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Efficient quantum process tomography for Clifford circuits

Physical Review A 2023年第3期108卷 032419-032419页

作者： Shichuan Xue Guangyao Huang Yong Liu Dongyang Wang Weixu Shi Yingwen Liu Xiang Fu Anqi Huang Mingtang Deng Junjie Wu Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha 410073 China

A Clifford circuit is a pivotal tool in quantum computing and has extensive applications in quantum error correction codes and topological quantum computing. Hence, it is essential to benchmark and verify the effect of Clifford circuits against noise and errors. Standard quantum process tomography is a fundamental technique for fully characterizing quantum dynamics, but at the cost of exponential time, space, and computation with an increasing number of qubits. Here, we propose an efficient quantum process tomography method for Clifford circuits. Combining with the stabilizer formalism, we prove theoretically that, for an n-qubit Clifford circuit, our method merely needs m ancillary qubits and ⌈n/m⌉ input stabilizer states to obtain the quantum process. Numerical simulation results show that our method could perfectly rebuild the unknown Clifford quantum circuit with fidelity over 99.99% to six qubit cases. Our work provides an efficient and practical approach to benchmark and verify Clifford circuits.

关键词： quantum circuits quantum information processing quantum simulation quantum tomography

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quantum algorithm and experimental demonstration for the subset sum problem

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Science China(Information Sciences) 2022年第8期65卷 261-274页

作者： Qilin ZHENG Pingyu ZHU Shichuan XUE Yang WANG Chao WU Xinyao YU Miaomiao YU Yingwen LIU Mingtang DENG Junjie WU Ping XU Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense Technology

To solve the subset sum problem, a well-known nondeterministic polynomial-time complete problem that is widely used in encryption and resource scheduling, we propose a feasible quantum algorithm that utilizes fewer qubits to encode and achieves quadratic speedup. Specifically, this algorithm combines an amplitude amplification algorithm with quantum phase estimation, and requires n + t + 1 qubits and O(2(0.5+o(1))n) operations to obtain the solution, where n is the number of elements, and t is the number of qubits used to store the eigenvalues. To verify the performance of the algorithm, we simulate the algorithm with the online quantum simulator of IBM named ibmq simulator using Qiskit and then run it on two IBM quantum computers called ibmq santiago and ibmq bogota. The experimental results indicate that compared with the brute force algorithm, the proposed algorithm results in quadratic acceleration for the problem of a set S with four elements and two subsets whose sum equals target w. Using the iterator twice, we obtain success probabilities of 0.940 ± 0.004, 0.751 ± 0.040, and 0.665 ± 0.060 on the simulator, ibmq santiago, and ibmq bogota, respectively, and the fidelity between the theoretical and experimental quantum states is calculated to be 0.944 ± 0.002, 0.753 ± 0.017, and 0.657 ± 0.028, respectively. If the error rates of the experimental quantum logic gates can be reduced, the success probabilities of the proposed algorithm on real quantum devices can be further improved.

关键词： quantum algorithm subset sum quadratic speedup encryption algorithm complexity

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quantum Relaxation for Solving Multiple Knapsack Problems

Quantum Relaxation for Solving Multiple Knapsack Problems

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quantum computing and Engineering (QCE), IEEE International Conference on

作者： Monit Sharma Yan Jin Hoong Chuin Lau Rudy Raymond School of Computing and Information Systems Singapore Management University Singapore Institute of High Performance Computing A*STAR Singapore IBM Quantum IBM Japan Japan JP Morgan Chase & Co. USA

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Combinatorial problems are a common challenge in business, requiring finding optimal solutions under specified constraints. While significant progress has been made with variational approaches such as QAOA, most problems addressed are unconstrained (such as Max-Cut). In this study, we investigate a hybrid quantum-classical method for constrained optimization problems, particularly those with knapsack constraints that occur frequently in financial and supply chain applications. Our proposed method relies firstly on relaxations to local quantum Hamiltonians, defined through commutative maps. Drawing inspiration from quantum random access code (QRAC) concepts, particularly quantum Random Access Optimizer (QRAO), we explore QRAO's potential in solving large constrained optimization problems. We employ classical techniques like Linear Relaxation as a presolve mechanism to handle constraints and cope further with scalability. We compare our approach with QAOA and present the final results for a real-world procurement optimization problem: a significant-sized multi-knapsack-constrained problem.

