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Sullivan, James

Publications and source records attributed to Sullivan, James.

Galaxy bias in the era of LSST: perturbative bias expansions

Upcoming imaging surveys will allow for high signal-to-noise measurements of galaxy clustering at small scales. In this work, we present the results of the Rubin Observatory Legacy Survey of Space and Time (LSST) bias challenge, the goal of which is to compare the performance of different nonlinear galaxy bias models in the context of LSST Year 10 (Y10) data. Specifically, we compare two perturbative approaches, Lagrangian perturbation theory (LPT) and Eulerian perturbation theory (EPT) to two variants of Hybrid Effective Field Theory (HEFT), with our fiducial implementation of these models including terms up to second order in the bias expansion as well as nonlocal bias and deviations from Poissonian stochasticity. Here, we consider a variety of different simulated galaxy samples and test the performance of the bias models in a tomographic joint analysis of LSST-Y10-like galaxy clustering, galaxy-galaxy-lensing and cosmic shear. We find both HEFT methods as well as LPT and EPT combined with non-perturbative predictions for the matter power spectrum to yield unbiased constraints on cosmological parameters up to at least a maximal scale of k max = 0.4 Mpc -1 for all samples considered, even in the presence of assembly bias. While we find that we can reduce the complexity of the bias model for HEFT without compromising fit accuracy, this is not generally the case for the perturbative models. We find significant detections of non-Poissonian stochasticity in all cases considered, and our analysis shows evidence that small-scale galaxy clustering predominantly improves constraints on galaxy bias rather than cosmological parameters. These results therefore suggest that the systematic uncertainties associated with current nonlinear bias models are likely to be subdominant compared to other sources of error for tomographic analyses of upcoming photometric surveys, which bodes well for future galaxy clustering analyses using these high signal-to-noise data.

79 ASTRONOMY AND ASTROPHYSICS↗

Novel spirometry based on optical surface imaging

Purpose: To evaluate the feasibility of using optical surface imaging (OSI) to measure the dynamic tidal volume (TV) of the human torso during free breathing. Methods: We performed experiments to measure volume or volume change in geometric and deformable phantoms as well as human subjects using OSI. To assess the accuracy of OSI in volume determination, we performed experiments using five geometric phantoms and two deformable body phantoms and compared the values with those derived from geometric calculations and computed tomography (CT) measurements, respectively. To apply this technique to human subjects, an institutional review board protocol was established and three healthy volunteers were studied. In the human experiment, a high-speed image capture mode of OSI was applied to acquire torso images at 4–5 frames per second, which was synchronized with conventional spirometric measurements at 5 Hz. An in-house MATLAB program was developed to interactively define the volume of interest (VOI), separate the thorax and abdomen, and automatically calculate the thoracic and abdominal volumes within the VOIs. The torso volume change (TV C = ΔV{sub torso} = ΔV{sub thorax} + ΔV{sub abdomen}) was automatically calculated using full-exhalation phase as the reference. The volumetric breathing pattern (BP{sub v} = ΔV{sub thorax}/ΔV{sub torso}) quantifying thoracic and abdominal volume variations was also calculated. Under quiet breathing, TVC should equal the tidal volume measured concurrently by a spirometer with a conversion factor (1.08) accounting for internal and external differences of temperature and moisture. Another MATLAB program was implemented to control the conventional spirometer that was used as the standard. Results: The volumes measured from the OSI imaging of geometric phantoms agreed with the calculated volumes with a discrepancy of 0.0% ± 1.6% (range −1.9% to 2.5%). In measurements from the deformable torso/thorax phantoms, the volume differences measured using OSI imaging and CT imaging were 1.2% ± 2.1% (range −0.5% to 3.6%), with a linear regression fitting (slope = 1.02 and R{sup 2} = 0.999). In volunteers, the relative error in OSI tidal volume measurement was −2.2% ± 4.9% (range −9.2% to 4.8%) and a correlation of r = 0.98 was found with spirometric measurement. The breathing pattern values of the three volunteers were substantially different from each other (BP{sub v} = 0.15, 0.45, and 0.32). Conclusions: This study demonstrates the feasibility of using OSI to measure breathing tidal volumes and breathing patterns with adequate accuracy. This is the first time that dynamic breathing tidal volume as well as breathing patterns is measured using optical surface imaging. The OSI-observed movement of the entire torso could serve as a new respiratory surrogate in the treatment room during radiation therapy.

60 APPLIED LIFE SCIENCES↗