Mutually Unbiased Bases, ETFs, and Zauner’s Conjecture — Problem 22
Mutually Unbiased Bases, ETFs, and Zauner’s Conjecture — Problem 22
Problem statement
Conjecture 22.
Let denote the largest possible number of (simultaneously) mutually unbiased bases (MUBs) in . We have .
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Source snapshot inspected on 10 September 2026. Subsequent research status and the accuracy of source formalizations have not been independently certified.
Entry 11 Mutually Unbiased Bases, ETFs, and Zauner’s Conjecture (ASB)
Finite frame theory is the source of many beautiful questions. A remarkable example concerns the existence of Mutually Unbiased Bases, objects of interest in Quantum Physics (see MW (24) for a review).
Definition 11.1 (Mutually Unbiased Bases).
Two orthonormal bases are called mutually unbiased if for all . Let denote the largest possible number of (simultaneously) mutually unbiased bases (MUBs) in .
In BBRV (02) it is shown that and that equality is achieved when is a prime power. For not a prime power, the problem of determining is still open. The smallest open instance is particularly well known for being a tantalizing open problem that has remained open (see Open Problem 6.2 in Ban (16)).
It is known that (see, e.g., BDK (22)). Note that for the existence of two mutually unbiased bases is equivalent to the existence of Hadamard Matrices, Conjeture 14 in this blog BKMR25b ().
An interesting approach to this problem is to try to build Sum-of-Squares proofs of . In BDK (22) it was shown that a certain relaxation related to degree-2 Sum-of-Squares cannot prove that . It is however unclear whether higher degree levels of Sum-of-Squares can provide such a proof.
Note that this is a statement about the existence, or not, of vectors for and satisfying
These can for example be encoded with quartic relations on the real and imaginary parts of the vectors components (since ). An alternative encoding can be written by noting that the constraints for are quadratic and that, since is the smallest possible value for the largest inner-product between vectors in different basis, one can rewrite the constraints as which are semidefinite constraints (on Hermitian matrices) involving a quadratic quantity: .
Another very interesting object in this field is an Equiangular Tight Frame (ETF). In a frame is a set of spanning vectors . A frame is called unit-normed if all vectors have unit-norm and it is called a tight frame if is a multiple of the identity matrix. In general the smallest eigenvalue of this matrix is called the lower frame bound, and the largest the upper frame bound, a tight frame corresponds to a frame for which these match (see §11 in Ban (25)). The worst-case coherence of a unit-norm frame is given by (note that Mutually Unbiased Bases, described above, have worst-case coherence ). Equiangular tight frames are the unit-norm frames with the smallest worst-case coherence among frames with the same size and dimension (see §12 in Ban (25)).
Definition 11.2 (Equiangular Tight Frame (ETF) in ).
A frame is an ETF if:
It is unit-normed: for all .
It is a tight frame: is a multiple of the identity matrix.
It is equiangular: there exists such that for all .
Note that needs to match the Welch bound, meaning that .
With a tensoring argument (see §12 in Ban (25)) one can show that . ETFs in with vectors are particularly important in Quantum Physics and are known as SIC-POVMs (Symmetric, Informationally Complete, Positive Operator-Valued Measures). It is a well known conjecture that they exist for all dimensions , known as Zauner’s Conjecture Zau (99).
There has been fascinating recent progress AFK (25): a proposed construction (corresponding to an orbit of the Weyl–Heisenberg group acting on ) has been conditionally proven to indeed be a SIC-POVM assuming a couple of conjectures in Number Theory, examples of so-called Stark Conjectures. This shows that these conjectures imply Zauner’s Conjecture. A unconditional proof of Zauner’s Conjecture remains unavailable.
CC BY 4.0; Afonso S. Bandeira, Daniil Dmitriev, Kevin Lucca, Petar Nizić-Nikolac and Almut Rödder. HTML converted to Markdown; original links and mathematical notation retained.
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