Resources for bosonic quantum computational advantage Article Swipe
Ulysse Chabaud
,
Mattia Walschaers
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.11781
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.11781
Quantum computers promise to dramatically outperform their classical counterparts. However, the non-classical resources enabling such computational advantages are challenging to pinpoint, as it is not a single resource but the subtle interplay of many that can be held responsible for these potential advantages. In this work, we show that every bosonic quantum computation can be recast into a continuous-variable sampling computation where all computational resources are contained in the input state. Using this reduction, we derive a general classical algorithm for the strong simulation of bosonic computations, whose complexity scales with the non-Gaussian stellar rank of both the input state and the measurement setup. We further study the conditions for an efficient classical simulation of the associated continuous-variable sampling computations and identify an operational notion of non-Gaussian entanglement based on the lack of passive separability, thus clarifying the interplay of bosonic quantum computational resources such as squeezing, non-Gaussianity and entanglement.
Related Topics
Concepts
Quantum entanglement
Computation
Computer science
Gaussian
Computational complexity theory
Quantum computer
Computational resource
Sampling (signal processing)
Quantum
Statistical physics
Continuous variable
Theoretical computer science
Reduction (mathematics)
Algorithm
Mathematics
Quantum mechanics
Mathematical optimization
Physics
Geometry
Filter (signal processing)
Computer vision
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2207.11781
- https://arxiv.org/pdf/2207.11781
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4288055352
All OpenAlex metadata
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https://openalex.org/W4288055352Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2207.11781Digital Object Identifier
- Title
-
Resources for bosonic quantum computational advantageWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-07-24Full publication date if available
- Authors
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Ulysse Chabaud, Mattia WalschaersList of authors in order
- Landing page
-
https://arxiv.org/abs/2207.11781Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2207.11781Direct 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
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https://arxiv.org/pdf/2207.11781Direct OA link when available
- Concepts
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Quantum entanglement, Computation, Computer science, Gaussian, Computational complexity theory, Quantum computer, Computational resource, Sampling (signal processing), Quantum, Statistical physics, Continuous variable, Theoretical computer science, Reduction (mathematics), Algorithm, Mathematics, Quantum mechanics, Mathematical optimization, Physics, Geometry, Filter (signal processing), Computer visionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.interplay | 31, 138 |
| abstract_inverted_index.pinpoint, | 20 |
| abstract_inverted_index.potential | 41 |
| abstract_inverted_index.resources | 12, 64, 143 |
| abstract_inverted_index.advantages | 16 |
| abstract_inverted_index.associated | 116 |
| abstract_inverted_index.clarifying | 136 |
| abstract_inverted_index.complexity | 88 |
| abstract_inverted_index.conditions | 108 |
| abstract_inverted_index.outperform | 5 |
| abstract_inverted_index.reduction, | 73 |
| abstract_inverted_index.simulation | 83, 113 |
| abstract_inverted_index.squeezing, | 146 |
| abstract_inverted_index.advantages. | 42 |
| abstract_inverted_index.challenging | 18 |
| abstract_inverted_index.computation | 52, 60 |
| abstract_inverted_index.measurement | 102 |
| abstract_inverted_index.operational | 123 |
| abstract_inverted_index.responsible | 38 |
| abstract_inverted_index.computations | 119 |
| abstract_inverted_index.dramatically | 4 |
| abstract_inverted_index.entanglement | 127 |
| abstract_inverted_index.non-Gaussian | 92, 126 |
| abstract_inverted_index.computational | 15, 63, 142 |
| abstract_inverted_index.computations, | 86 |
| abstract_inverted_index.counterparts. | 8 |
| abstract_inverted_index.entanglement. | 149 |
| abstract_inverted_index.non-classical | 11 |
| abstract_inverted_index.separability, | 134 |
| abstract_inverted_index.non-Gaussianity | 147 |
| abstract_inverted_index.continuous-variable | 58, 117 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.52873624 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |