Maximum Coronal Mass Ejection Speed as an Indicator of Solar and Geomagnetic Activities

We investigate the relationship between the monthly averaged maximal speeds of coronal mass ejections (CMEs), international sunspot number (ISSN), and the geomagnetic Dst and Ap indices covering the 1996-2008 time interval (solar cycle 23). Our new findings are as follows. (1) There is a noteworthy relationship between monthly averaged maximum CME speeds and sunspot numbers, Ap and Dst indices. Various peculiarities in the monthly Dst index are correlated better with the fine structures in the CME speed profile than that in the ISSN data. (2) Unlike the sunspot numbers, the CME speed index does not exhibit a double peak maximum. Instead, the CME speed profile peaks during the declining phase of solar cycle 23. Similar to the Ap index, both CME speed and the Dst indices lag behind the sunspot numbers by several months. (3) The CME number shows a double peak similar to that seen in the sunspot numbers. The CME occurrence rate remained very high even near the minimum of the solar cycle 23, when both the sunspot number and the CME average maximum speed were reaching their minimum values. (4) A well-defined peak of the Ap index between 2002 May and 2004 August was co-temporal with the excess of the mid-latitude coronal holes during solar cycle 23. The above findings suggest that the CME speed index may be a useful indicator of both solar and geomagnetic activities. It may have advantages over the sunspot numbers, because it better reflects the intensity of Earth-directed solar eruptions

Modeling and Optimization of Lactic Acid Synthesis by the Alkaline Degradation of Fructose in a Batch Reactor

The present work deals with the determination of the optimal operating conditions of lactic acid synthesis by the alkaline degradation of fructose. It is a complex transformation for which detailed knowledge is not available. It is carried out in a batch or semi-batch reactor. The ‘‘Tendency Modeling’’ approach, which consists of the development of an approximate stoichiometric and kinetic model, has been used. An experimental planning method has been utilized as the database for model development. The application of the experimental planning methodology allows comparison between the experimental and model response. The model is then used in an optimization procedure to compute the optimal process. The optimal control problem is converted into a nonlinear programming problem solved using the sequencial quadratic programming procedure coupled with the golden search method. The strategy developed allows simultaneously optimizing the different variables, which may be constrained. The validity of the methodology is illustrated by the determination of the optimal operating conditions of lactic acid production

Information theoretic approach to interactive learning

The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.Comment: 6 page

Quantum trajectories for the realistic measurement of a solid-state charge qubit

We present a new model for the continuous measurement of a coupled quantum dot charge qubit. We model the effects of a realistic measurement, namely adding noise to, and filtering, the current through the detector. This is achieved by embedding the detector in an equivalent circuit for measurement. Our aim is to describe the evolution of the qubit state conditioned on the macroscopic output of the external circuit. We achieve this by generalizing a recently developed quantum trajectory theory for realistic photodetectors [P. Warszawski, H. M. Wiseman and H. Mabuchi, Phys. Rev. A_65_ 023802 (2002)] to treat solid-state detectors. This yields stochastic equations whose (numerical) solutions are the ``realistic quantum trajectories'' of the conditioned qubit state. We derive our general theory in the context of a low transparency quantum point contact. Areas of application for our theory and its relation to previous work are discussed.Comment: 7 pages, 2 figures. Shorter, significantly modified, updated versio

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

Stochastic simulations of conditional states of partially observed systems, quantum and classical

In a partially observed quantum or classical system the information that we cannot access results in our description of the system becoming mixed even if we have perfect initial knowledge. That is, if the system is quantum the conditional state will be given by a state matrix $\rho_r(t)$ and if classical the conditional state will be given by a probability distribution $P_r(x,t)$ where $r$ is the result of the measurement. Thus to determine the evolution of this conditional state under continuous-in-time monitoring requires an expensive numerical calculation. In this paper we demonstrating a numerical technique based on linear measurement theory that allows us to determine the conditional state using only pure states. That is, our technique reduces the problem size by a factor of $N$, the number of basis states for the system. Furthermore we show that our method can be applied to joint classical and quantum systems as arises in modeling realistic measurement.Comment: 16 pages, 11 figure

Response to novel objects and foraging tasks by common marmoset (Callithrix Jacchus) female Pairs

