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quantum 2.0, quantum 2024 in quantum 2.0 Conference and Exhibition

作者： Sonoyama, Tatsuki Takahashi, Kazuma Nomura, Takefumi Sano, Tomoki China, Fumihiro Yabuno, Masahiro Miki, Shigehito Terai, Hirotaka Takase, Kan Asavanant, Warit Endo, Mamoru Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi-ku Hyogo Kobe651-2492 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan

Single-pixel superconducting nanostrip photon detectors (SNSPDs) have both low timing jitter of 50 ps and photon-number-resolving capability. We generate multi-photon Fock states with Wigner negativities using SNSPDs,... 详细信息

ISBN: (纸本)9781557525185

关键词： Timing jitter

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Learning to Predict Arbitrary quantum Processes

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PRX quantum 2023年第4期4卷 040337-040337页

作者： Hsin-Yuan Huang Sitan Chen John Preskill Institute for Quantum Information and Matter and Department of Computing and Mathematical Sciences Caltech Pasadena California USA Department of Electrical Engineering and Computer Sciences UC Berkeley Berkeley California USA AWS Center for Quantum Computing Pasadena California USA

We present an efficient machine-learning (ML) algorithm for predicting any unknown quantum process E over n qubits. For a wide range of distributions D on arbitrary n-qubit states, we show that this ML algorithm can learn to predict any local property of the output from the unknown process E, with a small average error over input states drawn from D. The ML algorithm is computationally efficient even when the unknown process is a quantum circuit with exponentially many gates. Our algorithm combines efficient procedures for learning properties of an unknown state and for learning a low-degree approximation to an unknown observable. The analysis hinges on proving new norm inequalities, including a quantum analogue of the classical Bohnenblust-Hille inequality, which we derive by giving an improved algorithm for optimizing local Hamiltonians. Numerical experiments on predicting quantum dynamics with evolution time up to 106 and system size up to 50 qubits corroborate our proof. Overall, our results highlight the potential for ML models to predict the output of complex quantum dynamics much faster than the time needed to run the process itself.

关键词： quantum computation quantum information processing quantum information theory

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Hamiltonian learning using machine-learning models trained with continuous measurements

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Physical Review Applied 2024年第4期22卷 044080页

作者： Kris Tucker Amit Kiran Rege Conor Smith Claire Monteleoni Tameem Albash Department of Applied Mathematics Department of Computer Science Center for Quantum Information and Control Department of Electrical and Computer Engineering Paris France Center for Computing Research

We build upon recent work on the use of machine-learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning, where the weak-measurement training record can be labeled with known Hamiltonian parameters, and (2) unsupervised learning, where no labels are available. The first has the advantage of not requiring an explicit representation of the quantum state, thus potentially scaling very favorably to a larger number of qubits. The second requires the implementation of a physical model to map the Hamiltonian parameters to a measurement record, which we implement using an integrator of the physical model with a recurrent neural network to provide a model-free correction at every time step to account for small effects not captured by the physical model. We test our construction on a system of two qubits and demonstrate accurate prediction of multiple physical parameters in both the supervised context and the unsupervised context. We demonstrate that the model benefits from larger training sets, establishing that it is “learning,” and we show robustness regarding errors in the assumed physical model by achieving accurate parameter estimation in the presence of unanticipated single-particle relaxation.

关键词： Entanglement detection Nonlocality quantum parameter estimation Machine learning Weak measurements

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Characterization, synthesis, and optimization of quantum circuits over multiple-control Z-rotation gates: A systematic study

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Physical Review A 2023年第2期108卷 022603-022603页

作者： Shihao Zhang Junda Wu Lvzhou Li Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou 510006 China

We conduct a systematic study of quantum circuits composed of multiple-control Z-rotation (mczr) gates as primitives, since they are widely used components in quantum algorithms and also have attracted much experimental interest in recent years. We establish a circuit-polynomial correspondence to characterize the functionality of quantum circuits over the mczr gate set with continuous parameters. An analytic method for exactly synthesizing such quantum circuit to implement any given diagonal unitary matrix with an optimal gate count is proposed, which also enables the circuit depth optimal for specific cases with pairs of complementary gates. Furthermore, we present a gate-exchange strategy together with a flexible iterative algorithm for effectively optimizing the depth of any mczr circuit, which can also be applied to quantum circuits over any other commuting gate set. Besides the theoretical investigation, the practical performance of our circuit synthesis and optimization techniques is further evaluated numerically on two typical examples in quantum computing, including diagonal Hermitian operators and quantum approximate optimization algorithm circuits with tens of qubits, which can demonstrate a reduction in circuit depth by 33.40% and 15.55% on average over relevant prior works, respectively. Therefore, our methods and results provide a pathway for implementing quantum circuits and algorithms on recently developed devices.

