Resummation of Singlet Parton Evolution at Small x

We propose an improvement of the splitting functions at small x which overcomes the apparent problems encountered by the BFKL approach. We obtain a stable expansion for the x-evolution function chi(M) near M=0 by including in it a sequence of terms derived from the one- and two-loop anomalous dimension gamma. The requirement of momentum conservation is always satisfied. The residual ambiguity on the splitting functions is effectively parameterized in terms of the value of lambda, which fixes the small x asymptotic behaviour x^-lambda of the singlet parton distributions. We derive from this improved evolution function an expansion of the splitting function which leads to good apparent convergence, and to a description of scaling violations valid both at large and small x.Comment: 16 pages, 6 figures, LaTeX with epsfig; final version, to be published in Nucl. Phys. B. A few typos corrected for the recor

Small x Resummation with Quarks: Deep-Inelastic Scattering

We extend our previous results on small-x resummation in the pure Yang--Mills theory to full QCD with nf quark flavours, with a resummed two-by-two matrix of resummed quark and gluon splitting functions. We also construct the corresponding deep-inelastic coefficient functions, and show how these can be combined with parton densities to give fully resummed deep-inelastic structure functions F_2 and F_L at the next-to-leading logarithmic level. We discuss how this resummation can be performed in different factorization schemes, including the commonly used MSbar scheme. We study the importance of the resummation effects by comparison with fixed-order perturbative results, and we discuss the corresponding renormalization and factorization scale variation uncertainties. We find that for x below 0.01 the resummation effects are comparable in size to the fixed order NNLO corrections, but differ in shape. We finally discuss the phenomenological impact of the small-x resummation, specifically in the extraction of parton distribution from present day experiments and their extrapolation to the kinematics relevant for future colliders such as the LHCComment: 45 pages, 16 figures, plain TeX with harvma

An anomalous dimension for small x evolution

We construct an anomalous dimension for small x evolution which goes beyond standard fixed order perturbative evolution by including resummed small x logarithms deduced from the leading order BFKL equation with running coupling. Surprisingly, we find that once running coupling effects are properly taken into account, the leading approximation is very close to standard perturbative evolution in the range of x accessible at HERA, in overall agreement with the data, with no need for phenomenological parameters to summarise subleading effects. We also show that further corrections due to subleading small x logarithms derived from the Fadin-Lipatov kernel can be kept under control, but that they involve substantial resummation ambiguities which limit their practical usefulness.Comment: 25 pages, 8 figures, plain TeX with harvmac; minor errors in the text correcte

Small-x Resummation and HERA Structure Function Data

We apply our systematic NLO small x resummation of singlet splitting functions to the scaling violations of structure functions and compare the results with data. We develop various theoretical tools which are needed in order to relate resummed parton distributions to measurable structure functions, and we present results from a variety of fits to HERA data for the structure functions F_2 and F_L using the resummation. The behaviour of the singlet splitting functions at small x and fixed Q^2 is effectively parametrized as x^{-lambda}. We find that, for lambda small or negative, the resummed description of scaling violations may be phenomenologically as good as or even better than the standard next-to-leading order treatment. However, the best fit gluon density and value of alpha_s can be significantly modified by the resummation.Comment: 40 pages, 15 figures. Final version, to be published in Nucl. Phys. B. Typos corrected in eq. 4.5 and eq. 4.20 and in caption to fig.

Advanced Data Chain Technologies for the Next Generation of Earth Observation Satellites Supporting On-Board Processing for Rapid Civil Alerts

The growing number of planned Earth Observation (EO) satellites, together with the increase in payload resolution and swath, brings to the fore the generation of unprecedented volumes of data that needs to be downloaded, processed and distributed with low latency. This creates a severe bottleneck problem, which overloads ground infrastructure, communications to ground, and hampers the provision of EO products to the End User with the required performances. The European H2020 EO-ALERT project (http://eo-alert-h2020.eu/), proposes the definition of next-generation EO missions by developing an on-board high speed EO data processing chain, based on a novel flight segment architecture that moves optimised key EO data processing elements from the ground segment to on-board the satellite. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, reaching latencies below 1 minute in some scenarios. The proposed architecture solves the above challenges through a combination of innovations in the on-board elements of the data chain and the communications link. Namely, the architecture introduces innovative technological solutions, including on-board reconfigurable data handling, on-board image generation and processing for generation of alerts (EO products) using Artificial Intelligence (AI), high-speed on-board avionics, on-board data compression and encryption using AI and reconfigurable high data rate communication links to ground including a separate chain for alerts with minimum latency and global coverage. Those key technologies have been studied, developed, implemented in software/hardware (SW/HW) and verified against previously established technologies requirements to meet the identified user needs. The paper presents an overview of the development of the innovative solutions defined during the project for each of the above mentioned technological areas and the results of the testing campaign of the individual SW/HW implementations within the context of two operational scenarios: ship detection and extreme weather observation (nowcasting), both requiring a high responsiveness to events to reduce the response time to few hours, or even to minutes, after an emergency situation arises. The technologies have been experimentally evaluated during the project using relevant EO historical sensor data. The results demonstrate the maturity of the technologies, having now reached TRL 4-5. Generally, the results show that, when implemented using COTS components and available communication links, the proposed architecture can generate and delivery globally EO products/alerts with a latency lower than five minutes, which demonstrates the viability of the EO-ALERT concept. The paper also discusses the implementation on an Avionic Test Bench (ATB) for the validation of the integrated technologies chain

Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio

A Novel Architecture for the Next Generation of Earth Observation Satellites Supporting Rapid Civil Alert

The EO-ALERT European Commission H2020 project proposes the definition, development, and verification and validation through ground hardware testing, of a next-generation Earth Observation (EO) data processing chain. The proposed data processing chain is based on a novel flight segment architecture that moves EO data processing elements traditionally executed in the ground segment to on-board the satellite, with the aim of delivering EO products to the end user with very low latency. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, and below one minute in realistic scenarios. The proposed EO-ALERT architecture is enabled by on-board processing, recent improvements in processing hardware using Commercial Off-The-Shelf (COTS) components, and persistent space-to-ground communications links. EO-ALERT combines innovations in the on-board elements of the data chain and the communications, namely: on-board reconfigurable data handling, on-board image generation and processing for the generation of alerts (EO products) using Machine Learning (ML) and Artificial Intelligence (AI), on-board AI-based compression and encryption, high-speed on-board avionics, and reconfigurable high data rate communication links to ground, including a separate chain for alerts with minimum latency and global coverage. This paper presents the proposed architecture, its hardware realization for the ground testing in a representative environment and its performance. The architecture’s performance is evaluated considering two different user scenarios where very low latency (almost-real-time) EO product delivery is required: ship detection and extreme weather monitoring/nowcasting. The hardware testing results show that, when implemented using COTS components and available communication links, the proposed architecture can deliver alerts to the end user with a latency below five minutes, for both SAR and Optical missions, demonstrating the viability of the EO-ALERT architecture. In particular, in several test scenarios, for both the TerraSAR-X SAR and DEIMOS-2 Optical Very High Resolution (VHR) missions, hardware testing of the proposed architecture has shown it can deliver EO products and alerts to the end user globally, with latency lower than one-point-five minutes