.

## Appendix E: Description of the released catalogs

The current release (Sect. 5) consists of a set of catalogs for the four HSC-CLAUDS regions. Several versions are available depending on the adopted photometry (based on the HSC pipeline (Sect. 3.1) or SExtractor run (Sect. 3.2)), the photometric code used (Phosphoros (Sect. 4.1) or Le Phare (Sect. 4.2)) and the number of photometric bands considered for the photometric redshift runs (*Ugrizy* and all-bands). Only subregions in the XMM-LSS and E-COSMOS fields are covered with the near-infrared VISTA imaging.

The description of the catalog outputs is given in Tab E.1 for the SExtractor -Le Phare catalogs and in Tab E.2 for the hscPipe -Phosphoros catalogs<fnref n="9" />.

As the footprints of the different surveys are different, the keyword FLAG_FIELD_BINARY allows the user to restrict the data to a specific dataset by combining its 7 boolean elements (described in Tab E.1). A version defined with a single integer is also available (FLAG_FIELD for Le Phare catalogs). To guarantee the selection of clean objects, the flags MASK and ST_TRAIL must be set to 0 (for SExtractor catalogs) or ISOUTSIDEMASK to "True" (for hscPipe catalogs).

All the catalogs include a stellar classification based on $\chi^2$ estimates between the Pickles stellar templates (Pickles 1998) and the galaxy templates. If the sources are compact and better fitted by a stellar template they are flagged as stars (OBJ_TYPE=2 or ISSTAR=True). In addition the Le Phare code also performs a classification using a QSO library (Salvato et al. 2011). If the sources are compact and better fitted by a QSO template, they are flagged as QSO (OBJ_TYPE=1).

For the catalogs based on the Phosphoros code, the PDZs of all sources are provided in separate catalogs for each tract of the

<footnote n="9">⁹ the catalogs do not contain all the information produced by the hscPipe output, but the raw photometry file are available through the HSC collaboration distribution portal. https://hsc-release.mtk.nao.ac.jp/doc/index.php/data-access__pdr3/</footnote>
<figure><img src="image_22.png" /><figcaption>**Fig. D.1.** Comparison of *Phosphoros* results when computing photo-zs on *hscPipe* (Top) and *SExtractor* (Middle) photometry. The results are also compared to those of *Le Phare* and *SExtractor* (Bottom). The comparison is made using photo-zs computed using only the *Ugrizy* bands in all three cases.</figcaption></figure>

HSC data system. They only contain the source IDs and the PDZ values within the redshift range $0 \le z \le 6$ in steps of $\delta z = 0.01$. For the catalogs based on the *Le Phare* code, we also provide the measurement of the physical parameters (Picouet et al., in prep.) derived with synthetic SEDs from the Bruzual & Charlot (2003) library.
<figure><img src="image_22.png" /><figcaption>**Fig. D.1.** Comparison of *Phosphoros* results when computing photo zs on hscPipe (Top) and *SExtractor* (Middle) photometry. The results are also compared to those of Le Phare and *SExtractor* (Bottom). The comparison is made using photo-zs computed using only the *Ugrizy* bands in all three cases.</figcaption></figure>

HSC data system. They only contain the source IDs and the PDZ
values within the redshift range 0 ≤ *z* ≤ 6 in steps of *δz* = 0.01.
For the catalogs based on the Le Phare code, we also provide
the measurement of the physical parameters (Picouet et al., in
prep.) derived with synthetic SEDs from the Bruzual & Charlot
(2003) library.