关键词： Procurement quantum computing Codes Scalability Supply chains Optimization Business

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quantum Enhanced Simulation Based Optimization for Newsvendor Problems

Quantum Enhanced Simulation Based Optimization for Newsvendo...

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quantum computing and Engineering (QCE), IEEE International Conference on

作者： Monit Sharma Hoong Chuin Lau Rudy Raymond School of Computing and Information Systems Singapore Management University Singapore Institute of High Performance Computing A*STAR Singapore IBM Quantum IBM Japan Japan Dept. of Computer Science The University of Tokyo

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Simulation-based optimization is a widely used method to solve stochastic optimization problems. This method aims to identify an optimal solution by maximizing the expected value of the objective function. However, due to its computational complexity, the function cannot be accurately evaluated directly, hence is estimated through simulation. Exploiting the enhanced efficiency of quantum Amplitude Estimation (QAE) compared to classical Monte Carlo simulation, it frequently outpaces classical simulation-based optimization, resulting in notable performance enhancements in various scenarios. In this work, we use a quantum-enhanced algorithm for simulation-based optimization and apply it to solve a variant of the classical Newsvendor Problem known to be NP-hard. Such problems provide the building block for supply chain management, particularly in inventory management and procurement optimization under risks and uncertainty.

关键词： Procurement quantum computing Uncertainty Monte Carlo methods Inventory management Linear programming Amplitude estimation Object recognition Computational complexity Optimization

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quantum-Enhanced Simulation-Based Optimization for Newsvendor Problems

arXiv

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arXiv 2024年

作者： Sharma, Monit Lau, Hoong Chuin Raymond, Rudy School of Computing and Information Systems Singapore Management University Singapore Institute of High Performance Computing A*STAR Singapore IBM Quantum IBM Japan Japan Dept. of Computer Science The University of Tokyo Japan

Simulation-based optimization is a widely used method to solve stochastic optimization problems. This method aims to identify an optimal solution by maximizing the expected value of the objective function. However, due to its computational complexity, the function cannot be accurately evaluated directly, hence it is estimated through simulation. Exploiting the enhanced efficiency of quantum Amplitude Estimation (QAE) compared to classical Monte Carlo simulation, it frequently outpaces classical simulation-based optimization, resulting in notable performance enhancements in various scenarios. In this work, we make use of a quantum-enhanced algorithm for simulation-based optimization and apply it to solve a variant of the classical Newsvendor Problem which is known to be NP-hard. Such problems provide the building block for supply chain management, particularly in inventory management and procurement optimization under risks and uncertainty. © 2024, CC BY.

关键词： quantum efficiency

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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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Bright 547-dimensional Hilbert-space entangled resource in 28-pair modes biphoton frequency comb from a reconfigurable silicon microring resonator

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Chinese Physics B 2022年第2期31卷 129-134页

作者： Qilin Zheng Jiacheng Liu Chao Wu Shichuan Xue Pingyu Zhu Yang Wang Xinyao Yu Miaomiao Yu Mingtang Deng Junjie Wu Ping Xu Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer.National University of Defense TechnologyChangsha 410073China College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha 410013China National Laboratory of Solid State Microstructures and School of Physics Nanjing University.Nanjing 210093China

high-dimensional entanglement provides valuable resources for quantum technologies,including quantum communication,quantum optical coherence tomography,and quantum *** a high brightness and dimensional entanglement source has significant *** we utilize a tunable asymmetric Mach–Zehnder interferometer coupled silicon microring resonator with 100 GHz free spectral range to achieve this *** the strategy of the tunable coupler,the dynamical and extensive tuning range of quality factors of the microring can be obtained,and then the biphoton pair generation rate can be *** selecting and characterizing 28 pairs from a more than 30-pair modes biphoton frequency comb,we obtain a Schmidt number of at least 23.4 and on-chip pair generation rate of 19.9 MHz/m W;under a low on-chip pump power,which corresponds to 547 dimensions Hilbert space in frequency *** results will prompt the wide applications of quantum frequency comb and boost the further large density and scalable on-chip quantum information processing.

