kokyuroku.dvi
|
|
|
- ともみ あかさか
- 6 years ago
- Views:
Transcription
1 On Applications of Rigorous Computing to Dynamical Systems (Zin ARAI) Department of Mathematics, Kyoto University 1 [12, 13] Lorenz 2 Lorenz Lorenz 2.1 Lorenz E. Lorenz R 3 ẋ = σx + σy ẏ = ρx y xz ż = βz + xy Lorenz σ, ρ, β Lorenz (σ, ρ, β) =(10, 28, 8/3)
2 z y x 1 Lorenz Lorenz Hilbert 23 S. Smale Lorenz 1990 W. Tucker k Σ k := i=0 {1, 2,...,k} k full-shift s :Σ k Σ k s(x 0,x 1,...)=(x 1,x 2,...) k k A =(a ij ) Σ A := {(s n ) Σ k a sn s n+1 0} s(σ A )=Σ A. 1 (Mishaikow-Mrozek[8, 9, 10]). Lorenz (σ, ρ, β) (10, 28, 8/3) I {z =27} P well-defined π :Inv(I,P) Σ 6 π P = s π 2
3 Σ A π(inv(i,p)) A A = (Galias-Zgliczyński[6]). Lorenz (σ, ρ, β) (10, 28, 8/3) I {z =27} P well-defined π :Inv(I,P 2 ) Σ 2 π P 2 = s π π Lorenz 3 (Tucker[14]). (σ, ρ, β) =(10, 28, 8/3) Lorenz robust starange attractor robust strange attractor [4] Tucker Mischaikow-Mrozek Galias-Zgliczyński 0 Mischaikow-Mrozek Galias-Zgliczyński Tucker Normal Form 1. Tucker Normal Form Poincaré 2. Poincaré 3
4 Tucker Euler Galias-Zgliczyński 4 Taylor Mischaikow-Mrozek 4 Runge-Kutta 4 Runge-Kutta Galias-Zgliczyński 4 Runge-Kutta 4 Taylor Taylor wrapping effect 2.3 Wrapping Effect 2 X X 4
5 X X 2 wrapping effect X wrapping effect Lorenz wrapping effect Tucker X wrapping effect Galias-Zgliczyński wrapping effect. x ɛ B(x, ɛ) h x h P P logarithmic norm P P B(x, ɛ) P Mischaikow-Mrozek wrapping effect {z =27} {z =27} wrapping effect wrapping effect 2 (x, y) (x + y, x y) X Lohner [16] 5
6 3 Results for Discrete Dynamical Systems [11] 3.1 X f : X X X f f(s) =S S X f int N N 4. S N S N, S =Inv(N,f) :={x N {x i } i Z N s.t. x 0 = x, f(x i )=x i+1 for all i Z} S =Inv(N,f) int N N S N f f C 0 g N Inv(N,f) Inv(N,g) N 6
7 5. S index pair P =(P 1,P 0 ) P 1 \P 0 S f(p 0 ) P 1 P 0 f(p 1 \P 0 ) P 1 3 P 1 /P 0 P 1 P 0 P 0 [P 0 ] f P : P 1 /P 0 P 1 /P 0 { [f(x)] f(x) P 1 f P ([x]) := [P 0 ] f P index map index map S f [7] P 1 /P 0 H (P 1 /P 0, [P 0 ]) f P f P : H (P 1 /P 0, [P 0 ]) H (P 1 /P 0, [P 0 ]) H (P 1 /P 0, [P 0 ]) (P 1 /P 0, [P 0 ]) H (P 1 /P 0, [P 0 ]) H k (P 1 /P 0, [P 0 ]) f P 0 k f P k : H k (P 1 /P 0, [P 0 ]) H k (P 1 /P 0, [P 0 ]) S index pair H (P 1 /P 0, [P 0 ]) f P 6. f : X X g : Y Y m r : X Y, s : Y X r f = g r, s g = f s, r s = g m,s r = f m S index pair P = (P 1,P 0 ) Q =(Q 1,Q 0 ) S index pair f P f Q 7
8 7. S P =(P 1,P 0 ) S index pair f P 8(Ważewski principle [7, 11]). P =(P 1,P 0 ) S index pair f P 0:{0} {0} S 9 (Index pair Lefschetz [7]). P = (P 1,P 0 ) S index pair L(f P ):= k ( 1)k tr f P k 0 S k ( 1)k tr f n P k 0 S f n [7, 15] connecting orbit [3] index pair index map 3.2 X = R n R n R n n n d i (i =1...n) { n } Ω:= [k i d i, (k i +1)d i ]:k i Z i=1 R n Ω B Ω B B R n f f ω Ω f( ω ) f(ω) f( ω ) Ω f( ω ) Ω F(ω) F :Ω {Ω } : ω {ω Ω: f( ω ) ω } f( ω ) int F(ω) f( ω ) F(ω) 8
