276 research outputs found
Detection and Correction of Step Discontinuities in Kepler Flux Time Series
PDC 8.0 includes an implementation of a new algorithm to detect and correct step discontinuities appearing in roughly one of every 20 stellar light curves during a given quarter. The majority of such discontinuities are believed to result from high-energy particles (either cosmic or solar in origin) striking the photometer and causing permanent local changes (typically -0.5%) in quantum efficiency, though a partial exponential recovery is often observed [1]. Since these features, dubbed sudden pixel sensitivity dropouts (SPSDs), are uncorrelated across targets they cannot be properly accounted for by the current detrending algorithm. PDC detrending is based on the assumption that features in flux time series are due either to intrinsic stellar phenomena or to systematic errors and that systematics will exhibit measurable correlations across targets. SPSD events violate these assumptions and their successful removal not only rectifies the flux values of affected targets, but demonstrably improves the overall performance of PDC detrending [1]
Measurements with the Chandra X-Ray Observatory's flight contamination monitor
NASA's Chandra X-ray Observatory includes a Flight Contamination Monitor
(FCM), a system of 16 radioactive calibration sources mounted to the inside of
the Observatory's forward contamination cover. The purpose of the FCM is to
verify the ground-to-orbit transfer of the Chandra flux scale, through
comparison of data acquired during the ground calibration with those obtained
in orbit, immediately prior to opening the Observatory's sun-shade door. Here
we report results of these measurements, which place limits on the change in
mirror--detector system response and, hence, on any accumulation of molecular
contamination on the mirrors' iridium-coated surfaces.Comment: 7pages,8figures,for SPIE 4012, paper 7
Dynamic Black-Level Correction and Artifact Flagging in the Kepler Data Pipeline
Instrument-induced artifacts in the raw Kepler pixel data include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, manifestations of drifting moir pattern as locally correlated nonstationary noise and rolling bands in the images which find their way into the calibrated pixel time series and ultimately into the calibrated target flux time series. Using a combination of raw science pixel data, full frame images, reverse-clocked pixel data and ancillary temperature data the Keplerpipeline models and removes the FGS crosstalk artifacts by dynamically adjusting the black level correction. By examining the residuals to the model fits, the pipeline detects and flags spatial regions and time intervals of strong time-varying blacklevel (rolling bands ) on a per row per cadence basis. These flags are made available to downstream users of the data since the uncorrected rolling band artifacts could complicate processing or lead to misinterpretation of instrument behavior as stellar. This model fitting and artifact flagging is performed within the new stand-alone pipeline model called Dynablack. We discuss the implementation of Dynablack in the Kepler data pipeline and present results regarding the improvement in calibrated pixels and the expected improvement in cotrending performances as a result of including FGS corrections in the calibration. We also discuss the effectiveness of the rolling band flagging for downstream users and illustrate with some affected light curves
AXAF VETA-I mirror encircled energy measurements and data reduction
The AXAF VETA-I mirror encircled energy was measured with a series of apertures and two flow gas proportional counters at five X-ray energies ranging from 0.28 to 2.3 keV. The proportional counter has a thin plastic window with an opaque wire mesh supporting grid. Depending on the counter position, this mesh can cause the X-ray transmission to vary as much as +/-9 percent, which directly translates into an error in the encircled energy. In order to correct this wire mesh effect, window scan measurements were made, in which the counter was scanned in both horizontal (Y) and vertical (Z) directions with the aperture fixed. Post VETA measurement of the VXDS setup were made to determine the exact geometry and position of the mesh grid. Computer models of the window mesh were developed to simulate the X-ray transmission based on this measurement. The window scan data were fitted to such mesh models and corrections were made. After this study, the mesh effect was well understood and the final results of the encircled energy were obtained with an uncertainty of less than 0.8 percent
Properties of the Chandra Sources in M81
The Chandra X-ray Observatory obtained a 50-ks observation of the central
region of M81 using the ACIS-S in imaging mode. The global properties of the 97
x-ray sources detected in the inner 8.3x8.3 arcmin field of M81 are examined.
