Simplified landscapes for optimization of shaken lattice interferometry

Motivated by recent results using shaken optical lattices to perform atom interferometry, we explore splitting of an atom cloud trapped in a phase-modulated ("shaken") optical lattice. Using a simple analytic model we are able to show that we can obtain the simplest case of $\pm2\hbar k_\mathrm{L}$ splitting via single-frequency shaking. This is confirmed both via simulation and experiment. Furthermore, we are able to split with a relative phase $\theta$ between the two split arms of $0$ or $\pi$ depending on our shaking frequency. Addressing higher-order splitting, we determine that $\pm6\hbar k_\mathrm{L}$ splitting is sufficient to be able to accelerate the atoms in counter-propagating lattices. Finally, we show that we can use a genetic algorithm to optimize $\pm4\hbar k_\mathrm{L}$ and $\pm6\hbar k_\mathrm{L}$ splitting to within $\approx0.1\%$ by restricting our optimization to the resonance frequencies corresponding to single- and two-photon transitions between Bloch bands

Star Formation in a Cosmological Simulation of Reionization

We study the luminosity functions of high-redshift galaxies in detailed hydrodynamic simulations of cosmic reionization, which are designed to reproduce the evolution of the Lyman-alpha forest between z=5 and z=6. We find that the luminosity functions and total stellar mass densities are in agreement with observations when plausible assumptions about reddenning at z=6 are made. Our simulations support the conclusion that stars alone reionized the universe.Comment: Accepted for publication in Ap

Flow establishment in a generic scramjet combustor

The establishment of a quasi-steady flow in a generic scramjet combustor was studied for the case of a time varying inflow to the combustor. Such transient flow is characteristic of the reflected shock tunnel and expansion tube test facilities. Several numerical simulations of hypervelocity flow through a straight duct combustor with either a side wall step fuel injector or a centrally located strut injector are presented. Comparisons were made between impulsively started but otherwise constant flow conditions (typical of the expansion tube or tailored operations of the reflected shock tunnel) and the relaxing flow produced by the 'undertailored' operations of the reflected shock tunnel. Generally the inviscid flow features, such as the shock pattern and pressure distribution, were unaffected by the time varying inlet conditions and approached steady state in approx. the times indicated by experimental correlations. However, viscous features, such as heat transfer and skin friction, were altered by the relaxing inlet flow conditions

Escaping stars from young low-N clusters

With the use of N-body calculations the amount and properties of escaping stars from low-N (N = 100 and 1000) young embedded star clusters prior to gas expulsion are studied over the first 5 Myr of their existence. Besides the number of stars also different initial radii and binary populations are examined as well as virialised and collapsing clusters. It is found that these clusters can loose substantial amounts (up to 20%) of stars within 5 Myr with considerable velocities up to more than 100 km/s. Even with their mean velocities between 2 and 8 km/s these stars will still be travelling between 2 and 30 pc during the 5 Myr. Therefore can large amounts of distributed stars in star-forming regions not necessarily be counted as evidence for the isolated formation of stars.Comment: 10 pages, 10 figures, accepted for publication by MNRA

Chemo-Archaeological Downsizing in a Hierarchical Universe: Impact of a Top Heavy IGIMF

We make use of a semi-analytical model of galaxy formation to investigate the origin of the observed correlation between [a/Fe] abundance ratios and stellar mass in elliptical galaxies. We implement a new galaxy-wide stellar initial mass function (Top Heavy Integrated Galaxy Initial Mass Function, TH-IGIMF) in the semi-analytic model SAG and evaluate its impact on the chemical evolution of galaxies. The SFR-dependence of the slope of the TH-IGIMF is found to be key to reproducing the correct [a/Fe]-stellar mass relation. Massive galaxies reach higher [a/Fe] abundance ratios because they are characterized by more top-heavy IMFs as a result of their higher SFR. As a consequence of our analysis, the value of the minimum embedded star cluster mass and of the slope of the embedded cluster mass function, which are free parameters involved in the TH-IGIMF theory, are found to be as low as 5 solar masses and 2, respectively. A mild downsizing trend is present for galaxies generated assuming either a universal IMF or a variable TH-IGIMF. We find that, regardless of galaxy mass, older galaxies (with formation redshifts > 2) are formed in shorter time-scales (< 2 Gyr), thus achieving larger [a/Fe] values. Hence, the time-scale of galaxy formation alone cannot explain the slope of the [a/Fe]-galaxy mass relation, but is responsible for the big dispersion of [a/Fe] abundance ratios at fixed stellar mass.We further test the hyphothesis of a TH-IGIMF in elliptical galaxies by looking into mass-to-light ratios, and luminosity functions. Models with a TH-IGIMF are also favoured by these constraints. In particular, mass-to-light ratios agree with observed values for massive galaxies while being overpredicted for less massive ones; this overprediction is present regardless of the IMF considered.Comment: 24 pages, 15 figures, 2 tables. (Comments most welcome). Summited to MNRA

Properties of hierarchically forming star clusters

We undertake a systematic analysis of the early (< 0.5 Myr) evolution of clustering and the stellar initial mass function in turbulent fragmentation simulations. These large scale simulations for the first time offer the opportunity for a statistical analysis of IMF variations and correlations between stellar properties and cluster richness. The typical evolutionary scenario involves star formation in small-n clusters which then progressively merge; the first stars to form are seeds of massive stars and achieve a headstart in mass acquisition. These massive seeds end up in the cores of clusters and a large fraction of new stars of lower mass is formed in the outer parts of the clusters. The resulting clusters are therefore mass segregated at an age of 0.5 Myr, although the signature of mass segregation is weakened during mergers. We find that the resulting IMF has a smaller exponent (alpha=1.8-2.2) than the Salpeter value (alpha=2.35). The IMFs in subclusters are truncated at masses only somewhat larger than the most massive stars (which depends on the richness of the cluster) and an universal upper mass limit of 150 Msun is ruled out. We also find that the simulations show signs of the IGIMF effect proposed by Weidner & Kroupa, where the frequency of massive stars is suppressed in the integrated IMF compared to the IMF in individual clusters. We identify clusters through the use of a minimum spanning tree algorithm which allows easy comparison between observational survey data and the predictions of turbulent fragmentation models. In particular we present quantitative predictions regarding properties such as cluster morphology, degree of mass segregation, upper slope of the IMF and the relation between cluster richness and maximum stellar mass. [abridged]Comment: 21 Pages, 25 Figure

Reinforcement Learning vs. Gradient-Based Optimisation for Robust Energy Landscape Control of Spin-1/2 Quantum Networks

We explore the use of policy gradient methods in reinforcement learning for quantum control via energy landscape shaping of XX-Heisenberg spin chains in a model agnostic fashion. Their performance is compared to finding controllers using gradient-based L-BFGS optimisation with restarts, with full access to an analytical model. Hamiltonian noise and coarse-graining of fidelity measurements are considered. Reinforcement learning is able to tackle challenging, noisy quantum control problems where L-BFGS optimization algorithms struggle to perform well. Robustness analysis under different levels of Hamiltonian noise indicates that controllers found by reinforcement learning appear to be less affected by noise than those found with L-BFGS.Comment: 7 pages, 7 figure