<table><caption>**Table E.1.** Summary of the SExtractor/Le Phare catalog.</caption><thead><tr><th>Column name</th><th>Unit</th><th>Description</th></tr></thead><tbody><tr><td colspan="3"><strong>General Parameters</strong></td></tr><tr><td>ID</td><td>-</td><td>Identifiant</td></tr><tr><td>RA, DEC</td><td>deg</td><td>Right ascension and declination of barycenter (J2000)</td></tr><tr><td>TRACT, PATCH</td><td>-</td><td>Position in the HSC frames</td></tr><tr><td>MASK</td><td>[0,1]</td><td>Bright stars mask, clean area: MASK==0</td></tr><tr><td>FLAG_FIELD_BINARY</td><td>Bool[x7]</td><td>[HSC, u, uS, J, VIRCAM, u<sup>a</sup><sub>deep</sub>, HSC<sub>deep</sub>]</td></tr><tr><td>FLAG_FIELD</td><td>integer</td><td>Σ<sub>HSC,u,u*,J,VIRCAM,u*<sup>a</sup><sub>deep,HSC<sub>deep</sub></sub></sub>2<sup>FLAG(band)</sup></td></tr><tr><td>Z_SPEC</td><td>-</td><td>Spectroscopic redshift for matched objects</td></tr><tr><td colspan="3"><strong>Photometry Parameters [SExtractor]</strong></td></tr><tr><td>A_WORLD, B_WORLD</td><td>deg</td><td>Profile RMS along ellipse's axis</td></tr><tr><td>KRON-radius</td><td>deg</td><td>Kron apertures in units of A or B</td></tr><tr><td>THETA_WORLD</td><td>deg</td><td>Ellipse orientation</td></tr><tr><td>ELONGATION</td><td>-</td><td>A_WORLD/B_WORLD</td></tr><tr><td>ELLIPTICITY</td><td>-</td><td>1 - B_WORLD/A_WORLD</td></tr><tr><td>EB_V</td><td>-</td><td>Galactic extinction (Schlegel et al. 1998)</td></tr><tr><td>FWHM WORLD_HSC_I</td><td>deg</td><td>FWHM assuming a gaussian core</td></tr><tr><td>FLUX-radius[0.25,0.5,0.75]_HSC_I</td><td>pix</td><td>Fraction-of-light radii</td></tr><tr><td>CLASS_STAR_HSC_I</td><td>pix</td><td>SExtractor star estimator</td></tr><tr><td>[BAND], [BAND]_ERR</td><td>mag</td><td>total mag, galactic extinction corrected</td></tr><tr><td>MAG_APER_2S_[BAND], MAGERR_APER_2S_[BAND]</td><td>mag</td><td>magnitude and magnitude error measured in a 2" aperture</td></tr><tr><td>MAG_APER_3S_[BAND], MAGERR_APER_3S_[BAND]</td><td>mag</td><td>magnitude and magnitude error measured in a 3" aperture</td></tr><tr><td>MAG_ISO_[BAND], MAGERR_ISO_[BAND]</td><td>mag</td><td>magnitude and magnitude error measured in isophotal aperture</td></tr><tr><td>OFFSET_[2S,3S,ISO]</td><td>mag</td><td>Total magnitude offsets to be added to the respective magnitudes</td></tr><tr><td colspan="3"><strong>Parameters computed with LePhare - Zphot</strong></td></tr><tr><td>Z_BEST, Z_BEST68_LOW, Z_BEST68_HIGH</td><td>-</td><td>Maximum of the ML distribution</td></tr><tr><td>NBAND_USED</td><td>integer</td><td>Number of bands</td></tr><tr><td>CHI_BEST, CHI_STAR, CHI_QSO</td><td>-</td><td>Chi2 of the best fit with galaxy, star, and QSO template</td></tr><tr><td>MOD_BEST, MOD_STAR, MOD_QSO</td><td>-</td><td>Best fit template</td></tr><tr><td>Z_ML, Z_ML68_LOW, Z_ML68_HIGH</td><td>-</td><td>Median of the ML distribution</td></tr><tr><td>Z_SEC</td><td>-</td><td>Redshift of the secondary peak</td></tr><tr><td>Z_QSO</td><td>-</td><td>QSO redshift computed</td></tr><tr><td>ZPHOT</td><td>-</td><td>Combination of photometric redshift: z<sub>ML</sub> → z<sub>BEST</sub></td></tr><tr><td colspan="3"><strong>Parameters computed with LePhare - BC03</strong></td></tr><tr><td>Z_BC03</td><td>-</td><td>best z combination used for BC03 run: z<sub>SPEC</sub> → z<sub>PHOT</sub></td></tr><tr><td>MAG>Abs_[BAND]</td><td>mag</td><td>LePhare computed absolute magnitude</td></tr><tr><td>MOD_BEST_BC03</td><td>integer</td><td>Best fit template</td></tr><tr><td>EBV_BEST</td><td>-</td><td>Best fit template</td></tr><tr><td>EXTLAW_BEST</td><td>-</td><td>Best fit template</td></tr><tr><td>AGE_X</td><td>year</td><td>Age of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>MASS_X</td><td>M<sub>☉</sub></td><td>Mass of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>SFR_X</td><td>M<sub>☉</sub> year<sup>-1</sup></td><td>SFR of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>SSFR_X</td><td>year<sup>-1</sup></td><td>sSFR of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>LUM_NUV_BEST</td><td>-</td><td>NUV luminosity</td></tr><tr><td>LUM_R_BEST</td><td>-</td><td>R luminosity</td></tr><tr><td>LUM_K_BEST</td><td>-</td><td>K luminosity</td></tr><tr><td colspan="3"><strong>Other parameters</strong></td></tr><tr><td>OBJ_TYPE</td><td>[0,1,2]</td><td>Object flag: 0 for galaxies, 1 for QSOs, 2 for stars</td></tr><tr><td>COMPACT</td><td>[0,1]</td><td>Flag for compact object (see eq 1)</td></tr><tr><td>PASSIVE</td><td>[0,1]</td><td>Flag for passive VS star-forming galaxies based on NUVrK</td></tr></tbody></table>
<table><caption>**Table E.1.** Summary of the SExtractor/Le Phare catalog.</caption><thead><tr><th>Column name</th><th>Unit</th><th>Description</th></tr></thead><tbody><tr><td colspan="3"><strong>General Parameters</strong></td></tr><tr><td>ID</td><td>-</td><td>Identifiant</td></tr><tr><td>RA, DEC</td><td>deg</td><td>Right ascension and declination of barycenter (J2000)</td></tr><tr><td>TRACT, PATCH</td><td>-</td><td>Position in the HSC frames</td></tr><tr><td>MASK</td><td>[0,1]</td><td>Bright stars mask, clean area: MASK==0</td></tr><tr><td>FLAG_FIELD_BINARY</td><td>Bool[x7]</td><td>[HSC, u, uS, J, VIRCAM, u<sup>a</sup><sub>deep</sub>, HSC<sub>deep</sub>]</td></tr><tr><td>FLAG_FIELD</td><td>integer</td><td>Σ<sub>HSC,u,u*,J,VIRCAM,u*<sup>a</sup><sub>deep,HSC<sub>deep</sub></sub></sub> 2<sup>FLAG(band)</sup></td></tr><tr><td>Z_SPEC</td><td>-</td><td>Spectroscopic redshift for matched objects</td></tr><tr><td colspan="3"><strong>Photometry Parameters [SExtractor]</strong></td></tr><tr><td>A_WORLD, B_WORLD</td><td>deg</td><td>Profile RMS along ellipse's axis</td></tr><tr><td>KRON-radius</td><td>deg</td><td>Kron apertures in units of A or B</td></tr><tr><td>THETA_WORLD</td><td>deg</td><td>Ellipse orientation</td></tr><tr><td>ELONGATION</td><td>-</td><td>A_WORLD/B_WORLD</td></tr><tr><td>ELLIPTICITY</td><td>-</td><td>1 - B_WORLD/A_WORLD</td></tr><tr><td>EB_V</td><td>-</td><td>Galactic extinction (Schlegel et al. 1998)</td></tr><tr><td>FWHM WORLD_HSC_I</td><td>deg</td><td>FWHM assuming a gaussian core</td></tr><tr><td>FLUX-radius[0.25,0.5,0.75]_HSC_I</td><td>pix</td><td>Fraction-of-light