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Line intensity mapping (LIM) is a new technique for tracing the global properties of galaxies over cosmic time. Detection of the very faint signals from redshifted carbon monoxide (CO), a tracer of star formation, pushes the limits of what is feasible with a total-power instrument. The CO Mapping Project Pathfinder is a first-generation instrument aiming to prove the concept and develop the technology for future experiments, as well as delivering early science products. With 19 receiver channels in a hexagonal focal plane arrangement on a 10.4 m antenna and an instantaneous 26â€"34 GHz frequency range with 2 MHz resolution, it is ideally suited to measuring CO (J = 1â€"0) from z ∼ 3. In this paper we discuss strategies for designing and building the Pathfinder and the challenges that were encountered. The design of the instrument prioritized LIM requirements over those of ancillary science. After a couple of years of operation, the instrument is well understood, and the first year of data is already yielding useful science results. Experience with this Pathfinder will guide the design of the next generations of experiments. [ABSTRACT FROM AUTHOR]

We introduce COMAP- EoR, the next generation of the Carbon Monoxide Mapping Array Project aimed at extending CO intensity mapping to the Epoch of Reionization. COMAP- EoR supplements the existing 30 GHz COMAP Pathfinder with two additional 30 GHz instruments and a new 16 GHz receiver. This combination of frequencies will be able to simultaneously map CO(1â€"0) and CO(2â€"1) at reionization redshifts (z ∼ 5â€"8) in addition to providing a significant boost to the z ∼ 3 sensitivity of the Pathfinder. We examine a set of existing models of the EoR CO signal, and find power spectra spanning several orders of magnitude, highlighting our extreme ignorance about this period of cosmic history and the value of the COMAP- EoR measurement. We carry out the most detailed forecast to date of an intensity mapping cross correlation, and find that five out of the six models we consider yield signal to noise ratios (S/Ns) ≳ 20 for COMAP- EoR, with the brightest reaching a S/N above 400. We show that, for these models, COMAP- EoR can make a detailed measurement of the cosmic molecular gas history from z ∼ 2â€"8, as well as probe the population of faint, star-forming galaxies predicted by these models to be undetectable by traditional surveys. We show that, for the single model that does not predict numerous faint emitters, a COMAP- EoR -type measurement is required to rule out their existence. We briefly explore prospects for a third-generation Expanded Reionization Array (COMAP- ERA) capable of detecting the faintest models and characterizing the brightest signals in extreme detail. [ABSTRACT FROM AUTHOR]

We describe the first-season CO Mapping Array Project (COMAP) analysis pipeline that converts raw detector readouts to calibrated sky maps. This pipeline implements four main steps: gain calibration, filtering, data selection, and mapmaking. Absolute gain calibration relies on a combination of instrumental and astrophysical sources, while relative gain calibration exploits real-time total-power variations. High-efficiency filtering is achieved through spectroscopic common-mode rejection within and across receivers, resulting in nearly uncorrelated white noise within single-frequency channels. Consequently, near-optimal but biased maps are produced by binning the filtered time stream into pixelized maps; the corresponding signal bias transfer function is estimated through simulations. Data selection is performed automatically through a series of goodness-of-fit statistics, including χ 2 and multiscale correlation tests. Applying this pipeline to the first-season COMAP data, we produce a data set with very low levels of correlated noise. We find that one of our two scanning strategies (the Lissajous type) is sensitive to residual instrumental systematics. As a result, we no longer use this type of scan and exclude data taken this way from our Season 1 power spectrum estimates. We perform a careful analysis of our data processing and observing efficiencies and take account of planned improvements to estimate our future performance. Power spectrum results derived from the first-season COMAP maps are presented and discussed in companion papers. [ABSTRACT FROM AUTHOR]

The CO Mapping Array Project (COMAP) aims to use line-intensity mapping of carbon monoxide (CO) to trace the distribution and global properties of galaxies over cosmic time, back to the Epoch of Reionization (EoR). To validate the technologies and techniques needed for this goal, a Pathfinder instrument has been constructed and fielded. Sensitive to CO(1â€"0) emission from z = 2.4â€"3.4 and a fainter contribution from CO(2â€"1) at z = 6â€"8, the Pathfinder is surveying 12 deg2 in a 5 yr observing campaign to detect the CO signal from z ∼ 3. Using data from the first 13 months of observing, we estimate P CO(k) = âˆ'2.7 ± 1.7 Ă— 104 ÎĽ K2 Mpc3 on scales k = 0.051 âˆ'0.62 Mpcâˆ'1, the first direct three-dimensional constraint on the clustering component of the CO(1â€"0) power spectrum. Based on these observations alone, we obtain a constraint on the amplitude of the clustering component (the squared mean CO line temperature bias product) of Tb 2 < 49 ÎĽ K2, nearly an order-of-magnitude improvement on the previous best measurement. These constraints allow us to rule out two models from the literature. We forecast a detection of the power spectrum after 5 yr with signal-to-noise ratio (S/N) 9â€"17. Cross-correlation with an overlapping galaxy survey will yield a detection of the COâ€"galaxy power spectrum with S/N of 19. We are also conducting a 30 GHz survey of the Galactic plane and present a preliminary map. Looking to the future of COMAP, we examine the prospects for future phases of the experiment to detect and characterize the CO signal from the EoR. [ABSTRACT FROM AUTHOR]

