689 research outputs found
Risk and Business Goal Based Security Requirement and Countermeasure Prioritization
Companies are under pressure to be in control of their assets but at the same time they must operate as efficiently as possible. This means that they aim to implement âgood-enough securityâ but need to be able to justify their security investment plans. Currently companies achieve this by means of checklist-based security assessments, but these methods are a way to achieve consensus without being able to provide justifications of countermeasures in terms of business goals. But such justifications are needed to operate securely and effectively in networked businesses. In this paper, we first compare a Risk-Based Requirements Prioritization method (RiskREP) with some requirements engineering and risk assessment methods based on their requirements elicitation and prioritization properties. RiskREP extends misuse case-based requirements engineering methods with IT architecture-based risk assessment and countermeasure definition and prioritization. Then, we present how RiskREP prioritizes countermeasures by linking business goals to countermeasure specification. Prioritizing countermeasures based on business goals is especially important to provide the stakeholders with structured arguments for choosing a set of countermeasures to implement. We illustrate RiskREP and how it prioritizes the countermeasures it elicits by an application to an action case
Recovering the state sequence of hidden Markov models using mean-field approximations
Inferring the sequence of states from observations is one of the most
fundamental problems in Hidden Markov Models. In statistical physics language,
this problem is equivalent to computing the marginals of a one-dimensional
model with a random external field. While this task can be accomplished through
transfer matrix methods, it becomes quickly intractable when the underlying
state space is large.
This paper develops several low-complexity approximate algorithms to address
this inference problem when the state space becomes large. The new algorithms
are based on various mean-field approximations of the transfer matrix. Their
performances are studied in detail on a simple realistic model for DNA
pyrosequencing.Comment: 43 pages, 41 figure
Jeans that fit : weighing the mass of the Milky Way analogues in the ÎCDM universe
The spherical Jeans equation is a widely used tool for dynamical study of gravitating systems in astronomy. Here, we test its efficacy in robustly weighing the mass of Milky Way analogues, given they need not be in equilibrium or even spherical. Utilizing Milky Way stellar haloes simulated in accordance with Î cold dark matter (ÎCDM) cosmology by Bullock and Johnston and analysing them under the Jeans formalism, we recover the underlying mass distribution of the parent galaxy, within distance r/kpc â [10, 100], with a bias of ⌠12âperâcent and a dispersion of ⌠14âperâcent. Additionally, the mass profiles of triaxial dark matter haloes taken from the surfs simulation, within scaled radius 0.2 < r/rmax < 3, are measured with a bias of ⌠â 2.4âperâcent and a dispersion of ⌠10âperâcent. The obtained dispersion is not because of Poisson noise due to small particle numbers as it is twice the later. We interpret the dispersion to be due to the inherent nature of the ÎCDM haloes, for example being aspherical and out-of-equilibrium. Hence, the dispersion obtained for stellar haloes sets a limit of about 12âperâcent (after adjusting for random uncertainty) on the accuracy with which the mass profiles of the Milky Way-like galaxies can be reconstructed using the spherical Jeans equation. This limit is independent of the quantity and quality of the observational data. The reason for a non-zero bias is not clear, hence its interpretation is not obvious at this stage.Publisher PDFPeer reviewe
From Stellar Halos to Intracluster Light: the physics of the Intra-Halo Stellar Component in cosmological hydrodynamical simulations
We study the Intra-Halo Stellar Component (IHSC) of Milky Way-mass systems up
to galaxy clusters in the Horizon-AGN cosmological hydrodynamical simulation.
We identify the IHSC using an improved phase-space galaxy finder algorithm
which provides an adaptive, physically motivated and shape-independent
definition of this stellar component, that can be applied to halos of arbitrary
masses. We explore the IHSC mass fraction-total halo's stellar mass,
, relation and the physical drivers of its scatter. We find
that on average the increases with , with the scatter
decreasing strongly with mass from 2 dex at to
0.3 dex at group masses. At high masses, ,
increases with the number of substructures, and with the mass
ratio between the central galaxy and largest satellite, at fixed .
