4,248 research outputs found
Retrodiction as a tool for micromaser field measurements
We use retrodictive quantum theory to describe cavity field measurements by
successive atomic detections in the micromaser. We calculate the state of the
micromaser cavity field prior to detection of sequences of atoms in either the
excited or ground state, for atoms that are initially prepared in the excited
state. This provides the POM elements, which describe such sequences of
measurements.Comment: 20 pages, 4(8) figure
Temperature time series forecasting in The Optimal Challenges in Irrigation (TO CHAIR)
Predicting and forecasting weather time series has always been a difficult field of research analysis with a very slow progress rate over the years. The main challenge in this project—The Optimal Challenges in Irrigation (TO CHAIR)—is to study how to manage irrigation problems as an optimal control problem: the daily irrigation problem of minimizing water consumption. For that it is necessary to estimate and forecast weather variables in real time in each monitoring area of irrigation. These time series present strong trends and high-frequency seasonality. How to best model and forecast these patterns has been a long-standing issue in time series analysis. This study presents a comparison of the forecasting performance of TBATS (Trigonometric Seasonal, Box-Cox Transformation, ARMA errors, Trend and Seasonal Components) and regression with correlated errors models. These methods are chosen due to their ability to model trend and seasonal fluctuations present in weather data, particularly in dealing with time series with complex seasonal patterns (multiple seasonal patterns). The forecasting performance is demonstrated through a case study of weather time series: minimum air temperature.publishe
Kepler-91b: a planet at the end of its life. Planet and giant host star properties via light-curve variations
The evolution of planetary systems is intimately linked to the evolution of
their host star. Our understanding of the whole planetary evolution process is
based on the large planet diversity observed so far. To date, only few tens of
planets have been discovered orbiting stars ascending the Red Giant Branch.
Although several theories have been proposed, the question of how planets die
remains open due to the small number statistics. In this work we study the
giant star Kepler-91 (KOI-2133) in order to determine the nature of a
transiting companion. This system was detected by the Kepler Space Telescope.
However, its planetary confirmation is needed. We confirm the planetary nature
of the object transiting the star Kepler-91 by deriving a mass of and a planetary radius of
. Asteroseismic analysis produces a
stellar radius of and a mass of
. We find that its eccentric orbit
() is just away
from the stellar atmosphere at the pericenter. Kepler-91b could be the previous
stage of the planet engulfment, recently detected for BD+48 740. Our
estimations show that Kepler-91b will be swallowed by its host star in less
than 55 Myr. Among the confirmed planets around giant stars, this is the
planetary-mass body closest to its host star. At pericenter passage, the star
subtends an angle of , covering around 10% of the sky as seen from
the planet. The planetary atmosphere seems to be inflated probably due to the
high stellar irradiation.Comment: 21 pages, 8 tables and 11 figure
Role of loop entropy in the force induced melting of DNA hairpin
Dynamics of a single stranded DNA, which can form a hairpin have been studied
in the constant force ensemble. Using Langevin dynamics simulations, we
obtained the force-temperature diagram, which differs from the theoretical
prediction based on the lattice model. Probability analysis of the extreme
bases of the stem revealed that at high temperature, the hairpin to coil
transition is entropy dominated and the loop contributes significantly in its
opening. However, at low temperature, the transition is force driven and the
hairpin opens from the stem side. It is shown that the elastic energy plays a
crucial role at high force. As a result, the phase diagram differs
significantly with the theoretical prediction.Comment: 9 pages, 8 figures; J. Chem. Phys (2011
Multivariate Copula Analysis Toolbox (MvCAT): Describing Dependence and Underlying Uncertainty Using a Bayesian Framework
We present a newly developed Multivariate Copula Analysis Toolbox (MvCAT) which includes a wide range of copula families with different levels of complexity. MvCAT employs a Bayesian framework with a residual-based Gaussian likelihood function for inferring copula parameters and estimating the underlying uncertainties. The contribution of this paper is threefold: (a) providing a Bayesian framework to approximate the predictive uncertainties of fitted copulas, (b) introducing a hybrid-evolution Markov Chain Monte Carlo (MCMC) approach designed for numerical estimation of the posterior distribution of copula parameters, and (c) enabling the community to explore a wide range of copulas and evaluate them relative to the fitting uncertainties. We show that the commonly used local optimization methods for copula parameter estimation often get trapped in local minima. The proposed method, however, addresses this limitation and improves describing the dependence structure. MvCAT also enables evaluation of uncertainties relative to the length of record, which is fundamental to a wide range of applications such as multivariate frequency analysis