In this article we present an adjoint method for the optimization of the catalyst distribution in proton exchange membrane fuel cells (PEMFCs). By using the theory of functional analysis we derive analytical equations for the sensitivity functions of the cell voltage with respect to the catalyst distribution in a very general framework, independent on the transport model used to simulate the PEMFC. Then we present an efficient numerical algorithm to calculate the sensitivity functions using the adjoint method. The adjoint method has the advantage that it can be applied to the optimization of systems with a large (>104) number of optimization variables that are computed simultaneously and independently to maximize the objective function. Finally, we apply the method to the optimization of 2-D platinum distribution in PEMFCs. We show that the optimum platinum distribution varies with the operating conditions, position of landings and openings, cell geometry, and dimensions of the catalyst layers. The method presented in this work can be naturally extended to the optimization of other 2-D and 3-D field variables such as the porosity of catalyst and gas diffusion layers, particle size distribution, or microstructure of the cell. [ABSTRACT FROM AUTHOR]

We demonstrate the Sunyaev-Zel'dovich (SZ) effect imaging capabilities of the Combined Array for Research in Millimeter-wave Astronomy (CARMA) by presenting an SZ map of the galaxy cluster RX J1347.5-1145. By combining data from multiple CARMA bands and configurations, we are able to capture the structure of this cluster over a wide range of angular scales, from its bulk properties to its core morphology. We find that roughly 9% of this cluster's thermal energy is associated with sub-arcminute-scale structure imparted by a merger, illustrating the value of high-resolution SZ measurements for pursuing cluster astrophysics and for understanding the scatter in SZ scaling relations. We also find that the cluster's SZ signal is lower in amplitude than suggested by a spherically symmetric model derived from X-ray data, consistent with compression along the line of sight relative to the plane of the sky. Finally, we discuss the impact of upgrades currently in progress that will further enhance CARMA's power as an SZ imaging instrument. [ABSTRACT FROM AUTHOR]

We present results of λ1.3 mm dust-polarization observations toward 16 nearby, low-mass protostars, mapped with ~2''. 5 resolution at CARMA. The results show that magnetic fields in protostellar cores on scales of ~1000 AU are not tightly aligned with outflows from the protostars. Rather, the data are consistent with scenarios where outflows and magnetic fields are preferentially misaligned (perpendicular), or where they are randomly aligned. If one assumes that outflows emerge along the rotation axes of circumstellar disks, and that the outflows have not disrupted the fields in the surrounding material, then our results imply that the disks are not aligned with the fields in the cores from which they formed. [ABSTRACT FROM AUTHOR]

We perform a joint analysis of X-ray and Sunyaev-Zel'dovich effect data using an analytic model that describes the gas properties of galaxy clusters. The joint analysis allows the measurement of the cluster gas mass fraction profile and Hubble constant independent of cosmological parameters. Weak cosmological priors are used to calculate the overdensity radius within which the gas mass fractions are reported. Such an analysis can provide direct constraints on the evolution of the cluster gas mass fraction with redshift. We validate the model and the joint analysis on high signal-to-noise data from the Chandra X-ray Observatory and the Sunyaev-Zel'dovich Array for two clusters, A2631 and A2204. [ABSTRACT FROM AUTHOR]

We have measured the Sunyaev-Zel'dovich (SZ) effect for a sample of 10 strong lensing selected galaxy clusters using the Sunyaev-Zel'dovich Array (SZA). The SZA is sensitive to structures on spatial scales of a few arcminutes, while the strong lensing mass modeling constrains the mass at small scales (typically <30"). Combining the two provides information about the projected concentrations of the strong lensing clusters. The Einstein radii we measure are twice as large as expected given the masses inferred from SZ scaling relations. A Monte Carlo simulation indicates that a sample randomly drawn from the expected distribution would have a larger median Einstein radius than the observed clusters about 3% of the time. The implied overconcentration has been noted in previous studies and persists for this sample, even when we take into account that we are selecting large Einstein radius systems, suggesting that the theoretical models still do not fully describe the observed properties of strong lensing clusters. [ABSTRACT FROM AUTHOR]

To determine if the parameters relating lung tissue displacement to a breathing surrogate signal in a previously published respiratory motion model vary with the rate of breathing during image acquisition. An anesthetized pig was imaged using multiple fast helical scans to sample the breathing cycle with simultaneous surrogate monitoring. Three datasets were collected while the animal was mechanically ventilated with different respiratory rates: 12 bpm (breaths per minute), 17 bpm, and 24 bpm. Three sets of motion model parameters describing the correspondences between surrogate signals and tissue displacements were determined. The model error was calculated individually for each dataset, as well asfor pairs of parameters and surrogate signals from different experiments. The values of one model parameter, a vector field denoted [Formula: see text] which related tissue displacement to surrogate amplitude, determined for each experiment were compared. The mean model error of the three datasets was 1.00  ±  0.36 mm with a 95th percentile value of 1.69 mm. The mean error computed from all combinations of parameters and surrogate signals from different datasets was 1.14  ±  0.42 mm with a 95th percentile of 1.95 mm. The mean difference in [Formula: see text] over all pairs of experiments was 4.7%  ±  5.4%, and the 95th percentile was 16.8%. The mean angle between pairs of [Formula: see text] was 5.0  ±  4.0 degrees, with a 95th percentile of 13.2 mm. The motion model parameters were largely unaffected by changes in the breathing rate during image acquisition. The mean error associated with mismatched sets of parameters and surrogate signals was 0.14 mm greater than the error achieved when using parameters and surrogate signals acquired with the same breathing rate, while maximum respiratory motion was 23.23 mm on average.