Testing GPU Numerics: Finding Numerical Differences Between NVIDIA and AMD GPUs
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Development of online pulse-finding algorithms for the Mu2e Stopping Target Monitor and an evaluation of the signal to background ratio for the Mu2e stopped-muon rate determination
This thesis presents a determination of the acceptance of the Mu2e Stopping Target Monitor (STM) detector for both signal and background events. The rate of X-rays of a specific energy in the STM is used to determine the rate of stopped muons in the aluminium stopping target, which is used as the normalisation for all Mu2e measurements, particularly the branching ratio for a charged lepton flavour violating (cLFV) process. The acceptance for the 347\,keV $2p-1s$ aluminium signal X-ray is determined to be $(8.03 \pm 0.05) \times 10^{-10}$\,cm$^{-2}$ and the acceptance for the background photons (at 347\,keV) to be $(3.19 \pm 0.21) \times 10^{-8}$\,cm$^{-2}$. This results in a signal-to-background ratio of approximately two which is significantly higher than had previously been estimated. These signal-to-background rates are used to determine the time required to achieve a statistical uncertainty of 10\% on the number of 347\,keV X-rays as a function of the detector resolution and back ground rate. For a resolution of 2\,keV, and the background rate determined in this thesis, approximately one minute of data is required. The three corrections needed to be applied to the measured 347\,keV rate to determine the rate of stopped muons are also determined and potential sources of bias arising from the background shape, background fit range and energy calibration are investigated and found to be insignificant. The raw energy of the particles in the STM detector comes from a 16-bit ADC digitising at $\sim 300$\,MHz. It is not possible to store all the raw digitisations and online algorithms have been developed to rapidly select pulses in the detector and reconstruct their energy. The performance of these algorithms has been characterised with simulated data as a function of detector rate and resolution and optimum operating points for the algorithms have been defined. The integrity of the algorithms has also been demonstrated and characterised on test-beam data at high r ates and with radioactive sources at low rates.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Initial Findings in Qualifying the Instrument Thimble 11 Position in the Advanced Test Reactor Critical
The Advanced Test Reactor (ATR) is a versatile nuclear research reactor located at the Idaho National Laboratory (INL) in Eastern Idaho, United States of America. It is one of the most powerful and flexible research reactors in the world and is primarily used for materials testing, isotope production and basic nuclear science research. The ATR is a light-water-cooled, beryllium-moderated reactor with a nominal thermal power capacity of 250 MW utilizing specially designed fuel, arranged in a serpentine pattern to create 9 flux traps. The special design of ATR allows for the neutron flux within each of the flux traps providing flexibility for experiments, programs and allowing experiments with different dose requirements to be irradiated simultaneously. The Advance Test Reactor Critical (ATRC) is a full-scale replica of the ATR core but is housed in a pool instead of a pressure vessel. ATRC is usually operated at less than 600 watts [1]. There are 12 dry instrument thimbles located around the outside of the core tank where a variety of measurement equipment is housed to facilitate reactor operations. Currently Instrument Thimble 11 (IT-11) is not utilized in ATR or ATRC. A range of measurements is ongoing to qualify IT-11 as a test platform for nuclear instrumentation research, development and further experimentation.
46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
Qudit Designs and Where to Find Them
Unitary t-designs are some of the most versatile tools in quantum information theory. Their applications range from randomized benchmarking and shadow tomography, to more fundamental ones such as emulating quantum chaos and establishing exponential separations between classical and quantum query complexity. While unitary designs originating from a group structure, such as the Clifford group, have proven to be incredibly useful for qubit systems, unfortunately, this is no longer true for qudits. In fact, the classification of finite-group representations rules out the existence of unitary 2-designs for arbitrary qudit dimensions. This severely limits the applicability of standard quantum information primitives when it comes to qudit systems. We overcome these limitations with a three-fold contribution. First, we introduce a general technique to construct families of weighted state t-designs in arbitrary qudit dimensions. These weighted state-designs generalize classical shadow tomography protocol from qubits to qudits. Second, we introduce a Clifford character RB that allows us to benchmark the qudit Clifford group in any dimension, including non-prime-power dimensions. And third, we establish bounds on the quantum circuit complexity of generating approximate unitary-designs from native gates in existing quantum hardware such as high-spin and cavity-QED qudits. Our work further highlights the analogy between spin and optical coherent states by proving that spin-GKP codewords form a state 2-design while spin coherent states do not; in direct analogy with the optical case. This work is structured as a pedagogical and self-contained introduction to unitary designs and their applications to qudit systems.
