159 research outputs found

    Protein folding tames chaos

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    Protein folding produces characteristic and functional three-dimensional structures from unfolded polypeptides or disordered coils. The emergence of extraordinary complexity in the protein folding process poses astonishing challenges to theoretical modeling and computer simulations. The present work introduces molecular nonlinear dynamics (MND), or molecular chaotic dynamics, as a theoretical framework for describing and analyzing protein folding. We unveil the existence of intrinsically low dimensional manifolds (ILDMs) in the chaotic dynamics of folded proteins. Additionally, we reveal that the transition from disordered to ordered conformations in protein folding increases the transverse stability of the ILDM. Stated differently, protein folding reduces the chaoticity of the nonlinear dynamical system, and a folded protein has the best ability to tame chaos. Additionally, we bring to light the connection between the ILDM stability and the thermodynamic stability, which enables us to quantify the disorderliness and relative energies of folded, misfolded and unfolded protein states. Finally, we exploit chaos for protein flexibility analysis and develop a robust chaotic algorithm for the prediction of Debye-Waller factors, or temperature factors, of protein structures

    Numerical representations of fluid mixing

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    The work contained within this thesis is concerned with a theoretical investigatiop of both laminar and thermally driven types of cavity flow, together with an analysis of their associated mixing processes which find applications to Industrial mixing and also to the environment. The mixing efficiency has been viewed from two perspectives namely the tracking of a selection of fluid particles, and also the simulation of the dispersive mixing of a coloured fluid element as carried along by the flow. This thesis also incorporates features of both Newtonian and a wide range of non-Newtonian fluids

    ๊ณ ์ฐจ์› ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ, ๋Œ€๊ธฐ์˜ˆ์ธก์„ฑ ๋ฐ ์ž๋ฃŒ๋™ํ™”

