We describe non-relativistic limits of the 3D Proca and $\sqrt{\rm Proca}$ theories that yield spin-1 Schroedinger equations. Analogous results are found by generalized null reduction of the 4D Maxwell or complex self-dual ...

We consider the self-induced motions of three-dimensional oblate spheroids of density $\rho_s$ with varying aspect ratios $AR=b/c \leq 1$, where $b$ and $c$ are the spheroids' centre-pole radius and centre-equator radius ...

We study inflation in models with many interacting fields subject to randomly generated scalar potentials. We use methods from non-equilibrium random matrix theory to construct the potentials and an adaption of the ‘transport ...

How systems transit between different stable states under external perturbation is an important practical issue. We discuss here how a recently developed energy optimization method for identifying the minimal disturbance ...

We consider the steady, supercritical flow of a fluid layer. The layer is bounded above by a free surface and below by a rigid no-slip base. The base is in two parts: the downstream part of the base is stationary, while ...

In the context of f(R)-gravity with a spatially flat FLRW metric containing an ideal fluid, we use the method of invariant transformations to specify families of models which are integrable. We find three families of f(R) ...

The two-twistor formulation of particle mechanics in D-dimensional anti-de Sitter space for D=4,5,7, which linearises invariance under the AdS isometry group Sp(4;K) for K=R,C,H,, is generalized to the massless N-extended ...

Is the future predictable? If we know the initial state of a system exactly, then do the laws of physics determine its state arbitrarily far into the future? In Newtonian mechanics, the answer is yes. Similarly in ...

We present CrowdLearn, a new system that processes an existing corpus of crowdsourced machine learning programs to learn how to generate effective pipelines for solving supervised machine learning problems. CrowdLearn uses ...

The positive semidefinite rank of a convex body $C$ is the size of its smallest positive semidefinite formulation. We show that the positive semidefinite rank of any convex body $C$ is at least $\sqrt{\log d}$ where $d$ is ...

To explore the mechanisms linking Arctic sea-ice loss to changes in mid-latitude surface temperatures, we conduct idealized modeling experiments using an intermediate general circulation model and with sea-ice loss confined ...

We present a new operator in the ambitwistor string which glues together correlators with fewer points or of lower genus. It underpins the recursive construction of tree-level CHY scattering amplitudes by Dolan & Goddard, ...

We study a model of a cyclic, spatially homogeneous, anisotropic mixmaster universe of Bianchi type IX 'mixmaster' universe, containing the a radiation field with non-comoving ('tilted' with respect to the tetrad frame of ...

We study a model of a cyclic, spatially homogeneous, anisotropic mixmaster universe of Bianchi type IX 'mixmaster' universe, containing the a radiation field with non-comoving ('tilted' with respect to the tetrad frame of ...

© 2017, The Author(s). Linear perturbations of extremal black holes exhibit the Aretakis instability, in which higher derivatives of a scalar field grow polynomially with time along the event horizon. This suggests that ...

In this paper we study the hyperbolicity of the equations of motion for the most general Horndeski theory of gravity in a generic "weak field" background. We first show that a special case of this theory, namely Einstein ...

We study the cosmological effects of adding terms of higher-order in the usual energy-momentum tensor to the matter lagrangian of general relativity. This is in contrast to most studies of higher-order gravity which focus ...

We further investigate postulates for realist versions of r elativistic quantum theory and quantum field theory in Minkowski space and other background space-t imes. According to these postulates, quantum theory is ...

The study of vortex-ring-induced mixing has been significant for understanding stratified turbulent mixing in the absence of a mean flow. Renewed interest in this topic has prompted the development of a one-dimensional ...

Researchers have recently proposed several systems that ease the process of developing Bayesian probabilistic inference algorithms. These include systems for automatic inference algorithm synthesis as well as stronger ...