Frequency Tracking and Parameter Estimation for Robust Quantum State-Estimation
In this paper we consider the problem of tracking the state of a quantum
system via a continuous measurement. If the system Hamiltonian is known
precisely, this merely requires integrating the appropriate stochastic master
equation. However, even a small error in the assumed Hamiltonian can render
this approach useless. The natural answer to this problem is to include the
parameters of the Hamiltonian as part of the estimation problem, and the full
Bayesian solution to this task provides a state-estimate that is robust against
uncertainties. However, this approach requires considerable computational
overhead. Here we consider a single qubit in which the Hamiltonian contains a
single unknown parameter. We show that classical frequency estimation
techniques greatly reduce the computational overhead associated with Bayesian
estimation and provide accurate estimates for the qubit frequencyComment: 6 figures, 13 page
Six Peaks Visible in the Redshift Distribution of 46,400 SDSS Quasars Agree with the Preferred Redshifts Predicted by the Decreasing Intrinsic Redshift Model
The redshift distribution of all 46,400 quasars in the Sloan Digital Sky
Survey (SDSS) Quasar Catalog III, Third Data Release, is examined. Six Peaks
that fall within the redshift window below z = 4, are visible. Their positions
agree with the preferred redshift values predicted by the decreasing intrinsic
redshift (DIR) model, even though this model was derived using completely
independent evidence. A power spectrum analysis of the full dataset confirms
the presence of a single, significant power peak at the expected redshift
period. Power peaks with the predicted period are also obtained when the upper
and lower halves of the redshift distribution are examined separately. The
periodicity detected is in linear z, as opposed to log(1+z). Because the peaks
in the SDSS quasar redshift distribution agree well with the preferred
redshifts predicted by the intrinsic redshift relation, we conclude that this
relation, and the peaks in the redshift distribution, likely both have the same
origin, and this may be intrinsic redshifts, or a common selection effect.
However, because of the way the intrinsic redshift relation was determined it
seems unlikely that one selection effect could have been responsible for both.Comment: 12 pages, 12 figure, accepted for publication in the Astrophysical
Journa
Analyzing the House Fly's Exploratory Behavior with Autoregression Methods
This paper presents a detailed characterization of the trajectory of a single
housefly with free range of a square cage. The trajectory of the fly was
recorded and transformed into a time series, which was fully analyzed using an
autoregressive model, which describes a stationary time series by a linear
regression of prior state values with the white noise. The main discovery was
that the fly switched styles of motion from a low dimensional regular pattern
to a higher dimensional disordered pattern. This discovered exploratory
behavior is, irrespective of the presence of food, characterized by anomalous
diffusion.Comment: 20 pages, 9 figures, 1 table, full pape
Economies of collaboration in build-to-model operations
This is the final version. Available from the publisher via the DOI in this record.The direct-from-model and tool-less manufacturing process of 3D printing (3DP) embodies a general-purpose technology, facilitating capacity sharing and outsourcing. Starting from a case study of a 3DP company (Shapeways) and a new market entrant (Panalpina), we develop dynamic practices for partial outsourcing in build-to-model manufacturing. We propose a new outsourcing scheme, bidirectional partial outsourcing (BPO), where 3D printers share capacity by alternating between the role of outsourcer and subcontractor based on need. Coupled with order book smoothing (OBS), where orders are released gradually to production, this provides 3D printers with two distinct ways to manage demand variability. By combining demand and cost field data with an analytical model, we find that BPO improves 3DP cost efficiency and delivery performance as the number of 3DP firms in the network increases. OBS is sufficient for an established 3D printer when alternatives to in-house manufacturing are few, or of limited capacity. Nevertheless, OBS comes at the cost of reduced responsiveness, whereas BPO shifts the cost and delivery performance frontier. Our analysis shows how BPO combined with OBS makes 3DP companies more resilient to downward movements in both demand and price levels.Innovate UKEngineering and Physical Sciences Research Council (EPSRC
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