Quantum Information and Algorithms for Correlated Quantum Matter

被引:82
|
作者
Head-Marsden, Kade [1 ]
Flick, Johannes [3 ]
Ciccarino, Christopher J. [1 ,2 ]
Narang, Prineha [1 ]
机构
[1] Harvard Univ, John A Paulson Sch Engn & Appl Sci, Cambridge, MA 02138 USA
[2] Harvard Univ, Dept Chem & Chem Biol, Cambridge, MA 02138 USA
[3] Flatiron Inst, Ctr Computat Quantum Phys, New York, NY 10010 USA
关键词
REDUCED-DENSITY-MATRIX; ELECTRONIC-STRUCTURE CALCULATIONS; PLESSET PERTURBATION-THEORY; NITROGEN-VACANCY CENTERS; COUPLED-CLUSTER THEORY; NUCLEAR-SPIN QUBITS; FUNCTIONAL-THEORY; ENERGY-TRANSFER; SINGLE SPINS; TIME EVOLUTION;
D O I
10.1021/acs.chemrev.0c00620
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Discoveries in quantum materials, which are characterized by the strongly quantum-mechanical nature of electrons and atoms, have revealed exotic properties that arise from correlations. It is the promise of quantum materials for quantum information science superimposed with the potential of new computational quantum algorithms to discover new quantum materials that inspires this Review. We anticipate that quantum materials to be discovered and developed in the next years will transform the areas of quantum information processing including communication, storage, and computing. Simultaneously, efforts toward developing new quantum algorithmic approaches for quantum simulation and advanced calculation methods for many-body quantum systems enable major advances toward functional quantum materials and their deployment. The advent of quantum computing brings new possibilities for eliminating the exponential complexity that has stymied simulation of correlated quantum systems on high-performance classical computers. Here, we review new algorithms and computational approaches to predict and understand the behavior of correlated quantum matter. The strongly interdisciplinary nature of the topics covered necessitates a common language to integrate ideas from these fields. We aim to provide this common language while weaving together fields across electronic structure theory, quantum electrodynamics, algorithm design, and open quantum systems. Our Review is timely in presenting the state-of-the-art in the field toward algorithms with nonexponential complexity for correlated quantum matter with applications in grand-challenge problems. Looking to the future, at the intersection of quantum information science and algorithms for correlated quantum matter, we envision seminal advances in predicting many-body quantum states and describing excitonic quantum matter and large-scale entangled states, a better understanding of high-temperature superconductivity, and quantifying open quantum system dynamics.
引用
收藏
页码:3061 / 3120
页数:60
相关论文
共 50 条
  • [1] Criticality in correlated quantum matter
    Angela Kopp
    Sudip Chakravarty
    Nature Physics, 2005, 1 : 53 - 56
  • [2] Criticality in correlated quantum matter
    Kopp, A
    Chakravarty, S
    NATURE PHYSICS, 2005, 1 (01) : 53 - 56
  • [3] Protecting Quantum Fisher Information in Correlated Quantum Channels
    Hu, Ming-Liang
    Wang, Hui-Fang
    ANNALEN DER PHYSIK, 2020, 532 (01)
  • [4] Quantum transport theory of strongly correlated matter
    Auerbach, Assa
    Bhattacharyya, Sauri
    PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 2024, 1091 : 1 - 63
  • [5] Strongly correlated quantum matter in optical lattices
    Bloch, I.
    Foelling, S.
    Widera, A.
    Mueller, T.
    Rom, T.
    Best, Th.
    van Oosten, D.
    Schneider, U.
    Paredes, B.
    Gerbier, F.
    ATOMIC PHYSICS 20, 2006, 869 : 191 - +
  • [6] Quantum Information Set Decoding Algorithms
    Kachigar, Ghazal
    Tillich, Jean-Pierre
    POST-QUANTUM CRYPTOGRAPHY, PQCRYPTO 2017, 2017, 10346 : 69 - 89
  • [7] Numerical algorithms for use in quantum information
    Ramos, RV
    JOURNAL OF COMPUTATIONAL PHYSICS, 2003, 192 (01) : 95 - 104
  • [8] Algorithms in quantum information processing - Foreword
    Berthiaume, A
    Rogers, JD
    THEORETICAL COMPUTER SCIENCE, 2003, 292 (03) : 573 - 573
  • [9] Maximum information and quantum prediction algorithms
    McElwaine, J
    PHYSICAL REVIEW A, 1997, 56 (03): : 1756 - 1766
  • [10] Efficient algorithms for quantum information bottleneck
    Hayashi, Masahito
    Yang, Yuxiang
    QUANTUM, 2023, 7