English
Related papers

Related papers: Interpreting canonical tensor model in minisupersp…

200 papers

Canonical transformations are defined and discussed along with the exponential, the coherent and the ultracoherent vectors. It is shown that the single-mode and the $n$-mode squeezing operators are elements of the group of canonical…

Quantum Physics · Physics 2009-11-10 Subhashish Banerjee , Joachim Kupsch

Canonical correlation analysis is a widely used multivariate statistical technique for exploring the relation between two sets of variables. This paper considers the problem of estimating the leading canonical correlation directions in…

Statistics Theory · Mathematics 2015-10-16 Chao Gao , Zongming Ma , Zhao Ren , Harrison H. Zhou

The development of compositional distributional models of semantics reconciling the empirical aspects of distributional semantics with the compositional aspects of formal semantics is a popular topic in the contemporary literature. This…

Logic · Mathematics 2013-04-30 Edward Grefenstette

Modelling compositionality has been a longstanding area of research in the field of vector space semantics. The categorical approach to compositionality maps grammar onto vector spaces in a principled way, but comes under fire for requiring…

Computation and Language · Computer Science 2019-01-31 Martha Lewis

We address an apparent conflict between the traditional canonical quantization framework of quantum theory and the spatially restricted quantum dynamics, when the translation invariance of the otherwise free quantum system is broken by…

Mathematical Physics · Physics 2015-06-26 P. Garbaczewski , W. Karwowski

Discrete canonical evolution is a key tool for understanding the dynamics in discrete models of spacetime, in particular those represented by a triangular Regge lattice. We consider a finite-dimensional system whose evolution is realized by…

General Relativity and Quantum Cosmology · Physics 2020-11-18 Jakub Káninský

The concept of fuzzy cardinal semantic transformation as a basis for creating fuzzy semantic numeration systems is introduced in this work. Both fuzziness of the initial data - cardinals of abstract entities - and fuzziness of the…

Artificial Intelligence · Computer Science 2022-06-24 Alexander Chunikhin , Vadym Zhytniuk

This study clarifies the proper criteria to assess the modeling capacity of a general tensor model. The work analyze the problem based on the study of tensor ranks, which is not a well-defined quantity for higher order tensors. To process,…

Quantum Physics · Physics 2022-04-19 Tong Yang

A method of constructing a canonical gauge invariant quantum formulation for a non-gauge classical theory depending on a set of parameters is advanced and then applied to the theory of closed bosonic string interacting with massive…

High Energy Physics - Theory · Physics 2009-10-30 I. L. Buchbinder , V. D. Pershin , G. B. Toder

The Ashtekar variables have been use to find a number of exact solutions in quantum gravity and quantum cosmology. We investigate the origin of these solutions in the context of a number of canonical transformations (both complex and real)…

General Relativity and Quantum Cosmology · Physics 2012-08-27 J. Fernando Barbero , Michael P. Ryan,

In the previous paper, the number distribution of the low-lying spectra around Gaussian solutions representing various dimensional fuzzy tori of a tensor model was numerically shown to be in accordance with the general relativity on tori.…

High Energy Physics - Theory · Physics 2009-01-06 Naoki Sasakura

To understand spacetime dynamics in the canonical tensor model of quantum gravity for the positive cosmological constant case, we analytically and numerically study the phase profile of its exact wave function in a coordinate…

High Energy Physics - Theory · Physics 2021-12-01 Naoki Sasakura

Quantization in the minisuperspace of non minimal scalar-tensor theories leads to a partial differential equation which is non separable. Through a conformal transformation we can recast the Wheeler-DeWitt equation in an integrable form,…

General Relativity and Quantum Cosmology · Physics 2009-10-31 Julio C. Fabris , Nelson Pinto-Neto , A. F. Velasco

A canonical relativistic formulation is introduced to quantize electromagnetic field in the presence of a polarizable and magnetizable moving medium. The medium is modeled by a continuum of four vectors in a phenomenological way. The…

Quantum Physics · Physics 2009-08-18 M. Amooshahi

We consider a dynamical triangulation model of euclidean quantum gravity where the topology is not fixed. This model is equivalent to a tensor generalization of the matrix model of two dimensional quantum gravity. A set of moves is given…

High Energy Physics - Lattice · Physics 2009-10-22 Bas V. de Bakker

Modeling an anisotropic spatially and temporarily dispersive magnetodielectric medium by two independent collections of three dimensional vector fields, we demonstrate a fully canonical quantization of electromagnetic field in the presence…

Quantum Physics · Physics 2010-01-29 Majid Amooshahi

The canonical dimension is an invariant attached to admissible representations of p-adic reductive groups, which has only received significant attention in the case of mod-p representations. In the case of complex representations, the…

Representation Theory · Mathematics 2025-09-30 Mick Gielen

Utilising dynamic electromagnetic field control over charged particles serves as the basis for a quantum machine learning platform that operates on observables rather than directly on states. Such a platform can be physically realised in…

Quantum Physics · Physics 2024-06-12 Jesús Fuentes

A canonical quantization of two-dimensional gravity minimally coupled to real scalar and spinor Majorana fields is presented. The physical state space of the theory is completely described and calculations are also made of the average value…

General Relativity and Quantum Cosmology · Physics 2007-05-23 S. N. Vergeles

Humans understand a set of canonical geometric transformations (such as translation and rotation) that support generalization by being untethered to any specific object. We explore inductive biases that help a neural network model learn…

Computer Vision and Pattern Recognition · Computer Science 2020-11-18 Zachary Dulberg , Jonathan Cohen