scholarly journals Integrated Analysis of Performance and Resources in Large-Scale Quantum Computing

2020 ◽  
Vol 13 (5) ◽  
Author(s):  
Yongsoo Hwang ◽  
Taewan Kim ◽  
Chungheon Baek ◽  
Byung-Soo Choi
Keyword(s):  
Quantum Computing ◽  
Large Scale ◽  
Integrated Analysis ◽  
Analysis Of Performance

scholarly journals An integrated life cycle and water footprint assessment of nonfood crops based bioenergy production

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun Li ◽  
Fengyin Xiong ◽  
Zhuo Chen
Keyword(s):  
Life Cycle ◽  
Environmental Sustainability ◽  
Large Scale ◽  
Water Footprint ◽  
Arable Land ◽  
Integrated Analysis ◽  
Actual Performance ◽  
Bioenergy Production ◽  
Trade Offs ◽  
Hybrid Pennisetum

AbstractBiomass gasification, especially distribution to power generation, is considered as a promising way to tackle global energy and environmental challenges. However, previous researches on integrated analysis of the greenhouse gases (GHG) abatement potentials associated with biomass electrification are sparse and few have taken the freshwater utilization into account within a coherent framework, though both energy and water scarcity are lying in the central concerns in China’s environmental policy. This study employs a Life cycle assessment (LCA) model to analyse the actual performance combined with water footprint (WF) assessment methods. The inextricable trade-offs between three representative energy-producing technologies are explored based on three categories of non-food crops (maize, sorghum and hybrid pennisetum) cultivated in marginal arable land. WF results demonstrate that the Hybrid pennisetum system has the largest impact on the water resources whereas the other two technology options exhibit the characteristics of environmental sustainability. The large variances in contribution ratio between the four sub-processes in terms of total impacts are reflected by the LCA results. The Anaerobic Digestion process is found to be the main contributor whereas the Digestate management process is shown to be able to effectively mitigate the negative environmental impacts with an absolute share. Sensitivity analysis is implemented to detect the impacts of loss ratios variation, as silage mass and methane, on final results. The methane loss has the largest influence on the Hybrid pennisetum system, followed by the Maize system. Above all, the Sorghum system demonstrates the best performance amongst the considered assessment categories. Our study builds a pilot reference for further driving large-scale project of bioenergy production and conversion. The synergy of combined WF-LCA method allows us to conduct a comprehensive assessment and to provide insights into environmental and resource management.

scholarly journals Quantum learning with noise and decoherence: a robust quantum neural network

2019 ◽  
Author(s):  
Elizabeth Behrman ◽  
Nam Nguyen ◽  
James Steck
Keyword(s):  
Neural Network ◽  
Quantum Computing ◽  
Large Scale ◽  
Learning Approaches ◽  
Quantum Neural Network ◽  
Quantum Learning ◽  
Learning With Noise ◽  
Robustness To Noise ◽  
Robust To Noise ◽  
Arbitrary Quantum

<p>Noise and decoherence are two major obstacles to the implementation of large-scale quantum computing. Because of the no-cloning theorem, which says we cannot make an exact copy of an arbitrary quantum state, simple redundancy will not work in a quantum context, and unwanted interactions with the environment can destroy coherence and thus the quantum nature of the computation. Because of the parallel and distributed nature of classical neural networks, they have long been successfully used to deal with incomplete or damaged data. In this work, we show that our model of a quantum neural network (QNN) is similarly robust to noise, and that, in addition, it is robust to decoherence. Moreover, robustness to noise and decoherence is not only maintained but improved as the size of the system is increased. Noise and decoherence may even be of advantage in training, as it helps correct for overfitting. We demonstrate the robustness using entanglement as a means for pattern storage in a qubit array. Our results provide evidence that machine learning approaches can obviate otherwise recalcitrant problems in quantum computing. </p> <p> </p>

scholarly journals Biosequence stratigraphical and palaeoenvironmental findings from the Cretaceous through Tertiary succession, Central Indus Basin, Pakistan

