115 research outputs found

    Graphs, Friends and Acquaintances

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    As is well known, a graph is a mathematical object modeling the existence of a certain relation between pairs of elements of a given set. Therefore, it is not surprising that many of the first results concerning graphs made reference to relationships between people or groups of people. In this article, we comment on four results of this kind, which are related to various general theories on graphs and their applications: the Handshake lemma (related to graph colorings and Boolean algebra), a lemma on known and unknown people at a cocktail party (to Ramsey theory), a theorem on friends in common (to distanceregularity and coding theory), and Hallโ€™s Marriage theorem (to the theory of networks). These four areas of graph theory, often with problems which are easy to state but difficult to solve, are extensively developed and currently give rise to much research work. As examples of representative problems and results of these areas, which are discussed in this paper, we may cite the following: the Four Colors Theorem (4CTC), the Ramsey numbers, problems of the existence of distance-regular graphs and completely regular codes, and finally the study of topological proprieties of interconnection networks.Preprin

    Revealing the Landscape of Globally Color-Dual Multi-loop Integrands

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    We report on progress in understanding how to construct color-dual multi-loop amplitudes. First we identify a cubic theory, semi-abelian Yang-Mills, that unifies many of the color-dual theories studied in the literature, and provides a prescriptive approach for constructing DD-dimensional color-dual numerators through one-loop directly from Feynman rules. By a simple weight counting argument, this approach does not further generalize to two-loops. As a first step in understanding the two-loop challenge, we use a DD-dimensional color-dual bootstrap to successfully construct globally color-dual local two-loop four-point nonlinear sigma model (NLSM) numerators. The double-copy of these NLSM numerators with themselves, pure Yang-Mills, and N=4\mathcal{N}=4 super-Yang-Mills correctly reproduce the known unitarity constructed integrands of special Galileons, Born-Infeld theory, and Dirac-Born-Infeld-Volkov-Akulov theory, respectively. Applying our bootstrap to two-loop four-point pure Yang-Mills, we exhaustively search the space of local numerators and find that it fails to satisfy global color-kinematics duality, completing a search previously initiated in the literature. We pinpoint the failure to the bowtie unitarity cut, and discuss a path forward towards non-local construction of color-dual integrands at generic loop order.Comment: 42 pages, 4 figures, ancillary fil

    Kanamycin uptake into Escherichia coli is facilitated by OmpF and OmpC porin channels located in the outer membrane

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    Despite decades of therapeutic application of aminoglycosides, it is still a matter of debate if porins contribute to the translocation of the antibiotics across the bacterial outer membrane. Here, we quantified the uptake of kanamycin across the major porin channels OmpF and OmpC present in the outer membrane of Escherichia coli. Our analysis revealed that, despite its relatively large size, about 10โ€“20 kanamycin molecules per second permeate through OmpF and OmpC under a 10 ฮผM concentration gradient, whereas OmpN does not allow the passage. Molecular simulations elucidate the uptake mechanism of kanamycin through these porins. Whole-cell studies with a defined set of E. coli porin mutants provide evidence that translocation of kanamycin via porins is relevant for antibiotic potency. The values are discussed with respect to other antibiotics

