Fetching the paper…
Reading the bibliography…
Until fault-tolerance becomes implementable at scale, quantum computing will heavily rely on noise mitigation techniques.
A. R. Calderbank and P. W. Shor, Good quantum error-correcting codes exist, Physical Review A 54
1996
Earlier work this paper cites.
J. Preskill, Fault-tolerant quantum computation, in Introduction to quantum computation and information (World Scientific, 1998) pp. 213–269
1998
Earlier work this paper cites.
D. Gottesman, The Heisenberg representation of quantum computers, arXiv preprint quant-ph/9807006 https://doi.org/10.48550/arXiv.quant-ph/9807006 (1998)
1998
Earlier work this paper cites.
S. Aaronson and D. Gottesman, Improved simulation of stabilizer circuits, Phys. Rev. A 70
2004
Earlier work this paper cites.
F. Verstraete and J. I. Cirac, Matrix product states represent ground states faithfully, Phys. Rev. B 73
2006
Earlier work this paper cites.
S. Anders and H. J. Briegel, Fast simulation of stabilizer circuits using a graph-state representation, Phys. Rev. A 73
2006
Earlier work this paper cites.
D. Perez-García, F. Verstraete, M. M. Wolf, and J. I. Cirac, Matrix product state representations, Quantum Information and Computation 7
2007
Earlier work this paper cites.
F. Verstraete, V. Murg, and J. I. Cirac, Matrix product states, projected entangled pair states, and variational renormalization group methods for quantum spin systems, Advances in Physics 57
2008
Earlier work this paper cites.
F. Fröwis, V. Nebendahl, and W. Dür, Tensor operators: Constructions and applications for long-range interaction systems, Phys. Rev. A 81
2010
Earlier work this paper cites.
M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information (Cambridge University Press, 2010)
2010
Earlier work this paper cites.
U. Schollwöck, The density-matrix renormalization group in the age of matrix product states, Annals of Physics 326
2011
Earlier work this paper cites.
M. R. Geller and Z. Zhou, Efficient error models for fault-tolerant architectures and the pauli twirling approximation, Phys. Rev. A 88
2013
Earlier work this paper cites.
A. H. Werner, D. Jaschke, P. Silvi, M. Kliesch, T. Calarco, J. Eisert, and S. Montangero, Positive tensor network approach for simulating open quantum many-body systems, Phys. Rev. Lett. 116
2016
Earlier work this paper cites.
J. J. Wallman and J. Emerson, Noise tailoring for scalable quantum computation via randomized compiling, Phys. Rev. A 94
2016
Earlier work this paper cites.
K. Temme, S. Bravyi, and J. M. Gambetta, Error mitigation for short-depth quantum circuits, Phys. Rev. Lett. 119
2017
Earlier work this paper cites.
C. Hubig, I. McCulloch, and U. Schollwöck, Generic construction of efficient matrix product operators, Physical Review B 95
2017
Earlier work this paper cites.
M. L. (https://mathoverflow.net/users/143/michael lugo), Sum of “the first k” binomial coefficients for fixed n n , MathOverflow (2017), https://mathoverflow.net/q/17236
2017
Earlier work this paper cites.
N. C. Rubin, R. Babbush, and J. McClean, Application of fermionic marginal constraints to hybrid quantum algorithms, New Journal of Physics 20
2018
Earlier work this paper cites.
S. Montangero, E. Montangero, and Evenson, Introduction to tensor network methods (Springer, 2018)
2018
Earlier work this paper cites.
S. Boyd and L. Vandenberghe, Introduction to applied linear algebra: vectors, matrices, and least squares (Cambridge university press, 2018)
2018
Earlier work this paper cites.
J. Gray, Quimb: A python package for quantum information and many-body calculations, Journal of Open Source Software 3
2018
Cited alongside, same era.
S. McArdle, X. Yuan, and S. Benjamin, Error-mitigated digital quantum simulation, Phys. Rev. Lett. 122
2019
Cited alongside, same era.
H.-Y. Huang, R. Kueng, and J. Preskill, Predicting many properties of a quantum system from very few measurements, Nature Physics 16
2020
Cited alongside, same era.
Z. Jiang, A. Kalev, W. Mruczkiewicz, and H. Neven, Optimal fermion-to-qubit mapping via ternary trees with applications to reduced quantum states learning, Quantum 4
2020
Cited alongside, same era.
A. Robert, P. K. Barkoutsos, S. Woerner, and I. Tavernelli, Resource-efficient quantum algorithm for protein folding, npj Quantum Information 7
2021
Cited alongside, same era.
