Search NASA⌕ Search

SEARCH · Search NASA

Results for “Systematic Error”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Systematic study of error sources in supersonic skin-friction balance measurements

An experimental study was performed to investigate potential error sources in data obtained with a self-nulling, moment-measuring, skin-friction balance. The balance was installed in the sidewall of a supersonic wind tunnel, and independent measurements of the three forces contributing to the balance output (skin friction, lip force, and off-center normal force) were made for a range of gap size and element protrusion. The relatively good agreement between the balance data and the sum of these three independently measured forces validated the three-term model used. No advantage to a small gap size was found; in fact, the larger gaps were preferable. Perfect element alignment with the surrounding test surface resulted in very small balance errors. However, if small protrusion errors are unavoidable, no advantage was found in having the element slightly below the surrounding test surface rather than above it.

Allen, J. M.↗
NASA NTRS1987

New dimension analyses with error analysis for quaking aspen and black spruce

Dimension analysis for black spruce in wetland stands and trembling aspen are reported, including new approaches in error analysis. Biomass estimates for sacrificed trees have standard errors of 1 to 3%; standard errors for leaf areas are 10 to 20%. Bole biomass estimation accounts for most of the error for biomass, while estimation of branch characteristics and area/weight ratios accounts for the leaf area error. Error analysis provides insight for cost effective design of future analyses. Predictive equations for biomass and leaf area, with empirically derived estimators of prediction error, are given. Systematic prediction errors for small aspen trees and for leaf area of spruce from different site-types suggest a need for different predictive models within species. Predictive equations are compared with published equations; significant differences may be due to species responses to regional or site differences. Proportional contributions of component biomass in aspen change in ways related to tree size and stand development. Spruce maintains comparatively constant proportions with size, but shows changes corresponding to site. This suggests greater morphological plasticity of aspen and significance for spruce of nutrient conditions.

Woods, K. D.↗
NASA NTRS1990

Note on apparent systematic and periodic errors in Geosat orbits

Apparent errors in Geosat orbits are estimated directly from the measurements. There are technical difficulties in such estimates from quasi-periodically gapped data. The dominant orbit errors display a line spectrum, in which the once/orbit error peak is split in a complex way into a series of narrow lines, with other errors being present as well. The spatial pattern of the errors is not random, displaying differences between mean ascending and descending orbits which are coherent over thousands of kilometers. Orbit errors do not decorrelate within a few orbit periods.

Sirkes, Ziv↗
DOE OSTI2013

Interfractional Position Variation of Pancreatic Tumors Quantified Using Intratumoral Fiducial Markers and Daily Cone Beam Computed Tomography

Purpose: The aim of this study was to quantify interfractional pancreatic position variation using fiducial markers visible on daily cone beam computed tomography (CBCT) scans. In addition, we analyzed possible migration of the markers to investigate their suitability for tumor localization. Methods and Materials: For 13 pancreatic cancer patients with implanted Visicoil markers, CBCT scans were obtained before 17 to 25 fractions (300 CBCTs in total). Image registration with the reference CT was used to determine the displacement of the 2 to 3 markers relative to bony anatomy and to each other. We analyzed the distance between marker pairs as a function of time to identify marker registration error (SD of linear fit residuals) and possible marker migration. For each patient, we determined the mean displacement of markers relative to the reference CT (systematic position error) and the spread in displacements (random position error). From this, we calculated the group systematic error, Σ, and group random error, σ. Results: Marker pair distances showed slight trends with time (range, −0.14 to 0.14 mm/day), possibly due to tissue deformation, but no shifts that would indicate marker migration. The mean SD of the fit residuals was 0.8 mm. We found large interfractional position variations, with for 116 of 300 (39%) fractions a 3-dimensional vector displacement of >10 mm. The spread in displacement varied significantly (P<.01) between patients, from a vector range of 9.1 mm to one of 24.6 mm. For the patient group, Σ was 3.8, 6.6, and 3.5 mm; and σ was 3.6, 4.7 and 2.5 mm, in left–right, superior–inferior, and anterior–posterior directions, respectively. Conclusions: We found large systematic displacements of the fiducial markers relative to bony anatomy, in addition to wide distributions of displacement. These results for interfractional position variation confirm the potential benefit of using fiducial markers rather than bony anatomy for daily online position verification for pancreatic cancer patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Probing gravity with a joint analysis of galaxy and CMB lensing and SDSS spectroscopy

