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Measurement of anom...
Measurement of anomalous diffusion using recurrent neural networks
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- Bo, Stefano (författare)
- KTH,Stockholms universitet,Nordiska institutet för teoretisk fysik (Nordita),Nordic Institute for Theoretical Physics NORDITA,Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, Dresden, DE-01187, Germany
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- Schmidt, Falko, 1992 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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- Eichhorn, Ralf (författare)
- KTH,Stockholms universitet,Nordiska institutet för teoretisk fysik (Nordita),Nordic Institute for Theoretical Physics NORDITA
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- Volpe, Giovanni, 1979 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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(creator_code:org_t)
- American Physical Society, 2019
- 2019
- Engelska.
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Ingår i: Physical Review E. - : American Physical Society. - 2470-0045 .- 2470-0053. ; 100:1
- Relaterad länk:
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https://gup.ub.gu.se...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Anomalous diffusion occurs in many physical and biological phenomena, when the growth of the mean squared displacement (MSD) with time has an exponent different from one. We show that recurrent neural networks (RNNs) can efficiently characterize anomalous diffusion by determining the exponent from a single short trajectory, outperforming the standard estimation based on the MSD when the available data points are limited, as is often the case in experiments. Furthermore, the RNNs can handle more complex tasks where there are no standard approaches, such as determining the anomalous diffusion exponent from a trajectory sampled at irregular times, and estimating the switching time and anomalous diffusion exponents of an intermittent system that switches between different kinds of anomalous diffusion. We validate our method on experimental data obtained from subdiffusive colloids trapped in speckle light fields and superdiffusive microswimmers.
Ämnesord
- NATURVETENSKAP -- Fysik (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences (hsv//eng)
- NATURVETENSKAP -- Matematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics (hsv//eng)
Nyckelord
- Physics
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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