9 I Ω I I index pair 1. I 2 2. I Inv( I,f) int I I B Ω o(b) :={ω Ω: ω B }, d(b) :=o(b) \B o(b) Ω B Inv(B, F) {ω B γ : Z B γ(0) = ω γ(k +1) F(γ(k)) } f( ω ) int F(ω) Inv( I,f) Inv(I, F) o(inv(i, F)) I Inv( I,f) Inv(I, F) int o(inv(i, F)) int I I o(inv(i, F)) I I [7] I I 3. I f B =Inv(I, F) (P 1, P 0 )= ( (d(b) F(B)) B, d(b) F(B) ) P =( P 1, P 0 ) Inv( I,f) index pair [7] 4. [7] H ( P 1 / P 0, [ P 0 ]) f P f F 4 CHomP F 9
10 y x 3 7 index pair H a,b : R 2 R 2 :(x, y) (a x 2 + by, x) 9 Hénon Hénon Lorenz a =1.4, b =0.3 3 index pair P 1 \ P 0 P 0 CHomP f P 1 = : Z 7 Z f P 0 tr((f P 1 ) 7 )=7 9 Inv(P 1 \ P 0 ) f 7 P 1 f Inv(P 1 \ P 0 ) 7 Hénon [3] [2] [1] 10
11 4 Software Packages 4.1 GAIO (Global Analysis of Invariant Objects) M. Dellnitz and O. Junge Python MATLAB MATLAB GAIO 3 GAIO PROFIL C/C++ MATLAB 4.2 CHomP (Computational HOMology Project) Conley P. Pilarczyk 4.3 BIAS (Basic Interval Arithmetic Subroutines) 11
12 O. Knüppel C PROFIL BIASINTERVAL C PROFIL b4m BIAS BiasF.c BIAS sin, cos, exp BiasExp libm exp BIAS 4.4 b4m (BIAS for MATLAB) J. Zemke MATLAB BAIS x = interval(1,2) x [1, 2] MATLAB BIAS BIAS 4.5 PROFIL (Programmer s Runtime Optimized Fast Interval Library) BIAS O. Knüppel C++ BIAS BIAS 4.6 CAPD (Computer Assisted Proofs in Dynamics) 2 [6] Z. Galias P. Zgliczyński CHomP P. Pilarczyk 2 Lohner 12
13 5 [1],,, 15 (2005), [2] Z. Arai, On Hyperbolic Plateaus of the Hénon Maps, preprint. [3] Z. Arai and K. Mischaikow, Rigorous Computations of Homoclinic Tangencies, preprint. [4] C. Bonatti, L. Díaz and M. Viana, Dyamics Beyound Uniform Hyperbolicity, Encyclopaedia of Mathematical Sciences, 102, Springer-Verlag, [5] M. Dellnitz and O. Junge, The algorithms behind GAIO - set oriented numerical methods for dynamical systems, Ergodic theory, analysis, and efficient simulation of dynamical systems, Springer, Berlin, 2001, , [6] Z. Galias and P. Zgliczyński, Computer assisted proof of chaos in the Lorenz equations, Physica D, 115 (1998), [7] T. Kaczynski, K. Mischaikow andm. Mrozek, Computational Homology, Applied Mathematical Sciences, 157, Springer-Verlag, [8] K. Mischaikow and M. Mrozek, Chaos in the Lorenz equations: a computer-assisted proof, Bull.Amer.Math.Soc.(N.S.), 3 (1995), [9] K. Mischaikow and M. Mrozek, Chaos in the Lorenz equations: a computer-assisted proof. II. Details, Mathematics of Computation, 67 (1998), [10] K. Mischaikow and M. Mrozek, Chaos in the Lorenz equations: a computer-assisted proof. III. Classical parameter vallues, J. Differential Equations, 169 (2001), [11] K. Mischaikow and M. Mrozek, The Conley index theory, Handbook of Dynamical Systems II, North-Holland, 2002, [12],,, [13],,, [14] W. Tucker, A rigorous ODE solver and Smale s 14th problem, Found. Comput. Math., 2 (2002), [15] A. Szymczak, The Conley index and symbolic dynamics, Topology, 35 (1996), [16] P. Zgliczyński, C 1 Lohner algorithm, Fuound. Comput. Math., 2 (2002),
sakigake1.dvi
(Zin ARAI) [email protected] http://www.cris.hokudai.ac.jp/arai/ 1 dynamical systems ( mechanics ) dynamical systems 3 G X Ψ:G X X, (g, x) Ψ(g, x) =:Ψ g (x) Ψ id (x) =x, Ψ gh (x) =Ψ h (Ψ g (x)) (
Shunsuke Kobayashi 1 [6] [11] [7] u t = D 2 u 1 x 2 + f(u, v) + s L u(t, x)dx, L x (0.L), t > 0, Neumann 0 v t = D 2 v 2 + g(u, v), x (0, L), t > 0. x
Shunsuke Kobayashi [6] [] [7] u t = D 2 u x 2 + fu, v + s L ut, xdx, L x 0.L, t > 0, Neumann 0 v t = D 2 v 2 + gu, v, x 0, L, t > 0. x2 u u v t, 0 = t, L = 0, x x. v t, 0 = t, L = 0.2 x x ut, x R vt, x
2008chom.pdf
CHomP Pawe l Pilarczyk 1 CHomP Computational Homology Project [3] OS Windows Mac Unix Linux [3] CHomP [3] 2 3 CHomP CHomP 4 5 C++ [1] 2 CHomP 1 2 K 1 = { A 1 A 2 A 3, A 1 A 2, A 2 A 3, A 1 A 3, A 3 A 4,
第5章 偏微分方程式の境界値問題
October 5, 2018 1 / 113 4 ( ) 2 / 113 Poisson 5.1 Poisson ( A.7.1) Poisson Poisson 1 (A.6 ) Γ p p N u D Γ D b 5.1.1: = Γ D Γ N 3 / 113 Poisson 5.1.1 d {2, 3} Lipschitz (A.5 ) Γ D Γ N = \ Γ D Γ p Γ N Γ
A
A05-132 2010 2 11 1 1 3 1.1.......................................... 3 1.2..................................... 3 1.3..................................... 3 2 4 2.1............................... 4 2.2
koji07-01.dvi
2007 I II III 1, 2, 3, 4, 5, 6, 7 5 10 19 (!) 1938 70 21? 1 1 2 1 2 2 1! 4, 5 1? 50 1 2 1 1 2 2 1?? 2 1 1, 2 1, 2 1, 2, 3,... 3 1, 2 1, 3? 2 1 3 1 2 1 1, 2 2, 3? 2 1 3 2 3 2 k,l m, n k,l m, n kn > ml...?
II ( ) (7/31) II ( [ (3.4)] Navier Stokes [ (6/29)] Navier Stokes 3 [ (6/19)] Re
II 29 7 29-7-27 ( ) (7/31) II (http://www.damp.tottori-u.ac.jp/~ooshida/edu/fluid/) [ (3.4)] Navier Stokes [ (6/29)] Navier Stokes 3 [ (6/19)] Reynolds [ (4.6), (45.8)] [ p.186] Navier Stokes I Euler Navier
86 6 r (6) y y d y = y 3 (64) y r y r y r ϕ(x, y, y,, y r ) n dy = f(x, y) (6) 6 Lipschitz 6 dy = y x c R y(x) y(x) = c exp(x) x x = x y(x ) = y (init
8 6 ( ) ( ) 6 ( ϕ x, y, dy ), d y,, dr y r = (x R, y R n ) (6) n r y(x) (explicit) d r ( y r = ϕ x, y, dy ), d y,, dr y r y y y r (6) dy = f (x, y) (63) = y dy/ d r y/ r 86 6 r (6) y y d y = y 3 (64) y
L P y P y + ɛ, ɛ y P y I P y,, y P y + I P y, 3 ŷ β 0 β y β 0 β y β β 0, β y x x, x,, x, y y, y,, y x x y y x x, y y, x x y y {}}{,,, / / L P / / y, P
005 5 6 y β + ɛ {x, x,, x p } y, {x, x,, x p }, β, ɛ E ɛ 0 V ɛ σ I 3 rak p 4 ɛ i N 0, σ ɛ ɛ y β y β y y β y + β β, ɛ β y + β 0, β y β y ɛ ɛ β ɛ y β mi L y y ŷ β y β y β β L P y P y + ɛ, ɛ y P y I P y,,
ii 3.,. 4. F. (), ,,. 8.,. 1. (75%) (25%) =7 20, =7 21 (. ). 1.,, (). 3.,. 1. ().,.,.,.,.,. () (12 )., (), 0. 2., 1., 0,.
