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At least 1,405 records · Page 78

Learning Optimal Solutions for Extremely Fast AC Optimal Power Flow

We develop, in this paper, a machine learning approach to optimize the real-time operation of electric power grids. In particular, we learn feasible solutions to the AC optimal power flow (OPF) problem with negligible optimality gaps. The AC OPF problem aims at identifying optimal operational conditions of the power grids that minimize power losses and/or generation costs. Due to the computational challenges with solving this nonconvex problem, many efforts have focused on linearizing or approximating the problem in order to solve the AC OPF on faster timescales. However, many of these approximations can be fairly poor representations of the actual system state and still require solving an optimization problem, which can be time consuming for large networks. In this work, we learn a mapping between the system loading and optimal generation values, enabling us to find near-optimal and feasible AC OPF solutions. This allows us to bypass solving the traditionally nonconvex AC OPF problem, resulting in a significant decrease in computational burden for grid operators.

machine learning↗

Solar prominences in the extreme ultraviolet as observed from the Apollo Telescope Mount

Observations of quiescent solar prominences with the Harvard College Observatory spectrometer aboard Skylab show that prominence material is optically thick in the Lyman alpha line and the Lyman continuum. The color temperature of the Lyman continuum has a mean of 6600 K and an upward gradient toward the top of the prominence. The departure coefficient of the ground state of hydrogen is found to be of the order of unity, as expected from theory. The optical depth of the C III sheath region is determined directly from the observation of the limb through the prominence and is used to infer the mean electron density and the temperature gradient of the sheath. The result implies that the sheath density is about 0.4, and the temperature gradient about 1.4 times the respective value in the C III transition zone of the quiet sun. The C III triplet-singlet ratio for the prominence is found to give a density compatible, within the uncertainty of the atomic parameters, with the density obtained from the optical depth.

Schmahl, E. J.↗

Thermal boundary conductance between high thermal conductivity boron arsenide and silicon

Thermal boundary conductance (TBC) is important for heat dissipation in light-emitting diodes (LEDs). In this study, we predicted the TBC between the high thermal conductivity boron arsenide (BAs) and silicon (Si) by nonequilibrium molecular dynamics (MD) simulations. From the thermal conductivity accumulation function with respect to phonon frequency, the dominant phonon frequencies for heat conduction in BAs are extremely different from those in Si. However, our nonequilibrium MD simulations indicated that the TBC of the BAs/Si interface was still high compared to most other interfaces, even though there was a major frequency mismatch in the thermal conductivity accumulation function between BAs and Si. The primary reason for the high TBC is the overlap of phonon density of states between BAs and Si in the frequency range of 5–8 THz. The range of predicted TBC of the BAs/Si interface was between 200 and 300 MW/m2 K in the temperature range of 300–700 K, and the values of the TBC were not sensitive to the temperature. We also found that the TBCs in Si/BAs and Si/Ge interfaces were close to each other considering the simulation uncertainty. This work indicates BAs as an excellent material for heat dissipation across the interfaces.

Wei, Zhiyong (ORCID:000000018686451X)↗

Analysis of the Range and Range Rate Tracking System

The "range and range rate"' (r(sub i) + r(sub i)) system in its very simplest form is described. In particular, the errors in position and velocity are treated using pessimistic values of the measured quantities r(sub i) and r(sub i). Thus, a realistic evaluation of tracking qualities can be made for different orbits over certain tracking stations. The range and range rate system briefly described in this paper is a high-precision tracking system. Knowledge of the uncertainty in position δ(sub xi) is important, but knowledge of the uncertainty of the velocity vector δ(sub xi) is of the utmost importance. Thus the use of coherent Doppler measurements to determine the velocity has a great advantage over any pulsed system and, in addition, permits extremely narrow frequency bandwidths (in the order of 10 to 100 cps) to be employed, reducing the power requirements considerably. The basis for using range r(sub i) and range rate r(sub i) only is the fact that r(sub i) and r(sub i) can be measured to very high precision, thus furnishing r and r with low errors. The nature of these errors is discussed.

