QA and SA solutions by truncated spectral expansion when

QA and SA solutions by truncated spectral expansion when

<p>. (a) Streamfunction averaged over 10 runs from SA (shading) and CG (black contour lines). (b) The difference of cost function values between the SA and CG methods (blue curve) and its standard deviation (orange curve) versus epoch calculated over 10 runs. (c) and (d) are the same as the up...

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Bibliographic Details
Main Author: Takuro Matsuta (21608505) (author)
Other Authors: Ryo Furue (11772699) (author)
Published: 2025
Subjects:
Physiology
Science Policy
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
truncated basis expansion
still relatively young
obtain good solutions
currently available algorithms
sa successfully reproduces
quantum computing suggest
machine &# 8217
intricate problems governed
combinatorial optimization tasks
atmospheric systems described
quantum annealing machines
qa ), one
ocean dynamics problems
sa ),
quantum annealing
atmospheric dynamics
optimization problems
quantum computation
machine limits
solvable problems
hard problems
simulated annealing
optimization problem
atmospheric science
two ways
suitable frameworks
stommel problem
stommel model
stokes equations
squares method
qa using
qa today
major paradigms
hardware limitations
first step
finite difference
exploring qa
expected solution
either expanding
either case
cost function
classical counterpart
classical computation
cases owing
appropriate parameters
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Summary:<p>. (a) Streamfunction averaged over 10 runs from SA (shading) and CG (black contour lines). (b) The difference of cost function values between the SA and CG methods (blue curve) and its standard deviation (orange curve) versus epoch calculated over 10 runs. (c) and (d) are the same as the upper panels but for QA. The hyperparameters are .</p>

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