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Efficient product formulas for commutators and applications to quantum simulation

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Physical Review Research 2022年第1期4卷 013191-013191页

作者： Yu-An Chen Andrew M. Childs Mohammad Hafezi Zhang Jiang Hwanmun Kim Yijia Xu Google Quantum AI 340 Main Street Venice California 90291 USA Department of Physics and Joint Quantum Institute NIST/University of Maryland College Park Maryland 20742 USA Condensed Matter Theory Center University of Maryland College Park Maryland 20472 USA Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Department of Computer Science University of Maryland College Park Maryland 20742 USA Institute for Advanced Computer Studies University of Maryland College Park Maryland 20742 USA Departments of Electrical and Computer Engineering and Institute for Research in Electronics and Applied Physics University of Maryland College Park Maryland 20742 USA Institute for Physical Science and Technology University of Maryland College Park Maryland 20742 USA

We construct product formulas for exponentials of commutators and explore their applications. First, we directly construct a third-order product formula with six exponentials by solving polynomial equations obtained using the operator differential method. We then derive higher-order product formulas recursively from the third-order formula. We improve over previous recursive constructions, reducing the number of gates required to achieve the same accuracy. In addition, we demonstrate that the constituent linear terms in the commutator can be included at no extra cost. As an application, we show how to use the product formulas in a digital protocol for counterdiabatic driving, which increases the fidelity for quantum state preparation. We also discuss applications to quantum simulation of one-dimensional fermion chains with nearest- and next-nearest-neighbor hopping terms, and two-dimensional fractional quantum Hall phases.

关键词： Fractional quantum Hall effect Quantum algorithms Quantum computation Quantum control Quantum simulation Abstract algebra

Figure-of-Merit for a Long-Term Survivorship of a Species Determined from the Short-Term Mortality Rate of Its Individual Organisms

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Biophysical Reviews and Letters 2021年第3期16卷 111-123页

作者： E. Suhir Bell Laboratories Physical Science and Engineering Research Division Murray Hill NJ USA Departments of Mechanical and Materials Engineering and Electrical and Computer Engineering Portland State University Portland OR USA Department of Applied Electronic Materials Institute of Sensors and Actuators Technical University Vienna Austria Mackay Institute of Research and Innovation James Cook University Townsville Queensland Australia ERS Co. 727 Alvina Ct. Los Altos CA 94024 USA

The two analytical (“mathematical”) probabilistic predictive models considered in this analysis suggest that (1) the nonrandom time-derivative of the long-term mortality rate at a rather arbitrary initial moment of time for a particular type of species of interest can be viewed as a suitable physical or biological criterion, a sort of a figure of merit (FoM), of its long-term viability/survivorship and that (2) this derivative can be determined as the variance of the random mortality rate for the significantly shorter, of course, lifespan of the individual organisms that the type of species as a whole, addressed by the first model, is comprised of. This suggestion is obtained as a modification and extension of and as an “analogy” to a concept that the author developed earlier in application to microelectronics products. So, it is assumed in our approach that the long-term survivorship of a species comprised of numerous individual organisms is analogous to the long-term performance of an electronic product comprised of numerous mass-produced components. In the original research, it was shown that the time-derivative at the initial moment of time of the nonrandom infant mortality portion (IMP) of the bathtub curve (BTC) for an electronic product is, in effect, the variance of the random failure rate (RFR) of the mass-produced components that this product is comprised of, and it is assumed that such an analogy is applicable also to the long-term survivorship of a species comprised of numerous individual organisms. The larger this variance, the shorter is the expected long-term lifetime (survivorship) of the species as a whole. Future work should be focused, first of all, on the verification of the trustworthiness of our basic assumption for different species, including humans, and on the accumulation of statistical data for long-term survivorship of various species and their existing or future habitats, with consideration of the roles of gravity, temperature, level of

关键词： Evolutionary biology figure-of-merit survivorship of species mortality rate individual organisms probabilistic approach

How likely is a random graph shift-enabled?

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arXiv 2021年

作者： Chen, Liyan Cheng, Samuel Stankovic, Vladimir Stankovic, Lina Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University Zhejiang Zhoushan316022 China Department of Computer Science and Technology Tongji University Shanghai201804 China School of Electrical and Computer Engineering University of Oklahoma OK74105 United States Department of Electronic and Electrical Engineering University of Strathclyde GlasgowG1 1XW United Kingdom

The shift-enabled property of an underlying graph is essential in designing distributed filters. This article discusses when a random graph is shift-enabled. In particular, popular graph models Erdős–Rényi (ER), Watts–Strogatz (WS), Barabási–Albert (BA) random graph are used, weighted and unweighted, as well as signed graphs. Our results show that the considered unweighted connected random graphs are shift-enabled with high probability when the number of edges is moderately high. However, very dense graphs, as well as fully connected graphs, are not shift-enabled. Interestingly, this behaviour is not observed for weighted connected graphs, which are always shift-enabled unless the number of edges in the graph is very low. © 2021, CC BY.

