Fetching the paper…
Reading the bibliography…
Due to complexity of the systems and processes it addresses, the development of computational quantum physics is influenced by the progress in computing technology.
R. Bellman, Dynamic Programmings (Princeton University Press, 1957)
1957
Earlier work this paper cites.
R. P. Feynman, “Simulating physics with computers,” Int. J. Theor. Phys. 21
1982
Earlier work this paper cites.
Y. Saad, “Analysis of Some Krylov Subspace Approximations to the Matrix Exponential Operator,” SIAM J. Numer. Anal. 29
1992
Earlier work this paper cites.
R. Kosloff, “Propagation methods for quantum molecular dynamics,” Annu. Rev. Phys. Chem. 45
1994
Earlier work this paper cites.
K. B. Davis et al., “Bose-Einstein condensation in a gas of sodium atoms,” Phys. Rev. Lett. 75
1995
Earlier work this paper cites.
S. Lloyd, “Universal quantum simulators,” Science 273
1996
Earlier work this paper cites.
H.-P. Breuer and F. Petruccione, The Theory of Open Quantum Systems (Oxford University Press, Oxford, 2002)
2002
Earlier work this paper cites.
G. Vidal, “Efficient classical simulation of slightly entangled quantum computations,” Phys. Rev. Lett. 91
2003
Earlier work this paper cites.
C. Moler and C. Van Loan, “Nineteen dubious ways to compute the exponential of a matrix, twenty-five years later,” SIAM Rev. 45
2003
Earlier work this paper cites.
S. Kohler, J. Lehmann, and P. Hänggi, “Driven quantum transport on the nanoscale,” Phys. Rep. 406
2005
Earlier work this paper cites.
H. Samet, Foundations of Multidimensional and Metric Data Structures (Morgan Kaufmann, 2006)
2006
Earlier work this paper cites.
V. Murg, F. Verstraete, and J. I. Cirac, “Variational study of hard-core bosons in a two-dimensional optical lattice using projected entangled pair states,” Phys. Rev. A 75
2007
Earlier work this paper cites.
J. Jordan, R. Orús, G. Vidal, F. Verstraete, and J. I. Cirac, “Classical simulation of infinite-size quantum lattice systems in two spatial dimensions,” Phys. Rev. Lett. 101
2008
Earlier work this paper cites.
I. V. Oseledets and E. E. Tyrtyshnikov, “Breaking the curse of dimensionality, or how to use SVD in many dimensions,” SIAM J. Sci. Comput. 31
2009
Earlier work this paper cites.
S. Blanes et al., “The Magnus expansion and some of its applications,” Phys. Rep. 470
2009
Earlier work this paper cites.
M. A. Nielsen, and I. L. Chuang, Quantum Computation and Quantum Information (Cambridge University Press, Cambridge, 2010)
2010
Earlier work this paper cites.
J. Haegeman et al., “Time-dependent variational principle for quantum lattices,” Phys. Rev. Lett. 107
2011
Earlier work this paper cites.
C. S. Bederián and A. D. Dente, “Boosting quantum evolutions using Trotter-Suzuki algorithms on GPUs,” In: Proceedings of HPCLatAm-11, 4th High-Performance Computing Symposium, Cordoba, Argentina (2011)
2011
Earlier work this paper cites.
U. Schollwoeck, “The density-matrix renormalization group in the age of matrix product states,” Ann. of Phys. 326
2011
Earlier work this paper cites.
A. J. Abhari et al., “Scaffold: Quantum programming language,” TR-934-12 (2012)
2012
Earlier work this paper cites.
R. Barendes et al., “Coherent Josephson qubit suitable for scalable quantum integrated circuits,” Phys. Rev. Lett. 11
2013
Earlier work this paper cites.
J. R. Johansson, P. D. Nation, and F. Nori, “QuTiP 2: A Python framework for the dynamics of open quantum systems,” Comp. Phys. Comm. 184
2013
Earlier work this paper cites.
P. Wittek and F. M. Cucchietti, “A second-order distributed Trotter-Suzuki solver with a hybrid CPU-GPU kernel,” Comp. Phys. Comm. 184
2013
Earlier work this paper cites.
A. S. Green et al., “Quipper: a scalable quantum programming language,” In: Proceedings of the 34th ACM SIGPLAN conference on Programming language design and implementation, 333-342 (2013)
2013
Earlier work this paper cites.
D. W. Berry et al., “Simulating Hamiltonian dynamics with a truncated Taylor series,” Phys. Rev. Lett. 114
2015
Earlier work this paper cites.
P. Wittek and L. Calderaro, “Extended computational kernels in a massively parallel implementation of the Trotter-Suzuki approximation,” Comp. Phys. Comm. 197
2015
Earlier work this paper cites.
Ho N. Phien et al., “Infinite projected entangled pair states algorithm improved: Fast full update and gauge fixing,” Phys. Rev. B 92
2015
Earlier work this paper cites.
J. Haegeman, C. Lubich, I. Oseledets, B. Vandereycken, and F. Verstraete, “Unifying time evolution and optimization with matrix product states,” Phys. Rev. B 94
2016
Cited alongside, same era.
T. V. Laptyeva et al., “Calculating Floquet states of large quantum systems: A parallelization strategy and its cluster implementation,” Comp. Phys. Comm. 201
2016
Cited alongside, same era.
