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Entanglement-assisted phase-estimation algorithm for calculating dynamical response functions

Physical Review A 2024年第2期110卷 022618页

作者： Rei Sakuma Shu Kanno Kenji Sugisaki Takashi Abe Naoki Yamamoto Materials Informatics Initiative RD Technology & Digital Transformation Center Quantum Computing Center Science & Innovation Center Yokohama 227-8502 Japan Graduate School of Science and Technology Centre for Quantum Engineering Research and Education Department of Applied Physics and Physico-Informatics

Dynamical response functions are fundamental quantities to describe the excited-state properties in quantum many-body systems. quantum algorithms have been proposed to evaluate these quantities by means of quantum phase estimation (QPE), where the energy spectra are directly extracted from the QPE measurement outcomes in the frequency domain. Accurate estimation of excitation energies and transition probabilities with these QPE-based approaches is, however, challenging because of the problem of spectral leakage (or peak broadening) which is inherent in the QPE algorithm. To overcome this issue, in this work we consider an extension of the QPE-based approach adopting the optimal entangled input states, which is known to achieve the Heisenberg-limited scaling for the estimation precision. We show that with this method the peaks in the calculated energy spectra are more localized than those calculated by the original QPE-based approaches, suggesting the mitigation of the spectral leakage problem. By analyzing the probability distribution with the entangled phase estimation, we propose a simple scheme to better estimate both the transition energies and the corresponding transition probabilities of the peaks of interest in the spectra. The validity of our prescription is demonstrated by numerical simulations in various quantum many-body problems: the spectral function of a simple electron-plasmon model in condensed-matter physics, the dipole transitions of the H2O molecule in quantum chemistry, and the electromagnetic transitions of the Li6 nucleus in nuclear physics.

关键词： Electronic transitions Nuclear transition rates quantum computation Green's function methods

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Secrecy Capacity Optimization in RF/FSO Systems: Impact of Mixed Rayleigh and Log-Normal Fading with Atmospheric Turbulence

Secrecy Capacity Optimization in RF/FSO Systems: Impact of M...

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2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

This paper investigates the secrecy capacity optimization in RF/FSO systems with mixed Rayleigh and log-normal fading, while masking eavesdroppers channel state information () as well as suffering from atmospheric turbulence. We explore the impact of several parameters including beamforming angles, modulation schemes and hybrid RF/FSO link configurations through a combination of simulations as well as analytical models. Secrecy capacity is enhanced for an improved SNR and vice versa under higher turbulence conditions and cooler influents eavesdropped scenarios. Performance of the hybrid RF/FSO systems dominates considerably over single-link solutions, especially at longer distances. All these mechanisms appreciably increase the secrecy capacity, while beamforming and advanced modulation techniques offer most of the improvement. The study also demonstrates the interdependencies of system parameters, providing guidelines for designing secure communication systems under different environmental and operational conditions. © 2024 IEEE.

关键词： Beamforming

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quantum-Enhanced LLM Efficient Fine Tuning

arXiv

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arXiv 2025年

作者： Kong, Xiaofei Li, Lei Dou, Menghan Chen, Zhaoyun Wu, Yuchun Guo, Guoping Origin Quantum Computing Company Limited Hefei230088 China Anhui Engineering Research Center of Quantum Computing Hefei230026 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Anhui Hefei230088 China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China

Low-Rank Adaptation (LoRA) enables efficient fine-tuning of pre-trained language models via low-rank matrix approximation, which is effective in many scenarios. However, its low-rank representation capacity is constrained in complex tasks or high-rank dependency settings, potentially limiting model adaptability. Addressing the expressive bottleneck of classical low-rank approximation in fine-tuning large language models, this paper proposes a parameter-efficient fine-tuning method based on a quantum Weighted Tensor Hybrid Network (QWTHN), which leverages quantum Neural Network (QNN). The study investigates quantum-classical hybrid parameter-efficient fine-tuning in low-rank spaces. QWTHN decomposes pre-trained weights into quantum neural network and tensor network representations, utilizing quantum state superposition and other methods to break through classical rank limitations. Experiments show that the proposed quantum fine-tuning technique for large models approaches or even surpasses the parameter efficiency of LoRA. On the CPsyCounD and R1-Distill-SFT datasets, QWTHN, compared to classical LoRA, reduces training loss by up to 15% while using 76% fewer parameters, and achieves an 8.4% performance improvement on the CPsyCounD test set. This research not only realizes lightweight and efficient adaptation of quantum resources to billion-parameter models but also validates the practical path of quantum hardware driven by large model tasks, laying the first engineering-ready technical foundation for future quantum-enhanced AGI systems. © 2025, CC BY.

