Finite size Emptiness Formation Probability for the XXZ spin chain at = 1/2
|
|
- Ἑκάβη Αλαφούζος
- 7 χρόνια πριν
- Προβολές:
Transcript
1 Finite size Emptiness Formation Probability for the XXZ spin chain at = 1/2 Luigi Cantini luigi.cantini@u-cergy.fr LPTM, Université de Cergy-Pontoise (France) CFT AND INTEGRABLE MODELS Bologna, September 12-15, 2011 Based on arxiv:1109.???? Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
2 XXZ spin chain at = 1 2 Hamiltonian of the XXZ spin chain H N ( ) = 1 2 N i=1 σxσ i x i+1 + σyσ i y i+1 + σzσ i z i+1 = q + q 1 2 [Razumov, Stroganov 00] = 1 2 g.s. energy E = 3N 4 N odd (N = 2n + 1) Periodic boundary conditions: σ α N+1 = σα 1. Two-fold degenerate ground state Ψ ± 2n+1, rational-valued components. N even (N = 2n) Twisted periodic boundary conditions: σ z N+1 = σz 1, while σ ± N+1 = e±i 2π 3 σ ± N+1, where σ± = σ x + ±iσ y. A single ground state Ψ e 2n, complex valued components. Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
3 Emptiness Formation Probability (EFP) The definition of the EFP ( (Ψ µ E µ N (k) = N ), ) k i=1 p+ i Ψ µ N (Ψ µ N, Ψµ N ), p + i = σz i µ = ±, e Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
4 Emptiness Formation Probability (EFP) The definition of the EFP ( (Ψ µ E µ N (k) = N ), ) k i=1 p+ i Ψ µ N (Ψ µ N, Ψµ N ), p + i = σz i µ = ±, e we define also a Pseudo EFP ( E ẽ2n(k) Ψ e 2n, ) k i=1 p+ i Ψ e 2n = (Ψ e 2n, Ψe 2n ). Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
5 Emptiness Formation Probability (EFP) The definition of the EFP ( (Ψ µ E µ N (k) = N ), ) k i=1 p+ i Ψ µ N (Ψ µ N, Ψµ N ), p + i = σz i µ = ±, e we define also a Pseudo EFP ( E ẽ2n(k) Ψ e 2n, ) k i=1 p+ i Ψ e 2n = (Ψ e 2n, Ψe 2n ). They have an analytical, factorized form! Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
6 Conjectures [Razumov, Stroganov 00] E 2n+1 (k 1) E 2n+1 (k) = E + 2n+1 (k 1) E + 2n+1 (k) = (2k 2)!(2k 1)!(2n + k)!(n k)! (k 1)!(3k 2)!(2n k + 1)!(n + k 1)! (2k 2)!(2k 1)!(2n + k)!(n k + 1)! (k 1)!(3k 2)!(2n k + 1)!(n + k)! E e 2n(k 1) E e 2n (k) = (2k 2)!(2k 1)!(2n + k 1)!(n k)! (k 1)!(3k 2)!(2n k)!(n + k 1)! E ẽ2n(k 1) = E ẽ2n (k) (2k 2)!(2k 1)!(2n + k 1)!(n k)! q (k 1)!(3k 3)!(3k 1)(2n k)!(n + k 1)! Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
7 Some partial results Asymptotics N [Maillet et al. 02] ( ) 3k 2 3 k lim E Γ(j 1/3)Γ(j + 1/3) N(k) = N 2 Γ(j 1/2)Γ(j + 1/2). j=1 Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
8 Some partial results Asymptotics N [Maillet et al. 02] ( ) 3k 2 3 k lim E Γ(j 1/3)Γ(j + 1/3) N(k) = N 2 Γ(j 1/2)Γ(j + 1/2). j=1 Norm [Di Francesco et al. 06] E ± 2n+1 (n) = A HT (2n + 1) 1 = n j=1 (2j 1)! 2 (2j)! 2 (j 1)!j!(3j 1)!(3j)! E ẽ2n(n) = ( q) n A 2 n = ( q) n CSSC(2n) 1 where: A n = # of n n Alternating Sign Matrices A HT (2n + 1) = # of (2n + 1) (2n + 1) Half-Turn Symmetric Alternating Sign Matrices Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
9 CSSC(2n, k 1) E ẽ2n(k 1) CSSC(2n, k 1) E ẽ2n (k) = q CSSC(2n, k) CSSC(2n, k 1) = # of lozange tilings of a regular hexagon of side length 2n, which are invariant under a rotation of π/3 and have a star shaped frozen region of length k, (CSSC(2n) := CSSC(2n, 0) = CSSC(2n, 1)) 2n 3k Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
10 Integrability R-matrix with Twist matrix R i,j (z) = a(z) = a(z) b(z) c 1 (z) 0 0 c 2 (z) b(z) a(z) qz q 1 q q 1 z, b(x) = z 1 q q 1 z, c 1 (z) = (q q 1 )z q q 1 z, c 2(z) = (q q 1 ) q q 1 z. Ω(φ) = ( e iφ 0 0 e iφ ) Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
11 R-Ω commutation [R i,j (x), Ω i (φ) Ω j (φ)] = 0 Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
12 R-Ω commutation Yang-Baxter equation [R i,j (x), Ω i (φ) Ω j (φ)] = 0 R i,j (z i /z j )R i,k (z i /z k )R j,k (z j /z k ) = R j,k (z j /z k )R i,k (z i /z k )R i,j (z i /z j ) Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
13 R-Ω commutation [R i,j (x), Ω i (φ) Ω j (φ)] = 0 Yang-Baxter equation R i,j (z i /z j )R i,k (z i /z k )R j,k (z j /z k ) = R j,k (z j /z k )R i,k (z i /z k )R i,j (z i /z j ) Transfer matrix T N (y z {1,...,N}, φ) = tr 0 [R 0,1 (y/z 1 )R 0,2 (y/z 2 )... R 0,N (y/z N )Ω 0 (φ)] Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
