bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cretan inscriptions to 400 bc
Authors: Probert Philomen 
Published: March 2015

AbstractChapter 13 considers relative clauses from Cretan alphabetic inscriptions up to the end of the fifth century BC. The relevant texts are all prescriptive, and inherently maximalizing relative clauses clearly predominate. Cretan inscriptions thus provide support for the impression gained in chapter 8, that Homer’s massive predominance of postnominal relative clauses does not extend to all varieties of early Greek. Once again the basic system is remarkably similar to that found in other types of text considered. Postnominal relative clauses are not simply interchangeable with inherently maximalizing constructions. The usual inherently maximalizing relative clause is the free relative clause. The authors of Cretan inscriptions did not, in general, take much care to make clear the syntactic role of a free relative clause. Relative-correlative sentences occasionally appear, however, when they are contrastive or (for ‘case hierarchy’ reasons) the role of a free relative clause would be difficult to work out.
Against four syntactic relics and for one
Authors: Probert Philomen 
Published: March 2015

AbstractChapter 14 returns to questions of linguistic history and prehistory. It begins with four syntactic phenomena sometimes considered relics from a stage before the development of Greek relative clauses as we know them: anaphoric hos, hē, ho; clause-final placement of postnominal relative clauses; verbless relative clauses; apodotic de. The chapter argues that none of these is actually such a relic, but that Greek relative clause syntax does include at least one genuine syntactic relic of an earlier stage: epic te. The earlier stage is, however, not a stage without relative clauses, but one in which relative clauses were necessarily already present. The chapter also makes the somewhat radical suggestion that one variety of early Greek relative clause may actually be a fairly recent development: the non-restrictive relative clause, which has often been taken to be the earliest Greek relative clause construction.
Optical lattice emulators
Authors: Duchon E. , Loh Y. L. , Trivedi N. 
Published: March 2015

Abstract
The equilibrium thermodynamics of bosons and fermions in optical lattices are considered in the single-band Hubbard regime, with an emphasis on interesting magnetic, superfluid, and spin liquid ground states. The parameters of the Hubbard model—the tunneling and interaction parameters—can be obtained quantitatively in terms of the strength and periodicity of the optical lattice potential, tuned by the laser intensity and wavelength. This direct link between the parameters of a theoretical model and the actual experimental optical lattice gives rise to the phase diagram of the Bose–Hubbard model. The definition of the order parameter as an expectation value of the annihilation operator in a coherent state is discussed. This phase-coherent superfluid state is contrasted with the phase-incoherent Mott state naturally defined in terms of number states. Following the repulsive Bose–Hubbard model, the phase diagram of the Fermi–Hubbard model is considered with both attractive and repulsive interactions.
Bose–Einstein condensation of magnons at room temperature
Authors: Dzyapko O. , Demidov V. E. , Demokritov S. O. , Melkov G. A. , Slavin A. N. 
Published: March 2015

Abstract
This chapter discusses the room-temperature kinetics and thermodynamics of the magnon gas in yttrium iron garnet films driven by a parametric microwave pumping. It shows that for high enough pumping powers, the thermalization of the driven gas results in a quasi-equilibrium state described by the Bose–Einstein statistics with a non-zero chemical potential. Further increase of the pumping power causes a Bose–Einstein condensation documented by an observation of the magnon accumulation at the lowest energy level. Using the sensitivity of the Brillouin light scattering spectroscopy to the coherence degree of the scattering magnons, the chapter demonstrates the spontaneous emergence of coherence of the magnons accumulated at the bottom of the spectrum, which occurs if their density exceeds a critical value.
Smoothers
Authors: Cosme E. 
Published: March 2015

AbstractThis chapter describes the use of smoothers in data assimilation. The filtering problem in data assimilation consists in estimating the state of a system based on past and present observations. In contrast to filters, amoothers implement Bayesian data assimilation using future observations. Smoothing problems can be posed in different ways. The main formulations in geophysics are fixed-point, fixed-interval, and fixed-lag smoothers. In this chapter, these problems are first introduced in a Bayesian framework, and the most straightforward Bayesian solutions are formulated. Common linear, Gaussian implementations, many of which are based on the classical Kalman filter, are then derived, followed by their ensemble counterparts, based on the usual ensemble Kalman filter techniques. Finally, the pros and cons, as well as the computational complexities, of all the schemes are discussed.
Observation impact on the short-range forecast
Authors: Cardinali C. 
Published: March 2015

Abstract
This chapter describes the concept of forecast error sensitivity to observations (FSO) and its use for diagnostic purposes. Assessment of the observational contribution to analysis and forecasting is among the most challenging aspects of diagnostics in data assimilation and numerical weather prediction. The FSO tool computes the contribution of all observations to the forecast error: a positive contribution is associated with an increase in forecast error and a negative contribution with a decrease. The technique is illustrated by an application to the weather prediction system of the European Centre for Medium-Range Weather Forecasts.
Particle filters for the geosciences
Authors: van Leeuwen P. J. 
Published: March 2015

