Results 61 to 70 of about 13,431 (178)

Inequalities on 2×2 block accretive partial transpose matrices

AIMS Mathematics
In this note, we first corrected a result of Alakhrass [1], then presented some inequalities related to 2 × 2 block accretive partial transpose matrices which generalized some results on block positive partial transpose matrices.
Lihong Hu, Junjian Yang
doaj   +1 more source

Quantum Powers and Primitive Ontology

Philosophy Compass, Volume 20, Issue 8, August 2025.
ABSTRACT This article surveys recent work on primitive ontology (PO) approaches to quantum mechanics, focusing on proposals that seek to integrate this approach with the metaphysics of causal powers. PO approaches aim to provide a clear metaphysical picture in which the world consists of local entities such as particles, matter density fields or ...
William M. R. Simpson
wiley   +1 more source

Relations for certain symmetric norms and anti-norms before and after partial trace

, 2012
Changes of some unitarily invariant norms and anti-norms under the operation of partial trace are examined. The norms considered form a two-parametric family, including both the Ky Fan and Schatten norms as particular cases.
A. Jamiołkowski, A. Jenčová, A. Rényi, A. Uhlmann, A. Wehrl, A.E. Rastegin, A.E. Rastegin, A.E. Rastegin, A.E. Rastegin, A.E. Rastegin, A.E. Rastegin, Alexey E. Rastegin, B. Lesche, C. Tsallis, D. Petz, D.A. Lidar, E.H. Lieb, F. Hansen, F. Hansen, F. Hiai, G. Lindblad, G.H. Hardy, G.M. D’Ariano, I. Bengtsson, J.-C. Bourin, J.S. Kim, K. Fan, K.M.R. Audenaert, K.M.R. Audenaert, L. Cai, M. Fannes, M. Ohya, M.-D. Choi, M.A. Nielsen, R. Alicki, R. Bhatia, R.A. Horn, S. Furuichi, S. Luo, S. Wehner, T. Ando, W. Roga, W.F. Stinespring, X. Cao, X. Hu, Z. Zhang   +45 more
core   +1 more source

What can we Learn from Quantum Convolutional Neural Networks?

Advanced Quantum Technologies, Volume 8, Issue 7, July 2025.
Quantum Convolutional Neural Networks have been long touted as one of the premium architectures for quantum machine learning (QML). But what exactly makes them so successful for tasks involving quantum data? This study unlocks some of these mysteries; particularly highlighting how quantum data embedding provides a basis for superior performance in ...
Chukwudubem Umeano, Annie E. Paine, Vincent E. Elfving, Oleksandr Kyriienko   +3 more
wiley   +1 more source

Graph rigidity for unitarily invariant matrix norms

Journal of Mathematical Analysis and Applications, 2020
A rigidity theory is developed for bar-joint frameworks in linear matrix spaces endowed with a unitarily invariant norm. Analogues of Maxwell's counting criteria are obtained and minimally rigid matrix frameworks are shown to belong to the matroidal class of (k,l)-sparse graphs for suitable k and l.
Kitson, Derek, Levene, Rupert H.
openaire   +2 more sources

Sparse graph signals – uncertainty principles and recovery

GAMM-Mitteilungen, Volume 48, Issue 2, June 2025.
ABSTRACT We study signals that are sparse either on the vertices of a graph or in the graph spectral domain. Recent results on the algebraic properties of random integer matrices as well as on the boundedness of eigenvectors of random matrices imply two types of support size uncertainty principles for graph signals.
Tarek Emmrich, Martina Juhnke, Stefan Kunis   +2 more
wiley   +1 more source

Further refinements of the Cauchy-Schwarz inequality for matrices [PDF]

, 2014
Let $A, B$ and $X$ be $n\times n$ matrices such that $A, B$ are positive semidefinite. We present some refinements of the matrix Cauchy-Schwarz inequality by using some integration techniques and various refinements of the Hermite--Hadamard inequality ...
Bakherad, Mojtaba
core  

On the stability of Runge–Kutta methods for arbitrarily large systems of ODEs

Communications on Pure and Applied Mathematics, Volume 78, Issue 4, Page 821-855, April 2025.
Abstract We prove that Runge–Kutta (RK) methods for numerical integration of arbitrarily large systems of Ordinary Differential Equations are linearly stable. Standard stability arguments—based on spectral analysis, resolvent condition or strong stability, fail to secure the stability of RK methods for arbitrarily large systems.
Eitan Tadmor
wiley   +1 more source

Preconditioning Techniques for Generalized Sylvester Matrix Equations

Numerical Linear Algebra with Applications, Volume 32, Issue 2, April 2025.
ABSTRACT Sylvester matrix equations are ubiquitous in scientific computing. However, few solution techniques exist for their generalized multiterm version, as they now arise in an increasingly large number of applications. In this work, we consider algebraic parameter‐free preconditioning techniques for the iterative solution of generalized multiterm ...
Yannis Voet
wiley   +1 more source

Unitarily invariant norm inequalities for some means [PDF]

Journal of Inequalities and Applications, 2014
We introduce some symmetric homogeneous means, and then show unitarily invariant norm inequalities for them, applying the method established by Hiai and Kosaki. Our new inequalities give the tighter bounds of the logarithmic mean than the inequalities given by Hiai and Kosaki.
openaire   +3 more sources