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ์ง€๊ตฌํ™˜๊ฒฝ๊ณผํ•™๋ถ€, 2021.8. ๋ฌธ์Šน์ฃผ.๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์€ ๋ ˆ์ผ๋ฆฌ ๋ฒ ๋‚˜๋ฅด ๋Œ€๋ฅ˜ ํ˜„์ƒ์˜ ๋‹จ์ˆœํ•œ ๋ชจํ˜•์œผ๋กœ ์ฒ˜์Œ ๊ณ ์•ˆ๋˜์—ˆ์œผ๋‚˜, ์ดํ›„ ์•ผ๋ฆ‡ํ•œ ๋Œ๊ฐœ์˜ ๋ฐœ๊ฒฌ ๋ฐ ํ˜ผ๋ˆ ์ด๋ก ์˜ ๊ธ‰์†ํ•œ ๋ฐœ์ „์— ๋Œ€ํ•œ ๊ธฐ์—ฌ ๋“ฑ์„ ํ†ตํ•ด ๊ทธ ์ค‘์š”์„ฑ์ด ๊พธ์ค€ํžˆ ๋ถ€๊ฐ๋˜์–ด ์™”๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‘ ๊ฐ€์ง€ ์ ‘๊ทผ ๋ฐฉ์‹์„ ํ†ตํ•ด ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์„ ๊ณ ์ฐจ์›์œผ๋กœ ํ™•์žฅํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ฒซ๋ฒˆ์งธ ์ ‘๊ทผ ๋ฐฉ์‹์€ ์œ ๋„ ๊ณผ์ •์—์„œ ๋น„๋กฏ๋˜๋Š” ํ‘ธ๋ฆฌ์— ๊ธ‰์ˆ˜์˜ ์ ˆ๋‹จ์— ์žˆ์–ด ์ถ”๊ฐ€ ๋ชจ๋“œ๋ฅผ ํ†ตํ•ด ์ฐจ์ˆ˜๋ฅผ ํ™•์žฅํ•˜๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋ฅผ ์ผ๋ฐ˜ํ™” ํ•˜์—ฌ ์ž„์˜์˜ ์ž์—ฐ์ˆ˜ NN์— ๋Œ€ํ•œ (3N)(3N) ๋ฐ (3N+2)(3N+2)์ฐจ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์„ ์œ ๋„ํ•˜์˜€๋‹ค. ๋‘๋ฒˆ์งธ๋Š” ๋ฌผ๋ฆฌ์  ํ™•์žฅ์ด๋ผ ๋ถˆ๋ฆฌ๋Š” ๋ฐฉ์‹์œผ๋กœ, ๋ ˆ์ผ๋ฆฌ ๋ฒ ๋‚˜๋ฅด ๋Œ€๋ฅ˜ ํ˜„์ƒ์„ ๊ด€์žฅํ•˜๋Š” ์ง€๋ฐฐ๋ฐฉ์ •์‹์— ๋‚˜ํƒ€๋‚ด๊ณ ์ž ํ•˜๋Š” ๋ฌผ๋ฆฌ ์„ฑ๋ถ„์„ ์ถ”๊ฐ€ํ•˜์—ฌ ๋” ๋†’์€ ์ฐจ์ˆ˜์˜ ๋ฐฉ์ •์‹๊ณ„๋ฅผ ์–ป๋Š” ๊ณผ์ •์ด๋‹ค. ์ด์— ์ถ”๊ฐ€ ๋ฌผ๋ฆฌ ์„ฑ๋ถ„์œผ๋กœ ๋ชจํ˜• ํ”„๋ ˆ์ž„์˜ ํšŒ์ „๊ณผ ๋‚ด๋ถ€์— ๋ถ€์œ ํ•˜๋Š” ์˜ค์—ผ ๋ฌผ์งˆ ๋”ฐ์œ„์˜ ์Šค์นผ๋ผ๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์ƒˆ๋กœ์šด 6์ฐจ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์„ ์œ ๋„ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋ ‡๊ฒŒ ์–ป์–ด์ง„ ๊ณ ์ฐจ์› ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์€ ๋น„์„ ํ˜•์„ฑ, ๋Œ€์นญ์„ฑ, ์†Œ์‚ฐ์„ฑ ๋“ฑ์˜ ๊ณตํ†ต๋œ ํŠน์ง•์„ ์ง€๋‹Œ๋‹ค. ์ƒˆ๋กญ๊ฒŒ ํ™•์žฅ๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์˜ ํ•ด์˜ ํŠน์„ฑ ๋ฐ ๊ทธ๋“ค์ด ๋‚˜ํƒ€๋‚ด๋Š” ๋‹ค์–‘ํ•œ ๋น„์„ ํ˜• ํ˜„์ƒ์˜ ๊ทœ๋ช…์€ ์ˆ˜์น˜ ์ ๋ถ„์„ ํ†ตํ•ด ์–ป์€ ํ•ด์˜ ๋ถ„์„์„ ๋ฐ”ํƒ•์œผ๋กœ ์ด๋ฃจ์–ด์กŒ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์นด์˜ค์Šค ์ด๋ก ์— ์ž…๊ฐํ•œ ์—ฌ๋Ÿฌ๊ฐ€์ง€ ๋ถ„์„ ๋ฐฉ๋ฒ•์ด ํ™œ์šฉ๋˜์—ˆ๋Š”๋ฐ, ์ด๋Ÿฌํ•œ ๋ถ„์„๋ฐฉ๋ฒ•์—๋Š” ํŒŒ๋ผ๋ฏธํ„ฐ ๊ณต๊ฐ„ ์ƒ์˜ ์ฃผ๊ธฐ์„ฑ๋„ํ‘œ, ๋ถ„๊ธฐ๋„ํ‘œ ๋ฐ ๋ฆฌ์•„ํ‘ธ๋…ธํ”„ ์ง€์ˆ˜ ๊ทธ๋ฆฌ๊ณ  ์œ„์ƒ ๊ณต๊ฐ„ ๋‚ด ํ•ด์˜ ๊ถค๋„ ๋ฐ ํ”„๋ ‰ํƒˆ ํก์ธ๊ฒฝ๊ณ„ ๋“ฑ์ด ์žˆ๋‹ค. ๋ฐํ˜€์ง„ ๋น„์„ ํ˜• ๋™์—ญํ•™์  ํ˜„์ƒ ์ค‘ ํŠนํžˆ ์ฃผ๋ชฉํ•  ๋งŒํ•œ ํ˜„์ƒ์—๋Š” ํŒŒ๋ผ๋ฏธํ„ฐ ๊ฐ’์— ๋”ฐ๋ฅธ ๋ถ„๊ธฐ ๊ตฌ์กฐ์˜ ๋ณ€๋™, ํ•˜๋‚˜์˜ ์œ„์ƒ ๊ณต๊ฐ„ ๋‚ด ์กด์žฌํ•˜๋Š” ์—ฌ๋Ÿฌ ํƒ€์ž…์˜ ํ•ด์˜ ๊ณต์กด, ์นด์˜ค์Šค์˜ ๋™๊ธฐํ™” ๋“ฑ์ด ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ํ˜„์ƒ์˜ ์ˆ˜ํ•™์ ~โ‹…\cdot~์ˆ˜์น˜์  ๋ถ„์„๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ด๊ฒƒ์ด ๋Œ€๊ธฐ๊ณผํ•™ ํŠนํžˆ ์ž๋ฃŒ๋™ํ™”์™€ ๋Œ€๊ธฐ์˜ˆ์ธก์„ฑ ๋ถ„์•ผ์— ํ•จ์˜ํ•˜๋Š” ๋ฐ”๊ฐ€ ๋ฌด์—‡์ธ์ง€๋„ ํƒ๊ตฌํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆ๋œ ์ผ๋ฐ˜ํ™” ๋ฐฉ์‹์— ๋”ฐ๋ผ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์˜ ์ฐจ์ˆ˜๋ฅผ ์˜ฌ๋ฆฌ๋ฉด ๋ถ„๊ธฐ ๊ตฌ์กฐ์— ๋ณ€๋™์ด ์ผ์–ด๋‚˜ ์ž„๊ณ„ ๋ ˆ์ผ๋ฆฌ ํŒŒ๋ผ๋ฏธํ„ฐ์˜ ์ฆ๊ฐ€๊ฐ€ ๋น„๋กฏ๋œ๋‹ค. ์—ฌ๊ธฐ์„œ ์ž„๊ณ„ ๋ ˆ์ผ๋ฆฌ ํŒŒ๋ผ๋ฏธํ„ฐ๋Š” ์นด์˜ค์Šค๊ฐ€ ์ฒ˜์Œ ๋ฐœ์ƒํ•˜๋Š” ๊ฐ€์žฅ ๋‚ฎ์€ ๋ ˆ์ผ๋ฆฌ ํŒŒ๋ผ๋ฏธํ„ฐ ๊ฐ’์ด๋ฏ€๋กœ ์ด๊ฒƒ์ด ์ฐจ์ˆ˜์— ๋”ฐ๋ผ ์ฆ๊ฐ€ํ•œ๋‹ค๋Š” ๊ฒƒ์€ ์ฆ‰ ๊ณ ์ฐจ์› ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์—์„œ๋Š” ์นด์˜ค์Šค์˜ ๋ฐœ์ƒ์ด ์ €์ฐจ์›์—์„œ๋ณด๋‹ค ๋” ์–ด๋ ต๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ์ฐจ์ˆ˜ ๋ฐ ํŒŒ๋ผ๋ฏธํ„ฐ ๊ณต๊ฐ„์— ๊ทธ๋ ค์ง„ ์ฃผ๊ธฐ์„ฑ ๋„ํ‘œ๋ฅผ ๋ณด๋ฉด ์นด์˜ค์Šค๊ฐ€ ์กด์žฌํ•˜๋Š” ์˜์—ญ์ด ์ฐจ์ˆ˜์— ๋”ฐ๋ผ ์ ์  ์ค„์–ด๋“ค๊ณ , ์–ด๋Š ์ฐจ์ˆ˜ ์ด์ƒ๋ถ€ํ„ฐ๋Š” ์‚ฌ๋ผ์ง€๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ๋ฌผ๋ฆฌ์ ์œผ๋กœ ํ™•์žฅ๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์—์„œ๋Š” ์ž„๊ณ„ ๋ ˆ์ผ๋ฆฌ ํŒŒ๋ผ๋ฏธํ„ฐ๊ฐ€ ์ถ”๊ฐ€๋œ ๋ฌผ๋ฆฌํ˜„์ƒ์„ ๋‚˜ํƒ€๋‚ด๋Š” ์ƒˆ๋กœ์šด ํŒŒ๋ผ๋ฏธํ„ฐ์˜ ๊ฐ’์„ ์ฆ๊ฐ€์‹œํ‚ด์— ๋”ฐ๋ผ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ํ•œํŽธ ์œ ์ฒด ๋‚ด ์Šค์นผ๋ผ ํšจ๊ณผ์™€ ์—ฐ๊ด€๋œ ํŒŒ๋ผ๋ฏธํ„ฐ๋งŒ ์ ์ง„์ ์œผ๋กœ ์˜ฌ๋ฆด ๊ฒฝ์šฐ์—๋Š” ์‹œ์Šคํ…œ์˜ ๋ถˆ์•ˆ์ •์„ ์•ผ๊ธฐํ•˜๋Š” ๋ ˆ์ผ๋ฆฌ ํŒŒ๋ผ๋ฏธํ„ฐ์™€ ์•ˆ์ •์„ ์•ผ๊ธฐํ•˜๋Š” ์Šค์นผ๋ผ ๊ด€๋ จ ํŒŒ๋ผ๋ฏธํ„ฐ ๊ฐ„์˜ ๊ฒฝ์Ÿ์œผ๋กœ ์ธํ•ด ์‹œ์Šคํ…œ์ด ์™„์ „ํžˆ ์•ˆ์ •ํ™” ๋˜๊ธฐ ์ „ ์นด์˜ค์Šค ํ•ด๊ฐ€ ํ•œ๋ฒˆ ๋” ๋ฐœ์ƒํ•˜๋Š” ํ˜„์ƒ์ด ์ผ์–ด๋‚œ๋‹ค. ์ด ๋‘๋ฒˆ์งธ ์นด์˜ค์Šค์— ๋Œ€์‘๋˜๋Š” ๋Œ๊ฐœ๋Š” ๊ธฐ์กด์— ์•Œ๋ ค์ง„ ๋กœ๋ Œ์ธ  ๋Œ๊ฐœ์™€๋Š” ์‚ฌ๋ญ‡ ๋‹ค๋ฅธ ๋ชจ์–‘์ƒˆ๋ฅผ ๋ณด์ธ๋‹ค. ํ•ด์˜ ๊ณต์กด ํ˜„์ƒ์€ ๋กœ๋ Œ์ธ ์— ์˜ํ•ด ๋ฐํ˜€์ง„ ํ•ด์˜ ์ดˆ๊ธฐ์กฐ๊ฑด์— ๋Œ€ํ•œ ๋ฏผ๊ฐ๋„์™€๋Š” ๊ตฌ๋ถ„๋˜๋Š” ๊ฐœ๋…์œผ๋กœ, ์ดˆ๊ธฐ์กฐ๊ฑด์œผ๋กœ ์ธํ•œ ์นด์˜ค์Šค ํ•ด ๊ฐ„์˜ ์ฐจ์ด๊ฐ€ ์ฆํญ๋˜๋Š” ์ด๋ฅธ๋ฐ” ๋‚˜๋น„ํšจ๊ณผ์™€๋Š” ๋‹ฌ๋ฆฌ ์ดˆ๊ธฐ์กฐ๊ฑด์— ๋”ฐ๋ผ ์™„์ „ํžˆ ๋‹ค๋ฅธ ํƒ€์ž…์˜ ํ•ด๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ๋Œ๊ฐœ๊ฐ€ ๊ฐ™์€ ์œ„์ƒ๊ณต๊ฐ„์— ๊ณต์กดํ•จ์„ ์˜๋ฏธํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋งŒ์•ฝ ์‹ค์ œ ๋‚ ์”จ๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ์‹œ์Šคํ…œ์ด ์ƒ์กดํ•˜๋Š” ์œ„์ƒ๊ณต๊ฐ„์—์„œ ์ด๋Ÿฌํ•œ ํ•ด์˜ ๊ณต์กด์ด ์‹ค์ œํ•œ๋‹ค๋ฉด ์ด๊ฒƒ์€ ์นด์˜ค์Šค์˜ ์ดˆ๊ธฐ์กฐ๊ฑด์— ๋Œ€ํ•œ ๋ฏผ๊ฐ์„ฑ๊ณผ ๋”๋ถˆ์–ด ๋Œ€๊ธฐ์˜ˆ์ธก์„ฑ ํŠนํžˆ ์•™์ƒ๋ธ” ์˜ˆ๋ณด์— ์ด๋ก ์ ์œผ๋กœ ์‹œ์‚ฌํ•˜๋Š” ๋ฐ”๊ฐ€ ํด ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. ๋ฌผ๋ฆฌ์ ์œผ๋กœ ํ™•์žฅ๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์—์„œ๋Š” ๊ธฐ์กด ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ๊ณผ ๊ฐ™์ด ๋ ˆ์ผ๋ฆฌ ํŒŒ๋ผ๋ฏธํ„ฐ์˜ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ๋ถ„๊ธฐ ๊ตฌ์กฐ์˜ ๋ถ€์ •ํ•ฉ์œผ๋กœ ์ธํ•ด ๋น„๋กฏ๋˜๋Š” ํ•ด์˜ ๊ณต์กด์ด ๋‚˜ํƒ€๋‚œ๋‹ค. ํ•ด์˜ ๊ณต์กด ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์€ ํŒŒ๋ผ๋ฏธํ„ฐ ์กฐํ•ฉ์„ ์ฐพ์•„๋‚ด๊ธฐ ์œ„ํ•ด ๋ฌผ๋ฆฌ์ ์œผ๋กœ ํ™•์žฅ๋œ 6์ฐจ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์˜ ๋ถ„๊ธฐ๊ตฌ์กฐ๋ฅผ ์ˆ˜์น˜์ ~โ‹…\cdot~ํ•ด์„์  ๋ฐฉ๋ฒ•์œผ๋กœ ๋„์ถœํ•˜์˜€๊ณ  ์ดˆ๊ธฐ์กฐ๊ฑด์— ๋”ฐ๋ผ ์„œ๋กœ ๋‹ค๋ฅธ ๋‘๊ฐ€์ง€ ์ข…๋ฅ˜์˜ ๋ถ„๊ธฐ ์ฆ‰ ํ˜ธํ”„ ๋ฐ ํ—คํ…Œ๋กœํด๋ฆฌ๋‹‰ ๋ถ„๊ธฐ๊ฐ€ ์—‡๊ฐˆ๋ฆฌ๋Š” ๊ตฌ๊ฐ„์„ ์ง‘์ค‘์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ธฐ์กด 3์ฐจ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์—์„œ ํ•˜๋‚˜์˜ ๋ณ€์ˆ˜์— ๋Œ€ํ•œ ์ •๋ณด ์ „๋‹ฌ ๋งŒ์œผ๋กœ๋„ ์ž๊ธฐ๋™๊ธฐํ™” ํ˜„์ƒ์ด ์ผ์–ด๋‚จ์€ ์ด๋ฏธ ์ž˜ ์•Œ๋ ค์ง„ ์‚ฌ์‹ค์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฌผ๋ฆฌ์ ์œผ๋กœ ํ™•์žฅ๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์—์„œ๋„ ๊ธฐ์กด ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ๊ณผ ๊ฐ™์€ ์กฐ๊ฑด ํ•˜์—์„œ ์นด์˜ค์Šค์˜ ์ž๊ธฐ๋™๊ธฐํ™”๊ฐ€ ์ผ์–ด๋‚˜๋Š” ์ ์„ ์ ์ ˆํ•œ ๋ฆฌ์•„ํ‘ธ๋…ธํ”„ ํ•จ์ˆ˜์˜ ์ œ์‹œ๋ฅผ ํ†ตํ•ด ์ฆ๋ช…ํ•˜์˜€๋‹ค. ์ผ๋ฐ˜ํ™”๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์˜ ์ž๊ธฐ๋™๊ธฐํ™”์— ๋Œ€ํ•ด์„œ๋Š” ๋น„๋ก ์ˆ˜ํ•™์  ์ฆ๋ช…์ด ๋™๋ฐ˜๋˜์ง€๋Š” ์•Š์•˜์ง€๋งŒ ์ˆ˜์น˜์  ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ์—ญ์‹œ ๊ฐ™์€ ์กฐ๊ฑด ํ•˜์—์„œ ์ž๊ธฐ๋™๊ธฐํ™”๊ฐ€ ์ผ์–ด๋‚จ์„ ๋’ท๋ฐ›์นจ ํ•  ๊ทผ๊ฑฐ๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ˆ˜์น˜ ์‹คํ—˜์„ ํ†ตํ•ด ์„œ๋กœ ๋‹ค๋ฅธ ์ฐจ์ˆ˜๋ฅผ ๊ฐ€์ง„ ์ผ๋ฐ˜ํ™”๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ ๊ฐ„ ๋™๊ธฐํ™”๊ฐ€ ์ผ์–ด๋‚˜๋Š” ์ •๋„๊ฐ€ ์ƒํ˜ธ ์ฐจ์ˆ˜๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๋‘ ์‹œ์Šคํ…œ ์‚ฌ์ด์˜ ๊ฑฐ๋ฆฌ์™€ ์Œ์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๊ฐ€์ง„๋‹ค๋Š” ์ ๋„ ํ™•์ธํ•˜์˜€๋‹ค. ์ถ”๊ฐ€ ํ‘ธ๋ฆฌ์— ๋ชจ๋“œ๋ฅผ ํฌํ•จํ•˜์—ฌ ๋” ์ž‘์€ ์Šค์ผ€์ผ์˜ ์šด๋™์„ ๋ถ„ํ•ดํ•  ์ˆ˜ ์žˆ๋Š” ๊ณ ์ฐจ์› ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ๊ณผ ๊ทธ๋ ‡๊ฒŒ ํ•˜์ง€ ๋ชปํ•˜๋Š” ์ €์ฐจ์› ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ ๊ฐ„ ๋™๊ธฐํ™”์˜ ๊ฐ€๋Šฅ์„ฑ์€ ๋Œ€๊ธฐ๊ณผํ•™์—์„œ ํŠนํžˆ ๋Œ€๊ธฐ ๋ชจํ˜• ๋ฐ ์ž๋ฃŒ๋™ํ™”์— ์žˆ์–ด ์ค‘์š”ํ•œ ๊ฐœ๋…์ ์ธ ํ•จ์˜๋ฅผ ๊ฐ€์ง„๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํŠน๋ณ„ํžˆ ์•™์ƒ๋ธ” ์นผ๋งŒ ํ•„ํ„ฐ ์ž๋ฃŒ๋™ํ™” ๊ธฐ๋ฒ•์„ ์ผ๋ก€๋กœ ์ผ๋ฐ˜ํ™”๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์ด ์ž๋ฃŒ๋™ํ™” ๊ธฐ๋ฒ•์˜ ๋น„๊ต์  ๋‹จ์ˆœํ•œ ํ…Œ์ŠคํŠธ๋ฒ ๋“œ๋กœ์จ์˜ ์—ญํ• ์„ ํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ํƒ๊ตฌํ•˜์˜€๋‹ค. ์นด์˜ค์Šค ๋™๊ธฐํ™” ํ˜„์ƒ์— ๊ธฐ๋ฐ˜์„ ๋‘” ๊ฐœ๋…์  ๋„์‹์œผ๋กœ ๋ฐœ์‹ ์ž๋ฅผ ์‹ค์ œ ๋Œ€๊ธฐ ํ˜„์ƒ, ์ˆ˜์‹ ์ž๋ฅผ ๋Œ€๊ธฐ ๋ชจํ˜•, ๊ทธ๋ฆฌ๊ณ  ๋ฐœ์‹ ์ž์—์„œ ์ˆ˜์‹ ์ž๋กœ ์ „๋‹ฌ๋˜๋Š” ์ •๋ณด๋ฅผ ๊ด€์ธก์— ๋Œ€์‘์‹œํ‚ด์œผ๋กœ์จ ์ˆ˜์‹ ์ž์™€ ๋ฐœ์‹ ์ž ๊ฐ„์˜ ์˜ค์ฐจ, ๋ฐœ์‹ ์ž์—์„œ ์ˆ˜์‹ ์ž๋กœ ์ „๋‹ฌํ•  ์ •๋ณด ์ถ”์ถœ ๊ณผ์ •์—์„œ ๋น„๋กฏ๋˜๋Š” ์˜ค์ฐจ ๋“ฑ์„ ํ†ตํ•ด ์‹ค์ œ ๋Œ€๊ธฐ ๋ชจํ˜•๊ณผ ๊ด€์ธก์˜ ๋ถˆ์™„์ „ํ•จ์„ ๊ฐœ๋…์ ์œผ๋กœ ๋ชจ์˜ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ผ๋ฐ˜ํ™”๋œ ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์—์„œ ์ดˆ๊ธฐ์กฐ๊ฑด์— ์•„์ฃผ ์ž‘์€ ์„ญ๋™์„ ์ค€ ํ•ด์™€ ๊ทธ๋ ‡์ง€ ์•Š์€ ํ•ด ๊ฐ„์˜ ๋น„๊ต๋ฅผ ํ†ตํ•ด ์ด๊ฒƒ์ด ๋Œ€๊ธฐ์˜ˆ์ธก์„ฑ์— ํ•จ์˜ํ•˜๋Š” ๋ฐ”๊ฐ€ ๋ฌด์—‡์ธ์ง€ ํƒ๊ตฌํ•˜์˜€๋‹ค. ์ด๋•Œ ์ด๋ ‡๊ฒŒ ๋‘ ํ•ด๊ฐ€ ๋ฒŒ์–ด์ง€๋Š” ์ •๋„๊ฐ€ ๊ธฐ์ค€๊ฐ’์„ ๋„˜๊ฒŒ ๋˜๋Š” ์‹œ๊ฐ„์„ ํŽธ์ฐจ์‹œ๊ฐ„์ด๋ผ ์นญํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํŽธ์ฐจ์‹œ๊ฐ„์ด ์ ์–ด๋„ ์ฃผ์–ด์ง„ ํŒŒ๋ผ๋ฏธํ„ฐ ๊ฐ’ ํ•˜์—์„œ๋Š” ๋กœ๋ Œ์ธ  ์‹œ์Šคํ…œ์˜ ์ฐจ์ˆ˜์— ๋Œ€ํ•œ ๊ฐ•ํ•œ ๋น„๋‹จ์กฐ์  ์˜์กด์„ฑ์„ ๋ณด์ž„์„ ๋ฐœ๊ฒฌํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ด๋ ‡๊ฒŒ ์ •์˜๋œ ํŽธ์ฐจ์‹œ๊ฐ„์„ ํ™œ์šฉํ•˜์—ฌ ์‹ค์ œ ๋‚ ์”จ ์‚ฌ๋ก€์˜ ์ˆ˜์น˜ ์˜ˆ๋ณด ๋ชจ์˜์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๋Œ€๊ธฐ์˜ˆ์ธก์„ฑ์„ ์ธก์ •ํ•˜์˜€์„๋•Œ, ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ๋Œ€๊ธฐ์˜ˆ์ธก์„ฑ์ด ์—ฐ์งํ•ด์ƒ๋„์— ๋Œ€ํ•œ ๋น„๋‹จ์กฐ์  ์˜์กด์„ฑ์„ ๋ณด์ด๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด์— ์ด๋Ÿฌํ•œ ๋น„๋‹จ์กฐ์  ์˜์กด์„ฑ์˜ ๊ทผ๋ณธ์ ์ธ ์›์ธ์€ ๋ชจํ˜•์˜ ๋Œ€๊ธฐ ๋‚˜์•„๊ฐ€ ์‹ค์ œ ๋‚ ์”จ์— ๋‚ด์žฌ๋œ ์นด์˜ค์Šค์— ์žˆ์„ ์ˆ˜ ์žˆ์Œ์„ ์ œ์•ˆํ•˜์˜€๋‹ค.The Lorenz system is a simplified model of Rayleigh--B\'{e}nard convection whose importance lies not only in understanding the fluid convection problem but also in its formative role in the discovery of strange attractors and the subsequent development of the modern theory of chaos. In this dissertation, two different approaches to extending the Lorenz system to higher dimensions are considered. First, by including additional wavenumber modes at the series truncation stage of the derivation, the so-called high-order Lorenz systems are obtained up to dimension 11, which are then generalized into (3N)(3N) and (3N+2)(3N+2) dimensions for any positive integer NN. Second, by incorporating additional physical ingredients, namely, rotation and density-affecting scalar in the governing equations, a new 6-dimensional physically extended Lorenz system is derived. All of these high-dimensional extensions of the Lorenz system are shown to share some basic properties such as nonlinearity, symmetry, and volume contraction. The numerically obtained solutions of the extended Lorenz systems are studied through periodicity diagrams, bifurcation diagrams, and Lyapunov exponent spectra in parameter spaces and also through solution trajectories and basin boundaries in the phase space, illuminating various nonlinear dynamical phenomena such as shifts in the bifurcation structures, attractor coexistence, and chaos synchronization. Accompanying these results are discussions about their applicability and theoretical implications, particularly in the context