Search for: All records

Abstract Superconducting on-chip filter banks provide a scalable, space saving solution to create imaging spectrometers at millimetre and submillimetre wavelengths. We present an easy to realise, lithographed superconducting filter design with a high tolerance to fabrication error. Using a capacitively coupled $$\lambda /2$$ λ / 2 microstrip resonator to define a narrow ( $$\lambda /\Delta \lambda = 300$$ λ / Δ λ = 300 ) spectral pass band, the filtered output of a given spectrometer channel directly connects to a lumped-element kinetic inductance detector. We show the tolerance analysis of our design, demonstrating $$<11\%$$ < 11 % change in filter quality factor to any one realistic fabrication error and a full filter-bank efficiency forecast to be 50% after accounting for fabrication errors and dielectric loss tangent. 

Including millimeter-wave data in multiwavelength studies of the variability of active galactic nuclei (AGN) can provide insights into AGN physics that are not easily accessible at other wavelengths. We demonstrate in this work the potential of cosmic microwave background (CMB) telescopes to provide long-term, high-cadence millimeter-wave AGN monitoring over large fractions of sky. We report on a pilot study using data from the SPTpol instrument on the South Pole Telescope (SPT), which was designed to observe the CMB at arcminute and larger angular scales. Between 2013 and 2016, SPTpol was used primarily to observe a single 500 deg²field, covering the entire field several times per day with detectors sensitive to radiation in bands centered at 95 and 150 GHz. We use SPT 150 GHz observations to create AGN light curves, and we compare these millimeter-wave light curves to those at other wavelengths, in particularγ-ray and optical. In this Letter, we focus on a single source, PKS 2326-502, which has extensive, day-timescale monitoring data in gamma-ray, optical, and now millimeter-wave between 2013 and 2016. We find PKS 2326-502 to be in a flaring state in the first 2 yr of this monitoring, and we present a search for evidence of correlated variability between millimeter-wave, opticalR-band, andγ-ray observations. This pilot study is paving the way for AGN monitoring with current and upcoming CMB experiments such as SPT-3G, Simons Observatory, and CMB-S4, including multiwavelength studies with facilities such as Vera C. Rubin Observatories Large Synoptic Survey Telescope.

 

Dissolution of CuO nanoparticles, releasing Cu ions, is a primary mechanism of Cu interaction in the rooting zone of plants. CuO dissolution is sometimes incorrectly considered negligible at high pH, since complexation of Cu with dissolved organic matter may enhance nanoparticle dissolution. Therefore data on the effects of plant-microbial-soil interactions on nanoparticle dissolution, particularly in alkaline soils, are needed. Dissolution of CuO nanoparticles (100 mg kg −1 Cu) was studied in sand supplemented with factorial combinations of wheat growth, a root-colonizing bacterium, and saturated paste extracts (SPEs) from three alkaline, calcareous soils. In control sand systems with 3.34 mM Ca(NO 3 ) 2 solution, dissolved Cu was low (266 μg L −1 Cu). Addition of dissolved organic matter via wheat root metabolites and/or soil SPEs increased dissolved Cu to 795–6250 μg L −1 Cu. Dissolution was correlated with dissolved organic carbon ( R = 0.916, p < 0.0001). Ligands >3 kDa, presumably fulvic acid from the SPEs, complexed Cu driving solubility; the addition of plant exudates further increased solubility 1.5–3.5×. The root-colonizing bacterium decreased dissolved Cu in sand pore waters from planted systems due to metabolism of root exudates. Batch solubility studies (10 mg L −1 Cu) with the soil SPEs and defined solutions containing bicarbonate or fulvic acid confirmed elevated CuO nanoparticle solubility at >7.5 pH. Nanoparticle dissolution was suppressed in batch experiments compared to sand, via nanoparticle organic matter coating or homoconjugation of dissolved organic matter. Alterations of CuO nanoparticles by soil organic matter, plant exudates, and bacteria will affect dissolution and bioavailability of the CuO nanoparticles in alkaline soils. 

CuO nanoparticles (NPs) are explored as fungicides and fertilizers, and are increasingly likely to be applied to agricultural soils. Consequently, interactions of CuO NPs with soil pore water (SPW) components, plants, and microbes must be understood. These experiments examined whether dissolved natural organic matter (DNOM) from SPW, or root/bacterial exudates, changed wheat ( Triticum aestivum L. v. Deloris) responses to 100 mg kg −1 (Cu/sand) as CuO NPs. Seedlings were grown in sand with 3.34 mM Ca(NO 3 ) 2 or one of three SPWs, differing in DNOM concentration and composition. At 10 days post-germination, CuO NPs stunted roots by 59% in the 3.34 mM Ca(NO 3 ) 2 and 26–35% in the three SPWs compared to plants grown without NPs. Malate, citrate, gluconate, and 2′-deoxymugineic acid (DMA), were elevated 1.3 to 5-fold in the rhizosphere with CuO NPs present. Cu was bioavailable through metallo-organic complexes, including Cu–DMA and Cu–gluconate. Fulvic acid in SPWs mitigated CuO NP-induced wheat root shortening. Pseudomonas chlororaphis O6 eliminated malate and citrate in the rhizospheres, reduced rhizosphere dissolved Cu ∼18–66%, and reduced root Cu 39% across all SPWs while enhancing root stunting ∼17% more across all SPWs than non-inoculated wheat grown with CuO NPs. Thus, both SPW components and root microbial colonization influenced wheat responses to CuO NPs. These interactions are likely in agricultural soils with additional processes, such as ion sorption, to influence CuO NP phytotoxicity, highlighting the importance of considering not just the target plant, but soil properties and associated microbiomes when evaluating impacts of NPs in agricultural usage. 

Abstract We perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg 2 of polarization observations from the SPTpol receiver on the South Pole Telescope. These data reach noise levels as low as 5.8 μ K arcmin in polarization, which are low enough that the typically used quadratic estimator (QE) technique for analyzing CMB lensing is significantly suboptimal. Conversely, the Bayesian procedure extracts all lensing information from the data and is optimal at any noise level. We infer the amplitude of the gravitational lensing potential to be A ϕ = 0.949 ± 0.122 using the Bayesian pipeline, consistent with our QE pipeline result, but with 17% smaller error bars. The Bayesian analysis also provides a simple way to account for systematic uncertainties, performing a similar job as frequentist “bias hardening” or linear bias correction, and reducing the systematic uncertainty on A ϕ due to polarization calibration from almost half of the statistical error to effectively zero. Finally, we jointly constrain A ϕ along with A L , the amplitude of lensing-like effects on the CMB power spectra, demonstrating that the Bayesian method can be used to easily infer parameters both from an optimal lensing reconstruction and from the delensed CMB, while exactly accounting for the correlation between the two. These results demonstrate the feasibility of the Bayesian approach on real data, and pave the way for future analysis of deep CMB polarization measurements with SPT-3G, Simons Observatory, and CMB-S4, where improvements relative to the QE can reach 1.5 times tighter constraints on A ϕ and seven times lower effective lensing reconstruction noise.