Fetching the paper…
Reading the bibliography…
Quantum computational chemistry (QCC) is the use of quantum computers to solve problems in computational quantum chemistry.
S. R. White and R. L. Martin, “Ab initio quantum chemistry using the density matrix renormalization group,” The Journal of Chemical Physics , vol. 110, no. 9, pp. 4127–4130, 1999. [Online]. Available: https://doi.org/10.1063/1.478295
1999
Earlier work this paper cites.
W. Gropp, W. D. Gropp, E. Lusk, A. Skjellum, and A. D. F. E. E. Lusk, Using MPI: portable parallel programming with the message-passing interface . MIT press, 1999, vol. 1
1999
Earlier work this paper cites.
G. Vidal, “Efficient classical simulation of slightly entangled quantum computations,” Physical review letters , vol. 91, no. 14, p. 147902, 2003
2003
Earlier work this paper cites.
C. Lattner and V. Adve, “Llvm: A compilation framework for lifelong program analysis & transformation,” in International Symposium on Code Generation and Optimization, 2004. CGO 2004. IEEE, 2004, pp. 75–86
2004
Earlier work this paper cites.
M. B. Hastings, “Light-cone matrix product,” Journal of mathematical physics , vol. 50, no. 9, p. 095207, 2009
2009
Earlier work this paper cites.
U. Schollwöck, “The density-matrix renormalization group in the age of matrix product states,” Annals of Physics , vol. 326, no. 1, p. 96–192, Jan 2011. [Online]. Available: http://dx.doi.org/10.1016/j.aop.2010.09.012
2010
Earlier work this paper cites.
G. K.-L. Chan and S. Sharma, “The density matrix renormalization group in quantum chemistry,” Annual review of physical chemistry , vol. 62, pp. 465–481, 2011
2011
Earlier work this paper cites.
G. Knizia and G. K. L. Chan, “Density matrix embedding: A simple alternative to dynamical mean-field theory,” Physical Review Letters , vol. 109, no. 18, pp. 1–5, 2012
2012
Earlier work this paper cites.
2012
Earlier work this paper cites.
E. Stoudenmire and S. R. White, “Real-space parallel density matrix renormalization group,” Physical review B , vol. 87, no. 15, p. 155137, 2013
2013
Earlier work this paper cites.
R. Orús, “A practical introduction to tensor networks: Matrix product states and projected entangled pair states,” Annals of physics , vol. 349, pp. 117–158, 2014
2014
Earlier work this paper cites.
D. Poulin, M. B. Hastings, D. Wecker, N. Wiebe, A. C. Doberty, and M. Troyer, “The trotter step size required for accurate quantum simulation of quantum chemistry,” Quantum Info. Comput. , vol. 15, p. 361, 2015
2015
Earlier work this paper cites.
K. D. Vogiatzis, D. Ma, J. Olsen, L. Gagliardi, and W. A. de Jong, “Pushing configuration-interaction to the limit: Towards massively parallel mcscf calculations,” vol. 147, no. 18, p. 184111, 2017. [Online]. Available: https://doi.org/10.1063/1.4989858
2017
Earlier work this paper cites.
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 , 2017, pp. 1–10
2017
Earlier work this paper cites.
S. J. Bennie, B. F. E. Curchod, F. R. Manby, and D. R. Glowacki, “Pushing the limits of eom-ccsd with projector-based embedding for excitation energies,” The Journal of Physical Chemistry Letters , vol. 8, no. 22, pp. 5559–5565, 2017, pMID: 29076727. [Online]. Available: https://doi.org/10.1021/acs.jpclett.7b02500
2017
Earlier work this paper cites.
D. S. Steiger, T. Häner, and M. Troyer, “ProjectQ: an open source software framework for quantum computing,” Quantum , vol. 2, p. 49, Jan. 2018. [Online]. Available: https://doi.org/10.22331/q-2018-01-31-49
2018
Earlier work this paper cites.
T. Yamazaki, S. Matsuura, A. Narimani, A. Saidmuradov, and A. Zaribafiyan, “Towards the practical application of near-term quantum computers in quantum chemistry simulations: A problem decomposition approach,” 2018
2018
Earlier work this paper cites.
Q. Sun, T. C. Berkelbach, N. S. Blunt, G. H. Booth, S. Guo, Z. Li, J. Liu, J. D. McClain, E. R. Sayfutyarova, S. Sharma, S. Wouters, and G. K.-L. Chan, “Pyscf: the python-based simulations of chemistry framework,” Wiley Interdiscip. Rev. Comput. Mol. Sci. , vol. 8, p. e1340, 2018. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/wcms.1340
2018
Earlier work this paper cites.