24(2012) (1 C106) 4 11 (2 C206) 4 12 http://www.math.is.tohoku.ac.jp/~obata,.,,,.. 1. 2. 3. 4. 5. 6. 7.,,. 1., 2007 (). 2. P. G. Hoel, 1995. 3... 1... 2.,,. ii 3.,. 4. F. (),.. 5... 6.. 7.,,. 8.,. 1. (75%)
2.1 H f 3, SL(2, Z) Γ k (1) f H (2) γ Γ f k γ = f (3) f Γ \H cusp γ SL(2, Z) f k γ Fourier f k γ = a γ (n)e 2πinz/N n=0 (3) γ SL(2, Z) a γ (0) = 0 f c
GL 2 1 Lie SL(2, R) GL(2, A) Gelbart [Ge] 1 3 [Ge] Jacquet-Langlands [JL] Bump [Bu] Borel([Bo]) ([Ko]) ([Mo]) [Mo] 2 2.1 H = {z C Im(z) > 0} Γ SL(2, Z) Γ N N Γ (N) = {γ SL(2, Z) γ = 1 2 mod N} g SL(2,
I A A441 : April 15, 2013 Version : 1.1 I Kawahira, Tomoki TA (Shigehiro, Yoshida )
I013 00-1 : April 15, 013 Version : 1.1 I Kawahira, Tomoki TA (Shigehiro, Yoshida) http://www.math.nagoya-u.ac.jp/~kawahira/courses/13s-tenbou.html pdf * 4 15 4 5 13 e πi = 1 5 0 5 7 3 4 6 3 6 10 6 17
( )/2 hara/lectures/lectures-j.html 2, {H} {T } S = {H, T } {(H, H), (H, T )} {(H, T ), (T, T )} {(H, H), (T, T )} {1
( )/2 http://www2.math.kyushu-u.ac.jp/ hara/lectures/lectures-j.html 1 2011 ( )/2 2 2011 4 1 2 1.1 1 2 1 2 3 4 5 1.1.1 sample space S S = {H, T } H T T H S = {(H, H), (H, T ), (T, H), (T, T )} (T, H) S
x () g(x) = f(t) dt f(x), F (x) 3x () g(x) g (x) f(x), F (x) (3) h(x) = x 3x tf(t) dt.9 = {(x, y) ; x, y, x + y } f(x, y) = xy( x y). h (x) f(x), F (x
[ ] IC. f(x) = e x () f(x) f (x) () lim f(x) lim f(x) x + x (3) lim f(x) lim f(x) x + x (4) y = f(x) ( ) ( s46). < a < () a () lim a log xdx a log xdx ( ) n (3) lim log k log n n n k=.3 z = log(x + y ),
2000年度『数学展望 I』講義録
2000 I I IV I II 2000 I I IV I-IV. i ii 3.10 (http://www.math.nagoya-u.ac.jp/ kanai/) 2000 A....1 B....4 C....10 D....13 E....17 Brouwer A....21 B....26 C....33 D....39 E. Sperner...45 F....48 A....53
. T ::= x f n t 1 t n F n,m (x(t 1 t n )t 1 t m) x, f n n, F n,m n, m-., F n,m (x(t 1 t n )t 1 t m), x, t 1,..., t n, t 1,..., t m. F n,m (x(t 1 t n )
Kazuki Nakamura Department of Mathematical and Computing Science, Tokyo Institute of Technology * 1 Kashima Ryo Department of Mathematical and Computing Science, Tokyo Institute of Technology 1,,., Σ,..,.
I, II 1, A = A 4 : 6 = max{ A, } A A 10 10%
1 2006.4.17. A 3-312 tel: 092-726-4774, e-mail: [email protected], http://www.math.kyushu-u.ac.jp/ hara/lectures/lectures-j.html Office hours: B A I ɛ-δ ɛ-δ 1. 2. A 1. 1. 2. 3. 4. 5. 2. ɛ-δ 1. ɛ-n
, CH n. CH n, CP n,,,., CH n,,. RH n ( Cartan )., CH n., RH n CH n,,., RH n, CH n., RH n ( ), CH n ( 1.1 (v), (vi) )., RH n,, CH n,., CH n,. 1.2, CH n
( ), Jürgen Berndt,.,. 1, CH n.,,. 1.1 ([6]). CH n (n 2), : (i) CH k (k = 0,..., n 1) tube. (ii) RH n tube. (iii). (iv) ruled minimal, equidistant. (v) normally homogeneous submanifold F k tube. (vi) normally
(a) (b) (c) Canny (d) 1 ( x α, y α ) 3 (x α, y α ) (a) A 2 + B 2 + C 2 + D 2 + E 2 + F 2 = 1 (3) u ξ α u (A, B, C, D, E, F ) (4) ξ α (x 2 α, 2x α y α,
[II] Optimization Computation for 3-D Understanding of Images [II]: Ellipse Fitting 1. (1) 2. (2) (edge detection) (edge) (zero-crossing) Canny (Canny operator) (3) 1(a) [I] [II] [III] [IV ] E-mail [email protected]