    ๋‹ค์ฒœ์ฒด ๋ถ„๊ด‘ ๊ด€์ธก ๋ฐ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ๊ด€์ธก์ž๋ฃŒ๋ฅผ ์ด์šฉํ•œ ๊ณ  ์ ์ƒ‰์ด๋™ ์€ํ•˜์˜ ํŠน์„ฑ ๋ฐ ํ™˜๊ฒฝ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ๋ฌผ๋ฆฌยท์ฒœ๋ฌธํ•™๋ถ€(์ฒœ๋ฌธํ•™์ „๊ณต), 2021.8. ์ž„๋ช…์‹ .ํ˜„๋Œ€ ์šฐ์ฃผ๋ก ์—์„œ ์ •์„ค๋กœ ๋ฐ›์•„๋“ค์—ฌ์ง€๊ณ  ์žˆ๋Š” ํ‘œ์ค€ ์šฐ์ฃผ ๋ชจํ˜•์ธ `์ฐจ๊ฐ€์šด ์•”ํ‘๋ฌผ์งˆ ์šฐ์ฃผ(ฮ›CDM ์šฐ์ฃผ ๋ชจํ˜•)' ์—์„œ๋Š” 138์–ต ๋…„ ์ „ ๋Œ€ํญ๋ฐœ(Big Bang, ์ดํ•˜ `๋น…๋ฑ…')์„ ํ†ตํ•ด ์šฐ์ฃผ๊ฐ€ ํ˜•์„ฑ๋˜์—ˆ๊ณ , ์šฐ์ฃผ ๋Œ€๋ถ€๋ถ„์˜ ์งˆ๋Ÿ‰์ด ์•”ํ‘๋ฌผ์งˆ(Dark Matter)๊ณผ ์•”ํ‘์—๋„ˆ์ง€(Dark Energy)๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ๋‹ค๊ณ  ์„ค๋ช…ํ•œ๋‹ค. 1965๋…„ ์•„๋…ธ ํŽœ์ง€์–ด์Šค์™€ ๋กœ๋ฒ„ํŠธ ์œŒ์Šจ์ด ๋ฐœ๊ฒฌํ•œ 3.7K ์šฐ์ฃผ๋ฐฐ๊ฒฝ๋ณต์‚ฌ(Cosmic Microwave Background Radiation)๊ฐ€ ๋น…๋ฑ… ์ด๋ก ์„ ์ง€์ง€ํ•˜๋Š” ํ˜„์žฌ์˜ ์šฐ์ฃผ๋ก  ๋ชจํ˜•์— ํž˜์„ ์‹ค์–ด ์ฃผ์—ˆ๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๋น…๋ฑ… ์งํ›„ ์žˆ์—ˆ๋˜ ์•„์ฃผ ์ž‘์€ ๋ฌผ์งˆ ์š”๋™ ๋•Œ๋ฌธ์— ์šฐ์ฃผ๊ฐ€ ๋น„ ๋“ฑ๋ฐฉ์ ์ธ ๋ฌผ์งˆ ๋ถ„ํฌ๋ฅผ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ฒŒ ๋˜์—ˆ๋‹ค. ๊ณ„์ธต์  ์šฐ์ฃผ ๊ตฌ์กฐ ์„ฑ์žฅ ๋ชจ๋ธ์—์„œ๋Š” ์ด๋ ‡๊ฒŒ ์ƒ๊ฒจ๋‚œ ์šฐ์ฃผ ์ดˆ๊ธฐ์˜ ๋ฌผ์งˆ ์š”๋™์ด ์ฃผ๋ณ€ ์š”๋™๊ณผ์˜ ๋ณ‘ํ•ฉ ๊ณผ์ •์„ ํ†ตํ•ด ์„ฑ์žฅํ•˜๊ณ , ์ตœ์ข…์ ์œผ๋กœ ํ˜„์žฌ์˜ ์šฐ์ฃผ์—์„œ๋Š” ์ดˆ๊ธฐ์˜ ๋ฌผ์งˆ ์š”๋™์˜ ์ •์ ์— ๊ฐ€์žฅ ํฌ๊ณ  ๋ฌด๊ฑฐ์šด ๊ตฌ์กฐ์ธ ์€ํ•˜๋‹จ๊ณผ ๊ฐ™์€ ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ๊ฐ€ ๋งŒ๋“ค์–ด์ง„๋‹ค๊ณ  ์„ค๋ช…ํ•˜๊ณ  ์žˆ๋‹ค. ์€ํ•˜๋‹จ์€ ์šฐ์ฃผ์—์„œ ๋ณผ ์ˆ˜ ์žˆ๋Š” ์ค‘๋ ฅ์œผ๋กœ ๋ฌถ์ธ ๊ฐ€์žฅ ํฐ ์ฒœ์ฒด๋กœ, ์šฐ์ฃผ ๊ตฌ์กฐ ์ง„ํ™”์™€ ์€ํ•˜ ์ง„ํ™”๋ฅผ ๋™์‹œ์— ์—ฐ๊ตฌํ•  ์ˆ˜ ์žˆ๋Š” ์ค‘์š”ํ•œ ์ฒœ์ฒด์ด๋‹ค. ์ ๊ฒŒ๋Š” ์ˆ˜์‹ญ ๊ฐœ์—์„œ ๋งŽ๊ฒŒ๋Š” ์ˆ˜๋ฐฑ ๊ฐœ์˜ ์€ํ•˜๊ฐ€ ์ค‘๋ ฅ์œผ๋กœ ๋ฌถ์—ฌ์žˆ๋Š” ์€ํ•˜๋‹จ์€ ๊ทธ ์งˆ๋Ÿ‰์ด ํƒœ์–‘์งˆ๋Ÿ‰์˜ 100 ์กฐ ๋ฐฐ ์ด์ƒ(> 10^{14} M_sun)์„ ๊ฐ€์ง€๋Š” ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ์ด๋ฉฐ, ์šฐ์ฃผ์˜ ์•”ํ‘๋ฌผ์งˆ ๋ถ„ํฌ๋ฅผ ๊ฐ„์ ‘์ ์œผ๋กœ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ๋Š” ์ค‘์š”ํ•œ ๋Œ€์ƒ์ด๋‹ค. ์šฐ์ฃผ ์ง„ํ™”์˜ ๊ณ„์ธต ์„ฑ์žฅ์˜ ๊ฐ€์žฅ ๊ผญ๋Œ€๊ธฐ์— ์žˆ๋Š” ์€ํ•˜๋‹จ์˜ ์ˆ˜๋ฐ€๋„๋‚˜ ์งˆ๋Ÿ‰์€ ํ‘œ์ค€ ์šฐ์ฃผ ๋ชจํ˜•์˜ ์ƒ์ˆ˜๋“ค๊ณผ ๋ฐ€์ ‘ํ•œ ๊ด€๊ณ„๊ฐ€ ์žˆ์–ด (Grossi et al. 2017; Peacoak et al. 2010) ์€ํ•˜๋‹จ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํ‘œ์ค€ ์šฐ์ฃผ ๋ชจํ˜•์—์„œ ์•”ํ‘๋ฌผ์งˆ์˜ ์ดˆ๊ธฐ ์กฐ๊ฑด์„ ํ†ต์ œํ•˜๋Š” ์šฐ์ฃผ์ƒ์ˆ˜๋ฅผ ๊ฒ€์ฆ, ๋ณด์™„, ์ˆ˜์ •ํ•  ์ˆ˜ ์žˆ๋‹ค(Einasto et al. 2011; Lim & Lee 2014). ฮ›CDM ์šฐ์ฃผ ๋ชจ๋ธ์—์„œ์˜ ์˜ˆ์ธก๊ณผ๋Š” ๋‹ค๋ฅด๊ฒŒ ์ ์ง€ ์•Š์€ ์ˆ˜์˜ ๋ฌด๊ฑฐ์šด ์€ํ•˜๋“ค๊ณผ ์€ํ•˜๋‹จ๋“ค์ด ์šฐ์ฃผ ์ดˆ๊ธฐ์—์„œ ๋ฐœ๊ฒฌ๋œ ์—ฐ๊ตฌ ์‚ฌ๋ก€๋“ค์ด ์†์† ๋“ฑ์žฅํ•˜๋ฉด์„œ(Kang & Im 2009; Durret et al. 2011; Toshikawa et al. 2012), ฮ›CDM ์šฐ์ฃผ ๋ชจ๋ธ์˜ ๊ฒ€์ฆ์„ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์šฐ์ฃผ ์‹œ๊ธฐ์—์„œ์˜ ๋” ๋งŽ์€ ์€ํ•˜๋‹จ ๋Œ€์ƒ๋“ค์„ ํ™•๋ณดํ•  ํ•„์š”์„ฑ์ด ๋Š์ž„์—†์ด ๋Œ€๋‘๋˜์—ˆ๋‹ค. ์€ํ•˜ ์ง„ํ™”์™€ ํ™˜๊ฒฝ ์—ฐ๊ตฌ์˜ ๊ด€์ ์—์„œ ์€ํ•˜๋‹จ, ์€ํ•˜๊ตฐ ํ˜น์€ ์ดˆ์€ํ•˜๋‹จ, ํ•„๋ผ๋ฉ˜ํŠธ, ๊ณต๋™๊ณผ ๊ฐ™์€ ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ๋Š” ์€ํ•˜๋“ค์ด ๋‹ค์–‘ํ•œ ํ™˜๊ฒฝ ์กฐ๊ฑด์—์„œ ์–ด๋–ป๊ฒŒ ์ง„ํ™”ํ•˜๋Š”์ง€ ์‚ดํŽด๋ณผ ์ˆ˜ ์žˆ๋Š” ์ข‹์€ ์šฐ์ฃผ๋ก ์  ์‹คํ—˜์‹ค์ด๋‹ค. ์šฐ์ฃผ๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ์€ํ•˜๋“ค์˜ ์ง„ํ™”๋ฅผ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์€ ํ˜„๋Œ€ ์ฒœ๋ฌธํ•™์˜ ์ค‘์š”ํ•œ ์—ฐ๊ตฌ์ฃผ์ œ์ด๋‹ค. ์€ํ•˜๋Š” ๋‚ด๋ถ€์  ์š”์ธ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์ฃผ๋ณ€ ์€ํ•˜์™€์˜ ์ƒํ˜ธ์ž‘์šฉ์ด๋‚˜ ๋ณ‘ํ•ฉ ๊ณผ์ •์„ ๊ฒช์œผ๋ฉฐ ์„ฑ์žฅํ•ด ๋‚˜๊ฐ„๋‹ค๋Š” ๊ฒƒ์€ ๋น„๊ต์  ์ž˜ ์•Œ๋ ค์ง„ ์‚ฌ์‹ค์ด๋‹ค. ์ด๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ๊ฐ€์žฅ ๋Œ€ํ‘œ์ ์ธ ์ƒ๊ด€๊ด€๊ณ„ ์ค‘ ํ•˜๋‚˜๋Š” ๊ฐ€๊นŒ์šด ์šฐ์ฃผ ์€ํ•˜๋‹จ์—์„œ, ์ค‘์‹ฌ๋ถ€์— ์žˆ๋Š” (๋ฐ€๋„๊ฐ€ ๋†’์€ ์ง€์—ญ์˜) ์€ํ•˜๋“ค์ด ๋” ๋ฌด๊ฒ๊ณ  ํฌ๊ณ  ๋ถ‰์€ ์กฐ๊ธฐํ˜• ์€ํ•˜ ํ˜•ํƒœ๋ฅผ ๋ณด์ธ๋‹ค๋Š” ์—ฐ๊ตฌ(์˜ˆ: Park2009ApJ)๊ฐ€ ์žˆ๋‹ค. ๋ฐ˜๋ฉด, ์ ์ƒ‰์ด๋™ 1 ์ด์ƒ์˜ ์ข€ ๋” ๋จผ ์šฐ์ฃผ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์—ญ์ „๋˜๋Š” ์–‘์ƒ์ด ๋ณด์ธ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋Š”๋ฐ (Elbaz et al. 2007), ์ด ์—ญ์ „ ํ˜„์ƒ์ด ์–ด๋Š ์šฐ์ฃผ ์‹œ๊ธฐ์— ์ผ์–ด๋‚˜๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ์šฐ์ฃผ ์ „๋ฐ˜์— ๊ฑธ์ณ ์ผ์–ด๋‚˜๋Š” ์ง„ํ™”์  ์š”์ธ์ธ์ง€, ๋‹ค๋ฅธ ๋ฌผ๋ฆฌ๋Ÿ‰์— ์˜ํ•œ ์˜ํ–ฅ์€ ์—†๋Š”์ง€์— ๋Œ€ํ•œ ์‹ฌ์ธต ์—ฐ๊ตฌ๋Š” ์•„์ง ๋ถ€์กฑํ•œ ์ƒํ™ฉ์ด๋‹ค(์˜ˆ: Hwang2019MNRAS). ์ด์— ๋”ฐ๋ผ ์ดˆ๊ธฐ ์šฐ์ฃผ๋ฅผ ๋น„๋กฏํ•œ ๋‹ค์–‘ํ•œ ์šฐ์ฃผ ์‹œ๊ธฐ์—์„œ์˜ ์€ํ•˜๋‹จ ๋Œ€์ƒ๋“ค์„ ํ™•๋ณดํ•˜๋Š” ๊ฒƒ๊ณผ ๋™์‹œ์—, ๋‹ค์–‘ํ•œ ์€ํ•˜๋‹จ์˜ ๋ฌผ๋ฆฌ๋Ÿ‰๊ณผ ํ™˜๊ฒฝ ์ง„ํ™”์˜ ์‹ฌ์ธต์  ์—ฐ๊ตฌ์˜ ํ•„์š”์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๊ธฐ์ˆ ๊ณผ ์žฌ์›์˜ ํ•œ๊ณ„๋กœ ์ œํ•œ์ ์ธ ์—ฐ๊ตฌ๋งŒ ์ˆ˜ํ–‰๋˜์–ด์™”๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” ์ฒซ ๋ฒˆ์งธ ์—ฐ๊ตฌ ์ฃผ์ œ๋กœ ๋ถ๋ฐ˜๊ตฌ 8.75 deg^2 ์˜์—ญ์˜ ELAIS-N1 ํ•˜๋Š˜ ์˜์—ญ์—์„œ ๊ด‘์‹œ์•ผ ๋‹คํŒŒ์žฅ ๊ด€์ธก์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ ์ƒ‰์ด๋™(redshift) 0.5๋ถ€ํ„ฐ 1.5๊นŒ์ง€ ๋‹ค์–‘ํ•œ ์šฐ์ฃผ ์‹œ๊ธฐ์—์„œ ์ƒˆ๋กœ์šด ์€ํ•˜๋‹จ ๋ฐ ์ดˆ์€ํ•˜๋‹จ์„ ๋ฐœ๊ฒฌํ•˜๋Š” ํƒ์‚ฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ๋กœ๋ถ€ํ„ฐ ์ƒˆ๋กญ๊ฒŒ ๋ฐœ๊ฒฌ๋œ 1,099๊ฐœ์˜ ์€ํ•˜๋‹จ ํ›„๋ณด ๋Œ€์ƒ์— ๋Œ€ํ•œ ์ฒœ์ฒด ๋ชฉ๋ก์„ ์ œ์ž‘ํ•œ ๋’ค ๊ทธ๋“ค์˜ ์ง„ํ™” ํŠน์„ฑ์„ ์—ฐ๊ตฌํ•ด ์€ํ•˜ ์ง„ํ™”์— ๋Œ€ํ•œ ์‹ค๋งˆ๋ฆฌ๋ฅผ ์ œ์‹œํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋ณธ ์—ฐ๊ตฌ๋กœ๋ถ€ํ„ฐ ๊ธฐ์กด์— ์•Œ๋ ค์ง€์ง€ ์•Š์€ ์ ์ƒ‰์ด๋™ 0.9 ๊ทผ์ฒ˜์˜ ~ 100 Mpc ํฌ๊ธฐ์˜ ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ (์ดˆ์€ํ•˜๋‹จ)๋ฅผ ๋ฐœ๊ฒฌํ–ˆ๋‹ค. EN1LSS (ELAIS-N1 Large Scale Structure) ๋กœ ๋ช…๋ช…ํ•œ ์ด ๊ตฌ์กฐ๋Š” Swinbank2007MNRAS ์—์„œ ๋ฐœ๊ฒฌํ•œ 5๊ฐœ์˜ ์€ํ•˜๋‹จ์œผ๋กœ ์ด๋ฃจ์–ด์ง„ ์ดˆ์€ํ•˜๋‹จ๋ณด๋‹ค ํ›จ์”ฌ ํฌ๊ณ  ๋ฌด๊ฑฐ์šด ๊ตฌ์กฐ๋กœ ๊ด€์ธก๋œ๋‹ค๋Š” ์ ์—์„œ ๋งค์šฐ ํฅ๋ฏธ๋กญ๋‹ค. ๋˜ํ•œ, ์ด ๊ตฌ์กฐ๋Š” ELAIS-N1 ์˜์—ญ ํฌ๊ธฐ์˜ ํ•˜๋Š˜์—์„œ ๊ธฐ์กด ์šฐ์ฃผ๋ก ์  ๋ชจ๋ธ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์—์„œ ์˜ˆ์ธก๋˜๋Š” ์ ์ƒ‰์ด๋™ 0.8 < z < 1.2 ์˜ ์ดˆ์€ํ•˜๋‹จ ๊ฐœ์ˆ˜์ธ 0.28๊ฐœ๋ฅผ ํ›จ์”ฌ ์›ƒ๋„๋Š” ๊ฒƒ์œผ๋กœ, ์ดˆ์€ํ•˜๋‹จ์˜ ๊ฒ€์ฆ ๋ฐ ์ถ”๊ฐ€ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์ƒˆ๋กญ๊ฒŒ ๋ฐœ๊ฒฌํ•œ ์ดˆ์€ํ•˜๋‹จ์— ๋Œ€ํ•ด ๋ฏธ๊ตญ ์• ๋ฆฌ์กฐ๋‚˜์˜ 6.5 m Multi Mirror Telescope (MMT) ๋ง์›๊ฒฝ์˜ ๋‹ค ์ฒœ์ฒด ๋ถ„๊ด‘๊ธฐ์ธ Hectospec์„ ํ™œ์šฉํ•˜์—ฌ ๋‹ค์ฒœ์ฒด ๋ถ„๊ด‘๊ด€์ธก์„ ์ˆ˜ํ–‰ํ–ˆ์œผ๋ฉฐ, ์ดˆ์€ํ•˜๋‹จ์„ ์ด๋ฃจ๋Š” ์€ํ•˜์™€ ๊ทธ ์ฃผ๋ณ€์˜ 110๊ฐœ ์€ํ•˜์— ๋Œ€ํ•œ ๋ถ„๊ด‘ ๊ฒ€์ฆ์„ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ํ•™์œ„ ๋…ผ๋ฌธ ์—ฐ๊ตฌ ์ฃผ์ œ๋กœ ๋„“๊ณ  ๊นŠ์€ ๊ฐ€์‹œ๊ด‘-์ ์™ธ์„  ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•ด SA22 ์˜์—ญ์—์„œ Kim et al. 2016 ์—์„œ ๋ฐœ๊ฒฌํ•œ ์€ํ•˜๋‹จ๊ณผ ์ดˆ์€ํ•˜๋‹จ ํ›„๋ณด๊ตฐ๋“ค์˜ ํ›„๋ณด ๊ฒ€์ฆ ๋ฐ ๋ฌผ๋ฆฌ๋Ÿ‰ ๋„์ถœ์˜ ํ™•์žฅ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์น ๋ ˆ Magellan ๋ง์›๊ฒฝ์˜ ๋‹ค์ฒœ์ฒด ๋ถ„๊ด‘๊ธฐ(IMACS)๋ฅผ ํ™œ์šฉํ•˜0๋ฉฐ 2016๋…„๋ถ€ํ„ฐ ์ด 8๊ฐœ ๊ตฌ์—ญ, ์ด 1,500๊ฐœ๊ฐ€๋Ÿ‰์˜ ์€ํ•˜๋‹จ ์€ํ•˜ ๋ฐ ํ•„๋“œ ์€ํ•˜์— ๋Œ€ํ•ด ๋ถ„๊ด‘ ๊ด€์ธก ๋ฐ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์•ž์„œ Kim et al. 2016์—์„œ ๋ถ„๊ด‘ ๊ด€์ธก์ž๋ฃŒ๋กœ ํ™•์ธ๋œ 3๊ฐœ์˜ ๋ฌด๊ฑฐ์šด ์€ํ•˜๋‹จ๋“ค์€ ์ ์ƒ‰์ด๋™ 0.91์—์„œ ๊ณต๊ฐ„์ƒ์œผ๋กœ 100Mpc์— ๊ฑธ์ณ ๋ถ„ํฌํ•˜๋Š” ์ดˆ์€ํ•˜๋‹จ์„ ์ƒˆ๋กญ๊ฒŒ ๋ฐœ๊ฒฌํ–ˆ๋Š”๋ฐ, ์€ํ•˜๋‹จ ๊ตฌ์„ฑ ์€ํ•˜๋“ค ์‚ฌ์ด์˜ ์ ์ƒ‰์ด๋™ ํŽธ์ฐจ๊ฐ€ ฮ”z ~ 0.01 ์— ๋ถˆ๊ณผํ•ด ์ƒ๋‹นํžˆ ๋ฌด๊ฑฐ์šด ๊ตฌ์กฐ๋ผ๋Š” ๊ฒƒ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ถ”๊ฐ€ ํ™•์žฅํ•œ ๋ถ„๊ด‘ ๊ด€์ธก ๋ฐ์ดํ„ฐ๋“ค๋กœ๋ถ€ํ„ฐ ์šฐ๋ฆฌ๋Š” 34๊ฐœ์˜ ์€ํ•˜๋‹จ์˜ ๋ถ„๊ด‘ ๊ฒ€์ฆ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ , ์ด๋“ค์€ ๋” ํฐ ์ดˆ์€ํ•˜๋‹จ์˜ ํ˜•ํƒœ๋กœ ๋ถ„ํฌํ•˜๋Š” ๊ฒƒ์„ ๋ณผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ฮ›CDM ์šฐ์ฃผ ๋ชจํ˜• ์ด๋ก ์œผ๋กœ๋ถ€ํ„ฐ ์˜ˆ์ธก๋˜๋Š” SA22 ์˜์—ญ์˜ ์ดˆ์€ํ•˜๋‹จ ๊ฐœ์ˆ˜๋Š” ์•ฝ 1๊ฐœ์ด๋‹ค. ํ•˜์ง€๋งŒ Kim et al. 2016์—์„œ ๋ฐœ๊ฒฌํ•œ ~15 Mpc ๊ทœ๋ชจ์˜ ์ดˆ์€ํ•˜๋‹จ๊ณผ ๋”๋ถˆ์–ด, ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋” ๋„“์€ ์˜์—ญ์—์„œ ์ตœ์†Œ 12๊ฐœ ์ด์ƒ์˜ ์€ํ•˜๊ตฐ, ์€ํ•˜๋‹จ๋“ค์ด ๊ตฌ์„ฑํ•˜๋Š” ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ๊ฐ€ ์กด์žฌํ•œ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. SA22 ์˜์—ญ์˜ ๋‹ค๋ฅธ ๋ถ„๊ด‘ ํƒ์‚ฌ์ž๋ฃŒ์ธ VVDS, VIPERS๊ฐ€ ๋‹ค๋ฃจ์ง€ ์•Š์•˜๋˜ ์˜์—ญ์—์„œ ๋ฌด๊ฑฐ์šด ์€ํ•˜๋‹จ ํ›„๋ณด๋“ค์„ ๋ฐœ๊ฒฌํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. VVDS, VIPERS ์ž๋ฃŒ์™€ ํ•จ๊ป˜ ํ•ด๋‹น ์ง€์—ญ์˜ ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ ๋ชฉ๋ก์„ ์ž‘์„ฑํ•˜์˜€์œผ๋ฉฐ, ์ถ”ํ›„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ถ„์„ ๋“ฑ์„ ํ†ตํ•ด ฮ›CDM ์šฐ์ฃผ ๋ชจํ˜•์„ ๊ฒ€์ฆํ•ด์•ผ ํ•  ํ•„์š”์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‚˜์•„๊ฐ€ ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋ถ„๊ด‘ ๊ฒ€์ฆํ•œ 34๊ฐœ ์€ํ•˜๋‹จ๋“ค์„ ์ด์šฉํ•ด ์€ํ•˜ ํ™˜๊ฒฝ๊ณผ ์€ํ•˜๋‹จ์˜ ๋ฌผ๋ฆฌ๋Ÿ‰๊ณผ์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ์šฐ์„  ์ƒˆ๋กญ๊ฒŒ ๋ฐœ๊ฒฌํ•œ ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ ์•ˆ์—์„œ์˜ ์€ํ•˜ ์œ„์น˜์™€ ์€ํ•˜์˜ ์งˆ๋Ÿ‰, ์ƒ‰์ง€์ˆ˜, ๋‹จ์œ„ ์งˆ๋Ÿ‰ ๋‹น ๋ณ„ ํƒ„์ƒ๋ฅ ๊ณผ์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์™€ ๋น„์Šทํ•˜๊ฒŒ, ๋ฌด๊ฑฐ์šด ์€ํ•˜๋“ค์€ ์ฃผ๋กœ ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ์˜ ๊ฐ€์žฅ ๋ฐ€์ง‘๋œ ์ง€์—ญ์— ๋ถ„ํฌํ•˜์˜€์œผ๋‚˜, ๋‹จ์œ„ ์งˆ๋Ÿ‰ ๋‹น ๋ณ„ ํƒ„์ƒ๋ฅ ์€ ๊ฐ€์žฅ ๋ฐ€์ง‘๋œ ์ง€์—ญ์—์„œ ํ•ญ์ƒ ๋‚ฎ์€ ๊ฐ’์„ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฝํ–ฅ์„ฑ์— ๋Œ€ํ•ด ์ข€ ๋” ์กฐ์‚ฌํ•˜๊ธฐ ์œ„ํ•ด ์šฐ๋ฆฌ๋Š” ๊ฐ ์€ํ•˜๋‹จ ๋‚ด๋ถ€์˜ ๋ณ„ ํƒ„์ƒ์ด ๋๋‚œ ์€ํ•˜ (Quiescent galaxy) ๋น„์œจ (f_{Quies.}) ์„ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ๋ฅผ ์ด๋ฃจ๋Š” ์€ํ•˜๋‹จ์˜ f_{Quies.}์ด ๊ต‰์žฅํžˆ ๋„“์€ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ๊ณผ ์ค‘๊ฐ„ ์ •๋„์˜ ๊ฐ’์„ ๊ฐ€์ง„๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ•˜์˜€๋‹ค. ๋ณ„ ํƒ„์ƒ์ด ๋๋‚œ ์€ํ•˜ ๋น„์œจ, f_{Quies.}์˜ ๋‹ค์–‘์„ฑ์„ ์ผ์œผํ‚ค๋Š” ์›์ธ์„ ์กฐ์‚ฌํ•˜๊ธฐ ์œ„ํ•ด ์šฐ๋ฆฌ๋Š” ์ฃผ๋ณ€ ๊ตฌ์กฐ์™€ ์–ผ๋งˆ๋‚˜ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ๋Š”์ง€๋ฅผ ๋ณด์—ฌ์ค„ ์ˆ˜ ์žˆ๋Š” ์ฒ™๋„์ธ, f_{FoF} ์„ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์ฃผ๋ณ€ ๊ตฌ์กฐ์™€ ๋” ์—ฐ๊ฒฐ๋œ ์€ํ•˜๋‹จ์ผ์ˆ˜๋ก ๋” ๋‚ฎ์€ f_{Quies.}์„ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ–ˆ๋‹ค. ๊ทธ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ๋ฅผ ์ด๋ฃจ๋Š” 12๊ฐœ ์€ํ•˜๋‹จ ๋‚ด๋ถ€์˜ ์ด ๋ณ„ ํƒ„์ƒ๋ฅ ์„ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์—ญ์‹œ ๋‹ค์–‘ํ•œ ๋ถ„ํฌ๋ฅผ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด 12๊ฐœ ์€ํ•˜๋‹จ๋“ค์— ๋Œ€ํ•œ ํ‰๊ท ๊ฐ’์„ ๋‹ค๋ฅธ ์—ฐ๊ตฌ๋“ค์—์„œ์˜ ๊ด€์ธก ๋ฐ ๋ชจ๋ธ๊ฐ’๊ณผ ๋น„๊ตํ•˜์˜€์„ ๋•Œ, ์ผ๋ฐ˜์ ์ธ ์€ํ•˜๋‹จ ์ˆ˜์ค€๋ณด๋‹ค ๋” ๋†’๊ณ , ์€ํ•˜๊ตฐ ๊ณผ ๋น„์Šทํ•œ ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ข…ํ•ฉํ•˜๋ฉด, ์šฐ์ฃผ ๊ฑฐ๋Œ€๊ตฌ์กฐ ์ฆ‰, ์ดˆ์€ํ•˜๋‹จ๊ณผ ๊ฐ™์ด ์„œ๋กœ ์—ฐ๊ฒฐ๋œ ๊ตฌ์กฐ์— ๋†“์ธ ์€ํ•˜๋‹จ๋“ค์€ ์ฃผ๋ณ€๋ถ€๋กœ๋ถ€ํ„ฐ์˜ ์ง€์†์ ์ธ ๋ณ„ ํƒ„์ƒ ์€ํ•˜์˜ ์œ ์ž…์œผ๋กœ ์ธํ•ด ์ง€์†์ ์ธ ๋ณ„ ํƒ„์ƒ์ด ์ด๋ฃจ์–ด์ง„๋‹ค๋Š” 'Web feeding Model'์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์ œ์ž„์Šค ํด๋Ÿฌํฌ ์„œ๋ธŒ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ๋ง์›๊ฒฝ(James Clerk Maxwell Telescope)์˜ SCUBA-2๋ฅผ ์ด์šฉํ•œ JWST-NEP ์ง€์—ญ์˜ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์€ํ•˜ ๋ชฉ๋ก ํŽธ์ฐฌ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์€ํ•˜(Sub-milimeter Galaxies; SMG) ๋Š” ์›์ ์™ธ์„ ์—์„œ ๋ฐฉ์ถœ๋œ ๋น›์ด ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์˜์—ญ์—์„œ ๊ด€์ธก๋˜์–ด ๋ณด์ด๋Š” ์€ํ•˜๋กœ ๋ณ„ ํƒ„์ƒ์ด ํ™œ๋ฐœํ•˜๋ฉด์„œ๋„ ๋จผ์ง€์— ์˜ํ•œ ์†Œ๊ด‘์ด ํฐ ๋Œ€์ƒ๋“ค๋กœ, ์€ํ•˜ ์ง„ํ™”์  ๊ด€์ ์—์„œ ํ˜„์žฌ ์šฐ์ฃผ์˜ ๋ณ„ ํƒ„์ƒ์ด ๋๋‚œ ๋ฌด๊ฑฐ์šด ํƒ€์›์€ํ•˜๋“ค์˜ ๊ณผ๊ฑฐ ๋ชจ์Šต์„ ๋Œ€๋ณ€ํ•œ๋‹ค๊ณ  ์˜ˆ์ƒ๋˜๋Š” ์ค‘์š” ๋Œ€์ƒ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฏธ๋ž˜์˜ ์ฐจ์„ธ๋Œ€ ์šฐ์ฃผ๋ง์›๊ฒฝ์ธ ์ œ์ž„์Šค ์›น ์šฐ์ฃผ๋ง์›๊ฒฝ(James Webb Space Telescope, JWST)์ด ์ˆ˜ํ–‰ํ•˜๊ฒŒ ๋  ์ „์ฒœ ํƒ์‚ฌ ์˜์—ญ ์ค‘ ๊ฐ€์žฅ ๊นŠ์€ ๋ฐ์ดํ„ฐ๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ๊ฒŒ ๋˜๋Š” ๋ถํ™ฉ๋Œ€(North Ecliptic Pole) ์ง€์—ญ์˜ 14๊ฐ๋ถ„ ์˜์—ญ์—์„œ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ํƒ์‚ฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์ด ์˜์—ญ์—๋Š” ๊ธฐ์กด์˜ ๋‹ค์–‘ํ•œ ํŒŒ์žฅ ์˜์—ญ๋Œ€์˜ ๊นŠ์€ ๋ฐ์ดํ„ฐ๋“ค์ด ๋‹ค์ˆ˜ ์กด์žฌํ•˜์ง€๋งŒ, ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์˜์—ญ์—์„œ๋Š” ๊ทธ ๊นŠ์ด๊ฐ€ ์ถฉ๋ถ„ํ•˜์ง€ ์•Š๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” JCMT SCUBA-2 ๊ด€์ธก์„ ํ†ตํ•ด ๊ฐ€์žฅ ๊นŠ์€ ์ง€์—ญ์—์„œ์˜ ์žก์Œ๊ฐ’(๋…ธ์ด์ฆˆ)์ด 0.79 mJy/beam ์ˆ˜์ค€์œผ๋กœ, SCUBA-2์˜ ๊ธฐ๊ธฐ์  ํŠน์„ฑ์— ๋”ฐ๋ฅธ ์žก์Œ ํ•œ๊ณ—๊ฐ’(Confusion limit)์ธ 0.7 mJy/beam์— ๋งค์šฐ ๊นŠ์€ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์ง€๋„๋ฅผ ํ™•๋ณดํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์–ป์€ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์ง€๋„๋กœ๋ถ€ํ„ฐ JWST-TDF ์˜์—ญ์˜ ์ƒˆ๋กœ์šด 114๊ฐœ์˜ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์€ํ•˜๋“ค์„ ๋ฐœ๊ฒฌํ•˜์˜€๊ณ , VLA 3GHz ์ „ํŒŒ ๊ด€์ธก์ž๋ฃŒ์™€์˜ ๋น„๊ต๋ฅผ ํ†ตํ•ด ์กฐ๊ธˆ ๋” ์‹ ๋ขฐ๋„๊ฐ€ ๋†’์€ 59๊ฐœ์˜ ์ž ์žฌ์ ์ธ ์ดˆ๊ธฐ ์šฐ์ฃผ์˜ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์€ํ•˜๋“ค์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ƒˆ๋กœ ๋ฐœ๊ฒฌํ•œ ์„œ๋ธŒ ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ์€ํ•˜๋“ค์˜ ํ”Œ๋Ÿญ์Šค ๋ฐ€๋„๋ณ„ ๊ฐœ์ˆ˜๋ฐ€๋„๋ฅผ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ๋‹ค๋ฅธ ์—ฐ๊ตฌ์ž๋ฃŒ๋“ค๊ณผ์˜ ๋น„๊ต๋ฅผ ํ†ตํ•ด ๋น„์Šทํ•œ ๋ถ„ํฌ๋ฅผ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ํ•˜์ง€๋งŒ, 850 \micron ํ”Œ๋Ÿญ์Šค ๋ฐ€๋„๊ฐ€ 10 mJy ์ด์ƒ์˜ ์˜์—ญ์—์„œ ๊ธฐ์กด ์ž๋ฃŒ๋“ค๊ณผ Schecter ํ•จ์ˆ˜์˜ ๊ฒฐ๊ด๊ฐ’์œผ๋กœ๋ถ€ํ„ฐ์˜ ์ดˆ๊ณผ ํ˜„์ƒ์ด ์žˆ๋Š”๋ฐ, ์ด๋Š” ๋ณธ ์—ฐ๊ตฌ์˜ ํƒ์‚ฌ ์˜์—ญ์˜ ์ž‘์€ ํฌ๊ธฐ๋กœ๋ถ€ํ„ฐ ๋น„๋กฏ๋œ ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. ์ด๋Ÿฌํ•œ ์ดˆ๊ณผ ํ˜„์ƒ์— ๊ธฐ์—ฌ ํ•˜๋Š” ๋ฐ์€ 4๊ฐœ ๋Œ€์ƒ๋“ค๊ณผ, ์ „ํŒŒ ์ž๋ฃŒ์˜ ๋Œ€์‘์ฒด(Counterpart)๊ฐ€ ์žˆ๋Š” ์„œ๋ธŒ๋ฐ€๋ฆฌ๋ฏธํ„ฐ์€ํ•˜์— ๋Œ€ํ•ด ๊ฐ€์‹œ๊ด‘-๊ทผ์ ์™ธ์„  ์ž๋ฃŒ๋ฅผ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์ด ๋Œ€์ƒ ๋“ค์— ๋Œ€ํ•œ ์ถ”๊ฐ€ ์—ฐ๊ตฌ์— ๋Œ€ํ•œ ํ•„์š”์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค.It is well known that galaxy evolution is affected by its environment. Galaxy clusters and superclusters, which are sitting on the top of the hierarchy structure formation in the universe, are useful objects to witness various types of galaxies and environments and to study how the properties of galaxies changed with their surroundings. Despite the advantage and uniqueness of the study, it has not been widely performed at higher redshifts due to the lack of wide and deep multi-wavelength dataset and spectroscopic data. In this thesis, we firstly performed the survey of galaxy clusters and large-scale structures at z > 1 and confirmed them with Multi-Object Spectroscopic observation (hereafter, MOS). Furthermore, we investigate sub-millimetre galaxies, which are thought to be dusty star forming populations in the high redshift (z > 3) with sub-mm data. First, we introduce the study of galaxy clusters and large scale structures in ELAIS-N1 field. Based on deep and wide multi-wavelength photometric