Many studies have shown that environmental enrichment can significantly improve the psychological well-being of captive primates, increasing the occurrence of explorative behavior and thus reducing boredom. The response of primates to enrichment devices may be affected by many factors such as species, sex, age, personality and social context. Environmental enrichment is particularly important for social primates living in unnatural social groupings (i.e. same-sex pairs or singly housed animals), who have very few, or no, benefits from the presence of social companions in addition to all the problems related to captivity (e.g. increased inactivity). This study analyses the effects of enrichment devices (i.e. novel objects and foraging tasks) on the behavior of common marmoset (Callithrix jacchus) female pairs, a species that usually lives in family groups. It aims to determine which aspects of an enrichment device are more likely to elicit explorative behaviors, and how aggressive and stress-related behaviors are affected by its presence. Overall, the marmosets explored foraging tasks significantly longer than novel objects. The type of object, which varied in size, shape and aural responsiveness (i.e. they made a noise when the monkey touched them), did not affect the response of the monkeys, but they explored objects that were placed higher in the enclosure more than those placed lower down.Younger monkeys were more attracted to the enrichment devices than the older ones. Finally, stress-related behavior (i.e. scratching) significantly decreased when the monkeys were presented with the objects; aggressive behavior as unaffected. This study supports the importance of environmental enrichment for captive primates and shows that in marmosets its effectiveness strongly depends upon the height of the device in the enclosure and the presence of hidden food. The findings can be explained ifone considers the foraging behavior of wild common marmosets. Broader applications for the research findings are suggested in relation to enrichment

A Random Matrix Approach to VARMA Processes

We apply random matrix theory to derive spectral density of large sample covariance matrices generated by multivariate VMA(q), VAR(q) and VARMA(q1,q2) processes. In particular, we consider a limit where the number of random variables N and the number of consecutive time measurements T are large but the ratio N/T is fixed. In this regime the underlying random matrices are asymptotically equivalent to Free Random Variables (FRV). We apply the FRV calculus to calculate the eigenvalue density of the sample covariance for several VARMA-type processes. We explicitly solve the VARMA(1,1) case and demonstrate a perfect agreement between the analytical result and the spectra obtained by Monte Carlo simulations. The proposed method is purely algebraic and can be easily generalized to q1>1 and q2>1.Comment: 16 pages, 6 figures, submitted to New Journal of Physic

Gas and dust in the Beta Pictoris Moving Group as seen by the Herschel Space Observatory

Context. Debris discs are thought to be formed through the collisional grinding of planetesimals, and can be considered as the outcome of planet formation. Understanding the properties of gas and dust in debris discs can help us to comprehend the architecture of extrasolar planetary systems. Herschel Space Observatory far-infrared (IR) photometry and spectroscopy have provided a valuable dataset for the study of debris discs gas and dust composition. This paper is part of a series of papers devoted to the study of Herschel PACS observations of young stellar associations. Aims. This work aims at studying the properties of discs in the Beta Pictoris Moving Group (BPMG) through far-IR PACS observations of dust and gas. Methods. We obtained Herschel-PACS far-IR photometric observations at 70, 100 and 160 microns of 19 BPMG members, together with spectroscopic observations of four of them. Spectroscopic observations were centred at 63.18 microns and 157 microns, aiming to detect [OI] and [CII] emission. We incorporated the new far-IR observations in the SED of BPMG members and fitted modified blackbody models to better characterise the dust content. Results. We have detected far-IR excess emission toward nine BPMG members, including the first detection of an IR excess toward HD 29391.The star HD 172555, shows [OI] emission, while HD 181296, shows [CII] emission, expanding the short list of debris discs with a gas detection. No debris disc in BPMG is detected in both [OI] and [CII]. The discs show dust temperatures in the range 55 to 264 K, with low dust masses (6.6*10^{-5} MEarth to 0.2 MEarth) and radii from blackbody models in the range 3 to 82 AU. All the objects with a gas detection are early spectral type stars with a hot dust component.Comment: 12 pages, 7 figures, 6 table

State and dynamical parameter estimation for open quantum systems

Following the evolution of an open quantum system requires full knowledge of its dynamics. In this paper we consider open quantum systems for which the Hamiltonian is ``uncertain''. In particular, we treat in detail a simple system similar to that considered by Mabuchi [Quant. Semiclass. Opt. 8, 1103 (1996)]: a radiatively damped atom driven by an unknown Rabi frequency $\Omega$ (as would occur for an atom at an unknown point in a standing light wave). By measuring the environment of the system, knowledge about the system state, and about the uncertain dynamical parameter, can be acquired. We find that these two sorts of knowledge acquisition (quantified by the posterior distribution for $\Omega$, and the conditional purity of the system, respectively) are quite distinct processes, which are not strongly correlated. Also, the quality and quantity of knowledge gain depend strongly on the type of monitoring scheme. We compare five different detection schemes (direct, adaptive, homodyne of the $x$ quadrature, homodyne of the $y$ quadrature, and heterodyne) using four different measures of the knowledge gain (Shannon information about $\Omega$, variance in $\Omega$, long-time system purity, and short-time system purity).Comment: 14 pages, 18 figure