2 2 1?? 2 1 1, 2 1, 2 1, 2, 3,... 1, 2 1, 3? , 2 2, 3? k, l m, n k, l m, n kn > ml...? 2 m, n n m
2009 IA I 22, 23, 24, 25, 26, 27 4 21 1 1 2 1! 4, 5 1? 50 1 2 1 1 2 1 4 2 2 2 1?? 2 1 1, 2 1, 2 1, 2, 3,... 1, 2 1, 3? 2 1 3 1 2 1 1, 2 2, 3? 2 1 3 2 3 2 k, l m, n k, l m, n kn > ml...? 2 m, n n m 3 2
³ÎΨÏÀ
2017 12 12 Makoto Nakashima 2017 12 12 1 / 22 2.1. C, D π- C, D. A 1, A 2 C A 1 A 2 C A 3, A 4 D A 1 A 2 D Makoto Nakashima 2017 12 12 2 / 22 . (,, L p - ). Makoto Nakashima 2017 12 12 3 / 22 . (,, L p
Trapezoidal Rule θ = 1/ x n x n 1 t = 1 [f(t n 1, x n 1 ) + f(t n, x n )] (6) 1. dx dt = f(t, x), x(t 0) = x 0 (7) t [t 0, t 1 ] f t [t 0, t 1 ], x x
University of Hyogo 8 8 1 d x(t) =f(t, x(t)), dt (1) x(t 0 ) =x 0 () t n = t 0 + n t x x n n x n x 0 x i i = 0,..., n 1 x n x(t) 1 1.1 1 1 1 0 θ 1 θ x n x n 1 t = θf(t n 1, x n 1 ) + (1 θ)f(t n, x n )
最新耐震構造解析 ( 第 3 版 ) サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 第 3 版 1 刷発行時のものです.
最新耐震構造解析 ( 第 3 版 ) サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/052093 このサンプルページの内容は, 第 3 版 1 刷発行時のものです. i 3 10 3 2000 2007 26 8 2 SI SI 20 1996 2000 SI 15 3 ii 1 56 6
d dt A B C = A B C d dt x = Ax, A 0 B 0 C 0 = mm 0 mm 0 mm AP = PΛ P AP = Λ P A = ΛP P d dt x = P Ax d dt (P x) = Λ(P x) d dt P x =
3 MATLAB Runge-Kutta Butcher 3. Taylor Taylor y(x 0 + h) = y(x 0 ) + h y (x 0 ) + h! y (x 0 ) + Taylor 3. Euler, Runge-Kutta Adams Implicit Euler, Implicit Runge-Kutta Gear y n+ y n (n+ ) y n+ y n+ y n+
(1) 3 A B E e AE = e AB OE = OA + e AB = (1 35 e ) e OE z 1 1 e E xy e = 0 e = 5 OE = ( 2 0 0) E ( 2 0 0) (2) 3 E P Q k EQ = k EP E y 0
(1) 3 A B E e AE = e AB OE = OA + e AB = (1 35 e 0 1 15 ) e OE z 1 1 e E xy 5 1 1 5 e = 0 e = 5 OE = ( 2 0 0) E ( 2 0 0) (2) 3 E P Q k EQ = k EP E y 0 Q y P y k 2 M N M( 1 0 0) N(1 0 0) 4 P Q M N C EP
微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 初版 1 刷発行時のものです.
微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. ttp://www.morikita.co.jp/books/mid/00571 このサンプルページの内容は, 初版 1 刷発行時のものです. i ii 014 10 iii [note] 1 3 iv 4 5 3 6 4 x 0 sin x x 1 5 6 z = f(x, y) 1 y = f(x)
( ) ( )
20 21 2 8 1 2 2 3 21 3 22 3 23 4 24 5 25 5 26 6 27 8 28 ( ) 9 3 10 31 10 32 ( ) 12 4 13 41 0 13 42 14 43 0 15 44 17 5 18 6 18 1 1 2 2 1 2 1 0 2 0 3 0 4 0 2 2 21 t (x(t) y(t)) 2 x(t) y(t) γ(t) (x(t) y(t))
2016 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1 16 2 1 () X O 3 (O1) X O, O (O2) O O (O3) O O O X (X, O) O X X (O1), (O2), (O3) (O2) (O3) n (O2) U 1,..., U n O U k O k=1 (O3) U λ O( λ Λ) λ Λ U λ O 0 X 0 (O2) n =
Gauss Fuchs rigid rigid rigid Nicholas Katz Rigid local systems [6] Fuchs Katz Crawley- Boevey[1] [7] Katz rigid rigid Katz middle convolu
rigidity 2014.9.1-2014.9.2 Fuchs 1 Introduction y + p(x)y + q(x)y = 0, y 2 p(x), q(x) p(x) q(x) Fuchs 19 Fuchs 83 Gauss Fuchs rigid rigid rigid 7 1970 1996 Nicholas Katz Rigid local systems [6] Fuchs Katz
等質空間の幾何学入門
2006/12/04 08 [email protected] i, 2006/12/04 08. 2006, 4.,,.,,.,.,.,,.,,,.,.,,.,,,.,. ii 1 1 1.1 :................................... 1 1.2........................................ 2 1.3......................................