Abstract
This chapter, compares results from the Canadian global ensemble Kalman filter (EnKF) with observations. This inevitably leads to discrepancies between the observed real atmosphere and its modelled equivalent. These discrepancies originate from system error. In a system simulation experiment, an attempt is made to obtain a coherent picture of the error evolution of a system. Errors can be due to things as different as an inappropriate closure assumption in a forecast model and inaccurate observations of surface pressure. This chapter, first describes Monte- Carlo methods in general to arrive at a definition of “‘system error”.‘. This is followed by an elimination procedure. First, medium-range ensemble forecasts are used to quantify the understanding of weaknesses of the forecast model. Subsequently, consideration turns to the data-assimilation context to see what additional error sources must be present. The chapter ends with some speculation on the types of errors that should be included.
Second-order methods for error propagation in variational data assimilation
Authors: Le Dimet F.-X. , Gejadze I. , Shutyaev V. 
Published: March 2015

AbstractThis chapter discusses the use of second-order methods for estimating error propagation in variational data assimilation. The basic variational approach to data assimilation exhibits the optimality system: it can be considered as a generalized model containing all the available information. To estimate the impact of errors due to the parameters of the model and/or to the observations, it is necessary to consider second-order properties. The variational approach can be used to estimate the propagation of uncertainties in the analysis. Two basic cases are considered. In the deterministic framework, the uncertainty is a virtual and deterministic perturbation on the model parameters, whose impact on some criterion is to be found. In the stochastic framework, the uncertainty is a random variable transported by the model as such. The output is a stochastic perturbation on the outputs of the analysis, for which it is necessary to determine its probabilistic characteristics.
Adjoints by automatic differentiation
Authors: Hascoët L. 
Published: March 2015

AbstractThis chapter describes how adjoint algorithms can be created by automatic differentiation (AD). Data assimilation makes intensive use of gradients. In many situations, the so-called adjoint approach is generally the most efficient way to compute gradients, by propagating derivatives backwards from the result of the given model or function. Writing an adjoint algorithm by hand is a complex, error-prone task. When the given model is provided in the form of a computer algorithm, AD can build its adjoint algorithm mechanically, for instance by program transformation. This chapter presents the principles of AD, focusing on the adjoint mode. It provides a brief panorama of existing AD tools, and the program analysis and compiler technology that they employ to produce efficient adjoint algorithms.
Assimilation of images
Authors: Vidard A. , Titaud O. 
Published: March 2015

Abstract
This chapter describes processes for direct assimilation of images. Among data available for assimilation, a significant portion can be considered as images or image sequences, i.e. structured and dense-in-space information. In meteorology, such observations are often obtained from spaceborne devices and are therefore expensive to acquire. Moreover, images contain information about system dynamics through the time evolution of a sequence or within the structures that are represented (fronts, filaments, etc.). Therefore, images are a valuable source of information. Historically, they have been assimilated by pseudo-observation, where part of the dynamical information is extracted by image processing techniques and then assimilated as conventional observations. This approach has proven quite effective, but the pre-processing renders error specification cumbersome and leads to loss of information. More recently, research has been carried out to assimilate images directly in the assimilation process; two of these proposed approaches are presented and discussed in this chapter.
Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation
Authors: Debreu L. , Neveu E. , Simon E. , Le Dimet F.-X. 
Published: March 2015

AbstractThis chapter looks at the use of multigrid methods and local mesh refinement algorithms in the context of the variational data assimilation method. Firstly, the chapter looks back at basic properties of the traditional variational data assimilation method and considers on the role of the background error covariance matrix. The next section shows how multigrid algorithms can efficiently solve the resulting system. Then the chapter deals with local mesh refinements and the final part of the chapter gives some ideas on how to couple the two approaches in the view of local multigrid algorithms.
Selected topics in multiscale data assimilation
Authors: Bocquet M. , Wu L. , Chevallier F. , Kookhan M. R. 
Published: March 2015

Abstract
This chapter discusses several approaches to developing original theoretical approaches to assimilate information at a given scale and consistently propagate it to other scales. This is motivated by the fact that models and observations both provide information at various spatial and temporal scales, but their respective scales do not necessarily match. This chapter discusses several approaches to this problem, such as the construction of a multiscale best linear unbiased estimator (BLUE). This approach is applied to the design of efficient adaptive grids in control space with minimal aggregation errors. Examples are chosen in the field of atmospheric constituents such as the inverse modelling of mesoscale CO2 fluxes and the observability of a nuclear test from the United Nations International Monitoring System.
Greenhouse gas flux inversion
Authors: Chevallier F. 
Published: March 2015