关键词： Iterative methods

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Frictional shear stress of ZnO nanowires on natural and pyrolytic graphite substrates

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Friction 2022年第12期10卷 2059-2068页

作者： Lizhen HOU Maofen HOU Tursunay YIBIBULLA James Lee MEAD Sergej FATIKOW Shiliang WANG Han HUANG Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education School of Physics and Electronic ScienceHunan Normal UniversityChangsha 410081China School of Physics and Electronics Central South UniversityChangsha 410083China Division Microrobotics and Control Engineering Department of Computing ScienceUniversity of OldenburgOldenburg D-26129Germany School of Mechanical and Mining Engineering The University of QueenslandBrisbaneQLD 4072Australia

The friction behaviour of ZnO nanowires on natural graphite(NG)and highly oriented pyrolytic graphite(HOPG)substrates was tested in ambient conditions by use of optical microscopy based *** on the step-free and waviness-free NG substrate exhibit a diameter-independent nominal frictional shear stress of 0.48 MPa,and this provides a benchmark for studying how the surface topography of graphite influences nanowire *** on the HOPG substrate present a significant diameter-dependent frictional shear stress,increasing from 0.25 to 2.78 MPa with the decrease of nanowire diameter from 485 to 142 *** waviness of HOPG has a limited effect on the nanowire friction,as a nanowire can fully conform to the *** surface steps on the HOPG can significantly enhance the nanowire friction and lead to a much higher frictional shear stress than that on NG due to mechanical blocking and the presence of a Schwoebel barrier at step *** surface steps,however,can also generate small wedge-shaped gaps between a nanowire and substrate,and thus reduce the nanowire *** the decrease in nanowire diameter,the capacity for the nanowire to better conform to the substrate reduces the length of the wedge-shaped gaps,leading to the observed increase in nanowire *** results have improved our understanding of the unique friction behaviour of *** an improved understanding is expected to benefit the design and operation of nanowire-friction-based devices,including bio-inspired fibrillar adhesives,soft grippers,rotary nanomotors,and triboelectric nanogenerators.

关键词： frictional shear stress nanowires graphite surface step waviness

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A Detailed Analysis of Secrecy and Performance Metrics in Hybrid RF/ FSO Communication Systems: Implications of Composite Weibull and Log-normal Fading with M Turbulent Channels

A Detailed Analysis of Secrecy and Performance Metrics in Hy...

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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 ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

In this paper, we have analyzed the secrecy performance and system operation performance for hybrid RF/FSO systems against composite Weibull-log-normal fading channel with M turbulent channels. The performance is evaluated by carrying out extensive simulations to calculate Signal-to-Noise Ratio (SNR), Bit Error Rate (BER) and outage probability, we also re-evaluate channel capacity and secrecy capacity with respect of environmental conditions. Compared with RF only system, FSO only standalone scheme and some meaningful orthogonal-modulation multicarrier IM/DD-based schemes proposed by the literatures. Similarly, the utilization of adaptive modulation schemes improved resistance to fading and roughness in systems. The above results confirm the hybridization of both RF and FSO a comprehensive solution for dependable communication in different and even hostile surrounding conditions which set this work as reliable foundation point towards forthcoming research activity or application relevance within all range telecommunication sector. © 2024 IEEE.