关键词： silicon microring resonator quantum entanglement biphoton frequency comb

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Anomalous negative magnetoresistance in quantum dot Josephson junctions with Kondo correlations

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 3-13页

作者： Mingtang Deng Chunlin Yu Guangyao Huang Rosa López Philippe Caroff Sepideh Ghalamestani Gloria Platero Hongqi Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China NanoLund and Division of Solid State Physics Lund UniversityLund S-22100Sweden China Greatwall Quantum Laboratory Changsha 410006China Institut de Física Interdisciplinària i de Sistemes Complexos IFISC Palma de Mallorca E-07122Spain Instituto de Ciencia de Materiales de Madrid Madrid 28049Spain Beijing Key Laboratory of Quantum Devices Key Laboratory for the Physics and Chemistry of Nanodevicesand Department of ElectronicsPeking UniversityBeijing 100871China Beijing Academy of Quantum Information Sciences Beijing 100193China Hefei National Laboratory Hefei 230088China

The interplay between superconductivity and the Kondo effect has stimulated significant interest in condensed matter *** compete when their critical temperatures are close and can give rise to a quantum phase transition that can mimic Majorana zero ***,we have fabricated and measured Al-InSb nanowire quantum dot-Al *** the Kondo regime,a supercurrent-induced zero-bias conductance peak *** zero-bias peak shows an anomalous negative magnetoresistance(NMR)at weak magnetic *** attribute this anomalous NMR to quasiparticle trapping at vortices in the superconductor leads as a weak magnetic field is *** trapping effect lowers the quasiparticle-caused dissipation and thus enhances the Josephson *** work connects the vortex physics and the supercurrent tunneling in Kondo regimes and can help further understand the physics of Josephson quantum dot system.

关键词： quantum dot Kondo correlation InSb nanowire quasiparticle trapping

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Task2Morph: Differentiable Task-inspired Framework for Contact-Aware Robot Design

arXiv

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arXiv 2024年

作者： Cai, Yishuai Yang, Shaowu Li, Minglong Chen, Xinglin Mao, Yunxin Yi, Xiaodong Yang, Wenjing The Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

Optimizing the morphologies and the controllers that adapt to various tasks is a critical issue in the field of robot design, aka. embodied intelligence. Previous works typically model it as a joint optimization problem and use search-based methods to find the optimal solution in the morphology space. However, they ignore the implicit knowledge of task-to-morphology mapping which can directly inspire robot design. For example, flipping heavier boxes tends to require more muscular robot arms. This paper proposes a novel and general differentiable task-inspired framework for contact-aware robot design called Task2Morph. We abstract task features highly related to task performance and use them to build a task-to-morphology mapping. Further, we embed the mapping into a differentiable robot design process, where the gradient information is leveraged for both the mapping learning and the whole optimization. The experiments are conducted on three scenarios, and the results validate that Task2Morph outperforms DiffHand, which lacks a task-inspired morphology module, in terms of efficiency and effectiveness. Copyright © 2024, The Authors. All rights reserved.

关键词： Morphology

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Evaluating performance Portability of SYCL and Kokkos: A Case Study on LBM Simulations

Evaluating Performance Portability of SYCL and Kokkos: A Cas...

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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yue Ding Chuanfu Xu Haozhong Qiu Qingsong Wang Weixi Dai Yongzhen Lin Yonggang Che Institute for Quantum Information & State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

Since modern high performance computing systems are evolving towards diverse and heterogeneous architectures, the emergence of high-level portable programming models leads to a particular focus on performance portability. In this paper, we evaluate the performance portability and explore performance optimization methods for two portable programming models SYCL and Kokkos. We take an open-source multi-phase Lattice Boltzmann Method (LBM) flow simulation code as a case study and implement portable versions with different optimizations. Then we compare our portable implementations with engineer-tuned OpenMP and CUDA versions on Intel CPUs and NVIDIA GPUs. Experimental results show that both SYCL and Kokkos can deliver superior performance than traditional programming models, but the best performance of the portable versions depends heavily on platform-specific optimizations. There is no single implementation that can achieve the best performance on both CPUs and GPUs. Consequently, we conclude that the performance portability still needs to be further improved for both SYCL and Kokkos. In addition, we present a comparative analysis of different optimization methods that qualify the performance enhancement when using SYCL and Kokkos on CPUs and GPUs. Our work offers valuable references for the development of both portable programming models and applications.

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