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A collection of tutorials -- both Jupyter notebooks and documentation-based --- demonstrating data access, analysis, and visualization techniques for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). These tutorials are intended for astronomers, educators, and data scientists working with LSST data products.
Hexagonal boron nitride (hBN), also known as white graphite, is a transparent layered crystal with a wide bandgap. Its crystal structure resembles graphite, featuring layers composed of honeycomb lattices held together through van der Waals forces. The layered crystal structure of hBN facilitates exfoliation into thinner flakes and makes it highly anisotropic in in-plane and out-of-plane directions. Unlike graphite, hBN is both insulating and transparent, making it an ideal material for isolating devices from the environment and acting as a waveguide. As a result, hBN has found extensive applications in optical devices, electronic devices, and quantum photonic devices. This comprehensive tutorial aims to provide readers with a thorough understanding of hBN, covering its synthesis, lattice and spectroscopic characterization, and various applications in optoelectronic and quantum photonic devices. This tutorial is designed for both readers without prior experience in hBN and those with expertise in specific fields seeking to understand its relevance and connections to others.
Tutorials for modeling of slot-die and slide-die coating flows with Goma 7, an open source finite element code, are presented. The tutorials cover the workflow to attaining steady state solutions for these flows, and continuation strategies for navigating the operating windows. Advanced topics of coating window prediction, automated multiparameter continuation, non-Newtonian rheology, dynamic contact line modeling, and some more solution strategies are also covered.
The purpose of this tutorial is to demonstrate how to use Markov chain Monte Carlo (MCMC) to calibrate a model. By calibration, we mean the selection of model parameters (and, when relevant, structures). A common goal in model development and diagnostics is calibration, or the identification of model structures and parameters which are consistent with data. While models can be calibrated through hand-tuning parameters or minimizing simple error metrics such as root-mean-square-error (RMSE), these approaches can underrepresent the probabilistic nature of the data-generating process, as well as the potential for multiple model configurations to be consistent with the data. Probabilistic uncertainty quantification, which is the topic of this notebook, can address these concerns. This tutorial is presented as an appendix to the e-book: Addressing Uncertainty in MultiSector Dynamics Research.
This document defines the guidelines, principles, and formats for user-facing tutorials that demonstrate how to use the Rubin Science Platform (RSP) to analyze data from the Legacy Survey of Space and Time (LSST). All Rubin staff and the broader science community should use these guidelines when contributing to the sets of Jupyter Notebook or documentation-based tutorials maintained by the Rubin Community Science team (CST).
The version of tutorial input implemented on the Modcomp used for antenna control at DSS 13 is described. Emphasis is on the use of the tutorial input; program operation is described to the extent that it makes the use more understandable. Flow charts are provided.
A disk array is a collection of physically small magnetic disks that is packaged as a single unit but operates in parallel. Disk arrays capitalize on the availability of small-diameter disks from a price-competitive market to provide the cost, volume, and capacity of current disk systems but many times their performance. Unfortunately, relative to current disk systems, the larger number of components in disk arrays leads to higher rates of failure. To tolerate failures, redundant disk arrays devote a fraction of their capacity to an encoding of their information. This redundant information enables the contents of a failed disk to be recovered from the contents of non-failed disks. The simplest and least expensive encoding for this redundancy, known as N+1 parity is highlighted. In addition to compensating for the higher failure rates of disk arrays, redundancy allows highly reliable secondary storage systems to be built much more cost-effectively than is now achieved in conventional duplicated disks. Disk arrays that combine redundancy with the parallelism of many small-diameter disks are often called Redundant Arrays of Inexpensive Disks (RAID). This combination promises improvements to both the performance and the reliability of secondary storage. For example, IBM's premier disk product, the IBM 3390, is compared to a redundant disk array constructed of 84 IBM 0661 3 1/2-inch disks. The redundant disk array has comparable or superior values for each of the metrics given and appears likely to cost less. In the first section of this tutorial, I explain how disk arrays exploit the emergence of high performance, small magnetic disks to provide cost-effective disk parallelism that combats the access and transfer gap problems. The flexibility of disk-array configurations benefits manufacturer and consumer alike. In contrast, I describe in this tutorial's second half how parallelism, achieved through increasing numbers of components, causes overall failure rates to rise. Redundant disk arrays overcome this threat to data reliability by ensuring that data remains available during and after component failures.
