The whole picture of the large-scale structure of the CL1604 supercluster at z$\sim$0.9

TL;DR

This study maps the extensive large-scale structure of the CL1604 supercluster at z~0.9, revealing it as part of a much larger network of galaxy clusters and analyzing the stellar populations of red-sequence galaxies within this structure.

Contribution

It provides the first large-scale mapping of the CL1604 supercluster extending over 50 Mpc, confirming its connection to larger structures and analyzing galaxy stellar populations across this vast region.

Findings

The supercluster is part of a larger structure extending beyond initial observations.

Red-sequence galaxies are predominantly old (>2 Gyr) across the structure.

Galaxies at similar redshifts have comparable stellar ages despite being 50 Mpc apart.

Abstract

We present the large-scale structure over more than 50 comoving Mpc scale at z $\sim$ 0.9 where the CL1604 supercluster, which is one of the largest structures ever known at high redshifts, is embedded. The wide-field deep imaging survey by the Subaru Strategic Program with Hyper Suprime-Cam reveals that the already-known CL1604 supercluster is a mere part of larger-scale structure extending to both the north and the south. We confirm that there are galaxy clusters at three slightly different redshifts in the northern and southern sides of the supercluster by determining the redshifts of 55 red-sequence galaxies and 82 star-forming galaxies in total by the follow-up spectroscopy with Subaru/FOCAS and Gemini-N/GMOS. This suggests that the structure ever known as the CL1604 supercluster is the tip of the iceberg. We investigate stellar population of the red-sequence galaxies using 4000 A break and Balmer H$\delta$ absorption line. Almost all of the red-sequence galaxies brighter than 21.5 mag in $z$-band show an old stellar population with $\gtrsim2$ Gyr. The comparison of composite spectra of the red-sequence galaxies in the individual clusters show that the galaxies at a similar redshift have similar stellar population age, even if they are located $\sim$50 Mpc apart from each other. However, there could be a large variation in the star formation history. Therefore, it is likely that galaxies associated with the large-scale structure at 50 Mpc scale formed at almost the same time, have assembled into the denser regions, and then have evolved with different star formation history along the hierarchical growth of the cosmic web.

Figures

Tables

Table 1. Table 1: A list of 55 red-sequence galaxies confirmed. The object ID in the first column is from the S16A release data and the other information is from the PDR2 data and spectrum.

object_id (S16A)	object_id (PDR2)	R.A.	Dec.	cluster	z mag.	r-z	spectrograph	redshift	EW(H$\delta$)[$\AA$]	EW(H$\delta$)[$\AA$]	$D_{n}4000$
									WO97	Fisher98	Balogh99
69617112015996160	69617112015996479	16:03:40.395	+42:38:38.425	S3	21.02	2.14	GMOS	0.890	-2.10$\pm$2.77	-6.05$\pm$2.78	1.70$\pm$0.12
69617112015996904	69617112015998074	16:03:33.596	+42:39:13.880	S3	21.45	2.26	GMOS	0.907	1.77$\pm$4.10	-4.20$\pm$4.55	1.59$\pm$0.17
69617112015997316	69617112015998454	16:03:46.199	+42:39:30.601	S3	20.20	2.15	GMOS	0.890	1.21$\pm$2.08	-4.10$\pm$2.65	1.50$\pm$0.09
69617112015972551	69617112015998558	16:03:40.219	+42:39:40.821	S3	21.78	2.08	GMOS	0.910	—	—	—
69617112015997717	69617112015998746	16:03:51.500	+42:39:53.591	S3	21.78	2.04	GMOS	0.898	—	—	—
69617112015997796	69617112015998848	16:03:47.229	+42:39:57.713	S3	21.11	2.03	GMOS	1.010	3.21$\pm$1.13	4.49$\pm$0.90	1.42$\pm$0.07
69617112015997981	69617112015999018	16:03:34.390	+42:40:07.680	S3	21.00	2.38	GMOS	0.903	1.27$\pm$2.26	1.05$\pm$2.21	1.56$\pm$0.11
69617116310940051	69617116310939901	16:03:55.668	+42:50:28.562	S2	20.70	1.98	GMOS	0.911	3.06$\pm$1.38	4.00$\pm$0.94	1.58$\pm$0.06
69617116310938517	69617116310964806	16:03:46.843	+42:48:53.180	S2	21.94	2.14	GMOS	0.918	—	—	—
69617116310965204	69617116310965707	16:03:48.209	+42:49:05.619	S2	20.35	2.15	GMOS	0.920	2.24$\pm$1.23	2.90$\pm$1.26	1.53$\pm$0.08
69617116310965418	69617116310966045	16:03:47.753	+42:49:34.080	S2	21.54	2.14	GMOS	0.917	—	—	—
69617116310965615	69617116310966133	16:03:46.631	+42:49:45.052	S2	21.80	1.84	GMOS	0.919	—	—	—
69617116310965997	69617116310966570	16:03:46.099	+42:50:06.593	S2	21.47	2.10	GMOS	0.916	0.98$\pm$2.86	-0.04$\pm$2.70	1.79$\pm$0.11
69617116310967412	69617116310967357	16:03:37.715	+42:51:07.775	S2	21.04	1.92	GMOS	0.988	6.49$\pm$1.36	7.25$\pm$1.32	1.07$\pm$0.07
69617116310966811	69617116310967364	16:03:37.056	+42:50:48.871	S2	21.28	2.09	GMOS	0.918	-1.66$\pm$2.64	-2.71$\pm$3.12	1.54$\pm$0.09
69617116310966802	69617116310967498	16:03:50.289	+42:50:48.359	S2	20.45	2.38	GMOS	0.988	3.80$\pm$0.95	4.37$\pm$1.28	1.68$\pm$0.09
69617120605920352	69617120605921712	16:03:42.419	+42:51:59.018	S2	21.27	1.94	GMOS	0.989	3.55$\pm$1.47	8.34$\pm$1.53	1.30$\pm$0.09
69617120605921126	69617120605922446	16:03:40.346	+42:52:36.029	S2	21.46	2.05	GMOS	0.944	0.13$\pm$2.41	2.98$\pm$2.15	2.03$\pm$0.16
69617120605921738	69617120605923049	16:03:35.961	+42:53:02.321	S2	21.27	2.56	GMOS	0.948	4.50$\pm$3.00	2.82$\pm$2.96	1.77$\pm$0.16
69617120605922187	69617120605923406	16:03:16.712	+42:53:14.113	S1	20.75	2.15	GMOS	0.985	-0.46$\pm$1.93	3.32$\pm$2.12	1.59$\pm$0.15
69617120605922445	69617120605923568	16:03:14.618	+42:53:28.231	S1	22.09	1.91	GMOS	0.983	—	—	—
69617120605923272	69617120605924511	16:03:24.090	+42:54:13.470	S1	21.91	2.13	GMOS	0.921	—	—	—
69617120605925007	69617120605926484	16:03:14.817	+42:55:39.814	S1	22.15	1.93	GMOS	0.887	—	—	—
69617120605925117	69617120605926513	16:03:18.248	+42:55:42.545	S1	21.81	1.77	GMOS	0.842	—	—	—
69617120605925431	69617120605926983	16:03:20.049	+42:56:05.017	S1	21.00	2.13	GMOS	0.949	-2.26$\pm$2.30	-1.63$\pm$2.59	2.30$\pm$0.14
69617120605926287	69617120605927999	16:03:10.009	+42:56:42.710	S1	21.39	2.06	GMOS	0.883	-6.30$\pm$3.22	-9.04$\pm$3.96	1.55$\pm$0.14
69617258044872416	69617258044871201	16:03:09.522	+42:52:03.196	S1	20.86	2.10	GMOS	0.930	3.15$\pm$2.86	-0.53$\pm$2.83	1.52$\pm$0.14
69617258044872673	69617258044871693	16:03:08.446	+42:52:16.457	S1	21.95	1.97	GMOS	0.975	—	—	—
69617258044877131	69617258044875360	16:03:09.587	+42:55:22.273	S1	21.74	2.00	GMOS	0.883	—	—	—
70399543388171802	70399543388172272	16:03:52.790	+43:40:02.320	N1	21.09	1.96	GMOS	0.887	-2.46$\pm$3.47	-8.67$\pm$3.60	1.29$\pm$0.13
70399543388149323	70399543388173819	16:03:53.691	+43:41:08.039	N1	21.76	2.09	GMOS	0.933	—	—	—
70399543388174556	70399543388174278	16:03:47.435	+43:41:33.969	N1	20.59	2.18	FOCAS	0.929	0.64$\pm$1.55	1.42$\pm$1.50	2.03$\pm$0.12
70399543388175946	70399543388175701	16:03:52.016	+43:42:35.393	N1	21.48	2.09	FOCAS	0.943	-5.10$\pm$3.26	-2.72$\pm$2.79	1.90$\pm$0.19
70399543388176326	70399543388176068	16:03:50.260	+43:42:54.783	N1	21.85	2.02	GMOS	0.871	—	—	—
70399543388176450	70399543388176321	16:03:51.211	+43:43:07.084	N1	20.51	2.12	FOCAS	0.874	-1.52$\pm$1.48	-0.32$\pm$1.18	2.33$\pm$0.14
70399543388176621	70399543388176379	16:03:56.928	+43:43:12.446	N1	20.72	2.21	GMOS	0.930	2.62$\pm$2.72	-1.48$\pm$2.92	1.71$\pm$0.12
70399543388177131	70399543388176965	16:04:02.224	+43:43:42.694	N1	21.06	2.17	GMOS	0.928	-3.75$\pm$5.22	-1.37$\pm$3.99	1.82$\pm$0.23
70399543388177394	70399543388177274	16:03:51.068	+43:43:55.430	N1	21.43	1.93	FOCAS	0.879	3.45$\pm$2.40	3.19$\pm$2.47	1.91$\pm$0.19
70399543388177404	70399543388177291	16:03:55.002	+43:43:56.749	N1	21.62	2.22	GMOS	0.921	—	—	—
70399543388177612	70399543388177324	16:04:00.444	+43:44:08.426	N1	22.32	2.07	FOCAS	0.975	—	—	—
70399543388177604	70399543388177513	16:03:55.311	+43:44:03.279	N1	21.48	2.15	FOCAS	0.912	7.52$\pm$3.82	9.16$\pm$3.47	1.60$\pm$0.16
70399543388177641	70399543388177524	16:03:54.306	+43:44:04.750	N1	21.37	2.25	GMOS	0.928	-4.41$\pm$4.87	0.19$\pm$3.43	2.00$\pm$0.22
70399543388177700	70399543388177564	16:03:52.119	+43:44:17.076	N1	20.54	1.88	FOCAS	0.881	-1.26$\pm$1.85	1.98$\pm$2.04	1.83$\pm$0.10
70399543388177702	70399543388177566	16:03:52.277	+43:44:18.158	N1	20.06	2.71	FOCAS	0.884	1.59$\pm$1.40	-0.85$\pm$1.49	1.86$\pm$0.09
70399543388177737	70399543388177865	16:03:54.781	+43:44:29.036	N1	21.66	2.07	FOCAS	0.888	—	—	—
70399543388152808	70399543388177938	16:03:48.655	+43:44:24.062	N1	21.99	2.16	GMOS	0.929	—	—	—
70399543388178162	70399543388178065	16:04:02.859	+43:44:25.165	N1	22.21	2.15	FOCAS	0.881	—	—	—
70399543388178592	70399543388178703	16:03:49.598	+43:45:00.030	N1	21.41	2.02	GMOS	0.930	1.40$\pm$6.67	-5.01$\pm$6.71	2.16$\pm$0.34
70399543388178729	70399543388178779	16:03:44.668	+43:44:58.905	N1	20.44	2.20	GMOS	0.970	-0.40$\pm$1.43	1.85$\pm$1.45	1.72$\pm$0.11
70399543388154281	70399543388179847	16:03:53.212	+43:45:41.672	N1	21.92	2.23	GMOS	0.867	—	—	—
70405040946315068	70405040946315286	16:04:09.272	+43:43:43.364	N1	22.14	2.17	FOCAS	0.882	—	—	—
70405040946315628	70405040946315935	16:04:04.083	+43:44:17.812	N1	20.11	2.14	FOCAS	0.920	3.65$\pm$1.58	3.24$\pm$1.36	2.02$\pm$0.09
70405040946316160	70405040946316384	16:04:04.581	+43:44:30.831	N1	22.07	2.26	FOCAS	0.854	—	—	—
70405040946316183	70405040946316459	16:04:08.803	+43:44:36.930	N1	20.94	1.93	FOCAS	0.920	2.68$\pm$0.93	2.22$\pm$0.93	1.54$\pm$0.05
70405040946317856	70405040946318093	16:04:05.887	+43:45:44.182	N1	21.76	2.06	FOCAS	0.824	—	—	—