Anand, Namit [NASA, Ames; Unlisted, US] (ORCID:000↗
AGR-5/6/7 Experiment Preliminary Findings
AGR-5/6/7 in-pile data have been published: Fuel irradiation conditions, Fission gas release-rate-to-birth-rate (R/B) ratios, PIE and safety testing are still in progress and only limited data have been published, and preliminary results.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
The Wind Energy Workforce in the United States: Training, Hiring, and Future Needs
Researchers received 247 completed interviews from wind industry employers and 50 completed interviews from representatives from educational institutions with wind energy courses, to better understand the wind industry workforce, hiring needs, and educational pathways . The interviews revealed that 68% of wind industry firms interviewed had difficulty hiring across most occupations. Twenty-five percent of firms searched outside of the United States to find candidates with appropriate skills and experience, which some employers consider lacking, among domestic candidates. At the same time, interview results showed that people who graduate from wind energy educational programs often do not enter the wind industry upon graduation - the majority find employment outside of the wind industry. In addition, some educational and training institutions with wind or renewable energy-specific programs reported difficulty filling courses. This difficulty of employers finding well qualified workers while wind and renewable energy graduates report difficulty finding jobs in the wind industry is the wind energy workforce gap. Narrowing this workforce gap - decreasing hiring difficulty while increasing graduates' ability to find jobs in the wind industry - could reduce recruiting costs, better satisfy employer needs, and grow the domestic wind workforce. Narrowing the gap would simultaneously help educational institutions more efficiently fill classrooms and communicate wind-industry career options to potential students. Twenty-five percent of firms searched outside of the United States to find candidates with appropriate skills and experience, which some employers consider lacking, among domestic candidates. At the same time, interview results showed that people who graduate from wind energy educational programs often do not enter the wind industry upon graduation - the majority find employment outside of the wind industry. In addition, some educational and training institutions with wind or renewable energy-specific programs reported difficulty filling courses. This difficulty of employers finding well qualified workers while wind and renewable energy graduates report difficulty finding jobs in the wind industry is the wind energy workforce gap. Narrowing this workforce gap - decreasing hiring difficulty while increasing graduates' ability to find jobs in the wind industry - could reduce recruiting costs, better satisfy employer needs, and grow the domestic wind workforce. Narrowing the gap would simultaneously help educational institutions more efficiently fill classrooms and communicate wind-industry career options to potential students.
17 WIND ENERGY↗
Dark Energy Survey year 1 results: Constraints on extended cosmological models from galaxy clustering and weak lensing
We present constraints on extensions of the minimal cosmological models dominated by dark matter and dark energy, Lambda CDM and wCDM, by using a combined analysis of galaxy clustering and weak gravitational lensing from the first-year data of the Dark Energy Survey (DES Y1) in combination with external data. We consider four extensions of the minimal dark energy-dominated scenarios: (1) nonzero curvature Omega(k), (2) number of relativistic species N-eff different from the standard value of 3.046, (3) time-varying equation-of-state of dark energy described by the parameters w(0) and w(a) (alternatively quoted by the values at the pivot redshift, w(p), and w(a)), and (4) modified gravity described by the parameters is mu(0) and Sigma(0) that modify the metric potentials. We also consider external information from Planck cosmic microwave background measurements; baryon acoustic oscillation measurements from SDSS, 6dF, and BOSS; redshift-space distortion measurements from BOSS; and type Ia supernova information from the Pantheon compilation of datasets. Constraints on curvature and the number of relativistic species are dominated by the external data; when these are combined with DES Y1, we find Omega(k) = 0.0020(-0.0032)(+0.0037) at the 68% confidence level, and the upper limit N-eff < 3.28(3.55) at 68% (95%) confidence, assuming a hard prior N-eff > 3.0. For the time-varying equation-of-state, we find the pivot value (w(p), w(a)) = (-0.91(-0.23)(+0.19), -0.57(-1.11)(+0.93)) at pivot redshift z(p )= 0.27 from DES alone, and (w(p), w(a)) = (-1.01(-0.04)(+0.04), -0.28(-0.48)(+0.37)) at z(p) = 0.20 from DES Y1 combined with external data; in either case we find no evidence for the temporal variation of the equation of state. For modified gravity, we find the present-day value of the relevant parameters to be Sigma(0) = 0.43(-)(0.29)(+0.28) from DES Y1 alone, and (Sigma(0), mu(0)) = (0.06(-0.07)(+0.08), -0.11(-0.46)(+0.42)) from DES Y1 combined with external data. These modified-gravity constraints are consistent with predictions from general relativity.
Abbott, T. M. C.↗
Rheo-electric measurements of carbon black suspensions containing polyvinylidene difluoride in N -methyl-2-pyrrolidone
Lithium-ion battery cathode slurries have a microstructure that depends sensitively on how they are processed due to carbon black's (CB) evolving structure when subjected coating flows. While polyvinylidene difluoride (PVDF), one of the main components of the cathode slurry, plays an important role in modifying the structure and rheology of CB, a quantitative understanding is lacking. In this work, we explore the role of PVDF in determining the structural evolution of Super C65 CB in N-methyl-2-pyrrolidinone (NMP) with rheo-electric measurements. We find that PVDF enhances the viscosity of NMP resulting in a more extensive structural erosion of CB agglomerates with increasing polymer concentration and molecular weight. We also show that the relative viscosity of all suspensions can be collapsed by the fluid Mason number (Mnf), which compares the hydrodynamic forces imposed by the medium to cohesive forces holding CB agglomerates together. Using simultaneous rheo-electric measurements, we find at high Mnf, the dielectric strength (Δε) scales with Mnf, and the power-law scaling can be quantitatively predicted by considering the self-similar break up of CB agglomerates. The collapse of the relative viscosity and scaling of Δε both suggest that PVDF increases the hydrodynamic force of the suspending medium without directly changing the CB agglomerate structure. These findings are valuable for optimizing the rheology of lithium ion battery cathode slurries. We also anticipate that these findings can be extended to understand the microstructure of similar systems under flow.
Mechanics↗
Rapid AI-based Dissection of Ashes using Raman and XRF Spectroscopy (RADAR-X)
Waste-to-energy (WTE) facilities incinerate ~35 million tons of municipal solid waste annually in the United States. The incineration process reduces the mass and the volume of the waste fraction by over 75 and 95%, respectively. The fraction left after incineration remains as ash residues and is referred to as WTE ash, compromising of bottom and fly ash. In the United States, ~10 million tons of WTE ashes are generated annually and predominantly landfilled because of the lack of secondary end-use pathways. This incurs a significant financial burden (landfilling costs) on U.S. WTE facilities and also results in the loss of materials to the landfill. The primary objective of this research is to understand better the elemental and mineralogical composition of WTE ashes from diverse origins and find composition dependent upcycling pathways for diverting these ashes from landfills. This primary objective was addressed through three research tasks –(Task I) An AI-led Multi-Modal Approach for Compositional Analysis, (Task II) Developing a Dissolution-Based Test for Real Time Analysis, and (Task III) Establishing composition-dependent end uses. The chemical composition of WTE ash is dependent on two factors, i.e., the input waste composition and the operational parameters of a WTE facility (combustion conditions). Amongst these two factors, the input waste composition will likely show spatial and temporal variation. As a result, the chemical composition of WTE ash will also fluctuate. To understand the spatial and temporal variation in WTE ash composition, in Task I, we collected 128 ash samples (62 bottom ash and 66 fly ash samples) from 11 WTE facilities located in 11 U.S. states and characterized them via X-ray Fluorescence, powder X-ray Diffraction, and Raman Spectroscopy. The findings from this extensive characterization work indicated that the key elements in WTE fly ashes are Ca, Cl (greater than 10 wt. %), Si, S, K, Zn ( between 1 and 10 wt. %), Mg, Al, P, Ti, Fe, Cu, Br, and Pb (between 0.1 and 1 wt. %). Similarly, the key elements in WTE bottom ash fraction finer than 45μm are Ca (greater than 10 wt. %), Mg, Al, Si, S, Cl, K, Ti, Fe, Zn (between 1 and 10 wt. %), P, V, Cr, Mn, Cu, Br, and Pb (between 0.1 and 1 wt. %). Here, we note that the dominant fraction of WTE bottom ash is the coarse fraction. The coarse WTE bottom ash fraction (rich in silicon) was not characterized in this study because of excessive grinding requirements and their unsuitability as a supplementary cementitious material due to their coarse nature. The elements in WTE bottom ashes are present as calcite, anhydrite, vaterite, hydroxyapatite, quartz, bassanite, gehlenite, akermanite, hydrocalumite, and portlandite. Similarly, the mineralogical species present in WTE fly ashes are calcium chloride hydroxide, halite, calcite, anhydrite, sylvite, hydrocalumite, vaterite, hannebachite, quartz, and bassanite. Temporal variation in ash composition may also result in significant fluctuations in chemical compositions. Therefore, a WTE facility may need to monitor the ash composition (elemental and mineralogical composition) in real time. In Task I, we evaluated the possibility of using a portable X-ray fluorescence (XRF) spectrometer to monitor the elemental composition in real-time. Specifically, we collected XRF data on identical specimens via a portable XRF spectrometer (low-end) and a lab-based benchtop XRF spectrometer (high-end). The collected data was used to train an A.I. algorithm (portable XRF data as an input and benchtop XRF data as an output) to predict accurate elemental composition using portable XRF data. Finally, we developed a 2-minute photobleaching protocol to monitor the mineralogical characteristics of WTE ashes via Raman spectroscopy. Overall, the activities in Task I improved our understanding of ash composition and developed techniques to monitor elemental and mineralogical composition in near real-time. Based on the findings of Task I, we find that WTE ashes exhibit wide variability in mineralogy. For ICP-based elemental analysis, all the mineralogical species in WTE ashes must be brought into solution. This is traditionally accomplished with acid digestion using a combination of multiple acids. However, acid digestion with multiple acids is time-consuming and often fails to ensure complete digestion of the ash matrix. To address this limitation, in Task II, we developed an alkali-fusion-based digestion protocol using a combination of lithium tetraborate, lithium metaborate, and their combinations as possible alkali fluxes for digesting WTE ashes entirely and rapidly. The validity of the developed method was evaluated on two standard ash specimens, i.e., SRM 1633c coal fly ash and BCR-176R incineration fly ash specimen. The findings suggest that the developed protocol can ensure complete digestion of elements such as Al, Ba, Ca, Cr, Cu, Mg, Mn, P, Sr, V, Zn, Be, K, and rare earth elements. The recent changes in the energy market towards renewables and increased metal recycling have resulted in reduced supplies of supplementary cementitious materials (coal fly ash and slag). Therefore, in Task III, we evaluated the possibility of employing WTE ashes as SCMs. As the chemical composition of WTE ashes varies temporally (on an hourly basis), there was also a need to develop tests that can evaluate the suitability of material to act as supplementary cementitious material rapidly, i.e., in a few minutes. Therefore, in Task II, we also developed a rapid test to assess the suitability of a material to act as an SCM in 5 minutes. This represents a significant advance over the state-of-the-art R 3 test, which takes ~144 hours. This test was initially validated on amorphous aluminosilicates, such as calcined clays, and could be extended to evaluate other industrial by-products, such as WTE ashes. In Task III, we evaluated the possibility of employing WTE ashes for two applications, i.e., as an SCM and a lime substitute for clay stabilization. The findings from Task I indicated that WTE ashes are enriched in chlorine and, therefore, cannot be used directly as an SCM due to corrosion-related risks and altered hydration kinetics. Accordingly, we developed an ash treatment protocol to reduce the solubility of chlorine-containing species in WTE ashes. The developed treatment protocol also immobilized lead in certain mineral forms. As a result of the treatment, WTE ashes can be used as SCMs without any corrosion or heavy metal leaching concerns. The second application examined in this study was clay stabilization. WTE ashes are calcium-rich and can be an adequate lime replacement for clay stabilization. Our findings reveal that the sum of the concentrations of Ca(OH) 2 and CaClOH controls the clay stabilization capability of WTE ashes. In summary, in this work, we evaluated the elemental and mineralogical characteristics of U.S. WTE ashes from diverse origins and developed tests to evaluate the chemical characteristics of these ashes in real time through a portable XRF and a benchtop Raman spectrometer. Based on the chemical characteristics of these ashes, we developed an ash treatment process to enable the use of WTE ashes as an SCM and also evaluated the possibility of employing these ashes for clay stabilization. Overall, the findings from this work enables the diversion of WTE ashes from landfills for multiple end-uses, i.e., as an SCM or a lime substitute for clay stabilization.
