9,951 research outputs found
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
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 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 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 and N, 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 to S 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 to S is identified. A universal chemical
potential function, , 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 , 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 , which introduces a costly dependence on the Markov chain size
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 ,
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
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