Vonbun, F. O.↗

Pressure correlations at a fluid/structure interface

The structure of pressure-pressure correlations at the interface of an incompressible steady-state turbulent flow with a rigid boundary was investigated. For the sake of completeness, the absolute value of the correlation between two random varying functions is herein defined as a number greater than or equal to zero and less than or equal to unity which is a measure of that fraction of one of the functions that 'follows' the second function (or vice versa). It was found that the soughtafter correlations can be determined by consideration of the high Re Navier-Stokes equation, but that the complexity of boundary layer turbulence, in particular the inhomogeneity perpendicular to the boundary and the anisotropy due to convective flow gradients, makes the structure of said correlations extremely difficult to assess. One of the earlier researchers in this field described the quantity under present consideration as 'a quantity which is beyond assessment.' Nonetheless, it was found that under some rather simplifying assumptions the determination of the required structure necessitates the formulation of the related structure of second order two-point correlations of turbulent velocity gradients, as well as third order two-point correlations of velocity gradients. The presence of these latter gradients is due to the nonlinearity in the turbulence ('turbulence self-interaction'). Both of these correlations are scaled, although not similarly, by factors dependent upon the magnitude of the convective flow, which can be modeled using a log law approximation. Fourth order correlations, although present, can be ignored, since they constitute 'higher order terms.' In a slightly more complex situation, it was found that convective flow gradients also have to be incorporated. At the moment, no definitive algebraic information peculiar to pressure-pressure correlations is available in the most highly idealized cases.

Trevino, George↗

Learning Optimal Solutions for Extremely Fast AC Optimal Power Flow: Preprint

We develop, in this paper, a machine learning approach to optimize the real-time operation of electric power grids. In particular, we learn feasible solutions to the AC optimal power flow (OPF) problem with negligible optimality gaps. The AC OPF problem aims at identifying optimal operational conditions of the power grids that minimize power losses and/or generation costs. Due to the computational challenges with solving this nonconvex problem, many efforts have focused on linearizing or approximating the problem in order to solve the AC OPF on faster timescales. However, many of these approximations can be fairly poor representations of the actual system state and still require solving an optimization problem, which can be time consuming for large networks. In this work, we learn a mapping between the system loading and optimal generation values, enabling us to find near-optimal and feasible AC OPF solutions. This allows us to bypass solving the traditionally nonconvex AC OPF problem, resulting in a significant decrease in computational burden for grid operators.

machine learning↗

Graph neural networks for mechanical property prediction of 2D fiber composites

This work investigates the ability of graph neural networks (GNNs) to homogenize 2D fiber composite microstructures. We use different inhomogeneity and anisotropy indices to motivate and show that the Volume Elements (VEs) used in ML methods should ideally be far from their Representative Volume Element (RVE) size limit and, consequently, are notably anisotropic. Hence, training only the isotropic limit properties may not be acceptable. Another aspect is the need to normalize elastic stiffness values for ML, especially when high elastic contrast ratios are encountered between composite phases or in the material set. We introduce a normalization technique based on the mean-field method (MFM) to handle such high contrast ratios and train for the entire stiffness tensor. We show that the proposed GNN approaches exhibit high accuracy and efficiency compared to traditional methods and convolutional neural networks, utilizing unstructured graphs constructed from microstructure topology. Our model successfully predicts the stiffness tensor, peak strength under bulk damage, and brittle fracture initiation strength across diverse microstructure configurations while maintaining high accuracy even for extreme material contrasts and volume fractions. We also present a method to improve prediction accuracy for small dataset sizes using Voronoi partitioning.

Brittle strength↗

Role of Intense Arctic Storm in Accelerating Summer Sea Ice Melt: An In Situ Observational Study

Abstract Intense storms have been more frequently observed in the Arctic during recent years, in coincidence with extreme sea ice loss events. However, it is still not fully understood how storms drive such events due to deficient observations and modeling discrepancies. Here we address this problem by analyzing in situ observations acquired during an Arctic expedition, which uniquely captured an intense storm in summer 2016. The result shows a pronounced acceleration of sea ice loss during the storm process. Diagnostic analysis indicates a net energy loss at the ice surface, not supporting the accelerated melting. Although the open water surface gained net heat energy, it was insufficient to increase the mixed‐layer temperature to the observed values. Dynamic analysis suggests that storm‐driven increase in ocean mixing and upward Ekman pumping of the Pacific‐origin warm water tremendously increased oceanic heat flux. The thermal advection by the Ekman pumping led to a warmed mixed layer by 0.05°C–0.12°C and, in consequence, an increased basal sea ice melt rate by 0.1–1.7 cm day −1 .