radii</td></tr><tr><td>CLASS_STAR_HSC_I</td><td>pix</td><td>SExtractor star estimator</td></tr><tr><td>[BAND], [BAND]_ERR</td><td>mag</td><td>total mag, galactic extinction corrected</td></tr><tr><td>MAG_APER_2S_[BAND], MAGERR_APER_2S_[BAND]</td><td>mag</td><td>magnitude and magnitude error measured in a 2" aperture</td></tr><tr><td>MAG_APER_3S_[BAND], MAGERR_APER_3S_[BAND]</td><td>mag</td><td>magnitude and magnitude error measured in a 3" aperture</td></tr><tr><td>MAG_ISO_[BAND], MAGERR_ISO_[BAND]</td><td>mag</td><td>magnitude and magnitude error measured in isophotal aperture</td></tr><tr><td>OFFSET_[2S,3S,ISO]</td><td>mag</td><td>Total magnitude offsets to be added to the respective magnitudes</td></tr><tr><td colspan="3"><strong>Parameters computed with LePhare - Zphot</strong></td></tr><tr><td>Z_BEST, Z_BEST68_LOW, Z_BEST68_HIGH</td><td>-</td><td>Maximum of the ML distribution</td></tr><tr><td>NBAND_USED</td><td>integer</td><td>Number of bands</td></tr><tr><td>CHI_BEST, CHI_STAR, CHI_QSO</td><td>-</td><td>Chi2 of the best fit with galaxy, star, and QSO template</td></tr><tr><td>MOD_BEST, MOD_STAR, MOD_QSO</td><td>-</td><td>Best fit template</td></tr><tr><td>Z_ML, Z_ML68_LOW, Z_ML68_HIGH</td><td>-</td><td>Median of the ML distribution</td></tr><tr><td>Z_SEC</td><td>-</td><td>Redshift of the secondary peak</td></tr><tr><td>Z_QSO</td><td>-</td><td>QSO redshift computed</td></tr><tr><td>ZPHOT</td><td>-</td><td>Combination of photometric redshift: z<sub>ML</sub> → z<sub>BEST</sub></td></tr><tr><td colspan="3"><strong>Parameters computed with LePhare - BC03</strong></td></tr><tr><td>Z_BC03</td><td>-</td><td>best z combination used for BC03 run: z<sub>SPEC</sub> → z<sub>PHOT</sub></td></tr><tr><td>MAG_abs_[BAND]</td><td>mag</td><td>LePhare computed absolute magnitude</td></tr><tr><td>MOD_BEST_BC03</td><td>integer</td><td>Best fit template</td></tr><tr><td>EBV_BEST</td><td>-</td><td>Best fit template</td></tr><tr><td>EXTLAW_BEST</td><td>-</td><td>Best fit template</td></tr><tr><td>AGE_X</td><td>year</td><td>Age of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>MASS_X</td><td>M<sub>☉</sub></td><td>Mass of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>SFR_X</td><td>M<sub>☉</sub> year<sup>-1</sup></td><td>SFR of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>SSFR_X</td><td>year<sup>-1</sup></td><td>sSFR of best fit with X in (BEST, MED, INF, SUP)</td></tr><tr><td>LUM_NUV_BEST</td><td>-</td><td>NUV luminosity</td></tr><tr><td>LUM_R_BEST</td><td>-</td><td>R luminosity</td></tr><tr><td>LUM_K_BEST</td><td>-</td><td>K luminosity</td></tr><tr><td colspan="3"><strong>Other parameters</strong></td></tr><tr><td>OBJ_TYPE</td><td>[0,1,2]</td><td>Object flag: 0 for galaxies, 1 for QSOs, 2 for stars</td></tr><tr><td>COMPACT</td><td>[0,1]</td><td>Flag for compact object (see eq 1)</td></tr><tr><td>PASSIVE</td><td>[0,1]</td><td>Flag for passive VS star-forming galaxies based on NUVrK</td></tr></tbody></table>
