Soft Pomerons and the Forward LHC Data

Recent data from LHC13 by the TOTEM Collaboration on $\sigma_{tot}$ and $\rho$ have indicated disagreement with all the Pomeron model predictions by the COMPETE Collaboration (2002). On the other hand, as recently demonstrated by Martynov and Nicolescu (MN), the new $\sigma_{tot}$ datum and the unexpected decrease in the $\rho$ value are well described by the maximal Odderon dominance at the highest energies. Here, we discuss the applicability of Pomeron dominance through fits to the \textit{most complete set} of forward data from $pp$ and $\bar{p}p$ scattering. We consider an analytic parametrization for $\sigma_{tot}(s)$ consisting of non-degenerated Regge trajectories for even and odd amplitudes (as in the MN analysis) and two Pomeron components associated with double and triple poles in the complex angular momentum plane. The $\rho$ parameter is analytically determined by means of dispersion relations. We carry out fits to $pp$ and $\bar{p}p$ data on $\sigma_{tot}$ and $\rho$ in the interval 5 GeV - 13 TeV (as in the MN analysis). Two novel aspects of our analysis are: (1) the dataset comprises all the accelerator data below 7 TeV and we consider \textit{three independent ensembles} by adding: either only the TOTEM data (as in the MN analysis), or only the ATLAS data, or both sets; (2) in the data reductions to each ensemble, uncertainty regions are evaluated through error propagation from the fit parameters, with 90 \% CL. We argument that, within the uncertainties, this analytic model corresponding to soft Pomeron dominance, does not seem to be excluded by the \textit{complete} set of experimental data presently available.Comment: 10 pages, 4 figures, 1 table. Two paragraphs and four references added. Accepted for publication in Phys. Lett.

Soft Methodology for Cost-and-error Sensitive Classification

Many real-world data mining applications need varying cost for different types of classification errors and thus call for cost-sensitive classification algorithms. Existing algorithms for cost-sensitive classification are successful in terms of minimizing the cost, but can result in a high error rate as the trade-off. The high error rate holds back the practical use of those algorithms. In this paper, we propose a novel cost-sensitive classification methodology that takes both the cost and the error rate into account. The methodology, called soft cost-sensitive classification, is established from a multicriteria optimization problem of the cost and the error rate, and can be viewed as regularizing cost-sensitive classification with the error rate. The simple methodology allows immediate improvements of existing cost-sensitive classification algorithms. Experiments on the benchmark and the real-world data sets show that our proposed methodology indeed achieves lower test error rates and similar (sometimes lower) test costs than existing cost-sensitive classification algorithms. We also demonstrate that the methodology can be extended for considering the weighted error rate instead of the original error rate. This extension is useful for tackling unbalanced classification problems.Comment: A shorter version appeared in KDD '1

Supersymmetry Without Prejudice at the LHC

The discovery and exploration of Supersymmetry in a model-independent fashion will be a daunting task due to the large number of soft-breaking parameters in the MSSM. In this paper, we explore the capability of the ATLAS detector at the LHC ($\sqrt s=14$ TeV, 1 fb$^{-1}$) to find SUSY within the 19-dimensional pMSSM subspace of the MSSM using their standard transverse missing energy and long-lived particle searches that were essentially designed for mSUGRA. To this end, we employ a set of $\sim 71$k previously generated model points in the 19-dimensional parameter space that satisfy all of the existing experimental and theoretical constraints. Employing ATLAS-generated SM backgrounds and following their approach in each of 11 missing energy analyses as closely as possible, we explore all of these $71$k model points for a possible SUSY signal. To test our analysis procedure, we first verify that we faithfully reproduce the published ATLAS results for the signal distributions for their benchmark mSUGRA model points. We then show that, requiring all sparticle masses to lie below 1(3) TeV, almost all(two-thirds) of the pMSSM model points are discovered with a significance $S>5$ in at least one of these 11 analyses assuming a 50\% systematic error on the SM background. If this systematic error can be reduced to only 20\% then this parameter space coverage is increased. These results are indicative that the ATLAS SUSY search strategy is robust under a broad class of Supersymmetric models. We then explore in detail the properties of the kinematically accessible model points which remain unobservable by these search analyses in order to ascertain problematic cases which may arise in general SUSY searches.Comment: 69 pages, 40 figures, Discussion adde

Robust predictions for an oscillatory bispectrum in Planck 2015 data from transient reductions in the speed of sound of the inflaton

We update the search for features in the Cosmic Microwave Background (CMB) power spectrum due to transient reductions in the speed of sound, using Planck 2015 CMB temperature and polarisation data. We enlarge the parameter space to much higher oscillatory frequencies of the feature, and define a robust prior independent of the ansatz for the reduction, guaranteed to reproduce the assumptions of the theoretical model and exhaustive in the regime in which the feature is easily distinguishable from the baseline cosmology. We find a fit to the $\ell\approx20$--$40$ minus/plus structure in Planck TT power spectrum, as well as features spanning along the higher $\ell$'s ($\ell\approx100$--$1500$). For the last ones, we compute the correlated features that we expect to find in the CMB bispectrum, and asses their signal-to-noise and correlation to the ISW-lensing secondary bispectrum. We compare our findings to the shape-agnostic oscillatory template tested in Planck 2015, and we comment on some tantalising coincidences with some of the traits described in Planck's 2015 bispectrum data.Comment: 19 pages - matches published versio

Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking

Bipartite ranking is a fundamental ranking problem that learns to order relevant instances ahead of irrelevant ones. The pair-wise approach for bi-partite ranking construct a quadratic number of pairs to solve the problem, which is infeasible for large-scale data sets. The point-wise approach, albeit more efficient, often results in inferior performance. That is, it is difficult to conduct bipartite ranking accurately and efficiently at the same time. In this paper, we develop a novel active sampling scheme within the pair-wise approach to conduct bipartite ranking efficiently. The scheme is inspired from active learning and can reach a competitive ranking performance while focusing only on a small subset of the many pairs during training. Moreover, we propose a general Combined Ranking and Classification (CRC) framework to accurately conduct bipartite ranking. The framework unifies point-wise and pair-wise approaches and is simply based on the idea of treating each instance point as a pseudo-pair. Experiments on 14 real-word large-scale data sets demonstrate that the proposed algorithm of Active Sampling within CRC, when coupled with a linear Support Vector Machine, usually outperforms state-of-the-art point-wise and pair-wise ranking approaches in terms of both accuracy and efficiency.Comment: a shorter version was presented in ACML 201

Supersymmetry Without Prejudice at the 7 TeV LHC

We investigate the model independent nature of the Supersymmetry search strategies at the 7 TeV LHC. To this end, we study the missing-transverse-energy-based searches developed by the ATLAS Collaboration that were essentially designed for mSUGRA. We simulate the signals for ~71k models in the 19-dimensional parameter space of the pMSSM. These models have been found to satisfy existing experimental and theoretical constraints and provide insight into general features of the MSSM without reference to a particular SUSY breaking scenario or any other assumptions at the GUT scale. Using backgrounds generated by ATLAS, we find that imprecise knowledge of these estimated backgrounds is a limiting factor in the potential discovery of these models and that some channels become systematics-limited at larger luminosities. As this systematic error is varied between 20-100%, roughly half to 90% of this model sample is observable with significance S>5 for 1 fb^{-1} of integrated luminosity. We then examine the model characteristics for the cases which cannot be discovered and find several contributing factors. We find that a blanket statement that squarks and gluinos are excluded with masses below a specific value cannot be made. We next explore possible modifications to the kinematic cuts in these analyses that may improve the pMSSM model coverage. Lastly, we examine the implications of a null search at the 7 TeV LHC in terms of the degree of fine-tuning that would be present in this model set and for sparticle production at the 500 GeV and 1 TeV Linear Collider.Comment: 51 pages, 26 figure

Uncertainty propagation and speculation in projective forecasts of environmental change: a lake-eutrophication example

The issue of whether models developed for current conditions can yield correct predictions when used under changed control, as is often the case in environmental management, is discussed. Two models of different complexity are compared on the basis of performance criteria, but it appears that good performance at the calibration stage does not guarantee correctly predicted behavior. A requirement for the detection of such a failure of the model is that the prediction uncertainty range is known. Two techniques to calculate uncertainty propagation are presented and compared: a stochastic first-order error propagation based on the extended Kalman filter (EKF), and a newly developed and robust Monte Carlo set-membership procedure (MCSM). The procedures are applied to a case study of water quality, generating a projective forecast of the algal dynamics in a lake (Lake Veluwe) in response to management actions that force the system into a different mode of behavior. It is found that the forecast from the more complex model falls within the prediction uncertainty range, but its informative value is low due to large uncertainty bounds. As a substitute for time-consuming revisions of the model, educated speculation about parameter shifts is offered as an alternative approach to account for expected but unmodelled changes in the system

The ASCA X-Ray Spectrum Of The Broad-Line Radio Galaxy Pictor A: A Simple Power Law With No Fe K-alpha Line

We present the X-ray spectrum of the broad-line radio galaxy Pictor A as observed by ASCA in 1996. The main objective of the observation was to detect and study the profiles of the Fe~K$\alpha$ lines. The motivation was the fact that the Balmer lines of this object show well-separated displaced peaks, suggesting an origin in an accretion disk. The 0.5-10 keV X-ray spectrum is described very well by a model consisting of a power law of photon index 1.77 modified by interstellar photoelectric absorption. We find evidence for neither a soft nor a hard (Compton reflection) excess. More importantly, we do not detect an Fe K-alpha line, in marked contrast with the spectra of typical Seyfert galaxies and other broad-line radio galaxies observed by ASCA. The 99%-confidence upper limit on the equivalent width of an unresolved line at a rest energy of 6.4 keV is 100 eV, while for a broad line (FWHM of approximately 60,000 km/s) the corresponding upper limit is 135 eV. We discuss several possible explanations for the weakness of the Fe K-alpha line in Pictor~A paying attention to the currently available data on the properties of Fe K-alpha lines in other broad-line radio galaxies observed by ASCA. We speculate that the absence of a hard excess (Compton reflection) or an Fe K-alpha line is an indication of an accretion disk structure that is different from that of typical Seyfert galaxies, e.g., the inner disk may be an ion torus.Comment: To appear in the Astrophysical Journal (18 pages, including 8 postscript figures; uses psfig.tex