36 MATERIALS SCIENCE↗
Dynamics and structure of turbulent premixed flames
In earlier work (Mantel & Bilger, 1994) the structure of the turbulent premixed flame was investigated using statistics based on conditional averaging with the reaction progress variable as the conditioning variable. The DNS data base of Trouve and Poinsot (1994) was used in this investigation. Attention was focused on the conditional dissipation and conditional axial velocity in the flame with a view to modeling these quantities for use in the conditional moment closure (CMC) approach to analysis of kinetics in premixed flames (Bilger, 1993). Two remarkable findings were made: there was almost no acceleration of the axial velocity in the flame front itself; and the conditional scalar dissipation remained as high, or higher, than that found in laminar premixed flames. The first finding was surprising since in laminar flames all the fluid acceleration occurs through the flame front, and this could be expected also for turbulent premixed flames at the flamelet limit. The finding gave hope of inventing a new approach to the dynamics of turbulent premixed flames through use of rapid distortion theory or an unsteady Bernoulli equation. This could lead to a new second order closure for turbulent premixed flames. The second finding was contrary to our measurements with laser diagnostics in lean hydrocarbon flames where it is found that conditional scalar dissipation drops dramatically below that for laminar flamelets when the turbulence intensity becomes high. Such behavior was not explainable with a one-step kinetic model, even at non-unity Lewis number. It could be due to depletion of H2 from the reaction zone by preferential diffusion. The capacity of the flame to generate radicals is critically dependent on the levels of H2 present (Bilger, et al., 1991). It seemed that a DNS computation with a multistep reduced mechanism would be worthwhile if a way could be found to make this feasible. Truly innovative approaches to complex problems often come only when there is the opportunity to work close at hand with the (in this case numerical) experimental data. Not only can one spot patterns and relationships in the data which could be important, but one can also get to know the limitations of the technique being used, so that when the next experiment is being designed it will address resolvable questions. A three-year grant from the Australian Research Council has enabled us to develop a small capability at the University of Sydney to work on DNS of turbulent reacting flow, and to analyze data bases generated at CTR. Collaboration between the University of Sydney and CTR is essential to this project and finding a workable modus operandum for this collaboration, given the constraints involved, has been a major objective of the past year's effort. The overall objectives of the project are: (1) to obtain a quantitative understanding of the dynamics of turbulent premixed flames at high turbulence levels with a view to developing improved second order closure models; and (2) to carry out new DNS experiments on turbulent premixed flames using a carefully chosen multistep reduced mechanism for the chemical kinetics, with a view to elucidating the laser diagnostic findings that are contrary to the findings for DNS using one-step kinetics. In this first year the objectives have been to make the existing CTR data base more accessible to coworkers at the University of Sydney, to make progress on understanding the dynamics of the flame in this existing CTR data base, and to carefully construct a suitable multistep reduced mechanism for use in a new set of DNS experiments on turbulent premixed flames.
Bilger, R. W.↗
Characterization of OCO-2 and ACOS-GOSAT biases and errors for flux estimates
We characterize the magnitude of seasonally and spatially varying biases in the National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2) Version 8 (v8) and the Atmospheric CO2 Observations from Space (ACOS) Greenhouse Gas Observing SATellite (GOSAT) version 7.3 (v7.3) satellite CO2 retrievals by comparisons to measurements collected by the Total Carbon Column Observing Network (TCCON), Atmospheric Tomography (ATom) experiment, and National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) and U. S. Department of Energy (DOE) aircraft, and surface stations. Although the ACOS-GOSAT estimates of the column averaged carbon dioxide (CO2) dry air mole fraction (XCO2) have larger random errors than the OCO-2 XCO2 estimates, and the space-based estimates over land have larger random errors than those over ocean, the systematic errors are similar across both satellites and surface types, 0.6 ± 0.1 ppm. We find similar estimates of systematic error whether dynamic versus geometric coincidences or ESRL/DOE aircraft versus TCCON are used for validation (over land), once validation and co-location errors are accounted for. We also find that areas with sparse throughput of good quality data (due to quality flags and preprocessor selection) over land have ~double the error of regions of high-throughput of good quality data. We characterize both raw and bias-corrected results, finding that bias correction improves systematic errors by a factor of 2 for land observations and improves errors by ~0.2 ppm for ocean. We validate the lowermost tropospheric (LMT) product for OCO-2 and ACOS-GOSAT by comparison to aircraft and surface sites, finding systematic errors of ~1.1 ppm, while having 2-3 times the variability of XCO2. We characterize the time and distance scales of correlations for OCO-2 XCO2 errors, and find error correlations on scales of 0.3 degrees, 5-10 degrees, and 60 days. We find comparable scale lengths for the bias correction term. Assimilation of the OCO-2 bias correction term is used to estimate flux errors resulting from OCO-2 seasonal biases, finding annual flux errors on the order of 0.3 and 0.4 PgC/yr for Transcom-3 ocean and land regions, respectively.
Susan S Kulawik↗
Atacama Cosmology Telescope measurements of a large sample of candidates from the Massive and Distant Clusters of WISE Survey: Sunyaev-Zeldovich effect confirmation of MaDCoWS candidates using ACT
Context. Galaxy clusters are an important tool for cosmology, and their detection and characterization are key goals for current and future surveys. Using data from the Wide-field Infrared Survey Explorer (WISE), the Massive and Distant Clusters of WISE Survey (MaDCoWS) located 2839 significant galaxy overdensities at redshifts 0.7 . z . 1.5, which included extensive follow-up imaging from the Spitzer Space Telescope to determine cluster richnesses. Concurrently, the Atacama Cosmology Telescope (ACT) has produced large area millimeter-wave maps in three frequency bands along with a large catalog of Sunyaev-Zeldovich (SZ)-selected clusters as part of its Data Release 5 (DR5). Aims. We aim to verify and characterize MaDCoWS clusters using measurements of, or limits on, their thermal SZ effect signatures. We also use these detections to establish the scaling relation between SZ mass and the MaDCoWS-defined richness. Methods. Using the maps and cluster catalog from DR5, we explore the scaling between SZ mass and cluster richness. We do this by comparing cataloged detections and extracting individual and stacked SZ signals from the MaDCoWS cluster locations. We use complementary radio survey data from the Very Large Array, submillimeter data from Herschel, and ACT 224 GHz data to assess the impact of contaminating sources on the SZ signals from both ACT and MaDCoWS clusters. We use a hierarchical Bayesian model to fit the mass-richness scaling relation, allowing for clusters to be drawn from two populations: one, a Gaussian centered on the mass-richness relation, and the other, a Gaussian centered on zero SZ signal. Results. We find that MaDCoWS clusters have submillimeter contamination that is consistent with a gray-body spectrum, while the ACT clusters are consistent with no submillimeter emission on average. Additionally, the intrinsic radio intensities of ACT clusters are lower than those of MaDCoWS clusters, even when the ACT clusters are restricted to the same redshift range as the MaDCoWS clusters. We find the best-fit ACT SZ mass versus MaDCoWS richness scaling relation has a slope of p1 = 1.84+0.15 −0.14, where the slope is defined as M ∝ λ p1 15 and λ15 is the richness. We also find that the ACT SZ signals for a significant fraction (∼57%) of the MaDCoWS sample can statistically be described as being drawn from a noise-like distribution, indicating that the candidates are possibly dominated by low-mass and unvirialized systems that are below the mass limit of the ACT sample. Further, we note that a large portion of the optically confirmed ACT clusters located in the same volume of the sky as MaDCoWS are not selected by MaDCoWS, indicating that the MaDCoWS sample is not complete with respect to SZ selection. Finally, we find that the radio loud fraction of MaDCoWS clusters increases with richness, while we find no evidence that the submillimeter emission of the MaDCoWS clusters evolves with richness. Conclusions. We conclude that the original MaDCoWS selection function is not well defined and, as such, reiterate the MaDCoWS collaboration’s recommendation that the sample is suited for probing cluster and galaxy evolution, but not cosmological analyses. We find a best-fit mass-richness relation slope that agrees with the published MaDCoWS preliminary results. Additionally, we find that while the approximate level of infill of the ACT and MaDCoWS cluster SZ signals (1–2%) is subdominant to other sources of uncertainty for current generation experiments, characterizing and removing this bias will be critical for next-generation experiments hoping to constrain cluster masses at the sub-percent level.
large↗
Assessment of Myocarditis: Cardiac MR, PET/CT, or PET/MR?
Purpose of Review: Diagnosis of myocarditis is challenging given its variable clinical manifestations and non-specific laboratory findings. Cardiac magnetic resonance (MR) is currently the preferred imaging modality for the diagnosis of myocarditis. {sup 18}F-fluoro-deoxy-glucose (FDG) positron emission tomography/computed tomography (PET/CT), as a functional imaging tool, has a potential role in the assessment of myocarditis by detecting the underlying myocardial inflammatory activity. Data are accumulating that simultaneous cardiac PET/MR may have complementary and incremental values for the evaluation of myocarditis compared to PET/CT or cardiac MR alone. The article aims to summarize the findings in the literature and discuss future directions of cardiac PET/MR for myocarditis. Recent Findings: The Lake Louis Criteria (CLL) of cardiac MR is widely used for the diagnosis of myocarditis. It has an overall acceptable sensitivity of 67% and specificity of 91% for acute myocarditis but does not have the same accuracy for chronic myocarditis. FDG PET/CT is capable of assessing myocarditis by providing metabolic information of inflammation as increased myocardial FDG uptake. In addition to reduced radiation exposure, FDG PET performed on a hybrid PET/MR may detect more myocarditis than