14 R-Ω commutation [R i,j (x), Ω i (φ) Ω j (φ)] = 0 Yang-Baxter equation R i,j (z i /z j )R i,k (z i /z k )R j,k (z j /z k ) = R j,k (z j /z k )R i,k (z i /z k )R i,j (z i /z j ) Transfer matrix T N (y z {1,...,N}, φ) = tr 0 [R 0,1 (y/z 1 )R 0,2 (y/z 2 )... R 0,N (y/z N )Ω 0 (φ)] Crucial idea! Consider the ground state with spectral parameters Ψ µ N Ψµ N (z), T N(y z {1,...,N}, φ)ψ µ N (z) = 1Ψµ N (z) Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
15 quantum Knizhnik Zamolodchikov (qkz) equations [Razumov, Stroganov & Zinn-Justin 07] The ground state satisfies a specialization q = e 2πi/3 of the U q (sl 2 ) qkz equations Ř i,i+1 (z i+1 /z i )Ψ µ N (..., z i, z i+1,... ) = Ψ µ N (..., z i+1, z i,... ) With σψ µ N (z 1, z 2,..., z N 1, z N ) = DΨ µ N (z 2,..., z N 1, z N, sz 1 ). σ(v 1 v 2 v N 1 v N ) = v 2 v N 1 v N v 1 Ř i,i+1 (z) = P i,i+1 R i,i+1 (z) P i,j (e µ i e ν j ) = e ν i e µ j, s = q 6, D = q 3N q 3(sz N +1)/2. Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
16 Inhomogenous EFP Using the solution of the U q (sl 2 ) qkz equations at level 1. we define an inhomogenous version of the EFP E µ N (k; y {1,...,2k}; z {1,...,N k} ) (P N,k (z)(ψ µ N (q 6 y {k+1,...,2k} ;z)), k i=1 p+ i Ψ µ N (y {1,...,k};z)) 1 i<j k (qy i q 1 y j )(qy i+k q 1 y j+k ) with P N,k (z) = N i=k+1 (z ip + i + p i ). and of the Pseudo EFP E ẽn (k; y {1,...,2k}; z {1,...,N k} ) ( Ψ µ N (k;q 6 y 1 {k+1,...,2k} ;z 1 ), k ) i=1 p+ i Ψ µ N (k;y {1,...,k};z) 1 i<j k (qy i q 1 y j )(qy i+k q 1 y j+k ) Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
17 Inhomogenous EFP Using the solution of the U q (sl 2 ) qkz equations at level 1. we define an inhomogenous version of the EFP E µ N (k; y {1,...,2k}; z {1,...,N k} ) (P N,k (z)(ψ µ N (q 6 y {k+1,...,2k} ;z)), k i=1 p+ i Ψ µ N (y {1,...,k};z)) 1 i<j k (qy i q 1 y j )(qy i+k q 1 y j+k ) with P N,k (z) = N i=k+1 (z ip + i + p i ). and of the Pseudo EFP E ẽn (k; y {1,...,2k}; z {1,...,N k} ) ( Ψ µ N (k;q 6 y 1 {k+1,...,2k} ;z 1 ), k ) i=1 p+ i Ψ µ N (k;y {1,...,k};z) 1 i<j k (qy i q 1 y j )(qy i+k q 1 y j+k ) We shall compute these and then take the specialization z i = y j = 1. Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
18 Properties of E µ N (k; y; z) and of E ẽ2n (k; y; z) 1 Symmetries under z i z j, y i y j. Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
19 Properties of E µ N (k; y; z) and of E ẽ2n (k; y; z) 1 Symmetries under z i z j, y i y j. 2 Specialization z i = 0 or z i lim z 2n 2n+1 E 2n+1 (k; y; z) E z 2n+1 2n(k; e y; z \ z 2n+1 ) E e 2n+2(k; y; z) z2n+2 =0 E + 2n+1 (k; y; z \ z 2n+2) Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
20 Properties of E µ N (k; y; z) and of E ẽ2n (k; y; z) 1 Symmetries under z i z j, y i y j. 2 Specialization z i = 0 or z i lim z 2n 2n+1 E 2n+1 (k; y; z) E z 2n+1 2n(k; e y; z \ z 2n+1 ) E e 2n+2(k; y; z) z2n+2 =0 E + 2n+1 (k; y; z \ z 2n+2) 3 Recursion relation for z j = q ±2 z i z i 2k l=1 qy l q 1 z i q q 1 E µ N (k; y; z) z j =q 2 z i E µ N 2 (k; y; z \ {z i, z j }) 1 l N k l i,j (qz l q 1 z i )(q 3 z i q 1 z l ) (q q 1 ) 2 Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
21 Properties of E µ N (k; y; z) and of E ẽ2n (k; y; z) 1 Symmetries under z i z j, y i y j. 2 Specialization z i = 0 or z i lim z 2n 2n+1 E 2n+1 (k; y; z) E z 2n+1 2n(k; e y; z \ z 2n+1 ) E e 2n+2(k; y; z) z2n+2 =0 E + 2n+1 (k; y; z \ z 2n+2) 3 Recursion relation for z j = q ±2 z i 2k l=1 qy l q 1 z i q q 1 E ẽ2n(k; y; z) zj =q 2 z i E ẽ2n 2 (k; y; z \ {z i, z j }) 1 l 2n k l i,j (qz l q 1 z i )(q 3 z i q 1 z l ) (q q 1 ) 2 Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
22 Properties of E µ N (k; y; z) and of E ẽn (k; y; z) 4 Factorized cases E e/ẽ (qz i q 1 z j )(qz j q 1 z i ) 2k (k; y; z) = (q q 1 ) 2 1 i<j k E + 2k+1 (k + 1; y; z) = E 2k+1 (k; y; z) = 1 i<j k 1 i<j k+1 (qz i q 1 z j )(qz j q 1 z i ) (q q 1 ) 2 k i=1 (qz i q 1 z j )(qz j q 1 z i ) (q q 1 ) 2. z 2 i Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
