Error-resistant Single Qubit Gates with Trapped Ions

Coherent operations constitutive for the implementation of single and multi-qubit quantum gates with trapped ions are demonstrated that are robust against variations in experimental parameters and intrinsically indeterministic system parameters. In particular, pulses developed using optimal control theory are demonstrated for the first time with trapped ions. Their performance as a function of error parameters is systematically investigated and compared to composite pulses.Comment: 5 pages 5 figure

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

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

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

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

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

Perceptual Centre correlates in Evoked Potentials

Perceptual centres (p-centres) are the subjective moments of occurrence of acoustic stimuli. When sounds are perceived in synchrony or are regularly spaced, it is their p-centres which occur synchronously or are isochronous. In order to analyse or model the acoustic features which influence the p-centre, it is necessary to measure p-centres for many stimuli. However there is a problem: it is difficult for an external observer to determine the exact time at which a listener perceives a sound’s occurrence. A possible solution is to find a measurable electrophysiological correlate of the p-centre. In order to investigate this, an experiment is described which compares features of the Auditory Evoked Potential (AEP) response and p-centres for a number of speech and synthetic stimuli. The results indicate a correlation between the latency of the dominant negative peak of the AEP and the p-centre

Bike Renting Data Analysis: The Case of Dublin City

Public bike renting is more and more popular in cities to incentivise a reduction in car journeys and to boost the use of green transportation alternatives. One of the challenges of this application is to effectively plan the resources usage. This paper presents some analysis of Dublin bike renting scheme based on statistics and data mining.It provides available bike patterns at the most interesting bike stations, that is, the busiest and the quietest stations. Consistency checking with new data reinforces confidence in the patterns obtained. Identifying available bike patterns helps to better address user needs such as organising the rebalancing of the bike numbers between stations in advance of demand

Budget Perspectives 2013. RESEARCH SERIES NUMBER 28 September 2012

The annual Budget Perspectives Conference provides a forum for discussing key public policy issues of both immediate and longer term concern. In the context of the current fiscal and economic crisis, research insights are needed at both the macro and micro level. The former are central to understanding and managing the significant reductions in the budget deficit needed to put Ireland's public finances on a sustainable footing. The latter are essential because a successful budgetary adjustment requires restructuring of both public expenditure and taxation. This in turn requires that policy adjustments take full account of both efficiency and equity issue and are seen to do so. The research papers presented at this year's annual Budget Perspectives Conference continue in this tradition, providing an opportunity for policymakers, social partners and researchers to engage with some of the major current issues