Abstract
This chapter is a short overview of the art of inferring CO2 sources and sinks from atmospheric mole fraction measurements, with an opening towards other greenhouse gases, such as methane, for which the inference problem is similar. The various components of this Bayesian estimation problem are recalled: the observations (in situ or from satellites), the prior information about the sources and sinks, the physical models that describe atmospheric transport, and the statistical models that describe the errors of all input information pieces. The chapter also discusses the pros and cons of this approach.
Data assimilation in atmospheric chemistry and air quality
Authors: Elbern H. , Friese E. , Nieradzik L. , Schwinger J. 
Published: March 2015

AbstractThis chapter discusses data assimilation in atmospheric chemistry and air quality. Atmospheric chemistry dynamics and its simulations are significantly forced by emissions, in addition to other parameters. Data assimilation typically aims at analysing the initial state of the system. Hence, for atmospheric chemistry simulations, data assimilation must be extended beyond initial-value identification to identify further parameters by estimation techniques. This chapter describes advanced spatio-temporal data assimilation techniques used in atmospheric chemistry. The objective is joint parameter-initial-state estimation for a coupled four-dimensional variational data assimilation/inversion system using the chemistry-transport model EURAD-IM and satisfying three criteria: both parameter families must have dominant influence on the dynamics, they must be poorly known, and they must impinge on the system on the same timescale. A coupled initial-value/emission-inversion system is described, along with assimilation of tropospheric satellite data from both gas-phase and aerosol retrievals. Examples of aerosol data assimilation are also given.
Data assimilation in coastal oceanography
Authors: Zavala-Garay J. , Wilkin J. , Levin J. 
Published: March 2015

Abstract
This chapter presents examples of variational data assimilation in coastal oceanography using the Regional Ocean Modeling System (ROMS). Realizing that satellite data is the only source of information in real time in most parts of the world ocean, the Ocean Modeling Group at Rutgers University has developed methodologies to exploit the information content in remotely sensed observations. This chapter evaluates the extent to which incremental, strong constraint, four-dimensional variational data assimilation (IS4DVAR) can improve prediction of mesoscale variability using ROMS. Examples of two applications of IS4DVAR in two very different dynamical regimes are presented: the East Australia Current (EAC) and the Middle Atlantic Bight (MAB). The two main sources of satellite information, namely sea surface temperature (SST) and sea surface height anomaly (SSHA), are found to be complementary, and therefore both need to be assimilated in order to approximate the three-dimensional structure of the ocean.
Data assimilation in glaciology
Authors: Bonan B. , Nodet M. , Ozenda O. , Ritz C. 
Published: March 2015

Abstract
This chapter addresses an inverse problem in glaciology, namely how to infer a climatic scenario (i.e. how to reconstruct past polar temperature) from ice volume records. Ice volume observations are available from oceanic records, giving information about sea level, and therefore about the amount of water stored in ice sheets, ice caps, and glaciers. The link between the climatic scenario and the ice sheet volume is complex. The temperature affects the ice mass budget (accumulating minus melting ice). Then, the ice mass budget is a key factor in ice dynamics, which is quite complex in itself (non-Newtonian fluid and nonlinear rheology). The few previous studies of this subject have used fairly simple inverse methods. The idea of the approach described in this chapter is to explore, with idealized twin experiments, the ability of the adjoint method to solve the inverse problem of reconstructing past temperature given all available observations.
Similarity, graphs and networks, random matrices, and SVD
Authors: Grindrod CBE Peter 
Published: March 2015

Abstract
This chapter considers how a range of ideas from linear algebra, nonnegative matrices, random matrices and modern graph theory may assist in the understanding of observed pairwise similarities and networks over a large population of people or objects. In particular it examines some well-known different types of network models and considers (inverse problems concerning) how best to represent any observed social and friendship networks within such classes. This provides methods for inverse problems and soft clustering. Example applications are given to social networks and to clinical data.
About the identification of signals at LHC
Authors: Mansoulié Bruno 
Published: March 2015

Abstract
This chapter describes the main ingredients and steps of the analysis used in the search for the Standard Model Higgs boson decaying into WW (l, l, νν) in the ATLAS experiment. It presents a short guide through a “modern” analysis, typical of the analyses performed on LHC data. The main ingredients are reviewed: irreducible and reducible backgrounds, background estimates from Monte Carlo or data-driven, signal and control regions, global fit, extraction of limits and signal, and the look-elsewhere effect.
Introduction to the theory of LHC collisions
Authors: Mangano Michelangelo L. 
Published: March 2015

