Modelling weak-coherent CV-QKD systems using a classical simulation framework

Accurate understanding and quantification of the risk to critical infrastructure posed by future large earthquakes continues to be a very challenging problem. Earthquake phenomena are quite complex and traditional approaches to predicting ground motions for future earthquake events have historically been empirically based whereby measured ground motion data from historical earthquakes are homogenized into a common data set and the ground motions for future postulated earthquakes are probabilistically derived based on the historical observations. This procedure has recognized significant limitations, principally due to the fact that earthquake ground motions tend to be dictated by the particular earthquake fault rupture and geologic conditions at a given site and are thus very site-specific. Historical earthquakes recorded at different locations are often only marginally representative. There has been strong and increasing interest in utilizing large-scale, physics-based regional simulations to advance the ability to accurately predict ground motions and associated infrastructure response. However, the computational requirements for simulations at frequencies of engineering interest have proven a major barrier to employing regional scale simulations. In a U.S. Department of Energy Exascale Computing Initiative project, the EQSIM application development is underway to create a framework for fault-to-structure simulations. This framework is being prepared to exploit emerging exascale platforms in order to overcome computational limitations. This article presents the essential methodology and computational workflow employed in EQSIM to couple regional-scale geophysics models with local soil-structure models to achieve a fully integrated, complete fault-to-structure simulation framework. The computational workflow, accuracy and performance of the coupling methodology are illustrated through example fault-to-structure simulations.

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Classical simulation of quantum circuits using fewer Gaussian eliminations

Physical Review A ◽

10.1103/physreva.103.022603 ◽

2021 ◽

Vol 103 (2) ◽

Author(s):

Lucas Kocia ◽

Mohan Sarovar

Keyword(s):

Quantum Circuits ◽

Classical Simulation

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Metamorphic Edge Processor Simulation Framework Using Flexible Runtime Partial Replacement of Software-Embedded Verilog RTL Models

2021 IEEE International Symposium on Circuits and Systems (ISCAS) ◽

10.1109/iscas51556.2021.9401354 ◽

2021 ◽

Author(s):

Jisu Kwon ◽

Sejong Oh ◽

Daejin Park

Keyword(s):

Partial Replacement ◽

Simulation Framework ◽

Processor Simulation

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Exploring RRAM Variability as Synapses on Inception Simulation Framework to Characterize the Prediction Accuracy and Power Estimation per Bit for Convolution Neural Network

2020 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) ◽

10.1109/ipfa49335.2020.9260780 ◽

2020 ◽

Author(s):

N.L. Prabhu ◽

N. Raghavan

Keyword(s):

Neural Network ◽

Prediction Accuracy ◽

Power Estimation ◽

Convolution Neural Network ◽

Simulation Framework

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Multi-Criteria, Co-Evolutionary Charging Behavior: An Agent-Based Simulation of Urban Electromobility

World Electric Vehicle Journal ◽

10.3390/wevj12010018 ◽

2021 ◽

Vol 12 (1) ◽

pp. 18

Author(s):

Lennart Adenaw ◽

Markus Lienkamp

Keyword(s):

Urban Areas ◽

City Planning ◽

User Behavior ◽

Transport Sector ◽

Simulation Framework ◽

Agent Based Simulation ◽

Agent Based ◽

Charging Station ◽

Spatio Temporal

In order to electrify the transport sector, scores of charging stations are needed to incentivize people to buy electric vehicles. In urban areas with a high charging demand and little space, decision-makers are in need of planning tools that enable them to efficiently allocate financial and organizational resources to the promotion of electromobility. As with many other city planning tasks, simulations foster successful decision-making. This article presents a novel agent-based simulation framework for urban electromobility aimed at the analysis of charging station utilization and user behavior. The approach presented here employs a novel co-evolutionary learning model for adaptive charging behavior. The simulation framework is tested and verified by means of a case study conducted in the city of Munich. The case study shows that the presented approach realistically reproduces charging behavior and spatio-temporal charger utilization.

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A Comprehensive Open-Source Simulation Framework for LiFi Communication

Sensors ◽

10.3390/s21072485 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2485

Author(s):

Shakir Ullah ◽

Saeed Ur Rehman ◽

Peter Han Joo Chong

Keyword(s):

Open Source ◽

Hybrid System ◽

Resource Sharing ◽

Optical Gain ◽

Packet Delay ◽

Mobility Model ◽

Network Simulator ◽

Simulation Framework ◽

Light Spectrum ◽

Seamless Integration

Light Fidelity (LiFi) is a new candidate for wireless networking that utilizes the visible light spectrum and exploits the existing lighting infrastructure in the form of light-emitting diodes (LEDs). It provides point-to-point and point-to-multipoint communication on a bidirectional channel at very high data rates. However, the LiFi has small coverage, and its optical gain is closely related to the receiver’s directionality vis-à-vis the transmitter, therefore it can experience frequent service outages. To provide reliable coverage, the LiFi is integrated with other networking technologies such as wireless fidelity (WiFi) thus forming a hybrid system. The hybrid LiFi/WiFi system faces many challenges including but not limited to seamless integration with the WiFi, support for mobility, handover management, resource sharing, and load balancing. The existing literature has addressed one or the other aspect of the issues facing LiFi systems. There are limited free source tools available to holistically address these challenges in a scalable manner. To this end, we have developed an open-source simulation framework based on the network simulator 3 (ns-3), which realizes critical aspects of the LiFi wireless network. Our developed ns-3 LiFi framework provides a fully functional AP equipped with the physical layer and medium access control (MAC), a mobility model for the user device, and integration between LiFi and WiFi with a handover facility. Simulation results are produced to demonstrate the mobility and handover capabilities, and the performance gains from the LiFi-WiFi hybrid system in terms of packet delay, throughput, packet drop ratio (PDR), and fairness between users. The source code of the framework is made available for the use of the research community.

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