journal article Oct 26, 2022

The future of quantum computing with superconducting qubits

View at Publisher Save 10.1063/5.0082975
Abstract
For the first time in history, we are seeing a branching point in computing paradigms with the emergence of quantum processing units (QPUs). Extracting the full potential of computation and realizing quantum algorithms with a super-polynomial speedup will most likely require major advances in quantum error correction technology. Meanwhile, achieving a computational advantage in the near term may be possible by combining multiple QPUs through circuit knitting techniques, improving the quality of solutions through error suppression and mitigation, and focusing on heuristic versions of quantum algorithms with asymptotic speedups. For this to happen, the performance of quantum computing hardware needs to improve and software needs to seamlessly integrate quantum and classical processors together to form a new architecture that we are calling quantum-centric supercomputing. In the long term, we see hardware that exploits qubit connectivity in higher than 2D topologies to realize more efficient quantum error correcting codes, modular architectures for scaling QPUs and parallelizing workloads, and software that evolves to make the intricacies of the technology invisible to the users and realize the goal of ubiquitous, frictionless quantum computing.
Topics

No keywords indexed for this article. Browse by subject →

References
135
[1]
[2]
[3]
Quantum Algorithm Providing Exponential Speed Increase for Finding Eigenvalues and Eigenvectors

Daniel S. Abrams, Seth Lloyd

Physical Review Letters 1999 10.1103/physrevlett.83.5162
[4]
Quantum Algorithm for Linear Systems of Equations

Aram W. Harrow, Avinatan Hassidim, Seth Lloyd

Physical Review Letters 2009 10.1103/physrevlett.103.150502
[5]
[6]
[7]
"Toward the first quantum simulation with quantum speedup" Proc. Natl. Acad. Sci. USA (2018) 10.1073/pnas.1801723115
[8]
"Fault-tolerant quantum computation by anyons" Ann. Phys. (2003) 10.1016/s0003-4916(02)00018-0
[9]
(1998)
[10]
Error Mitigation for Short-Depth Quantum Circuits

Kristan Temme, Sergey Bravyi, Jay M. Gambetta

Physical Review Letters 2017 10.1103/physrevlett.119.180509
[11]
"Efficient variational quantum simulator incorporating active error minimization" Phys. Rev. X (2017) 10.1103/physrevx.7.021050
[12]
"Trading classical and quantum computational resources" Phys. Rev. X (2016) 10.1103/physrevx.6.021043
[13]
"Simulating large quantum circuits on a small quantum computer" Phys. Rev. Lett. (2020) 10.1103/physrevlett.125.150504
[15]
"Constructing a virtual two-qubit gate by sampling single-qubit operations" New J. Phys. (2021) 10.1088/1367-2630/abd7bc
[16]
D. Gottesman , “Fault-tolerant quantum computation with constant overhead,” arXiv:1310.2984 (2013).
[17]
"Quantum low-density parity-check codes" PRX Quantum (2021) 10.1103/prxquantum.2.040101
[18]
N. Baspin and A.Krishna, “Quantifying nonlocality: How outperforming local quantum codes is expensive,” arXiv:2109.10982 (2021). 10.1103/physrevlett.129.050505
[19]
Universal Quantum Simulators

Seth Lloyd

Science 1996 10.1126/science.273.5278.1073
[20]
Quantum Algorithm for Linear Systems of Equations

Aram W. Harrow, Avinatan Hassidim, Seth Lloyd

Physical Review Letters 2009 10.1103/physrevlett.103.150502
[21]
Quantum algorithms for topological and geometric analysis of data

Seth Lloyd, Silvano Garnerone, Paolo Zanardi

Nature Communications 2016 10.1038/ncomms10138
[22]
C. Gyurik , C.Cade, and V.Dunjko, “Towards quantum advantage via topological data analysis,” arXiv:2005.02607 (2020).
[23]
S. Ubaru , I. Y.Akhalwaya, M. S.Squillante, K. L.Clarkson, and L.Horesh, “Quantum topological data analysis with linear depth and exponential speedup,” arXiv:2108.02811 (2021).
[24]
"A polynomial quantum algorithm for approximating the Jones polynomial" Algorithmica (2009) 10.1007/s00453-008-9168-0
[25]
Quantum Random Access Memory

Vittorio Giovannetti, Seth Lloyd, Lorenzo Maccone

Physical Review Letters 2008 10.1103/physrevlett.100.160501
[26]
Simulating physics with computers

Richard P. Feynman

International Journal of Theoretical Physics 1982 10.1007/bf02650179
[27]
Quantum thermalization through entanglement in an isolated many-body system

Adam M. Kaufman, M. Eric Tai, Alexander Lukin et al.