Roughly half the sources are concentrated within the central bulge. The
remainder are distributed throughout the disk with the brightest disk sources
lying preferentially along spiral arms. The average hardness ratios of both
bulge and disk sources are consistent with power law spectra of index Gamma~1.6
indicative of a population of x-ray binaries. A group of much softer sources
are also present. The background source-subtracted logN-logS distribution of
the disk follows a power law of index ~ -0.5 with no change in slope over three
decades in flux. The logN-logS distribution of the bulge follows a similar
shape but with a steeper slope above ~4.0e+37 ergs/s. There is unresolved x-ray
flux from the bulge with a radial profile similar to that of the bulge sources.
This unresolved flux is softer than the average of the bulge sources and
extrapolating the bulge logN-logS distribution towards weaker sources can only
account for 20% of the unresolved flux. No strong time variability was observed
for any source with the exception of one bright, soft source.Comment: 5 pages, 3 color PS figures, to appear in ApJ
Dynamic Black-Level Correction and Artifact Flagging for Kepler Pixel Time Series
Methods applied to the calibration stage of Kepler pipeline data processing [1] (CAL) do not currently use all of the information available to identify and correct several instrument-induced artifacts. These include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, and manifestations of drifting moire pattern as locally correlated nonstationary noise, and rolling bands in the images which find their way into the time series [2], [3]. As the Kepler Mission continues to improve the fidelity of its science data products, we are evaluating the benefits of adding pipeline steps to more completely model and dynamically correct the FGS crosstalk, then use the residuals from these model fits to detect and flag spatial regions and time intervals of strong time-varying black-level which may complicate later processing or lead to misinterpretation of instrument behavior as stellar activity
Characterization of the Inner Knot of the Crab: The Site of the Gamma-ray Flares?
One of the most intriguing results from the gamma-ray instruments in orbit
has been the detection of powerful flares from the Crab Nebula. These flares
challenge our understanding of pulsar wind nebulae and models for particle
acceleration. We report on the portion of a multiwavelength campaign using
Keck, HST, and Chandra concentrating on a small emitting region, the Crab's
inner knot, located a fraction of an arcsecond from the pulsar.
We find that the knot's radial size, tangential size, peak flux, and the
ratio of the flux to that of the pulsar are correlated with the projected
distance of the knot from the pulsar. A new approach, using singular value
decomposition for analyzing time series of images, was introduced yielding
results consistent with the more traditional methods while some uncertainties
were substantially reduced.
We exploit the characterization of the knot to discuss constraints on
standard shock-model parameters that may be inferred from our observations
assuming the inner knot lies near to the shocked surface. These include
inferences as to wind magnetization, shock shape parameters such as incident
angle and poloidal radius of curvature, as well as the IR/optical emitting
particle enthalpy fraction. We find that while the standard shock model gives
good agreement with observation in many respects, there remain two puzzles: (a)
The observed angular size of the knot relative to the pulsar--knot separation
is much smaller than expected; (b) The variable, yet high degree of
polarization reported is difficult to reconcile with a highly relativistic
downstream flow.Comment: 46 pages, 14 figures, submitted to the Astrophysical Journa
Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves
Kepler provides light curves of 156,000 stars with unprecedented precision.
However, the raw data as they come from the spacecraft contain significant
systematic and stochastic errors. These errors, which include discontinuities,
systematic trends, and outliers, obscure the astrophysical signals in the light
curves. To correct these errors is the task of the Presearch Data Conditioning
(PDC) module of the Kepler data analysis pipeline. The original version of PDC
in Kepler did not meet the extremely high performance requirements for the
detection of miniscule planet transits or highly accurate analysis of stellar
activity and rotation. One particular deficiency was that astrophysical
features were often removed as a side-effect to removal of errors. In this
paper we introduce the completely new and significantly improved version of PDC
which was implemented in Kepler SOC 8.0. This new PDC version, which utilizes a
Bayesian approach for removal of systematics, reliably corrects errors in the
light curves while at the same time preserving planet transits and other
astrophysically interesting signals. We describe the architecture and the
algorithms of this new PDC module, show typical errors encountered in Kepler
data, and illustrate the corrections using real light curve examples.Comment: Submitted to PASP. Also see companion paper "Kepler Presearch Data
Conditioning II - A Bayesian Approach to Systematic Error Correction" by Jeff
C. Smith et a
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