关键词： Bit error rate

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Improved quantum linear system solver via quantum phase discrimination

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The European Physical Journal Special Topics 2025年 1-11页

作者： Liu, Zihao Li, Guanzhong Li, Lvzhou Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area (Guangdong) Shenzhen China

The problem of solving linear systems is of great significance in both theory and practice, for which quantum solvers have been shown to provide an exponential speedup over the best-known classical solvers. Recently, a quantum linear system solver has been developed with the state-of-the-art complexity [1], which combines two techniques, namely, discrete adiabatic evolution and eigenstate filtering. However, the parameters of the quantum circuit for eigenstate filtering need to be precomputed classically via the discrete Fourier transform, which introduces additional computational overhead. In this paper, we improve the solver by presenting a new eigenstate filtering process termed quantum phase discrimination in which the circuit parameters are given directly in a concise and analytical form with negligible classical overhead, while maintaining the same quantum complexity.

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Cross-resonance control of an oscillator with an auxiliary fluxonium qubit

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Physical Review Applied 2025年第2期23卷 024067-024067页

作者： Guo Zheng Simon Lieu Emma L. Rosenfeld Kyungjoo Noh Connor T. Hann Pritzker School of Molecular Engineering The University of Chicago Chicago 60637 USA AWS Center for Quantum Computing Pasadena California 91125 USA

The conditional displacement (CD) gate between an oscillator and a discrete-variable auxiliary qubit plays a key role in quantum information processing tasks, such as enabling universal control of the oscillator and longitudinal readout of the qubit; however, the gate is unprotected against the propagation of auxiliary qubit decay errors, meaning it is not fault tolerant. Here, we propose a CD gate scheme with fluxonium as the auxiliary qubit, which has been experimentally demonstrated to have a large noise bias and millisecond-level lifetimes. The proposed gate is applied cross-resonantly by modulating the external flux of the fluxonium at the frequency of the target oscillator, which requires minimal hardware overhead and does not increase sensitivity to decoherence mechanisms such as dephasing. We further provide a perturbative description of the gate mechanism and identify the error budget. Additionally, we develop an approximate procedure for choosing device and gate parameters that optimize gate performance. Following the procedure for multiple sets of fluxonium parameters from the literature, we numerically demonstrate CD gates with unitary fidelity exceeding 99.9% and gate times of hundreds of nanoseconds.

关键词： Budget control

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Sparse Channel Estimation in Massive MIMO Systems Using Compressed Sensing and Neural Networks

Sparse Channel Estimation in Massive MIMO Systems Using Comp...

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

ISBN: (纸本)9798350379525

In this paper, based on compressed sensing and neural networks, we present an intelligent sparse channel estimation technique for Massive MIMO systems. We show that our approach improves considerably the estimation accuracy in terms of Mean Squared Error (MSE) and Normalized Mean Squared Error (NMSE) with respect to classical methods. We demonstrate [Figure: ] that our approach is computationally more efficient, requires less time and resources (memory/disk) compared to the existing literature but for a robustness of performance across distal or low Signal-to-Noise Ratios (SNRs). We also confirm our method exhibits fast convergence and efficiently accommodates a variety of sparsity levels. By visualizing it using heatmaps and ROC curves we show that this method is able to effectively differentiate between signal and noise, asserting our approach as a powerful tool for the contemporary set of problems present in wireless communications. © 2024 IEEE.

关键词： Signal to noise ratio

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Transfer Learning Approaches for Channel State Prediction in Heterogeneous Fading Networks

Transfer Learning Approaches for Channel State Prediction in...

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

ISBN: (纸本)9798350379525

In this work, we leverage state-of-the-art machine learning algorithms to predict Channel State Information (CSI), for enhancing performance of wireless communication systems. The simulation and analysis stop with transfer learning to finetune, adaptive domain adaptations, multitasking (MTL) as well a few shot meta-learning models framework under different network packet loss rate scenarios. By generalizing better from one domain to another, transfer learning pushes the performance beyond what traditional methods can obtain. Further, fine-tuning also helps to align the source and target domain distributions in feature space by a partial (or full) reduction of re-stylization error. This work proposes multi-Task learning as a tool to mitigate loses in light of predicting across fading scenarios. Considering multi-task learning also provides benefits from shared learnings, so experience is pooled between the tasks which indirectly improve prediction as well and it helps in training both of these algorithms together. Moreover, the few-shot learning models prove to be highly desirable as they deliver state-of-the-art performance with minimal training data for difficult problems. These results show the potential of AI-based methods to improve CSI prediction, and have implications for improving reliability and throughput when deploying real wireless communication systems. © 2024 IEEE.

关键词： Contrastive Learning

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