23 Properties of E µ N (k; y; z) and of E ẽn (k; y; z) 4 Factorized cases E e/ẽ (qz i q 1 z j )(qz j q 1 z i ) 2k (k; y; z) = (q q 1 ) 2 1 i<j k E + 2k+1 (k + 1; y; z) = E 2k+1 (k; y; z) = 1 i<j k 1 i<j k+1 (qz i q 1 z j )(qz j q 1 z i ) (q q 1 ) 2 k i=1 (qz i q 1 z j )(qz j q 1 z i ) (q q 1 ) 2. z 2 i These properties completely determine E µ N (k; y; z) and E ẽ2n(k; y; z)! Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
24 Combinatorial point q = e 2πi/3 Let ρ, σ be strictly increasing infinite sequences of nonnegative integers. Introduce the following matrices z ρ 1 1 z ρ z ρr+s z ρ 1 2 z ρ z ρr+s z ρ 1 r z ρ 2 r... zr ρr+s z σ 1 1 z σ z σr+s 1 M ( ρ, σ) (r, s; y; z) = z σ 1 2 z σ z σr+s z σ 1 r z σ 2 r... zr σr+s y ρ 1 1 y ρ y ρr+s 1 y σ 1 1 y σ y σr+s y ρ 1 2s y ρ 2 2s... y ρr+s 2s y σ 1 2s y σ 2 2s... y σr+s 2s Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
25 Combinatorial point q = e 2πi/3 Define the following polynomials S ( ρ, σ) (r, s; y; z) = det M ( ρ, σ) (r,s;y;z) 1 i<j r (z i z j ) 2 1 i<j 2s (y i y j ). 1 i r (z i y j ) 1 j 2s Using the Laplace expansion along the first r + s columns we can write S ( ρ, σ) (r, s; y; z) as a bilinear in Schur polynomials I {1,...2s} I =s S ( ρ, σ) (r, s; y; z) = ( 1) ɛ(i ) i<j I (y i y j ) i<j I c (y i y j ) 1 i<j 2s (y i y j ) S ρ(r+s) (z, y I )S σ(r+s) (z, y I c), Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
26 Combinatorial point q = e 2πi/3 Now let us introduce the following family of integer sequences λ i (r) = 3i 3 + r, 2 λ(0) = {0, 1, 3, 4, 6, 7,... } λ(1) = {0, 2, 3, 5, 6, 8,... } λ(2) = {1, 2, 4, 5, 7, 8,... } We claim that E 2n+1 (k; y; z) S( λ(0), λ(1)) (2n + 1 k, k; y; z) E + 2n+1 (k; y; z) S( λ(1), λ(2)) (2n + 1 k, k; y; z) E2n(k; e y; z) S ( λ(0), λ(1)) (2n k, k; y; z) E ẽ2n(k; y; z) S ( λ(0), λ(2)) (2n k, k; y; z) Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
27 t specialization Setting and z = {z 1 = t 0, z 2 = t 1,..., z N k = t N k 1 } y = {y 1 = t N k,..., y 2k = t N+k 1 } the functions E µ N (k; y; z) and E ẽ2n(k; y; z), as rational functions of t, have simple factors. Using the usual t-numbers and t-factorial [i] t = ti 1 t 1 and [n] t! = n [i] t. i=1 Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
28 t specialization: result E2n(k e 1; t) E2n e (k; t) [2n + k 1] t![n k] t3![2k 1] t3![2k 2] t3! [2n k] t![n + k 1] t 3![k 1] t 3![3k 2] t! E ẽ2n(k 1; t) ( q)e ẽ2n (k; t) [2n + k 1] t![n k] t3![2k 1] t3![2k 2] t3! [2n k] t![n + k 1] t 3![k 1] t 3![3k 3] t![3k 1] t E 2n+1 (k 1; t) E 2n+1 (k; t) [2n + k] t![n k] t 3![2k 1] t 3![2k 2] t 3! [2n k + 1] t![n + k 1] t 3![k 1] t 3![3k 2] t! E + 2n+1 (k 1; t) E + 2n+1 (k; t) [2n + k] t![n k + 1] t3![2k 1] t3![2k 2] t3! [2n k + 1] t![n + k] t 3![k 1] t 3![3k 2] t! ( ) k 1 The coefficients in front are of the form t β [3]t 3 1. t 1 Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
29 What if q is generic? We have found a multiresidua formula n k {qz i } l=1 E µ 2n ɛ(µ) (k; y; z) dw l w α(µ) 2k j=1 (w l y j ) 2πi 2n k ɛ(µ) i=1 (w l qz i )(w l q 1 z i ) K n k(w) where ɛ(±) = ±1, ɛ(e) = ɛ(ẽ) = 0, α(+) = α(e) = 0, α(ẽ) = 1, α( ) = 2 and K N (w) = (w i w j ) 2 (qw i q 1 w j )(qw j q 1 w i ). 1 i<j N Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
30 Perspectives Consider other correlation functions. Other boundary conditions (e.g. open chain with diagonal K matrices) Higher spins or also U q (sl N ) spin chain. Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
31 Thank you! Cantini (LPTM Cergy-Pontoise) EFP at = 1/2 Bologna, / 21
Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)
Phys460.nb 81 ψ n (t) is still the (same) eigenstate of H But for tdependent H. The answer is NO. 5.5.5. Solution for the tdependent Schrodinger s equation If we assume that at time t 0, the electron starts
g-selberg integrals MV Conjecture An A 2 Selberg integral Summary Long Live the King Ole Warnaar Department of Mathematics Long Live the King
Ole Warnaar Department of Mathematics g-selberg integrals The Selberg integral corresponds to the following k-dimensional generalisation of the beta integral: D Here and k t α 1 i (1 t i ) β 1 1 i
