Rydberg Quantum Wires for Maximum Independent Set Problems with Nonplanar and High-Degree Graphs

One prominent application of near-term quantum computing devices is to solve combinatorial optimization such as non-deterministic polynomial-time hard (NP-hard) problems. Here we present experiments with Rydberg atoms to solve one of the NP-hard problems, the maximum independent set (MIS) of graphs. We introduce the Rydberg quantum wire scheme with auxiliary atoms to engineer long-ranged networks of qubit atoms. Three-dimensional (3D) Rydberg-atom arrays are constructed, overcoming the intrinsic limitations of two-dimensional arrays. We demonstrate Kuratowski subgraphs and a six-degree graph, which are the essentials of non-planar and high-degree graphs. Their MIS solutions are obtained by realizing a programmable quantum simulator with the quantum-wired 3D arrays. Our construction provides a way to engineer many-body entanglement, taking a step toward quantum advantages in combinatorial optimization.Comment: 8 pages, 4 figure

Solving PDE-constrained Control Problems using Operator Learning

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An Autonomous Coil Alignment System for the Dynamic Wireless Charging of Electric Vehicles to Minimize Lateral Misalignment

This paper proposes an autonomous coil alignment system (ACAS) for electric vehicles (EVs) with dynamic wireless charging (DWC) to mitigate the reduction in received power caused by lateral misalignment between the source and load coils. The key component of the ACAS is a novel sensor coil design, which can detect the load coil’s left or right position relative to the source coil by observing the change in voltage phase. This allows the lateral misalignment to be estimated through the wireless power transfer (WPT) system alone, which is a novel tracking method for vehicular applications. Once misalignment is detected, the vehicle’s lateral position is self-adjusted by an autonomous steering function. The feasibility of the overall operation of the ACAS was verified through simulation and experiments. In addition, an analysis based on experimental results was conducted, demonstrating that 26% more energy can be transferred during DWC with the ACAS, just by keeping the vehicle’s load coil aligned with the source coil

Large-scale, single-oriented ZnO nanostructure on h-BN films for flexible inorganic UV sensors

We report the growth of large-scale, single-oriented zinc oxide (ZnO) nanowall networks on epitaxial hexagonal boron nitride (h-BN) films and their application to flexible inorganic ultraviolet (UV) light sensors. Using catalyst-free metal-organic vapor phase epitaxy, ZnO nanowall networks with good vertical alignment are grown on epitaxial h-BN films. The single-oriented crystal structure of the ZnO nanostructures on h-BN is investigated using x-ray diffraction (XRD) spectroscopy, and the heteroepitaxial relationship between ZnO and h-BN is revealed through synchrotron radiation XRD. Interestingly, when utilizing the grown ZnO nanostructure as a channel for UV sensors, better performance merits such as a high I-UV/I-dark ratio, faster recovery time, and low dark current are achieved if h-BN is employed as a growth template. As an example of inorganic flexible optoelectronic device applications, flexible UV sensors are fabricated using ZnO/h-BN heterostructures owing to the insulating and transferrable nature of h-BN substrates. The sensor maintained an excellent performance, even under highly bent conditions

A newly developed capture-based sequencing panel for genomic assay of lung cancer

Background The increase in genetic alterations targeted by specific chemotherapy in lung cancer has led to the need for universal use of more comprehensive genetic testing, which has highlighted the development of a lung cancer diagnostic panel using next-generation sequencing. Objective We developed a hybridization capture-based massively parallel sequencing assay named Friendly, Integrated, Research-based, Smart and Trustworthy (FIRST)-lung cancer panel (LCP), and evaluated its performance. Methods FIRST-LCP comprises 64 lung cancer-related genes to test for various kinds of genetic alterations including single nucleotide variations (SNVs), insertions and deletions (indels), copy number variations (CNVs), and structural variations. To assess the performance of FIRST-LCP, we compiled test sets using HapMap samples or tumor cell lines with disclosed genetic information, and also tested our clinical lung cancer samples whose genetic alterations were known by conventional methods. Results FIRST-LCP accomplished high sensitivity (99.4%) and specificity (100%) of the detection of SNVs. High precision was also achieved, with intra- or inter-run concordance rate of 0.99, respectively. FIRST-LCP detected indels and CNVs close to the expected allele frequency and magnitude, respectively. Tests with samples from lung cancer patients also identified all SNVs, indels and fusions. Conclusion Based on the current state of the art, continuous application of the panel design and analysis pipeline following up-to-date knowledge could ensure precision medicine for lung cancer patients.