In this work, we introduce a framework for designing system-agnostic quantum experiments at the pulse level. Our framework uses pulselib, a Python package for system independent graphical representations of arbitrary ...
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ISBN:
(纸本)9798331541378
In this work, we introduce a framework for designing system-agnostic quantum experiments at the pulse level. Our framework uses pulselib, a Python package for system independent graphical representations of arbitrary pulses, as the domain-specific language for describing experiments. We bridge the gap between the abstract pulse representation in pulselib and the specifics of a target backend by defining a set of operations necessary to convert and synthesize pulses. By employing a handle-based architecture, we decouple experiment code from the underlying backend instruction set. We demonstrate the utility of this framework by enabling reusable quantum experiments using an ARTIQ platform equipped with direct digital synthesizers and recreating complex pulse modulation schemes relevant to trapped-ion experiments.
The Unmanned Surface Vehicle(USV) cluster system is an organization system which realizes the grouping of many unmanned Vehicle on demand under the support of marine information system, and realizes the integration of...
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With the changes in modern families and the needs of infants, traditional parenting methods are no longer able to meet the needs of parents. In order to provide a more advanced and convenient parenting method, this st...
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Parallel discrete event simulation is a fundamental simulation technology that is essential to the parallelization of event-based models including hardware and transportation systems. Parallelization is often difficul...
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ISBN:
(纸本)9798400703638
Parallel discrete event simulation is a fundamental simulation technology that is essential to the parallelization of event-based models including hardware and transportation systems. Parallelization is often difficult due to dynamic data-dependencies and limited computational work for hiding runtime overheads. We present Devastator, a scalable parallel discrete event simulation framework for modern C++. Devastator provides a productive API that leverages C++'s type system to eliminate boilerplate code. Devastator has been designed to specifically optimize performance on distributed many-core architectures with deepening memory hierarchies. Devastator relies on the GASNet-Ex communication runtime as well as lock-free message queues to achieve highly competitive performance. We perform strong and weak scaling studies on NERSC's Perlmutter up to 32,698 cores and demonstrate an up to 5x speed-up over the ROSS simulator for workloads with substantial locality.
Due to the complexity of the structure of doubly-fed induction generator (DFIG), it is difficult to conduct real-time simulation. For this reason, this paper designs an embeddable parallel digital image IP of DFIG bas...
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Due to the complexity of the structure of doubly-fed induction generator (DFIG), it is difficult to conduct real-time simulation. For this reason, this paper designs an embeddable parallel digital image IP of DFIG based on field programmable logic array (FPGA) to realize efficient electromagnetic simulation of DFIG. First, this paper proposes a virtual capacitor equivalent method for induction machine equivalent "T" circuit decoupling;Secondly, based on the principle of data independence and parallelism within the time step, a parallel algorithm for the internal components of DFIG is proposed;Finally, the FPGA-DFIG digital image constructed in this paper is connected to the RT-LAB/power grid, and hardware experiments are carried out under three working conditions: steady state, voltage sag and DC side fault. The experimental results are compared with the simulation results of DFIG grid connected system built in MATLAB/Simulink environment to verify the effectiveness and rapidity of the methods and models proposed in this paper.(C) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 2nd international Joint conference on Energy and Environmental Engineering, CoEEE, 2022.
The constant evolution of high-speed digital inter- faces has created a demand for robust and reliable designs. As a key component in ensuring reliable data transfer, receiver training sequence modules play a critical...
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Turbulence is a three-dimensional fluid motion state with multiple scales and mutual coupling in time and space. Studying turbulence phenomena is crucial for the design and drag reduction of aircraft and engines. In r...
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ISBN:
(纸本)9798331520519;9798331520502
Turbulence is a three-dimensional fluid motion state with multiple scales and mutual coupling in time and space. Studying turbulence phenomena is crucial for the design and drag reduction of aircraft and engines. In recent years, with the powerful computing power of computers, data-based turbulence research methods have become a hot topic, such as the Direct Numerical simulation (DNS) method, which is receiving attention. However, compared to Large Eddy simulation (LES), the amount of data generated by direct numerical simulation methods far exceeds that of traditional LES, which brings difficulties in data storage. Abroad, multiple research institutions in Europe, the United States, and Japan have established multiple turbulence data sharing platforms, but the construction of turbulence data sharing platforms in China is still in a blank stage. This article first analyzes the characteristics of turbulence science big data, and then starts from the practical problems faced by domestic research institutions when sharing and using data, designs and implements the first independently controllable turbulence data sharing platform in China. Currently, the platform has integrated 180TB of data from five domestic universities and research institutions, providing an important resource sharing platform and data research tool for turbulence researchers in China.
Recent advances in reinforcement learning (RL) have shown much promise across a variety of applications. However, issues such as scalability, explainability, and Markovian assumptions limit its applicability in certai...
Recent advances in reinforcement learning (RL) have shown much promise across a variety of applications. However, issues such as scalability, explainability, and Markovian assumptions limit its applicability in certain domains. We observe that many of these shortcomings emanate from the simulator as opposed to the RL training algorithms themselves. As such, we propose a semantic proxy for simulation based on a temporal extension to annotated logic. In comparison with two high-fidelity simulators, we show up to three orders of magnitude speed-up while preserving the quality of policy learned. In addition, we show the ability to model and leverage non-Markovian dynamics and instantaneous actions while providing an explainable trace describing the outcomes of the agent actions.
Aiming at the problems of the old models of fuel oil and lube oil separators in the existing domestic and foreign marine engine simulators, which can not carry out fault checking training and can not meet the requirem...
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Based on the detection process of the armored target by millimeter wave radiometer on bomb, the radiometer coordinate system, the armored target coordinate system, and the background coordinate system were established...
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