Causal Asymmetry in a Quantum World
| Autor: | Andrew J. P. Garner, Mile Gu, John R. Mahoney, James P. Crutchfield, Vlatko Vedral, Jayne Thompson |
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| Přispěvatelé: | School of Physical and Mathematical Sciences, Complexity Institute |
| Rok vydání: | 2018 |
| Předmět: |
Quantum Physics
Stochastic process Computer science Physics QC1-999 media_common.quotation_subject General Physics and Astronomy FOS: Physical sciences Science::Physics [DRNTU] Topology Condensed Matter Physics 01 natural sciences Asymmetry 010305 fluids & plasmas 0103 physical sciences Reverse time Overhead (computing) Quantum Information Quantum world Quantum information 010306 general physics Quantum Physics (quant-ph) Quantum Astronomical and Space Sciences media_common |
| Zdroj: | Physical Review X, vol 8, iss 3 Physical Review X, Vol 8, Iss 3, p 031013 (2018) |
| Popis: | Causal asymmetry is one of the great surprises in predictive modelling: the memory required to predict the future differs from the memory required to retrodict the past. There is a privileged temporal direction for modelling a stochastic process where memory costs are minimal. Models operating in the other direction incur an unavoidable memory overhead. Here we show that this overhead can vanish when quantum models are allowed. Quantum models forced to run in the less natural temporal direction not only surpass their optimal classical counterparts, but also any classical model running in reverse time. This holds even when the memory overhead is unbounded, resulting in quantum models with unbounded memory advantage. Comment: Journal reference included, 7 pages, 4 figures plus appendices, comments welcome |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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