58 GEOSCIENCES↗

Laboratory Studies of Fischer-Tropsch-Type Reactions and Their Implications for Organics in Asteroids and Comets

We have been studying Fischer-Tropsch type (FTT) reactions as a source for organic materials both in the gas phase of the solar nebula and incorporated into primitive comets and asteroids for almost 10 years, and over this time our concept has evolved greatly from the standard "catalytic" model to a much more robust chemical scenario. Our simulations have been conducted at temperatures that are much higher than we like, primarily for practical reasons such as the timescale of individual reactions, and we are just starting a series of measurements to allow us to measure reaction rates at temperatures from 873K down to as low as 373K. We have preliminary data on the carbon (d13C = -50) & nitrogen (d15N = +9.5) isotopic fractionation at 873K, but not on materials produced at lower temperature. Isotope values are on the VPDB scale for carbon and vs. Air for nitrogen. We have also investigated the noble gas trapping efficiency of the FTT process by adding a small amount of a noble gas mix to our standard synthesis mix. The noble gas ratio is 49:49:1:1::Ne:Ar:Kr:Xe. Xe and Kr are trapped at 873K and are more efficiently trapped at 673K with no isotopic fractionation at either temperature. Ar trapping is detected at 673K, but not at 873K. Ne has not yet been observed in our samples. The solar nebula was an extremely complex system, mixing materials from the innermost regions out to well into the zones where comets formed and thus mixing highly processed nebular materials with grains and coatings formed before the nebula began to collapse. Laboratory studies may provide the means to separate such diverse components based on carbon or nitrogen isotopic fractionation or the quantities of noble gases trapped in grain coatings and their thermal release patterns, among other observables. The ultimate goal of laboratory synthesis of nebular analogs is to provide the means to identifY the conditions under which natural samples were formed and the signatures of subsequent metamorphic events.

Nuth, Joseph↗

Method of Using Power Grid as Large Antenna for Geophysical Imaging

A high-voltage power transmission system is used as an extremely large antenna to extract spatiotemporal space, physical, and geological information from geomagnetically induced currents (GIC). A differential magnetometer method is used to measure GIC and involves acquiring line measurements from a first fluxgate magnetometer under a high-voltage transmission line, acquiring natural field measurements from a reference magnetometer nearby but not under the transmission line, subtracting the natural field measurements from the line measurements, and determining the GIC-related Biot-Savart field from the difference. NASA warning and alarm systems can be triggered based on determinations of GIC amplitude levels that exceed a set threshold value.

Pulkkinen, Antti A.↗

Assessing the Needs of NASA's Near Real-Time Earth Observation Products

"The 2017-2027 Decadal Survey for Earth Science and Applications from Space stated that NASA's Earth Science with planned implementation of applications provides sustained earth observations for societal benefits [1]. The Decadal Survey indicated that data latency is invaluable for time-sensitive applications including disaster risk reduction, wildland fire carbon emissions quantification, real-time measurements of the state of the hydrologic systems and many more. Data latency refers to the time between earth observation and data products available to users. During the past 13 years, NASA's Land, Atmosphere Near Real-Time Capability for Earth Observing Systems (LANCE) continues to provide free access to earth observation products that are made available much quicker than routine processing allows. The latency of most LANCE data products is Near Real-time (NRT) which is defined as less than three hours from satellite observations [2]. LANCE is managed by the Earth Science Data and Information System (ESDIS) Project at NASA Goddard Space Flight Center [3], and a User Working Group (UWG) is responsible for providing guidance to LANCE. LANCE data are used by direct users and brokers who add value to the data [4]. NASA Earth Applied Sciences Program (ASP) is one of the primary users of LANCE, which collaborates with partner organizations and provides support to scientists to solve problems in applications of earth observations. ASP promotes the use of LANCE NRT data products to demonstrate applications in decision making, facilitates end-user feedback to the science team to improve data products, and provides information on future demands for research. LANCE supports applications that need a rapid response including detecting wildland fires and volcanic eruptions, tracking smoke, ash and dust plumes, monitoring air quality and tracking extreme weather events such as hurricanes, landslides, and floods. To gather feedback regarding the availability, accessibility and actionability of NASA's NRT data products for societal benefit, three surveys and a few discussions with experts involved in the topic within ASP were conducted from the perspective of users. Feedback has been collected from users who are interested in using low latency NASA data within application communities of agriculture, disasters, water resources, health and air quality, ecological conservation, wildland fires and capacity building. Analysis-ready NRT data products in a variety of formats have been mentioned many times in the collected feedback, especially for applied users with little to no experience using research-grade earth observation products. Users prefer to have products that can be easily integrated into their existing workflows and take their analysis to the data. HDF5 is a commonly used data format for research, but typically requires some conversion to a more friendly format for applications and regular use in decision-making. Users prefer the GeoTIFF data format that can be directly ingested into a GIS mapping software and platform for data analysis and visualization. For example, LANCE’s fire, flood, SO2 and Black Marble Nighttime Blue/Yellow Composite data products have been integrated into NASA Disasters Mapping Portal, which is an GIS-based open data portal, for users in the disaster management community. There are 291 LANCE NRT layers available through GIBS and Worldview, where users can download a snapshot in GeoTIFF format. Operational users expect data to be processed as close to the user as possible. The collected feedback indicates that LANCE fire products within 3 hours latency would meet the needs of the wildland fire community. The ideal latency for volcanic application is 10-15 minutes. Users in Volcanic Ash Advisory Centers (VAAC) reported that the first forecast volcanic product should be issued within 75 minutes from the volcano eruption [5]. Overall, for disaster applications, data latency within 3 hours is useful while latency greater than 12 hours is not timely enough for operational use. Capacity building and training are critical for users to be able to access, interpret and use data products and tools for their decision making, especially for applied users with limited experience using earth observation products. LANCE data products have been used in a number of capacity building projects domestically and internationally [6]. As LANCE continues to bring new products into the system, users request training to utilize LANCE new and upcoming data products and capabilities in their applications. Due to the limitation of bandwidth and downstream flow paths, users in some developing countries need tools to select and download data for a specific area of interest instead of bulk downloads. The collected feedback also shows the lack of available SAR satellite low latency data products. The advantages of SAR to monitor conditions and changes on the ground through darkness, clouds, volcanic ash, and other atmospheric conditions, are appealing to low latency users. For example, terabytes of low latency but cloudy optical images are not helpful in rapidly identifying the extent of flood or fire impacts. LANCE could be complemented with low latency measurements via the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission [7]. Requests for higher spatial resolution products are expressed. A user from the wildland fire management community reported that products with 30-m spatial resolution could be used to detect small fires. The 30-m Landsat OLI fire data is now part of NASA’s Fire Information for Resource Management System (FIRMS) US/Canada [8]. Within the open and free NASA resources, LANCE disseminates NRT data products in a manner that allows them to be accessible and understandable to both scientific and applied users. In many application areas, latency plays an important or even decisive role where low latency earth observations help people to observe areas of interest, detect and track changes in the environment and make timely decisions. NASA’s Earth Applied Sciences Program promotes the use of LANCE NRT products and builds a bridge between application users and research teams. The collected feedback indicates data latency within 3 hours is useful for most of the applications, and shows the needs of user-friendly, analysis-ready products, and requests training on LANCE’s new and upcoming data products. User feedback has been provided to LANCE UWG for guidance and recommendations, and for translating findings into something actionable.