Matrices and Determinants
Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z
SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions
SCHOOL OF MATHEMATICAL SCIENCES GLMA Linear Mathematics 00- Examination Solutions. (a) i. ( + 5i)( i) = (6 + 5) + (5 )i = + i. Real part is, imaginary part is. (b) ii. + 5i i ( + 5i)( + i) = ( i)( + i)
Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013
Notes on Average Scattering imes and Hall Factors Jesse Maassen and Mar Lundstrom Purdue University November 5, 13 I. Introduction 1 II. Solution of the BE 1 III. Exercises: Woring out average scattering
Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3
Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3 1 State vector space and the dual space Space of wavefunctions The space of wavefunctions is the set of all
Partial Differential Equations in Biology The boundary element method. March 26, 2013
The boundary element method March 26, 203 Introduction and notation The problem: u = f in D R d u = ϕ in Γ D u n = g on Γ N, where D = Γ D Γ N, Γ D Γ N = (possibly, Γ D = [Neumann problem] or Γ N = [Dirichlet
D Alembert s Solution to the Wave Equation
D Alembert s Solution to the Wave Equation MATH 467 Partial Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Objectives In this lesson we will learn: a change of variable technique
6.1. Dirac Equation. Hamiltonian. Dirac Eq.
6.1. Dirac Equation Ref: M.Kaku, Quantum Field Theory, Oxford Univ Press (1993) η μν = η μν = diag(1, -1, -1, -1) p 0 = p 0 p = p i = -p i p μ p μ = p 0 p 0 + p i p i = E c 2 - p 2 = (m c) 2 H = c p 2
Chapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
New bounds for spherical two-distance sets and equiangular lines
New bounds for spherical two-distance sets and equiangular lines Michigan State University Oct 8-31, 016 Anhui University Definition If X = {x 1, x,, x N } S n 1 (unit sphere in R n ) and x i, x j = a
4.6 Autoregressive Moving Average Model ARMA(1,1)
84 CHAPTER 4. STATIONARY TS MODELS 4.6 Autoregressive Moving Average Model ARMA(,) This section is an introduction to a wide class of models ARMA(p,q) which we will consider in more detail later in this
Concrete Mathematics Exercises from 30 September 2016
Concrete Mathematics Exercises from 30 September 2016 Silvio Capobianco Exercise 1.7 Let H(n) = J(n + 1) J(n). Equation (1.8) tells us that H(2n) = 2, and H(2n+1) = J(2n+2) J(2n+1) = (2J(n+1) 1) (2J(n)+1)
Homework 8 Model Solution Section
MATH 004 Homework Solution Homework 8 Model Solution Section 14.5 14.6. 14.5. Use the Chain Rule to find dz where z cosx + 4y), x 5t 4, y 1 t. dz dx + dy y sinx + 4y)0t + 4) sinx + 4y) 1t ) 0t + 4t ) sinx
Other Test Constructions: Likelihood Ratio & Bayes Tests
Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :
Tridiagonal matrices. Gérard MEURANT. October, 2008
Tridiagonal matrices Gérard MEURANT October, 2008 1 Similarity 2 Cholesy factorizations 3 Eigenvalues 4 Inverse Similarity Let α 1 ω 1 β 1 α 2 ω 2 T =......... β 2 α 1 ω 1 β 1 α and β i ω i, i = 1,...,
Example Sheet 3 Solutions
Example Sheet 3 Solutions. i Regular Sturm-Liouville. ii Singular Sturm-Liouville mixed boundary conditions. iii Not Sturm-Liouville ODE is not in Sturm-Liouville form. iv Regular Sturm-Liouville note
2 Composition. Invertible Mappings
Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Composition. Invertible Mappings In this section we discuss two procedures for creating new mappings from old ones, namely,
Homework 3 Solutions
Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For
derivation of the Laplacian from rectangular to spherical coordinates
derivation of the Laplacian from rectangular to spherical coordinates swapnizzle 03-03- :5:43 We begin by recognizing the familiar conversion from rectangular to spherical coordinates (note that φ is used
Trigonometric Formula Sheet
Trigonometric Formula Sheet Definition of the Trig Functions Right Triangle Definition Assume that: 0 < θ < or 0 < θ < 90 Unit Circle Definition Assume θ can be any angle. y x, y hypotenuse opposite θ
Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.