We present measurements of EG, a probe of gravity from large-scale structure, using BOSS LOWZ and CMASS spectroscopic samples, with lensing measurements from SDSS (galaxy lensing) and Planck (CMB lensing). Using SDSS lensing and the BOSS LOWZ sample, we measure &#x27E8; E G &#x27E9; = 0.40 &#x2212;<!-- - --> 0.04 + 0.05 (stat), ±0.026 (systematic), consistent with the predicted value from the Planck ΛCDM model, EG=0.46. Using CMB lensing, we measure &#x27E8; E G &#x27E9; = 0.46 &#x2212;<!-- - --> 0.09 + 0.08 (stat) for LOWZ (statistically consistent with galaxy lensing and Planck predictions) and &#x27E8; E G &#x27E9; = 0.39 &#x2212;<!-- - --> 0.05 + 0.05 (stat) for the CMASS sample, consistent with the Planck prediction of E G =0.40 given the higher redshift of the sample. We also study the redshift evolution of E G by splitting the LOWZ sample into two samples based on redshift, with results being consistent with model predictions. We estimate systematic uncertainties on the above $\langle$E G $\rangle$ numbers to be ~6% (when using galaxy-galaxy lensing) or ~3% (when using CMB lensing), subdominant to the quoted statistical errors. These systematic error budgets are dominated by observational systematics in galaxy-galaxy lensing and by theoretical modeling uncertainties, respectively. We do not estimate observational systematics in galaxy-CMB lensing cros-correlations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-E-T-613: Dosimetric Consequences of Systematic MLC Leaf Positioning Errors

Purpose: The purpose of this study is to determine the dosimetric consequences of systematic MLC leaf positioning errors for clinical IMRT patient plans so as to establish detection tolerances for quality assurance programs. Materials and Methods: Dosimetric consequences were simulated by extracting mlc delivery instructions from the TPS, altering the file by the specified error, reloading the delivery instructions into the TPS, recomputing dose, and extracting dose-volume metrics for one head-andneck and one prostate patient. Machine error was simulated by offsetting MLC leaves in Pinnacle in a systematic way. Three different algorithms were followed for these systematic offsets, and are as follows: a systematic sequential one-leaf offset (one leaf offset in one segment per beam), a systematic uniform one-leaf offset (same one leaf offset per segment per beam) and a systematic offset of a given number of leaves picked uniformly at random from a given number of segments (5 out of 10 total). Dose to the PTV and normal tissue was simulated. Results: A systematic 5 mm offset of 1 leaf for all delivery segments of all beams resulted in a maximum PTV D98 deviation of 1%. Results showed very low dose error in all reasonably possible machine configurations, rare or otherwise, which could be simulated. Very low error in dose to PTV and OARs was shown in all possible cases of one leaf per beam per segment being offset (<1%), or that of only one leaf per beam being offset (<.2%). The errors resulting from a high number of adjacent leaves (maximum of 5 out of 60 total leaf-pairs) being simultaneously offset in many (5) of the control points (total 10–18 in all beams) per beam, in both the PTV and the OARs analyzed, were similarly low (<2–3%). Conclusions: The above results show that patient shifts and anatomical changes are the main source of errors in dose delivered, not machine delivery. These two sources of error are “visually complementary” and uncorrelated (albeit not additive in the final error) and one can easily incorporate error resulting from machine delivery in an error model based purely on tumor motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Exploring Milkyway Halo Substructures with Large-Area Sky Surveys