空間多次元 Navier-Stokes 方程式に対する無反射境界条件
81 Navier-Stokes Poinsot Lele Poinsot Lele Thompson Euler Navier-Stokes A Characteristic Nonreflecting Boundary Condition for the Multidimensional Navier-Stokes Equations Takaharu YAGUCHI, Kokichi SUGIHARA
ALGEBRA I Hiroshi SUZUKI Department of Mathematics International Christian University
ALGEBRA I Hiroshi SUZUKI Department of Mathematics International Christian University 2004 1 1 1 2 2 1 3 3 1 4 4 1 5 5 1 6 6 1 7 7 1 8 8 1 9 9 1 10 10 1 E-mail:[email protected] 0 0 1 1.1 G G1 G a, b,
9 2 1 f(x, y) = xy sin x cos y x y cos y y x sin x d (x, y) = y cos y (x sin x) = y cos y(sin x + x cos x) x dx d (x, y) = x sin x (y cos y) = x sin x
2009 9 6 16 7 1 7.1 1 1 1 9 2 1 f(x, y) = xy sin x cos y x y cos y y x sin x d (x, y) = y cos y (x sin x) = y cos y(sin x + x cos x) x dx d (x, y) = x sin x (y cos y) = x sin x(cos y y sin y) y dy 1 sin
waseda2010a-jukaiki1-main.dvi
November, 2 Contents 6 2 8 3 3 3 32 32 33 5 34 34 6 35 35 7 4 R 2 7 4 4 9 42 42 2 43 44 2 5 : 2 5 5 23 52 52 23 53 53 23 54 24 6 24 6 6 26 62 62 26 63 t 27 7 27 7 7 28 72 72 28 73 36) 29 8 29 8 29 82 3
* 1 1 (i) (ii) Brückner-Hartree-Fock (iii) (HF, BCS, HFB) (iv) (TDHF,TDHFB) (RPA) (QRPA) (v) (vi) *
* 1 1 (i) (ii) Brückner-Hartree-Fock (iii) (HF, BCS, HFB) (iv) (TDHF,TDHFB) (RPA) (QRPA) (v) (vi) *1 2004 1 1 ( ) ( ) 1.1 140 MeV 1.2 ( ) ( ) 1.3 2.6 10 8 s 7.6 10 17 s? Λ 2.5 10 10 s 6 10 24 s 1.4 ( m
,. Black-Scholes u t t, x c u 0 t, x x u t t, x c u t, x x u t t, x + σ x u t, x + rx ut, x rux, t 0 x x,,.,. Step 3, 7,,, Step 6., Step 4,. Step 5,,.
9 α ν β Ξ ξ Γ γ o δ Π π ε ρ ζ Σ σ η τ Θ θ Υ υ ι Φ φ κ χ Λ λ Ψ ψ µ Ω ω Def, Prop, Th, Lem, Note, Remark, Ex,, Proof, R, N, Q, C [a, b {x R : a x b} : a, b {x R : a < x < b} : [a, b {x R : a x < b} : a,
No δs δs = r + δr r = δr (3) δs δs = r r = δr + u(r + δr, t) u(r, t) (4) δr = (δx, δy, δz) u i (r + δr, t) u i (r, t) = u i x j δx j (5) δs 2
No.2 1 2 2 δs δs = r + δr r = δr (3) δs δs = r r = δr + u(r + δr, t) u(r, t) (4) δr = (δx, δy, δz) u i (r + δr, t) u i (r, t) = u i δx j (5) δs 2 = δx i δx i + 2 u i δx i δx j = δs 2 + 2s ij δx i δx j
x = a 1 f (a r, a + r) f(a) r a f f(a) 2 2. (a, b) 2 f (a, b) r f(a, b) r (a, b) f f(a, b)
2011 I 2 II III 17, 18, 19 7 7 1 2 2 2 1 2 1 1 1.1.............................. 2 1.2 : 1.................... 4 1.2.1 2............................... 5 1.3 : 2.................... 5 1.3.1 2.....................................