FDG PET/CT, because of the delayed PET acquisition time on PET/MR. Case-based observations and small clinical studies of FDG PET/MR have shown that FDG PET findings as abnormally increased myocardial uptake correlate well with the cardiac MR biomarkers. FDG PET findings may add complementary and incremental values to cardiac MR by improving the sensitivity of cardiac MR for mild or borderline myocarditis, and increasing specificity for chronic myocarditis. Summary: Preliminary data from retrospective and case-based observational studies have suggested the complementary and incremental values of simultaneous cardiac FDG PET/MR for evaluation of myocarditis, compared to PET/CT or MR alone. Well-designed studies are needed to confirm the findings and to assess the value of cardiac PET/MR for clinical management and more importantly patient’s outcome in both acute and chronic myocarditis.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Engineering Antifreeze Proteins to Optimally Resist Engulfment by Ice
Antifreeze proteins (AFPs) facilitate the survival of organisms in cold climates by inhibiting the growth and/or recrystallization of ice. To function, AFPs must first bind to ice crystals; bound AFPs must then resist engulfment by using their nonbinding side (NBS) to pin the ice–water interface. Here, we seek to understand how the molecular characteristics of an NBS, such as its ice-phobicity or shape, influence its ability to resist engulfment. By characterizing the free energy barriers that impede the engulfment of model AFPs, we find that the critical supercooling ΔT*, above which an AFP is engulfed, is dictated by an optimal pinning site on the NBS. We further find that the optimal pinning site is determined by an interplay between the contact line perimeter P and a pinning efficiency η, with ΔT* ∝ ηP at the optimal pinning site. For a hemispherical AFP, which displays progressively inward tapering, we find that η increases during engulfment, whereas P decreases; conversely, an NBS with outward tapering can achieve high P, but it suffers from low η. Because the product of η and P determines ΔT*, the inverse correlation between them limits ΔT. To circumvent such limiting behavior, we propose an NBS shape with an outward bulge; by initially tapering outward, a bulged NBS permits higher P, and by subsequently tapering inward, it promotes high η as well. Importantly, we find that ΔT* is enhanced by more than a factor of 2 with an outward bulge of only 1 nm. We also find that the more ice-phobic an NBS is, the more efficiently it pins the ice–water interface, resulting in a higher ΔT. Furthermore, our findings shed light on how the NBS molecular characteristics influence ΔT* and suggest strategies for engineering the NBS to optimally resist engulfment by ice.
Antifreeze↗
BEYONDPLANCK VI. Noise characterization and modeling
We present a Bayesian method for estimating instrumental noise parameters and propagating noise uncertainties within the global BeyondPlanck Gibbs sampling framework, and apply this to Planck Low Frequency Instrument (LFI) time-ordered data. Following previous literature, we initially adopt a 1/ f model for the noise power spectral density (PSD), but find the need for an additional lognormal component in the noise model for the 30 and 44 GHz bands. We implement an optimal Wiener-filter (or constrained realization) gap-filling procedure to account for masked data. We then use this procedure to both estimate the gapless correlated noise in the time-domain, n corr , and to sample the noise PSD parameters, ξ n = {σ 0 , f knee , α, A p }. In contrast to previous Planck analyses, we assume piecewise stationary noise only within each pointing period (PID), not throughout the full mission, but we adopt the LFI Data Processing Center (DPC) results as priors on α and f knee . On average, we find best-fit correlated noise parameters that are mostly consistent with previous results, with a few notable exceptions. However, a detailed inspection of the time-dependent results reveals many important findings. First and foremost, we find strong evidence for statistically significant temporal variations in all noise PSD parameters, many of which are directly correlated with satellite housekeeping data. Second, while the simple 1/ f model appears to be an excellent fit for the LFI 70 GHz channel, there is evidence for additional correlated noise not described by a 1/ f model in the 30 and 44 GHz channels, including within the primary science frequency range of 0.1–1 Hz. In general, most 30 and 44 GHz channels exhibit deviations from 1/ f at the 2–3σ level in each one hour pointing period, motivating the addition of the lognormal noise component for these bands. For some periods of time, we also find evidence of strong common mode noise fluctuations across the entire focal plane. Overall, we conclude that a simple 1/ f profile is not adequate to fully characterize the Planck LFI noise, even when fitted hour-by-hour, and a more general model is required. These findings have important implications for large-scale CMB polarization reconstruction with the Planck LFI data, and the current work is a first attempt at understanding and mitigating these issues.