Over the last two decades, our understanding of the Milky Way has been improved thanks to large data sets arising from large-area digital sky surveys. The stellar halo is now known to be inhabited by a variety of spatial and kinematic stellar substructures, including stellar streams and stellar clouds, all of which are predicted by hierarchical Lambda Cold Dark Matter models of galaxy formation. In this dissertation, we first present the analysis of spectroscopic observations of individual stars from the two candidate structures discovered using an M-giant catalog from the Two Micron All-Sky Survey. The follow-up observations show that one of the candidates is a genuine structure which might be associated with the Galactic Anticenter Stellar Structure, while the other one is a false detection due to the systematic photometric errors in the survey or dust extinction in low Galactic latitudes. We then presented the discovery of an excess of main sequence turn-off stars in the direction of the constellations of Eridanus and Phoenix from the first-year data of the Dark Energy Survey (DES) – a five-year, 5,000 deg2 optical imaging survey in the Southern Hemisphere. The Eridanus-Phoenix (EriPhe) overdensity is centered around l ~ 285° and b ~ -60° and the Poisson significance of the detection is at least 9σ. The EriPhe overdensity has a cloud-like morphology and the extent is at least ~ 4 kpc by ~ 3 kpc in projection, with a heliocentric distance of about d ~ 16 kpc. The EriPhe overdensity is morphologically similar to the previously-discovered Virgo overdensity and Hercules-Aquila cloud. These three overdensities lie along a polar plane separated by ~ 120° and may share a common origin. In addition to the scientific discoveries, we also present the work to improve the photometric calibration in DES using auxiliary calibration systems, since the photometric errors can cause false detection in first the halo substructure. We present a detailed description of the two auxiliary calibration systems built at Texas A&M University. We then discuss how the auxiliary systems in DES can be used to improve the photometric calibration of the systematic chromatic errors – source color-dependent systematic errors that are caused by variations in the wavelength dependence of the atmospheric transmission and the instrumental throughput.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Absolute beam emittance measurements at RHIC using ionization profile monitors

In the past, comparisons between emittance measurements obtained using ionization profile monitors, Vernier scans (using as input the measured rates from the zero degree counters, or ZDCs), the polarimeters and the Schottky detectors evidenced significant variations of up to 100%. In this report we present studies of the RHIC ionization profile monitors (IPMs). After identifying and correcting for two systematic instrumental errors in the beam size measurements, we present experimental results showing that the remaining dominant error in beam emittance measurements at RHIC using the IPMs was imprecise knowledge of the local beta functions. After removal of the systematic errors and implementation of measured beta functions, precise emittance measurements result. Also, consistency between the emittances measured by the IPMs and those derived from the ZDCs was demonstrated.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

SU-F-J-47: Inherent Uncertainty in the Positional Shifts Determined by a Volumetric Cone Beam Imaging System

Purpose: To quantify inherent uncertainty associated with a volumetric imaging system in its determination of positional shifts. Methods: The study was performed on an Elekta Axesse™ linac’s XVI cone beam computed tomography (CBCT) system. A CT image data set of a Penta- Guide phantom was used as reference image by placing isocenter at the center of the phantom.The phantom was placed arbitrarily on the couch close to isocenter and CBCT images were obtained. The CBCT dataset was matched with the reference image using XVI software and the shifts were determined in 6-dimensions. Without moving the phantom, this process was repeated 20 times consecutively within 30 minutes on a single day. Mean shifts and their standard deviations in all 6-dimensions were determined for all the 20 instances of imaging. For any given day, the first set of shifts obtained was kept as reference and the deviations of the subsequent 19 sets from the reference set were scored. Mean differences and their standard deviations were determined. In this way, data were obtained for 30 consecutive working days. Results: Tabulating the mean deviations and their standard deviations observed on each day for the 30 measurement days, systematic and random errors in the determination of shifts by XVI software were calculated. The systematic errors were found to be 0.03, 0.04 and 0.03 mm while random errors were 0.05, 0.06 and 0.06 mm in lateral, craniocaudal and anterio-posterior directions respectively. For rotational shifts, the systematic errors were 0.02°, 0.03° and 0.03° and random errors were 0.06°, 0.05° and 0.05° in pitch, roll and yaw directions respectively. Conclusion: The inherent uncertainties in every image guidance system should be assessed and baseline values established at the time of its commissioning. These shall be periodically tested as part of the QA protocol.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-F-BRD-07: Empirical Derivation of Site-Specific Margin Formulas

