Standardizing design performance comparison in microfluidic manufacturing

Microfluidic devices published in literature today lack sufficient information for automating the physical design process. Moreover, the constantly changing landscape of manufacturing and technological requirements poses a large problem in the physical design automation space. In this talk, we discuss some of the methodologies and standards formulated by CIDAR at BU and CARES at UC Riverside that allow not only allow the researchers in the physical design automation space to share and compare their results but also provide means for capturing the Specify, Design and Build lifecycle in microfluidic design

CMB-S4: Forecasting Constraints on Primordial Gravitational Waves

CMB-S4---the next-generation ground-based cosmic microwave background (CMB) experiment---is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the Universe, from the highest energies at the dawn of time through the growth of structure to the present day. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semi-analytic projection tool, targeted explicitly towards optimizing constraints on the tensor-to-scalar ratio, $r$, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2--3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments given a desired scientific goal. To form a closed-loop process, we couple this semi-analytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for $r > 0.003$ at greater than $5\sigma$, or, in the absence of a detection, of reaching an upper limit of $r < 0.001$ at $95\%$ CL.Comment: 24 pages, 8 figures, 9 tables, submitted to ApJ. arXiv admin note: text overlap with arXiv:1907.0447

The Redshift Evolution of the Mean Temperature, Pressure, and Entropy Profiles in 80 SPT-Selected Galaxy Clusters

We present the results of an X-ray analysis of 80 galaxy clusters selected in the 2500 deg2 South Pole Telescope survey and observed with the Chandra X-ray Observatory. We divide the full sample into subsamples of ∼20 clusters based on redshift and central density, performing a joint X-ray spectral fit to all clusters in a subsample simultaneously, assuming self-similarity of the temperature profile. This approach allows us to constrain the shape of the temperature profile over 0 R500) regions than their low-z (0.3 < z < 0.6) counterparts. Combining the average temperature profile with measured gas density profiles from our earlier work, we infer the average pressure and entropy profiles for each subsample. Confirming earlier results from this data set, we find an absence of strong cool cores at high z, manifested in this analysis as a significantly lower observed pressure in the central 0.1R500 of the high-z cool-core subset of clusters compared to the low-z cool-core subset. Overall, our observed pressure profiles agree well with earlier lower-redshift measurements, suggesting minimal redshift evolution in the pressure profile outside of the core. We find no measurable redshift evolution in the entropy profile at r . 0.7R500 – this may reflect a long-standing balance between cooling and feedback over long timescales and large physical scales. We observe a slight flattening of the entropy profile at r & R500 in our high-z subsample. This flattening is consistent with a temperature bias due to the enhanced (∼3×) rate at which group-mass (∼2 keV) halos, which would go undetected at our survey depth, are accreting onto the cluster at z ∼ 1. This work demonstrates a powerful method for inferring spatially-resolved cluster properties in the case where individual cluster signal-to-noise is low, but the number of observed clusters is high.Physic

Galaxy Clusters Discovered via the Sunyaev-Zel'dovich Effect in the 2500-square-degree SPT-SZ survey

We present a catalog of galaxy clusters selected via their Sunyaev-Zel'dovich (SZ) effect signature from 2500 deg2 of South Pole Telescope (SPT) data. This work represents the complete sample of clusters detected at high significance in the 2500 deg2 SPT-SZ survey, which was completed in 2011. A total of 677 (409) cluster candidates are identified above a signal-to-noise threshold of ξ = 4.5 (5.0). Ground- and space-based optical and near-infrared (NIR) imaging confirms overdensities of similarly colored galaxies in the direction of 516 (or 76%) of the ξ > 4.5 candidates and 387 (or 95%) of the ξ > 5 candidates; the measured purity is consistent with expectations from simulations. Of these confirmed clusters, 415 were first identified in SPT data, including 251 new discoveries reported in this work. We estimate photometric redshifts for all candidates with identified optical and/or NIR counterparts; we additionally report redshifts derived from spectroscopic observations for 141 of these systems. The mass threshold of the catalog is roughly independent of redshift above z ~ 0.25 leading to a sample of massive clusters that extends to high redshift. The median mass of the sample is M 500c(ρcrit) $\sim 3.5\times 10^{14}\,M_\odot \,h_{70}^{-1}$, the median redshift is z med = 0.55, and the highest-redshift systems are at z > 1.4. The combination of large redshift extent, clean selection, and high typical mass makes this cluster sample of particular interest for cosmological analyses and studies of cluster formation and evolution.Physic

CMB-S4: Forecasting Constraints on Primordial Gravitational Waves

Abstract: CMB-S4—the next-generation ground-based cosmic microwave background (CMB) experiment—is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensor-to-scalar ratio, r, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2–3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments, given a desired scientific goal. To form a closed-loop process, we couple this semianalytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for r > 0.003 at greater than 5σ, or in the absence of a detection, of reaching an upper limit of r < 0.001 at 95% CL

Placement, Routing, and Post-Processing of Microfluidic Device Flow-Layers

Continuous flow based microfluidic devices have made great strides in fields like rapid DNA sequencing and ex-vivo tissue samples, so-called organ-on-a-chip devices, for biological testing. While a large number of new components and biological processes have been developed, tools to help design these devices have not followed suit. As the field grows and the devices being designed become more complex, they will quickly become too difficult for a single person or small group to develop without computer assistance. This necessitates the development of tools and algorithms that can accelerate or automate parts of the design process. This dissertation presents and evaluates a collection of algorithms that form the crux of a larger software platform for microfluidic design. Algorithms are presented here for automated flow layer design and post-processing for area reduction and to automate the process of high-throughput conversions. It concludes by introducing a suite of benchmarks and design metrics to facilitate unbiased comparisons between the microfluidic design automation algorithms introduced here, and future work in the space to be performed by others

Placement, Routing, and Post-Processing of Microfluidic Device Flow-Layers

Continuous flow based microfluidic devices have made great strides in fields like rapid DNA sequencing and ex-vivo tissue samples, so-called organ-on-a-chip devices, for biological testing. While a large number of new components and biological processes have been developed, tools to help design these devices have not followed suit. As the field grows and the devices being designed become more complex, they will quickly become too difficult for a single person or small group to develop without computer assistance. This necessitates the development of tools and algorithms that can accelerate or automate parts of the design process. This dissertation presents and evaluates a collection of algorithms that form the crux of a larger software platform for microfluidic design. Algorithms are presented here for automated flow layer design and post-processing for area reduction and to automate the process of high-throughput conversions. It concludes by introducing a suite of benchmarks and design metrics to facilitate unbiased comparisons between the microfluidic design automation algorithms introduced here, and future work in the space to be performed by others