The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Efficient tensor network simulation of IBM's largest quantum processors
Open accessAbstract
We show how quantum-inspired 2D tensor networks can be used to efficiently and accurately simulate the largest quantum processors from IBM, namely Eagle (127 qubits), Osprey (433 qubits), and Condor (1121 qubits). We simulate the dynamics of a complex quantum many-body system—specifically, the kicked Ising experiment considered recently by IBM in Y. Kim , —using graph-based projected entangled pair states (gPEPS), which was proposed by some of us in . Our results show that simple tensor updates are already sufficient to achieve very large unprecedented accuracy with remarkably low computational resources for this model. Apart from simulating the original experiment for 127 qubits, we also extend our results to 433 and 1121 qubits, and for evolution times around eight times longer, thus setting a benchmark for the newest IBM quantum machines. We also report accurate simulations for infinitely many qubits. Our results show that gPEPS are a natural tool to efficiently simulate quantum computers with an underlying lattice-based qubit connectivity, such as all quantum processors based on superconducting qubits. Published by the American Physical Society 2024
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The self-consistent combination of SO with SU has been successfully applied in related PEPS applications, and this method is feasible in all of our lattices.
“The self-consistent combination of SO with SU has been successfully applied in related PEPS applications 94 , and this method is feasible in all of our lattices.”
From Beyond-classical computation in quantum simulation (2025) · cites this paper as [94]
The Method section says the authors used simple update (SU) in gPEPS and found their approach accurate for the systems studied. It does not describe a self-consistent combination of SO with SU, so it supports the related PEPS application but not the specific combined method attributed to it. The statement about feasibility in the citing authors’ lattices is not attached to this citation. (LLM, conf=0.78)
Experimental — accuracy not yet measuredSU methods have been successfully applied for the simulation of a kicked Ising model on a heavy-hex lattice, which despite finite dimensionality (2) has a paucity of short loops.
“SU methods have been successfully applied for the simulation of a kicked Ising model on a heavy-hex lattice for example, which despite finite dimensionality (2) has a paucity of short loops 16,94 .”
From Beyond-classical computation in quantum simulation (2025) · cites this paper as [94]
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Cites
Superconducting Qubits: Current State of Play
Kjaergaard, M., Schwartz, M. E., Braumüller, J., Krantz, P., Wang, J. I.-J., Gustavsson, S., & Oliver, W. D. (2020) · Annual Review of Condensed Matter Physics · doi:10.1146/annurev-conmatphys-031119-050605 · Cited by 1,544 · cited 1×
“While several hardware architectures have been developed, the largest available quantum processors are those built with superconducting qubit technology [1].”
BackgroundOrús, R., & Vidal, G. (2009) · Physical Review B · doi:10.1103/physrevb.80.094403 · Cited by 387
Self-citationBegušić, T., Gray, J., & Chan, G. K.-L. (2024) · Science Advances · doi:10.1126/sciadv.adk4321 · Cited by 89
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Research works printed but not linked: 11
- 10.1038/s41586-023-06096-3 · DOI · Paper page
- 10.1103/PRXQuantum.5.010308 · DOI · Paper page
- 10.1016/j.aop.2014.06.013 · DOI · Paper page
- 10.1038/s42254-019-0086-7 · DOI
- 10.1103/PhysRevLett.101.250602 · DOI · Paper page
- 10.1103/PhysRevB.99.195105 · DOI
- 10.1103/PhysRevLett.101.090603 · DOI · Paper page
- 10.1088/1367-2630/16/3/033014 · DOI
- 10.1103/PhysRevB.90.064425 · DOI · Paper page
- 10.1103/PhysRevB.92.035142 · DOI · Paper page
- 10.1103/PhysRevResearch.3.023073 · DOI · Paper page
Cited by
Sorted by citations
Beyond-classical computation in quantum simulation
King, A. D., Nocera, A., Rams, M. M., Dziarmaga, J., Wiersema, R., Bernoudy, W., Raymond, J., Kaushal, N., Heinsdorf, N., Harris, R., et al. (2025) · Science · doi:10.1126/science.ado6285 · Cited by 138
Bias-field digitized counterdiabatic quantum algorithm for higher-order binary optimization
Romero, S. V., Visuri, A.-M., Cadavid, A. G., Simen, A., Solano, E., & Hegade, N. N. (2025) · Communications Physics · doi:10.1038/s42005-025-02270-3 · Cited by 18
Metadata
- Authors
- Patra, S., Jahromi, S. S., Singh, S., & Orús, R.
- Affiliations
- Donostia International Physics Center (ES)
- Multiverse Computing (Spain) (ES)
- Multiverse Computing, Spadina Ave., Toronto, ON M5T 2C2, Canada
- Ikerbasque (ES)
- Venue
- Physical Review Research
- Publisher
- American Physical Society (APS)
- Published
- 2024-03-26
- Volume
- 6
- Issue
- 1
- ISSN
- 2643-1564 (ISSN-L)
- OpenAlex
- W4393191351
- Cited by
- 63
- References
- 3
- Citations by year
- 2026: 16 · 2025: 27 · 2024: 19
- FWCI
- 9.88
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Physical Review Research (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- Egg Industry Center
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Keywords
- tensor network simulation, IBM quantum processors, quantum many-body dynamics, superconducting qubits
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