Results 151 to 160 of about 9,834 (320)
WEIGHTED TRACES ON ALGEBRAS OF PSEUDO-DIFFERENTIAL OPERATORS AND GEOMETRY ON LOOP GROUPS [PDF]
, 2002 Alexander Cardona +3 more
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 +2 more
wiley +1 more source
Feynman integrals, elliptic integrals and two-parameter K3 surfaces
Journal of High Energy PhysicsThe three-loop banana integral with three equal masses and the conformal two-loop five-point traintrack integral in two dimensions are related to a two-parameter family of K3 surfaces.
Claude Duhr, Sara Maggio
doaj +1 more source
Geometry of differential operators of second order, the algebra of densities, and groupoids
, 2012 H. M. Khudaverdian, Th.Th. Voronov
openalex +1 more source
A Pharmacometric Workflow for Resolving Model Instability in Model Use‐Reuse Settings
CPT: Pharmacometrics &Systems Pharmacology, EarlyView.ABSTRACT The development of fit‐for‐purpose pharmacokinetic‐pharmacodynamic (PKPD) models based on clinical and pre‐clinical data is a critically important process in model informed drug development. This process is often hampered by modeling stability issues that are often multifactorial in nature and difficult to overcome, leading to protracted model
Stephen B. Duffull +5 more
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
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 +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 +3 more
wiley +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 +2 more
wiley +1 more source