Efficient Climate Simulation via Machine Learning Method

Hybrid modeling combining data-driven techniques and numerical methods is an emerging and promising research direction for efficient climate simulation. However, previous works lack practical platforms, making developing hybrid modeling a challenging programming problem. Furthermore, the lack of standard data sets and evaluation metrics may hamper researchers from comprehensively comparing various algorithms under a uniform condition. To address these problems, we propose a framework called NeuroClim for hybrid modeling under the real-world scenario, a basic setting to simulate the real climate that we live in. NeuroClim consists of three parts: (1) Platform. We develop a user-friendly platform NeuroGCM for efficiently developing hybrid modeling in climate simulation. (2) Dataset. We provide an open-source dataset for data-driven methods in hybrid modeling. We investigate the characteristics of the data, i.e., heterogeneity and stiffness, which reveals the difficulty of regressing climate simulation data; (3) Metrics. We propose a methodology for quantitatively evaluating hybrid modeling, including the approximation ability of machine learning models and the stability during simulation. We believe that NeuroClim allows researchers to work without high level of climate-related expertise and focus only on machine learning algorithm design, which will accelerate hybrid modeling research in the AI-Climate intersection. The codes and data are released at https://github.com/x-w19/NeuroClim.Comment: Work in progres

Phase-locking matter-wave interferometer of vortex states

Matter-wave interferometer of ultracold atoms with different linear momenta has been extensively studied in theory and experiment. The vortex matter-wave interferometer with different angular momenta is applicable as a quantum sensor for measuring the rotation, interatomic interaction, geometric phase, etc. Here we report the first experimental realization of a vortex matter-wave interferometer by coherently transferring the optical angular momentum to an ultracold Bose condensate. After producing a lossless interferometer with atoms only populating the two spin states, we demonstrate that the phase difference between the interferences in the two spin states is locked on $\pi$. We also demonstrate the robustness of this out-of-phase relation, which is independent of the angular-momentum difference between the two interfering vortex states, constituent of Raman optical fields and expansion of the condensate. The experimental results agree well with the calculation from the unitary evolution of wave packet in quantum mechanics. This work opens a new way to build a quantum sensor and measure the atomic correlation in quantum gases.Comment: 5 figure

Pyrolysis characteristics of waste tire particles in fixed-bed reactor with internals

This study investigated the characteristics of pyrolysis for waste tire particles in the newly developed fixed-bed reactor with internals that are a central gas collection channel mounted inside reactor. And a few metallic plates vertically welded on the internal wall of the reactors and extending to the region closing their central gas collection pipe walls. Experiments were conducted in two laboratory fixed bed reactors with or without the internals. The results shown that employing internals produced more light oil at externally heating temperatures above 700 °C due to the inhibited secondary reactions in the reactor. The oil from the reactor with internals contained more aliphatic hydrocarbons and fewer aromatic hydrocarbons, leading to its higher H/C atomic ratios as for crude petroleum oil. The char yield was relatively stable for two beds and showed the higher heating values (HHVs) of about 23 MJ/kg. The gaseous product of pyrolysis mainly consisted of H2 and CH4, but the use of internals led to less pyrolysis gas through its promotion of oil production. Keywords: Pyrolysis, Waste tire, Fixed bed, Internals, Secondary reaction

A few recent developments in fluidized bed technology applications for fuel conversion

In recent years, the process concepts based on two-stage and dual bed have been widely adopted in developing fuel conversion technologies including pyrolysis, combustion, gasification and catalytic cracking. These provide indeed advantages of, for example, easy operation and control, poly-generation of products, and high efficiency in elimination of undesirable product or pollutants. The so-called micro fluidized bed analyzer (MFBRA) has been newly developed to measure reaction rates at arbitrary temperatures, giving a great support to fundamental research and technology developments for fuel conversion. This report intends to summarize the involved new concepts, major fundamental understandings, pilot test and/or industrial demonstrations of a few newly developed fuel conversion technologies. Concretely, it will report fluidized bed two-stage gasification (FBTSG), dual fluidized bed pyrolysis combustion (DBPC), fluidized bed cracking gasification (FBCG) and MFBRA. The FBTSG technology separates fuel pyrolysis in a FB pyrolyzer and char gasification in a transport bed gasifier. The latter enables high-temperature tar cracking under catalysis of char to enable remarkably low tar content in the produced gas [1]. For fuel with high contents of water and nitrogen, the DBPC technology first removes fuel water and most fuel volatile in a pyrolyzer. This, on the one hand, ensures stable combustion of the fuel, and on the other hand facilitates NOx reduction by char and pyrolysis gas [2]. The FBCG technology separates the catalytic cracking of heavy feedstock for liquid and the gasification of char, the cokes formed on the catalyst surface, to produce syngas and also to regenerate the catalyst. By using micro fluidized bed, the MFBRA is newly developed to enable the on-line pulse feeding and rapid heating of particle reactant. It effectively suppresses the interfacial diffusion limitation and minimizes the intra-particle diffusion [3]. Thus, MFBRA provides isothermal reaction analysis in comparison with that in TGA based on programmed heating. REFERENCES 1. X. Zeng, et al. Pilot verification of a low-tar two-stage coal gasification process with a FB pyrolyzer and fixed bed gasifier. Applied Energy, 115, 9–16, 2014. 2. P. Dagaut, et al. Experiments and kinetic modeling study of NO-reburning by gases from biomass pyrolysis in a JSR. Energy & Fuels, 17(3), 608-613, 2003. 3. J. Yu, et al. Kinetics and mechanism of solid reactions in a micro fluidized bed reactor. AIChE Journal, 56, 2905-2912, 2010

Mesenchymal Stem Cells: A Double-edged Sword in Regulating Immune Responses

Mesenchymal stem cells (MSCs) have been employed successfully to treat various immune disorders in animal models and clinical settings. Our previous studies have shown that MSCs can become highly immunosuppressive upon stimulation by inflammatory cytokines, an effect exerted through the concerted action of chemokines and nitric oxide (NO). Here, we show that MSCs can also enhance immune responses. This immune-promoting effect occurred when proinflammatory cytokines were inadequate to elicit sufficient NO production. When inducible nitric oxide synthase (iNOS) production was inhibited or genetically ablated, MSCs strongly enhance T-cell proliferation in vitro and the delayed-type hypersensitivity response in vivo. Furthermore, iNOS-/- MSCs significantly inhibited melanoma growth. It is likely that in the absence of NO, chemokines act to promote immune responses. Indeed, in CCR5-/- CXCR3-/- mice, the immune-promoting effect of iNOS-/- MSCs is greatly diminished. Thus, NO acts as a switch in MSC-mediated immunomodulation. More importantly, the dual effect on immune reactions was also observed in human MSCs, in which indoleamine 2,3-dioxygenase (IDO) acts as a switch. This study provides novel information about the pathophysiological roles of MSCs. © 2012 Macmillan Publishers Limited All rights reserved

Gaussian Boson Sampling with Pseudo-Photon-Number Resolving Detectors and Quantum Computational Advantage

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ~ 600 years using exact methods, whereas our quantum computer, Jiuzhang 3.0, takes only 1.27 us to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier ~ 3.1*10^10 years.Comment: submitted on 10 Apri

Gaussian Boson Sampling with Pseudo-Photon-Number-Resolving Detectors and Quantum Computational Advantage

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for the characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical spoofing mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ∼600 yr using exact methods, whereas our quantum computer, Jizhāng 3.0, takes only 1.27 μs to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier∼3.1×1010 yr.</p