Characterization of multilayer stack parameters from X-ray reflectivity data using the PPM program: measurements and comparison with TEM results

Future hard (10 -100 keV) X-ray telescopes (SIMBOL-X, Con-X, HEXIT-SAT, XEUS) will implement focusing optics with multilayer coatings: in view of the production of these optics we are exploring several deposition techniques for the reflective coatings. In order to evaluate the achievable optical performance X-Ray Reflectivity (XRR) measurements are performed, which are powerful tools for the in-depth characterization of multilayer properties (roughness, thickness and density distribution). An exact extraction of the stack parameters is however difficult because the XRR scans depend on them in a complex way. The PPM code, developed at ERSF in the past years, is able to derive the layer-by-layer properties of multilayer structures from semi-automatic XRR scan fittings by means of a global minimization procedure in the parameters space. In this work we will present the PPM modeling of some multilayer stacks (Pt/C and Ni/C) deposited by simple e-beam evaporation. Moreover, in order to verify the predictions of PPM, the obtained results are compared with TEM profiles taken on the same set of samples. As we will show, PPM results are in good agreement with the TEM findings. In addition, we show that the accurate fitting returns a physically correct evaluation of the variation of layers thickness through the stack, whereas the thickness trend derived from TEM profiles can be altered by the superposition of roughness profiles in the sample image

Large Chiral Diffeomorphisms on Riemann Surfaces and W-algebras

The diffeomorphism action lifted on truncated (chiral) Taylor expansion of a complex scalar field over a Riemann surface is presented in the paper under the name of large diffeomorphisms. After an heuristic approach, we show how a linear truncation in the Taylor expansion can generate an algebra of symmetry characterized by some structure functions. Such a linear truncation is explicitly realized by introducing the notion of Forsyth frame over the Riemann surface with the help of a conformally covariant algebraic differential equation. The large chiral diffeomorphism action is then implemented through a B.R.S. formulation (for a given order of truncation) leading to a more algebraic set up. In this context the ghost fields behave as holomorphically covariant jets. Subsequently, the link with the so called W-algebras is made explicit once the ghost parameters are turned from jets into tensorial ghost ones. We give a general solution with the help of the structure functions pertaining to all the possible truncations lower or equal to the given order. This provides another contribution to the relationship between KdV flows and W-diffeomorphimsComment: LaTeX file, 31 pages, no figure. Version to appear in J. Math. Phys. Work partly supported by Region PACA and INF

Metamorph: Real-Time High-Level Sound Transformations Based On A Sinusoids Plus Noise Plus Transients Model

Spectral models provide ways to manipulate musical audio signals that can be both powerful and intuitive, but high-level control is often required in order to provide flexible real-time control over the potentially large parameter set. This paper introduces Metamorph, a new open source library for high-level sound transformation. We describe the real-time sinusoids plus noise plus transients model that is used by Metamorph and explain the opportunities that it provides for sound manipulation

Real-time segmentation of the temporal evolution of musical sounds

Since the studies of Helmholtz, it has been known that the temporal evolution of musical sounds plays an important role in our perception of timbre. The accurate temporal segmentation of musical sounds into regions with distinct characteristics is therefore of interest to researchers in the field of timbre perception as well as to those working with different forms of sound modelling and manipulation. Following recent work by Hajda (1996), Peeters (2004) and Caetano et al (2010), this paper presents a new method for the automatic segmentation of the temporal evolution of isolated musical sounds in real-time. We define attack, sustain and release segments using cues from a combination of the amplitude envelope, the spectro- temporal evolution and a measurement of the stability of the sound that is derived from the onset detection function. We conclude with an evaluation of the method

Python for audio signal processing

This paper discusses the use of Python for developing audio signal processing applications. Overviews of Python language, NumPy, SciPy and Matplotlib are given, which together form a powerful platform for scientic computing. We then show how SciPy was used to create two audio programming libraries, and describe ways that Python can be integrated with the SndObj library and Pure Data, two existing environments for music composition and signal processing

Python for audio signal processing

This paper discusses the use of Python for developing audio signal processing applications. Overviews of Python language, NumPy, SciPy and Matplotlib are given, which together form a powerful platform for scientic computing. We then show how SciPy was used to create two audio programming libraries, and describe ways that Python can be integrated with the SndObj library and Pure Data, two existing environments for music composition and signal processing

SIMPL: A Python Library for Sinusoidal Modelling

This paper introduces Simpl, a new open source library for sinusoidal modelling written in Python. The library is presented as a resource for researchers in spectral signal processing, who might like to access existing methods and techniques. The text provides an overview of the design of the library, describing its data abstractions and integration with other systems. This is complemented by some brief examples exploring the functionality of the library

Real-Time Detection of Musical Onsets with Linear Prediction and Sinusoidal Modelling

Real-time musical note onset detection plays a vital role in many audio analysis processes, such as score following, beat detection and various sound synthesis by analysis methods. This paper provides a review of some of the most commonly used techniques for real-time onset detection. We suggest ways to improve these techniques by incorporating linear prediction, as well as presenting a novel algorithm for real-time onset detection using sinusoidal modelling. We provide comprehensive results for both the detection accuracy and the computational performance of all of the described techniques, evaluated using Modal, our new open source library for musical onset detection, which comes with a free database of samples with hand-labelled note onsets