Generation and reduction of the data for the Ulysses gravitational wave experiment

A procedure for the generation and reduction of the radiometric data known as REGRES is described. The software is implemented on a HP-1000F computer and was tested on REGRES data relative to the Voyager I spacecraft. The REGRES data are a current output of NASA's Orbit Determination Program. The software package was developed in view of the data analysis of the gravitational wave experiment planned for the European spacecraft Ulysses

The dependence of test-mass thermal noises on beam shape in gravitational-wave interferometers

In second-generation, ground-based interferometric gravitational-wave detectors such as Advanced LIGO, the dominant noise at frequencies $f \sim 40$ Hz to $\sim 200$ Hz is expected to be due to thermal fluctuations in the mirrors' substrates and coatings which induce random fluctuations in the shape of the mirror face. The laser-light beam averages over these fluctuations; the larger the beam and the flatter its light-power distribution, the better the averaging and the lower the resulting thermal noise. In semi-infinite mirrors, scaling laws for the influence of beam shape on the four dominant types of thermal noise (coating Brownian, coating thermoelastic, substrate Brownian, and substrate thermoelastic) have been suggested by various researchers and derived with varying degrees of rigour. Because these scaling laws are important tools for current research on optimizing the beam shape, it is important to firm up our understanding of them. This paper (1) gives a summary of the prior work and of gaps in the prior analyses, (2) gives a unified and rigorous derivation of all four scaling laws, and (3) explores, relying on work by J. Agresti, deviations from the scaling laws due to finite mirror size.Comment: 25 pages, 10 figures, submitted to Class. Quantum Gra

Moessbauer Spectroscopy of Martian and Sverrefjell Carbonates

Mars, in its putative "warmer, wetter: early history, could have had a CO2 atmosphere much denser than its current value of <10 mbar. The question of where all this early CO2 has gone has long been debated. Now, several instruments on Mars Exploration Rover (MER) Spirit, including its Moessbauer spectrometer MIMOS II, have identified Mg-Fe carbonate in rock outcrops at Comanche Spur in the Columbia Hills of Gusev Crater. With this finding, carbonate cements in volcanic breccia collected on Sverrefjell Volcano on Spitzbergen Island in the Svalbard Archipelago (Norway) during the AMASE project are mineralogical and possible process analogues of the newly discovered martian carbonate. We report further analyses of Mossbauer spectra from Comanche Spur and discuss their relationship to Mossbauer data acquired on Sverrefjell carbonates. The spectra were velocity calibrated with MERView and fit using MERFit. Instead of the "average temperature" Comanche spectrum (data from all temperature windows summed), we refit the Comanche data for QS within each temperature window, modeling as doublets for Fe2+(carbonate), Fe2+(olivine), and Fe3+(npOx). The temperature dependences of QS for the Comanche carbonate and for a low-Ca carbonate from Chocolate Pots in Yellowstone National Park (YNP) are shown; they are the same within error. For Comanche carbonate summed over 210-270 K, (CS, QS) = (1.23, 1.95) mm/s. The value of QS for Sverrefjell carbonate at 295 K, (CS, QS) = (1.25, 1.87) mm/s, is also plotted, and the plot shows that the QS for the Sverrefjell carbonate agrees within error with the Comanche data extrapolated to 295 K. This agreement is additional evidence that the Sverrefjell carbonates are Mossbauer analogues for the Comanche carbonates, and that both carbonates might have precipitated from solutions that became carbonate rich by passing through buried carbonate deposits

Mineralogy of SNC Meteorite EET79001 by Simultaneous Fitting of Moessbauer Backscatter Spectra

