Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Paul M. Riechers"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network. Recently, a “next-generation
Externí odkaz:
https://doaj.org/article/8566a6af65dd49d8a1f312001bb97d60
Publikováno v:
PRX Quantum, Vol 5, Iss 3, p 030318 (2024)
We investigate and ascertain the ideal inputs to any finite-time physical process. We demonstrate that the expectation values of entropy flow, heat, and work can all be determined via Hermitian observables of the initial state. These Hermitian operat
Externí odkaz:
https://doaj.org/article/f8384cd13799440f8aee21b465541015
Publikováno v:
Quantum, Vol 7, p 1203 (2023)
Quantum information-processing techniques enable work extraction from a system's inherently quantum features, in addition to the classical free energy it contains. Meanwhile, the science of computational mechanics affords tools for the predictive mod
Externí odkaz:
https://doaj.org/article/bf5194dbe99f403cade786bfb5edea23
Autor:
Paul M. Riechers, James P. Crutchfield
Publikováno v:
Physical Review Research, Vol 3, Iss 1, p 013170 (2021)
Power spectral densities are a common, convenient, and powerful way to analyze signals, so much so that they are now broadly deployed across the sciences and engineering—from quantum physics to cosmology and from crystallography to neuroscience to
Externí odkaz:
https://doaj.org/article/1971760422b54bd7b758c951a1fad344
Publikováno v:
Physical Review Research, Vol 2, Iss 3, p 033524 (2020)
Modern digital electronics support remarkably reliable computing, especially given the challenge of controlling nanoscale logical components that interact in fluctuating environments. However, we demonstrate that the high-reliability limit is subject
Externí odkaz:
https://doaj.org/article/d1259f8ca1de4d4d91b30f21f8650d4a
Autor:
Paul M. Riechers, James P. Crutchfield
Publikováno v:
AIP Advances, Vol 8, Iss 6, Pp 065305-065305-31 (2018)
Nonlinearities in finite dimensions can be linearized by projecting them into infinite dimensions. Unfortunately, the familiar linear operator techniques that one would then hope to use often fail since the operators cannot be diagonalized. The curse
Externí odkaz:
https://doaj.org/article/b0c324ca5b1c4ff3b4d162b67cc260d3
Publikováno v:
Journal of Statistical Physics, vol 183, iss 1
Nonequilibrium information thermodynamics determines the minimum energy dissipation to reliably erase memory under time-symmetric control protocols. We demonstrate that its bounds are tight and so show that the costs overwhelm those implied by Landau
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21da24ec5f0b8d32cfb03d09835ba63d
https://escholarship.org/uc/item/4632v615
https://escholarship.org/uc/item/4632v615
Autor:
James P. Crutchfield, Paul M. Riechers
Publikováno v:
Physical Review Research, vol 3, iss 1
Power spectral densities are a common, convenient, and powerful way to analyze signals. So much so that they are now broadly deployed across the sciences and engineering---from quantum physics to cosmology, and from crystallography to neuroscience to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a5f251e31d9a06e22fb7fd63987f724
https://escholarship.org/uc/item/27f9t8th
https://escholarship.org/uc/item/27f9t8th
Autor:
Mile Gu, Paul M. Riechers
The thermodynamic cost of resetting an arbitrary initial state to a particular desired state is lower bounded by Landauer's bound. However, here we demonstrate that this lower bound is necessarily unachievable for nearly every initial state, for any
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31f7b04dfe5afc5e4cb3b718b1181756
https://hdl.handle.net/10356/154963
https://hdl.handle.net/10356/154963
Publikováno v:
Physical Review Research, vol 2, iss 3
Modern digital electronics support remarkably reliable computing, especially given the challenge of controlling nanoscale logical components that interact in fluctuating environments. However, we demonstrate that the high-reliability limit is subject
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78a3f2e4a8092bb36441ee628b32ae16
https://escholarship.org/uc/item/8j09r0z9
https://escholarship.org/uc/item/8j09r0z9