Part () () Γ Part ,
Contents a 6 6 6 6 6 6 6 7 7. 8.. 8.. 8.3. 8 Part. 9. 9.. 9.. 3. 3.. 3.. 3 4. 5 4.. 5 4.. 9 4.3. 3 Part. 6 5. () 6 5.. () 7 5.. 9 5.3. Γ 3 6. 3 6.. 3 6.. 3 6.3. 33 Part 3. 34 7. 34 7.. 34 7.. 34 8. 35
24 I ( ) 1. R 3 (i) C : x 2 + y 2 1 = 0 (ii) C : y = ± 1 x 2 ( 1 x 1) (iii) C : x = cos t, y = sin t (0 t 2π) 1.1. γ : [a, b] R n ; t γ(t) = (x
24 I 1.1.. ( ) 1. R 3 (i) C : x 2 + y 2 1 = 0 (ii) C : y = ± 1 x 2 ( 1 x 1) (iii) C : x = cos t, y = sin t (0 t 2π) 1.1. γ : [a, b] R n ; t γ(t) = (x 1 (t), x 2 (t),, x n (t)) ( ) ( ), γ : (i) x 1 (t),
Untitled
II 14 14-7-8 8/4 II (http://www.damp.tottori-u.ac.jp/~ooshida/edu/fluid/) [ (3.4)] Navier Stokes [ 6/ ] Navier Stokes 3 [ ] Reynolds [ (4.6), (45.8)] [ p.186] Navier Stokes I 1 balance law t (ρv i )+ j
v v = v 1 v 2 v 3 (1) R = (R ij ) (2) R (R 1 ) ij = R ji (3) 3 R ij R ik = δ jk (4) i=1 δ ij Kronecker δ ij = { 1 (i = j) 0 (i
1. 1 1.1 1.1.1 1.1.1.1 v v = v 1 v 2 v 3 (1) R = (R ij ) (2) R (R 1 ) ij = R ji (3) R ij R ik = δ jk (4) δ ij Kronecker δ ij = { 1 (i = j) 0 (i j) (5) 1 1.1. v1.1 2011/04/10 1. 1 2 v i = R ij v j (6) [
ohp_06nov_tohoku.dvi
2006 11 28 1. (1) ẋ = ax = x(t) =Ce at C C>0 a0 x(t) 0(t )!! 1 0.8 0.6 0.4 0.2 2 4 6 8 10-0.2 (1) a =2 C =1 1. (1) τ>0 (2) ẋ(t) = ax(t τ) 4 2 2 4 6 8 10-2 -4 (2) a =2 τ =1!! 1. (2) A. (2)
all.dvi
38 5 Cauchy.,,,,., σ.,, 3,,. 5.1 Cauchy (a) (b) (a) (b) 5.1: 5.1. Cauchy 39 F Q Newton F F F Q F Q 5.2: n n ds df n ( 5.1). df n n df(n) df n, t n. t n = df n (5.1) ds 40 5 Cauchy t l n mds df n 5.3: t
function2.pdf
2... 1 2009, http://c-faculty.chuo-u.ac.jp/ nishioka/ 2 11 38 : 5) i) [], : 84 85 86 87 88 89 1000 ) 13 22 33 56 92 147 140 120 100 80 60 40 20 1 2 3 4 5 7.1 7 7.1 1. *1 e = 2.7182 ) fx) e x, x R : 7.1)
20 4 20 i 1 1 1.1............................ 1 1.2............................ 4 2 11 2.1................... 11 2.2......................... 11 2.3....................... 19 3 25 3.1.............................
非可換Lubin-Tate理論の一般化に向けて
Lubin-Tate 2012 9 18 ( ) Lubin-Tate 2012 9 18 1 / 27 ( ) Lubin-Tate 2012 9 18 2 / 27 Lubin-Tate p 1 1 ( ) Lubin-Tate 2012 9 18 2 / 27 Lubin-Tate p 1 1 Lubin-Tate GL n n 1 Lubin-Tate ( ) Lubin-Tate 2012
i
009 I 1 8 5 i 0 1 0.1..................................... 1 0.................................................. 1 0.3................................. 0.4........................................... 3
1 1.1 ( ). z = a + bi, a, b R 0 a, b 0 a 2 + b 2 0 z = a + bi = ( ) a 2 + b 2 a a 2 + b + b 2 a 2 + b i 2 r = a 2 + b 2 θ cos θ = a a 2 + b 2, sin θ =
1 1.1 ( ). z = + bi,, b R 0, b 0 2 + b 2 0 z = + bi = ( ) 2 + b 2 2 + b + b 2 2 + b i 2 r = 2 + b 2 θ cos θ = 2 + b 2, sin θ = b 2 + b 2 2π z = r(cos θ + i sin θ) 1.2 (, ). 1. < 2. > 3. ±,, 1.3 ( ). A
ε ε x x + ε ε cos(ε) = 1, sin(ε) = ε [6] [5] nonstandard analysis 1974 [4] We shoud add that, to logical positivist, a discussion o
dif engine 2017/12/08 Math Advent Calendar 2017(https://adventar.org/calendars/2380) 12/8 IST(Internal Set Theory; ) 1 1.1 (nonstandard analysis, NSA) ε ε (a) ε 0. (b) r > 0 ε < r. (a)(b) ε sin(x) d sin(x)
IA [email protected] Last updated: January,......................................................................................................................................................................................
21 2 26 i 1 1 1.1............................ 1 1.2............................ 3 2 9 2.1................... 9 2.2.......... 9 2.3................... 11 2.4....................... 12 3 15 3.1..........
1 (1) ( i ) 60 (ii) 75 (iii) 315 (2) π ( i ) (ii) π (iii) 7 12 π ( (3) r, AOB = θ 0 < θ < π ) OAB A 2 OB P ( AB ) < ( AP ) (4) 0 < θ < π 2 sin θ
1 (1) ( i ) 60 (ii) 75 (iii) 15 () ( i ) (ii) 4 (iii) 7 1 ( () r, AOB = θ 0 < θ < ) OAB A OB P ( AB ) < ( AP ) (4) 0 < θ < sin θ < θ < tan θ 0 x, 0 y (1) sin x = sin y (x, y) () cos x cos y (x, y) 1 c
数学の基礎訓練I
I 9 6 13 1 1 1.1............... 1 1................ 1 1.3.................... 1.4............... 1.4.1.............. 1.4................. 3 1.4.3........... 3 1.4.4.. 3 1.5.......... 3 1.5.1..............
2 1 Introduction (1.1.2) Logistic ث Malthus (1.1.3) (( ) ث)( ) α = ( ) ( + ) [Verhulst 1845] 0 ( ) ( + ) lim ( ) = 0 t (1.1.4) (( ) ث)( ) α = ( ) Logi
1 1 Introduction 1.1 ( ) ( ) Malthus ( ) (1.1.1) ( ) α = ( ) ( + ) 0 ( ) ( + ) lim ( ) = 0 t ( ) α = ( ) αt م = ( ) ( ) = ( 0 ) 0 (1.1.2) αt م 0 = ( ) (1.1.1) ( ) ( α + (1 = ( + ) = 0 1 ( ( ) 2... ) geometric
18 I ( ) (1) I-1,I-2,I-3 (2) (3) I-1 ( ) (100 ) θ ϕ θ ϕ m m l l θ ϕ θ ϕ 2 g (1) (2) 0 (3) θ ϕ (4) (3) θ(t) = A 1 cos(ω 1 t + α 1 ) + A 2 cos(ω 2 t + α
18 I ( ) (1) I-1,I-2,I-3 (2) (3) I-1 ( ) (100 ) θ ϕ θ ϕ m m l l θ ϕ θ ϕ 2 g (1) (2) 0 (3) θ ϕ (4) (3) θ(t) = A 1 cos(ω 1 t + α 1 ) + A 2 cos(ω 2 t + α 2 ), ϕ(t) = B 1 cos(ω 1 t + α 1 ) + B 2 cos(ω 2 t
Nosé Hoover 1.2 ( 1) (a) (b) 1:
1 [email protected] 1 1.1 Nosé Hoover 1. ( 1) (a) (b) 1: T ( f(p x, p y, p z ) exp p x + p y + p ) z (1) mk B T p x p y p = = z = 1 m m m k BT () k B T = 1.3 0.04 0.03 0.0 0.01 0-5 -4-3 - -1 0
<4D F736F F D B B83578B6594BB2D834A836F815B82D082C88C60202E646F63>
MATLAB/Simulink による現代制御入門 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/9241 このサンプルページの内容は, 初版 1 刷発行当時のものです. i MATLAB/Simulink MATLAB/Simulink 1. 1 2. 3. MATLAB/Simulink
Excel ではじめる数値解析 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 初版 1 刷発行時のものです.
Excel ではじめる数値解析 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/009631 このサンプルページの内容は, 初版 1 刷発行時のものです. Excel URL http://www.morikita.co.jp/books/mid/009631 i Microsoft Windows
() n C + n C + n C + + n C n n (3) n C + n C + n C 4 + n C + n C 3 + n C 5 + (5) (6 ) n C + nc + 3 nc n nc n (7 ) n C + nc + 3 nc n nc n (
3 n nc k+ k + 3 () n C r n C n r nc r C r + C r ( r n ) () n C + n C + n C + + n C n n (3) n C + n C + n C 4 + n C + n C 3 + n C 5 + (4) n C n n C + n C + n C + + n C n (5) k k n C k n C k (6) n C + nc
1 = = = (set) (element) a A a A a A a A a A {2, 5, (0, 1)}, [ 1, 1] = {x; 1 x 1}. (proposition) A = {x; P (x)} P (x) x x a A a A Remark. (i) {2, 0, 0,
2005 4 1 1 2 2 6 3 8 4 11 5 14 6 18 7 20 8 22 9 24 10 26 11 27 http://matcmadison.edu/alehnen/weblogic/logset.htm 1 1 = = = (set) (element) a A a A a A a A a A {2, 5, (0, 1)}, [ 1, 1] = {x; 1 x 1}. (proposition)
