Quantum Optimization with Arbitrary Connectivity Using Rydberg Atom Arrays
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Subatomic physics shares with other basic sciences the need to innovate, invent, and develop tools, techniques, and technologies to carry out its mission to explore the nature of matter, energy, space, and time. In some cases, entire detectors or technologies developed specifically for particle physics research have been adopted by other fields of research or in commercial applications. In most cases, however, the development of new devices and technologies by particle physics for its own research has added value to other fields of research or to applications beneficial to society by integrating them in the existing technologies. Thus, detector research and development has not only advanced the current state of technology for particle physics, but has often advanced research in other fields of science and has underpinned progress in numerous applications in medicine and national security. At the same time particle physics has profited immensely from developments in industry and applied them to great benefit for the use of particle physics detectors. Finally, this symbiotic relationship has seen strong mutual benefits with sometimes unexpected far reach.
The development of systematic effective field theories (EFTs) for nuclear forces and advances in solving the nuclear many-body problem have greatly improved our understanding of dense nuclear matter and the structure of finite nuclei. For global nuclear calculations, density functional theories (DFTs) have been developed to reduce the complexity and computational cost required in describing nuclear systems. However, DFT often makes approximations and assumptions about terms included in the functional, which may introduce systematic uncertainties compared to microscopic calculations using EFTs. In this work, we investigate possible avenues of improving nuclear DFT using nonlinear relativistic mean-field (RMF) theory. We explore the impact of RMF model extensions by fitting the nonlinear RMF model to predictions of nuclear matter and selected closed-shell nuclei using four successful chiral EFT Hamiltonians. We find that these model extensions are impactful and important in capturing the physics present within chiral Hamiltonians, particularly for charge radii and neutron skins of closed-shell nuclei. However, there are additional effects that are not captured within the RMF model, particularly within the isoscalar sector of RMF theory. Additional model extensions and the reliability of the nonlinear RMF model are discussed.
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This paper presents the design and development of an open-code Type-3 wind turbine virtual-testbed for real-time simulations. The proposed testbed includes the bare code for all the models required to emulate a Type-3 wind turbine system: the Doubly-Fed Induction Generator (DFIG) dynamic model, single-mass drive train, wind turbine system, and average model of the back to back power. This testbed can be executed in PC-layer for offline simulations or can be executed in real-time on the National Instruments (NI)-CompactRIO (cRIO) platform. The discrete-time models are implemented on the Field Programmable Gate Array (FPGA), using LabVIEW, and validated against a physical hardware setup. The emulated stator and rotor currents and DC-link voltage are compared against physical measurements creating a validated platform independent from third-party models and suitable for applications in real-time. The proposed testbed is intended to be available to researchers, wind turbine manufacturers, and utility companies to perform tests using a validated platform to verify proposed control designs of DFIG wind turbines.
In this study, a novel three-phase Oak Ridge ac to ac converter is introduced for wireless mobility energy storage system (WMESS) applications for grid support or ancillary service applications. The proposed topology can be used in bidirectional operation between ac grid and ac terminals of energy storage (output of the ESS inverter) by accomplishing unity power factor. Inherent merit of the technology is that it can directly merge ac input 60 Hz grid frequency with the high frequency by superimposing them with the Oak Ridge Converter (ORC) and through the wireless coils. Theoretical and simulation results are provided for 10 kW output power. The functionality of the proposed three-phase system is demonstrated with the coupling coils separated by 6 inches of air gap with the input / output of 277 V AC,RMS . The system overall design is presented, and simulation results demonstrate achieving 3% current total harmonic distortion (THD) and 0.99 power factor (PF) at full load of 10 kW wireless power transfer.
The objective of this paper is to realize a universal dc-side controller for photovoltaic (PV) systems where the control is agnostic to the downstream converter configuration. To achieve this, the downstream power converter and its controls are manipulated into an effective power control loop that is then cast into a generalized multi-loop design framework. On the dc side, a nonlinear small-signal model of the PV input is realized exclusively in terms of PV datasheet parameters (i.e., open-circuit voltage, short-circuit current, and maximum power point). Finally, a linear controller is used to modulate the dc-side PV system with the generic downstream power controller. A Lyapunov candidate is proposed to analyze the stability of the interconnected system and provide a streamlined approach for the controller design. The proposed design is validated on a 1k VA experimental setup that interfaces a PV module to the grid.
