Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Grosvenor, Kevin T."'
Publikováno v:
JHEP 12 (2023) 022
We derive the action and symmetries of the bosonic sector of non-Lorentzian IIB supergravity by taking the non-relativistic string limit. We find that the bosonic field content is extended by a Lagrange multiplier that implements a restriction on the
Externí odkaz:
http://arxiv.org/abs/2306.04741
Autor:
Bukva, Aleksandar, de Gier, Jurriaan, Grosvenor, Kevin T., Jefferson, Ro, Schalm, Koenraad, Schwander, Eliot
Deep feedforward networks initialized along the edge of chaos exhibit exponentially superior training ability as quantified by maximum trainable depth. In this work, we explore the effect of saturation of the tanh activation function along the edge o
Externí odkaz:
http://arxiv.org/abs/2304.04784
We investigate how SL(2,Z) duality is realized in nonrelativistic type IIB superstring theory, which is a self-contained corner of relativistic string theory. Within this corner, we realize manifestly SL(2,Z)-invariant (p,q)-string actions. The const
Externí odkaz:
http://arxiv.org/abs/2208.13815
Publikováno v:
Phys. Rev. B 107, 045139 (2023)
Proliferation of defects is a mechanism that allows for topological phase transitions. Such a phase transition is found in two dimensions for the XY-model, which lies in the Berezinskii-Kosterlitz-Thouless (BKT) universality class. The transition poi
Externí odkaz:
http://arxiv.org/abs/2207.14343
There has been a surge of interest in effective non-Lorentzian theories of excitations with restricted mobility, known as fractons. Examples include defects in elastic materials, vortex lattices or spin liquids. In the effective theory novel coordina
Externí odkaz:
http://arxiv.org/abs/2112.00531
Autor:
Grosvenor, Kevin T., Jefferson, Ro
We explicitly construct the quantum field theory corresponding to a general class of deep neural networks encompassing both recurrent and feedforward architectures. We first consider the mean-field theory (MFT) obtained as the leading saddlepoint in
Externí odkaz:
http://arxiv.org/abs/2109.13247
We investigate the analogy between the renormalization group (RG) and deep neural networks, wherein subsequent layers of neurons are analogous to successive steps along the RG. In particular, we quantify the flow of information by explicitly computin
Externí odkaz:
http://arxiv.org/abs/2107.06898
Publikováno v:
Phys.Rev.Res. 3 (2021), 043186
Low-energy dynamics of many-body fracton excitations necessary to describe topological defects should be governed by a novel type of hydrodynamic theory. We use a Poisson bracket approach to systematically derive hydrodynamic equations from conservat
Externí odkaz:
http://arxiv.org/abs/2105.01084
Publikováno v:
JHEP 2104 (2021) 178
We develop a new heat kernel method that is suited for a systematic study of the renormalization group flow in Horava gravity (and in Lifshitz field theories in general). This method maintains covariance at all stages of the calculation, which is ach
Externí odkaz:
http://arxiv.org/abs/2101.03177
We study the quantum properties of a Galilean-invariant abelian gauge theory coupled to a Schr\"odinger scalar in 2+1 dimensions. At the classical level, the theory with minimal coupling is obtained from a null-reduction of relativistic Maxwell theor
Externí odkaz:
http://arxiv.org/abs/2007.03033