Zobrazeno 1 - 10
of 216
pro vyhledávání: '"Crutchfield J"'
Autor:
Venegas-Li, A., Crutchfield, J. P.
If an experimentalist observes a sequence of emitted quantum states via either projective or positive-operator-valued measurements, the outcomes form a time series. Individual time series are realizations of a stochastic process over the measurements
Externí odkaz:
http://arxiv.org/abs/2205.03958
Oscillator networks display intricate synchronization patterns. Determining their stability typically requires incorporating the symmetries of the network coupling. Going beyond analyses that appeal only to a network's automorphism group, we explore
Externí odkaz:
http://arxiv.org/abs/2010.09131
Adaptive systems -- such as a biological organism gaining survival advantage, an autonomous robot executing a functional task, or a motor protein transporting intracellular nutrients -- must model the regularities and stochasticity in their environme
Externí odkaz:
http://arxiv.org/abs/2006.15416
Autor:
Marzen, S. E., Crutchfield, J. P.
Inferring models, predicting the future, and estimating the entropy rate of discrete-time, discrete-event processes is well-worn ground. However, a much broader class of discrete-event processes operates in continuous-time. Here, we provide new metho
Externí odkaz:
http://arxiv.org/abs/2005.03750
Autor:
Marzen, S. E., Crutchfield, J. P.
Reservoir computers (RCs) and recurrent neural networks (RNNs) can mimic any finite-state automaton in theory, and some workers demonstrated that this can hold in practice. We test the capability of generalized linear models, RCs, and Long Short-Term
Externí odkaz:
http://arxiv.org/abs/1910.07663
Publikováno v:
Phys. Rev. Research 2, 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:
http://arxiv.org/abs/1909.06650
Autor:
Riechers, P. M., Crutchfield, J. P.
Publikováno v:
Phys. Rev. Research 3, 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:
http://arxiv.org/abs/1908.11405
Landauer's Principle states that the energy cost of information processing must exceed the product of the temperature and the change in Shannon entropy of the information-bearing degrees of freedom. However, this lower bound is achievable only for qu
Externí odkaz:
http://arxiv.org/abs/1812.11241
Given a classical channel---a stochastic map from inputs to outputs---the input can often be transformed to an intermediate variable that is informationally smaller than the input. The new channel accurately simulates the original but at a smaller tr
Externí odkaz:
http://arxiv.org/abs/1709.08101
Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essential. Deep learning is quickly becoming a standard approach for such a
Externí odkaz:
http://arxiv.org/abs/1709.03184