• Tidak ada hasil yang ditemukan

Wainberg Dorin. 129KB Jun 04 2011 12:09:41 AM

N/A
N/A
Protected

Academic year: 2017

Membagikan "Wainberg Dorin. 129KB Jun 04 2011 12:09:41 AM"

Copied!
7
0
0

Teks penuh

(1)

ON SOME PROPERTIES OF THE SYMPLECTIC AND

HAMILTONIAN MATRICES

by

Dorin Wainberg

Abstract: In the first part of the paper the symplectic and Hamiltonian matrices are defined and some properties are pointed, and in the second part a relation between those two sets of matrices is proved.

1. Proprieties of symplectic and Hamiltonian matrices

For the beginning it will be introduced the square matrix J ∈ M2n×2n() defined by

J =

  

 

n n

n n

I I

0 0

(1)

where: 0n∈ Mn×n() – zero matrix In∈ Mn×n() – identity matrix Remark 1

It is not very complicated to prove that the next properties of the matrix J

are real (properties that will be very useful to prove some propositions that follow):

i) Jt = -J

ii) J-1 = Jt iii) JtJ = I2n iv) Jt Jt= - I2n v) J2 = - I2n vi) det J = ±1

Now the definition of the symplectic and Hamiltonian matrices are given:

Definition 1

A matrix A∈ M2n×2n() is called symplectic if:

(2)

where J∈ M2n×2n() is from (1). We will denote by SP(n, )

not

= { A ∈M2n×2n() | At J A = J } the set of 2n

× 2n real symplectic matrices. Definition 2

In the next part some properties of those sets of matrices will be proved, for example:

(3)

= Jt (J A)tJ J At J = J2 = - I2n = Jt A Jt (- I2n) At J =

= - Jt A Jt At J = A Jt At = (At J A)t = Jt = - Jt Jt J = Jt Jt = - I2n

= JA-1 ∈ SP(n, )

We will proof now that AB∈ SP(n, ):

(AB)tJ AB = Bt At J A B = At J A = J

= Bt J B =

= JAB∈ SP(n, )

Consequence. The set of symplectic matrices SP(n, ) is a subgroup of the set of nonsingular matrices GL(n, ) reported to multiplication. Indeed we have AB∈ SP(n, ), ∀ A, B∈ SP(n, ), and AB-1∈ SP(n, ), ∀ A, B∈ SP(n, ).

Proposition 2

Let A ∈ SP(n, ) and pA(x) - the characteristic polynomial of the matrix

A. If pA(c)= 0, then pA(1c)= pA(c)= pA(1c)= 0, where c∈ . Proof

) (x

pA = det(AxI2n) = A = - J A-1J

= det(- J A-1JxI2n) = I2n = - J2

= det( J( - A-1)J + x J2) = = det( J( - A-1 + xI2n)J ) =

= det J det( - A-1 + xI2n)det J = det J = ±1 = det( - A-1 + xI2n) =

= det( - A-1 + xAA-1) =

= det( - I2n + xA ) det( A-1 )= = ±det(xA - I2n ) = ±x2n det(A - x1

n

I2 ) = ±x2npA(1x) ⇒

x2npA(1x) = 0 ⇒ pA(1x) = 0 ⇒ pA(1c) = 0 ⇒ pA(c) = 0 ⇒ pA(1c) = 0. Proposition 3

The next relations are equivalent:

a) A is a Hamiltonian matrix; b) A = JS , where S = St ; c) ( JA )t = JA.

(4)
(5)

i) [ αA + βB, C] = α[A, C] + β[B, C] - evidently ⇒ the operation is bilinear.

ii) [A, B] = ABBA = - (BAAB) = - [B, A] ⇒ the operation is antisymmetric.

iii) Jacobi’s relation is satisfied:

[[A, B], C] + [[C, A], B] + [[B, C], A] = [ABBA, C] + [CAAC, B] + [BCCB, A] = =ABCBAC – (CABCBA) + CABACB – (BCA

BAC) + BCACBA – (ABCACB) = 0 Proposition 5

Let A ∈ sp(n, ) and pA(x) - the characteristic polynomial of the matrix A. Then:

a) pA(x) = pA(−x)

b) if pA(c)= 0, then pA(−c) = pA(c) = pA(−c) = 0, where c∈ . Proof

a) pA(x)= det(A – xI2n) , but A = J At J ⇒ )

(x

pA = det(J At J – xI2n) A = - J A-1J

= det(J At J – J x J) = = det( J( At + xI2n)J ) =

= det J det(At + xI2n)det J = det J = ±1 = det(At + xI2n) = det(At + xI2nt) =

= det(A + xI2n)t =

= det(A + xI2n) = det(A – (–x )I2n) = pA(−x) b) pA(c)= 0

) a

pA(−c) = 0. )

(x

pA is a real coefficients polynomial ⇒ pA(c) = 0 ) a

pA(−c) = 0.

2.A relation between the sets sp(n, ) and SP(n, )

Theorem:

Let A∈ M2n×2n(). The next relations are equivalent: a. A∈ sp (n, )

b. exp (At) ∈ SP (n, ) Proof

„a ⇒ b”

(6)

Let U(t) = (exp(At))tJ exp(At)

[1] Mircea Puta – Calcul matriceal, Timişoara, Editura Mirton, 2000

[2] Mircea Puta – Varietăţi diferenţiabile - probleme, Timişoara, Editura Mirton, 2002

[3] Mircea Puta – Hamiltonian Mechanical Systems and Geometric

Quantinization, Kluwer, 1993.

[4] R. Abraham, J. Marsden and T. Ratiu - Manifolds, Tensor Analysis and

Applications, Second Edition, Applied Math. Sciences 75, Springer Verlag,

(7)

Referensi

Dokumen terkait

Since projections are diagonalizable matrices with eigenvalues restricted to be in the set { 0, 1 } , it follows that the product in the generating function for the cycle index is

The perturbation of real eigenvalues of real skew-Hamiltonian matrices under structured perturbations is discussed as well and these results are used to analyze the properties of

Criteria for existence of Hamiltonian quaternionic matrices that are square roots of a given skewHamiltonian quaternionic matrix are developed.. The criteria are formulated in terms

For normal matrices in WPFn and those in WPFn for which the spectral radius is simple, we present approximating matrices that satisfy the strong P-F property and are polynomials

Following the result of Feingold and Varga, a well-known theorem of Taussky on the eigenvalue distribution is extended to block diagonally dominant matrices and block H − matrices

Still in the Gaussian case, [13] derived upper bounds of large deviations type for the spectral measure of band matrices, including certain sample covariance matrices.. Her

The most popular algorithm for finding the leaf whose value trickles up to the root (which corresponds to the best moves when two intelligent players are playing) is

Nextly, Mursaleen [31] and Mur- saleen and Edely [32] have defined the almost strong regularity of matrices for double sequences and applied these matrices to establish a core