<table><caption>Table E.2. Summary of the hscPipe/Phosphoros catalog.</caption><thead><tr><th>Column name</th><th>Unit</th><th>Description</th></tr></thead><tbody><tr><td colspan="3"><strong>Id and locations</strong></td></tr><tr><td>ID</td><td>—</td><td>Identifiant</td></tr><tr><td>RA, DEC</td><td>deg</td><td>Right ascension and declination of centroid (J2000)</td></tr><tr><td>TRACT, PATCH</td><td>—</td><td>Tract and patch ids in the hscPipe system</td></tr><tr><td colspan="3"><strong>Photometry</strong></td></tr><tr><td>FLUX_APER_2_[BAND], FLUXERR_APER_2_[BAND]</td><td>μJy</td><td>Flux and flux error measured in a 2" aperture</td></tr><tr><td>FLUX_APER_3_[BAND], FLUXERR_APER_3_[BAND]</td><td>μJy</td><td>Flux and flux error measured in a 3" aperture</td></tr><tr><td>FLUX_PSF_[BAND], FLUXERR_PSF_[BAND]</td><td>μJy</td><td>Flux and flux error measured using PSF modeling</td></tr><tr><td>FLUX_KRON_[BAND], FLUXERR_KRON_[BAND]</td><td>μJy</td><td>Flux and flux error measured in Kron apertures</td></tr><tr><td>RADIUS_KRON_[BAND]</td><td>"</td><td>Kron radius</td></tr><tr><td>FLUX_CMODEL_[BAND], FLUXERR_CMODEL_[BAND]</td><td>μJy</td><td>Flux and flux error measured using cmodel fitting</td></tr><tr><td>HASBADPHOTOMETRY_[BAND]</td><td>Bool</td><td>Flag indicating problem in photometry measurement</td></tr><tr><td>ISDUPLICATED_[BAND]</td><td>Bool</td><td>Flag indicating if source is duplication of primary source</td></tr><tr><td>ISNODATA_[BAND]</td><td>Bool</td><td>Flag indicating if source is not extracted from observed data</td></tr><tr><td>ISSKY_[BAND]</td><td>Bool</td><td>Flag indicating if source is extracted from sky</td></tr><tr><td>ISPARENT_[BAND]</td><td>Bool</td><td>Flag indicating if source a parent blended source</td></tr><tr><td>NOTOBSERVED_[BAND]</td><td>Bool</td><td>Flag indicating if source is observed in the band</td></tr><tr><td>ISCLEAN_[BAND]</td><td>Bool</td><td>Flag indicating if all photometry flags are false</td></tr><tr><td>ISCOMPACT_[HSC-BAND]</td><td>Bool</td><td>Flag indicating if source is compact in HSC band</td></tr><tr><td>ISCOMPACT</td><td>Bool</td><td>Flag indicating if source is compact all HSC bands</td></tr><tr><td colspan="3"><strong>Results computed with Phosphoros</strong></td></tr><tr><td>ZPHOT_NIR, Z_LOW68_NIR, Z_HIGH68_NIR<sup>a</sup></td><td>—</td><td>PDZ median and limits encompassing 68% of PDZ using all bands</td></tr><tr><td>Z_CHI_NIR<sup>a</sup></td><td>—</td><td>Point estimate with highest likelihood using all bands</td></tr><tr><td>Z_PEAK_NIR<sup>a</sup></td><td>—</td><td>Point estimate with highest PDZ value using all bands</td></tr><tr><td>POSTERIOR-LOG_NIR<sup>a</sup></td><td>—</td><td>Log of best posterior value</td></tr><tr><td>LIKELIHOOD-LOG_NIR<sup>a</sup></td><td>—</td><td>Log of best likelihood value</td></tr><tr><td>ZPHOT_6B, Z_LOW68_6B, Z_HIGH68_6B<sup>a</sup></td><td>—</td><td>PDZ median and limits encompassing 68% of PDZ using Ugrizy bands</td></tr><tr><td>Z_CHI_6B<sup>a</sup></td><td>—</td><td>Point estimate with highest likelihood using Ugrizy bands</td></tr><tr><td>Z_PEAK_6B<sup>a</sup></td><td>—</td><td>Point estimate