Exercises 0 More exercises are available in Elementary Differential Equations. If you have a problem to solve any of them, feel free to come to office hour. Problem Find a fundamental matrix of the given
3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β
3.4 SUM AND DIFFERENCE FORMULAS Page Theorem cos(αβ cos α cos β -sin α cos(α-β cos α cos β sin α NOTE: cos(αβ cos α cos β cos(α-β cos α -cos β Proof of cos(α-β cos α cos β sin α Let s use a unit circle
Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics
Fourier Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Introduction Not all functions can be represented by Taylor series. f (k) (c) A Taylor series f (x) = (x c)
ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Αν κάπου κάνετε κάποιες υποθέσεις να αναφερθούν στη σχετική ερώτηση. Όλα τα αρχεία που αναφέρονται στα προβλήματα βρίσκονται στον ίδιο φάκελο με το εκτελέσιμο
Empirical best prediction under area-level Poisson mixed models
Noname manuscript No. (will be inserted by the editor Empirical best prediction under area-level Poisson mixed models Miguel Boubeta María José Lombardía Domingo Morales eceived: date / Accepted: date
ST5224: Advanced Statistical Theory II
ST5224: Advanced Statistical Theory II 2014/2015: Semester II Tutorial 7 1. Let X be a sample from a population P and consider testing hypotheses H 0 : P = P 0 versus H 1 : P = P 1, where P j is a known
Srednicki Chapter 55
Srednicki Chapter 55 QFT Problems & Solutions A. George August 3, 03 Srednicki 55.. Use equations 55.3-55.0 and A i, A j ] = Π i, Π j ] = 0 (at equal times) to verify equations 55.-55.3. This is our third
Overview. Transition Semantics. Configurations and the transition relation. Executions and computation
Overview Transition Semantics Configurations and the transition relation Executions and computation Inference rules for small-step structural operational semantics for the simple imperative language Transition
A Bonus-Malus System as a Markov Set-Chain. Małgorzata Niemiec Warsaw School of Economics Institute of Econometrics
A Bonus-Malus System as a Markov Set-Chain Małgorzata Niemiec Warsaw School of Economics Institute of Econometrics Contents 1. Markov set-chain 2. Model of bonus-malus system 3. Example 4. Conclusions
ECE Spring Prof. David R. Jackson ECE Dept. Notes 2
ECE 634 Spring 6 Prof. David R. Jackson ECE Dept. Notes Fields in a Source-Free Region Example: Radiation from an aperture y PEC E t x Aperture Assume the following choice of vector potentials: A F = =
General 2 2 PT -Symmetric Matrices and Jordan Blocks 1
General 2 2 PT -Symmetric Matrices and Jordan Blocks 1 Qing-hai Wang National University of Singapore Quantum Physics with Non-Hermitian Operators Max-Planck-Institut für Physik komplexer Systeme Dresden,
Laplace Expansion. Peter McCullagh. WHOA-PSI, St Louis August, Department of Statistics University of Chicago
Laplace Expansion Peter McCullagh Department of Statistics University of Chicago WHOA-PSI, St Louis August, 2017 Outline Laplace approximation in 1D Laplace expansion in 1D Laplace expansion in R p Formal
The ε-pseudospectrum of a Matrix
The ε-pseudospectrum of a Matrix Feb 16, 2015 () The ε-pseudospectrum of a Matrix Feb 16, 2015 1 / 18 1 Preliminaries 2 Definitions 3 Basic Properties 4 Computation of Pseudospectrum of 2 2 5 Problems
Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.
Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο The time integral of a force is referred to as impulse, is determined by and is obtained from: Newton s 2 nd Law of motion states that the action
Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee
Appendi to On the stability of a compressible aisymmetric rotating flow in a pipe By Z. Rusak & J. H. Lee Journal of Fluid Mechanics, vol. 5 4, pp. 5 4 This material has not been copy-edited or typeset
Space-Time Symmetries
Chapter Space-Time Symmetries In classical fiel theory any continuous symmetry of the action generates a conserve current by Noether's proceure. If the Lagrangian is not invariant but only shifts by a
Chapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- -----------------
Inverse trigonometric functions & General Solution of Trigonometric Equations. 1. Sin ( ) = a) b) c) d) Ans b. Solution : Method 1. Ans a: 17 > 1 a) is rejected. w.k.t Sin ( sin ) = d is rejected. If sin
CRASH COURSE IN PRECALCULUS
CRASH COURSE IN PRECALCULUS Shiah-Sen Wang The graphs are prepared by Chien-Lun Lai Based on : Precalculus: Mathematics for Calculus by J. Stuwart, L. Redin & S. Watson, 6th edition, 01, Brooks/Cole Chapter
Second Order Partial Differential Equations
Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y
Section 8.3 Trigonometric Equations
99 Section 8. Trigonometric Equations Objective 1: Solve Equations Involving One Trigonometric Function. In this section and the next, we will exple how to solving equations involving trigonometric functions.
( y) Partial Differential Equations
Partial Dierential Equations Linear P.D.Es. contains no owers roducts o the deendent variables / an o its derivatives can occasionall be solved. Consider eamle ( ) a (sometimes written as a ) we can integrate
On the Galois Group of Linear Difference-Differential Equations
On the Galois Group of Linear Difference-Differential Equations Ruyong Feng KLMM, Chinese Academy of Sciences, China Ruyong Feng (KLMM, CAS) Galois Group 1 / 19 Contents 1 Basic Notations and Concepts
The Simply Typed Lambda Calculus
Type Inference Instead of writing type annotations, can we use an algorithm to infer what the type annotations should be? That depends on the type system. For simple type systems the answer is yes, and
Parametrized Surfaces
Parametrized Surfaces Recall from our unit on vector-valued functions at the beginning of the semester that an R 3 -valued function c(t) in one parameter is a mapping of the form c : I R 3 where I is some
CE 530 Molecular Simulation
C 53 olecular Siulation Lecture Histogra Reweighting ethods David. Kofke Departent of Cheical ngineering SUNY uffalo kofke@eng.buffalo.edu Histogra Reweighting ethod to cobine results taken at different
Every set of first-order formulas is equivalent to an independent set
Every set of first-order formulas is equivalent to an independent set May 6, 2008 Abstract A set of first-order formulas, whatever the cardinality of the set of symbols, is equivalent to an independent
Approximation of distance between locations on earth given by latitude and longitude
Approximation of distance between locations on earth given by latitude and longitude Jan Behrens 2012-12-31 In this paper we shall provide a method to approximate distances between two points on earth
SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018
Journal of rogressive Research in Mathematics(JRM) ISSN: 2395-028 SCITECH Volume 3, Issue 2 RESEARCH ORGANISATION ublished online: March 29, 208 Journal of rogressive Research in Mathematics www.scitecresearch.com/journals
Finite Field Problems: Solutions
Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The
Areas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
w o = R 1 p. (1) R = p =. = 1
Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 205 ιδάσκων : Α. Μουχτάρης Τριτη Σειρά Ασκήσεων Λύσεις Ασκηση 3. 5.2 (a) From the Wiener-Hopf equation we have:
forms This gives Remark 1. How to remember the above formulas: Substituting these into the equation we obtain with
Week 03: C lassification of S econd- Order L inear Equations In last week s lectures we have illustrated how to obtain the general solutions of first order PDEs using the method of characteristics. We
Areas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
Congruence Classes of Invertible Matrices of Order 3 over F 2
International Journal of Algebra, Vol. 8, 24, no. 5, 239-246 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/.2988/ija.24.422 Congruence Classes of Invertible Matrices of Order 3 over F 2 Ligong An and
b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds!
MTH U341 urface Integrals, tokes theorem, the divergence theorem To be turned in Wed., Dec. 1. 1. Let be the sphere of radius a, x 2 + y 2 + z 2 a 2. a. Use spherical coordinates (with ρ a) to parametrize.
Solutions to Exercise Sheet 5
Solutions to Eercise Sheet 5 jacques@ucsd.edu. Let X and Y be random variables with joint pdf f(, y) = 3y( + y) where and y. Determine each of the following probabilities. Solutions. a. P (X ). b. P (X
Optimal Parameter in Hermitian and Skew-Hermitian Splitting Method for Certain Two-by-Two Block Matrices
Optimal Parameter in Hermitian and Skew-Hermitian Splitting Method for Certain Two-by-Two Block Matrices Chi-Kwong Li Department of Mathematics The College of William and Mary Williamsburg, Virginia 23187-8795
Practice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1
Conceptual Questions. State a Basic identity and then verify it. a) Identity: Solution: One identity is cscθ) = sinθ) Practice Exam b) Verification: Solution: Given the point of intersection x, y) of the
Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit
Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ting Zhang Stanford May 11, 2001 Stanford, 5/11/2001 1 Outline Ordinal Classification Ordinal Addition Ordinal Multiplication Ordinal
Orbital angular momentum and the spherical harmonics
Orbital angular momentum and the spherical harmonics March 8, 03 Orbital angular momentum We compare our result on representations of rotations with our previous experience of angular momentum, defined
ES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems
ES440/ES911: CFD Chapter 5. Solution of Linear Equation Systems Dr Yongmann M. Chung http://www.eng.warwick.ac.uk/staff/ymc/es440.html Y.M.Chung@warwick.ac.uk School of Engineering & Centre for Scientific
Finite difference method for 2-D heat equation
Finite difference method for 2-D heat equation Praveen. C praveen@math.tifrbng.res.in Tata Institute of Fundamental Research Center for Applicable Mathematics Bangalore 560065 http://math.tifrbng.res.in/~praveen
Uniform Convergence of Fourier Series Michael Taylor
Uniform Convergence of Fourier Series Michael Taylor Given f L 1 T 1 ), we consider the partial sums of the Fourier series of f: N 1) S N fθ) = ˆfk)e ikθ. k= N A calculation gives the Dirichlet formula
Lecture 10 - Representation Theory III: Theory of Weights
Lecture 10 - Representation Theory III: Theory of Weights February 18, 2012 1 Terminology One assumes a base = {α i } i has been chosen. Then a weight Λ with non-negative integral Dynkin coefficients Λ
Lecture 13 - Root Space Decomposition II
Lecture 13 - Root Space Decomposition II October 18, 2012 1 Review First let us recall the situation. Let g be a simple algebra, with maximal toral subalgebra h (which we are calling a CSA, or Cartan Subalgebra).
