Evolution of the Dynamic Integrated Climate-Economy (DICE) model : decomposition of changes over time

Global warming is one of the major environmental challenges of the modern era. Global temperature in 2005 has increased about 0.7°C (1.3°F) compare to 1900, also CO₂ concentrations increased by 100 parts per million (ppm). Estimated expense to decrease the CO₂ concentrations by 1 ppm is about 1 trillion (Pielke, 2009). Overcoming global warming is difficult because it is interdisciplinary problem and involves many parts of society. Any proposed policies must balance the economic costs of operations today and future corresponding economic and environmental benefits. There are several studies and models which used economics and mathematical modeling to analyzed the efficiency of different approaches and policies to slowing global warming. Dynamic Integrated model of Climate and the Economy (DICE) model uses economics and mathematical modeling to analyzed the efficiency of different approaches and policies to slow global warming (William D. Nordhaus, 1994, 2008, 2017, 2017a; William D. Nordhaus & Boyer, 2000). The main distinguishing feature of the DICE model is connecting economy and climate change factors including the carbon cycle, radiative forcing equation, climate change equations, and climate damage relationship. DICE finds optimal emissions control rate by balancing abatement costs of reducing emissions, and economic growth due to avoiding future climate damages. DICE-2016 shows following results under optimal emissions reduction policy, emissions reduction rate for CO₂ is increasing to 36 percent by 2050 and 84 percent by 2100 relative to the baseline. Corresponding, CO₂ concentrations is decreased and increase in global temperature relative to 1900 is decreased to 6.17°F (3.43°C) for 2100 and 6.96°F (3.87°C) for 2200. The net present value abatement cost and climate damages of the optimal policy is 42.6 trillion beneficial relative to no control. This includes $20.4 trillion of abatement costs and$63 trillion of reduced climatic damages. There is still $81.8 trillion climate damage even after taking optimal policy. We compared the outputs of DICE-2016 and DICE-2007 to understand the economic effect of climate change and how climate changing is modeled in these two models. By comparing these models, we obtained estimated economical abatement costs to reduce emissions, social cost of carbon, and impact of climate change and global warming on the economy. We were trying to identify which changes have the most effect on the difference between these two models.Operations Research and Industrial Engineerin

Binary Classifier Calibration using an Ensemble of Near Isotonic Regression Models

Learning accurate probabilistic models from data is crucial in many practical tasks in data mining. In this paper we present a new non-parametric calibration method called \textit{ensemble of near isotonic regression} (ENIR). The method can be considered as an extension of BBQ, a recently proposed calibration method, as well as the commonly used calibration method based on isotonic regression. ENIR is designed to address the key limitation of isotonic regression which is the monotonicity assumption of the predictions. Similar to BBQ, the method post-processes the output of a binary classifier to obtain calibrated probabilities. Thus it can be combined with many existing classification models. We demonstrate the performance of ENIR on synthetic and real datasets for the commonly used binary classification models. Experimental results show that the method outperforms several common binary classifier calibration methods. In particular on the real data, ENIR commonly performs statistically significantly better than the other methods, and never worse. It is able to improve the calibration power of classifiers, while retaining their discrimination power. The method is also computationally tractable for large scale datasets, as it is $O(N \log N)$ time, where $N$ is the number of samples

Proposal for an Optomechanical Traveling Wave Phonon-Photon Translator

In this article we describe a general optomechanical system for converting photons to phonons in an efficient, and reversible manner. We analyze classically and quantum mechanically the conversion process and proceed to a more concrete description of a phonon-photon translator formed from coupled photonic and phononic crystal planar circuits. Applications of the phonon-photon translator to RF-microwave photonics and circuit QED, including proposals utilizing this system for optical wavelength conversion, long-lived quantum memory and state transfer from optical to superconducting qubits are considered.Comment: 32 pages, 11 figure

Slot-mode-coupled optomechanical crystals

We present a design methodology and analysis of a cavity optomechanical system in which a localized GHz frequency mechanical mode of a nanobeam resonator is evanescently coupled to a high quality factor (Q>10^6) optical mode of a separate nanobeam optical cavity. Using separate nanobeams provides flexibility, enabling the independent design and optimization of the optics and mechanics of the system. In addition, the small gap (approx. 25 nm) between the two resonators gives rise to a slot mode effect that enables a large zero-point optomechanical coupling strength to be achieved, with g/2pi > 300 kHz in a Si3N4 system at 980 nm and g/2pi approx. 900 kHz in a Si system at 1550 nm. The fact that large coupling strengths to GHz mechanical oscillators can be achieved in SiN is important, as this material has a broad optical transparency window, which allows operation throughout the visible and near-infrared. As an application of this platform, we consider wide-band optical frequency conversion between 1300 nm and 980 nm, using two optical nanobeam cavities coupled on either side to the breathing mode of a mechanical nanobeam resonator