Table 2. Table 2: The same as table LABEL:tbl:RSGs , but for 82 star-forming galaxies confirmed. In the last column, detection or non-detection of the line is shown by ∘ \circ or × \times , respectively, and — means that the spectrum does not cover the wavelength for the emission line.

object_id (S16A)	object_id (PDR2)	R.A.	Dec.	cluster	z mag.	r-z	spectrograph	redshift	emission lines detected∗
									[O\emissiontypeII]3727	H$\beta$	[O\emissiontypeIII]5007
69617112015971747	69617112015972223	16:03:41.447	+42:38:53.698	S3	22.20	1.01	GMOS	0.891	$\circ$	$\circ$	$\circ$
69617112015998043	69617112015973587	16:03:43.742	+42:40:12.950	S3	23.89	1.13	GMOS	0.878	$\circ$	$\circ$	$\circ$
69617112015994346	69617112015995528	16:03:41.877	+42:37:15.491	S3	22.85	0.84	GMOS	0.895	$\circ$	$\circ$	$\circ$
69617112015995059	69617112015996295	16:03:48.869	+42:37:57.262	S3	22.22	0.47	GMOS	0.895	$\circ$	$\circ$	$\circ$
69617112015995799	69617112015996841	16:03:34.176	+42:38:16.865	S3	22.36	1.11	GMOS	0.902	$\circ$	$\circ$	$\times$
69617112015995802	69617112015996843	16:03:35.001	+42:38:20.476	S3	22.20	1.00	GMOS	1.009	$\circ$	$\circ$	$\times$
69617112015995909	69617112015996963	16:03:35.844	+42:38:25.340	S3	23.41	0.91	GMOS	0.986	$\circ$	$\times$	$\times$
69617112015996131	69617112015997201	16:03:35.224	+42:38:37.830	S3	21.14	1.15	GMOS	0.884	$\circ$	$\circ$	$\circ$
69617112015997302	69617112015998278	16:03:43.310	+42:39:31.621	S3	21.83	1.04	GMOS	0.877	$\circ$	$\circ$	$\circ$
69617112015997635	69617112015998643	16:03:55.195	+42:39:47.280	S3	22.51	0.96	GMOS	0.916	$\circ$	$\times$	$\circ$
69617112015997683	69617112015998696	16:03:33.160	+42:39:53.549	S3	22.81	0.88	GMOS	0.903	$\circ$	$\times$	$\times$
69617112015997789	69617112015998795	16:03:56.552	+42:39:55.355	S3	22.88	0.81	GMOS	0.932	$\circ$	$\times$	$\circ$
69617112015997875	69617112015998896	16:03:48.370	+42:40:02.643	S3	23.27	0.63	GMOS	0.907	$\circ$	$\circ$	$\circ$
69617112015998121	69617112015999163	16:03:30.843	+42:40:17.391	S3	23.13	1.09	GMOS	0.902	$\circ$	$\times$	—
69617112015998126	69617112015999228	16:03:37.178	+42:40:20.260	S3	23.22	1.07	GMOS	0.854	$\circ$	$\times$	$\circ$
69617116310940018	69617116310939871	16:03:33.639	+42:50:26.516	S2	22.84	1.43	GMOS	0.881	$\circ$	$\circ$	$\circ$
69617116310940107	69617116310939957	16:03:36.047	+42:50:31.268	S2	23.60	1.01	GMOS	0.847	$\circ$	$\times$	$\times$
69617116310954407	69617116310954387	16:03:37.944	+42:41:30.252	S3	23.22	1.15	GMOS	0.901	$\circ$	$\circ$	$\times$
69617116310955103	69617116310955133	16:03:37.582	+42:42:06.415	S3	23.82	0.71	GMOS	0.903	$\circ$	$\circ$	—
69617116310955318	69617116310955367	16:03:37.297	+42:42:16.047	S3	22.12	0.98	GMOS	0.901	$\circ$	$\circ$	—
69617116310955586	69617116310955661	16:03:41.623	+42:42:39.416	S3	22.18	0.92	GMOS	0.911	$\circ$	$\circ$	$\times$
69617116310955800	69617116310955864	16:03:36.450	+42:42:44.562	S3	23.17	1.05	GMOS	1.032	$\circ$	—	—
69617116310956200	69617116310956331	16:03:43.304	+42:42:58.427	S3	22.35	0.96	GMOS	0.949	$\circ$	$\times$	—
69617116310965358	69617116310965934	16:03:44.390	+42:49:27.582	S2	22.47	0.79	GMOS	0.897	$\circ$	$\circ$	$\circ$
69617116310965750	69617116310966450	16:03:46.985	+42:49:58.922	S2	23.07	1.20	GMOS	0.915	$\circ$	$\times$	$\times$
69617116310965831	69617116310966562	16:03:38.822	+42:49:57.133	S2	23.33	0.42	GMOS	0.883	$\circ$	$\circ$	$\circ$
69617116310966485	69617116310967306	16:03:55.025	+42:50:33.612	S2	22.23	1.33	GMOS	0.910	$\circ$	$\circ$	—
69617116310940789	69617116310968260	16:03:46.155	+42:51:12.847	S2	23.72	1.20	GMOS	0.944	$\circ$	$\times$	$\times$
69617116310967672	69617116310968440	16:03:54.928	+42:51:19.114	S2	23.72	0.89	GMOS	0.957	$\circ$	—	—
69617116310967867	69617116310968531	16:03:44.318	+42:51:29.132	S2	23.38	1.11	GMOS	0.956	$\circ$	$\times$	$\circ$
69617120605898714	69617120605898781	16:03:54.415	+42:53:31.323	S2	22.37	0.86	GMOS	1.054	$\circ$	—	—
69617120605899000	69617120605899079	16:03:17.325	+42:53:51.542	S1	22.10	1.25	GMOS	0.983	$\circ$	$\circ$	$\times$
69617120605899227	69617120605899310	16:03:22.279	+42:54:05.236	S1	22.93	0.87	GMOS	0.949	$\circ$	$\times$	$\circ$
69617120605899657	69617120605899755	16:03:30.230	+42:54:31.474	S1	22.48	0.52	GMOS	0.891	$\circ$	$\circ$	$\circ$
69617120605899803	69617120605899905	16:03:17.542	+42:54:39.815	S1	23.59	0.97	GMOS	0.987	$\circ$	$\times$	$\times$
69617120605897004	69617120605921438	16:03:11.168	+42:51:51.535	S1	22.68	1.00	GMOS	0.979	$\circ$	$\times$	$\times$
69617120605920797	69617120605922105	16:03:27.971	+42:52:16.585	S1	22.80	1.19	GMOS	0.946	$\circ$	$\times$	$\times$
69617120605920815	69617120605922137	16:03:47.543	+42:52:16.158	S2	23.53	0.42	GMOS	0.954	$\circ$	$\times$	$\circ$
69617120605921069	69617120605922379	16:03:28.520	+42:52:31.786	S1	22.87	0.94	GMOS	1.033	$\circ$	$\circ$	$\circ$
69617120605921347	69617120605922626	16:03:47.224	+42:52:49.718	S2	23.09	1.10	GMOS	1.071	$\circ$	$\times$	—
69617120605921273	69617120605922639	16:03:31.879	+42:52:46.904	S2	22.65	0.82	GMOS	0.989	$\circ$	$\circ$	$\times$
69617120605921450	69617120605922659	16:03:15.737	+42:52:59.612	S1	23.06	0.99	GMOS	0.882	$\circ$	$\circ$	$\circ$
69617120605922162	69617120605923361	16:03:56.630	+42:53:12.514	S2	21.81	1.07	GMOS	0.956	$\circ$	—	—
69617120605922575	69617120605923738	16:03:55.681	+42:53:24.606	S2	21.63	1.58	GMOS	0.987	$\circ$	—	—
69617120605922682	69617120605923835	16:03:16.698	+42:53:38.852	S1	22.68	1.02	GMOS	0.885	$\circ$	$\circ$	$\times$
69617120605922760	69617120605923979	16:03:49.229	+42:53:40.665	S2	22.78	0.89	GMOS	0.899	$\circ$	$\circ$	$\circ$
69617120605922974	69617120605924154	16:03:12.469	+42:53:53.035	S1	21.38	1.16	GMOS	0.846	$\circ$	$\circ$	$\circ$
69617120605923017	69617120605924233	16:03:49.656	+42:53:57.493	S2	21.75	0.73	GMOS	0.918	$\circ$	$\circ$	$\circ$
69617120605924331	69617120605925643	16:03:14.368	+42:55:04.030	S1	23.13	0.65	GMOS	0.888	$\circ$	$\circ$	$\circ$
69617120605924664	69617120605926078	16:03:19.527	+42:55:24.706	S1	22.37	1.04	GMOS	1.024	$\circ$	$\circ$	$\times$
69617120605925260	69617120605926785	16:03:20.346	+42:55:51.081	S1	23.35	0.94	GMOS	0.950	$\circ$	$\times$	$\times$
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69617258044851644	69617258044851490	16:03:02.811	+42:53:06.735	S1	22.00	0.86	GMOS	0.870	$\circ$	$\circ$	—
70399543388150085	70399543388150126	16:03:50.626	+43:41:51.193	N1	22.91	1.03	FOCAS	0.925	$\circ$	$\times$	$\circ$
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70399543388175737	70399543388175424	16:03:52.191	+43:42:20.824	N1	21.12	1.22	FOCAS	0.977	$\circ$	$\circ$	$\times$
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70399543388176189	70399543388175958	16:03:53.693	+43:42:46.050	N1	21.95	1.02	FOCAS	0.919	$\circ$	$\times$	$\times$
70399543388176413	70399543388176183	16:03:42.241	+43:43:07.711	N1	23.05	1.10	GMOS	0.964	$\circ$	$\times$	$\times$
70399543388176687	70399543388176496	16:03:55.607	+43:43:17.332	N1	22.91	1.11	GMOS	0.977	$\circ$	$\times$	$\times$
70399543388176843	70399543388176655	16:03:46.502	+43:43:26.261	N1	22.81	0.69	FOCAS	0.927	$\circ$	$\circ$	$\circ$
70399543388177267	70399543388177159	16:03:59.120	+43:43:48.143	N1	21.40	1.10	FOCAS	0.878	$\circ$	$\circ$	$\times$
70399543388177396	70399543388177276	16:03:51.165	+43:44:00.382	N1	23.16	0.99	GMOS	0.899	$\circ$	$\circ$	$\times$
70399543388177591	70399543388177499	16:04:02.434	+43:44:04.793	N1	22.41	1.07	FOCAS	0.886	$\circ$	$\circ$	$\times$
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70399543388179063	70399543388179128	16:03:55.791	+43:45:10.326	N1	22.88	0.84	GMOS	1.012	$\circ$	—	—
70399543388179264	70399543388179385	16:03:55.148	+43:45:19.152	N1	22.82	0.82	GMOS	0.881	$\circ$	$\circ$	$\times$
70399680827104655	70399680827105070	16:03:36.322	+43:43:11.819	N1	23.62	0.99	GMOS	0.951	$\circ$	$\times$	$\circ$
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70405040946312828	70405040946316492	16:04:04.500	+43:44:46.922	N1	19.96	1.35	FOCAS	0.868	$\circ$	$\circ$	$\times$
70405040946317759	70405040946317910	16:04:07.673	+43:45:37.973	N1	22.18	0.91	FOCAS	0.890	$\circ$	$\circ$	$\circ$

Full text

1 Introduction

The canonical model of the cold dark matter structure formation suggests that small-scale building blocks merge via gravitational interactions and then grow into more massive structures in the universe. Distribution of dark matter deviates from uniformity as time goes on, and large-scale structures of dark matter haloes that consist of voids, filaments, groups, and clusters become prominent gradually (e.g., [Springel et al. (2005), Vogelsberger et al. (2014), Schaye et al. (2015)]). Given that galaxies are hosted in dark matter haloes, galaxy formation and evolution is expected to be closely linked to the growth of large-scale structures. Therefore, it is important to understand how galaxies have evolved while the dark matter haloes grow hierarchically. The cosmological simulations predict that the local clusters consist of galaxies that were located in the wide areas over several tens Mpc scale at high redshifts and then assembled into the high-density regions, although the cluster member galaxies are currently bounded within about Mpc scale (Muldrew et al., 2015; Chiang et al., 2017). This suggests that when we investigate the large-scale structures at higher redshifts, a wider survey volume is essential to reveal the structure formation.

Observationally, the cosmic web structures of galaxies at z $\lesssim$ 1 are revealed by wide-field spectroscopic surveys such as Sloan Digital Sky Survey (SDSS, Blanton et al. (2003); Abazajian et al. (2009)), 2dF Galaxy Redshift Survey (2dFGRS, Colless et al. (2001)), VIMOS VLT Deep Survey (VVDS, Garilli et al. (2008)), VIMOS Public Extragalactic Redshift Survey (VIPERS, Guzzo et al. (2014)), Observations of Redshift Evolution in Large-Scale Environments (ORELSE) Survey (Lubin et al., 2009; Gal et al., 2008), DEEP2 survey (Gerke et al., 2012; Newman et al., 2013), Prism multi-object survey (PRIMUS, Skibba et al. (2014); Coil et al. (2011)), and HectoMAP survey (Hwang et al., 2016; Sohn et al., 2018). Indeed, as seen in cosmological simulation of the cold dark matter model, it is observed that galaxy clusters are located at the intersections of filamentary structures over the several tens Mpc scale and galaxy clusters also compose larger-scale superclusters embedded in the cosmic web (Haynes & Giovanelli, 1986; Nakata et al., 2005; Swinbank et al., 2007; Tanaka et al., 2009; Einasto et al., 2011; Liivamägi et al., 2012; Chow-Martínez et al., 2014; Tully et al., 2014; Nevalainen et al., 2015; Kim et al., 2016; Lietzen et al., 2016; Pompei et al., 2016; Kraan-Korteweg et al., 2017; Haines et al., 2018; Paulino-Afonso et al., 2018; Koyama et al., 2018). As represented by the large-scale structures such as the XLSSsC N01 supercluster at $z\sim 0.3$ (Guglielmo et al., 2018), the BOSS Great Wall at $z\sim 0.47$ (Lietzen et al., 2016), the Cl J021734-0513 supercluster at $z\sim 0.65$ (Galametz et al., 2018), the COSMOS Wall at $z\sim 0.73$ (Iovino et al., 2016), the RCS 2319+00 supercluster (Gilbank et al., 2008), and the Lynx supercluster at $z\sim 1.3$ (Nakata et al., 2005), there are many known structures at high redshifts and they are interesting and important from the perspective of the growth of the structures in the universe. Among the high-$z$ structures surveyed, the CL1604 supercluster at $z\sim 0.9$ investigated by the ORELSE survey is one of the largest complex structures ever known at high redshifts over $\sim 0.5\deg$ ($\sim 26$ comoving Mpc), which consists of three galaxy clusters with $M_{cl}>10^{14}M_{\solar}$ and at least five galaxy groups with $M_{g}>10^{13}M_{\solar}$ (Lemaux et al., 2012; Hung et al., 2019).

At present, there are wide-field imaging surveys covering over several hundreds to about a thousand deg2 such as Pan-STARRS (Chambers et al., 2016), DES (Dark Energy Survey Collaboration et al., 2016), and KiDS (de Jong et al., 2015). Among them, Subaru Strategic Program (SSP) with Hyper Suprime-Cam (HSC, Miyazaki et al. (2018); Komiyama et al. (2018); Kawanomoto et al. (2018); Furusawa et al. (2018)) is an ongoing imaging survey in $grizy$ five bands that combines both a coverage of 1400 deg2 and a depth of $r_{AB}\approx 26$ by making full use of a field of view (FoV) of HSC, 1.77 deg2, and 8-m class Subaru telescope (Aihara et al., 2018b). The HSC-SSP survey provides us with wide-field, deep data set that is essential to investigating large-scale structures at high redshifts. The survey area of the HSC-SSP covers the regions including the already-known structures of the CL1604 supercluster. The HSC data in five broadband of $grizy$ became available in the DR1 S16A internal release in August 2016 (Aihara et al., 2018a). Then, the second public data release (PDR2) of HSC-SSP data111https://hsc.mtk.nao.ac.jp/ssp/ is in May 2019 (Aihara et al., 2019). Interestingly, we have found a strong evidence that the already-known CL1604 supercluster is embedded within more extended large-scale structures (Fig. 1). We are on the verge of revealing a complete picture of the CL1604 supercluster with more than 50 comoving Mpc scale ($>1$deg) at $z\sim 0.9$.

This paper aims to reveal the whole picture of the large-scale structures around the CL1604 by the HSC-SSP imaging data and confirm them spectroscopically, which is described in section 2. This undoubtedly allows us to investigate how the galaxies associated with the large-scale structures have assembled into the denser regions and then evolved along the hierarchical growth of the cosmic web of the underlying dark matter haloes. In section 3, we investigate the stellar populations of red-sequence galaxies, compare the stellar populations between the galaxies in different clusters confirmed and discuss the formation process of the large-scale structure. Finally, our conclusions are presented in section 4. Throughout this paper, magnitudes are presented in the AB system (Oke & Gunn, 1983). The cosmological parameters of H0 = 70 km s*-1* Mpc*-1*, $\Omega_{m}$ = 0.3, and $\Omega_{\Lambda}$ = 0.7 are adopted.

2 Revealing the whole picture of the CL1604 supercluster

2.1 Wide-field imaging survey with Subaru HSC

The HSC data around the CL1604 supercluster are available from both the HSC-SSP S16A internal release and PDR2. Among three layers of the HSC-SSP survey of Wide, Deep, and UltraDeep, the CL1604 supercluster is located in the Wide layer with a field name of HECTOMAP (Aihara et al., 2019). The HECTOMAP field is designed to cover the field of \timeform13h20m $\leqq$ R.A. $\leqq$ \timeform16h40m and \timeform42D $\leqq$ Dec. $\leqq$ \timeform44.5D, i.e. $\sim$ 90 deg2 (Aihara et al., 2018b). In this paper, the limited $\sim 2\times 2$ deg2 area is used to reveal the large-scale structures around the CL1604 supercluster. The HSC-SSP is an on-going survey and the pipeline used for data processing is also still developing (Aihara et al., 2019). The different version of data release means that the data are processed by the different version of the pipeline. The S16A data are processed with the pipeline, hscPipe v4.0.2 (Bosch et al., 2018), and the PDR2 data are processed with the latest pipeline, hscPipe v6 (Bosch et al., 2018; Aihara et al., 2019). Measurement flags given by a version of the pipeline to each object, which are used for e.g., object selection, validation of data quality and reliability of photometry, cannot be necessarily coincident with those by another version of the pipeline. Therefore, HSC data used in this section are extracted from the S16A internal release (Aihara et al., 2018a), not PDR2, to keep a consistency between our original investigation of the galaxy distribution around the CL1604 supercluster and the subsequent target selection for the follow-up spectroscopy. A composite model magnitude named cmodel is used for the photometry of galaxies. The cmodel photometry measures fluxes of objects by simultaneously fitting two components of a de Vaucouleur and an exponential profile convolved with a point-spread function (PSF) (see Bosch et al. (2018) for more details).