of data assimilation and atmospheric predictability. The shifts in bifurcation structures induced by raising the dimension lead to higher critical Rayleigh parameter values, implying that it gets more difficult for chaos to emerge at higher dimensions. Periodicity diagrams reveal that the parameter ranges in which chaos resides tend to diminish with rising dimensions, eventually vanishing altogether. Likewise, simultaneously increasing the newly added parameters in the physically extended Lorenz system leads to higher critical Rayleigh parameter values; however, raising only the scalar-related parameter leads to an eventual return of chaos albeit with an attractor with qualitatively distinct features from the Lorenz attractor. The peculiar bifurcation structure shaped by the competition between the opposing effects of raising the Rayleigh and the scalar-related parameters helps explain this second onset of chaos. Attractor coexistence refers to the partition of the phase space by basin boundaries so that different types of attractors emerge depending on the initial condition. Similar to the original Lorenz system, the physically extended Lorenz system is found to exhibit attractor coexistence stemming from mismatches between the Hopf and heteroclinic bifurcations. If the atmosphere is found to exhibit such behavior, it can have grave implications for atmospheric predictability and ensemble forecasting beyond mere sensitive dependence on initial conditions, which only applies to chaotic solutions. Chaos synchronization is another curious phenomenon known to occur in the Lorenz system. By finding an appropriate Lyapunov function, the physically extended Lorenz system is shown to self-synchronize under the same condition that guarantees self-synchronization in the original Lorenz system. Regarding the generalized Lorenz systems, numerical evidence in support of self- as well as some degree of generalized synchronization, that is, synchronization between two Lorenz systems differing in their dimensions, is provided. Numerical results suggest that the smaller the dimensional difference between the two, the stronger they tend to synchronize. Some conceptual implications of such results are discussed in relation to atmospheric modeling and data assimilation. Especially, the feasibility of using the (3N)(3N)-dimensional Lorenz systems as a testbed for data assimilation methods is explored. For demonstration, the ensemble Kalman filter method is implemented to assimilate observations with ensembles of model outputs generated using the generalized Lorenz systems, whose imperfections are simulated through varying the severity of ensemble over- or underdispersion, dimensional differences, random forcing, and model or observation biases. Further investigation of the generalized Lorenz systems is carried out from the perspective of predictability, showing that predictability measured by deviation time, which is the time when the threshold-exceeding deviations among ensemble members occur, can respond non-monotonically to increases in the system's dimension. Accordingly, deviation time is put forward as a direct measure of predictability due to weather's sensitive dependence on initial conditions. Raising the dimension under the proposed generalizations is thought to be analogous to resolving smaller-scale motions in the vertical direction. The estimated deviation times in an ensemble of real-case simulations using a realistic numerical weather forecasting model reveal that the