T. Besard, C. Foket, and B. De Sutter, “Effective extensible programming: Unleashing Julia on GPUs,” IEEE Transactions on Parallel and Distributed Systems , 2018
2018
Earlier work this paper cites.
Y. Cao, J. Romero, J. P. Olson, M. Degroote, P. D. Johnson, M. Kieferová, I. D. Kivlichan, T. Menke, B. Peropadre, N. P. Sawaya et al. , “Quantum chemistry in the age of quantum computing,” Chemical reviews , vol. 119, no. 19, pp. 10 856–10 915, 2019
2019
Cited alongside, same era.
F. Arute, K. Arya, R. Babbush, D. Bacon, J. C. Bardin, R. Barends, R. Biswas, S. Boixo, F. G. Brandao, D. A. Buell et al. , “Quantum supremacy using a programmable superconducting processor,” Nature , vol. 574, no. 7779, pp. 505–510, 2019
2019
Cited alongside, same era.
C. Guo, Y. Liu, M. Xiong, S. Xue, X. Fu, A. Huang, X. Qiang, P. Xu, J. Liu, S. Zheng et al. , “General-purpose quantum circuit simulator with projected entangled-pair states and the quantum supremacy frontier,” Physical review letters , vol. 123, no. 19, p. 190501, 2019
2019
Cited alongside, same era.
B. Villalonga, S. Boixo, B. Nelson, C. Henze, E. Rieffel, R. Biswas, and S. Mandra, “A flexible high-performance simulator for verifying and benchmarking quantum circuits implemented on real hardware,” npj Quantum Information , vol. 5, no. 1, pp. 1–16, 2019
2021
Later among the works it cites.
C. Huang, F. Zhang, M. Newman, X. Ni, D. Ding, J. Cai, X. Gao, T. Wang, F. Wu, G. Zhang et al. , “Efficient parallelization of tensor network contraction for simulating quantum computation,” Nature Computational Science , vol. 1, no. 9, pp. 578–587, 2021
2021
Later among the works it cites.
Y. Liu, X. Liu, F. Li, H. Fu, Y. Yang, J. Song, P. Zhao, Z. Wang, D. Peng, H. Chen et al. , “Closing the” quantum supremacy” gap: achieving real-time simulation of a random quantum circuit using a new sunway supercomputer,” in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis , 2021, pp. 1–12
2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2019
Cited alongside, same era.
T. Jones, A. Brown, I. Bush, and S. C. Benjamin, “Quest and high performance simulation of quantum computers,” Sci. Rep. , vol. 9, p. 10736, 2019
2019
Cited alongside, same era.
A. Dang, C. D. Hill, and L. C. Hollenberg, “Optimising matrix product state simulations of shor’s algorithm,” Quantum , vol. 3, p. 116, 2019
2019
Cited alongside, same era.
J.-G. Liu, Y.-H. Zhang, Y. Wan, and L. Wang, “Variational quantum eigensolver with fewer qubits,” Phys. Rev. Research , vol. 1, p. 023025, Sep 2019. [Online]. Available: https://link.aps.org/doi/10.1103/PhysRevResearch.1.023025
2019
Cited alongside, same era.
X. Z. Luo, J. G. Liu, P. Zhang, and L. Wang, “Yao.jl: Extensible, efficient framework for quantum algorithm design,” 2019
2019
Cited alongside, same era.
2019
Cited alongside, same era.
K. Kaiser, L. M. Scriven, F. Schulz, P. Gawel, L. Gross, and H. L. Anderson, “An sp-hybridized molecular carbon allotrope, cyclo[18]carbon,” Science , vol. 365, no. 6459, pp. 1299–1301, 2019. [Online]. Available: https://www.science.org/doi/abs/10.1126/science.aay1914
2019
Cited alongside, same era.
S. McArdle, S. Endo, A. Aspuru-Guzik, S. C. Benjamin, and X. Yuan, “Quantum computational chemistry,” Reviews of Modern Physics , vol. 92, no. 1, p. 015003, 2020
2020
Cited alongside, same era.
V. E. Elfving, B. W. Broer, M. Webber, J. Gavartin, M. D. Halls, K. P. Lorton, and A. Bochevarov, “How will quantum computers provide an industrially relevant computational advantage in quantum chemistry?” 2020
2020
Cited alongside, same era.
2021
Later among the works it cites.