The number density map of the photo-$z$ selected galaxies with $z_{ph}=$ 0.85–0.95 (Aihara et al., 2018a; Tanaka et al., 2018) shows the large-scale structures extending in north-to-south direction well beyond the already-known structures of the CL1604 supercluster (figure 1). In the S16A release, the photometric redshifts calculated by six different codes are available. Among them, we use the photo-$z$ calculated by the code named ephor_ab and the photo-$z$ quality is $\sigma_{z}\sim 0.035$ (Tanaka et al., 2018). Note that even if we use the photo-$z$ calculated by any of the other codes, the number density map of galaxies with $z_{ph}=$ 0.85–0.95 is consistent with each other. As shown in figure 1, the structure of the photo-$z$ selected galaxies coincides with the distribution of the galaxy clusters at $z_{ph,cl}$=0.9$\pm$0.1 ($\sigma_{z_{ph,cl}}\sim 0.01$) identified by a red sequence galaxy finder named CAMIRA (Oguri, 2014; Oguri et al., 2018), suggesting that we are seeing the real global structures at $z\sim 0.9$. We also make sure that galaxies with photometric redshifts of 0.70–0.80 or 0.95–1.05 do not show the similar structure of overdensity regions and structures of galaxies with photometric redshifts of 0.75–0.85 or 0.90–1.00 are not so prominent as shown in figure 1. These support that the large-scale structure of galaxies with photometric redshifts of 0.85–0.95 is real. Figure 2 shows the color–magnitude diagram of the galaxies selected in the several overdense regions, where the prominent red sequence is seen compared with that in the general fields. Note that we define the boundary of $r-z=1.7$ to distinguish red-sequence galaxies from star-forming galaxies (figure 2). The concentration of red galaxies also convinces us that the galaxies selected are associated with the large-scale structures including the CL1604 supercluster.

Figure 1 demonstrates that the Subaru HSC has the unique ability to survey the large-scale structures at high redshifts thanks to both the wide-field coverage and the depth of the data. However, these evidences are all based on the photometric data. The spectroscopic confirmation is essential to proceed with further detailed studies on the structure formation and cluster galaxy evolution. To do that, we visually select four regions showing the highest number density based on figure 1; one is to the north of the already-known CL1604 supercluster and three are to the south.

2.2 Spectroscopic confirmation of the large-scale structure

2.2.1 Spectroscopy with Subaru and Gemini-N

We used FOCAS/Subaru (Kashikawa et al., 2002) and GMOS-North/Gemini (Hook et al., 2004) to conduct follow-up observations for galaxies selected in section 2.1 and then confirm four overdense regions associated with the extended large-scale structures at $z\sim 0.9$ (figure 1). The observations were conducted through two programs of S18A-125 for the FOCAS run (PI: T. Kodama) and GN-2018A-FT-107 for the GMOS run (PI: M. Hayashi). The FOCAS run was in classical mode on March 8, 2018 (UT) and the GMOS run was in queue mode on June 14 and 16, 2018 (UT). The multi-object spectroscopy (MOS) observations are summarized in table 2.2.

FOCAS has a circular field of view (FoV) of 6 arcmin in diameter. We used a MOS mask in the FOCAS run to observe the galaxies in the N1 region. Among the candidates within the FoV, red-sequence galaxies with $z-$band mag $<$ 22.5 and $r-z=$ 1.8–2.3 are selected as a first priority and then star-forming galaxies with $r-z<$ 1.6 are selected. Higher priority is given to brighter galaxies. In the mask, 28 slits are allocated to 29 galaxies, i.e., a pair of close targets is observed with a single slit (15 red-sequence galaxies and 14 star-forming galaxies). A slit is allocated to a star for monitoring the sky condition such as seeing and transparency. The slit width is 0.8 arcsec. We use VPH850 grating and SO58 order sorting filter, which provides spectral resolution of $R=750$ for 0.8 arcsec slit and wavelength coverage of 5800–10350 Å. Since 2 pixels are binned along spatial direction in each readout of frame, a pixel scale is 1.19 Å and 0.2076 arcsec per pixel. The spectra in the sequence of the exposures were obtained by dithering by $\pm 1$ arcsec from the central position along the slit. We took seven exposures with 900 sec on-source integration each, and thus the total integration time is 1.75 hours. The seeing ranges between 0.72 and 0.93 arcsec, which are measured from the spectra of the monitoring star. The sky was in almost photometric condition during the observation with this mask.

GMOS has a rectangular FoV of 5.5$\times$5.5 arcmin2. We used a MOS mask in the GMOS run to observe the galaxies in each candidate of galaxy cluster, i.e., 4 MOS masks were used in total. We selected the target galaxies based on the same strategy as in the FOCAS run. We targeted red-sequence galaxies with $z-$band mag $<$ 22.3 and $r-z=$ 1.85–2.3 and star-forming galaxies with $r-z<$ 1.45. As shown in table 2.2, 31–38 slits are allocated to red-sequence galaxies and star-forming galaxies. Furthermore, a slit is allocated to a star in each mask for monitoring the sky condition. The slit width is 1.0 arcsec. We use R400 grating and OG515 blocking filter, which provides spectral resolution of $R=959$ for 1.0 arcsec slit and wavelength coverage of $>$6150 Å. Since 2 pixels are binned along both spatial and spectral direction in each readout of frame, a pixel scale is 1.52 Å and 0.1614 arcsec per pixel. The spectra were obtained by dithering along spectral direction at three central wavelengths of 7800, 7900, and 8000 Å to fill the gap between the detectors. Note that we did not use the Nod & Shuffle mode. Five exposures with 868 sec on-source integration each were taken under the dark night condition of cloud cover CC=50% (clear) and image quality IQ=70 (good), and thus the total integration time is 1.21 hours. The seeing ranges between 0.60 and 0.90 arcsec, which are measured from the spectra of the monitoring star.

Consequently, we observed 164 galaxies (60 red-sequence galaxies and 104 star-forming galaxies) in the north FoV (HSC-N1) and the south FoVs (HSC-S1, HSC-S2, and HSC-S3) in total (see also table 2.2). Among the selected galaxies in each FoV, 58%, 50%, 44%, and 32% of the red-sequence galaxies were observed in the N1, S1, S2, and S3 regions, respectively. For star-forming galaxies, 16%, 17%, 21%, and 16% of the selected galaxies were observed in the N1, S1, S2, and S3 regions, respectively. Although we targeted almost the same fraction of star-forming galaxies in each FoV, the fraction of red-sequence galaxies observed in the S3 FoV is smaller than those in the other FoVs.

2.2.2 Reduction of the spectroscopic data

We used the FOCASRED package, which includes the IRAF222IRAF is distributed by the National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. scripts, for the Subaru/FOCAS data reduction. We also used the Gemini IRAF22footnotemark: 2 package and reduced the Gemini-N/GMOS data with PyRAF333PyRAF is a product of the Space Telescope Science Institute, which is operated by AURA for NASA. according to the GMOS Data Reduction Cookbook hosted on the US National Gemini Office (NGO) pages444http://ast.noao.edu/sites/default/files/GMOS_Cookbook/.