Tian Yao↗

Machine learning maximized Anderson localization of phonons in aperiodic superlattices

Nanostructuring materials to achieve ultra-low lattice thermal conductivity has proven to be extremely attractive for numerous applications such as thermoelectric energy conversion. Anderson localization of phonons due to aperiodicity can reduce thermal conductivity in superlattices, but the lower limit of thermal conductivity remains elusive due to the prohibitively large design space. In this work, we demonstrate that an intuition-based manual search for aperiodic superlattice structures (random multilayers or RMLs) with the lowest thermal conductivity yields only a local minimum, while a genetic algorithm (GA) based approach can efficiently identify the globally minimum thermal conductivity by only exploring a small fraction of the design space. Our results show that this minimum value occurs at an average RML period that is, surprisingly, smaller than the period corresponding to the minimum SL thermal conductivity. Interestingly, above this critical period, scattering of incoherent phonons at interfaces is less, whereas below this period, the room for randomization becomes less, thus putting more coherent phonons out of Anderson localization and causing increased thermal conductivity. Moreover, the lower limit of the thermal conductivity occurs at a moderate rather than maximum randomness of the layer thickness. Our machine learning approach demonstrates a general process of exploring an otherwise prohibitively large design space to gain non-intuitive physical insights.

42 ENGINEERING↗

Mn(Pt 1–x Pd x ) 5 P: Isovalent tuning of Mn-sublattice magnetic order

Here, e report the growth and characterization of MnPd 5 P, a rare-earth-free ferromagnet, with T C ≈ 295 K and planar anisotropy, and conduct a substitutional study with its antiferromagnetic analogue MnPt 5 P. We provide a solution route to grow large single crystals of MnPd 5 P and the series Mn(Pt 1–x Pd x ) 5 P by adding Mn into Pd-P and (Pt 1–x Pd x )-P based melts. All compounds in the family adopt the layered anti-CeCoIn5 type structure with the space group P4/mmm, and EDS and X-ray diffraction results indicate that MnPt 5 P and MnPd 5 P form a complete solid solution. Based on measurements of the temperature- and field-dependent magnetization and resistance, we construct a temperature-composition (T-x) phase diagram for Mn(Pt 1–x Pd x ) 5 P and demonstrate that the initial antiferromagnetic order found in MnPt 5 P is extraordinarily sensitive to Pd substitution. At low Pd fractions (x < 0.010), the single antiferromagnetic transition in pure MnPt 5 P splits into a higher temperature ferromagnetic transition followed first, upon cooling, by a lower temperature ferromagnetic to antiferromagnetic transition and then by a re-entrant antiferromagnetic to ferromagnetic transition at even lower temperatures. The antiferromagnetic region makes up a bubble phase that persists up to x ≈ 0.008-0.009 for T ≈ 150 K, with all samples x < 0.008 recovering their initial ferromagnetic state upon further cooling to base temperature. Over the same low substitution range we find a non-monotonic change in the room temperature value of the unit cell volume, further suggesting that pure MnPt 5 P is very close to an instability. Once x > 0.010, Mn(Pt 1–x Pd x ) 5 P undergoes a only single transition into the ferromagnetic phase. The Curie temperature initially increases rapidly with x, rising from T C ≈ 197 K at x = 0.013 to a maximum of T C ≈ 312 K for x ≈ 0.62, and then falling back to T C ≈ 295 K for pure MnPd 5 P (x = 1.00). Given that Pt and Pd are isoelectronic, this work raises questions as to the origin of the extreme sensitivity of the magnetic ground state in MnPt 5 P upon introducing Pd.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Air Pollution Scenario over Pakistan: Characterization and Ranking of Extremely Polluted Cities using Long-Term Concentrations of Aerosols and Trace Gases

Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectroradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used. For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 μg/cu. m, over all Pakistan from 2003 to 2020. This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 μg/cu. m annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 <35 μg/cu. m). The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan’s air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries. Statistically significant positive (increasing) trends in PM1, PM2.5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in ~89%, ~67%, ~48%, 91%, and ~88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.

Muhammad Bilal↗

The Extreme Spin of the Black Hole Cygnus X-1

Remarkably, an astronomical black hole is completely described by the two numbers that specify its mass and its spin. Knowledge of spin is crucial for understanding how, for example, black holes produce relativistic jets. Recently, it has become possible to measure the spins of black holes by focusing on the very inner region of an accreting disk of hot gas orbiting the black hole. According to General Relativity (GR), this disk is truncated at an inner radius 1 that depends only on the mass and spin of the black hole. We measure the radius of the inner edge of this disk by fitting its continuum X-ray spectrum to a fully relativistic model. Using our measurement of this radius, we deduce that the spin of Cygnus X-1 exceeds 97% of the maximum value allowed by GR.