predictability of real-case simulations also depend non-monotonically on model vertical resolution. It is suggested that beneath this non-monotonicity fundamentally lies chaos inherent to the model atmospheres and, by extension, weather at large.1 Overview 1 1.1 Chaos and the Lorenz system 1 1.2 Extending the Lorenz system 6 1.3 Bifurcations and related phenomena 8 1.4 Chaos in the atmosphere 14 1.5 Organization of the dissertation 16 2 Chaos and Periodicity of the High-Order Lorenz Systems 18 2.1 Introduction 18 2.2 The high-order Lorenz systems 20 2.2.1 Derivation 22 2.2.2 Some properties of the Lorenz systems 24 2.3 Numerical methods 26 2.4 Results 32 2.4.1 Periodicity diagrams 32 2.4.2 Bifurcation diagrams and phase portraits 34 2.5 Discussion 40 3 A Physically Extended Lorenz System with Rotation and Density-Affecting Scalar 42 3.1 Introduction 42 3.2 Derivation 45 3.3 Effects of rotation and scalar 49 3.3.1 Fixed points and stability 49 3.3.2 Bifurcation structure in the rT-ฯƒ space 52 3.3.3 Bifurcations along rC and s 55 3.4 The case when ฮฒ < 0 65 3.4.1 Bifurcation and the onset of chaos 67 3.4.2 Chaotic attractors and associated flow patterns 73 3.5 Self-synchronization 81 3.6 Discussion 85 4 Coexisting Attractors in the Physically Extended Lorenz System 87 4.1 Introduction 87 4.2 Methodology 89 4.3 Results 92 4.3.1 Coexisting attractors in the LorenzStenflo system 92 4.3.2 Coexisting attractors under rotation and scalar 100 4.4 Discussion 110 5 The (3N)- and (3N + 2)-Dimensional Generalizations of the Lorenz System 113 5.1 Introduction 113 5.2 The generalized Lorenz systems 115 5.2.1 The Pk- and Qk-sets for nonlinear terms 115 5.2.2 The (3N)- and (3N + 2)-dimensional systems 116 5.2.3 Choosing the nonlinear pairs 117 5.3 Derivation 119 5.3.1 The (3N)-dimensional generalization 121 5.3.2 The (3N + 2)-dimensional generalization 126 5.4 Effects of dimension in parameter spaces 126 5.4.1 Linear stability analysis 126 5.4.2 Chaos in dimension-parameter spaces 130 5.5 Perspectives on predictability 136 5.5.1 Notions of predictability 136 5.5.2 Twin experiments and deviation time 138 5.6 Discussion 144 6 Chaos Synchronization in the Generalized Lorenz Systems 147 6.1 Introduction 147 6.2 Self-synchronization 149 6.2.1 Numerical evidence 149 6.2.2 Error subsystems 155 6.3 Application in image encryption 157 6.3.1 Demonstration: A simple approach 157 6.3.2 Demonstration: An alternative approach 168 6.4 Beyond self-synchronization 172 6.5 Discussion 180 7 The Generalized Lorenz Systems as a Testbed for Data Assimilation: The Ensemble Kalman Filter 182 7.1 Introduction 182 7.2 Methodology 187 7.2.1 Implementation of the ensemble Kalman filter 188 7.3 Results 191 7.3.1 Effects of ensemble size and model accuracy 191 7.3.2 Effects of observation frequency and accuracy 205 7.3.3 Effects of observation and model biases 214 7.4 Discussion 218 8 Can Chaos Theory Explain Non-Monotonic Dependence of Atmospheric Predictability on Model Vertical Resolution 220 8.1 Introduction 220 8.2 Background 222 8.2.1 Lorenz's ideas about atmospheric predictability 222 8.2.2 Model vertical resolution and predictability in numerical weather prediction 224 8.3 Results 229 8.3.1 Deviation time in the Lorenz systems revisited 229 8.3.2 WRF model control simulations 232 8.3.3 WRF model ensemble experiments and deviation time 241 8.3.4 Spatial distribution of deviation time 254 8.4 Discussion 261 9 Summary and Final Remarks 264 Bibliography 271 Abstract in Korean 295 Acknowledgments 299 Index 303๋ฐ•