79 ASTRONOMY AND ASTROPHYSICS↗
Coupled laboratory and field investigations resolve microbial interactions that underpin persistence in hydraulically fractured shales
Hydraulic fracturing is one of the industrial processes behind the surging natural gas output in the United States. This technology inadvertently creates an engineered microbial ecosystem thousands of meters below Earth’s surface. Here, we used laboratory reactors to perform manipulations of persisting shale microbial communities that are currently not feasible in field scenarios. Metaproteomic and metabolite findings from the laboratory were then corroborated using regression based modeling performed on metagenomic and metabolite data from more than 40 produced fluids from five hydraulically fractured shale wells. Collectively, our findings show that Halanaerobium, Geotoga, and Methanohalophilius strain abundances predict a significant fraction of nitrogen and carbon metabolites in the field. Our laboratory findings also exposed cryptic predatory, cooperative, and competitive interactions that impact microorganisms across fractured shales. Scaling these results from the laboratory to the field identified mechanisms underpinning biogeochemical reactions, yielding knowledge that can be harnessed to potentially increase energy yields and inform management practices in hydraulically fractured shales.
hydraulic fracturing, metaproteomics, methanogenes↗
The Atacama Cosmology Telescope: DR6 constraints on extended cosmological models
We use new cosmic microwave background (CMB) primary temperature and polarization anisotropy measurements from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) to test foundational assumptions of the standard cosmological model, ΛCDM, and set constraints on extensions to it. We derive constraints from the ACT DR6 power spectra alone, as well as in combination with legacy data from the Planck mission. To break geometric degeneracies, we include ACT and Planck CMB lensing data and baryon acoustic oscillation data from DESI Year-1. To test the dependence of our results on non-ACT data, we also explore combinations replacing Planck with WMAP and DESI with BOSS, and further add supernovae measurements from Pantheon+ for models that affect the late-time expansion history. We verify the near-scale-invariance (running of the spectral index dn s /d ln k = 0.0062 ± 0.0052) and adiabaticity of the primordial perturbations. Neutrino properties are consistent with Standard Model predictions: we find no evidence for new light, relativistic species that are free-streaming (N eff = 2.86 ± 0.13, which combined with astrophysical measurements of primordial helium and deuterium abundances becomes N eff = 2.89 ± 0.11), for non-zero neutrino masses (∑m ν < 0.089 eV at 95% CL), or for neutrino self-interactions. We also find no evidence for self-interacting dark radiation (N idr < 0.134), or for early-universe variation of fundamental constants, including the fine-structure constant (α EM /α EM,0 = 1.0043 ± 0.0017) and the electron mass (m e /m e,0 = 1.0063 ± 0.0056). Our data are consistent with standard big bang nucleosynthesis (we find Y p = 0.2312 ± 0.0092), the COBE/FIRAS-inferred CMB temperature (we find T CMB = 2.698 ± 0.016 K), a dark matter component that is collisionless and with only a small fraction allowed as axion-like particles, a cosmological constant (w = -0.986 ± 0.025), and the late-time growth rate predicted by general relativity (γ = 0.663 ± 0.052). We find no statistically significant preference for a departure from the baseline ΛCDM model. In fits to models invoking early dark energy, primordial magnetic fields, or an arbitrary modified recombination history, we find H 0 = 69.9 +0.8 -1.5 , 69.1 ± 0.5, or 69.6 ± 1.0 km/s/Mpc, respectively; using BOSS instead of DESI BAO data reduces the central values of these constraints by 1–1.5 km/s/Mpc while only slightly increasing the error bars. In general, models introduced to increase the Hubble constant or to decrease the amplitude of density fluctuations inferred from the primary CMB are not favored over ΛCDM by our data.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
A generative graph model for electrical infrastructure networks
We propose a generative graph model for electrical infrastructure networks that accounts for heterogeneity in both node and edge type. To inform the design of this model, we analyze the properties of power grid graphs derived from the U.S. Eastern Interconnection, Texas Interconnection, and Poland transmission system power grids. Across these datasets, we find subgraphs induced by nodes of the same voltage level exhibit shared structural properties atypical to small-world networks, including low local clustering, large diameter and large average distance. On the other hand, we find subgraphs induced by transformer edges linking nodes of different voltage types contain a more limited structure, consisting mainly of small, disjoint star graphs. The goal of our proposed model is to match both these inter and intra-network properties by proceeding in two phases: we first generate subgraphs for each voltage level and then generate transformer edges that connect these subgraphs. The first phase of the model adapts the Chung-Lu random graph model, taking desired vertex degrees and desired diameter as inputs, while the second phase of the model is based on a simpler random star graph generation process. We test the performance of our model by comparing its output across many runs to the aforementioned real data. In nearly all categories tested, we find our model is more accurate in reproducing the unusual mixture of properties apparent in the data than the Chung-Lu model. We also include graph visualization comparisons, as well as a brief analysis of edge-deletion resiliency. Ultimately, our model may be used to generate synthetic graph data, test hypotheses and algorithms at different scales, and serve as a baseline model on top of which further electrical network properties, device models, and interdependencies to other networks, may be appended.
24 POWER TRANSMISSION AND DISTRIBUTION↗