Integration of BPM systems

New technologies have emerged to support the global economy where for instance suppliers, manufactures and retailers are working together in order to minimise the cost and maximise efficiency. One of the technologies that has become a buzz word for many businesses is business process management or BPM. A business process comprises activities and tasks, the resources required to perform each task, and the business rules linking these activities and tasks. The tasks may be performed by human and/or machine actors. Workflow provides a way of describing the order of execution and the dependent relationships between the constituting activities of short or long running processes. Workflow allows businesses to capture not only the information but also the processes that transform the information - the process asset (Koulopoulos, T. M., 1995). Applications which involve automated, human-centric and collaborative processes across organisations are inherently different from one organisation to another. Even within the same organisation but over time, applications are adapted as ongoing change to the business processes is seen as the norm in today’s dynamic business environment. The major difference lies in the specifics of business processes which are changing rapidly in order to match the way in which businesses operate. In this chapter we introduce and discuss Business Process Management (BPM) with a focus on the integration of heterogeneous BPM systems across multiple organisations. We identify the problems and the main challenges not only with regards to technologies but also in the social and cultural context. We also discuss the issues that have arisen in our bid to find the solutions

When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment

Reinforcement learning (RL) algorithms face two distinct challenges: learning effective representations of past and present observations, and determining how actions influence future returns. Both challenges involve modeling long-term dependencies. The transformer architecture has been very successful to solve problems that involve long-term dependencies, including in the RL domain. However, the underlying reason for the strong performance of Transformer-based RL methods remains unclear: is it because they learn effective memory, or because they perform effective credit assignment? After introducing formal definitions of memory length and credit assignment length, we design simple configurable tasks to measure these distinct quantities. Our empirical results reveal that Transformers can enhance the memory capacity of RL algorithms, scaling up to tasks that require memorizing observations $1500$ steps ago. However, Transformers do not improve long-term credit assignment. In summary, our results provide an explanation for the success of Transformers in RL, while also highlighting an important area for future research and benchmark design

Analysis of two-point statistics of cosmic shear: III. Covariances of shear measures made easy

In recent years cosmic shear, the weak gravitational lensing effect by the large-scale structure of the Universe, has proven to be one of the observational pillars on which the cosmological concordance model is founded. Several cosmic shear statistics have been developed in order to analyze data from surveys. For the covariances of the prevalent second-order measures we present simple and handy formulae, valid under the assumptions of Gaussian density fluctuations and a simple survey geometry. We also formulate these results in the context of shear tomography, i.e. the inclusion of redshift information, and generalize them to arbitrary data field geometries. We define estimators for the E- and B-mode projected power spectra and show them to be unbiased in the case of Gaussianity and a simple survey geometry. From the covariance of these estimators we demonstrate how to derive covariances of arbitrary combinations of second-order cosmic shear measures. We then recalculate the power spectrum covariance for general survey geometries and examine the bias thereby introduced on the estimators for exemplary configurations. Our results for the covariances are considerably simpler than and analytically shown to be equivalent to the real-space approach presented in the first paper of this series. We find good agreement with other numerical evaluations and confirm the general properties of the covariance matrices. The studies of the specific survey configurations suggest that our simplified covariances may be employed for realistic survey geometries to good approximation.Comment: 15 pages, including 4 figures (Fig. 3 reduced in quality); minor changes, Fig. 4 extended; published in A&

Cosmological constraints from the capture of non-Gaussianity in Weak Lensing data

Weak gravitational lensing has become a common tool to constrain the cosmological model. The majority of the methods to derive constraints on cosmological parameters use second-order statistics of the cosmic shear. Despite their success, second-order statistics are not optimal and degeneracies between some parameters remain. Tighter constraints can be obtained if second-order statistics are combined with a statistic that is efficient to capture non-Gaussianity. In this paper, we search for such a statistical tool and we show that there is additional information to be extracted from statistical analysis of the convergence maps beyond what can be obtained from statistical analysis of the shear field. For this purpose, we have carried out a large number of cosmological simulations along the {\sigma}8-{\Omega}m degeneracy, and we have considered three different statistics commonly used for non-Gaussian features characterization: skewness, kurtosis and peak count. To be able to investigate non-Gaussianity directly in the shear field we have used the aperture mass definition of these three statistics for different scales. Then, the results have been compared with the results obtained with the same statistics estimated in the convergence maps at the same scales. First, we show that shear statistics give similar constraints to those given by convergence statistics, if the same scale is considered. In addition, we find that the peak count statistic is the best to capture non-Gaussianities in the weak lensing field and to break the {\sigma}8-{\Omega}m degeneracy. We show that this statistical analysis should be conducted in the convergence maps: first, because there exist fast algorithms to compute the convergence map for different scales, and secondly because it offers the opportunity to denoise the reconstructed convergence map, which improves non-Gaussian features extraction.Comment: Accepted for publication in MNRAS (11 pages, 5 figures, 9 tables

