Analysis of temporal structure of laser chaos by Allan variance Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2208.02961
Allan variance has been widely utilized in evaluating the stability of the time series generated by atomic clocks and lasers, in time regimes ranging from short to extremely long. This multi-scale examination capability of the Allan variance may also be beneficial in evaluating the chaotic oscillating dynamics of semiconductor lasers, not just for conventional phase stability analysis purposes. Here we demonstrate Allan variance analysis of the complex time series generated by a semiconductor laser with delayed feedback, including low-frequency fluctuations (LFFs), which exhibit both fast and slow dynamics. Whereas the detection of LFFs is not easy with the conventional power spectrum analysis method in the low-frequency regime, we show that the Allan variance approach clearly captured the appearance of multiple time-scale dynamics, like LFFs. This study demonstrates that Allan variance can help in understanding and characterizing versatile laser dynamics, including LFFs, which involve dynamics spanning a wide range of time scales.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2208.02961
- https://arxiv.org/pdf/2208.02961
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4299798643
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4299798643Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2208.02961Digital Object Identifier
- Title
-
Analysis of temporal structure of laser chaos by Allan varianceWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-08-05Full publication date if available
- Authors
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Naoki Asuke, Nicolas Chauvet, André Röhm, Kazutaka Kanno, Atsushi Uchida, Tomoaki Niiyama, Satoshi Sunada, Ryoichi Horisaki, Makoto NaruseList of authors in order
- Landing page
-
https://arxiv.org/abs/2208.02961Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2208.02961Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2208.02961Direct OA link when available
- Concepts
-
Allan variance, Variance (accounting), Chaotic, Statistical physics, Stability (learning theory), Laser, Scale (ratio), Series (stratigraphy), Time series, Computer science, Optics, Physics, Mathematics, Statistics, Standard deviation, Artificial intelligence, Geology, Quantum mechanics, Paleontology, Business, Accounting, Machine learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.of | 10, 33, 47, 64, 91, 118, 148 |
| abstract_inverted_index.to | 26 |
| abstract_inverted_index.we | 59, 107 |
| abstract_inverted_index.and | 18, 85, 134 |
| abstract_inverted_index.can | 130 |
| abstract_inverted_index.for | 52 |
| abstract_inverted_index.has | 2 |
| abstract_inverted_index.may | 37 |
| abstract_inverted_index.not | 50, 94 |
| abstract_inverted_index.the | 8, 11, 34, 43, 65, 89, 97, 104, 110, 116 |
| abstract_inverted_index.Here | 58 |
| abstract_inverted_index.LFFs | 92 |
| abstract_inverted_index.This | 29, 124 |
| abstract_inverted_index.also | 38 |
| abstract_inverted_index.been | 3 |
| abstract_inverted_index.both | 83 |
| abstract_inverted_index.easy | 95 |
| abstract_inverted_index.fast | 84 |
| abstract_inverted_index.from | 24 |
| abstract_inverted_index.help | 131 |
| abstract_inverted_index.just | 51 |
| abstract_inverted_index.like | 122 |
| abstract_inverted_index.show | 108 |
| abstract_inverted_index.slow | 86 |
| abstract_inverted_index.that | 109, 127 |
| abstract_inverted_index.time | 12, 21, 67, 149 |
| abstract_inverted_index.wide | 146 |
| abstract_inverted_index.with | 74, 96 |
| abstract_inverted_index.Allan | 0, 35, 61, 111, 128 |
| abstract_inverted_index.LFFs, | 140 |
| abstract_inverted_index.LFFs. | 123 |
| abstract_inverted_index.laser | 73, 137 |
| abstract_inverted_index.long. | 28 |
| abstract_inverted_index.phase | 54 |
| abstract_inverted_index.power | 99 |
| abstract_inverted_index.range | 147 |
| abstract_inverted_index.short | 25 |
| abstract_inverted_index.study | 125 |
| abstract_inverted_index.which | 81, 141 |
| abstract_inverted_index.atomic | 16 |
| abstract_inverted_index.clocks | 17 |
| abstract_inverted_index.method | 102 |
| abstract_inverted_index.series | 13, 68 |
| abstract_inverted_index.widely | 4 |
| abstract_inverted_index.(LFFs), | 80 |
| abstract_inverted_index.Whereas | 88 |
| abstract_inverted_index.chaotic | 44 |
| abstract_inverted_index.clearly | 114 |
| abstract_inverted_index.complex | 66 |
| abstract_inverted_index.delayed | 75 |
| abstract_inverted_index.exhibit | 82 |
| abstract_inverted_index.involve | 142 |
| abstract_inverted_index.lasers, | 19, 49 |
| abstract_inverted_index.ranging | 23 |
| abstract_inverted_index.regime, | 106 |
| abstract_inverted_index.regimes | 22 |
| abstract_inverted_index.scales. | 150 |
| abstract_inverted_index.analysis | 56, 63, 101 |
| abstract_inverted_index.approach | 113 |
| abstract_inverted_index.captured | 115 |
| abstract_inverted_index.dynamics | 46, 143 |
| abstract_inverted_index.multiple | 119 |
| abstract_inverted_index.spanning | 144 |
| abstract_inverted_index.spectrum | 100 |
| abstract_inverted_index.utilized | 5 |
| abstract_inverted_index.variance | 1, 36, 62, 112, 129 |
| abstract_inverted_index.detection | 90 |
| abstract_inverted_index.dynamics, | 121, 138 |
| abstract_inverted_index.dynamics. | 87 |
| abstract_inverted_index.extremely | 27 |
| abstract_inverted_index.feedback, | 76 |
| abstract_inverted_index.generated | 14, 69 |
| abstract_inverted_index.including | 77, 139 |
| abstract_inverted_index.purposes. | 57 |
| abstract_inverted_index.stability | 9, 55 |
| abstract_inverted_index.versatile | 136 |
| abstract_inverted_index.appearance | 117 |
| abstract_inverted_index.beneficial | 40 |
| abstract_inverted_index.capability | 32 |
| abstract_inverted_index.evaluating | 7, 42 |
| abstract_inverted_index.time-scale | 120 |
| abstract_inverted_index.demonstrate | 60 |
| abstract_inverted_index.examination | 31 |
| abstract_inverted_index.multi-scale | 30 |
| abstract_inverted_index.oscillating | 45 |
| abstract_inverted_index.conventional | 53, 98 |
| abstract_inverted_index.demonstrates | 126 |
| abstract_inverted_index.fluctuations | 79 |
| abstract_inverted_index.low-frequency | 78, 105 |
| abstract_inverted_index.semiconductor | 48, 72 |
| abstract_inverted_index.understanding | 133 |
| abstract_inverted_index.characterizing | 135 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile.value | 0.13540552 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |