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RE: Re: for higher dimensions?

  I don't think there's any alternative to recasting your problem as a
conventional eigenproblem -- but it's not too messy to do so. For example:

  mm = Array[a, {2, 3, 4, 5}]
  MatrixForm[newm = Flatten[Transpose[Flatten[mm, 1], {3, 1, 2}], 1]]

 Then a judicious application of Partition[] to the result will get you your
A matrix.

  Tony Harker

Dr A.H. Harker
Department of Physics and Astronomy
University College London
Gower Street


]->-----Original Message-----
]->From: AES [mailto:siegman at] 
To: mathgroup at
]->Subject: [mg68585] [mg68532] Re: for higher dimensions?
]->In article <eb9p00$srh$1 at>,
]-> "Adriano Pascoletti" <pascolet at> wrote:
]->> Yes. Use Eigensystem.
]->> For instance
]->> M = {{2, 0, -3}, {3, 5, 6}, {1, 1, -1}};esys = Eigensystem[M];
]->Thanks -- but this, in my interpretation at least, is a 3 X 
]->3 but still
]->*two-dimensional* (rows and columns) matrix. 
]->My current task is to find eigensolutions to a problem that 
]->might be written most conveniently, with it's indices shown 
]->explicitly, as
]->   M_{i,j,m,n} A_{m,n}  = lambda A_{i,j}  
]->with M known and the objective being find a set of 
]->eigenvalues lambda[k] and "eigenmatrices"  A_{i,j}[k] that 
]->satisfy this equation.

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