1,499 research outputs found
The Aemulus Project III: Emulation of the Galaxy Correlation Function
Using the N-body simulations of the AEMULUS Project, we construct an emulator
for the non-linear clustering of galaxies in real and redshift space. We
construct our model of galaxy bias using the halo occupation framework,
accounting for possible velocity bias. The model includes 15 parameters,
including both cosmological and galaxy bias parameters. We demonstrate that our
emulator achieves ~ 1% precision at the scales of interest, 0.1<r<10 h^{-1}
Mpc, and recovers the true cosmology when tested against independent
simulations. Our primary parameters of interest are related to the growth rate
of structure, f, and its degenerate combination fsigma_8. Using this emulator,
we show that the constraining power on these parameters monotonically increases
as smaller scales are included in the analysis, all the way down to 0.1 h^{-1}
Mpc. For a BOSS-like survey, the constraints on fsigma_8 from r<30 h^{-1} Mpc
scales alone are more than a factor of two tighter than those from the fiducial
BOSS analysis of redshift-space clustering using perturbation theory at larger
scales. The combination of real- and redshift-space clustering allows us to
break the degeneracy between f and sigma_8, yielding a 9% constraint on f alone
for a BOSS-like analysis. The current AEMULUS simulations limit this model to
surveys of massive galaxies. Future simulations will allow this framework to be
extended to all galaxy target types, including emission-line galaxies.Comment: 14 pages, 8 figures, 1 table; submitted to ApJ; the project webpage
is available at https://aemulusproject.github.io ; typo in Figure 7 and
caption updated, results unchange
The Aemulus Project I: Numerical Simulations for Precision Cosmology
The rapidly growing statistical precision of galaxy surveys has lead to a
need for ever-more precise predictions of the observables used to constrain
cosmological and galaxy formation models. The primary avenue through which such
predictions will be obtained is suites of numerical simulations. These
simulations must span the relevant model parameter spaces, be large enough to
obtain the precision demanded by upcoming data, and be thoroughly validated in
order to ensure accuracy. In this paper we present one such suite of
simulations, forming the basis for the AEMULUS Project, a collaboration devoted
to precision emulation of galaxy survey observables. We have run a set of 75
(1.05 h^-1 Gpc)^3 simulations with mass resolution and force softening of
3.51\times 10^10 (Omega_m / 0.3) ~ h^-1 M_sun and 20 ~ h^-1 kpc respectively in
47 different wCDM cosmologies spanning the range of parameter space allowed by
the combination of recent Cosmic Microwave Background, Baryon Acoustic
Oscillation and Type Ia Supernovae results. We present convergence tests of
several observables including spherical overdensity halo mass functions, galaxy
projected correlation functions, galaxy clustering in redshift space, and
matter and halo correlation functions and power spectra. We show that these
statistics are converged to 1% (2%) for halos with more than 500 (200)
particles respectively and scales of r>200 ~ h^-1 kpc in real space or k ~ 3 h
Mpc^-1 in harmonic space for z\le 1. We find that the dominant source of
uncertainty comes from varying the particle loading of the simulations. This
leads to large systematic errors for statistics using halos with fewer than 200
particles and scales smaller than k ~ 4 h^-1 Mpc. We provide the halo catalogs
and snapshots detailed in this work to the community at
https://AemulusProject.github.io.Comment: 16 pages, 12 figures, 3 Tables Project website:
https://aemulusproject.github.io
The Aemulus Project II: Emulating the Halo Mass Function
Existing models for the dependence of the halo mass function on cosmological
parameters will become a limiting source of systematic uncertainty for cluster
cosmology in the near future. We present a halo mass function emulator and
demonstrate improved accuracy relative to state-of-the-art analytic models. In
this work, mass is defined using an overdensity criteria of 200 relative to the
mean background density. Our emulator is constructed from the AEMULUS
simulations, a suite of 40 N-body simulations with snapshots from z=3 to z=0.
