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Titlebook: Upper Bounds for Grothendieck Constants, Quantum Correlation Matrices and CCP Functions; Frank Oertel Book 2024 The Editor(s) (if applicab

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楼主: Julienne
发表于 2025-3-25 05:09:04 | 显示全部楼层
,Introduction and Motivation: The Outstanding Story of Grothendieck’s Theorem,rview of the historical perspective and highlight the key role and strong implications of A. Grothendieck’s seminal result, which lead to the introduction of a general theory of operator ideals (in the sense of A. Pietsch), an expansion of the “local” theory of Banach spaces, and which enabled a fur
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A Quantum Correlation Matrix Version of the Grothendieck Inequality,son, with quantum correlation matrices and thus with Bell’s inequalities, which play a fundamental role in the foundations of quantum physics. In doing so, we show that the sign of any of the . entries of the real Walsh-Hadamard transform can be determined in exactly . calculation steps. We point to
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Completely Correlation Preserving Functions,P), i.e., non-linear functions which map a classical correlation matrix of any size—entrywise—into a correlation matrix of the same size, such as Grothendieck’s function . (in the real case). Important connections between CCP functions, an entrywise functional calculus for positive semidefinite matr
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,The Real Case: Towards Extending Krivine’s Approach,show that the real Grothendieck inequality and Krivine’s approach can be unified in terms of—invertible—CCP-functions and with help of Hermite polynomials. Our general approach is built on a decisive link between “suitably compressed” inverses of CCP functions and quantum correlation matrices. In ge
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Book 2024x Grothendieck constant (an open problem since 1953). It describes in detail the state of the art in research on this fundamental inequality, including Krivine‘s recent contributions, and sheds light on related questions in mathematics, physics and computer science, particularly with respect to the
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0075-8434 rising links to neighbouring fields, including quantum inforThis book concentrates on the famous Grothendieck inequality and the continued search for the still unknown best possible value of the real and complex Grothendieck constant (an open problem since 1953). It describes in detail the state of
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Powers of Inner Products of Random Vectors, Uniformly Distributed on the Sphere,perators and reveal their connection with real and complex Gaussian variables, leading to the more general integration of expected powers of inner products of random vectors, uniformly distributed on the sphere, which are also of importance in statistical machine learning theory (in form of the so called “kernel trick”).
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