关键词： Signal processing

Decoherence of a tunable capacitively shunted flux qubit

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arXiv 2023年

作者： Trappen, R. Dai, X. Yurtalan, M.A. Melanson, D. Tennant, D.M. Martinez, A.J. Tang, Y. Gibson, J. Grover, J.A. Disseler, S.M. Basham, J.I. Das, R. Kim, D.K. Melville, A.J. Niedzielski, B.M. Hirjibehedin, C.F. Serniak, K. Weber, S.J. Yoder, J.L. Oliver, W.D. Lidar, D.A. Lupascu, A. Institute for Quantum Computing Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy Dartmouth College Hanover03755 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Lincoln Laboratory Massachusetts Institute of Technology LexingtonMA02421 United States Departments of Electrical & Computer Engineering Chemistry and Physics Center for Quantum Information Science & Technology University of Southern California Los AngelesCA90089 United States Waterloo Institute for Nanotechnology University of Waterloo WaterlooONN2L 3G1 Canada

We present a detailed study of the coherence of a tunable capacitively-shunted flux qubit, designed for coherent quantum annealing applications. The measured relaxation at the qubit symmetry point is mainly due to intrinsic flux noise in the main qubit loop for qubit frequencies below ∼ 3 GHz. At higher frequencies, thermal noise in the bias line makes a significant contribution to the relaxation, arising from the design choice to experimentally explore both fast annealing and high-frequency control. The measured dephasing rate is primarily due to intrinsic low-frequency flux noise in the two qubit loops, with additional contribution from the low-frequency noise of control electronics used for fast annealing. The flux-bias dependence of the dephasing time also reveals apparent noise correlation between the two qubit loops, possibly due to non-local sources of flux noise or junction critical-current noise. Our results are relevant for ongoing efforts toward building superconducting quantum annealers with increased coherence. Copyright © 2023, The Authors. All rights reserved.

关键词： Qubits

Polarimetric infrared spectroscopic imaging using quantum cascade lasers

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Polarimetric infrared spectroscopic imaging using quantum ca...

Advanced Chemical Microscopy for Life science and Translational Medicine 2020

作者： Phal, Yamuna Yeh, Kevin Bhargava, Rohit Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL United States Departments of Bioengineering Chemical and Biomolecular Engineering Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL United States Cancer Center at Illinois University of Illinois at Urbana-Champaign UrbanaIL United States 4265 Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 N. Mathews Avenue UrbanaIL61801 United States

ISBN: (纸本)9781510632677

Infrared spectroscopic imaging has emerged as a powerful label-free diagnostic tool to study the molecular composition and organization in biological tissues and cells. We report infrared spectroscopic imaging using polarized light to study differential absorption of plane-polarized light by an oriented sample to detect valuable information, such as, birefringence and dichroism. For instance, the organization of collagen, specifically fiber orientation and alignment, is crucial in understanding the progression and metastasis of cancer. Recent advancements in the development of Quantum Cascade Lasers (QCL) sources have opened new avenues for high SNR measurements in the field of IR spectroscopy. In addition, QCL sources are intrinsically polarized and orientation information can be obtained at discrete frequencies with different polarization orientations, allowing much faster acquisition than a corresponding FT-IR approach. We demonstrate improved performance in terms of fast and comprehensive polarimetric image acquisition and analysis using custom-built QCL microscope and evaluate its impact on applications by analyzing the important spectral bands of surgical tissue sections. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Collagen

A hybrid facial recognition approach based on grasshopper optimization method

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AIP Conference Proceedings 2023年第1期2979卷

作者： Dyala R. Ibrahim Hisham A. Shehadeh Mohammad A. Aladaileh Kamal Alieyan Ghaith M. Jaradat We’am Telfah Xiaopeng Wang Cyber Security Department Amman Arab University Amman Jordan Computer Science and Computer Information System departments Amman Arab University Amman Jordan School of Computer Sciences Universiti Sains Malaysia Penang Malaysia Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava Czech Republic

This paper introduces a new “Facial Recognition (FR)” approach based on a new relatively optimization method. This new FR approach is used to mitigate the limitations of recent FR approaches, which are low accuracy and efficiency that caused by high dimensionality of facial images according to unconstrained conditions, such as expression, occlusion, and noise. The “Grasshopper Optimization Algorithm (GOA)” is selected in this work, which outperformed thirteen optimization methods compared early in the literature. In this paper, the efficacy of a hybrid extraction method in conjunction with the K-nearest neighbor classifier is investigated. When compared to other recently developed FR approaches, the performance evaluation of the hybrid “Facial Recognition System (FRS)” depends on the “Grasshopper Optimization Algorithm (GOA)” indicates a near-ideal recognition rate with optimization. In comparisons with the other approaches of recent proposed facial recognition techniques, the proposed algorithm achieved a significant accuracy.

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PSGR: Pixel-wise sparse graph reasoning for COVID-19 pneumonia segmentation in CT images

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arXiv 2021年

作者： Jia, Haozhe Tang, Haoteng Ma, Guixiang Cai, Weidong Huang, Heng Zhan, Liang Xia, Yong National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China Intel Labs 2111 NE 25th Ave HillsboroOR97124 United States School of Computer Science University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States JD Finance America Corporation Mountain View CaliforniaCA94043 United States

Automated and accurate segmentation of the infected regions in computed tomography (CT) images is critical for the prediction of the pathological stage and treatment response of COVID-19. Several deep convolutional neural networks (DCNNs) have been designed for this task, whose performance, however, tends to be suppressed by their limited local receptive fields and insufficient global reasoning ability. In this paper, we propose a pixel-wise sparse graph reasoning (PSGR) module and insert it into a segmentation network to enhance the modeling of long-range dependencies for COVID-19 infected region segmentation in CT images. In the PSGR module, a graph is first constructed by projecting each pixel on a node based on the features produced by the segmentation backbone, and then converted into a sparsely-connected graph by keeping only K strongest connections to each uncertain pixel. The long-range information reasoning is performed on the sparsely-connected graph to generate enhanced features. The advantages of this module are two-fold: (1) the pixel-wise mapping strategy not only avoids imprecise pixel-to-node projections but also preserves the inherent information of each pixel for global reasoning;and (2) the sparsely-connected graph construction results in effective information retrieval and reduction of the noise propagation. The proposed solution has been evaluated against four widely-used segmentation models on three public datasets. The results show that the segmentation model equipped with our PSGR module can effectively segment COVID-19 infected regions in CT images, outperforming all other competing models. Copyright © 2021, The Authors. All rights reserved.

关键词： Pixels

Quantum Gates on Individually-Addressed Atomic Qubits Subject to Noisy Transverse Motion

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arXiv 2020年

作者： Cetina, M. Egan, L.N. Noel, C.A. Goldman, M.L. Risinger, A.R. Zhu, D. Biswas, D. Monroe, C. Joint Quantum Institute Center for Quantum Information and Computer Science Departments of Physics and Electrical and Computer Engineering University of Maryland College ParkMD20742 United States

Individual trapped atomic qubits represent one of the most promising technologies to scale quantum computers, owing to their negligible idle errors and the ability to implement a full set of reconfigurable gate operations via focused optical fields. However, the fidelity of quantum gate operations can be limited by weak confinement of the atoms transverse to the laser. We present measurements of this effect by performing individually-addressed entangling gates in chains of up to 25 trapped atomic ions that are weakly confined along the chain axis. We present a model that accurately describes the observed decoherence from the residual heating of the ions caused by noisy electric fields. We propose to suppress these effects through the use of ancilla ions interspersed in the chain to sympathetically cool the qubit ions throughout a quantum circuit. Copyright © 2020, The Authors. All rights reserved.

关键词： Logic gates

CIDNet: Cross-Scale Interference Mining Detection Network for underwater object detection

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Knowledge-Based Systems 2025年 324卷

作者： Gaoli Zhao Kefei Zhang Liangzhi Wang Wenyi Zhao Weidong Zhang School of Computer and Technology Henan Institute of Science and Technology Xinxiang China University of Sheffield Sheffield England United Kingdom Beijing University of Posts and Telecommunications Beijing China School of Information Engineering Henan Institute of Science and Technology Xinxiang China Advanced Ocean Institute of Southeast University Southeast University Nantong China School of Electrical and Information Engineering Zhengzhou University Zhengzhou China

Underwater object detection plays a crucial role in advancing marine economics, protecting the environment, and promoting the planet’s sustainable development. Compared to land-based scenes, underwater object detection is often hindered by color deviation and low visibility. To effectively address these interference issues, we propose a Cross-Scale Interference Mining Detection Network (CIDNet). We first extract multidimensional feature representations from the input images using a standard residual network backbone, which uses a deep structure and residual connectivity mechanism. We then refine these features through interference mining and cross-scale feature fusion strategies, and further enhance feature hierarchy levels using adaptive feature mapping optimization. In addition, we introduce three-dimensional convolution combination with a channel dimension unification strategy to enhance the fine-grained representation of hierarchical feature layers. Finally, the refined features are fed into a Task-aligned detection head module, which improves the detection accuracy by optimizing a collaboration between classification and localization tasks through a task-aligned learning strategy. Extensive experiments conducted on the DUO and COCO datasets demonstrate that our method effectively detects hidden objects in realistic underwater scenes and significantly outperforms current state-of-the-art methods in terms of accuracy. The codes and model weights will be available at https://***/publication/390270613_CIDNet .

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