Impossibility of dimension reduction in the nuclear norm
نویسندگان
چکیده
Let S1 (the Schatten–von Neumann trace class) denote the Banach space of all compact linear operators T : `2 → `2 whose nuclear norm ‖T‖S1 = ∑∞ j=1 σj(T ) is finite, where {σj(T )} ∞ j=1 are the singular values of T . We prove that for arbitrarily large n ∈ N there exists a subset C ⊆ S1 with |C| = n that cannot be embedded with bi-Lipschitz distortion O(1) into any n-dimensional linear subspace of S1. C is not even a O(1)-Lipschitz quotient of any subset of any n-dimensional linear subspace of S1. Thus, S1 does not admit a dimension reduction result á la Johnson and Lindenstrauss (1984), which complements the work of Harrow, Montanaro and Short (2011) on the limitations of quantum dimension reduction under the assumption that the embedding into low dimensions is a quantum channel. Such a statement was previously known with S1 replaced by the Banach space `1 of absolutely summable sequences via the work of Brinkman and Charikar (2003). In fact, the above set C can be taken to be the same set as the one that Brinkman and Charikar considered, viewed as a collection of diagonal matrices in S1. The challenge is to demonstrate that C cannot be faithfully realized in an arbitrary low-dimensional subspace of S1, while Brinkman and Charikar obtained such an assertion only for subspaces of S1 that consist of diagonal operators (i.e., subspaces of `1). We establish this by proving that the Markov 2-convexity constant of any finite dimensional linear subspace X of S1 is at most a universal constant multiple of √ log dim(X). E-mail addresses: [email protected], [email protected], [email protected]. Date: October 25, 2017. 2010 Mathematics Subject Classification. 30L05, 46B85, 46B20, 46B80.
منابع مشابه
On the Impossibility of Dimension Reduction in `1
The Johnson-Lindenstrauss Lemma shows that any n points in Euclidean space (with distances measured by the `2 norm) may be mapped down to O((log n)/ε) dimensions such that no pairwise distance is distorted by more than a (1+ε) factor. Determining whether such dimension reduction is possible in `1 has been an intriguing open question. We show strong lower bounds for general dimension reduction i...
متن کاملFractal Study on Nuclear Boundary of Cancer Cells in Urinary Smears
Background & Objectives: Cancer is a serious problem for human being and is becoming a serious problem day-by-day .A prerequisite for any therapeutic modality is early diagnosis. Automated cancer diagnosis by automatic image feature extraction procedures can be used as a feature extraction in the field of fractal dimension. The aim of this survey was to introduce a quantitative and objective...
متن کاملOn the Impossibility of Dimension Reduction for Doubling Subsets of ℓp, p>2
A major open problem in the field of metric embedding is the existence of dimension reduction for n-point subsets of Euclidean space, such that both distortion and dimension depend only on the doubling constant of the pointset, and not on its cardinality. In this paper, we negate this possibility for `p spaces with p > 2. In particular, we introduce an n-point subset of `p with doubling constan...
متن کاملOn the Impossibility of Dimension Reduction for Doubling Subsets
A major open problem in the field of metric embedding is the existence of dimension reduction for n-point subsets of Euclidean space, such that both distortion and dimension depend only on the doubling constant of the pointset, and not on its cardinality. In this paper, we negate this possibility for `p spaces with p > 2. In particular, we introduce an n-point subset of `p with doubling constan...
متن کاملDiagnosis of B-CLL Leukemia Using Fractal Dimension
Background:Leukemia is cancer of blood and bone marrow cells. In general, there are four types of leukemia: chronic myelogenous leukemia (CML), acute myeloid leukemia (AML), B-cell chronic lymphocytic leukemia (CLL) and acute lymphoblastic leukemia (ALL). Fractal geometry can be introduced as one of the effective ways to detect this type of cancer. In this study, with introduc...
متن کامل