Results 161 to 170 of about 276,684 (327)

Geometry of differential operators of second order, the algebra of densities, and groupoids

, 2012
H. M. Khudaverdian, Th.Th. Voronov
openalex   +1 more source

Early Adolescent Cyberbullying Victimization, Learning Readiness, and Academic Achievement Among South Australian Students

Psychology in the Schools, EarlyView.
ABSTRACT Cyberbullying is an increasingly researched topic in the field of adolescence, largely due to its pervasiveness and negative wellbeing outcomes for victims. However, existing literature in this area largely focuses on those aged above 13 years, despite evidence suggesting that early adolescents (ages 10–13) also experience victimization ...
Jasmin Williams, Sarah Halliday
wiley   +1 more source

Chiral-Yang-Mills theory, non commutative differential geometry, and the need for a Lie super-algebra [PDF]

, 2006
Jean Thierry‐Mieg
openalex   +1 more source

Modeling General Asymptotic Calabi–Yau Periods

Fortschritte der Physik, EarlyView.
Abstract In the quest to uncovering the fundamental structures that underlie some of the asymptotic Swampland conjectures the authors initiate the general study of asymptotic period vectors of Calabi–Yau manifolds. The strategy is to exploit the constraints imposed by completeness, symmetry, and positivity, which are formalized in asymptotic Hodge ...
Brice Bastian, Thomas W. Grimm, Damian van de Heisteeg   +2 more
wiley   +1 more source

Affine differential geometry and affine rotation surfaces: algebraic surfaces invariant under non-Euclidean affine rotations

, 2018
Juan Gerardo Alcázar, Ron Goldman
openalex   +2 more sources

Toward Useful Quantum Kernels

Advanced Quantum Technologies, EarlyView.
The hybrid approach to Quantum Supervised Machine Learning is compatible with Noisy Intermediate Scale Quantum (NISQ) devices but hardly useful. Pure quantum kernels requiring fault‐tolerant quantum computers are more promising. Examples are kernels computed by means of the Quantum Fourier Transform (QFT) and kernels defined via the calculation of ...
Massimiliano Incudini, Francesco Martini, Alessandra Di Pierro   +2 more
wiley   +1 more source

What can we Learn from Quantum Convolutional Neural Networks?

Advanced Quantum Technologies, EarlyView.
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

(1) A New Geometry (2) Algebra Part II, for the Use of Students preparing for the Intermediate and Previous Examinations of Indian Universities (3) Parametric Coefficients in the Differential Geometry of Curves [PDF]

, 1911

openalex   +1 more source

Reproducing the Effects of Quantum Deformation in the Undeformed Jaynes‐Cummings Model

Advanced Quantum Technologies, EarlyView.
The inverse problem approach, where atomic probabilities are modulated according to a time‐dependent coupling, is studied for the Jaynes‐Cummings (JC) model. In particular, emphasis is placed on how to reproduce the effects of quantum deformation in a non‐deformed JC model.
Thiago T. Tsutsui, Antonio S. M. de Castro, Fabiano M. Andrade   +2 more
wiley   +1 more source

Neural networks for structured grid generation. [PDF]

Sci Rep
Khairullin B, Rykovanov S, Zagidullin R.
europepmc   +1 more source