Dualities and Hidden Supersymmetry in String Quantum Cosmology

A supersymmetric approach to string quantum cosmology based on the non-compact, global duality symmetries of the effective action is developed. An N=2 supersymmetric action is derived whose bosonic component is the Neveu-Schwarz/Neveu-Schwarz sector of the $(d+1)$--dimensional effective action compactified on a $d$--torus. A representation for the supercharges is found and the form of the zero-and one-fermion quantum states is determined. The purely bosonic component of the wavefunction is unique and manifestly invariant under the symmetry of the action. The formalism applies to a wide class of non-linear sigma-models.Comment: 18 pages, plain Latex, no figure

The sign problem in full configuration interaction quantum Monte Carlo: Linear and sub-linear representation regimes for the exact wave function

We investigate the sign problem for full configuration interaction quantum Monte Carlo (FCIQMC), a stochastic algorithm for finding the ground state solution of the Schr\"odinger equation with substantially reduced computational cost compared with exact diagonalisation. We find $k$-space Hubbard models for which the solution is yielded with storage that grows sub-linearly in the size of the many-body Hilbert space, in spite of using a wave function that is simply linear combination of states. The FCIQMC algorithm is able to find this sub-linear scaling regime without bias and with only a choice of Hamiltonian basis. By means of a demonstration we solve for the energy of a 70-site half-filled system (with a space of $10^{38}$ determinants) in 250 core hours, substantially quicker than the $\sim$10$^{36}$ core hours that would be required by exact diagonalisation. This is the largest space that has been sampled in an unbiased fashion. The challenge for the recently-developed FCIQMC method is made clear: expand the sub-linear scaling regime whilst retaining exact on average accuracy. This result rationalizes the success of the initiator adaptation (i-FCIQMC) and offers clues to improve it. We argue that our results changes the landscape for development of FCIQMC and related methods.Comment: 6 pages, 4 figures. The mentioned supplementary material is included as "Ancillary files". Comments welcom

The emergence of magnetic flux through a partially ionised solar atmosphere

We present results from 2.5D numerical simulations of the emergence of magnetic flux from the upper convection zone through the photosphere and chromosphere into the corona. Certain regions of the solar atmosphere are at sufficiently low temperatures to be only partially ionised, in particular the lower chromosphere. This leads to Cowling resistivities orders of magnitude larger than the Coulomb values, and thus to anisotropic dissipation in Ohm’s law. This also leads to localised low magnetic Reynolds numbers (R m < 1). We find that the rates of emergence of magnetic field are greatly increased by the partially ionised regions of the model atmosphere, and the resultant magnetic field is more diffuse. More importantly, the only currents associated with the magnetic field to emerge into the corona are aligned with the field, and thus the newly formed coronal field is force-free

Generative deep fields : arbitrarily sized, random synthetic astronomical images through deep learning

© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society.Generative Adversarial Networks (GANs) are a class of artificial neural network that can produce realistic, but artificial, images that resemble those in a training set. In typical GAN architectures these images are small, but a variant known as Spatial-GANs (SGANs) can generate arbitrarily large images, provided training images exhibit some level of periodicity. Deep extragalactic imaging surveys meet this criteria due to the cosmological tenet of isotropy. Here we train an SGAN to generate images resembling the iconic Hubble Space Telescope eXtreme Deep Field (XDF). We show that the properties of 'galaxies' in generated images have a high level of fidelity with galaxies in the real XDF in terms of abundance, morphology, magnitude distributions and colours. As a demonstration we have generated a 7.6-billion pixel 'generative deep field' spanning 1.45 degrees. The technique can be generalised to any appropriate imaging training set, offering a new purely data-driven approach for producing realistic mock surveys and synthetic data at scale, in astrophysics and beyond.Peer reviewe