2,539 research outputs found
A robust empirical seasonal prediction of winter NAO and surface climate
A key determinant of winter weather and climate in Europe and North America is the North Atlantic Oscillation (NAO), the dominant mode of atmospheric variability in the Atlantic domain. Skilful seasonal forecasting of the surface climate in both Europe and North America is reflected largely in how accurately models can predict the NAO. Most dynamical models, however, have limited skill in seasonal forecasts of the winter NAO. A new empirical model is proposed for the seasonal forecast of the winter NAO that exhibits higher skill than current dynamical models. The empirical model provides robust and skilful prediction of the December-January-February (DJF) mean NAO index using a multiple linear regression (MLR) technique with autumn conditions of sea-ice concentration, stratospheric circulation, and sea-surface temperature. The predictability is, for the most part, derived from the relatively long persistence of sea ice in the autumn. The lower stratospheric circulation and sea-surface temperature appear to play more indirect roles through a series of feedbacks among systems driving NAO evolution. This MLR model also provides skilful seasonal outlooks of winter surface temperature and precipitation over many regions of Eurasia and eastern North America
Time-Symmetric Quantum Theory of Smoothing
Smoothing is an estimation technique that takes into account both past and
future observations, and can be more accurate than filtering alone. In this
Letter, a quantum theory of smoothing is constructed using a time-symmetric
formalism, thereby generalizing prior work on classical and quantum filtering,
retrodiction, and smoothing. The proposed theory solves the important problem
of optimally estimating classical Markov processes coupled to a quantum system
under continuous measurements, and is thus expected to find major applications
in future quantum sensing systems, such as gravitational wave detectors and
atomic magnetometers.Comment: 4 pages, 1 figure, v2: accepted by PR
Self-Averaging Scaling Limits of Two-Frequency Wigner Distribution for Random Paraxial Waves
Two-frequency Wigner distribution is introduced to capture the asymptotic
behavior of the space-frequency correlation of paraxial waves in the radiative
transfer limits. The scaling limits give rises to deterministic transport-like
equations. Depending on the ratio of the wavelength to the correlation length
the limiting equation is either a Boltzmann-like integral equation or a
Fokker-Planck-like differential equation in the phase space. The solutions to
these equations have a probabilistic representation which can be simulated by
Monte Carlo method. When the medium fluctuates more rapidly in the longitudinal
direction, the corresponding Fokker-Planck-like equation can be solved exactly.Comment: typos correcte
CONVERGENCE OF AMERICAN OPTION VALUES FROM DISCRETE- TO CONTINUOUS-TIME FINANCIAL MODELS 1
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75553/1/j.1467-9965.1994.tb00059.x.pd
A fully-discrete scheme for systems of nonlinear Fokker-Planck-Kolmogorov equations
We consider a system of Fokker-Planck-Kolmogorov (FPK) equations, where the
dependence of the coefficients is nonlinear and nonlocal in time with respect
to the unknowns. We extend the numerical scheme proposed and studied recently
by the authors for a single FPK equation of this type. We analyse the
convergence of the scheme and we study its applicability in two examples. The
first one concerns a population model involving two interacting species and the
second one concerns two populations Mean Field Games
Bellman equations for optimal feedback control of qubit states
Using results from quantum filtering theory and methods from classical
control theory, we derive an optimal control strategy for an open two-level
system (a qubit in interaction with the electromagnetic field) controlled by a
laser. The aim is to optimally choose the laser's amplitude and phase in order
to drive the system into a desired state. The Bellman equations are obtained
for the case of diffusive and counting measurements for vacuum field states. A
full exact solution of the optimal control problem is given for a system with
simpler, linear, dynamics. These linear dynamics can be obtained physically by
considering a two-level atom in a strongly driven, heavily damped, optical
cavity.Comment: 10 pages, no figures, replaced the simpler model in section
Some Estimates for Finite Difference Approximations
Some estimates for the approximation of optimal stochastic control problems by discrete time problems are obtained. In particular an estimate for the solutions of the continuous time versus the discrete time Hamilton-Jacobi-Bellman equations is given. The technique used is more analytic than probabilistic
A Quantum Langevin Formulation of Risk-Sensitive Optimal Control
In this paper we formulate a risk-sensitive optimal control problem for
continuously monitored open quantum systems modelled by quantum Langevin
equations. The optimal controller is expressed in terms of a modified
conditional state, which we call a risk-sensitive state, that represents
measurement knowledge tempered by the control purpose. One of the two
components of the optimal controller is dynamic, a filter that computes the
risk-sensitive state.
The second component is an optimal control feedback function that is found by
solving the dynamic programming equation. The optimal controller can be
implemented using classical electronics.
The ideas are illustrated using an example of feedback control of a two-level
atom
Climate‐related variations in mixing dynamics in an Alaskan arctic lake
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109805/1/lno2009546part22401.pd
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