data, we could find 1,099 galaxy cluster candidates at 0.5 โ‰ค z โ‰ค 1.5 and 393 of them are at 0.8 1015Mand a large scale structure at z โˆผ 0.9 which is made up of at least 12 galaxy clusters/groups of galaxies. Newly found very massive clusters and the large scale structures are beyond the number expected to derive from the ฮ›CDM cosmological model. Especially, the large scale structure found in this study, EN1LSS, is a very huge structure whose size is โˆผ 100 Mpc encompassing the entire ELAIS-N1 field. To confirm EN1LSS, we performed follow-up spectroscopy observation with Hectospec, a multi-object spectrograph mounted on 6.5 m Multi Mirror Telescope. From the redshift determination from the spectroscopic data, we could confirm some galaxies belong to the large scale structure. We show the galaxy cluster candidates and galaxies that have spectroscopic redshifts from the Hectospec observation. Second, we study galaxy evolution with the -large scale structure- environment with confirmed galaxy clusters from MOS observation by using Inamori Magellan Areal Camera and Spectrograph (IMACS) mounted on the 6.5 m Magellan/Baade telescope in Las Campanas Observatory. With the MOS observation, we could spectroscopically confirm 34 galaxy clusters including 3 galaxy clusters discovered in Kim et al. (2016) and 11 of them have halo mass of > 1014.5M. Among the confirmed clusters, 12 galaxy clusters consist of the large scale structure at z โˆผ 0.9 and their size stretches to 40 Mpc co-moving scale. From this study, we checked the โ€˜web feeding modelโ€™, which is that more linked (with their environment) galaxy clusters have less quenched population by investigating the correlation between properties of confirmed galaxy clusters and the large scale structure environment. Lastly, we found galaxy clusters that make up the large scale structure have larger and widely spread values of total star formation density (ฮฃ SFR /Mhalo) than normal clusters at similar redshifts. Finally, we investigate bright sub-millimeter galaxies in the James Webb Space Telescope - Time Domain Field, where the deepest data will be achieved and show us the deepest early universe ever had. We performed deep 850 ฮผm survey with James Clerk Maxwell Telescope for searching new sub-millimeter galaxies (SMGs) which are high-z populations highly star-forming (SFR > 300 M/yr) holding the hints to reveal the mystery of star formation history in the early universe. We achieve deep 850 ฮผm map covering the full area of JWST-TDF down to ฯƒerr = 0.79 mJy beamโˆ’1 and could find 114 and 82 SCUBA-2 850 ฮผm sources detected at S/N > 3.5 and > 4. We checked the existence of radio counterparts of new sub-mm sources with VLA 3GHz radio catalog and 64 sources have radio identifications. We also studied the number counts of detected 850 ฮผm sources have similar trend in the S850 = 1 - 10 mJy compared to the other previous studies, however there are slight excess in the bright regime (S850 > 10 mJy), thought to be from the effect of relatively small survey area or from the possibility of existence of overdensities at high redshifts. Through the thesis, we introduce newly found galaxy clusters, large scale structures and submillimeter galaxies at various epochs of the universe. Moreover, we present how the environment affects galaxy evolution, especially, the correlation between the large scale structure and the star formation activities in galaxy clusters to answer to the question, โ€œHow the star formation in galaxies varies through their environment and their redshifts?โ€. We found that there are effects not only from the galaxy environment but also from the large scale structure environment into the galaxy population and star formation activities in galaxy clusters. Moreover, we found that large-scale structure can be a role of gas feeding to make galaxy clusters maintain continuous star formation and the consequential enhancement in total star formation rate than normal galaxy clusters.1 Introduction 1 1.1 Galaxy Clusters and Superclusters 1 1.2 Star Formation in Galaxy Cluster 5 1.3 Galaxy Cluster Search and Multi-Object Spectroscopy (MOS) 6 1.3.1 Galaxy Cluster Search 6 1.3.2 Multi Object Spectroscopy (MOS) 9 1.4 Sub-millimeter Galaxies 14 1.5 Outline of Thesis 17 2 Galaxy Clusters and Large Scale Structures at zโˆผ1 in ELAIS-N1 Field 19 2.1 Introduction 19 2.2 Data and Data Reduction 21 2.2.1 Near-IR UKIRT WFCAM Data and Photometry 24 2.2.2 Construction of a Multi-Wavelength Catalog and Star-GalaxySeparation 28 2.3 Galaxy Cluster Candidate Selection 29 2.3.1 Photometric Redshifts 29 2.3.2 Density Map Construction 31 2.4 Cluster Properties and Galaxy Cluster Catalog 33 2.4.1 Galaxy Properties 33 2.4.2 Halo Mass Estimation and Galaxy Cluster Catalog 39 2.4.3 Discovery of Large Scale Structures Spanned over 100 Mpc at zโˆผ0.9 47 2.5 Hectospec Observation and Spectroscopic Redshifts 50 2.5.1 Target Selection 50 2.5.2 Observations and Spectral Analysis 50 2.5.3 Other Spectroscpic Redshifts 61 2.6 Discussion 63 2.6.1 EN1LSS: A Large Scale Structures in ELAIS-N1 Field 63 2.6.2 Massive Galaxy Clusters 68 2.7 Conclusion 73 3 Large Scale Structures at zโˆผ1in SA22 Field and EnvironmentalDependence of Galaxy Properties 75 3.1 Introduction 75 3.2 Data and Cluster Catalog 78 3.2.1 Photometric Catalog and Spectroscopic Redshift Survey Data 78 3.2.2 Photometric Redshifts and Galaxy Cluster Candidates 85 3.2.3 Spectral Energy Distribution Fitting 88 3.3 Multi Object Spectroscopic Observation for Cluster Confirmation 92 3.3.1 IMACS Multi-Object Spectroscopy Observation 92 3.3.2 Multi-Object Spectroscopy Data Reduction 97 3.3.3 Spectroscopic Redshift Measurement 97 3.4 Cluster Confirmation and Cluster Properties Measurement 110 3.4.1 Determination of Cluster Membership for Cluster Confirmation 110 3.4.2 The Newly Confirmed Clusters and Halo Mass Measurement 112 3.4.3 Characteristic Figure for Confirmed Clusters 114 3.5 Discussion 153 3.5.1 Massive Galaxy Clusters 153 3.5.2 Galaxy Distribution in Large Scale Structure 156 3.5.3 Quiescent Galaxy Fraction and Galaxy Environment 164 3.5.4 Large-Scale Structure Environment and Quiescent Fraction 169 3.5.5 Star Formation Rate Density vs. Redshift in LSSs 177 3.6 Conclusion 180 4 JCMT SCUBA-2 Catalog of Submm Sources in the James Webb Space Telescope North Ecliptic Pole Time-domain Field 181 4.1 Introduction 181 4.2 Observation and Data Reduction 184 4.2.1 SCUBA-2 Observations 184 4.2.2 SCUBA-2 Data Reduction 188 4.2.3 Improving Astrometry with VLA Data 193 4.3 Analysis 197 4.3.1 Source Detection 197 4.3.2 Completeness and Flux Deboosting with Jackknife Simulation 200 4.3.3 False Detection Rates 207 4.3.4 Positional Accuracy 209 4.3.5 JWST-TDF 850ฮผm Source Catalog 211 4.4 Identification of Radio Counterpart of 850ฮผm Sources 217 4.5 Discussion 226 4.5.1 850ฮผm Number Count 226 4.6 Conclusion 243 5 Conclusion 245 Bibliography 248 Appendix 264 A Full Catalog of the Spectroscopic Redshift Measurement from theObservation with Hectospec 265 B Combination of Color Magnitude Diagram for Tracing Red Sequenceof Galaxy Cluster 281 C List of Cluster Galaxies and Field Galaxies for MOS Spectroscopy in SA22 Field 291 ์š”์•ฝ 299๋ฐ•

    Space-Efficient Algorithms and Verification Schemes for Graph Streams

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    Structured data-sets are often easy to represent using graphs. The prevalence of massive data-sets in the modern world gives rise to big graphs such as web graphs, social networks, biological networks, and citation graphs. Most of these graphs keep growing continuously and pose two major challenges in their processing: (a) it is infeasible to store them entirely in the memory of a regular server, and (b) even if stored entirely, it is incredibly inefficient to reread the whole graph every time a new query appears. Thus, a natural approach for efficiently processing and analyzing such graphs is reading them as a stream of edge insertions and deletions and maintaining a summary that can be (a) stored in affordable memory (significantly smaller than the input size) and (b) used to detect properties of the original graph. In this thesis, we explore the strengths and limitations of such graph streaming algorithms under three main paradigms: classical or standard streaming, adversarially robust streaming, and streaming verification. In the classical streaming model, an algorithm needs to process an adversarially chosen input stream using space sublinear in the input size and return a desired output at the end of the stream. Here, we study a collection of fundamental directed graph problems like reachability, acyclicity testing, and topological sorting. Our investigation reveals that while most problems are provably hard for general digraphs, they admit efficient algorithms for the special and widely-studied subclass of tournament graphs. Further, we exhibit certain problems that become drastically easier when the stream elements arrive in random order rather than adversarial order, as well as problems that do not get much easier even under this relaxation. Furthermore, we study the graph coloring problem in this model and design color-efficient algorithms using novel parameterizations and establish complexity separations between different versions of the problem. The classical streaming setting assumes that the entire input stream is fixed by an adversary before the algorithm reads it. Many randomized algorithms in this setting, however, fail when the stream is extended by an adaptive adversary based on past outputs received. This is the so-called adversarially robust streaming model. We show that graph coloring is significantly harder in the robust setting than in the classical setting, thus establishing the first such separation for a ``natural\u27\u27 problem. We also design a class of efficient robust coloring algorithms using novel techniques. In classical streaming, many important problems turn out to be ``intractable\u27\u27, i.e., provably impossible to solve in sublinear space. It is then natural to consider an enhanced streaming setting where a space-bounded client outsources the computation to a space-unbounded but untrusted cloud service, who replies with the solution and a supporting ``proof\u27\u27 that the client needs to verify. This is called streaming verification or the annotated streaming model. It allows algorithms or verification schemes for the otherwise intractable problems using both space and proof length sublinear in the input size. We devise efficient schemes that improve upon the state of the art for a variety of fundamental graph problems including triangle counting, maximum matching, topological sorting, maximal independent set, graph connectivity, and shortest paths, as well as for computing frequency-based functions such as distinct items and maximum frequency, which have broad applications in graph streaming. Some of our schemes were conjectured to be impossible, while some others attain smooth and optimal tradeoffs between space and communication costs

    Normal mode computations and applications

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    Proteins are fundamental functional units in cells. Proteins form stable and yet somewhat flexible 3D structures and often function by interacting with other molecules. Their functional behaviors are determined by their 3-D structures as well as their flexibilities. In this thesis, I focus my study on protein dynamics and its role in protein function. One of the most powerful computational methods for studying protein dynamics is normal mode analysis (NMA). Especially its low frequency modes having the intrinsic dynamics of proteins are of interest for most of protein dynamics studies. Although NMA provides analytical solutions to a protein\u27s collective motions, it is inconvenient to use because of its requirement of energy minimization, and it is prohibitive due to the large memory consumption and the long computation time especially when the system is too large. Additionally, it is unclear what meanings the frequencies of normal modes have, and if those meanings can be validated by comparison with the experimental results. The majority of this thesis resolves the above issues. I have addressed following sequence of questions and developed several simplified NMAs as answers: (1) what is the role of inter residue forces; (2) how to remove the energy minimization requirement in NMA yet to keep most of accuracy; (3) how to efficiently build the coarse-grained model from the all-atomic model with keeping atomic accuracy. Additionally, using newly developed models and traditional NMA, I have examined the meaning of normal modes in all frequency range, and have found the connection with experimental results. The last part of this thesis addresses, as an application of normal modes, how the normal modes can depict the sequence of breathing motion of myoglobin to find the transition pathway that dynamically opens ligand migration channels. The results have an excellent agreement with molecular dynamics simulation results and experimentally determined reaction rate constants

    A Computational Study of Amyloid Fibrils and their Structural Properties

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    The term amyloid describes misfolded protein aggregates in which a highly ordered cross ฮฒ-sheet pattern is adopted. While there exist functional amyloids, the majority of known amyloids are associated with diseases in multicellular organisms. One example is the association is that between Amyloid ฮฒ (Aฮฒ) and Alzheimerโ€™s disease, a neurodegenerative disorder in humans. Several mechanisms of toxicity have been proposed, yet a lack of dynamic data prevents a full molecular explanation for the toxicity of Aฮฒ and other amyloid systems. Mutational effects often increase the degree of polymorphism in observable structures, compounding the issues with a molecular level examination. In this thesis, Molecular Dynamic (MD) simulations of wild-type and mutant sequences of both Aฮฒ and Prion proteins are performed to explore the structural dynamics of amyloids and amyloid-like systems. The data generated will provide physics-based explanations of the traits of amyloids on a molecular level which may guide further physical experimentation into the mechanism of amyloid toxicity and formation

    Schematics of Graphs and Hypergraphs

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    Graphenzeichnen als ein Teilgebiet der Informatik befasst sich mit dem Ziel Graphen oder deren Verallgemeinerung Hypergraphen geometrisch zu realisieren. Beschrรคnkt man sich dabei auf visuelles Hervorheben von wesentlichen Informationen in Zeichenmodellen, spricht man von Schemata. Hauptinstrumente sind Konstruktionsalgorithmen und Charakterisierungen von Graphenklassen, die fรผr die Konstruktion geeignet sind. In dieser Arbeit werden Schemata fรผr Graphen und Hypergraphen formalisiert und mit den genannten Instrumenten untersucht. In der Dissertation wird zunรคchst das โ€žpartial edge drawingโ€œ (kurz: PED) Modell fรผr Graphen (bezรผglich gradliniger Zeichnung) untersucht. Dabei wird um Kreuzungen im Zentrum der Kante visuell zu eliminieren jede Kante durch ein kreuzungsfreies Teilstรผck (= Stummel) am Start- und am Zielknoten ersetzt. Als Standard hat sich eine PED-Variante etabliert, in der das Lรคngenverhรคltnis zwischen Stummel und Kante genau 1โ„4 ist (kurz: 1โ„4-SHPED). Fรผr 1โ„4-SHPEDs werden Konstruktionsalgorithmen, Klassifizierung, Implementierung und Evaluation prรคsentiert. AuรŸerdem werden PED-Varianten mit festen Knotenpositionen und auf Basis orthogonaler Zeichnungen erforscht. Danach wird das BUS Modell fรผr Hypergraphen untersucht, in welchem Hyperkanten durch fette horizontale oder vertikale โ€“ als BUS bezeichnete โ€“ Segmente reprรคsentiert werden. Dazu wird eine vollstรคndige Charakterisierung von planaren Inzidenzgraphen von Hypergraphen angegeben, die eine planare Zeichnung im BUS Modell besitzen, und diverse planare BUS-Varianten mit festen Knotenpositionen werden diskutiert. Zum Schluss wird erstmals eine Punktmenge von subquadratischer GrรถรŸe angegeben, die eine planare Einbettung (Knoten werden auf Punkte abgebildet) von 2-auรŸenplanaren Graphen ermรถglicht
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