Crouzeix's conjecture is an unsolved problem in matrix analysis. It was proposed by Michel Crouzeix in 2004,[1] and it can be stated as follows:
where the set is the field of values of a n×n (i.e. square) complex matrix and is a complex function that is analytic in the interior of and continuous up to the boundary of . Slightly reformulated, the conjecture can also be stated as follows: for all square complex matrices and all complex polynomials :
holds, where the norm on the left-hand side is the spectral operator 2-norm.
History
Crouzeix's theorem, proved in 2007, states that:[2]
(the constant is independent of the matrix dimension, thus transferable to infinite-dimensional settings).
Michel Crouzeix and Cesar Palencia proved in 2017 that the result holds for ,[3] improving the original constant of . The not yet proved conjecture states that the constant can be refined to .
Special cases
While the general case is unknown, it is known that the conjecture holds for some special cases. For instance, it holds for all normal matrices,[4] for tridiagonal 3×3 matrices with elliptic field of values centered at an eigenvalue[5] and for general n×n matrices that are nearly Jordan blocks.[4] Furthermore, Anne Greenbaum and Michael L. Overton provided numerical support for Crouzeix's conjecture.[6]
Further reading
Ransford, Thomas; Schwenninger, Felix L. (2018-03-01). "Remarks on the Crouzeix–Palencia Proof that the Numerical Range is a -Spectral Set". SIAM Journal on Matrix Analysis and Applications. 39 (1): 342–345. arXiv:1708.08633. doi:10.1137/17M1143757. S2CID43945191.
Gorkin, Pamela; Bickel, Kelly (2018-10-27). "Numerical Range and Compressions of the Shift". arXiv:1810.11680 [math.FA].
^Crouzeix, Michel; Palencia, Cesar (2017-06-07). "The Numerical Range is a -Spectral Set". SIAM Journal on Matrix Analysis and Applications. 38 (2): 649–655. doi:10.1137/17M1116672.
^Glader, Christer; Kurula, Mikael; Lindström, Mikael (2018-03-01). "Crouzeix's Conjecture Holds for Tridiagonal 3 x 3 Matrices with Elliptic Numerical Range Centered at an Eigenvalue". SIAM Journal on Matrix Analysis and Applications. 39 (1): 346–364. arXiv:1701.01365. doi:10.1137/17M1110663. S2CID43922128.