15 research outputs found

    Aerosol versus Greenhouse Gas Effects on Tropical Cyclone Potential Intensity and the Hydrologic Cycle

    Get PDF
    Aerosol cooling reduces tropical cyclone (TC) potential intensity (PI) more strongly, by about a factor of 2 per degree of sea surface temperature change, than greenhouse gas warming increases it. This study analyzes single-forcing and historical experiments from phase 5 of the Coupled Model Intercomparison Project, aiming to understand the physical mechanisms behind this difference. Calculations are done for the tropical oceans of each hemisphere during the relevant TC seasons, emphasizing multimodel means. PI theory is used to interpret the difference in the PI response to aerosol and greenhouse gas forcings in terms of three factors. The net surface turbulent heat flux (sum of the latent and sensible heat fluxes) explains half of the difference, thermodynamic efficiency explains at most a small fraction, and surface wind speed does not explain the remainder, perhaps because of the use of monthly mean data. Changes in turbulent surface heat fluxes are interpreted as responses to surface radiative flux changes in the context of the energy balance of the ocean mixed layer. Radiative kernels are used to estimate what fractions of the surface radiative flux changes are feedbacks due to temperature and water vapor changes. The greater effect of aerosol forcing occurs because shortwave forcing has a greater direct, temperature-independent component at the surface than does longwave forcing, for a forcing amplitude that provokes the same SST change. This conclusion recalls prior work on the response of precipitation to radiative forcing, and the similarities and differences between precipitation and potential intensity in this regard are discussed

    OpenFermion: The Electronic Structure Package for Quantum Computers

    Get PDF
    Quantum simulation of chemistry and materials is predicted to be an important application for both near-term and fault-tolerant quantum devices. However, at present, developing and studying algorithms for these problems can be difficult due to the prohibitive amount of domain knowledge required in both the area of chemistry and quantum algorithms. To help bridge this gap and open the field to more researchers, we have developed the OpenFermion software package (www.openfermion.org). OpenFermion is an open-source software library written largely in Python under an Apache 2.0 license, aimed at enabling the simulation of fermionic models and quantum chemistry problems on quantum hardware. Beginning with an interface to common electronic structure packages, it simplifies the translation between a molecular specification and a quantum circuit for solving or studying the electronic structure problem on a quantum computer, minimizing the amount of domain expertise required to enter the field. The package is designed to be extensible and robust, maintaining high software standards in documentation and testing. This release paper outlines the key motivations behind design choices in OpenFermion and discusses some basic OpenFermion functionality which we believe will aid the community in the development of better quantum algorithms and tools for this exciting area of research.Comment: 22 page

    Overview of NASA QuAIL Team Research

    No full text
    NASA is constantly confronting massively challenging computational problems. These problems have the potential to limit mission scope and aim. NASA's Quantum Artificial Intelligence Laboratory (QuAIL) Group was formed to determine the potential for quantum computation to enable more ambitious NASA missions in the future. This presentation highlights recent work by the QuAIL team that is focused on physics insights and applications associated with the D-Wave 2000Q quantum annealing hardware that is located at NASA Ames Research Center
    corecore