Purpose: To empirically derive margin formulas from existing clinical radiotherapy plans accounting for respiratory motion and setup uncertainties. Methods: We simulated realistic treatment scenarios, including respiratory motion and setup errors. Individual probability density functions (PDF) from respiratory data were used to simulate respiratory motion. Random (σ) and systematic (Σ) setup errors were modeled as Gaussian distributions. One-dimensional dose profiles were extracted from existing radiotherapy plans and convolved with respiratory PDFs and random error distributions to produce blurred dose profiles. Each blurred dose profile was then shifted 1000 times by randomly sampling the simulated systematic error distribution. Margins were determined from the distance between the simulated treatment and the original 95% isodose level. An equation was fit for each (σ, Σ) combination to derive margin formulas for 90% of the population receiving 95% dose. This methodology can be applied to different tumor sites. Here, dose profiles were extracted from partial breast 3DCRT plans in the anterior-posterior (AP) and superior-inferior (SI) directions. Respiratory motion data was from healthy volunteers, and a clinically relevant range of random and systematic setup errors (standard deviations 1 – 4 mm) was determined from the literature. Results: The PBI margin formulas in the AP and SI directions for 95% dose coverage for 90% of the population were very similar: M= 0.68σ + 1.54Σ and M= 0.72σ + 1.50Σ, respectively. Systematic setup errors had the largest influence on required margin size, whereas realistic respiratory amplitude had minimal impact. The derived formulas resulted in a smaller systematic component than commonly-used theoretical margin recipes. Conclusion: We have demonstrated a method to derive empirical margin formulas from existing patient radiotherapy plans, incorporating realistic respiratory motion and appropriate ranges of random and systematic error. Site-specific margin formulas may be better suited to patient populations than theoretically derived, ideal geometry general margin formulas.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-CAMPUS-J-05: Quantitative Investigation of Random and Systematic Uncertainties From Hardware and Software Components in the Frameless 6DBrainLAB ExacTrac System

Purpose: To evaluate setup accuracy and quantify individual systematic and random errors for the various hardware and software components of the frameless 6D-BrainLAB ExacTrac system. Methods: 35 patients with cranial lesions, some with multiple isocenters (50 total lesions treated in 1, 3, 5 fractions), were investigated. All patients were simulated with a rigid head-and-neck mask and the BrainLAB localizer. CT images were transferred to the IPLAN treatment planning system where optimized plans were generated using stereotactic reference frame based on the localizer. The patients were setup initially with infrared (IR) positioning ExacTrac system. Stereoscopic X-ray images (XC: X-ray Correction) were registered to their corresponding digitally-reconstructed-radiographs, based on bony anatomy matching, to calculate 6D-translational and rotational (Lateral, Longitudinal, Vertical, Pitch, Roll, Yaw) shifts. XC combines systematic errors of the mask, localizer, image registration, frame, and IR. If shifts were below tolerance (0.7 mm translational and 1 degree rotational), treatment was initiated; otherwise corrections were applied and additional X-rays were acquired to verify patient position (XV: X-ray Verification). Statistical analysis was used to extract systematic and random errors of the different components of the 6D-ExacTrac system and evaluate the cumulative setup accuracy. Results: Mask systematic errors (translational; rotational) were the largest and varied from one patient to another in the range (−15 to 4mm; −2.5 to 2.5degree) obtained from mean of XC for each patient. Setup uncertainty in IR positioning (0.97,2.47,1.62mm;0.65,0.84,0.96degree) was extracted from standard-deviation of XC. Combined systematic errors of the frame and localizer (0.32,−0.42,−1.21mm; −0.27,0.34,0.26degree) was extracted from mean of means of XC distributions. Final patient setup uncertainty was obtained from the standard deviations of XV (0.57,0.77,0.67mm,0.39,0.35,0.30degree). Conclusion: Statistical analysis was used to calculate cumulative and individual systematic errors from the different hardware and software components of the 6D-ExacTrac-system. Patients were treated with cumulative errors (<1mm,<1degree) with XV image guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Automated Quantitative Analysis of Extended Irradiation Defects - Dislocations, Voids and Precipitates in Neutron Irradiated HT-9 Steel