with highest PDZ value using Ugrizy bands</td></tr><tr><td>POSTERIOR-LOG_6B<sup>a</sup></td><td>—</td><td>Log of best posterior value using Ugrizy bands</td></tr><tr><td>LIKELIHOOD-LOG_6B<sup>a</sup></td><td>—</td><td>Log of best likelihood value using Ugrizy bands</td></tr><tr><td>ZPHOT, Z_LOW68, Z_HIGH68</td><td>—</td><td>PDZ median and limits encompassing 68% of PDZ using all bands</td></tr><tr><td>Z_CHI</td><td>—</td><td>Point estimate with highest likelihood using all bands</td></tr><tr><td>Z_PEAK</td><td>—</td><td>Point estimate with highest PDZ value using all bands</td></tr><tr><td>POSTERIOR-LOG</td><td>—</td><td>Log of best posterior value</td></tr><tr><td>LIKELIHOOD-LOG</td><td>—</td><td>Log of best likelihood value</td></tr><tr><td>LIKELIHOOD-LOG_STAR</td><td>—</td><td>Log of best likelihood value star templates with all bands available</td></tr><tr><td colspan="3"><strong>Other info</strong></td></tr><tr><td>ISOUTSIDEMASK</td><td>[0,1]</td><td>Source outside of updated bright stars mask and satellite trail footprint</td></tr><tr><td>FLAG_FIELD_BINARY</td><td>Bool[x7]</td><td>[HSC, u, u*, J, VIRCAM, u*<sub>deep</sub>, HSC<sub>deep</sub>]</td></tr><tr><td>ISSTARTEMP</td><td>Bool</td><td>Have a better Likelihood-Log with star template than galaxy templates</td></tr><tr><td>ISSTAR</td><td>Bool</td><td>ISSTARTEMP &amp; ISCOMPACT</td></tr></tbody></table>

<footnote>a Only for E-COSMOS and XMM-LSS fields as they both benefit from additional NIR data.</footnote>
<table><caption>**Table E.2.** Summary of the hscPipe/Phosphoros catalog.</caption><thead><tr><th>Column name</th><th>Unit</th><th>Description</th></tr></thead><tbody><tr><td colspan="3"><strong>Id and locations</strong></td></tr><tr><td>ID</td><td>—</td><td>Identifiant</td></tr><tr><td>RA, DEC</td><td>deg</td><td>Right ascension and declination of centroid (J2000)</td></tr><tr><td>TRACT, PATCH</td><td>—</td><td>Tract and patch ids in the hscPipe system</td></tr><tr><td colspan="3"><strong>Photometry</strong></td></tr><tr><td>FLUX_APER_2_[BAND], FLUXERR_APER_2_[BAND]</td><td>μJy</td><td>Flux and flux error measured in a 2" aperture</td></tr><tr><td>FLUX_APER_3_[BAND], FLUXERR_APER_3_[BAND]</td><td>μJy</td><td>Flux and flux error measured in a 3" aperture</td></tr><tr><td>FLUX_PSF_[BAND], FLUXERR_PSF_[BAND]</td><td>μJy</td><td>Flux and flux error measured using PSF modeling</td></tr><tr><td>FLUX_KRON_[BAND], FLUXERR_KRON_[BAND]</td><td>μJy</td><td>Flux and flux error measured in Kron apertures</td></tr><tr><td>RADIUS_KRON_[BAND]</td><td>"</td><td>Kron radius</td></tr><tr><td>FLUX_CMODEL_[BAND], FLUXERR_CMODEL_[BAND]</td><td>μJy</td><td>Flux and flux error measured using cmodel fitting</td></tr><tr><td>HASBADPHOTOMETRY_[BAND]</td><td>Bool</td><td>Flag indicating problem in photometry measurement</td></tr><tr><td>ISDUPLICATED_[BAND]</td><td>Bool</td><td>Flag indicating if source is duplication of primary source</td></tr><tr><td>ISNODATA_[BAND]</td><td>Bool</td><td>Flag indicating if source is not extracted from observed