Results 91 to 100 of about 657 (192)

Non-Markovian quantum exceptional points

Nature Communications
10+5 pages, 2 ...
Jhen-Dong Lin, Po-Chen Kuo, Neill Lambert, Adam Miranowicz, Franco Nori, Yueh-Nan Chen   +5 more
openaire   +4 more sources

Profiling the sleep architecture of ageing adults using a seven‐state continuous‐time Markov model

Journal of Sleep Research, Volume 34, Issue 2, April 2025.
Summary Sleep is a complex biological process regulated by networks of neurons and environmental factors. As one falls asleep, neurotransmitters from sleep–wake regulating neurones work in synergy to control the switching of different sleep states throughout the night. As sleep disorders or underlying neuropathology can manifest as irregular switching,
Jonathon Jacobs, Caitlin E. Martin, Bernard Fuemmeler, Shanshan Chen   +3 more
wiley   +1 more source

Quantum scarring enhances non-Markovianity of subsystem dynamics

New Journal of Physics
Given that any subsystem of a closed out-of-equilibrium quantum system is an open quantum system, its dynamics (reduced from the full system’s unitary evolution) can be either Markovian (memory-less) or non-Markovian, with the latter necessarily impeding
Aditya Banerjee
doaj   +1 more source

A Conditional Tail Expectation Type Risk Measure for Time Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT We consider the estimation of the conditional expectation 𝔼(Xh|X0>UX(1/p)), provided 𝔼|X0|<∞, at extreme levels, where (Xt)t∈ℤ$$ {\left({X}_t\right)}_{t\in \mathbb{Z}} $$ is a strictly stationary time series, UX$$ {U}_X $$ its tail quantile function, h$$ h $$ is a positive integer and p∈(0,1)$$ p\in \left(0,1\right) $$ is such that p→0$$ p\to ...
Yuri Goegebeur, Armelle Guillou, Jing Qin   +2 more
wiley   +1 more source

Non-Markovianity between Site Pairs in FMO Complex Using Discrete-Time Quantum Jump Model. [PDF]

ACS Omega, 2022
Kundu M, Chandrashekar CM.
europepmc   +1 more source

Autoregressive Hypergraph

Journal of Time Series Analysis, EarlyView.
ABSTRACT Traditional graph representations are insufficient for modelling real‐world phenomena involving multi‐entity interactions, such as collaborative projects or protein complexes, necessitating the use of hypergraphs. While hypergraphs preserve the intrinsic nature of such complex relationships, existing models often overlook temporal evolution in
Xianghe Zhu, Qiwei Yao
wiley   +1 more source

Multiple Chains Markov Switching Vector Autoregression

Journal of Time Series Analysis, EarlyView.
ABSTRACT Both the U.S. stock and bond returns exhibit distinct Markovian regimes. However, because these regimes display limited coherence, conventional models typically require highly parameterized systems to adequately capture their joint distribution.
Leopoldo Catania
wiley   +1 more source

The impact of memory on learning sequence-to-sequence tasks

Machine Learning: Science and Technology
The recent success of neural networks in natural language processing has drawn renewed attention to learning sequence-to-sequence (seq2seq) tasks. While there exists a rich literature that studies classification and regression tasks using solvable models
Alireza Seif, Sarah A M Loos, Gennaro Tucci, Édgar Roldán, Sebastian Goldt   +4 more
doaj   +1 more source

On Testing for Independence Between Generalized Error Models of Several Time Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi, Bouchra R. Nasri, Bruno N. Rémillard   +2 more
wiley   +1 more source

Non-Markovian control in the Situation Calculus

Artificial Intelligence, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources