An Ensemble Approach for Compressive Sensing with Quantum Article Swipe
Ramin Ayanzadeh
,
Milton Halem
,
Tim Finin
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.13016/m2o2sr-qgvl
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.13016/m2o2sr-qgvl
We leverage the idea of a statistical ensemble to improve the quality of quantum annealing based binary compressive sensing. Since executing quantum machine instructions on a quantum annealer can result in an excited state, rather than the ground state of the given Hamiltonian, we use different penalty parameters to generate multiple distinct quadratic unconstrained binary optimization (QUBO) functions whose ground state(s) represent a potential solution of the original problem. We then employ the attained samples from minimizing all corresponding (different) QUBOs to estimate the solution of the problem of binary compressive sensing. Our experiments, on a D-Wave 2000Q quantum processor, demonstrated that the proposed ensemble scheme is notably less sensitive to the calibration of the penalty parameter that controls the trade-off between the feasibility and sparsity of recoveries.
Related Topics
Concepts
Quantum annealing
Quadratic unconstrained binary optimization
Compressed sensing
Quantum
Ground state
Binary number
Leverage (statistics)
Hamiltonian (control theory)
Computer science
Statistical ensemble
Algorithm
Quadratic equation
Excited state
Simulated annealing
Mathematical optimization
Quantum computer
Mathematics
Physics
Artificial intelligence
Quantum mechanics
Canonical ensemble
Statistics
Geometry
Monte Carlo method
Arithmetic
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2006.04682
- https://arxiv.org/pdf/2006.04682
- OA Status
- green
- References
- 20
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3033597366
All OpenAlex metadata
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https://openalex.org/W3033597366Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.13016/m2o2sr-qgvlDigital Object Identifier
- Title
-
An Ensemble Approach for Compressive Sensing with QuantumWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-06-08Full publication date if available
- Authors
-
Ramin Ayanzadeh, Milton Halem, Tim FininList of authors in order
- Landing page
-
https://arxiv.org/abs/2006.04682Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2006.04682Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2006.04682Direct OA link when available
- Concepts
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Quantum annealing, Quadratic unconstrained binary optimization, Compressed sensing, Quantum, Ground state, Binary number, Leverage (statistics), Hamiltonian (control theory), Computer science, Statistical ensemble, Algorithm, Quadratic equation, Excited state, Simulated annealing, Mathematical optimization, Quantum computer, Mathematics, Physics, Artificial intelligence, Quantum mechanics, Canonical ensemble, Statistics, Geometry, Monte Carlo method, ArithmeticTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
- References (count)
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20Other works algorithmically related by OpenAlex
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