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Peter G. Casazza

Publications and source records attributed to Peter G. Casazza.

At least 19 recordsLinked to original sources
arXiv2023

Real matrices whose columns have equal modulus coordinates

We study $m \times n$ matrices whose columns are of the form \[\{(a_{1j},\ldots, a_{nj}): \quad a_{1j} = λ_j,\ a_{ij} = \pmλ_j\ , \ λ_j >0 ,\ j=1,2,\ldots,n\}.\] We explicitly construct for all $a = (a_1,\ldots, a_{\frac{m(m- 1)}{2}}) \in \mathbb{R}^{\frac{m(m-1)}{2}}$ a matrix of the above form whose rows have pairwise dot product equal to $a$. Using Hardamard matrices constructed by Sylvester we classify all matrices of the above form whose rows have pairwise dot product equal to $a$. We also use our results to reformulate the Hadamard conjecture.

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arXiv2023

New characterizations of the unit vector basis of $c_0$ or $\ell_p$

Motivated by Altshuler's famous characterization of the unit vector basis of $c_0$ or $\ell_p$ among symmetric bases, we obtain similar characterizations among democratic bases and among bidemocratic bases. We also prove a separate characterization of the unit vector basis of $\ell_1$.

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arXiv2022

Remarks on scalable frames

This paper investigates scalable frame in ${\mathbb R}^n$. We define the reduced diagram matrix of a frame and use it to classify scalability of the frame under some conditions. We give a new approach to the scaling problem by breaking the problem into two smaller ones, each of which is easily solved, giving a simple way to check scaling. Finally, we study the scalability of dual frames.

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arXiv2022

Piecewise scalable frames

In this paper we define "piecewise scalable frames". This new scaling process allows us to alter many frames to Parseval frames which is impossible by the previous standard scaling. We give necessary and sufficient conditions for a frame to be piecewise scalable. We show that piecewise scalability is preserved under unitary transformations. Unlike standard scaling, we show that all frames in $\RR^2$ and $\RR^3$ are piecewise scalable. We also show that if the frame vectors are close to each other, then they might not be piecewise scalable. Several properties of scaling constants are also presented.

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arXiv2022

The core of a Grassmannian frame

Let $X=\{x_i\}_{i=1}^m$ be a set of unit vectors in $\RR^n$. The coherence of $X$ is $\coh(X):=\max_{i\not=j}|\langle x_i, x_j\rangle|$. A vector $x\in X$ is said to be isolable if there are no unit vectors $x'$ arbitrarily close to $x$ such that $|\langle x', y\rangle|<\coh(X)$ for all other vectors $y$ in $X$. We define the {\bf core} of a Grassmannian frame $X=\{x_i\}_{i=1}^m$ in $\RR^n$ at angle $α$ as a maximal subset of $X$ which has coherence $α$ and has no isolable vectors. In other words, if $Y$ is a subset of $X$, $\coh(Y)=α$, and $Y$ has no isolable vectors, then $Y$ is a subset of the core. We will show that every Grassmannian frame of $m>n$ vectors for $\RR^n$ has the property that each vector in the core makes angle $α$ with a spanning family from the core. Consequently, the core consists of $\ge n+1$ vectors. We then develop other properties of Grassmannian frames and of the core.

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arXiv2021

On uniqueness and plentitude of subsymmetric sequences

We explore the diversity of subsymmetric basic sequences in spaces with a subsymmetric basis. We prove that the subsymmetrization $Su(T^*)$ of Tsirelson's original Banach space provides the first known example of a space with a unique subsymmetric basic sequence that is additionally non-symmetric. Contrastingly, we provide a criterion for a space with a subsymmetric basis to contain a continuum of nonequivalent subsymmetric basic sequences and apply it to $Su(T^*)^*$. Finally, we provide a criterion for a subsymmetric sequence to be equivalent to the unit vector basis of some $\ell_p$ or $c_0$.

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arXiv2021

An elementary proof of a fundamental result in phase retrieval

Edidin [3] proved a fundamental result in phase retrieval: Theorem: A family of orthogonal projections $\{P_i\}_{i=1}^m$ does phase retrieval in $\mathbb{R}^n$ if and only if for every $0\not= x\in \mathbb{R}^n$, the family $\{P_ix\}_{i=1}^m$ spans $\mathbb{R}^n$. The proof of this result relies on Algebraic Geometry and so is inaccessible to many people in the field. We will give an elementary proof of this result without Algebraic Geometry. We will also solve the complex version of this result by showing that the "if" part fails and the "only if" part holds in $\mathbb{C}^n$. Finally, we will show that these techniques can be used to verify two classifications of norm retrieval.

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arXiv2019

A notion of optimal packings of subspaces with mixed-rank and solutions

We resolve a longstanding open problem by reformulating the Grassmannian fusion frames to the case of mixed dimensions and show that this satisfies the proper properties for the problem. In order to compare elements of mixed dimension, we use a classical embedding to send all fusion frame elements to points on a higher dimensional Euclidean sphere, where they are given "equal footing". Over the embedded images -- a compact subset in the higher dimensional embedded sphere -- we define optimality in terms of the corresponding restricted coding problem. We then construct infinite families of solutions to the problem by using maximal sets of mutually unbiased bases and block designs. Finally, we show that using Hadamard 3-designs in this construction leads to infinite examples of maximal orthoplectic fusion frames of constant-rank. Moreover, any such fusion frames constructed by this method must come from Hadamard 3-designs.

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arXiv2019

Regular two distance sets

This paper makes a deep study of regular two-distance sets. A set of unit vectors $X$ in Euclidean space $\RR^n$ is said to be regular two-distance set if the inner product of any pair of its vectors is either $α$ or $β$, and the number of $α$ (and hence $β$) on each row of the Gram matrix of $X$ are the same. We present various properties of these sets as well as focus on the case where they form tight frames for the underling space. We then give some constructions of regular two-distance sets, in particular, two-distance frames, both tight and non-tight cases. Connections among two-distance sets, equiangular lines and quasi-symmetric designs are also given.

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arXiv2019

Optimal Parseval frames: Total coherence and total volume

We introduce three quantities called total coherence, total volume, and nuclear energy, and we show that equiangular Parseval frames maximize all three of these quantities over the set of all Parseval frames. We then show that equiangular Parseval frames also maximize the total volume and nuclear energy over the set of equal norm frames. Along the way we derive a bound on the smallest k-dimensional volume in an equal norm frame which is a generalization of the Welch bound. We conclude with an extensive list of open questions.

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arXiv2018

Constructions and properties of optimally spread subspace packings via symmetric and affine block designs and mutually unbiased bases

We continue the study of optimal chordal packings, with emphasis on packing subspaces of dimension greater than one. Following a principle outlined in a previous work, where the authors use maximal affine block designs and maximal sets of mutually unbiased bases to construct Grassmannian $2$-designs, we show that their method extends to other types of block designs, leading to a plethora of optimal subspace packings characterized by the orthoplex bound. More generally, we show that any optimal chordal packing is necessarily a fusion frame and that its spatial complement is also optimal.

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arXiv2018

The Solution to the Frame Quantum Detection Problem

We will give a complete solution to the frame quantum detection problem. We will solve both cases of the problem: the quantum injectivity problem and quantum state estimation problem. We will answer the problem in both the real and complex cases and in both the finite dimensional and infinite dimensional cases. Finite Dimensional Case: (1) We give two complete classifications of the sets of vectors which solve the injectivity problem - for both the real and complex cases. We also give methods for constructing them. (2) We show that the frames which solve the injectivity problem are open and dense in the family of all frames. (3) We show that the Parseval frames which give injectivity are dense in the Parseval frames. (4) We classify all frames for which the state estimation problem is solvable, and when it is not solvable, we give the best approximation to a solution. Infinite Dimensional Case: (1) We give a classification of all frames which solve the injectivity problem and give methods for constructing solutions. (2) We show that the frames solving the injectivity problem are neither open nor dense in all frames. (3) We give necessary and sufficient conditions for the state estimation problem to always have solutions for measurements in $\ell_1$ and show that there is no injective frame for which the state estimation problem is solvable for all measurements in $\ell_2$. (4) When the state estimation problem does not have an exact solution, we give the best approximation to a solution.

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arXiv2018

Phase Retrieval in $\ell_2(\RR)$

We will review the major results in finite dimensional real phase retrieval for vectors and projections. We then (1)prove that many of these theorems hold in infinite dimensions, (2) give counter-examples to show that many others fail in infinite dimensions, (3)list finite dimensional results are unknown for $\ell_2$.

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arXiv2017

On the structures of Grassmannian frames

A common criterion in the design of finite Hilbert space frames is minimal coherence, as this leads to error reduction in various signal processing applications. Frames that achieve minimal coherence relative to all unit-norm frames are called Grassmannian frames, a class which includes the well-known equiangular tight frames. However, the notion of "coherence minimization" varies according to the constraints of the ambient optimization problem, so there are other types of "minimally coherent" frames one can speak of. In addition to Grassmannian frames, we consider the class of frames which minimize coherence over the space of frames which are both unit-norm and tight, which we call 1-Grassmannian frames. We observe that these two types of frames coincide in many settings, but not all; accordingly, we investigate some of the differences between the resulting theories. For example, one noteworthy advantage enjoyed by 1-Grassmannian frames is that their optimality properties are preserved under the Naimark complement.

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arXiv2017

Toward the Classification of Biangular Harmonic Frames

Equiangular tight frames (ETFs) and biangular tight frames (BTFs) - sets of unit vectors with basis-like properties whose pairwise absolute inner products admit exactly one or two values, respectively - are useful for many applications. A well-understood class of ETFs are those which manifest as harmonic frames - vector sets defined in terms of the characters of finite abelian groups - because they are characterized by combinatorial objects called difference sets. This work is dedicated to the study of the underlying combinatorial structures of harmonic BTFs. We show that if a harmonic frame is generated by a divisible difference set, a partial difference set or by a special structure with certain Gauss summing properties - all three of which are generalizations of difference sets that fall under the umbrella term "bidifference set" - then it is either a BTF or an ETF. However, we also show that the relationship between harmonic BTFs and bidifference sets is not as straightforward as the correspondence between harmonic ETFs and difference sets, as there are examples of bidifference sets that do not generate harmonic BTFs. In addition, we study another class of combinatorial structures, the nested divisible difference sets, which yields an example of a harmonic BTF that is not generated by a bidifference set.

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arXiv2017

The exact constant for the $\ell_1-\ell_2$ norm inequality

A fundamental inequality for Hilbert spaces is the $\ell_1-\ell_2$-norm inequality which gives that for any $x \in H^n$, $\|x\|_1\le \sqrt{n}\|x\|_2.$ But this is a strict inequality for all but vectors with constant modulus for their coefficients. We will give a trivial method to compute, for each x, the constant $c$ for which $\|x\|_1=c\sqrt{n}\|x\|_2.$ Since this inequality is one of the most used results in Hilbert space theory, we believe this will have unlimited applications in the field. We will also show some variations of this result.

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arXiv2017

Associating vectors in $\CC^n$ with rank 2 projections in $\RR^{2n}$: with applications

We will see that vectors in $\CC^n$ have natural analogs as rank 2 projections in $\RR^{2n}$ and that this association transfers many vector properties into properties of rank two projections on $\RR^{2n}$. We believe that this association will answer many open problems in $\CC^n$ where the corresponding problem in $\RR^n$ has already been answered - and vice versa. As a application, we will see that phase retrieval (respectively, phase retrieval by projections) in $\CC^n$ transfers to a variation of phase retrieval by rank 2 projections (respectively, phase retrieval by projections) on $\RR^{2n}$. As a consequence, we will answer the open problem: Give the complex version of Edidin's Theorem \cite{E} which classifies when projections do phase retrieval in $\RR^n$. As another application we answer a longstanding open problem concerning fusion frames by showing that fusion frames in $\CC^n$ associate with fusion frames in $\RR^{2n}$ with twice the dimension. As another application, we will show that a family of mutually unbiased bases in $\CC^n$ has a natural analog as a family of mutually unbiased rank 2 projections in $\RR^{2n}$. The importance here is that there are very few real mutually unbiased bases but now there are unlimited numbers of real mutually unbiased rank 2 projections to be used in their place. As another application, we will give a variaton of Edidin's theorem which gives a surprising classification of norm retrieval. Finally, we will show that equiangular and biangular frames in $\CC^n$ have an analog as equiangular and biangular rank 2 projections in $\RR^{2n}$.

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