data</td></tr><tr><td>ISSKY_[BAND]</td><td>Bool</td><td>Flag indicating if source is extracted from sky</td></tr><tr><td>ISPARENT_[BAND]</td><td>Bool</td><td>Flag indicating if source a parent blended source</td></tr><tr><td>NOTOBSERVED_[BAND]</td><td>Bool</td><td>Flag indicating if source is observed in the band</td></tr><tr><td>ISCLEAN_[BAND]</td><td>Bool</td><td>Flag indicating if all photometry flags are false</td></tr><tr><td>ISCOMPACT_[HSC-BAND]</td><td>Bool</td><td>Flag indicating if source is compact in HSC band</td></tr><tr><td>ISCOMPACT</td><td>Bool</td><td>Flag indicating if source is compact all HSC bands</td></tr><tr><td colspan="3"><strong>Results computed with Phosphoros</strong></td></tr><tr><td>ZPHOT_NIR, Z_LOW68_NIR, Z_HIGH68_NIR<sup>a</sup></td><td>—</td><td>PDZ median and limits encompassing 68% of PDZ using all bands</td></tr><tr><td>Z_CHI_NIR<sup>a</sup></td><td>—</td><td>Point estimate with highest likelihood using all bands</td></tr><tr><td>Z_PEAK_NIR<sup>a</sup></td><td>—</td><td>Point estimate with highest PDZ value using all bands</td></tr><tr><td>POSTERIOR-LOG_NIR<sup>a</sup></td><td>—</td><td>Log of best posterior value</td></tr><tr><td>LIKELIHOOD-LOG_NIR<sup>a</sup></td><td>—</td><td>Log of best likelihood value</td></tr><tr><td>ZPHOT_6B, Z_LOW68_6B, Z_HIGH68_6B<sup>a</sup></td><td>—</td><td>PDZ median and limits encompassing 68% of PDZ using Ugrizy bands</td></tr><tr><td>Z_CHI_6B<sup>a</sup></td><td>—</td><td>Point estimate with highest likelihood using Ugrizy bands</td></tr><tr><td>Z_PEAK_6B<sup>a</sup></td><td>—</td><td>Point estimate with highest PDZ value using Ugrizy bands</td></tr><tr><td>POSTERIOR-LOG_6B<sup>a</sup></td><td>—</td><td>Log of best posterior value using Ugrizy bands</td></tr><tr><td>LIKELIHOOD-LOG_6B<sup>a</sup></td><td>—</td><td>Log of best likelihood value using Ugrizy bands</td></tr><tr><td>ZPHOT, Z_LOW68, Z_HIGH68</td><td>—</td><td>PDZ median and limits encompassing 68% of PDZ using all bands</td></tr><tr><td>Z_CHI</td><td>—</td><td>Point estimate with highest likelihood using all bands</td></tr><tr><td>Z_PEAK</td><td>—</td><td>Point estimate with highest PDZ value using all bands</td></tr><tr><td>POSTERIOR-LOG</td><td>—</td><td>Log of best posterior value</td></tr><tr><td>LIKELIHOOD-LOG</td><td>—</td><td>Log of best likelihood value</td></tr><tr><td>LIKELIHOOD-LOG_STAR</td><td>—</td><td>Log of best likelihood value star templates with all bands available</td></tr><tr><td colspan="3"><strong>Other info</strong></td></tr><tr><td>ISOUTSIDEMASK</td><td>[0,1]</td><td>Source outside of updated bright stars mask and satellite trail footprint</td></tr><tr><td>FLAG_FIELD_BINARY</td><td>Bool[x7]</td><td>[HSC, u, u*, J, VIRCAM, u*<sub>deep</sub>, HSC<sub>deep</sub>]</td></tr><tr><td>ISSTARTEMP</td><td>Bool</td><td>Have a better Likelihood-Log with star template than galaxy templates</td></tr><tr><td>ISSTAR</td><td>Bool</td><td>ISSTARTEMP &amp; ISCOMPACT</td></tr></tbody></table>

<footnote><sup>a</sup> Only for E-COSMOS and XMM-LSS fields as they both benefit from additional NIR data.</footnote>