Structural alloys that make up the core components of nuclear reactors are exposed to radiation that can substantially alter the microstructure and mechanical properties of the material. Irradiation can cause the formation of extended defects including dislocation line and loops, voids and various types of precipitates. To understand the irradiation effects, it is critical to characterize these defects individually and collectively to quantify how they evolve throughout irradiation stages. Transmission electron microscopy (TEM) is a standard tool for providing extensive size, number density and spatial distribution of extended irradiation defects, however, manual measurement of defect size and number density requires time-intensive effort to analyze enough defects that provide a statistically meaningful result and are prone to errors of subjectivity. In this work, we developed a set of MATLAB algorithms offering robust and automated identification and quantification of extended irradiation defects like dislocation lines, voids and precipitates commonly observed in neutron irradiated cladding alloys [1]. Using a neutron-irradiated HT-9 martensitic alloy irradiated at 412°C to 111.8 dpa, we demonstrate the capability of these algorithms for quantitative defect analysis. Figure 1 presents defect images of the HT-9 using an advanced diffraction contrast imaging scanning transmission electron microscopy (DCI STEM) that suppresses bend contours and provides better defect contrast compared to conventional TEM [2]. The first step of defect analysis is defect identification, a process that can be digitally achieved by contrast thresholding (for simple defect contrast) and by machine learning computer vision for defect semantic segmentation [3]. Here, labeled binary defect images (Figures 2a and 2c) were used. For dislocation density quantification, we employed an optimized circular-grid intersection method first introduced by Dr. John Steeds [4]. This method is shown in Figures 2a and 2b, where the number of intersections of dislocation lines with circular traces was measured. This produces an unbiased sampling of dislocation lines, regardless of their orientation. This process was optimized with automated digital intersection number and grid length registration. Interestingly, it was found that a relatively large number of circles in a set circular gird is was needed to produce an invariant result (Figure 2b), with a low systematic measurement error. This demonstrates the main advantage of computer-based defect analysis, in performing repetitive operations quickly with a reduced systematic error. For the quantitative analysis of voids and precipitates a challenge encountered with automated defect analysis is feature overlap, particularly when the density of voids/precipitates is high. To mitigate this problem, as shown in Figure 2d, we modified the popular circular Hough transformation and treated ‘circular shape’ as the particle descriptor for voids/precipitates, efficiently resolving the overlapping particles. In summary, this automated digital quantification together with machine learning enabled defect identification [3] opens new opportunities for standardizing the characterization workflow for quantitative analysis of extended irradiation defects.

Sainju, Rajat↗
NASA NTRS1993

Evaluating the design of an Earth Radiation Budget Instrument with systen simulations. Part 1: Instantaneous estimates

A set of system simulations has been performed to evaluate candidate scanner designs for an Earth Radiation Budget Instrument (ERBI) for the Earth Observing System (EOS) of the late 1990s. Five different instruments are considered: (1) the Active Cavity Array (ACA), (2) the Clouds and Earth's Radiant Energy System-Instrument (CERES-I), (3) the Conically Scanning Radiometer (CSR), (4) the Earth Radiation Budget Experiment Cross-Track Scanner (ERBE), and (5) the Nimbus-7 Biaxial Scanner (N7). Errors in instantaneous, top-of-the-atmosphere (TOA) satellite flux estimates are assumed to arise from two measurement problems: the sampling of space over a given geographic domain, and sampling in angle about a given spatial location. When angular sampling errors vanish due to the application of correct angular dependence models (ADMs) during inversion, the accuracy of each scanner design is determined by the instrument's ability to map the TOA radiance field in a uniform manner. In this regard, the instruments containing a cross-track scanning component (CERES-I and ERBE) do best. As errors in ADMs are encountered, cross-track instruments incur angular sampling errors more rapidly than biaxial instruments (N7, ACA, and CSR) and eventually overtake the biaxial designs in their total error amounts. A latitude bias (north-south error gradient) in the ADM error of cross-track instruments also exists. This would be objectionable when ADM errors are systematic over large areas of the globe. For instantaneous errors, however, cross-track scanners outperform biaxial or conical scanners for 2.5 deg latitude x 2.5 deg longitude target areas, providing that the ADM error is less than or equal to 30%. A key issue is the amount of systematic ADM error (departures from the mean models) that is present at the 2.5 deg resolution of the ERBE target areas. If this error is less than 30%, then the CERES-I, ERBE, and CSR, in order of increasing error, provide the most accurate instantaneous flux estimates, within 2-3 W/sq m of each other in reflected shortwave flux. The magnitude of this error is near the 10 W/sq m accuracy requirement of the user community. Longwave flux errors have been found to have the same space and time characteristics as errors in shortwave radiation, but only about 25% as large.

Stowe, Larry↗
DOE OSTI2014

WE-D-18A-01: Evaluation of Three Commercial Metal Artifact Reduction Methods for CT Simulations in Radiation Therapy Treatment Planning

