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Register a new userEfficient and Versatile Toolbox for Analysis of Time-Tagged Measurements
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Acquisition and analysis of time-tagged events is a ubiquitous tool in scientific and industrial applications. With increasing time resolution, number of input channels, and acquired events, the amount of data can be overwhelming for standard processing techniques. We developed the Extensible Time-tag Analyzer (ETA), a powerful and versatile, yet easy to use software to efficiently analyze and display time-tagged data. Our tool allows for flexible extraction of correlation from time-tagged data beyond start-stop measurements that were traditionally used. A combination of state diagrams and simple code snippets allows for analysis of arbitrary complexity while keeping computational efficiency high.
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We consider how to analyze microcalorimeter pulses for quantities that are nonlinear in the data, while preserving the signal-to-noise advantages of lin- ear optimal filtering. We successfully apply our chosen approach to compute the electrothermal feedback energy deficit (the Joule energy) of a pulse, which has been proposed as a linear estimator of the deposited photon energy.
Time-Correlated Single Photon Counting (TCSPC) and time tagging of individual photon detections are powerful tools in many quantum optical experiments and other areas of applied physics. Using TCSPC, e.g., for the purpose of fluorescence lifetime measurements, is often limited in speed due to dead-time losses and pile-up. We show that this limitation can be lifted by reducing the dead-time of the timing electronics to the absolute minimum imposed by the speed of the detector signals while maintaining high temporal resolution. A complementing approach to speedy data acquisition is parallelization by means of simultaneous readout of many detector channels. This puts high demands on the data throughput of the TCSPC system, especially in time tagging of individual photon arrivals. Here, we present a new design approach, supporting up to 16 input channels, an extremely short dead-time of 650 ps, very high time tagging throughput, and a timing resolution of 80 ps. In order to facilitate remote synchronization of multiple such instruments with highest precision, the new TCSPC electronics provide an interface for White Rabbit fiber optic networks. Beside fundamental research in the field of astronomy, such remote synchronization tasks arise routinely in quantum communication networks with node to node distances on the order of tens of kilometers. In addition to showing design features and benchmark results of new TCSPC electronics, we present application results from spectrally resolved and high-speed fluorescence lifetime imaging in medical research. We furthermore show how pulse-pile-up occurring in the detector signals at high photon flux can be corrected for and how this data acquisition scheme performs in terms of accuracy and efficiency.
To handle time series with complicated oscillatory structure, we propose a novel time-frequency (TF) analysis tool that fuses the short time Fourier transform (STFT) and periodic transform (PT). Since many time series oscillate with time-varying frequency, amplitude and non-sinusoidal oscillatory pattern, a direct application of PT or STFT might not be suitable. However, we show that by combining them in a proper way, we obtain a powerful TF analysis tool. We first combine the Ramanujan sums and $l_1$ penalization to implement the PT. We call the algorithm Ramanujan PT (RPT). The RPT is of its own interest for other applications, like analyzing short signal composed of components with integer periods, but that is not the focus of this paper. Second, the RPT is applied to modify the STFT and generate a novel TF representation of the complicated time series that faithfully reflect the instantaneous frequency information of each oscillatory components. We coin the proposed TF analysis the Ramanujan de-shape (RDS) and vectorized RDS (vRDS). In addition to showing some preliminary analysis results on complicated biomedical signals, we provide theoretical analysis about RPT. Specifically, we show that the RPT is robust to three commonly encountered noises, including envelop fluctuation, jitter and additive noise.
Silicon drift detectors (SDDs) revolutionized spectroscopy in fields as diverse as geology and dentistry. For a subset of experiments at ultra-fast, x-ray free-electron lasers (FELs), SDDs can make substantial contributions. Often the unknown spectrum is interesting, carrying science data, or the background measurement is useful to identify unexpected signals. Many measurements involve only several discrete photon energies known a priori, allowing single event decomposition of pile-up and spectroscopic photon counting. We designed a pulse function and demonstrated that the signal amplitude and rise time are obtained for each pulse by fitting, thus removing the need for pulse shaping. By avoiding pulse shaping, rise times of tens of nanoseconds resulted in reduced pulse pile-up and allowed decomposition of remaining pulse pile-up at photon separation times down to hundreds of nanoseconds while yielding time-of-arrival information with precision of 10 nanoseconds. Waveform fitting yields simultaneously high energy resolution and high counting rates (2 orders of magnitude higher than current digital pulse processors). We showed that pile-up spectrum fitting is relatively simple and preferable to pile-up spectrum deconvolution. We developed a photon pile-up statistical model for constant intensity sources, extended it to variable intensity sources (typical for FELs) and used it to fit a complex pile-up spectrum. We subsequently developed a Bayesian pile-up decomposition method that allows decomposing pile-up of single events with up to 6 photons from 6 monochromatic lines with 99% accuracy. The usefulness of SDDs will continue into the x-ray FEL era of science. Their successors, the ePixS hybrid pixel detectors, already offer hundreds of pixels, each with similar performance to an SDD, in a compact, robust and affordable package
Electric signals have been recently recorded at the Earths surface with amplitudes appreciably larger than those hitherto reported. Their entropy in natural time is smaller than that, $S_u$, of a ``uniform distribution. The same holds for their entropy upon time-reversal. This behavior, as supported by numerical simulations in fBm time series and in an on-off intermittency model, stems from infinitely ranged long range temporal correlations and hence these signals are probably Seismic Electric Signals (critical dynamics). The entropy fluctuations are found to increase upon approaching bursting, which reminds the behavior identifying sudden cardiac death individuals when analysing their electrocardiograms.
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