A tutorial on the development of a formal specification and its verification using the Prototype Verification System (PVS) is presented. The tutorial presents the formal specification and verification techniques by way of specific example - an airline reservation system. The airline reservation system is modeled as a simple state machine with two basic operations. These operations are shown to preserve a state invariant using the theorem proving capabilities of PVS. The technique of validating a specification via 'putative theorem proving' is also discussed and illustrated in detail. This paper is intended for the novice and assumes only some of the basic concepts of logic. A complete description of user inputs and the PVS output is provided and thus it can be effectively used while one is sitting at a computer terminal.
This tutorial will introduce Fortran developers to unit-testing and test-driven development (TDD) using pFUnit. As with other unit-testing frameworks, pFUnit, simplifies the process of writing, collecting, and executing tests while providing clear diagnostic messages for failing tests. pFUnit specifically targets the development of scientific-technical software written in Fortran and includes customized features such as: assertions for multi-dimensional arrays, distributed (MPI) and thread-based (OpenMP) parallellism, and flexible parameterized tests.These sessions will include numerous examples and hands-on exercises that gradually build in complexity. Attendees are expected to have working knowledge of F90, but familiarity with object-oriented syntax in F2003 and MPI will be of benefit for the more advanced examples. By the end of the tutorial the audience should feel comfortable in applying pFUnit within their own development environment.
Although free space cannot generate electromagnetic waves, the majority of existing accounts of frequency-domain electromagnetic scattering by particles and particle groups are based on the postulate of existence of an impressed incident field, usually in the form of a plane wave. In this tutorial we discuss how to account for the actual existence of impressed source currents rather than impressed incident fields. Specifically, we outline a self-consistent theoretical formalism describing electromagnetic scattering by an arbitrary finite object in the presence of arbitrarily distributed impressed currents, some of which can be far removed from the object and some can reside in its vicinity, including inside the object. To make the resulting formalism applicable to a wide range of scattering-object morphologies, we use the framework of the volume integral equation formulation of electromagnetic scattering, couple it with the notion of the transition operator, and exploit the fundamental symmetry property of this operator. Among novel results, this tutorial includes a streamlined proof of fundamental symmetry (reciprocity) relations, a simplified derivation of the Foldy equations, and an explicit analytical expression for the transition operator of a multi-component scattering object.
Our recent tutorial referred to in the title has summarized a general theoretical formalism of electromagnetic scattering by an arbitrary finite object in the presence of arbitrarily distributed impressed currents. This addendum builds on the tutorial to provide a streamlined discussion of specific far-field limits and the corresponding reciprocity relations by introducing appropriate far-field operators and linear maps and deriving the reciprocity relations through the pseudo adjoint of these maps. We thereby extend the compact operator calculus used previously to consider the fields and sources near or inside the scattering object.
Tutorial describing how to use NEQAIR v15.1 User Tutorial: NEQAIR was NASA’s first radiative heating code and has been the go-to-tool for 30+ years.
This tutorial will highlight the most recent efforts from the National Renewable Energy Laboratory (NREL) to track solar photovoltaic (PV) technology trends and manufacturing costs, project levelized cost of electricity (LCOE), and project levelized cost of solar plus storage (LCOSS) for systems across the globe. We will begin with an overview of the global PV supply chain and 2021 benchmark input data for NREL's crystalline silicon (c-Si) and thin film PV module manufacturing cost models. The framework that we follow and will review during this tutorial provides a methodology to prepare bottom-up manufacturing cost models including the items within the U.S. Generally Accepted Accounting Principles (GAAP) and the International Financial Reporting Standards (IFRS). For the polysilicon, wafer, cell conversion, and module assembly steps of the c-Si supply chain, and for thin film modules, we will review input data and methods useful for calculating the costs of goods sold (COGS); research and development (R&D) expenses; and sales, general, and business administration (S, G, &A) expenses. This 2021 benchmark analysis is compiled for state-of-the-art c-Si and thin film module manufacturing. We will also review methods for our 2021 system benchmark costs calculations and LCOE technoeconomic analysis of PV systems and solar plus storage systems. Next generation technologies that lower PV manufacturing and installation costs, reduce operations and maintenance (O&M) expenses, and improve system energy yield will also be highlighted. Techniques for comparing LCOE performance will also be reviewed. We look forward to sharing NREL's extensive work in these areas and discussing ideas for future directions.
