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Quantum computing and chemistry

delete2024-09-01
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OA
AI
J
Jared D. Weidman
M
Manas Sajjan
Z
Zachary J. Stewart
J
J. Pollanen
S
Sabre Kais
A
Angela K. Wilson *
DOI:10.1016/j.xcrp.2024.102105delete
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Abstract

Abstract

En 中文
As the year-to-year gains in speeds of classical computers continue to taper off, computational chemists are increasingly examining quantum computing as a possible route to achieve greater computational performance. Quantum computers, built upon the properties of superposition, interference, and entanglement of quantum bits, offer, in principle, the possibility to outperform classical computers for solving many important classes of problems. In the field of chemistry, quantum algorithm development offers promising propositions for solving classically intractable problems in areas such as electronic structure, chemical quantum dynamics, spectroscopy, and cheminformatics. However, physical implementations of quantum computers are still in their infancy and have yet to outperform classical computers for useful computations. Still, quantum software development for chemistry is a highly active area of research. In this perspective, we summarize recent progress in the areas of quantum computing algorithms, hardware, and software, and we describe the challenges that remain for useful implementations of quantum computing for chemical applications.
Keywords:
COMPUTATIONAL ADVANTAGE
SUPERCONDUCTING QUBITS
ERROR-CORRECTION
DENSITY-MATRIX
DYNAMICS
SPIN
ENTANGLEMENT
EIGENSOLVER
ALGORITHM
STATE

Journal

Cell Reports Physical Science cover
Cell Reports Physical Science
IF:
7.3
Papers:
2.8K
Citations:
1.2W

Organization

Purdue University System cover
Purdue University System
Scholars:
4.0W
Papers: 3.6W
Citations: 66
M
michigan state university
Scholars:
3.6W
Papers: 3.2W
Citations: 44
Cited Papers

Cited Papers

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The Aitape 1998 Tsunami: Reconstructing the Event from Interviews and Field Mapping
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Power of data in quantum machine learning
err2021-05-11
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errHuang, Hsin-Yuan; Broughton, Michael; Mohseni, Masoud; Babbush, Ryan; Boixo, Sergio; Neven, Hartmut; McClean, Jarrod R.
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Noise-induced barren plateaus in variational quantum algorithms
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errWang, Samson; Fontana, Enrico; Cerezo, M.; Sharma, Kunal; Sone, Akira; Cincio, Lukasz; Coles, Patrick J.
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Barren plateaus in quantum neural network training landscapes
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errMcClean, Jarrod R.; Boixo, Sergio; Smelyanskiy, Vadim N.; Babbush, Ryan; Neven, Hartmut
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Superconducting Quantum Interference Single-Electron Transistor
err2016-06-30
err10
errOAAI
errEnrico, Emanuele; Giazotto, Francesco
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Application of quantum machine learning using the quantum kernel algorithm on high energy physics analysis at the LHC
err2021-09-08
err57
errOAAI
errWu, Sau Lan; Sun, Shaojun; Guan, Wen; Zhou, Chen; Chan, Jay; Cheng, Chi Lung; Pham, Tuan; Qian, Yan; Wang, Alex Zeng; Zhang, Rui; Livny, Miron; Glick, Jennifer; Barkoutsos, Panagiotis Kl; Woerner, Stefan; Tavernelli, Ivano; Carminati, Federico; Di Meglio, Alberto; Li, Andy C. Y.; Lykken, Joseph; Spentzouris, Panagiotis; Chen, Samuel Yen-Chi; Yoo, Shinjae; Wei, Tzu-Chieh
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