Purpose: To evaluate three commercial metal artifact reduction methods (MAR) in the context of radiation therapy treatment planning. Methods: Three MAR strategies were evaluated: Philips O-MAR, monochromatic imaging using Gemstone Spectral Imaging (GSI) dual energy CT, and monochromatic imaging with metal artifact reduction software (GSIMARs). The Gammex RMI 467 tissue characterization phantom with several metal rods and two anthropomorphic phantoms (pelvic phantom with hip prosthesis and head phantom with dental fillings), were scanned with and without (baseline) metals. Each MAR method was evaluated based on CT number accuracy, metal size accuracy, and reduction in the severity of streak artifacts. CT number difference maps between the baseline and metal scan images were calculated, and the severity of streak artifacts was quantified using the percentage of pixels with >40 HU error (“bad pixels”). Results: Philips O-MAR generally reduced HU errors in the RMI phantom. However, increased errors and induced artifacts were observed for lung materials. GSI monochromatic 70keV images generally showed similar HU errors as 120kVp imaging, while 140keV images reduced errors. GSI-MARs systematically reduced errors compared to GSI monochromatic imaging. All imaging techniques preserved the diameter of a stainless steel rod to within ±1.6mm (2 pixels). For the hip prosthesis, O-MAR reduced the average % bad pixels from 47% to 32%. For GSI 140keV imaging, the percent of bad pixels was reduced from 37% to 29% compared to 120kVp imaging, while GSI-MARs further reduced it to 12%. For the head phantom, none of the MAR methods were particularly successful. Conclusion: The three MAR methods all improve CT images for treatment planning to some degree, but none of them are globally effective for all conditions. The MAR methods were successful for large metal implants in a homogeneous environment (hip prosthesis) but were not successful for the more complicated case of dental artifacts.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2013

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Modeling↗
DOE OSTI2016

WE-AB-207B-03: A Computational Methodology for Determination of CTV-To-PTV Margins with Inter Fractional Shape Variations Based On a Statistical Point Distribution Model for Prostate Cancer Radiation Therapy

Purpose: Our assumption was that interfractional shape variations of target volumes could not be negligible for determination of clinical target volume (CTV)-to-planning target volume (PTV) margins. The aim of this study was to investigate this assumption as a simulation study by developing a computational framework of CTV-to-PTV margins with taking the interfractional shape variations into account based on point distribution model (PDM) Methods: The systematic and random errors for interfractional shape variations and translations of target volumes were evaluated for four types of CTV regions (only a prostate, a prostate plus proximal 1-cm seminal vesicles, a prostate plus proximal 2-cm seminal vesicles, and a prostate plus whole seminal vesicles). The CTV regions were delineated depending on prostate cancer risk groups on planning computed tomography (CT) and cone beam CT (CBCT) images of 73 fractions of 10 patients. The random and systematic errors for shape variations of CTV regions were derived from PDMs of CTV surfaces for all fractions of each patient. Systematic errors of shape variations of CTV regions were derived by comparing PDMs between planning CTV surfaces and average CTV surfaces. Finally, anisotropic CTV-to-PTV margins with shape variations in 6 directions (anterior, posterior, superior, inferior, right, and left) were computed by using a van Herk margin formula. Results: Differences between CTV-to-PTV margins with and without shape variations ranged from 0.7 to 1.7 mm in anterior direction, 1.0 to 2.8 mm in posterior direction, 0.8 to 2.8 mm in superior direction, 0.6 to 1.6 mm in inferior direction, 1.4 to 4.4 mm in right direction, and 1.3 to 5.2 mm in left direction. Conclusion: More than 1.0 mm additional margins were needed at least in 3 directions to guarantee CTV coverage due to shape variations. Therefore, shape variations should be taken into account for the determination of CTV-to-PTV margins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Constraining the mass–richness relationship of redMaPPer clusters with angular clustering

The potential of using cluster clustering for calibrating the mass–richness relation of galaxy clusters has been recognized theoretically for over a decade. In this paper, we demonstrate the feasibility of this technique to achieve high-precision mass calibration using redMaPPer clusters in the Sloan Digital Sky Survey North Galactic Cap. By including cross-correlations between several richness bins in our analysis, we significantly improve the statistical precision of our mass constraints. The amplitude of the mass–richness relation is constrained to 7 per cent statistical precision by our analysis. However, the error budget is systematics dominated, reaching a 19 per cent total error that is dominated by theoretical uncertainty in the bias–mass relation for dark matter haloes. We confirm the result from Miyatake et al. that the clustering amplitude of redMaPPer clusters depends on galaxy concentration as defined therein, and we provide additional evidence that this dependence cannot be sourced by mass dependences: some other effect must account for the observed variation in clustering amplitude with galaxy concentration. Assuming that the observed dependence of redMaPPer clustering on galaxy concentration is a form of assembly bias, we find that such effects introduce a systematic error on the amplitude of the mass–richness relation that is comparable to the error bar from statistical noise. Finally, the results presented here demonstrate the power of cluster clustering for mass calibration and cosmology provided the current theoretical systematics can be ameliorated.

79 ASTRONOMY AND ASTROPHYSICS↗