Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collaboration (DESC) has been tasked with deriving constraints on cosmological parameters from LSST data. Each of the cosmological probes for LSST is heavily impacted by the choice of observing strategy. This white paper is written by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy that will benefit all cosmological analyses with LSST. It is accompanied by the DESC DDF (Deep Drilling Fields) white paper (Scolnic et al.). We use a variety of metrics to understand the effects of the observing strategy on measurements of weak lensing, large-scale structure, clusters, photometric redshifts, supernovae, strong lensing and kilonovae. In order to reduce systematic uncertainties, we conclude that the current baseline observing strategy needs to be significantly modified to result in the best possible cosmological constraints. We provide some key recommendations: moving the WFD (Wide-Fast-Deep) footprint to avoid regions of high extinction, taking visit pairs in different filters, changing the 2×15s snaps to a single exposure to improve efficiency, focusing on strategies that reduce long gaps (>15 days) between observations, and prioritizing spatial uniformity at several intervals during the 10-year survey.

This work investigated the effect of friction stir welding (FSW) tool rotation rate and welding speed on the grain structure evolution in the nugget zone through the thickness of the 10 mm thick AA5083/AA5754 weldments. Three joints were produced at different combinations of FSW parameters. The grain structure and texture were investigated using electron backscattering diffraction (EBSD). In addition, both the hardness and tensile properties were investigated. It was found that the grain size varied through the thickness in the nugget (NG), which was reduced from the top to the base in all welds. Reducing the rotation rate from 600 rpm to 400 rpm at a constant welding speed of 60 mm/min reduced the average grain size from 33 µm to 25 µm at the top and from 19 µm to 12 µm at the base. On the other hand, the increase of the welding speed from 20 mm/min to 60 mm/min had no obvious effect on the average grain size. This implied that the rotation rate was more effective in grain size reduction than the welding speed. The texture was the mainly simple shear texture that required some rotations to obtain the ideal simple shear texture. The hardness distribution, mapped for the nugget zone, and the parent alloys indicated a diffused softened welding zone. The heating effect of the pressure and rotation of the pin shoulder and the heat input parameter (ω/v) on the hardness value of the nugget zone were dominating. Tensile stress-strain curves of the base alloys and that of the FSWed joints were evaluated and presented. Moreover, the true stress-true strain curves were determined and described by the empirical formula after Ludwik, and then the materials strengthening parameters were determined. The tensile specimens of the welded joint at a revolution speed of 400 rpm and travel speed of 60 mm/min possessed the highest strain hardening parameter (n = 0.494).

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Dual phase weathering (DP-weathering) steels were developed by inter-critical annealing treatments from a commercial hot-rolled weathering steel. The effects of martensite volume fraction (MVF) and microstructural changes accompanied the martensitic transformation on mechanical properties, formability, and corrosion behavior were investigated by metallography, mechanical, and corrosion testing. The investigations revealed that the final microstructures consisted mostly of island-shape martensite particles impeded in a ferrite matrix except for the highest temperature of 840 8C. Depending on MVF and martensite morphology, a wide range of mechanical properties was achieved; yield strength of 370-408 MPa and tensile strength of 580-689 MPa. The coupling of the results from metallography and mechanical testing emphasized the enhanced formability of the developed DP-weathering steels. The optimum combination of strength and formability was achieved for specimens treated at 810 8C and attained a MVF of 26%. Although, the presence of martensite phase raised the corrosion rate of DP-weathering steels during the initial corrosion cycles, it accelerated the nucleation process of the protective FeOOH layer. X-ray diffraction (XRD) investigations demonstrated that the rust layers formed on DP-weathering steels composed mainly of g-FeOOH, a-FeOOH, and Fe x O.

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Future surveys such as the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will observe an order of magnitude more astrophysical transient events than any previous survey before. With this deluge of photometric data, it will be impossible for all such events to be classified by humans alone. Recent efforts have sought to leverage machine learning methods to tackle the challenge of astronomical transient classification, with ever improving success. Transformers are a recently developed deep learning architecture, first proposed for natural language processing, that have shown a great deal of recent success. In this work we develop a new transformer architecture, which uses multi-head self attention at its core, for general multi-variate time-series data. Furthermore, the proposed time-series transformer architecture supports the inclusion of an arbitrary number of additional features, while also offering interpretability. We apply the time-series transformer to the task of photometric classification, minimising the reliance of expert domain knowledge for feature selection, while achieving results comparable to state-of-the-art photometric classification methods. We achieve a weighted logarithmic-loss of 0.507 on imbalanced data in a representative setting using data from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC). Moreover, we achieve a micro-averaged receiver operating characteristic area under curve of 0.98 and micro-averaged precision-recall area under curve of 0.87.

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A novel medium manganese (MMn) steel with additions of Cr (18%), Ni (5%), V (1%), and N (0.3%) was developed in order to provide an enhanced corrosion resistance along with a superior strength–ductility balance. The laboratory melted ingots were hot rolled, cold rolled, and finally annealed at 1000 °C for 3 min. The recrystallized single-phase austenitic microstructure consisted of ultrafine grains (~1.3 µm) with a substantial amount of Cr- and V-based precipitates in a bimodal particle size distribution (100–400 nm and <20 nm). The properties of the newly developed austenitic MMn steel X20CrNiMnVN18-5-10 were compared with the standard austenitic stainless steel X5CrNi18-8 and with the austenitic twinning-induced plasticity (TWIP) steel X60MnAl17-1. With a total elongation of 45%, the MMn steel showed an increase in yield strength by 300 MPa and in tensile strength by 150 MPa in comparison to both benchmark steels. No deformation twins were observed even after fracture for the MMn steel, which emphasizes the role of the grain size and precipitation-induced change in the austenite stability in controlling the deformation mechanism. The potentio-dynamic polarization measurements in 5% NaCl revealed a very low current density value of 7.2 × 10−4 mA/cm2 compared to that of TWIP steel X60MnAl17-1 of 8.2 × 10−3 mA/cm2, but it was relatively higher than that of stainless steel X5CrNi18-8 of 2.0 × 10−4 mA/cm2. This work demonstrates that the enhanced mechanical properties of the developed MMn steel are tailored by maintaining an ultrafine grain microstructure with a significant amount of nanoprecipitates, while the high corrosion resistance in 5% NaCl solution is attributed to the high Cr and N contents as well as to the ultrafine grain size.