Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light

Zhong, Han-Sen; Deng, Yu-Hao; Qin, Jian; Wang, Hui; Chen, Ming-Cheng; Peng, Li-Chao; Luo, Yi-Han; Wu, Dajun; Gong, Si-Qiu; Su, Hao; Hu, Yi; Hu, Peng; Yang, Xiaoyan; Zhang, Weijun; Li, Hao; Li, Yuxuan; Jiang, Xiao; Gan, Lin; Yang, Guangwen; You, Lixing; Wang, Zhen; Li, Li; Liu, Nai-Le; Renema, Jelmer J.; Lu, Chao‐Yang; Pan, Jian-Wei

doi:10.1103/physrevlett.127.180502

Cited by 305 publications

(228 citation statements)

References 74 publications

Supporting

Mentioning

210

Contrasting

Unclassified

Order By: Relevance

“…Conventional supercomputers, albeit versatile and remarkably reliable, seem to be outpaced by ever-increasing demand for computational power when developing new drugs [ 1 ], modeling nanoparticles [ 2 ], or assessing problems in materials science [ 3 ] and nuclear physics [ 4 , 5 ]. In contrast to the well-established conventional technologies, quantum computers are expected to provide exponentially growing computational power thanks to the their use of quantum effects [ 6 , 7 ], and the first indications of so-called quantum advantage/supremacy have already been demonstrated [ 8 , 9 , 10 ]. Unfortunately, the current capabilities of quantum computers are still rather limited by numerous methodological issues, a lack of suitable software tools, challenges when physically realizing quantum circuits, noise, which reduces their reliability, as well as a very low number of quantum platforms available for users.…”

Section: Introductionmentioning

confidence: 99%

Best-Practice Aspects of Quantum-Computer Calculations: A Case Study of the Hydrogen Molecule

et al. 2022

View full text Add to dashboard Cite

Quantum computers are reaching one crucial milestone after another. Motivated by their progress in quantum chemistry, we performed an extensive series of simulations of quantum-computer runs that were aimed at inspecting the best-practice aspects of these calculations. In order to compare the performance of different setups, the ground-state energy of the hydrogen molecule was chosen as a benchmark for which the exact solution exists in the literature. Applying the variational quantum eigensolver (VQE) to a qubit Hamiltonian obtained by the Bravyi–Kitaev transformation, we analyzed the impact of various computational technicalities. These included (i) the choice of the optimization methods, (ii) the architecture of the quantum circuits, as well as (iii) the different types of noise when simulating real quantum processors. On these, we eventually performed a series of experimental runs as a complement to our simulations. The simultaneous perturbation stochastic approximation (SPSA) and constrained optimization by linear approximation (COBYLA) optimization methods clearly outperformed the Nelder–Mead and Powell methods. The results obtained when using the Ry variational form were better than those obtained when the RyRz form was used. The choice of an optimum entangling layer was sensitively interlinked with the choice of the optimization method. The circular entangling layer was found to worsen the performance of the COBYLA method, while the full-entangling layer improved it. All four optimization methods sometimes led to an energy that corresponded to an excited state rather than the ground state. We also show that a similarity analysis of measured probabilities can provide a useful insight.

show abstract

Section: Introductionmentioning

confidence: 99%

Best-Practice Aspects of Quantum-Computer Calculations: A Case Study of the Hydrogen Molecule

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Beyond tests of quantum computational complexity using photons [3,27], optical approaches to universal measurement-based quantum computation rely on the generation of small entangled states that can be combined to build up a cluster resource state [28,29]. The effect of photon distinguishability on fault tolerant schemes has been investigated [30], but a more general treatment also including effects of photon impurity -and routes to protect against such errors -will become crucial as the scale of optical quantum technologies continues to grow.…”

Section: Discussionmentioning

confidence: 99%

Distinguishability and mixedness in quantum interference

Jones¹,

Kumar²,

D'Aurelio³

et al. 2022

Preprint

View full text Add to dashboard Cite

We study the impact of distinguishability and mixedness -two fundamental properties of quantum states -on quantum interference. We show that these can influence the interference of multiple particles in different ways, leading to effects that cannot be observed in the interference of two particles alone. This is demonstrated experimentally by interfering three independent photons in pure and mixed states and observing their different multiphoton interference, despite exhibiting the same two-photon Hong-Ou-Mandel (HOM) interference. Besides its fundamental relevance, our observation has important implications for quantum technologies relying on photon interference.

show abstract

“…Indeed, the computing experiments and data analysis have shown that a 200-second job of Gaussian Boson sampling on Jiuzhang would require 0.6 billon years for the fastest supercomputer available at the time to finish. It was reported in Zhong et al, 2021 that the second generation of Jiuzhang was built with up to 113 qubits and enhanced performance.…”

Section: Quantum Factoring Algorithms and Cryptographymentioning

confidence: 99%

When Quantum Computation Meets Data Science: Making Data Science Quantum

Wang

2022

Harvard Data Science Review

View full text Add to dashboard Cite

Quantum computation and quantum information have attracted considerable attention on multiple frontiers of scientific fields ranging from physics to chemistry and engineering, as well as from computer science to mathematics and statistics. Data science combines statistical methods, computational algorithms, and domain science information to extract knowledge and insights from big data, and to solve complex real-world problems. While it is well-known that quantum computation has the potential to revolutionize data science, much less has been said about the potential of data science to advance quantum computation. Yet because the stochasticity of quantum physics renders quantum computation random, data science can play an important role in the development of quantum computation and quantum information. This article gives an overview of quantum computation and promotes interplay between quantum science and data science. Overall, it advocates for the development of quantum data science for advancing quantum computation and quantum information.

show abstract

Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light

Cited by 305 publications

References 74 publications

Best-Practice Aspects of Quantum-Computer Calculations: A Case Study of the Hydrogen Molecule

Best-Practice Aspects of Quantum-Computer Calculations: A Case Study of the Hydrogen Molecule

Distinguishability and mixedness in quantum interference

When Quantum Computation Meets Data Science: Making Data Science Quantum

Contact Info

Product

Resources

About