Gou, Lijun↗

First saturation correction in high energy proton-nucleus collisions. Part III. Ensemble averaging

In high energy proton-nucleus collisions, the gluon saturation effects from the nucleus are fully incorporated into the light-like Wilson lines. The gluon saturation effects from the proton, which are anticipated to be important either in the extreme high energy limit or towards the dense-dense (nucleus-nucleus) collision regimes, have been studied perturbatively within the Color Glass Condensate effective theory in previous papers of this series. A configuration-by-configuration expression for the single inclusive semi-hard gluon production including the first saturation correction was obtained. In this paper, we perform ensemble averaging in the McLerran-Venugopalan model and the Dipole Approximation. We find that, in the saturation correction, the effects of the initial state interactions are negligible while the final state interactions play most important role and give a positive-valued contribution to the semi-hard gluon spectrum. Furthermore, we show that the single gluon spectrum scales approximately 1/$k$$^{4}_{⊥}$ at small k ⊥ , suggesting that a resummation of higher order saturation corrections is required to regulate the infrared region of the gluon spectrum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Planck 2018 results: III. High frequency instrument data processing and frequency maps

This paper presents the High Frequency Instrument (HFI) data processing procedures for the Planck 2018 release. Major improvements in mapmaking have been achieved since the previous Planck 2015 release, many of which were used and described already in an intermediate paper dedicated to the Planck polarized data at low multipoles. These improvements enabled the first significant measurement of the reionization optical depth parameter using Planck-HFI data. This paper presents an extensive analysis of systematic effects, including the use of end-to-end simulations to facilitate their removal and characterize the residuals. The polarized data, which presented a number of known problems in the 2015 Planck release, are very significantly improved, especially the leakage from intensity to polarization. Calibration, based on the cosmic microwave background (CMB) dipole, is now extremely accurate and in the frequency range 100-353 GHz reduces intensity-to-polarization leakage caused by calibration mismatch. The Solar dipole direction has been determined in the three lowest HFI frequency channels to within one arc minute, and its amplitude has an absolute uncertainty smaller than 0.35 μK, an accuracy of order 10 -4 . This is a major legacy from the Planck HFI for future CMB experiments. The removal of bandpass leakage has been improved for the main high-frequency foregrounds by extracting the bandpass-mismatch coefficients for each detector as part of the mapmaking process; these values in turn improve the intensity maps. This is a major change in the philosophy of "frequency maps", which are now computed from single detector data, all adjusted to the same average bandpass response for the main foregrounds. End-to-end simulations have been shown to reproduce very well the relative gain calibration of detectors, as well as drifts within a frequency induced by the residuals of the main systematic effect (analogue-to-digital convertor non-linearity residuals). Using these simulations, we have been able to measure and correct the small frequency calibration bias induced by this systematic effect at the 10 -4 level. There is no detectable sign of a residual calibration bias between the first and second acoustic peaks in the CMB channels, at the 10 -3 level.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of the ''Range and Range Rate'' Tracking System

The "Range and Range Rate" (r(sub j) + r ̇(sub j)) System in its very simplest form is described. In particular, the errors in position and velocity are treated usingpessimistic values of the measured quantities r(sub j) and r ̇(sub j). Thus, a realistic evaluation of tracking qualities can be made for different orbits over certain tracking stations. The Range and Range Rate System briefly described in this report is a high precision tracking system. Knowledge of the uncertainty in position δ (sub x(sub i) is important, but knowledge of the uncertainty of the velocity vector δ (sub x(sub i) is of the utmost importance. Thus the use of coherent Doppler measurements to determine the velocity has a great advantage over any pulsed system and, in addition, permits extremely narrow frequency bands (in the order of 10 to 100 cps) to be employed, reducing the power requirements considerably. The basis for using range r(sub j) and range rate r ̇(sub j) only is the fact that r(sub j) and r ̇(sub j) can be measured to very high precision, thus furnishing r and r with low errors. The nature of these errors is discussed.

Tracking system↗