We reduced both the FOCAS and GMOS data in a standard manner. All of bias subtraction, overscan subtraction, flat fielding, distortion correction, wavelength calibration, sky-subtraction, coadd, and flux calibration are conducted in order. The wavelength calibration is based on the bright sky emission lines for FOCAS data and the CuAr spectrum for GMOS data. As a spectroscopic standard star, HZ44 and Feige66 are observed with FOCAS and GMOS, respectively. The spectra of the standard stars are used to correct for telluric absorption. Furthermore, to correct for the flux loss from the slit, we normalize the flux density of the spectrum to the broadband photometry for the red-sequence galaxies with stellar continuum detected. We perform no correction to the star-forming galaxies only detected in emission line, because we do not use the fluxes of emission lines in this paper.

2.2.3 Redshift measurement

The redshifts for red-sequence galaxies are measured based on the stellar continuum of the observed spectra as well as HSC broadband photometry. For the redshift measurement, the optical broadband photometry of the galaxies is extracted from the latest database of HSC-SSP PDR2 (Aihara et al., 2019). The measurement values for the individual galaxies are shown in Appendix B. If required, readers can obtain additional information of the galaxies provided by the HSC-SSP survey in the data release website11footnotemark: 1.

We use the C++ version555https://github.com/cschreib/fastpp of the FAST code (Kriek et al., 2009) to fit the model spectral energy distribution (SED) derived by stellar population synthesis to the observed stellar continuum, where the redshift is one of the free parameters. The model SED templates are generated by the code of Bruzual & Charlot (2003) and the Chabrier (2003) initial mass function (IMF) is assumed. The star formation histories of the exponentially declining model are adopted, where we set an e-folding time of $\mathrm{log}(\tau/\mathrm{yr})=8.5\mbox{--}10.0$ with ${\rm{\Delta}}\mathrm{log}(\tau/\mathrm{yr})\,=0.1$ (Wuyts et al., 2011). Ages of 0.1-–10.0 Gyr are acceptable with a step of ${\rm{\Delta}}\mathrm{log}(\mathrm{age}/\mathrm{yr})=0.1$. The extinction curve of Calzetti et al. (2000) is assumed, and $A_{V}$ ranges from 0.0 to 3.0. Metallicity is fixed to the solar value. The absorption lines of Ca H+K and Balmer series are well fitted by the model SED and useful to determine a redshift. The uncertainty of the redshifts is $\Delta z$=0.001. Among the 60 red-sequence galaxies observed, we obtain the redshifts for 55 galaxies with the stellar continuum detected with enough signal-to-noise ratio. A success rate of the confirmation for red-sequence galaxies is 91.7%. The redshifts for red-sequence galaxies confirmed are listed in table LABEL:tbl:RSGs.

The redshifts for star-forming galaxies are determined based on [O\emissiontypeII]$\lambda 3727$ emission line. Among the 104 star-forming galaxies observed, emission lines are detected from 82 galaxies. The detection of emission lines is visually inspected on both 1D and 2D spectra for the individual galaxies. A success rate of the confirmation for star-forming galaxies is 78.8%. Although 28 galaxies have a single line detected in the spectrum, 54 galaxies have multiple emission lines such as H$\beta$ and/or [O\emissiontypeIII]$\lambda\lambda 4959,5007$ detected. In the case of the single line detected in the individual spectrum, we assume that the emission line is [O\emissiontypeII]$\lambda 3727$. The assumption should be reasonable, because the lines are detected around $\sim$7000 Å in the observed frame and the wavelength of the line detection is consistent with the expectation from the photometric redshifts estimated with the optical broadband photometry. Note that the spectra of 9 galaxies with the only single line detected do not cover the wavelength of H$\beta$ and/or [O\emissiontypeIII]$\lambda\lambda 4959,5007$. The redshifts of the galaxies with multiple emission lines detected are more securely determined. The redshifts are measured from the peak wavelength of the profile of [O\emissiontypeII] emission line derived by Gaussian fitting. The redshifts and the emission lines detected for star-forming galaxies confirmed are listed in table LABEL:tbl:SFGs.

In total, we confirm 137 galaxies at $z$=0.8–1.1 among the 164 galaxies observed. Figure 3 shows the comparison between the photometric redshifts used in the target selection and the spectroscopic redshifts determined by this study. The spectroscopic redshifts tend to be systematically higher than the photometric redshifts by $\sim$0.03, which indicates the importance of follow-up spectroscopic observations. The systematic difference between the photometric and spectroscopic redshifts is similar for both red-sequence galaxies and star-forming galaxies. However, the dispersion of the redshift difference is slightly larger in the star-forming galaxies than the red-sequence galaxies (lower panel of figure 3). The larger dispersion in star-forming galaxies seems to be due to a larger fraction of star-forming galaxies with photometric redshifts underestimated. This systematic offset of photometric redshift towards lower values suggests that our photo-$z$ selection of galaxies can cause a lower completeness of galaxies at lower redshifts among the redshift range of 0.85–0.95. Indeed, we find that among the galaxies confirmed in Lemaux et al. (2012), 67% of the galaxies at spectroscopic redshifts of 0.90–1.0 are selected by our photometric redshift selection, while 45% of the galaxies at spectroscopic redshifts of 0.85–0.90 are selected. This is why in figure 1 the position of the cluster-B at $z=0.865$ is not as overdense as the other clusters at higher redshifts of $z\gtrsim 0.9$ among the clusters presented by Lemaux et al. (2012). We make sure that the spatial distribution of galaxies selected with the photometric redshift range shifted lower by 0.05 is more similar to the structures presented by Lemaux et al. (2012). The accuracy of the photometric redshifts demonstrates that most of member galaxies associated with the galaxy clusters and groups at $z\gtrsim 0.9$ should be surely selected by the criteria we apply.

Figure 4 shows redshift distributions of the red-sequence galaxies (red histogram) and the star-forming galaxies (blue histogram) confirmed in each overdensity region. The peaks of redshift distribution are coincident between red-sequence galaxies and star-forming galaxies. The individual redshift peaks show a wide range of the fraction of red-sequence galaxies. Some overdensity regions show about $\gtrsim$ 50% of the fraction of red-sequence galaxies, while some regions show as small as one-third. In particular, the S3 region shows the strong concentration of star-forming galaxies, suggesting that the cluster is less mature than the others. We note that there is a bias in the target selection where the fraction of red-sequence galaxies observed in the S3 region is smaller than those in the other regions (section 2.2.1). Even if we correct for the bias, the fraction of red-sequence galaxies in the S3 region is not as high as those in the other regions. The difference of the red fraction may reflect the structure formation in this supercluster region, which is discussed in section 3 along with stellar population of red-sequence galaxies.

2.3 Overview of the large-scale structure of CL1604 supercluster

Figure 5 shows the close-up view of spatial distribution, color-magnitude diagram, redshift distribution of the confirmed galaxies, where the symbols are color-coded based on the redshift range. The red-sequence galaxies in the N1 region show three peaks in the distribution, suggesting three clusters/groups are superposed and thus this region looks as if there is prominent structure in the projected 2D map of galaxies (figures 1 and 5). The spatial distribution of galaxies with different redshift ranges cannot be separated. The difference of the redshifts in three peaks corresponds to more than 6000–7000 km s*-1* away from each other. Since a typical velocity dispersion of member galaxies in galaxy clusters is $\sim$ 1000–2000 km s*-1* depending on the cluster richness (e.g., Girardi et al. (1993)), the structures at the different redshifts are likely to be independent. The comoving distance between three peaks with different redshifts is $\sim$ 100 comoving Mpc. The S1 region shows three small peaks. Interestingly, although these are not as prominent as the peaks in the N1 region, the redshifts of the peaks are quite similar. Given that both the structures are located apart by $\sim$43 comoving Mpc from each other, there is likely to be three layers of the large-scale structures at three different redshifts. The galaxies in the regions between the N1 and S1 also show similar redshift distribution (figure 6, Lemaux et al. (2012), Gal et al. (2008)). The south part of S2 that consists of galaxies at $z\approx 0.9$ seems to be connected to the structure of S3. The redshift distribution is similar between the S2 and S3 overdense regions. Therefore, we confirm that this supercluster extends toward not only the north-south direction but also the redshift direction, namely, this is a complex three-dimensional structure more extended than already-known. As shown in figure 6, since there is a large spatial gap between galaxies observed by this study and those confirmed by Lemaux et al. (2012), it is difficult to conclude whether the structures are sheets/filaments or the assembly of galaxy clusters. However, since the local concentrations of galaxies are seen in both of the declination and redshift directions, it must be certain that the galaxy groups/clusters comprise the large scale structures. These results may suggest that the assembly of galaxies associated with the large-scale structures is synchronized over 50 comoving Mpc scale. The structures confirmed are summarized in table 2.2.3.

3 Formation history of the large-scale structure

3.1 Stellar population of red-sequence galaxies

Stellar population of galaxies associated with the large-scale structures are useful for understanding how the galaxies have evolved along the hierarchical growth of host dark matter haloes. To do that, we measure the strength of 4000Å break of stellar continuum, $D_{n}4000$, and strength of Balmer H$\delta$ absorption line. The $D_{n}4000$ index is sensitive to stellar population age in the sense that young galaxies have small 4000Å break and old metal-rich galaxies have large 4000Å break (Kauffmann et al., 2003). The equivalent width of H$\delta$, EW(H$\delta$), is sensitive to the time scale of star formation history in the sense that the absorption is the strongest 0.1–1.0 Gyr after burst of star formation (Kauffmann et al., 2003). Therefore, a diagram of H$\delta$ versus $D_{n}4000$ is widely used to characterize stellar population of galaxies.

We apply the definition by Balogh et al. (1999) for the measurement of $D_{n}4000$ index, where flux densities of stellar continuum at 3850–3950Å and 4000–4100Å are measured as a blue and red side continuum level, respectively. There are several frequently used definitions for EW(H$\delta$) depending on a difference in a wavelength range of continuum level and/or absorption line (Worthey & Ottaviani, 1997; Fisher et al., 1998). Worthey & Ottaviani (1997) define H$\delta_{A}$ as a measurement from the blue continuum of 4041.60–4079.75 Å, the red continuum of 4128.50–4161.00 Å, and the absorption band of 4083.50–4122.25 Å, while Fisher et al. (1998) define it by the blue continuum of 4017.0–4057.0 Å, the red continuum of 4153.0–4193.0 Å, and the absorption band of 4083.5–4122.25 Å. The difference between the two definitions of H$\delta$ is how the continuum level is determined. We apply the definition by Worthey & Ottaviani (1997) for the measurement of EW(H$\delta$) here. The positive value of EW means that H$\delta$ is an absorption line.

Figure 7 shows the measurements of H$\delta$ spectral feature as a function of those of $D_{n}4000$. The error shows the standard deviation of 100 measurements for the individual spectrum with 1$\sigma$ noise added following a normal distribution. We measure the spectral indices for only the 33 red-sequence galaxies with $z$-band mag brighter than 21.5, because the other 22 fainter galaxies have too large uncertainty in the measurement to determine the indices on an individual basis. The limiting magnitude corresponds to stellar mass of $\gtrsim 10^{10.8}$ M\solar, and 85% of the bright galaxies have stellar mass larger than $10^{11}$ M\solar. For comparison with the stellar population synthesis model, model tracks of the Bruzual & Charlot (2003) spectra (updated version 2016666http://www.bruzual.org/bc03/) with different star formation histories are also plotted in figure 7. The star formation histories that we consider are simple stellar population (SSP), exponentially declining one with e-folding time of 0.1 Gyr, 0.3 Gyr, and 1.0 Gyr, and constant star formation. When the $D_{n}4000$ index ranges with the values less than 1.4, which corresponds to age $\lesssim$ 2 Gyr, EW(H$\delta$) can take different values depending on the time scale of star formation. However, after $\sim 2$ Gyr, the tracks with different star formation histories converge. Furthermore, as a reference, the distribution of the line indices of galaxies at $z$=0.04–0.1, which are extracted from the SDSS DR7 catalog of spectrum measurements released by the MPA-JHU777https://wwwmpa.mpa-garching.mpg.de/SDSS/DR7/ is also shown (Kauffmann et al., 2003).

Most of the bright red-sequence galaxies have old ages, although the individual galaxies show large variations on the H$\delta$–$D_{n}4000$ diagram (figure 7). Different symbols denote the different locations on the sky, and different colors reflect different redshifts (the color coding is the same as in figure 5). The red-sequence galaxies in N1 region tend to have larger values of $D_{n}4000$, compared with the galaxies in southern structures. On the other hand, irrespective of the clusters where the galaxies are located, there seems to be weak trend that the red-sequence galaxies associated with the structure at similar redshift (i.e., symbols with the same color) have similar spectral indices. However, the individual measurements of EW(H$\delta$) and $D_{n}4000$ have large uncertainties even for bright galaxies with $z-$band mag $<21.5$. Hereafter, we use composite spectra of the red-sequence galaxies in each sub-structure to investigate the average properties. Then, we discuss formation history of the CL1604 supercluster and stellar populations of the red-sequence galaxies.

To make composite spectra of the red-sequence galaxies in each sub-structure, we first convert the wavelength in observed frame to that in rest frame and then normalize the flux densities of each spectrum at 4000Å. After that, we stack the spectra with an equal weight. We do not use a weight of 1/$\sigma^{2}$ for stacking, because we prefer not to be biased to bright targets. However, even if the spectra are stacked with a weight of 1/$\sigma^{2}$, our discussions in this paper do not change. For this analysis, all of the red-sequence galaxies confirmed are used, namely, including not only bright galaxies but also fainter galaxies with $z-$band mag $>21.5$. The composite spectra of red-sequence galaxies are shown in figure 8, and the number of galaxies stacked for each composite spectrum is shown in table 3.2. The spectral indices of the composite spectra are measured in the same manner as for the spectra of individual galaxies. The strength of H$\delta$ for the composite spectra is also shown as a function of that of 4000Å break in figure 7, while the measurements are listed in table 3.2. In the next section, we discuss the evolution of the large-scale structure around the CL1604 supercluster.

3.2 Implication for the evolution of the large-scale structure

The composite spectra of red-sequence galaxies in the structures at similar redshifts have comparable values of the spectral indices within the errors. All but one (S1_a) indicate the spectra with stellar population older than 2 Gyr, which is comparable with the measurement by Lemaux et al. (2012) for the already known CL1604 clusters. Although the red-sequence galaxies are located in the large-scale structures over 50 Mpc scale, our results suggest that the formation epoch is likely to be similar over the whole of structures.

There are several composite spectra of red-sequence galaxies with spectral indices deviating from the model tracks towards the upper right direction. Since the Balmer H$\delta$ is sensitive to the time scale of star formation, one possibility is that the star-formation activity is dependent on the sub-structures along the growth of the large-scale structure. Figure 4 shows that there is a large variation in the fraction of star-forming galaxies between the substructures. The sub-structures at higher redshift, i.e., the N1_c and S1_c, with the larger deviation may have higher fraction of star-forming galaxies, although the S3_a with the spectral indices on the model tracks also seems to be dominated by star-forming galaxies. We should note that the target selection for our spectroscopic observation can cause a bias in the fraction of the population (see also the discussion of target selection bias in section 2.2.3). However, it is possible that the star formation activity, i.e., the fraction of star-forming galaxies, is different between clusters depending on the assembly process such as timing of accretion into more massive halo and interaction with surroundings. In the model of stellar population synthesis, we assume the SSP or smooth history of star formation declining exponentially with time, which means that the model can not take account of the small starburst occurred recently and/or on-going weak dusty star formation. Recent studies of post-starburst galaxies with strong Balmer absorption which are selected by principal component analysis (PCA) show that there are post-starburst galaxies in red sequence rejuvenated by a minor merger with a gas-rich galaxy and dusty starburst galaxies are a population of major contaminants of post-starburst galaxies (Pawlik et al., 2018, 2019). Given the facts, the second small starburst in the later phase can change the strength of spectral indices (Kauffmann et al., 2003; Marcillac et al., 2006; Lemaux et al., 2012). However, although the 4000Å break (H$\delta$ absorption) gets small (strong) soon after the burst, as time passes, the effect of the second starburst becomes negligible. The spectral indices observed in the continuum spectra cannot be explained by only stellar continuum with multiple starbursts.

If star-formation occurs in the galaxies, emission lines from Hii regions should be superposed on the stellar continuum spectra. In fact, there are composite spectra showing [Oii] emission line (figure 8), suggesting that non-negligible star formation activity. That is, the sample of the red-sequence galaxies can include a large fraction of so-called ‘E+A’ galaxies (Dressler et al., 1999; Poggianti et al., 1999). The PCA for galaxy spectra shows that there are post-starburst galaxies with emission lines (Wild et al., 2007; Pawlik et al., 2018). The red-sequence galaxies do not seem to be purely quiescent galaxies. There is another possibility that the emission lines comes from the existence of active galactic nuclei (Yan et al., 2006). They all suggest that the star formation history of the red-sequence galaxies is not as simple as the assumption in the stellar population synthesis model, but the red-sequence galaxies have more complex, various histories of star formation.

Both the 4000Å break and H$\delta$ absorption are sensitive to metallicity and dust attenuation as well (Kauffmann et al., 2003; Marcillac et al., 2006), in the sense that more metal-rich and/or heavier dust attenuation make the galaxies move slightly towards the upper right direction on the H$\delta$–$D_{n}4000$ diagram. It is probable that dusty starburst galaxies at higher redshifts make a larger contribution to the spectral indices. Several previous studies reports that the dusty starburst galaxies are found in the overdense regions at high redshifts (Geach et al., 2009; Koyama et al., 2010, 2011).

Lemaux et al. (2012) found that the red-sequence galaxies in the central clusters of this large-scale structure have stellar population consistent with that by a single starburst. Therefore, by combining the results with ours, a picture of the formation of the large-scale structure is that the galaxies in the central massive halo are already mature and the galaxies in the course of accretion into the denser region can have a chance of rejuvenation with small multiple starburst showing a complex star formation history.

4 Conclusions

In this paper, we reveal the whole picture of the CL1604 supercluster at $z\sim 0.9$. Although the CL1604 supercluster was already known as a large-scale structure over $\sim 26$ comoving Mpc consisting of three galaxy clusters with $M_{cl}>10^{14}M_{\solar}$ and at least five galaxy groups with $M_{g}>10^{13}M_{\solar}$ (Lemaux et al., 2012), the HSC-SSP deep wide-field imaging survey reveals the larger-scale structures extended to the north and south over more than 50 comoving Mpc scale using galaxies selected with photometric redshifts of $z\sim 0.9$. We then confirm that there are galaxy clusters and/or groups in both the northern and southern side by determining the redshifts of 55 red-sequence galaxies and 82 star-forming galaxies in total. It is found that the already-known CL1604 supercluster is a mere part of larger-scale structures and the tip of the iceberg.

We investigate stellar population of the red sequence galaxies by measuring strength of 4000Å break, $D_{n}4000$, and equivalent width of Balmer H$\delta$ absorption line, EW(H$\delta$). Almost all of the red-sequence galaxies brighter than 21.5 mag in $z$-band show the old stellar population with $D_{n}4000>1.5$, which corresponds to stellar age of $\gtrsim 2$ Gyr. The comparison of composite spectra of red-sequence galaxies in individual clusters show that even if the red-sequence galaxies are located $>$50 Mpc apart, they at a similar redshift have similar stellar population age. However, there is a large variation in the star formation history. Therefore, it is likely that galaxies associated with the large-scale structures at 50 Mpc scale formed at almost the same time, have assembled into the denser regions, and then evolved along the hierarchical growth of the cosmic web.

{ack}

We thank the anonymous referee for providing constructive comments and suggestions. We thank Dr. Brian C. Lemaux and Prof. Lori M. Lubin for kindly providing us with the catalog of the confirmed galaxies used in Lemaux et al. (2012) and Lemaux et al. (2018). We are also grateful to Dr. Brian C. Lemaux for his comments and suggestions. All of them are useful to improve this paper.

This paper is based on data collected at Subaru Telescope and Gemini-North Telescope via the time exchange program between Subaru and the Gemini Observatory and data retrieved from the Hyper Suprime-Cam (HSC) data archive system, which is operated by the Subaru Telescope and Astronomy Data Center at National Astronomical Observatory of Japan.

The HSC collaboration includes the astronomical communities of Japan and Taiwan, and Princeton University. The HSC instrumentation and software were developed by the National Astronomical Observatory of Japan (NAOJ), the Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU), the University of Tokyo, the High Energy Accelerator Research Organization (KEK), the Academia Sinica Institute for Astronomy and Astrophysics in Taiwan (ASIAA), and Princeton University. Funding was contributed by the FIRST program from Japanese Cabinet Office, the Ministry of Education, Culture, Sports, Science and Technology (MEXT), the Japan Society for the Promotion of Science (JSPS), Japan Science and Technology Agency (JST), the Toray Science Foundation, NAOJ, Kavli IPMU, KEK, ASIAA, and Princeton University. The Pan-STARRS1 Surveys (PS1) have been made possible through contributions of the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, Queen’s University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation under Grant No. AST-1238877, the University of Maryland, and Eotvos Lorand University (ELTE). This paper makes use of software developed for the Large Synoptic Survey Telescope. We thank the LSST Project for making their code available as free software at http://dm.lsst.org.

Appendix A The measurement of H$\delta$ with the different spectral index

Here, we use the definition by Fisher et al. (1998) for the measurement of Balmer H$\delta$ absorption line in the composite spectra. This is because Lemaux et al. (2012) use the definition of H$\delta$ for the galaxies in the already-known central structures. Compared with the measurement with the definition by Worthey & Ottaviani (1997), there is a large dispersion in the H$\delta$ strength (figure 9 and table 3.2). As shown in figure 8, the difference between the indices is the wavelength range used to estimate stellar continuum level. Since the index of Fisher et al. (1998) use the wavelength range apart from the H$\delta$ rather than the index of Worthey & Ottaviani (1997), the measurement of H$\delta$ is more sensitive to the stellar continuum, which could cause the larger dispersion. Although the reason of the large dispersion is unknown, there are several sky lines around H$\delta$ and the accuracy of subtraction of the sky lines can affect the signal-to-noise ratio of the continuum spectrum. Note that we did not use the nod and shuffle mode in the spectroscopic observations. Therefore, we use the definition by Worthey & Ottaviani (1997) for the discussion in section 3. The measurements by Lemaux et al. (2012) are plotted in figure 9 for comparison with our results.

Appendix B The catalogs of galaxies confirmed

Tables LABEL:tbl:RSGs and LABEL:tbl:SFGs shows the catalogs of the red-sequence galaxies and star-forming galaxies that are confirmed by the observations, where the information of object_id, coordinates, magnitude, and color are extracted from the HSC-SSP PDR2 data (Aihara et al., 2019). For reference, only object_id of the S16A data is shown. The S16A data are internally released and used in the original target selection described in section 2. For the red-sequence galaxies, the redshift, equivalent width of H$\delta$, and $D_{n}4000$ index are measured from the spectra of individual galaxies in subsections 2.2.3 and 3.1. For the star-forming galaxies, the last column of table LABEL:tbl:SFGs shows the emission lines detected in the spectra of individual galaxies. In the case that a single emission line is detected, we assume that the line is [O\emissiontypeII] and then the redshift is measured. If required, additional information of the individual galaxies can be extracted from the HSC-SSP PDR2 database11footnotemark: 1, based on object_id.