2002 ◽  
Vol 21 (2) ◽  
pp. 115-130 ◽  
Author(s):  
M. I. Wakefield ◽  
E. Monteil
Keyword(s):  
Large Scale ◽  
Age Dating ◽  
Indus Basin ◽  
Arabian Plate ◽  
Integrated Analysis ◽  
Low Oxygen ◽  
Candidate Sequence ◽  
Oceanic Anoxic Event ◽  
Palynological Data ◽  
Sequence Boundaries

Abstract. Integrated analysis of foraminiferal and palynological data from the Duljan-1 well, Central Indus Basin, Pakistan, is used to identify critical surfaces (candidate sequence boundaries (SB) and maximum flooding surfaces (MFS)) and construct a biosequence stratigraphical framework. Within the Barremian through Bartonian–Priabonian? succession 15 depositional sequences have been recognized, each with a candidate MFS. These biosequences are shown to equate with the local lithostratigraphy and tentatively with the ‘global’ large-scale depositional cycles of Haq et al. (1987). Detailed dating has enabled seven candidate MFS to be tentatively equated with MFS identified on the nearby Arabian plate (Sharland et al., 2001). A combination of detailed age dating and palaeobathymetric determinations indicates significant basin uplift and erosion at end Cretaceous and end Eocene times, the latter coinciding with closure of Neo-Tethys. Smaller-scale unconformities are also noted. Multi-disciplinary palaeoenvironmental interpretations enable recognition of detailed changes in water mass conditions. Palynological data suggest these changes result from variations in terrestrial/freshwater input, though evidence of periodically low oxygen bottom water conditions/shallowing of the oxygen minimum zone, possibly ‘Oceanic Anoxic Event-2’ (OAE-2; late Cenomanian–Turonian) is suggested as a further control.

Promising routes to large-scale photonic quantum computing

Scilight ◽  
2019 ◽  
Vol 2019 (24) ◽  
pp. 240007
Author(s):  
Meeri Kim
Keyword(s):  
Quantum Computing ◽  
Large Scale

scholarly journals Satellite Perspectives of Sea Surface Temperature Diurnal Warming on Atmospheric Moistening and Radiative Heating During MJO

2020 ◽  
pp. 1-56
Author(s):  
Kyle Itterly ◽  
Patrick Taylor ◽  
J. Brent Roberts
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Active Phase ◽  
Radiative Heating ◽  
Sea Surface ◽  
Integrated Analysis ◽  
Moist Static Energy ◽  
Diurnal Warming ◽  
Static Energy

AbstractDiurnal air-sea coupling affects climate modes such as the Madden-Julian Oscillation (MJO) via the regional moist static energy budget. Prior to MJO initiation, large-scale subsidence increases (decreases) surface shortwave insolation (winds). These act in concert to significantly warm the uppermost layer of the ocean over the course of a single day and the ocean mixed layer over the course of 1-2 weeks. Here, we provide an integrated analysis of multiple surface, top-of-atmosphere, and atmospheric column observations to assess the covariability related to regions of strong diurnal sea surface temperature (dSST) warming over 44 MJO events between 2000-2018 to assess their role in MJO initiation. Combining satellite observations of evaporation and precipitation with reanalysis moisture budget terms, we find 30-50% enhanced moistening over high dSST regions during late afternoon using either ERA5 or MERRA-2 despite large model biases. Diurnally developing moisture convergence, only modestly weaker evaporation, and diurnal minimum precipitation act to locally enhance moistening over broad regions of enhanced diurnal warming, which rectifies onto the larger scale. Field campaign ship and sounding data corroborate that strong dSST periods are associated with reduced middle tropospheric humidity and larger diurnal amplitudes of surface warming, evaporation, instability, and column moistening. Further, we find greater daytime increases in low cloud cover and evidence of enhanced radiative destabilization for the top 50th dSST percentile. Together, these results support that dSST warming acts in concert with large-scale dynamics to enhance moist static energy during the suppressed to active phase transition of the MJO.

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