3,559 research outputs found
Covariants,joint invariants and the problem of equivalence in the invariant theory of Killing tensors defined in pseudo-Riemannian spaces of constant curvature
The invariant theory of Killing tensors (ITKT) is extended by introducing the
new concepts of covariants and joint invariants of (product) vector spaces of
Killing tensors defined in pseudo-Riemannian spaces of constant curvature. The
covariants are employed to solve the problem of classification of the
orthogonal coordinate webs generated by non-trivial Killing tensors of valence
two defined in the Euclidean and Minkowski planes. Illustrative examples are
provided.Comment: 60 pages. to appear in J. Math. Phy
The E-Eigenvectors of Tensors
We first show that the eigenvector of a tensor is well-defined. The
differences between the eigenvectors of a tensor and its E-eigenvectors are the
eigenvectors on the nonsingular projective variety . We show that a generic
tensor has no eigenvectors on . Actually, we show that a generic
tensor has no eigenvectors on a proper nonsingular projective variety in
. By these facts, we show that the coefficients of the
E-characteristic polynomial are algebraically dependent. Actually, a certain
power of the determinant of the tensor can be expressed through the
coefficients besides the constant term. Hence, a nonsingular tensor always has
an E-eigenvector. When a tensor is nonsingular and symmetric, its
E-eigenvectors are exactly the singular points of a class of hypersurfaces
defined by and a parameter. We give explicit factorization of the
discriminant of this class of hypersurfaces, which completes Cartwright and
Strumfels' formula. We show that the factorization contains the determinant and
the E-characteristic polynomial of the tensor as irreducible
factors.Comment: 17 page
Estimation under group actions: recovering orbits from invariants
Motivated by geometric problems in signal processing, computer vision, and
structural biology, we study a class of orbit recovery problems where we
observe very noisy copies of an unknown signal, each acted upon by a random
element of some group (such as Z/p or SO(3)). The goal is to recover the orbit
of the signal under the group action in the high-noise regime. This generalizes
problems of interest such as multi-reference alignment (MRA) and the
reconstruction problem in cryo-electron microscopy (cryo-EM). We obtain
matching lower and upper bounds on the sample complexity of these problems in
high generality, showing that the statistical difficulty is intricately
determined by the invariant theory of the underlying symmetry group.
In particular, we determine that for cryo-EM with noise variance
and uniform viewing directions, the number of samples required scales as
. We match this bound with a novel algorithm for ab initio
reconstruction in cryo-EM, based on invariant features of degree at most 3. We
further discuss how to recover multiple molecular structures from heterogeneous
cryo-EM samples.Comment: 54 pages. This version contains a number of new result
Symmetry groups, semidefinite programs, and sums of squares
We investigate the representation of symmetric polynomials as a sum of
squares. Since this task is solved using semidefinite programming tools we
explore the geometric, algebraic, and computational implications of the
presence of discrete symmetries in semidefinite programs. It is shown that
symmetry exploitation allows a significant reduction in both matrix size and
number of decision variables. This result is applied to semidefinite programs
arising from the computation of sum of squares decompositions for multivariate
polynomials. The results, reinterpreted from an invariant-theoretic viewpoint,
provide a novel representation of a class of nonnegative symmetric polynomials.
The main theorem states that an invariant sum of squares polynomial is a sum of
inner products of pairs of matrices, whose entries are invariant polynomials.
In these pairs, one of the matrices is computed based on the real irreducible
representations of the group, and the other is a sum of squares matrix. The
reduction techniques enable the numerical solution of large-scale instances,
otherwise computationally infeasible to solve.Comment: 38 pages, submitte
Partial normalizations of coxeter arrangements and discriminants
We study natural partial normalization spaces of Coxeter arrangements and discriminants
and relate their geometry to representation theory. The underlying ring structures arise from Dubrovinās
Frobenius manifold structure which is lifted (without unit) to the space of the arrangement. We also
describe an independent approach to these structures via duality of maximal CohenāMacaulay fractional
ideals. In the process, we find 3rd order differential relations for the basic invariants of the Coxeter
group. Finally, we show that our partial normalizations give rise to new free divisors
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