We have acquired M ssbauer spectra for SNC meteorite EET79001 with a MIMOS II backscatter M ssbauer spectrometer [1] similar to those now operating on Mars as part of the Mars Exploration Rover (MER) missions. We are working to compare the Fe mineralogical composition of martian meteorites with in-situ measurements on Mars. Our samples were hand picked from the >1 mm size fraction of saw fines on the basis of lithology, color, and grain size (Table 1). The chips were individually analyzed at approx.300K by placing them on a piece of plastic that was in turn supported by the contact ring of the instrument (oriented vertically). Tungsten foil was used to mask certain areas from analysis. As shown in Figure 1, a variety of spectra was obtained, each resulting from different relative contributions of the Fe-bearing minerals present in the sample. Because the nine samples are reasonably mixtures of the same Fe-bearing phases in variable proportions, the nine spectra were fit simultaneously (simfit) with a common model, adjusting parameters to a single minimum chi-squared convergence criterion [2]. The starting point for the fitting model and values of hyperfine parameters was the work of Solberg and Burns [3], who identified olivine, pyroxene, and ferrous glass as major, and ilmenite and a ferric phase as minor (<5%), Fe-bearing phases in EET79001

Measuring software technology

Results are reported from a series of investigations into the effectiveness of various methods and tools used in a software production environment. The basis for the analysis is a project data base, built through extensive data collection and process instrumentation. The project profiles become an organizational memory, serving as a reference point for an active program of measurement and experimentation on software technology

Unsupervised domain adaptation for mobile semantic segmentation based on cycle consistency and feature alignment

The supervised training of deep networks for semantic segmentation requires a huge amount of labeled real world data. To solve this issue, a commonly exploited workaround is to use synthetic data for training, but deep networks show a critical performance drop when analyzing data with slightly different statistical properties with respect to the training set. In this work, we propose a novel Unsupervised Domain Adaptation (UDA) strategy to address the domain shift issue between real world and synthetic representations. An adversarial model, based on the cycle consistency framework, performs the mapping between the synthetic and real domain. The data is then fed to a MobileNet-v2 architecture that performs the semantic segmentation task. An additional couple of discriminators, working at the feature level of the MobileNet-v2, allows to better align the features of the two domain distributions and to further improve the performance. Finally, the consistency of the semantic maps is exploited. After an initial supervised training on synthetic data, the whole UDA architecture is trained end-to-end considering all its components at once. Experimental results show how the proposed strategy is able to obtain impressive performance in adapting a segmentation network trained on synthetic data to real world scenarios. The usage of the lightweight MobileNet-v2 architecture allows its deployment on devices with limited computational resources as the ones employed in autonomous vehicles

Interface engineering for perovskite solar cells based on 2d‐materials: A physics point of view

The last decade has witnessed the advance of metal halide perovskites as a promising low-cost and efficient class of light harvesters used in solar cells (SCs). Remarkably, the efficiency of lab-scale perovskite solar cells (PSCs) reached a power conversion efficiency of 25.5% in just similar to 10 years of research, rivalling the current record of 26.1% for Si-based PVs. To further boost the performances of PSCs, the use of 2D materials (such as graphene, transition metal dichalcogenides and transition metal carbides, nitrides and carbonitrides) has been proposed, thanks to their remarkable optoelectronic properties (that can be tuned with proper chemical composition engineering) and chemical stability. In particular, 2D materials have been demonstrated as promising candidates for (i) accelerating hot carrier transfer across the interfaces between the perovskite and the charge extraction layers; (ii) improving the crystallization of the perovskite layers (when used as additives in the precursor solution); (iii) favoring electronic bands alignment through tuning of the work function. In this mini-review, we discuss the physical mechanisms underlying the increased efficiency of 2D material-based PSCs, focusing on the three aforementioned effects

Advances in Perovskites for Photovoltaic Applications in Space

Perovskites have emerged as promising light harvesters in photovoltaics. The resulting solar cells (i) are thin and lightweight, (ii) can be produced through solution processes, (iii) mainly use low-cost raw materials, and (iv) can be flexible. These features make perovskite solar cells intriguing as space technologies; however, the extra-terrestrial environment can easily cause the premature failure of devices. In particular, the presence of highenergy radiation is the most dangerous factor that can damage space technologies. This Review discusses the status and perspectives of perovskite photovoltaics in space applications. The main factors used to describe the space environment are introduced, and the results concerning the radiation hardness of perovskites toward protons, electrons, neutrons, and gamma-rays are presented. Emphasis is given to the physicochemical processes underlying radiation damage in such materials. Finally, the potential use of perovskite solar cells in extra-terrestrial conditions is discussed by considering the effects of the space environment on the choice of the architecture and components of the devices