Symbolic Computation of Recursion Operators of Nonlinear Differential-Difference Equations

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Symbolic Computation of Recursion Operators of Nonlinear Differential-Difference Equations Ünal Göktaş and Willy Hereman Department of Computer Engineering Turgut Özal University, Keçiören, Ankara, Turkey unalgoktas@ttmail.com Department of Mathematical & Computer Sciences Colorado School of Mines, Golden, Colorado, U.S.A. whereman@mines.edu 1st International Symposium on Computing in Science & Engineering (ISCSE) 2010 Kuşadası, Aydın, Turkey Friday, June 4, 2010, 10:55a.m.

Acknowledgements Mark Hickman (Univ. of Canterbury, New Zealand) Bernard Deconinck (Univ. of Washington, U.S.A.) Jan Sanders (Free University, Amsterdam, The Netherlands) Jing-Ping Wang (Univ. of Kent, Canterbury, U.K.) Research supported in part by NSF under Grant No. CCF-0830783 This presentation was made in TeXpower

Outline Motivation Definitions Systems of Differential-difference equations Dilation Invariance Up-shift and Down-shift Operators Conservation Law Generalized (Higher Order) Symmetry Recursion Operator Algorithm Computer Demonstration

Motivation Differential-difference Equations (DDEs) arise in key branches of physics (classical, quantum, particle, statistical and plasma physics) model wave phenomena in nonlinear optics arise in bio-sciences An integrable DDE is linearizable or solvable via IST has infinite sequence of conservation laws has infinite sequence of generalized (higher order) symmetries has recursion operator(s) linking these symmetries

Systems of nonlinear DDEs Consider a system of nonlinear DDEs of first order, u n = F(u n l,..., u n 1, u n, u n+1,..., u n+m ) where u n and F are vector-valued functions with N components, and F is nonlinear function. DDEs with one discrete variable, denoted by integer n, which often corresponds to the discretization of a space variable dot stands for differentiation with respect to the continuous variable (time t) each component of F is assumed to be a polynomial with constant coefficients

Leading Example: The Toda Lattice One of the earliest and most famous examples of completely integrable DDEs is the Toda lattice: ÿ n = exp (y n 1 y n ) exp (y n y n+1 ), where y n is the displacement from equilibrium of the nth particle with unit mass under an exponential decaying interaction force between nearest neighbors. In new variables (u n, v n ), defined by u n = ẏ n, v n = exp (y n y n+1 ), lattice can be written in polynomial form u n = v n 1 v n, v n = v n (u n u n+1 )

Dilation Invariance A DDE is dilation invariant if it is invariant under a dilation (scaling) symmetry. Example Toda Lattice is invariant under scaling symmetry (t, u n, v n ) (λ 1 t, λ 1 u n, λ 2 v n )

Uniformity in Rank Define the weight, w, of a variable as the exponent of the scaling parameter (λ) which multiplies that variable. Since λ can be selected at will, t can always be replaced by t λ and, thus, w( d dt ) = w(d t) = 1. Weights of dependent variables are nonnegative, rational, and independent of n. For example, w(u n 3 ) = = w(u n ) = = w(u n+2 ). The rank, R, of a monomial is defined as the total weight of the monomial. An expression is uniform in rank if all of its terms have the same rank. Dilation symmetries, which are special Lie-point symmetries, are common to many DDEs.

Example For the Toda lattice: w(u n ) = 1, and w(v n ) = 2 Requiring uniformity in rank for each equation in the Toda lattice allows one to compute the weights of the dependent variables (and, thus, the scaling symmetry) with simple linear algebra. Balancing the weights of the various terms, w(u n ) + 1 = w(v n ), w(v n ) + 1 = w(u n ) + w(v n ), yields w(u n ) = 1, w(v n ) = 2 which confirms the dilation symmetry.

Up-Shift and Down-Shift Operator Define the shift operator D by Du n = u n+1. The operator D is often called the up-shift operator or forward- or right-shift operator. The inverse, D 1, is the down-shift operator or backward- or left-shift operator, D 1 u n = u n 1. Shift operators apply to functions by acting on the arguments of the functions. For example, DF(u n l,, u n 1, u n, u n+1,, u n+m ) = F(Du n l,, Du n 1, Du n, Du n+1,..., Du n+m ) = F(u n l+1,..., u n, u n+1, u n+2,, u n+m+1 ).

Conservation Law A conservation law of a DDE system D t ρ + J = 0 connects a conserved density ρ to an associated flux J, where both are scalar functions depending on u n and its shifts. D t is the total derivative with respect to time, = D I is the forward difference operator, I is the identity operator For readability, the components of u n will be denoted by u n, v n, w n, etc.

Example The Toda lattice has infinitely many conservation laws List of the densities of rank 1 R 4 : ρ (1) = u n ρ (2) = 1 2 u2 n + v n ρ (3) = 1 3 u3 n + u n (v n 1 + v n ) ρ (4) = 1 4 u4 n + u2 n (v n 1 + v n ) + u n u n+1 v n + 1 2 v2 n + v n v n+1 The first two density-flux pairs are easily computed by hand, and so is ρ (0) n = ln(v n ) which is the only non-polynomial density (of rank 0).

Generalized Symmetry A vector function G(u n ) is called a generalized symmetry of DDE system if the infinitesimal transformation u n u n + ɛg leaves the DDE system invariant up to order ɛ. G must then satisfy D t G = F (u n )[G] on solutions of the DDE system, where F (u n )[G] is the Fréchet derivative of F in the direction of G.

In the vector case with, say, components u n and v n, the Fréchet derivative operator is a matrix operator: F 1 k D k u n+k k F 1 D k v n+k F (u n ) = k F 2 u n+k D k k F 2 v n+k D k. Applied to G = (G 1 G 2 ) T, where T is transpose, one obtains F i (u n )[G] = k with i = 1, 2. F i u n+k D k G 1 + k F i v n+k D k G 2,

Example The first two non-trivial symmetries of the Toda lattice are G (1) = G (2) = v n v n 1 v n (u n+1 u n ), v n(u n + u n+1 ) v n 1 (u n 1 + u n ) v n (u 2 n+1 u2 n + v n+1 v n 1 ).

Recursion Operator A recursion operator R connects symmetries G (j+s) = RG (j), where j = 1, 2,, and s is the gap length. The symmetries are linked consecutively if s = 1. This happens in most (but not all) cases. For N-component systems, R is an N N matrix operator. The defining equation for R is D t R + [R, F (u n )] = R t + R [F] + R F (u n ) F (u n ) R = 0, where [, ] denotes the commutator and the composition of operators.

R [F] is the Fréchet derivative of R in the direction of F. For the scalar case, the operator R is of the form R = U(u n ) O((D I) 1, D 1, I, D) V (u n ), and then R [F ] = k (D k F ) U u n+k OV + k UO(D k F ) V u n+k. For the vector case, the elements of the N N operator matrix R are of the form R ij = U ij (u n ) O ij ((D I) 1, D 1, I, D) V ij (u n ).

Hence, for the 2-component case R [F] ij = k (D k F 1 ) U ij u n+k O ij V ij + k + k + k (D k F 2 ) U ij v n+k O ij V ij U ij O ij (D k F 1 ) V ij u n+k U ij O ij (D k F 2 ) V ij v n+k.

Example The recursion operator of the Toda lattice is u n I D 1 +I+(v n v n 1 )(D I) 1 1 v n I R=. v n I+v n D u n+1 I+v n (u n+1 u n )(D I) 1 1 v n I It is straightforward to verify that RG (1) = G (2). Algorithm for Recursion Operators We will now construct the recursion operator the recursion operator for the Toda lattice.

Step 1: Determine the Rank of the Recursion Operator The difference in the ranks of symmetries is used to compute the rank of the elements of the recursion operator. Recall that rank G (1) = 2 3, rank G (2) = 3 4. Assume that R G (1) = G (2) and use the formula rank R ij = rank G (k+1) i rank G (k) j, to compute a rank matrix associated to operator R : rank R = 1 0. 2 1

Step 2: Determine the Form of the Recursion Operator Assume that R = R 0 + R 1. R 0 is a sum of terms involving D 1, I, and D. The coefficients of these terms are admissible power combinations of u n, u n+1, v n, and v n 1 (which come from the terms on the right hand sides of the Toda lattice), so that all the terms have the correct rank. The maximum up-shift and down-shift operator that should be included can be determined by comparing two consecutive symmetries. For the Toda lattice, R 0 = (R 0) 11 (R 0 ) 12 (R 0 ) 21 (R 0 ) 22,

with (R 0 ) 11 = (c 1 u n + c 2 u n+1 ) I, (R 0 ) 12 = c 3 D 1 + c 4 I, (R 0 ) 21 = (c 5 u 2 n + c 6 u n u n+1 + c 7 u 2 n+1 + c 8 v n 1 + c 9 v n ) I +(c 10 u 2 n + c 11 u n u n+1 + c 12 u 2 n+1 + c 13 v n 1 +c 14 v n ) D, (R 0 ) 22 = (c 15 u n + c 16 u n+1 ) I. R 1 is a linear combination (with undetermined coefficients c jk ) of all suitable products of symmetries and covariants, i.e. Fréchet derivatives of densities, sandwiching (D I) 1. Hence, c jk G (j) (D I) 1 ρ (k) n, j k

where denotes the matrix outer product, defined as G(j) ( ) 1 G (j) (D I) 1 ρ (k) n,1 ρ (k) n,2 = 2 G(j) 1 (D I) 1 ρ (k) n,1 G (j) 1 (D I) 1 ρ (k) n,2 G (j) 2 (D I) 1 ρ (k) n,1 G (j) 2 (D I) 1 ρ (k) n,2. Only the pair (G (1), ρ (0) n ) can be used, otherwise the ranks in the recursion operator would be exceeded. Computing ρ (0) n = ( 0 1 v n I ),

After renaming c 10 to c 17, obtain R 1 = 0 c 17(v n 1 v n )(D I) 1 1 v n I 0 c 17 v n (u n u n+1 )(D I) 1 1 v n I. Then, R = R 0 + R 1.

Step 3: Determine the unknown coefficients Compute all the terms in the defining equation to find the c i. We refer to our papers for the details of the computation, resulting in c 2 = c 5 = c 6 = c 7 = c 8 = c 10 = c 11 = c 12 = c 13 = c 15 = 0, c 1 = c 3 = c 4 = c 9 = c 14 = c 16 = 1, and c 17 = 1. Substitute the constants into the candidate recursion operator to get its final form: u n I D 1 +I+(v n v n 1 )(D I) 1 1 v n I R=. v n I+v n D u n+1 I+v n (u n+1 u n )(D I) 1 1 v n I

Software Demonstration

Software packages in Mathematica Codes are available via the Internet: URL: http://inside.mines.edu/ whereman/

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