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Abstract We measure the stacked lensing signal in the direction of galaxy clusters in the Dark Energy Survey Year 3 (DES Y3) redMaPPer sample, using cosmic microwave background (CMB) temperature data from SPT-3G, the third-generation CMB camera on the South Pole Telescope (SPT). Here, we estimate the lensing signal using temperature maps constructed from the initial 2 years of data from the SPT-3G 'Main' survey, covering 1500 deg²of the Southern sky. We then use this lensing signal as a proxy for the mean cluster mass of the DES sample. The thermal Sunyaev-Zel'dovich (tSZ) signal, which can contaminate the lensing signal if not addressed, is isolated and removed from the data before obtaining the mass measurement. In this work, we employ three versions of the redMaPPer catalogue: a Flux-Limited sample containing 8865 clusters, a Volume-Limited sample with 5391 clusters, and a Volume&Redshift-Limited sample with 4450 clusters. For the three samples, we detect the CMB lensing signal at a significance of 12.4σ, 10.5σand 10.2σand find the mean cluster masses to be  M_200m= 1.66±0.13 [stat.]± 0.03 [sys.], 1.97±0.18 [stat.]± 0.05 [sys.], and 2.11±0.20 [stat.]± 0.05 [sys.]×10¹⁴M_⊙, respectively. This is a factor of ∼ 2 improvement relative to the precision of measurements with previous generations of SPT surveys and the most constraining cluster mass measurements using CMB cluster lensing to date. Overall, we find no significant tensions between our results and masses given by redMaPPer mass-richness scaling relations of previous works, which were calibrated using CMB cluster lensing, optical weak lensing, and velocity dispersion measurements from various combinations of DES, SDSS and Planck data. We then divide our sample into 3 redshift and 3 richness bins, finding no significant discrepancies with optical weak-lensing calibrated masses in these bins. We forecast a 5.7% constraint on the mean cluster mass of the DES Y3 sample with the complete SPT-3G surveys when using both temperature and polarization data and including an additional ∼ 1400 deg²of observations from the 'Extended' SPT-3G survey. 

Fast generation of personalized head-related transfer functions is essential for rendering spatial audio. In this paper we propose to generate head-related transfer functions using a single graphics processing unit (GPU). We optimize the implementation of the conventional boundary element solver on a GPU. The simulation of a single frequency can be completed in seconds. A psychoacoustic experiment is conducted to study the perceptual performance of the computed HRTFs. In general, perceptual accuracy in the back is better than that in the front. 

Crowd-based open innovation communities have received increasing attention, based on the premise that leveraging the power and diversity of the crowd can lead to innovative outcomes. However, we still know little about how work is coordinated over time in this context, especially as the innovation process moves from idea generation to elaboration. Based on literature and theories of coordination and collaboration in traditional creative contexts and on emergent evidence from research on crowd work, we develop hypotheses about the unique interaction patterns that characterize co-creation and how these patterns impact, over time, submission quality. To test our hypotheses, we conducted a study of a crowd-based open innovation platform. We found that, in general, the diversity of contributors increased over time, but for high quality submissions, the number of contributors decreased and a small group of involved people became more dominant in providing feedback. Further, we observe that the creators of more successful submissions, while not dominating the discussion, were particularly engaged in the discussions in later stages. Our work contributes to understanding the temporal dynamics in open innovation communities by providing evidence that successful interaction patterns vary depending on the phase of the project.