2,324 research outputs found
Bayesian inference for inverse problems
Traditionally, the MaxEnt workshops start by a tutorial day. This paper
summarizes my talk during 2001'th workshop at John Hopkins University. The main
idea in this talk is to show how the Bayesian inference can naturally give us
all the necessary tools we need to solve real inverse problems: starting by
simple inversion where we assume to know exactly the forward model and all the
input model parameters up to more realistic advanced problems of myopic or
blind inversion where we may be uncertain about the forward model and we may
have noisy data. Starting by an introduction to inverse problems through a few
examples and explaining their ill posedness nature, I briefly presented the
main classical deterministic methods such as data matching and classical
regularization methods to show their limitations. I then presented the main
classical probabilistic methods based on likelihood, information theory and
maximum entropy and the Bayesian inference framework for such problems. I show
that the Bayesian framework, not only generalizes all these methods, but also
gives us natural tools, for example, for inferring the uncertainty of the
computed solutions, for the estimation of the hyperparameters or for handling
myopic or blind inversion problems. Finally, through a deconvolution problem
example, I presented a few state of the art methods based on Bayesian inference
particularly designed for some of the mass spectrometry data processing
problems.Comment: Presented at MaxEnt01. To appear in Bayesian Inference and Maximum
Entropy Methods, B. Fry (Ed.), AIP Proceedings. 20pages, 13 Postscript
figure
Weak gravitational lensing with DEIMOS
We introduce a novel method for weak-lensing measurements, which is based on
a mathematically exact deconvolution of the moments of the apparent brightness
distribution of galaxies from the telescope's PSF. No assumptions on the shape
of the galaxy or the PSF are made. The (de)convolution equations are exact for
unweighted moments only, while in practice a compact weight function needs to
be applied to the noisy images to ensure that the moment measurement yields
significant results. We employ a Gaussian weight function, whose centroid and
ellipticity are iteratively adjusted to match the corresponding quantities of
the source. The change of the moments caused by the application of the weight
function can then be corrected by considering higher-order weighted moments of
the same source. Because of the form of the deconvolution equations, even an
incomplete weighting correction leads to an excellent shear estimation if
galaxies and PSF are measured with a weight function of identical size. We
demonstrate the accuracy and capabilities of this new method in the context of
weak gravitational lensing measurements with a set of specialized tests and
show its competitive performance on the GREAT08 challenge data. A complete C++
implementation of the method can be requested from the authors.Comment: 7 pages, 3 figures, fixed typo in Eq. 1
Calibration Challenges for Future Radio Telescopes
Instruments for radio astronomical observations have come a long way. While
the first telescopes were based on very large dishes and 2-antenna
interferometers, current instruments consist of dozens of steerable dishes,
whereas future instruments will be even larger distributed sensor arrays with a
hierarchy of phased array elements. For such arrays to provide meaningful
output (images), accurate calibration is of critical importance. Calibration
must solve for the unknown antenna gains and phases, as well as the unknown
atmospheric and ionospheric disturbances. Future telescopes will have a large
number of elements and a large field of view. In this case the parameters are
strongly direction dependent, resulting in a large number of unknown parameters
even if appropriately constrained physical or phenomenological descriptions are
used. This makes calibration a daunting parameter estimation task, that is
reviewed from a signal processing perspective in this article.Comment: 12 pages, 7 figures, 20 subfigures The title quoted in the meta-data
is the title after release / final editing
Exploiting flow dynamics for super-resolution in contrast-enhanced ultrasound
Ultrasound localization microscopy offers new radiation-free diagnostic tools
for vascular imaging deep within the tissue. Sequential localization of echoes
returned from inert microbubbles with low-concentration within the bloodstream
reveal the vasculature with capillary resolution. Despite its high spatial
resolution, low microbubble concentrations dictate the acquisition of tens of
thousands of images, over the course of several seconds to tens of seconds, to
produce a single super-resolved image. %since each echo is required to be well
separated from adjacent microbubbles. Such long acquisition times and stringent
constraints on microbubble concentration are undesirable in many clinical
scenarios. To address these restrictions, sparsity-based approaches have
recently been developed. These methods reduce the total acquisition time
dramatically, while maintaining good spatial resolution in settings with
considerable microbubble overlap. %Yet, non of the reported methods exploit the
fact that microbubbles actually flow within the bloodstream. % to improve
recovery. Here, we further improve sparsity-based super-resolution ultrasound
imaging by exploiting the inherent flow of microbubbles and utilize their
motion kinematics. While doing so, we also provide quantitative measurements of
microbubble velocities. Our method relies on simultaneous tracking and
super-localization of individual microbubbles in a frame-by-frame manner, and
as such, may be suitable for real-time implementation. We demonstrate the
effectiveness of the proposed approach on both simulations and {\it in-vivo}
contrast enhanced human prostate scans, acquired with a clinically approved
scanner.Comment: 11 pages, 9 figure
The IPAC Image Subtraction and Discovery Pipeline for the intermediate Palomar Transient Factory