Towards the goal of improving functional and performance portability of SYCL, we study a bioinformatics application that has been accelerated with CUDA and fast pseudorandom number generation on a GPU. We describe the experience of migrating pseudorandom number generation from CUDA to SYCL, evaluate the performance of pseudorandom number generators using the CUDA random number generation library, suggest the support of the XORWOW pseudorandom number generator in the oneAPI math kernel library (oneMKL) interface for performance portability, and identify the performance gap using the MKL interface in SYCL that supports pseudorandom number generation with third-party libraries. We hope that the results are valuable for the development of the SYCL ecosystem.
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The residential sector consumes a significant portion of the electricity sold in the United States. Above 60% of the energy used in the sector is used to operate heating, ventilation, and air conditioning (HVAC) systems and water heating (WH) systems. With the increase of intelligence in the grid and the new decision and control options enabled by the Internet of Things; control of these devices can be used to support the grid. Therefore, this article presents a scalable multiagent system for optimizing HVAC and WH systems while maintaining comfort. It allows a utility to orchestrate the shifting of energy from critical periods without direct control, but instead by using a price signal. The architecture, optimization formulation, implementation strategy and results from an implementation project are discussed.
Reducing the power loss of a converter without increasing its volume or cost in hardware has always been a much sought-after but challenging goal. This article proposes a comprehensive variable switching frequency (VSF) scheme to improve the overall system efficiency while still meeting a given total harmonic distortion (THD) requirement without any hardware changes, achieved only by changes to the controller. In this article, it is analyzed that for the H-bridge inverter, the inductor copper loss and the switch conduction loss are independent of the switching frequency (SF), while the device switching loss and the inductor core loss are functions of the SF. This article aims at weighting the combined switching loss and inductor core loss for both the unipolar and bipolar modulation techniques, with the constraint on the output THD, which, for fixed passive components, is a function of inductor ripple current that in turn depends on the SF. An optimal VSF scheme is devised through rigorous mathematical analysis of the output ripple component and the SF-dependent losses. In each switching cycle, the inductor ripple current is predicted with the circuit parameters, such as duty cycle, switching period, inductance, and dc voltage, and by implementing the VSF scheme, the current ripple is optimally varied such as to satisfy the THD requirement while reducing the SF-dependent losses. A generalized method to design VSF schemes for any topology and specifications is also presented, which would help future users in designing the VSF controller. A 1-kW H-bridge inverter using SiC MOSFETs and powdered iron/ferrite core has been built to validate the theoretical analysis. Both constant SF (CSF) scheme (200 kHz) and optimal VSF scheme with simple controller modification have been implemented in the experimental prototype using DSP TMS320f28335. Compared with the CSF scheme, the optimal VSF scheme shows a significant improvement in the system efficiency at rated power from 94.7%...
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U.S. national research laboratories and agencies play an integral role in advancing science and technology for the public good. The authors of this article, as research software engineers (RSEs) and allies from eight unique national R&D organizations, came together to explore RSE needs from the perspective of national institutions. We identified three key areas of improvement for future RSEs to pursue science in the national interest: community establishment, hiring and retention, and recognition. In conclusion, to retain and cultivate this essential talent, U.S. national institutions must evolve to support appropriate career pathways for RSEs, and to recognize and reward RSEs’ work.
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Energy system integration promises in-creased resiliency and the unlocking of synergies, while also contributing to our goal of decarbonization. It is enabled by both old and new technologies, glued together with data and digital services. Hydrolyzers, heat pumps, distributed renewable generation, smart buildings, and the digital grid edge are all currently the subject of integration with the power system and the energy sector at large. To plan and operate such a multidisciplinary and multisectoral system properly, insight, tools, and expertise are all needed. Further, this is exactly where the state of the art fails to deliver: tools for integrated energy systems (IESs) are still in their infancy, and many times, even academia treats these sectors separately, producing experts in each of them but not across.