Y. Suzuki, Y. Kawase, Y. Masumura, Y. Hiraga, M. Nakadai, J. Chen, K. M. Nakanishi, K. Mitarai, R. Imai, S. Tamiya, T. Yamamoto, T. Yan, T. Kawakubo, Y. O. Nakagawa, Y. Ibe, Y. Zhang, H. Yamashita, H. Yoshimura, A. Hayashi, and K. Fujii, “Qulacs: a fast and versatile quantum circuit simulator for research purpose,” Quantum , vol. 5, p. 559, Oct. 2021. [Online]. Available: https://doi.org/10.22331/q-2021-10-06-559
2021
Later among the works it cites.
W. Li, Z. Huang, C. Cao, Y. Huang, Z. Shuai, X. Sun, J. Sun, X. Yuan, and D. Lv, “Toward practical quantum embedding simulation of realistic chemical systems on near-term quantum computers,” 2021
2021
Later among the works it cites.
X. Yuan, J. Sun, J. Liu, Q. Zhao, and Y. Zhou, “Quantum simulation with hybrid tensor networks,” Phys. Rev. Lett. , vol. 127, p. 040501, Jul 2021. [Online]. Available: https://link.aps.org/doi/10.1103/PhysRevLett.127.040501
2021
Later among the works it cites.
J. Qiao and Q. Jie, “Density matrix embedding theory of excited states for spin systems,” Computer Physics Communications , vol. 261, p. 107712, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0010465520303519
2021
Later among the works it cites.
F. Li, X. Liu, Y. Liu, P. Zhao, Y. Yang, H. Shang, W. Sun, Z. Wang, E. Dong, and D. Chen, “Sw_qsim: a minimize-memory quantum simulator with high-performance on a new sunway supercomputer,” in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis , 2021, pp. 1–13
2021
Later among the works it cites.
S. Byrne, L. C. Wilcox, and V. Churavy, “Mpi. jl: Julia bindings for the message passing interface,” in Proceedings of the JuliaCon Conferences , vol. 1, no. 1, 2021, p. 68
2021
Later among the works it cites.
J. J. M. Kirsopp, C. D. Paola, D. Z. Manrique, M. Krompiec, W. Guba, A. Meyder, D. Wolf, M. Strahm, and D. Mu, “Quantum Computational Quantification of Protein-Ligand Interactions,” 2021
2021
Later among the works it cites.
Y. Wang, S. Murlidaran, and D. A. Pearlman, “Quantum simulations of SARS-CoV-2 main protease Mpro enable high-quality scoring of diverse ligands,” Journal of Computer-Aided Molecular Design , vol. 35, no. 9, pp. 963–971, sep 2021. [Online]. Available: https://link.springer.com/10.1007/s10822-021-00412-7
2021
Later among the works it cites.
K. Bharti, A. Cervera-Lierta, T. H. Kyaw, T. Haug, S. Alperin-Lea, A. Anand, M. Degroote, H. Heimonen, J. S. Kottmann, T. Menke et al. , “Noisy intermediate-scale quantum algorithms,” Reviews of Modern Physics , vol. 94, no. 1, p. 015004, 2022
2022
Closest in time.
Q. Zhu, S. Cao, F. Chen, M.-C. Chen, X. Chen, T.-H. Chung, H. Deng, Y. Du, D. Fan, M. Gong et al. , “Quantum computational advantage via 60-qubit 24-cycle random circuit sampling,” Science Bulletin , vol. 67, no. 3, pp. 240–245, 2022
2022
Closest in time.
F. Pan and P. Zhang, “Simulation of quantum circuits using the big-batch tensor network method,” Physical Review Letters , vol. 128, no. 3, p. 030501, 2022
2022
Closest in time.
J. Y. Araz and M. Spannowsky, “Classical versus Quantum: comparing Tensor Network-based Quantum Circuits on LHC data,” 2022
2022
Closest in time.
J. Romero, R. Babbush, J. R. McClean, C. Hempel, P. J. Love, and A. Aspuru-Guzik, “Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz,” Quantum Science and Technology , vol. 4, no. 1, p. 014008, oct 2018. [Online]. Available: https://doi.org/10.1088/2058-9565/aad3e4
2058
Closest in time.
I. G. Ryabinkin, A. F. Izmaylov, and S. N. Genin, “A posteriori corrections to the iterative qubit coupled cluster method to minimize the use of quantum resources in large-scale calculations,” Quantum Sci. Technol. , vol. 6, no. 2, p. 024012, mar 2021. [Online]. Available: https://doi.org/10.1088/2058-9565/abda8e
2058
Closest in time.