M. Ẑnidarič, A. Scardicchio, and V. K. Varma, “Diffusive and subdiffusive spin transport in the ergodic phase of a many-body localizable system,” Phys. Rev. Lett. 117
2016
Cited alongside, same era.
2016
Cited alongside, same era.
I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning (The MIT Press, 2016)
2019
Later among the works it cites.
2019
Later among the works it cites.
K. Björnson, “TBTK: A quantum mechanics software development kit,” SoftwareX 9
2019
Later among the works it cites.
A. Liniov et al., “Unfolding a quantum master equation into a system of real-valued equations: Computationally effective expansion over the basis of SU (N) generators,” Phys. Rev. E 100
2019
Later among the works it cites.
I. Meyerov et al., “Transforming the Lindblad equation into a system of linear equations: Performance optimization and parallelization,” arXiv: 1912.01491 (2019)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2016
Cited alongside, same era.
G. H. Low and I. L. Chuang, “Optimal Hamiltonian simulation by quantum signal processing,” Phys. Rev. Lett. 118
2017
Cited alongside, same era.
G. Carleo and M. Troyer, “Solving the quantum many-body problem with artificial neural networks,” Science 355
2017
Cited alongside, same era.
B. Schmidt and U. Lorenz, “WavePacket: A Matlab package for numerical quantum dynamics. I: Closed quantum systems and discrete variable representations,” Comp. Phys. Comm. 213
2017
Cited alongside, same era.
A. W. Cross et al., “Open quantum assembly language,” arXiv:1707.03429 (2017)
2017
Cited alongside, same era.
T. Häner and D. S. Steiger, “0.5 petabyte simulation of a 45-qubit quantum circuit,” In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 1-10 (2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
V. Volokitin, A. Liniov, I. Meyerov, M. Hartmann, M. Ivanchenko, P. Hänggi, and S. Denisov, “Computation of the asymptotic states of modulated open quantum systems with a numerically exact realization of the quantum trajectory method ,” Phys. Rev. E 96
2017
Cited alongside, same era.
2019
Later among the works it cites.
V. Volokitin et al., “Propagating large open quantum systems towards their asymptotic states: cluster implementation of the time-evolving block decimation scheme,” J. of Phys.: Conf. Series 1392
2019
Later among the works it cites.
M. Brenes et al., “Massively parallel implementation and approaches to simulate quantum dynamics using Krylov subspace techniques,” Comput. Phys. Commun. 235
2019
Later among the works it cites.
2019
Later among the works it cites.
S. Paeckel et al., “Time-evolution methods for matrix-product states,” Ann. of Phys. 411
2019
Later among the works it cites.
A. M. Childs et al., “Toward the first quantum simulation with quantum speedup,” PNAS 115
2019
Later among the works it cites.
We do not address here the issue of fault tolerant quantum computations and different error mitigation techniques, which are subjects of active research; see, e.g., recent works S. Endo, S. C. Benjamin, and Ying Li, “Practical quantum error mitigation for near-future applications,” Phys. Rev. X 8
2019
Later among the works it cites.
T. Jones, A. Brown, I. Bush, and S. C. Benjami, “QuEST and high performance simulation of Quantum Computer,” Sci. Rep. 9
2019
Later among the works it cites.
Zhih-Ahn Jia et al., “Quantum neural network states: A brief review of methods and applications,” Adv. Quantum Technol., 1800077 (2019)
2019
Later among the works it cites.
M. Amy and V. Gheorghiu, “staq–A full-stack quantum processing toolkit,” arXiv:1912.06070 (2019)
2019
Later among the works it cites.
A. B. de Avila et al., “State-of-the-art quantum computing simulators: Features, optimizations, and improvements for D-GM,” Neurocomputing (2019)
2019
Later among the works it cites.
S. Khatri et al., “Quantum-assisted quantum compiling,” Quantum 3
2019
Later among the works it cites.
Gartner: Hype Cycle Research Methodology. https://www.gartner.com/en/research/methodologies/gartner-hype-cycle . Accessed 2020
2020
Closest in time.
IBM Q Experience. https://www.ibm.com/quantum-computing/technology/experience/ . Accessed 2020
2020
Closest in time.
QuEST – Quantum Exact Simulation Toolkit. https://quest.qtechtheory.org/ . Accessed 2020
2020
Closest in time.
List of QC simulators. https://quantiki.org/wiki/list-qc-simulators . Accessed April 2020
2020
Closest in time.
2020
Closest in time.
G. Aleksandrowicz et al., “Qiskit: An open-source framework for quantum computing,” https://zenodo.org/record/2562111 . Accessed April 2020
2020
Closest in time.
E. Pednault et al., “On ”Quantum Supremacy”,” https://www.ibm.com/blogs/research/2019/10/on-quantum-supremacy/ . Accessed 2020
2020
Closest in time.
Increasing AI Performance and Efficiency with Intel DL Boost. https://www.intel.ai/increasing-ai-performance-intel-dlboost/#gs.117qh4 . Accessed 2020
2020
Closest in time.
Intel Unveils New GPU Architecture with High-Performance Computing and AI Acceleration. https://newsroom.intel.com/news-releases/intel-unveils-new-gpu-architecture-optimized-for-hpc-ai-oneapi/#gs.11dtfx . Accessed 2020
2020
Closest in time.
Graphcore. https://www.graphcore.ai/ . Accessed 2020
2020
Closest in time.