These simulations cover the flat wCDM parameter space allowed by recent Cosmic
Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae
results, varying the parameters w, Omega_m, Omega_b, sigma_8, N_{eff}, n_s, and
H_0. We validate our emulator using five realizations of seven different
cosmologies, for a total of 35 test simulations. These test simulations were
not used in constructing the emulator, and were run with fully independent
initial conditions. We use our test simulations to characterize the modeling
uncertainty of the emulator, and introduce a novel way of marginalizing over
the associated systematic uncertainty. We confirm non-universality in our halo
mass function emulator as a function of both cosmological parameters and
redshift. Our emulator achieves better than 1% precision over much of the
relevant parameter space, and we demonstrate that the systematic uncertainty in
our emulator will remain a negligible source of error for cluster abundance
studies through at least the LSST Year 1 data set.Comment: https://aemulusproject.github.io
Physics-Based Modeling for Determining Transient Current Flow in Multi-Layer Pcb Pi Designs
A physics-based modeling methodology for determining the transient current flow path in multi-layer PI designs is given in this paper using a commercial board with a complicated structure as an example. Board structure analysis is done first to provide a physical basis of post-layout analytical and equivalent circuit modeling. A match of the PDN impedance between commercial tool simulation, post-layout analytical calculation, and the physics-based equivalent circuit modeling was achieved to support the model for the transient simulation. By analyzing the current response in all the vias, a clear representation of transient current flow across all via segments can be given layer-by-layer. The maximum current density in vertical vias can also be extracted in this process, providing a reference for preventing transient overcurrent design
Testing metallicity indicators at z~1.4 with the gravitationally lensed galaxy CASSOWARY 20
We present X-shooter observations of CASSOWARY 20 (CSWA 20), a star-forming
(SFR ~6 Msol/yr) galaxy at z=1.433, magnified by a factor of 11.5 by the
gravitational lensing produced by a massive foreground galaxy at z=0.741. We
analysed the integrated physical properties of the HII regions of CSWA 20 using
temperature- and density-sensitive emission lines. We find the abundance of
oxygen to be ~1/7 of solar, while carbon is ~50 times less abundant than in the
Sun. The unusually low C/O ratio may be an indication of a particularly rapid
timescale of chemical enrichment. The wide wavelength coverage of X-shooter
gives us access to five different methods for determining the metallicity of
CSWA 20, three based on emission lines from HII regions and two on absorption
features formed in the atmospheres of massive stars. All five estimates are in
agreement, within the factor of ~2 uncertainty of each method. The interstellar
medium of CSWA 20 only partially covers the star-forming region as viewed from
our direction; in particular, absorption lines from neutrals and first ions are
exceptionally weak. We find evidence for large-scale outflows of the
interstellar medium (ISM) with speeds of up 750 km/s, similar to the values
measured in other high-z galaxies sustaining much higher rates of star
formation.Comment: 18 pages, 11 figures, accepted for publication in MNRA
Feature Guided Training and Rotational Standardisation for the Morphological Classification of Radio Galaxies
State-of-the-art radio observatories produce large amounts of data which can
be used to study the properties of radio galaxies. However, with this rapid
increase in data volume, it has become unrealistic to manually process all of
the incoming data, which in turn led to the development of automated approaches
for data processing tasks, such as morphological classification. Deep learning
plays a crucial role in this automation process and it has been shown that
convolutional neural networks (CNNs) can deliver good performance in the
morphological classification of radio galaxies. This paper investigates two
adaptations to the application of these CNNs for radio galaxy classification.
The first adaptation consists of using principal component analysis (PCA)
during preprocessing to align the galaxies' principal components with the axes
of the coordinate system, which will normalize the orientation of the galaxies.
This adaptation led to a significant improvement in the classification accuracy
of the CNNs and decreased the average time required to train the models. The
second adaptation consists of guiding the CNN to look for specific features
within the samples in an attempt to utilize domain knowledge to improve the
training process. It was found that this adaptation generally leads to a
stabler training process and in certain instances reduced overfitting within
the network, as well as the number of epochs required for training.Comment: 20 pages, 17 figures, this is a pre-copyedited, author-produced PDF
of an article accepted for publication in the Monthly Notices of the Royal
Astronomical Societ
After Implementation of the ACA – Coverage Gaps among Rural Latinos Still Remain
In this study, we assessed health needs and insurance coverage among a rural Latino population. A health needs survey was conducted in 2015 with approximately 100 Latino residents living in a rural Florida county. The survey included questions on socio-economic characteristics, type of insurance coverage, lapses in coverage, delays in care and satisfaction with health services. Only 15% of respondents had insurance through their employer, and 11% had Medicaid. Over 45% of participants had no health insurance, and 20% had no insurance for more than three years. One in ten had a medication delay due to lack of coverage/money, and 17% expressed they had medical bills they were paying off. Gaps in coverage highlight the need for targeted outreach efforts, while gaps in access and affordability highlight the need for new strategies to address barriers to care and out of pocket expenses for those with health insurance
Pain Management for Primary Care Providers: A Narrative Review of High-Impact Studies, 2014-2016
Objective:
This manuscript reviews high-impact, peer-reviewed studies published from January 2014 to March 2016 that are relevant to pain management in primary care. Given the recent release of the US Centers for Disease Control and Prevention's "Guideline for Prescribing Opioids for Chronic Pain" emphasizing the primacy of nonopioid treatment, we focused our review on nonopioid pain management.
Design:
Narrative review of peer-reviewed literature.
Methods:
We searched three article summary services and queried expert contacts for high-impact, English-language studies related to the management of pain in adults in primary care. All authors reviewed 142 study titles to arrive at group consensus on article content domains. Within article domains, individual authors selected studies approved by the larger group according to their impact on primary care clinical practice, policy, and research, as well as quality of the study methods. Through iterative discussion, 12 articles were selected for detailed review, discussion, and presentation in this narrative review.
Results:
We present key articles addressing each of six domains of pain management: pharmacotherapy for acute pain; interventional treatments; medical cannabis; complementary and integrative medicine; care management in chronic pain; and prevention. Within each section, we conclude with implications for pain management in primary care.
Conclusions:
There is growing evidence for multiple nonopioid treatment modalities available to clinicians for the management of pain in primary care. The dissemination and implementation of these studies, including innovative care management interventions, warrant additional study and support from clinicians, educators, and policy-makers
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