K. Bharti, A. Cervera-Lierta, T. H. Kyaw, T. Haug, S. Alperin-Lea, A. Anand, M. Degroote, H. Heimonen, J. S. Kottmann, T. Menke, W.-K. Mok, S. Sim, L.-C. Kwek, and A. Aspuru-Guzik, Noisy intermediate-scale quantum algorithms, Rev. Mod. Phys. 94
2022
Later among the works it cites.
F. D. Malone, R. M. Parrish, A. R. Welden, T. Fox, M. Degroote, E. Kyoseva, N. Moll, R. Santagati, and M. Streif, Towards the simulation of large scale protein–ligand interactions on NISQ-era quantum computers, Chemical Science 13
2022
Later among the works it cites.
J. J. M. Kirsopp, C. Di Paola, D. Z. Manrique, M. Krompiec, G. Greene-Diniz, W. Guba, A. Meyder, D. Wolf, M. Strahm, and D. Muñoz Ramo, Quantum computational quantification of protein–ligand interactions, International Journal of Quantum Chemistry 122
2022
Later among the works it cites.
H. Kamakari, S.-N. Sun, M. Motta, and A. J. Minnich, Digital quantum simulation of open quantum systems using quantum imaginary–time evolution, PRX Quantum 3
2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
B. Koczor, Exponential error suppression for near-term quantum devices, Phys. Rev. X 11
2021
Cited alongside, same era.
P. Suchsland, F. Tacchino, M. H. Fischer, T. Neupert, P. K. Barkoutsos, and I. Tavernelli, Algorithmic Error Mitigation Scheme for Current Quantum Processors, Quantum 5
2021
Cited alongside, same era.
P. Czarnik, A. Arrasmith, P. J. Coles, and L. Cincio, Error mitigation with Clifford quantum-circuit data, Quantum 5
2021
Cited alongside, same era.
A. Strikis, D. Qin, Y. Chen, S. C. Benjamin, and Y. Li, Learning-based quantum error mitigation, PRX Quantum 2
2021
Cited alongside, same era.
H.-Y. Huang, R. Kueng, and J. Preskill, Efficient estimation of Pauli observables by derandomization, Physical Review Letters 127
2021
Cited alongside, same era.
G. García-Pérez, M. A. Rossi, B. Sokolov, F. Tacchino, P. K. Barkoutsos, G. Mazzola, I. Tavernelli, and S. Maniscalco, Learning to measure: Adaptive informationally complete generalized measurements for quantum algorithms, PRX Quantum 2
2021
Cited alongside, same era.
J. I. Cirac, D. Pérez-García, N. Schuch, and F. Verstraete, Matrix product states and projected entangled pair states: Concepts, symmetries, theorems, Rev. Mod. Phys. 93
2021
Cited alongside, same era.
Later among the works it cites.
C. Piveteau, D. Sutter, and S. Woerner, Quasiprobability decompositions with reduced sampling overhead, npj Quantum Information 8
2022
Later among the works it cites.
Y. Guo and S. Yang, Quantum error mitigation via matrix product operators, PRX Quantum 3
2022
Later among the works it cites.
C. Hadfield, S. Bravyi, R. Raymond, and A. Mezzacapo, Measurements of quantum Hamiltonians with locally-biased classical shadows, Communications in Mathematical Physics 391
2022
Later among the works it cites.
G. Evenbly, A practical guide to the numerical implementation of tensor networks i: Contractions, decompositions, and gauge freedom, Frontiers in Applied Mathematics and Statistics 8
2022
Later among the works it cites.
2022
Later among the works it cites.
2022
Later among the works it cites.
N. Keenan, N. Robertson, T. Murphy, S. Zhuk, and J. Goold, Evidence of Kardar-Parisi-Zhang scaling on a digital quantum simulator, npj Quantum Inf. 9
2023
Closest in time.
2023
Closest in time.
Y. Kim, A. Eddins, S. Anand, K. X. Wei, E. Van Den Berg, S. Rosenblatt, H. Nayfeh, Y. Wu, M. Zaletel, K. Temme, et al. , Evidence for the utility of quantum computing before fault tolerance, Nature 618
2023
Closest in time.
2023
Closest in time.
E. Van Den Berg, Z. K. Minev, A. Kandala, and K. Temme, Probabilistic error cancellation with sparse pauli–lindblad models on noisy quantum processors, Nature Physics (2023)
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
G. Torlai, C. J. Wood, A. Acharya, G. Carleo, J. Carrasquilla, and L. Aolita, Quantum process tomography with unsupervised learning and tensor networks, Nat. Commun. 14
2023
Closest in time.