关键词： Tensors

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quantum Poisson solver without arithmetic

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Intelligent Marine Technology and Systems 2024年第1期2卷 1-15页

作者： Wang, Shengbin Wang, Zhimin Cui, Guolong Shi, Shangshang Shang, Ruimin Li, Jiaxin Li, Wendong Wei, Zhiqiang Gu, Yongjian Faculty of Information Science and Engineering Ocean University of China Qingdao China Origin Quantum Computing Company Limited Hefei China Beijing Zhongke Arclight Quantum Software Technology Co. Ltd. Beijing China High Performance Computing Center Pilot National Laboratory for Marine Science and Technology (Qingdao) Qingdao China

Solving differential equations is one of the most promising applications of quantum computing. The Poisson equation has applications in various domains of physics and engineering, including the simulation of ocean current dynamics. Here, we propose an efficient quantum algorithm for solving the one-dimensional Poisson equation based on the controlled Ry rotations. Our quantum Poisson solver (QPS) removes the need for expensive routines such as phase estimation, quantum arithmetic or Hamiltonian simulation. The computational cost of our QPS is 3n in qubits and 5/3n 3 in one- and two-qubit gates, where n is the logarithmic of the number of discrete points. An overwhelming reduction of the constant factors of the big-O complexity is achieved, which is critical to evaluate the practicality of implementing the algorithm on a quantum computer. In terms of the error ε, the complexity is log(1/ε) in qubits and poly(log(1/ε)) in operations. The algorithms are demonstrated using a quantum virtual computing system, and the circuits are executed successfully on the IBM real quantum computers. The present QPS could exhibit a potential real-world application for solving differential equations on noisy intermediate-scale quantum (NISQ) devices.

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Graphene amplifier reaches the quantum-noise limit

arXiv

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arXiv 2023年

作者： Fong, Kin Chung Raytheon Bbn Technologies Quantum Engineering and Computing Group CambridgeMA02138 United States

关键词： Graphene

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Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure

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IEEE Transactions on Dependable and Secure computing 2025年

作者： Deng, Zehang Sun, Ruoxi Xue, Minhui Wen, Sheng Camtepe, Seyit Nepal, Surya Xiang, Yang Swinburne University of Technology School of Science Computing and Engineering Technologies MelbourneVIC Australia CSIRO's Data61 Cybersecurity and Quantum Systems Group Australia

AI-enabled critical infrastructures (ACIs) integrate artificial intelligence (AI) technologies into various essential systems and services that are vital to the functioning of society, offering significant implications for efficiency, security and resilience. While adopting decentralized AI approaches (such as federated learning technology) in ACIs is plausible, private and sensitive data are still susceptible to data reconstruction attacks through gradient optimization. In this work, we propose Compressed Differentially Private Aggregation (CDPA), a leakage-resilient, communication-efficient, and carbon-neutral approach for ACI networks. Specifically, CDPA has introduced a novel random bit-flipping mechanism as its primary innovation. This mechanism first converts gradients into a specific binary representation and then selectively flips masked bits with a certain probability. The proposed bit-flipping introduces a larger variance to the noise while providing differentially private protection and commendable efforts in energy savings while applying vector quantization techniques within the context of federated learning. The experimental evaluation indicates that CDPA can reduce communication cost by half while preserving model utility. Moreover, we demonstrate that CDPA can effectively defend against state-of-the-art data reconstruction attacks in both computer vision and natural language processing tasks. We highlight existing benchmarks that generate 2.6× to over 100× more carbon emissions than CDPA. We hope that the CDPA developed in this paper can inform the federated AI-enabled critical infrastructure of a more balanced trade-off between utility and privacy, resilience protection, as well as a better carbon offset with less communication overhead. © 2004-2012 IEEE.

关键词： Federated learning

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Characterizing photon emission from a quantum dot excited by long aboveband pulses

Characterizing photon emission from a quantum dot excited by...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Venuturumilli, S.S. Al Maruf, Rubayet Poole, P.J. Dalacu, D. Reimer, Michael Bajcsy, Michal Department of Electrical and Computer Engineering University of Waterloo WaterlooON Canada Department of Physics and Astronomy University of Waterloo WaterlooON Canada Institute of Quantum Computing University of Waterloo WaterlooON Canada National Research Council Canada OttawaON Canada

We experimentally investigate the quality of single photons produced with longpulse aboveband excitation of a quantum dot embedded in a semiconductor nanowire and model the results via rate equations and Markovchains.... 详细信息

ISBN: (纸本)9781957171258

关键词： Semiconductor quantum dots

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Progress Towards quantum-Enhanced Microwave Remote Sensing and Communication Applications

Progress Towards Quantum-Enhanced Microwave Remote Sensing a...

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US National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)

作者： Jérôme Bourassa Christopher M. Wilson Qubic Inc. Sherbrooke QC CANADA Institute for Quantum Computing & Department of Electrical and Computer Engineering University of Waterloo ON CANADA

RADAR and communications are vulnerable as noise and interference contaminate the received signals and produce errors limiting their resolution, their accuracy and speed. To answer the growing needs for more reliable and accurate microwave intelligence in an ever more complex electromagnetic environment, there is a growing need to develop innovative microwave sensors with greater signal sensitivity, selectivity and integrity.

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Secure Image Communication Using Galois Field,Hyper 3D Logistic Map,and B92 quantum Protocol

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Computers, Materials & Continua 2024年第12期81卷 4435-4463页

作者： De Rosal Ignatius Moses Setiadi Nova Rijati Ahmad Rofiqul Muslikh Bonifacius Vicky Indriyono Aceng Sambas Faculty of Computer Science Universitas Dian NuswantoroSemarang50131Central JavaIndonesia Research Center for Quantum Computing and Materials Informatics Faculty of Computer ScienceUniversitas Dian NuswantoroSemarang50131Central JavaIndonesia Faculty of Information Technology Universitas MerdekaMalang65146East JavaIndonesia Faculty of Economics and Business Universitas STRADA IndonesiaKediri64133East JavaIndonesia Faculty of Informatics and Computing Universiti Sultan Zainal AbidinCampus BesutBesut22200TerengganuMalaysia Department of Mechanical Engineering Universitas Muhammadiyah TasikmalayaTamansari GobrasTasikmalaya46196Indonesia

In this paper,we propose a novel secure image communication system that integrates quantum key distribution and hyperchaotic encryption techniques to ensure enhanced security for both key distribution and plaintext ***,we leverage the B92 quantum Key Distribution(QKD)protocol to secure the distribution of encryption keys,which are further processed through Galois Field(GF(28))operations for increased *** encrypted plaintext is secured using a newly developed Hyper 3D Logistic Map(H3LM),a chaotic system that generates complex and unpredictable sequences,thereby ensuring strong confusion and diffusion in the encryption *** hybrid approach offers a robust defense against quantum and classical cryptographic attacks,combining the advantages of quantum-level key distribution with the unpredictability of hyperchaos-based *** proposed method demonstrates high sensitivity to key changes and resilience to noise,compression,and cropping attacks,ensuring both secure key transmission and robust image encryption.

关键词： Galois field hyper 3D logistic map hyperchaotic map image security improved logistic map secure communication quantum security

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Reversible Tuning of Nanowire quantum Dot to Cesium D1 line

Reversible Tuning of Nanowire Quantum Dot to Cesium D1 line

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Al Maruf, Rubayet Venuturumilli, Sreesh Bharadwaj, Divya Anderson, Paul Qiu, Jiawei Zeeshan, Mohd Semnani, Behrooz Poole, Philip Dalacu, Dan Reimer, Michael Bajcsy, Michal Institute for Quantum Computing University of Waterloo WaterlooON Canada Electrical and Computer Engineering University of Waterloo WaterlooON Canada Dept. of Physics and Astronomy University of Waterloo WaterlooON Canada National Research Council of Canada OttawaON Canada

We report local reversible tuning of nanowire quantum dot emission to cesium D1 line (~ 894.6 nm) and demonstrate slow light and resonant absorption of single photons in hot cesium vapor. © 2023 The Author(s)

ISBN: (纸本)9781957171258

关键词： Nanowires

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