From mid-size groups and systems below , we find that
the central galaxy's stellar rotation-to-dispersion velocity ratio, V/{\sigma},
displays the strongest (anti)-correlation with at fixed
of all the galaxy and halo properties explored, transitioning from
<0.1% for high V/{\sigma}, to % for low
V/{\sigma} galaxies. By studying the temporal evolution, we find
that, in the former, mergers not always take place, but if they did, they
happened early (z>1), while the high population displays a much
more active merger history. In the case of massive groups and galaxy clusters,
, a fraction 10-20% is reached at
and then they evolve across lines of constant modulo
some small perturbations. Because of the limited simulation's volume, the
latter is only tentative and requires a larger sample of simulated galaxy
clusters to confirm.Comment: 21 pages, 17 figures. Submitted to MNRAS. Comments are welcome
Shark: introducing an open source, free and flexible semi-analytic model of galaxy formation
We present a new, open source, free semi-analytic model (SAM) of galaxy
formation, Shark, designed to be highly flexible and modular, allowing easy
exploration of different physical processes and ways of modelling them. We
introduce the philosophy behind Shark and provide an overview of the physical
processes included in the model. Shark is written in C++11 and has been
parallelized with OpenMP. In the released version (v1.1), we implement several
different models for gas cooling, active galactic nuclei, stellar and
photo-ionisation feedback, and star formation (SF). We demonstrate the basic
performance of Shark using the Planck15 cosmology SURFS simulations, by
comparing against a large set of observations, including: the stellar mass
function (SMF) and stellar-halo mass relation at z=0-4; the cosmic evolution of
the star formation rate density (SFRD), stellar mass, atomic and molecular
hydrogen; local gas scaling relations; and structural galaxy properties,
finding excellent agreement. Significant improvements over previous SAMs are
seen in the mass-size relation for disks/bulges, the gas-stellar mass and
stellar mass-metallicity relations. To illustrate the power of Shark in
exploring the systematic effects of the galaxy formation modelling, we quantify
how the scatter of the SF main sequence and the gas scaling relations changes
with the adopted SF law, and the effect of the starbursts H depletion
timescale on the SFRD and . We compare Shark with other SAMs
and the hydrodynamical simulation EAGLE, and find that SAMs have a much higher
halo baryon fractions due to large amounts of intra-halo gas, which in the case
of EAGLE is in the intergalactic medium.Comment: Final MNRAS version of accepted pape
Exploring Galaxy Formation Models and Cosmologies with Galaxy Clustering
Using N-body simulations and galaxy formation models, we study the galaxy
stellar mass correlation and the two-point auto-correlation. The simulations
are run with cosmological parameters from the WMAP first, third and seven year
results, which mainly differ in the perturbation amplitude of \sigma_{8}. The
stellar mass of galaxies are determined using either a semi-analytical galaxy
formation model or a simple empirical abundance matching method. Compared to
the SDSS DR7 data at z=0 and the DEEP2 results at z=1, we find that the
predicted galaxy clusterings from the semi-analytical model are higher than the
data at small scales, regardless of the adopted cosmology. Conversely, the
abundance matching method predicts good agreement with the data at both z=0 and
z=1 for high \sigma_8 cosmologies (WMAP1 & WMAP7), but the predictions from a
low \sigma_8 cosmology (WMAP3) are significantly lower than the data at z=0. We
find that the excess clustering at small-scales in the semi-analytical model
mainly arises from satellites in massive haloes, indicating that either the
star formation is too efficient in low-mass haloes or tidal stripping is too
inefficient at high redshift. Our results show that galaxy clustering is
strongly affected by the models for galaxy formation, thus can be used to
constrain the baryonic physics. The weak dependence of galaxy clustering on
cosmological parameters makes it difficult to constrain the WMAP1 and WMAP7
cosmologies.Comment: 8 pages, 7 figures. Accepted to MNRA
The detection of sub-solar mass dark matter halos
Dark matter halos of sub-solar mass are the first bound objects to form in
cold dark matter theories. In this article, I discuss the present understanding
of "microhalos'', their role in structure formation, and the implications of
their potential presence, in the interpretation of dark matter experiments.Comment: 18 pages, 7 figures. Invited contribution to NJP Focus Issue on "Dark
Matter and Particle Physics
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