    Fourth SIAM Conference on Applications of Dynamical Systems

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    Data-based Master Equations for the Stratosphere

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    Three-dimensional data-based master equations are developed and subsequently used to study climate variability in the stratosphere. Master equations are used to develop understanding of observed systems where no dynamic equations are available. Master equations are used in this thesis as prognostic equations for the probability density in a discretized phase space spanned by climate variables. The evolution of the probability density may then reveal information about the relationship between these variables. The phase space is partitioned into several hundred boxes of equal grid size representing at any one time states that the system can assume. In this discretized version of the phase space, the coefficients of a master equation may be estimated from the relative frequencies of transitions observed in a time series of the variables obtained from observations or numerical model runs. Data-based master equations are numerical structures whose success depends among other things on the resolution and volume of the available time series. These dependencies are studied on the basis of data from the famous three-component Lorenz convection model extended with a stochastic forcing. Time series of the desired length and time resolution can thus be generated easily. Furthermore, the results can be compared directly. Best results are obtained through the combination of a long data record and a coarse time resolution. The choice of the variables and their number also play a crucial role in the success of a master equation. Time series of stratospheric climate indices obtained from the reanalyses ERA-40 lead also to these last results. The stratosphere serves now as an implementation area. The master equation shows that during the eastern phase of the quasi-biennial oscillation (QBO) of equatorial zonal wind the arctic stratosphere is about 2 K warmer than during the western phase. Thus the relationship between QBO and arctic stratosphere can be quantified. The influence of the 11-year solar cycle is described by the master equation. It emerges that the relationship between QBO and temperature anomaly of the arctic stratosphere shows a dependence on solar variability. The implications of stratospheric processes on the climate in the troposphere are analysed with a master equation for a time series of an index of the Arctic Oscillation (AO) at stratospheric and tropospheric pressure levels. The master equation captures the main features of this interaction between stratosphere and troposphere. It is shown that anomalies of the AO in the middle stratospere propagate deeply into the troposphere with a time scale of 4 weeks. Furthermore the master equation shows that the influence of strong tropospheric AO-anomalies remains confined to the lower stratosphere

    Spatiotemporal behavior and nonlinear dynamics in a phase conjugate resonator

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    The work described can be divided into two parts. The first part is an investigation of the transient behavior and stability property of a phase conjugate resonator (PCR) below threshold. The second part is an experimental and theoretical study of the PCR's spatiotemporal dynamics above threshold. The time-dependent coupled wave equations for four-wave mixing (FWM) in a photorefractive crystal, with two distinct interaction regions caused by feedback from an ordinary mirror, was used to model the transient dynamics of a PCR below threshold. The conditions for self-oscillation were determined and the solutions were used to define the PCR's transfer function and analyze its stability. Experimental results for the buildup and decay times confirmed qualitatively the predicted behavior. Experiments were carried out above threshold to study the spatiotemporal dynamics of the PCR as a function of Pragg detuning and the resonator's Fresnel number. The existence of optical vortices in the wavefront were identified by optical interferometry. It was possible to describe the transverse dynamics and the spatiotemporal instabilities by modeling the three-dimensional-coupled wave equations in photorefractive FWM using a truncated modal expansion approach

    Fundamental Carrier-Envelope Phase Noise Limitations during Pulse Formation and Detection

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    The difference between the positions of the maximum peak of the carrier wave of a laser pulse and the maximum of its intensity envelope is termed carrier-envelope phase (CEP). In the last decades, the control and stabilization of this parameter has greatly improved, which enables many applications in research fields that rely on CEP-stable pulses such as attosecond science and optical frequency metrology. Further progress in these fields depends strongly on minimizing the CEP noise that restricts stabilization performance. While the CEP of most high repetition-rate low-energy laser oscillators has been stabilized to a remarkable precision, some types of oscillators show extensive noise that inhibits precise stabilization. The CEP stabilization performance of low repetition-rate high peak-power amplified laser systems also remains limited by noise, which is believed to stem mainly from the CEP detection process. In this thesis, the origins of the CEP noise within four oscillators as well as the noise induced by the measurement of the CEP of amplified pulses are investigated. In the first part, the properties of the CEP noise of one Ti:sapphire oscillator and three different fiber oscillators are extracted by analyzing the unstabilized CEP traces by means of time-resolved correlation analysis of carrier-envelope amplitude and phase noise as well as by methods that reveal the underlying statistical noise properties. In the second part, investigations into the origin of CEP noise induced by the measurement of the CEP of amplified pulses are conducted by comparing several different CEP detection designs that are based on f -2 f interferometry. These detection setups differ in the employed sources of spectral broadening as well as frequency doubling media, both necessary steps to measure the CEP. The results in both parts of this thesis show that white quantum noise dominates most CEP measurements. In one particular fiber oscillator, the strong white noise is found to be a result of a correlating mechanism within the employed SESAM. During amplifier CEP detection, the CEP noise is found to be originating only to a marginal degree from the number of photons that are detected during the measurement, which excludes shot noise as a limiting source. Instead, the analysis reveals that the origin of the observed strong white noise can be interpreted as a loss of coherence during detection. This type of coherence is termed here intra-pulse coherence and describes the phase transfer within f -2 f interferometry. Its degradation is a result of amplitude-to-phase coupling during the spectral broadening process that leads to pulse-to-pulse fluctuations of the phases at the edges of the extended spectrum. Numerical simulations support the concept of intra-pulse coherence degradation and show that the degradation is substantially stronger during plasma-driven spectral broadening as compared to self-phase modulation-dominated spectral broadening. This difference in degradation also explains the much stronger CEP noise typically observed in amplified systems as compared to oscillators, as the former typically rely on filamentation-based and hence plasma-dominated spectral broadening for CEP detection. The concept of intra-pulse coherence constitutes a novel measure to assess the suitability of a spectral broadening mechanism for application in active as well as in passive CEP stabilization schemes and provides new strategies to reduce the impact of the CEP detection on the overall stabilization performance of most lasers.Diese Arbeit beschรคftigt sich mit der Identifizierung und Minimierung fundamentaler Rauschquellen, die zu einer Limitierung des erreichbaren Carrier-Envelope Phasen (CEP) Jitters fรผhren. Die Carrier-Envelope Phase beschreibt die Differenz zwischen dem Maximum der Trรคgerwelle und dem Scheitelpunkt der Intensitรคtseinhรผllenden. In den letzten Jahrzehnten hat sich die Kontrolle und Stabilisierung der CEP deutlich verbessert, was zu einem schnellen Fortschritt in Forschungsfeldern gefรผhrt hat, bei denen CEP-stabile Pulse notwendig sind. Diese Forschungsfelder umfassen die Attosekundenforschung und optische Frequenzmetrologie. Weitere Entwicklungen in diesen Feldern hรคngt stark von der Minimierung von CEP Rauschen ab, welches die CEP Stabilisierung stark beeintrรคchtigt. Obwohl die CEP der Pulse der meisten Laseroszillatoren mit hohen Repetitionsraten รคuรŸerst genau stabilisiert werden kann, existieren einige Laseroszillatoren bei denen starke Rauschquellen eine Stabilisierung verhindern oder stark einschrรคnken. Des Weiteren zeigen vor Allem verstรคrkte System mit niedrigen Repetitionsraten und hohen Spitzenleistungen eine Beschrรคnkung der CEP Stabilisierung aufgrund von Rauschen, dass vermutlich zum groรŸen Teil durch den Detektionsprozess entsteht. In dieser Arbeit ist der Ursprung von CEP Rauschen in vier unterschiedlichen Laseroszillatoren sowie wรคhrend der Detektion der CEP von verstรคrkten Systemen untersucht worden. Im ersten Teil wurden die Eigenschaften des CEP Rauschens eines Ti:Saphir-basierten Oszillators und drei verschiedener Faserlaser analysiert. Hierzu wurde das Rauschen unter anderem mittels zeitaufgelรถster Korrelationsanalyse von Carrier-Envelope Amplituden- und Phasenrauschen sowie mittels Methoden, die die statistischen Eigenschaften des Rauschens offenlegen, analysiert. Im zweiten Teil der Arbeit wurde das Rauschen untersucht, welches durch den Messprozess der CEP von verstรคrkten Pulsen mittels f -2 f Interferometrie entsteht. Experimentell wurden hierzu vier unterschiedliche Detektionsanordnungen verwendet, die sich durch die Nutzung unterschiedlicher nichtlinearer Prozesse zum Erzeugen der spektralen Verbreiterung sowie zur Erzeugung der zweiten Harmonischen unterscheiden. Die Ergebnisse in beiden Teilen der Arbeit zeigen dominierendes weiรŸes Quantenrauschen in den meisten CEP Messungen. In einem bestimmten Faserlaser, in dem besonders starkes weiรŸes Rauschen vorlag, konnte der Ursprung einerWechselwirkung innerhalb des verwendeten halbleiterbasierten sรคttigbaren Absorbers zugeordnet werden. Bei der Detektion der CEP bei verstรคrkten Systemen wurde hingegen gezeigt, dass niedrige Photonenzahlen und damit Schrotrauschen nur zum kleinen Teil fรผr die starken weiรŸen Rauschanteile verantwortlich gemacht werden kann. Stattdessen kann die Ursache des starken Rauschens einem Verlust von Kohรคrenz zugeordnet werden. Diese Art von Kohรคrenz ist hier mit intra-Puls Kohรคrenz bezeichnet und beschreibt den Phasentransfer innerhalb der Detektion mittels f -2 f Interferometrie. Der Verlust von intra-Puls Kohรคrenz ist eine Folge von Amplituden-zu-Phasen Koppelung wรคhrend der spektralen Verbreiterung. Von Puls zu Puls fรผhrt dies zu Fluktuationen der Phase an beiden Rรคndern der erzeugten spektralen Verbreiterung. Numerische Simulationen unterstรผtzen das Konzept der intra-Puls Kohรคrenz und zeigen auf, dass die Degradation bedeutend stรคrker bei plasmadominierten Prozessen ausfรคllt als im Vergleich zu spektraler Verbreiterung mittels Selbstphasenmodulation. Dieser unterschiedlich starke Verlust der intra-Puls Kohรคrenz erklรคrt das deutlich hรถhere Rauschniveau in verstรคrkten Systemen im Vergleich zu Oszillatoren, da verstรคrkte Systeme plasmadominierte Prozesse zur spektralen Verbreiterung nutzen. Das Konzept der intra-Puls Kohรคrenz stellt ein neues MaรŸ zur Einschรคtzung einer Methode zur spektralen Verbreiterung fรผr eine bestimmte Anwendung dar, die sowohl in aktiven sowie passiven CEP Stabilisierungen von Lasern eine Rolle spielt. Es ermรถglicht somit neue Strategien, um den Einfluss der Detektion auf die CEP Stabilisierung der meisten Laser zu senken

    5th EUROMECH nonlinear dynamics conference, August 7-12, 2005 Eindhoven : book of abstracts

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