The share of vehicles with fully electric propulsion systems is constantly increasing, and so is their traction drive power. The continuous push to increase power of electric vehicle (EV) traction drives necessitates their efficient cooling to prevent damage to temperature sensitive components of the drive system and achieving higher power outputs in a smaller footprint. With increasing power and power density of electric traction drives, their thermal management is becoming increasingly challenging. This tutorial will provide an overview of thermal management approaches for electric motors and power electronics in EV applications. It will review examples of current industry solutions for power-dense electric motor cooling, power electronics (inverter) cooling, their integration concepts and thermal management system solutions. We'll look at the advantages and challenges of power electronics integration into a single traction drive unit and respective thermal management system concepts. We'll talk about barriers to implementation of a unified thermal management system. The tutorial will also review key aspects of thermal management system design: modeling and simulation using FEA and CFD tools, experimental characterization, and general workflow for thermal management system evaluation.
In situ and operando (scanning) transmission electron microscopy [(S)TEM] is a powerful characterization technique that uses imaging, diffraction, and spectroscopy to gain nano-to-atomic scale insights into the structure–property relationships in materials. This technique is both customizable and complex because many factors impact the ability to collect structural, compositional, and bonding information from a sample during environmental exposure or under application of an external stimulus. In the past two decades, in situ and operando (S)TEM methods have diversified and grown to encompass additional capabilities, higher degrees of precision, dynamic tracking abilities, enhanced reproducibility, and improved analytical tools. Much of this growth has been shared through the community and within commercialized products that enable rapid adoption and training in this approach. This tutorial aims to serve as a guide for students, collaborators, and nonspecialists to learn the important factors that impact the success of in situ and operando (S)TEM experiments and assess the value of the results obtained. As this is not a step-by-step guide, readers are encouraged to seek out the many comprehensive resources available for gaining a deeper understanding of in situ and operando (S)TEM methods, property measurements, data acquisition, reproducibility, and data analytics.
The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.
Here, in this tutorial review, we report the state-of-the-art of the modeling approaches of Single Atom Catalysts (SAC) for water splitting and fuel cells reactions. The discussion applies for Hydrogen Evolution Reaction (HER), Oxygen Reduction Reaction (OER), Hydrogen Oxidation Reaction (HOR), and Oxygen Reduction Reaction (ORR). The main scope of this work is to underline the relevant aspects of SACs modelling. On the one hand, the review could help computational chemists aiming to start the study of SACs. On the other hand, experimentalists could find the critical analysis of DFT results of interest to understand better the strengths and weaknesses of simulations, and how to interpret computational results. After an introductory section of SACs, we start by briefly presenting the state-of-the-art methodologies. Then, we analyze the critical aspects for a reliable prediction of the electronic properties, and we discuss the robustness of the structural models and ways to validate them. Furthermore, we discuss the main approaches to predict catalytic activity and selectivity, which is the final goal of the computational catalysis. We conclude this review with a critical analysis of the current challenges in the field, and the main limitations of the modeling approaches that are described.
This tutorial is a pedagogical introduction to recent methods of computing quantum spin entanglement witnesses from spectroscopy, with a special focus on neutron scattering on quantum spin systems. We offer a brief introduction to the concepts and equations, define a data analysis protocol, and discuss the interpretation of three entanglement witnesses: one-tangle, two-tangle, and Quantum Fisher Information. We also discuss practical experimental considerations, and give three examples of extracting entanglement witnesses from experimental data: Copper Nitrate, KCuF 3 , and NiPS 3 .