LHC-ILC synergy

I will begin by making a few general comments on the synergy between the Large Hadron Collider (LHC) which will go in action in 2007 and the International Linear Collider (ILC) which is under planning. I will then focus on the synergy between the LHC and the PLC option at the ILC, which is expected to be realised in the later stages of the ILC program. In this I will cover the possible synergy in the Higgs sector (with and without CP violation), in the determination of the anomalous vector boson couplings and last but not the least, in the search for extra dimensions and radions.Comment: 12 pages,8 figures, uses appolb.cls, talk presented at the PLC2005 workshop, Kazimierz, Poland, 5-8 September, to appear in Acta Physics Polonic

The principles of integration in urban transport strategies

Integration as a principle in urban transport policy is frequently advocated but rarely defined. We suggest a range of types of integration, and highlight the problems in developing an effective integrated strategy, given the number of variables involved. We argue that integration should be designed to serve agreed objectives of transport policy, rather than being an objective in its own right. We then consider the principles for designing an effective integrated strategy. We define the concept of synergy, which is often advocated as a benefit of integration, and discuss whether it, and other aggregation benefits short of true synergy, are achievable. We then consider the alternative approach of using integration to overcome barriers, an approach which is likely to be in conflict with pursuit of synergy, but more likely to lead to readily implemented strategies. We then review a number of examples where these principles have been applied, and investigate them to assess whether synergy has been demonstrated. Generally we find little evidence of synergy in outcome indicators. We conclude with some more general guidance on approaches to integration

The Gaia-LSST Synergy

We discuss the synergy of Gaia and the Large Synoptic Survey Telescope (LSST) in the context of Milky Way studies. LSST can be thought of as Gaia's deep complement because the two surveys will deliver trigonometric parallax, proper-motion, and photometric measurements with similar uncertainties at Gaia's faint end at $r=20$, and LSST will extend these measurements to a limit about five magnitudes fainter. We also point out that users of Gaia data will have developed data analysis skills required to benefit from LSST data, and provide detailed information about how international participants can join LSST.Comment: Presented at "The Milky Way Unravelled by Gaia", Barcelona, Dec 1-5, 2014; 7 pages, 1 color figur

Disentangled Representations via Synergy Minimization

Scientists often seek simplified representations of complex systems to facilitate prediction and understanding. If the factors comprising a representation allow us to make accurate predictions about our system, but obscuring any subset of the factors destroys our ability to make predictions, we say that the representation exhibits informational synergy. We argue that synergy is an undesirable feature in learned representations and that explicitly minimizing synergy can help disentangle the true factors of variation underlying data. We explore different ways of quantifying synergy, deriving new closed-form expressions in some cases, and then show how to modify learning to produce representations that are minimally synergistic. We introduce a benchmark task to disentangle separate characters from images of words. We demonstrate that Minimally Synergistic (MinSyn) representations correctly disentangle characters while methods relying on statistical independence fail.Comment: 8 pages, 4 figures, 55th Annual Allerton Conference on Communication, Control, and Computing, 201

A methodology for assessing the effect of correlations among muscle synergy activations on task-discriminating information

Muscle synergies have been hypothesized to be the building blocks used by the central nervous system to generate movement. According to this hypothesis, the accomplishment of various motor tasks relies on the ability of the motor system to recruit a small set of synergies on a single-trial basis and combine them in a task-dependent manner. It is conceivable that this requires a fine tuning of the trial-to-trial relationships between the synergy activations. Here we develop an analytical methodology to address the nature and functional role of trial-to-trial correlations between synergy activations, which is designed to help to better understand how these correlations may contribute to generating appropriate motor behavior. The algorithm we propose first divides correlations between muscle synergies into types (noise correlations, quantifying the trial-to-trial covariations of synergy activations at fixed task, and signal correlations, quantifying the similarity of task tuning of the trial-averaged activation coefficients of different synergies), and then uses single-trial methods (task-decoding and information theory) to quantify their overall effect on the task-discriminating information carried by muscle synergy activations. We apply the method to both synchronous and time-varying synergies and exemplify it on electromyographic data recorded during performance of reaching movements in different directions. Our method reveals the robust presence of information-enhancing patterns of signal and noise correlations among pairs of synchronous synergies, and shows that they enhance by 9–15% (depending on the set of tasks) the task-discriminating information provided by the synergy decompositions. We suggest that the proposed methodology could be useful for assessing whether single-trial activations of one synergy depend on activations of other synergies and quantifying the effect of such dependences on the task-to-task differences in muscle activation patterns