Unbiased clustering estimation in the presence of missing observations

In order to be efficient, spectroscopic galaxy redshift surveys do not obtain redshifts for all galaxies in the population targeted. The missing galaxies are often clustered, commonly leading to a lower proportion of successful observations in dense regions. One example is the close-pair issue for SDSS spectroscopic galaxy surveys, which have a deficit of pairs of observed galaxies with angular separation closer than the hardware limit on placing neighbouring fibers. Spatially clustered missing observations will exist in the next generations of surveys. Various schemes have previously been suggested to mitigate these effects, but none works for all situations. We argue that the solution is to link the missing galaxies to those observed with statistically equivalent clustering properties, and that the best way to do this is to rerun the targeting algorithm, varying the angular position of the observations. Provided that every pair has a non-zero probability of being observed in one realisation of the algorithm, then a pair-upweighting scheme linking targets to successful observations, can correct these issues. We present such a scheme, and demonstrate its validity using realisations of an idealised simple survey strategy.Comment: 14 pages, 8 figures, published in MNRA

Are stellar-mass black-hole binaries too quiet for LISA?

The progenitors of the high-mass black-hole mergers observed by LIGO and Virgo are potential LISA sources and promising candidates for multiband GW observations. In this letter, we consider the minimum signal-to-noise ratio these sources must have to be detected by LISA. Our revised threshold of $\rho_{\rm thr}\sim 15$ is higher than previous estimates, which significantly reduces the expected number of events. We also point out the importance of the detector performance at high-frequencies and the duration of the LISA mission, which both influence the event rate substantially.Comment: 6 pages, 3 figures. Published in MNRAS letters. DOI 10.1093/mnrasl/slz10

Improving the modelling of redshift-space distortions - II. A pairwise velocity model covering large and small scales

We develop a model for the redshift-space correlation function, valid for both dark matter particles and halos on scales $>5\,h^{-1}$Mpc. In its simplest formulation, the model requires the knowledge of the first three moments of the line-of-sight pairwise velocity distribution plus two well-defined dimensionless parameters. The model is obtained by extending the Gaussian-Gaussianity prescription for the velocity distribution, developed in a previous paper, to a more general concept allowing for local skewness, which is required to match simulations. We compare the model with the well known Gaussian streaming model and the more recent Edgeworth streaming model. Using N-body simulations as a reference, we show that our model gives a precise description of the redshift-space clustering over a wider range of scales. We do not discuss the theoretical prescription for the evaluation of the velocity moments, leaving this topic to further investigation.Comment: 18 pages, 10 figures, published in MNRA

A universal chemical potential for sulfur vapours

The unusual chemistry of sulfur is illustrated by the tendency for catenation. Sulfur forms a range of open and closed S$_n$ species in the gas phase, which has led to speculation on the composition of sulfur vapours as a function of temperature and pressure for over a century. Unlike elemental gases such as O$_2$ and N$_2$, there is no widely accepted thermodynamic potential for sulfur. Here we combine a first-principles global structure search for the low energy clusters from S$_2$ to S$_8$ with a thermodynamic model for the mixed-allotrope system, including the Gibbs free energy for all gas-phase sulfur on an atomic basis. A strongly pressure-dependent transition from a mixture dominant in S$_2$ to S$_8$ is identified. A universal chemical potential function, $\mu_{\mathrm{S}}(T,P)$, is proposed with wide utility in modelling sulfurisation processes including the formation of metal chalcogenide semiconductors.Comment: 12 pages, 9 figures. Supporting code and data is available at https://github.com/WMD-Bath/sulfur-model [snapshot DOI: 10.5281/zenodo.28536]. Further data will be available from DOI:10.6084/m9.figshare.1513736 and DOI:10.6084/m9.figshare.1513833 following peer-revie

Faster quantum mixing for slowly evolving sequences of Markov chains

Markov chain methods are remarkably successful in computational physics, machine learning, and combinatorial optimization. The cost of such methods often reduces to the mixing time, i.e., the time required to reach the steady state of the Markov chain, which scales as $\delta^{-1}$, the inverse of the spectral gap. It has long been conjectured that quantum computers offer nearly generic quadratic improvements for mixing problems. However, except in special cases, quantum algorithms achieve a run-time of $\mathcal{O}(\sqrt{\delta^{-1}} \sqrt{N})$, which introduces a costly dependence on the Markov chain size $N,$ not present in the classical case. Here, we re-address the problem of mixing of Markov chains when these form a slowly evolving sequence. This setting is akin to the simulated annealing setting and is commonly encountered in physics, material sciences and machine learning. We provide a quantum memory-efficient algorithm with a run-time of $\mathcal{O}(\sqrt{\delta^{-1}} \sqrt[4]{N})$, neglecting logarithmic terms, which is an important improvement for large state spaces. Moreover, our algorithms output quantum encodings of distributions, which has advantages over classical outputs. Finally, we discuss the run-time bounds of mixing algorithms and show that, under certain assumptions, our algorithms are optimal.Comment: 20 pages, 2 figure

Numerical Simulations of Gamma-Ray Burst Explosions

Gamma-ray bursts are a complex, non-linear system that evolves very rapidly through stages of vastly different conditions. They evolve from scales of few hundred kilometers where they are very dense and hot to cold and tenuous on scales of parsecs. As such, our understanding of such a phenomenon can truly increase by combining theoretical and numerical studies adopting different numerical techniques to face different problems and deal with diverse conditions. In this review, we will describe the tremendous advancement in our comprehension of the bursts phenomenology through numerical modeling. Though we will discuss studies mainly based on jet dynamics across the progenitor star and the interstellar medium, we will also touch upon other problems such as the jet launching, its acceleration, and the radiation mechanisms. Finally, we will describe how combining numerical results with observations from Swift and other instruments resulted in true understanding of the bursts phenomenon and the challenges still lying ahead.Comment: 14 Pages, Journal of High Energy Astrophysics for the dedicated issue: "Swift: Ten Years of Discovery", in pres