A companion to a quasar at redshift 4.7

There is a growing consensus that the emergence of quasars at high redshifts is related to the onset of galaxy formation, suggesting that the detection of concentrations of gas accompanying such quasars should provide clues about the early history of galaxies. Quasar companions have been recently identified at redshifts up to $z \approx 3$. Here we report observations of Lyman-$\alpha$ emission (a tracer of ionised hydrogen) from the companion to a quasar at $z$=4.702, corresponding to a time when the Universe was less than ten per cent of its present age. We argue that most of the emission arises in a gaseous nebula that has been photoionised by the quasar, but an additional component of continuum light -perhaps quasar light scattered from dust in the companion body, or emission from young stars within the nebula- appears necessary to explain the observations. These observations may be indicative of the first stages in the assembly of galaxy-sized structures.Comment: 8 pages, 4 figures, plain LaTeX. Accepted for publication in Natur

Self calibration of photometric redshift scatter in weak lensing surveys

Photo-z errors, especially catastrophic errors, are a major uncertainty for precision weak lensing cosmology. We find that the shear-(galaxy number) density and density-density cross correlation measurements between photo-z bins, available from the same lensing surveys, contain valuable information for self-calibration of the scattering probabilities between the true-z and photo-z bins. The self-calibration technique we propose does not rely on cosmological priors nor parameterization of the photo-z probability distribution function, and preserves all of the cosmological information available from shear-shear measurement. We estimate the calibration accuracy through the Fisher matrix formalism. We find that, for advanced lensing surveys such as the planned stage IV surveys, the rate of photo-z outliers can be determined with statistical uncertainties of 0.01-1% for $z<2$ galaxies. Among the several sources of calibration error that we identify and investigate, the {\it galaxy distribution bias} is likely the most dominant systematic error, whereby photo-z outliers have different redshift distributions and/or bias than non-outliers from the same bin. This bias affects all photo-z calibration techniques based on correlation measurements. Galaxy bias variations of $O(0.1)$ produce biases in photo-z outlier rates similar to the statistical errors of our method, so this galaxy distribution bias may bias the reconstructed scatters at several-$\sigma$ level, but is unlikely to completely invalidate the self-calibration technique.Comment: v2: 19 pages, 10 figures. Added one figure. Expanded discussions. Accepted to MNRA

Optimising cosmic shear surveys to measure modifications to gravity on cosmic scales

We consider how upcoming photometric large scale structure surveys can be optimized to measure the properties of dark energy and possible cosmic scale modifications to General Relativity in light of realistic astrophysical and instrumental systematic uncertainities. In particular we include flexible descriptions of intrinsic alignments, galaxy bias and photometric redshift uncertainties in a Fisher Matrix analysis of shear, position and position-shear correlations, including complementary cosmological constraints from the CMB. We study the impact of survey tradeoffs in depth versus breadth, and redshift quality. We parameterise the results in terms of the Dark Energy Task Force figure of merit, and deviations from General Relativity through an analagous Modified Gravity figure of merit. We find that intrinsic alignments weaken the dependence of figure of merit on area and that, for a fixed observing time, a fiducial Stage IV survey plateaus above roughly 10,000deg2 for DE and peaks at about 5,000deg2 as the relative importance of IAs at low redshift penalises wide, shallow surveys. While reducing photometric redshift scatter improves constraining power, the dependence is shallow. The variation in constraining power is stronger once IAs are included and is slightly more pronounced for MG constraints than for DE. The inclusion of intrinsic alignments and galaxy position information reduces the required prior on photometric redshift accuracy by an order of magnitude for both the fiducial Stage III and IV surveys, equivalent to a factor of 100 reduction in the number of spectroscopic galaxies required to calibrate the photometric sample.Comment: 13 pages, 6 figures. Fixed an error in equation 19 which changes the right hand panels of figures 1 and 2, and modifies conclusions on the results for fixed observing tim