( ) 2 and compare to M.
Problems and Solutions for Section 4.2 4.9 through 4.33) 4.9 Calculate the square root of the matrix 3!0 M!0 8 Hint: Let M / 2 a!b ; calculate M / 2!b c ) 2 and compare to M. Solution: Given: 3!0 M!0 8
Two generalisations of the binomial theorem
39 Two generalisations of the binomial theorem Sacha C. Blumen Abstract We prove two generalisations of the binomial theorem that are also generalisations of the q-binomial theorem. These generalisations
DiracDelta. Notations. Primary definition. Specific values. General characteristics. Traditional name. Traditional notation
DiracDelta Notations Traditional name Dirac delta function Traditional notation x Mathematica StandardForm notation DiracDeltax Primary definition 4.03.02.000.0 x Π lim ε ; x ε0 x 2 2 ε Specific values
SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM
SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr T t N n) Pr max X 1,..., X N ) t N n) Pr max
DERIVATION OF MILES EQUATION FOR AN APPLIED FORCE Revision C
DERIVATION OF MILES EQUATION FOR AN APPLIED FORCE Revision C By Tom Irvine Email: tomirvine@aol.com August 6, 8 Introduction The obective is to derive a Miles equation which gives the overall response
ω ω ω ω ω ω+2 ω ω+2 + ω ω ω ω+2 + ω ω+1 ω ω+2 2 ω ω ω ω ω ω ω ω+1 ω ω2 ω ω2 + ω ω ω2 + ω ω ω ω2 + ω ω+1 ω ω2 + ω ω+1 + ω ω ω ω2 + ω
0 1 2 3 4 5 6 ω ω + 1 ω + 2 ω + 3 ω + 4 ω2 ω2 + 1 ω2 + 2 ω2 + 3 ω3 ω3 + 1 ω3 + 2 ω4 ω4 + 1 ω5 ω 2 ω 2 + 1 ω 2 + 2 ω 2 + ω ω 2 + ω + 1 ω 2 + ω2 ω 2 2 ω 2 2 + 1 ω 2 2 + ω ω 2 3 ω 3 ω 3 + 1 ω 3 + ω ω 3 +
Second Order RLC Filters
ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor
Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1
Eon : Fall 8 Suggested Solutions to Problem Set 8 Email questions or omments to Dan Fetter Problem. Let X be a salar with density f(x, θ) (θx + θ) [ x ] with θ. (a) Find the most powerful level α test
Problem Set 3: Solutions
CMPSCI 69GG Applied Information Theory Fall 006 Problem Set 3: Solutions. [Cover and Thomas 7.] a Define the following notation, C I p xx; Y max X; Y C I p xx; Ỹ max I X; Ỹ We would like to show that C
SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM
SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr (T t N n) Pr (max (X 1,..., X N ) t N n) Pr (max
3+1 Splitting of the Generalized Harmonic Equations
3+1 Splitting of the Generalized Harmonic Equations David Brown North Carolina State University EGM June 2011 Numerical Relativity Interpret general relativity as an initial value problem: Split spacetime
Quadratic Expressions
Quadratic Expressions. The standard form of a quadratic equation is ax + bx + c = 0 where a, b, c R and a 0. The roots of ax + bx + c = 0 are b ± b a 4ac. 3. For the equation ax +bx+c = 0, sum of the roots
k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +
Chapter 3. Fuzzy Arithmetic 3- Fuzzy arithmetic: ~Addition(+) and subtraction (-): Let A = [a and B = [b, b in R If x [a and y [b, b than x+y [a +b +b Symbolically,we write A(+)B = [a (+)[b, b = [a +b
Bessel functions. ν + 1 ; 1 = 0 for k = 0, 1, 2,..., n 1. Γ( n + k + 1) = ( 1) n J n (z). Γ(n + k + 1) k!
Bessel functions The Bessel function J ν (z of the first kind of order ν is defined by J ν (z ( (z/ν ν Γ(ν + F ν + ; z 4 ( k k ( Γ(ν + k + k! For ν this is a solution of the Bessel differential equation
Math221: HW# 1 solutions
Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin
Arithmetical applications of lagrangian interpolation. Tanguy Rivoal. Institut Fourier CNRS and Université de Grenoble 1
Arithmetical applications of lagrangian interpolation Tanguy Rivoal Institut Fourier CNRS and Université de Grenoble Conference Diophantine and Analytic Problems in Number Theory, The 00th anniversary
HOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:
HOMEWORK 4 Problem a For the fast loading case, we want to derive the relationship between P zz and λ z. We know that the nominal stress is expressed as: P zz = ψ λ z where λ z = λ λ z. Therefore, applying
6. MAXIMUM LIKELIHOOD ESTIMATION
6 MAXIMUM LIKELIHOOD ESIMAION [1] Maximum Likelihood Estimator (1) Cases in which θ (unknown parameter) is scalar Notational Clarification: From now on, we denote the true value of θ as θ o hen, view θ
Reminders: linear functions
Reminders: linear functions Let U and V be vector spaces over the same field F. Definition A function f : U V is linear if for every u 1, u 2 U, f (u 1 + u 2 ) = f (u 1 ) + f (u 2 ), and for every u U
Numerical Analysis FMN011
Numerical Analysis FMN011 Carmen Arévalo Lund University carmen@maths.lth.se Lecture 12 Periodic data A function g has period P if g(x + P ) = g(x) Model: Trigonometric polynomial of order M T M (x) =
Section 9.2 Polar Equations and Graphs
180 Section 9. Polar Equations and Graphs In this section, we will be graphing polar equations on a polar grid. In the first few examples, we will write the polar equation in rectangular form to help identify
ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =?
Teko Classes IITJEE/AIEEE Maths by SUHAAG SIR, Bhopal, Ph (0755) 3 00 000 www.tekoclasses.com ANSWERSHEET (TOPIC DIFFERENTIAL CALCULUS) COLLECTION # Question Type A.Single Correct Type Q. (A) Sol least
Notations. Primary definition. Specific values. General characteristics. Traditional name. Traditional notation. Mathematica StandardForm notation
KelvinKei Notations Traditional name Kelvin function of the second kind Traditional notation kei Mathematica StandardForm notation KelvinKei Primary definition 03.5.0.000.0 kei kei 0 Specific values Values
6.3 Forecasting ARMA processes
122 CHAPTER 6. ARMA MODELS 6.3 Forecasting ARMA processes The purpose of forecasting is to predict future values of a TS based on the data collected to the present. In this section we will discuss a linear
The Pohozaev identity for the fractional Laplacian
The Pohozaev identity for the fractional Laplacian Xavier Ros-Oton Departament Matemàtica Aplicada I, Universitat Politècnica de Catalunya (joint work with Joaquim Serra) Xavier Ros-Oton (UPC) The Pohozaev
Appendix A. Curvilinear coordinates. A.1 Lamé coefficients. Consider set of equations. ξ i = ξ i (x 1,x 2,x 3 ), i = 1,2,3
Appendix A Curvilinear coordinates A. Lamé coefficients Consider set of equations ξ i = ξ i x,x 2,x 3, i =,2,3 where ξ,ξ 2,ξ 3 independent, single-valued and continuous x,x 2,x 3 : coordinates of point
Testing for Indeterminacy: An Application to U.S. Monetary Policy. Technical Appendix
Testing for Indeterminacy: An Application to U.S. Monetary Policy Technical Appendix Thomas A. Lubik Department of Economics Johns Hopkins University Frank Schorfheide Department of Economics University
Product Identities for Theta Functions
Product Identities for Theta Functions Zhu Cao April 7, 008 Defining Products of Theta Functions n 1 (a; q) 0 = 1, (a; q) n = (1 aq k ), n 1, k=0 (a; q) = lim (a; q) n, q < 1. n Jacobi s triple product
Local Approximation with Kernels
Local Approximation with Kernels Thomas Hangelbroek University of Hawaii at Manoa 5th International Conference Approximation Theory, 26 work supported by: NSF DMS-43726 A cubic spline example Consider
ExpIntegralE. Notations. Primary definition. Specific values. Traditional name. Traditional notation. Mathematica StandardForm notation
ExpIntegralE Notations Traditional name Exponential integral E Traditional notation E Mathematica StandardForm notation ExpIntegralE, Primary definition 06.34.0.000.0 E t t t ; Re 0 Specific values Specialied
The form factor program - a review and new results - the nested SU(N)-off-shell Bethe ansatz - 1/N expansion
The form factor program - a review and new results - the nested SU(N-off-shell Bethe ansatz - 1/N expansion H. Babujian, A. Foerster, and M. Karowski Yerevan-Tbilisi, October 2007 Babujian, Foerster, Karowski
Section 7.6 Double and Half Angle Formulas
09 Section 7. Double and Half Angle Fmulas To derive the double-angles fmulas, we will use the sum of two angles fmulas that we developed in the last section. We will let α θ and β θ: cos(θ) cos(θ + θ)
Lecture 26: Circular domains
Introductory lecture notes on Partial Differential Equations - c Anthony Peirce. Not to be copied, used, or revised without eplicit written permission from the copyright owner. 1 Lecture 6: Circular domains