Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines
Takuro Matsuta, Ryo Furue
TL;DR
This paper explores using quantum annealing to solve ocean dynamics problems, but finds current hardware limitations hinder success.
Contribution
The paper formulates ocean dynamics as optimization problems suitable for quantum annealing and evaluates its feasibility.
Findings
Simulated annealing successfully solves the Stommel problem when parameters are chosen appropriately.
Quantum annealing fails due to hardware limitations like restricted connectivity.
Improving connectivity or embedding algorithms is needed for quantum machines to handle such problems.
Abstract
Recent advancements in quantum computing suggest the potential to revolutionize computational algorithms across various scientific domains including oceanography and atmospheric science. The field is still relatively young and quantum computation is so different from classical computation that suitable frameworks to represent oceanic and atmospheric dynamics are yet to be explored. Quantum annealing (QA), one of the major paradigms, focuses on combinatorial optimization tasks. Given its potential to excel in NP-hard problems, QA may significantly accelerate the calculation of ocean and atmospheric systems described by the Navier-Stokes equations in the future. In this paper, we apply both QA and simulated annealing (SA), its classical counterpart, to a simplified ocean model known as the Stommel problem. We use the Stommel problem, which is not an NP problem and therefore does not…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27
Figure 28
Figure 29
Figure 30
Figure 31
Figure 32
Figure 33
Figure 34
Figure 35
Figure 36
Figure 37
Figure 38
Figure 39
Figure 40
Figure 41
Figure 42
Figure 43
Figure 44
Figure 45
Figure 46
Figure 47
Figure 48
Figure 49
Figure 50Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Neural Networks and Reservoir Computing · Optical Network Technologies