Science 2016 10.1126/science.aaf6725
[28]
"Unitary subharmonic response and floquet Majorana modes" Phys. Rev. Lett. (2020) 10.1103/physrevlett.125.086804
[29]
I. Aleiner , F.Arute, K.Arya, J.Atalaya, R.Babbush, J. C.Bardin, R.Barends, A.Bengtsson, S.Boixo, A.Bourassaet al., “Accurately computing electronic properties of materials using eigenenergies,” arXiv:2012.00921 (2020).
[30]
"Quantum simulators, continuous-time automata, and translationally invariant systems" Phys. Rev. Lett. (2008) 10.1103/physrevlett.100.010501
[31]
"Hamiltonian quantum cellular automata in one dimension" Phys. Rev. A (2008) 10.1103/physreva.78.032311
[32]
"Computational power of symmetric hamiltonians" Phys. Rev. A (2008) 10.1103/physreva.78.012346
[33]
B. A. Chase and A. J.Landahl, “Universal quantum walks and adiabatic algorithms by 1D hamiltonians,” arXiv:0802.1207 (2008).
[34]
Lieb-Robinson Bounds and the Generation of Correlations and Topological Quantum Order

S. Bravyi, M. B. Hastings, F. Verstraete

Physical Review Letters 2006 10.1103/physrevlett.97.050401
[35]
"Efficient approximation of the dynamics of one-dimensional quantum spin systems" Phys. Rev. Lett. (2006) 10.1103/physrevlett.97.157202
[36]
"The density-matrix renormalization group in the age of matrix product states" Ann. Phys. (2011) 10.1016/j.aop.2010.09.012
[37]
"Observations outside the light cone: Algorithms for nonequilibrium and thermal states" Phys. Rev. B (2008) 10.1103/physrevb.77.144302
[38]
[39]
"Faster quantum simulation by randomization" Quantum (2019) 10.22331/q-2019-09-02-182
[40]
"Qubitization of arbitrary basis quantum chemistry leveraging sparsity and low rank factorization" Quantum (2019) 10.22331/q-2019-12-02-208
[41]
"Class of quantum error-correcting codes saturating the quantum Hamming bound" Phys. Rev. A (1996) 10.1103/physreva.54.1862
[42]
"Quantum error correction and orthogonal geometry" Phys. Rev. Lett. (1997) 10.1103/physrevlett.78.405
[43]
Low-density parity-check codes

R. Gallager

IEEE Transactions on Information Theory 1962 10.1109/tit.1962.1057683
[44]
"Quantum LDPC codes with positive rate and minimum distance proportional to the square root of the blocklength" IEEE Trans. Inf. Theory (2013) 10.1109/tit.2013.2292061
[45]
"NP-hardness of decoding quantum error-correction codes" Phys. Rev. A (2011) 10.1103/physreva.83.052331
[46]
[47]
"Hardness of decoding quantum stabilizer codes" IEEE Trans. Inf. Theory (2015) 10.1109/tit.2015.2422294
[48]
Fault-Tolerant Quantum Computation with High Threshold in Two Dimensions

Robert Raussendorf, Jim Harrington

Physical Review Letters 2007 10.1103/physrevlett.98.190504
[49]
"High-threshold universal quantum computation on the surface code" Phys. Rev. A (2009) 10.1103/physreva.80.052312
[50]
"Surface code quantum computing with error rates over 1%" Phys. Rev. A (2011) 10.1103/physreva.83.020302

Showing 50 of 135 references

Cited By
283
Advanced Materials
The Journal of Supercomputing
IEEE Transactions on Applied Superc...
Nature
CMOS on-chip thermometry at deep cryogenic temperatures

Grayson M. Noah, Thomas H. Swift · 2024

Applied Physics Reviews
Journal of Chemical Information and...
Related

You May Also Like

Detailed Balance Limit of Efficiency ofp-nJunction Solar Cells

William Shockley, Hans J. Queisser · 1961

11,889 citations

A comprehensive review of ZnO materials and devices

Ü. Özgür, Ya. I. Alivov · 2005

10,305 citations

Contact and Rubbing of Flat Surfaces

J. F. Archard · 1953

6,810 citations

A Powder Technique for the Evaluation of Nonlinear Optical Materials

S. K. Kurtz, T. T. Perry · 1968

5,757 citations