We describe the near real-time transient-source discovery engine for the
intermediate Palomar Transient Factory (iPTF), currently in operations at the
Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system
the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for
PSF-matching, image subtraction, detection, photometry, and machine-learned
(ML) vetting of extracted transient candidates. We also review the performance
of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively
unconfused regions, "bogus" candidates from processing artifacts and imperfect
image subtractions outnumber real transients by ~ 10:1. This can be
considerably higher for image data with inaccurate astrometric and/or
PSF-matching solutions. Despite this occasionally high contamination rate, the
ML classifier is able to identify real transients with an efficiency (or
completeness) of ~ 97% for a maximum tolerable false-positive rate of 1% when
classifying raw candidates. All subtraction-image metrics, source features, ML
probability-based real-bogus scores, contextual metadata from other surveys,
and possible associations with known Solar System objects are stored in a
relational database for retrieval by the various science working groups. We
review our efforts in mitigating false-positives and our experience in
optimizing the overall system in response to the multitude of science projects
underway with iPTF.Comment: 66 pages, 21 figures, 7 tables, accepted by PAS
KiDS-i-800: Comparing weak gravitational lensing measurements in same-sky surveys
We present a weak gravitational lensing analysis of 815 square degree of
-band imaging from the Kilo-Degree Survey (KiDS--800). In contrast to the
deep -band observations, which take priority during excellent seeing
conditions and form the primary KiDS dataset (KiDS--450), the complementary
yet shallower KiDS--800 spans a wide range of observing conditions. The
overlapping KiDS--800 and KiDS--450 imaging therefore provides a unique
opportunity to assess the robustness of weak lensing measurements. In our
analysis, we introduce two new `null' tests. The `nulled' two-point shear
correlation function uses a matched catalogue to show that the calibrated
KiDS--800 and KiDS--450 shear measurements agree at the level of \%. We use five galaxy lens samples to determine a `nulled' galaxy-galaxy
lensing signal from the full KiDS--800 and KiDS--450 surveys and find
that the measurements agree to \% when the KiDS--800 source
redshift distribution is calibrated using either spectroscopic redshifts, or
the 30-band photometric redshifts from the COSMOS survey.Comment: 24 pages, 20 figures. Submitted to MNRAS. Comments welcom
Improving PSF modelling for weak gravitational lensing using new methods in model selection
A simple theoretical framework for the description and interpretation of
spatially correlated modelling residuals is presented, and the resulting tools
are found to provide a useful aid to model selection in the context of weak
gravitational lensing. The description is focused upon the specific problem of
modelling the spatial variation of a telescope point spread function (PSF)
across the instrument field of view, a crucial stage in lensing data analysis,
but the technique may be used to rank competing models wherever data are
described empirically. As such it may, with further development, provide useful
extra information when used in combination with existing model selection
techniques such as the Akaike and Bayesian Information Criteria, or the
Bayesian evidence. Two independent diagnostic correlation functions are
described and the interpretation of these functions demonstrated using a
simulated PSF anisotropy field. The efficacy of these diagnostic functions as
an aid to the correct choice of empirical model is then demonstrated by
analyzing results for a suite of Monte Carlo simulations of random PSF fields
with varying degrees of spatial structure, and it is shown how the diagnostic
functions can be related to requirements for precision cosmic shear
measurement. The limitations of the technique, and opportunities for
improvements and applications to fields other than weak gravitational lensing,
are discussed.Comment: 18 pages, 12 figures. Modified to match version accepted for
publication in MNRA
Characterizing 51 Eri b from 1-5 m: a partly-cloudy exoplanet
We present spectro-photometry spanning 1-5 m of 51 Eridani b, a 2-10
M planet discovered by the Gemini Planet Imager Exoplanet Survey.
In this study, we present new (1.90-2.19 m) and (2.10-2.40
m) spectra taken with the Gemini Planet Imager as well as an updated
(3.76 m) and new (4.67 m) photometry from the NIRC2 Narrow
camera. The new data were combined with (1.13-1.35 m) and
(1.50-1.80 m) spectra from the discovery epoch with the goal of better
characterizing the planet properties. 51 Eri b photometry is redder than field
brown dwarfs as well as known young T-dwarfs with similar spectral type
(between T4-T8) and we propose that 51 Eri b might be in the process of
undergoing the transition from L-type to T-type. We used two complementary
atmosphere model grids including either deep iron/silicate clouds or
sulfide/salt clouds in the photosphere, spanning a range of cloud properties,
including fully cloudy, cloud free and patchy/intermediate opacity clouds.
Model fits suggest that 51 Eri b has an effective temperature ranging between
605-737 K, a solar metallicity, a surface gravity of (g) = 3.5-4.0 dex,
and the atmosphere requires a patchy cloud atmosphere to model the SED. From
the model atmospheres, we infer a luminosity for the planet of -5.83 to -5.93
(), leaving 51 Eri b in the unique position as being one of
the only directly imaged planet consistent with having formed via cold-start
scenario. Comparisons of the planet SED against warm-start models indicates
that the planet luminosity is best reproduced by a planet formed via core
accretion with a core mass between 15 and 127 M.Comment: 27 pages, 19 figures, Accepted for publication in The Astronomical
Journa
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