Abstract
This chapter illustrates the basic principles underlying the use of perturbative QCD in predicting the structure of hard processes in high-energy hadronic collisions. It starts with a discussion of the factorization formula, which is the basis for the description of all hard processes in terms of universal functions parametrizing the density of quarks and gluons inside the proton. It then discusses the evolution of the perturbative final states, made of quarks and gluons, toward physical systems made of hadrons. Finally, several applications and examples of comparisons between the theoretical predictions and current data are presented. These provide a picture of the success of this theoretical framework, giving good confidence in the reliability of its future applications to the study of LHC collisions.
An introduction to the gauge/gravity duality
Authors: Maldacena Juan M. 
Published: March 2015

Abstract
This chapter is a short introduction to the gauge/gravity duality or AdS/CFT correspondence. After reviewing some basic facts about anti-de-Sitter space, the author describes some of the basic elements of the dictionary between the two sides. The author relates fields in the interior to operators in the boundary. The author also relates the thermodynamics of the field theory to properties of black holes in the gravity solution.
Introduction to the AdS/CFT correspondence
Authors: Boer Jan de 
Published: March 2015

Abstract
This chapter provides a summary of some of the most important aspects of the AdS/CFT correspondence, together with pointers to some of the vast number of papers that have been published on this subject. The AdS/CFT correspondence is one of the most exciting discoveries in theoretical physics of the past 20 years, providing a framework in which it is possible to study strongly coupled field theories using weakly coupled gravity, and at the same time yielding a non-perturbative definition of quantum gravity in anti-de Sitter space.
Hydrodynamics and black holes
Authors: Oz Yaron 
Published: March 2015

Abstract
This chapter describes how the AdS/CFT correspondence (the Holographic Principle) relates field theory hydrodynamics to perturbations of black hole (brane) gravitational backgrounds. The hydrodynamics framework is first presented from the field theory point of view, after which the dual gravitational description is outlined, first for relativistic fluids and then for the nonrelativistic case. Further details of the fluid/gravity correspondence are then discussed, including the bulk geometry and the dynamics of the black hole horizon.
Spontaneous breakdown of local conformal invariance in quantum gravity
Authors: Hooft Gerard ’t 
Published: March 2015

AbstractThis chapter shows how the black hole complementarity principle can be naturally implemented by treating local conformal invariance as an exact but spontaneously broken symmetry of quantum gravity. This allows a description of the black hole either in terms of the imploding particles or entirely in terms of the emerging Hawking particles. These complementary representations can be obtained from one another by a local conformal transformation; this implies that the black hole scattering matrix is equivalent to a local conformal gauge transformation. Perturbative canonical quantum gravity, coupled to a renormalizable model for matter fields, has this conformal symmetry built in, and this symmetry would be exact if the local conformal anomalies cancelled. The Einstein–Hilbert action can be regarded as breaking local conformal invariance only dynamically, not explicitly. The functional integral over the dilaton component of the metric field can be disentangled from the other integrations over the metric and the matter fields, turning the remainder of the theory into a trivially conformally invariant system. When the residual metric is treated as a flat background, this leads to a novel constraint: in combination with the dilaton contributions, the matter Lagrangian should have a vanishing beta function. The zeros of this beta function are isolated points in the landscape of quantum field theories, and so one arrives at a denumerable, or perhaps even finite, set of quantum theories for matter, where coupling constants, masses, and cosmological constant are all fixed, and computable in terms of Planck units.
Renormalization group flows and anomalies
Authors: Komargodski Zohar 
Published: March 2015

Abstract
This chapter reviews various aspects of renormalization group flows and anomalies. The chapter considers specific Euclidean two-dimensional theories. Namely, the theories are invariant under translations and rotations in the two space directions. Here the chapter studies theories where, if possible, certain equations hold in fact also at coincident points. In other words, the chapter looks at theories where there is no local gravitational anomaly.
The description of N=1,d=4 supergravity using twisted supersymmetric fields
Authors: Baulieu Laurent 
Published: March 2015

Abstract
This chapter describes how the method of twisted supersymmetric fields used for describing global supersymmetry, as in the context of topological field theories, can be extended to the description of local supersymmetry. As an example, the method is applied to the case of N = 1 Euclidean supergravity on a 4-manifold with an almost complex structure, with its couplings to scalar and vector multiplets.
High-energy collisions of particles, strings, and branes
Authors: Veneziano Gabriele 
Published: March 2015

AbstractThis chapter summarizes some 25 years of work on the transplanckian-energy collisions of particles, strings, and branes, seen as a theoretical laboratory for understanding how gravity and quantum mechanics can be consistently combined in string theory. The ultimate aim of the exercise is to understand whether and how a consistent quantization of gravity can solve some longstanding paradoxes, such as the apparent loss of information in the production and decay of black holes at a semiclassical level. Considerable progress has been made in understanding the emergence of General Relativity expectations and in evaluating several kinds of quantum string corrections to them in the weak-gravity regime while keeping unitarity manifest. While some progress has also been made in the strong-gravity/gravitational collapse domain, full control of how unitarity works in that regime is still lacking.