7,869 research outputs found
Deep Learning Reconstruction of Ultra-Short Pulses
Ultra-short laser pulses with femtosecond to attosecond pulse duration are
the shortest systematic events humans can create. Characterization (amplitude
and phase) of these pulses is a key ingredient in ultrafast science, e.g.,
exploring chemical reactions and electronic phase transitions. Here, we propose
and demonstrate, numerically and experimentally, the first deep neural network
technique to reconstruct ultra-short optical pulses. We anticipate that this
approach will extend the range of ultrashort laser pulses that can be
characterized, e.g., enabling to diagnose very weak attosecond pulses
Single-shot compressed ultrafast photography: a review
Compressed ultrafast photography (CUP) is a burgeoning single-shot computational imaging technique that provides an imaging speed as high as 10 trillion frames per second and a sequence depth of up to a few hundred frames. This technique synergizes compressed sensing and the streak camera technique to capture nonrepeatable ultrafast transient events with a single shot. With recent unprecedented technical developments and extensions of this methodology, it has been widely used in ultrafast optical imaging and metrology, ultrafast electron diffraction and microscopy, and information security protection. We review the basic principles of CUP, its recent advances in data acquisition and image reconstruction, its fusions with other modalities, and its unique applications in multiple research fields
Classification and Recovery of Radio Signals from Cosmic Ray Induced Air Showers with Deep Learning
Radio emission from air showers enables measurements of cosmic particle
kinematics and identity. The radio signals are detected in broadband Megahertz
antennas among continuous background noise. We present two deep learning
concepts and their performance when applied to simulated data. The first
network classifies time traces as signal or background. We achieve a true
positive rate of about 90% for signal-to-noise ratios larger than three with a
false positive rate below 0.2%. The other network is used to clean the time
trace from background and to recover the radio time trace originating from an
air shower. Here we achieve a resolution in the energy contained in the trace
of about 20% without a bias for of the traces with a signal. The
obtained frequency spectrum is cleaned from signals of radio frequency
interference and shows the expected shape.Comment: 20 pages, 13 figures, resubmitted to JINS
Simulation and Analysis Chain for Acoustic Ultra-high Energy Neutrino Detectors in Water
Acousticneutrinodetectionisapromisingapproachforlarge-scaleultra-highenergyneutrinodetectorsinwater.In
this article, a Monte Carlo simulation chain for acoustic neutrino detection
devices in water will be presented. The simulation chain covers the generation
of the acoustic pulse produced by a neutrino interaction and its propagation to
the sensors within the detector. Currently, ambient and transient noise models
for the Mediterranean Sea and simulations of the data acquisition hardware,
equivalent to the one used in ANTARES/AMADEUS, are implemented. A pre-selection
scheme for neutrino-like signals based on matched filtering is employed, as it
is used for on-line filtering. To simulate the whole processing chain for
experimental data, signal classification and acoustic source reconstruction
algorithms are integrated in an analysis chain. An overview of design and
capabilities of the simulation and analysis chain will be presented and
preliminary studies will be discussed.Comment: 6 pages, 5 figures, ARENA 2012. arXiv admin note: substantial text
overlap with arXiv:1304.057
Noise Effects on a Proposed Algorithm for Signal Reconstruction and Bandwidth Optimization
The development of wireless technology in recent years has increased the demand for channel resources within a limited spectrum. The system\u27s performance can be improved through bandwidth optimization, as the spectrum is a scarce resource. To reconstruct the signal, given incomplete knowledge about the original signal, signal reconstruction algorithms are needed. In this paper, we propose a new scheme for reducing the effect of adding additive white Gaussian noise (AWGN) using a noise reject filter (NRF) on a previously discussed algorithm for baseband signal transmission and reconstruction that can reconstruct most of the signal’s energy without any need to send most of the signal’s concentrated power like the conventional methods, thus achieving bandwidth optimization. The proposed scheme for noise reduction was tested for a pulse signal and stream of pulses with different rates (2, 4, 6, and 8 Mbps) and showed good reconstruction performance in terms of the normalized mean squared error (NMSE) and achieved an average enhancement of around 48%. The proposed schemes for signal reconstruction and noise reduction can be applied to different applications, such as ultra-wideband (UWB) communications, radio frequency identification (RFID) systems, mobile communication networks, and radar systems
Background identification algorithm for future self-triggered air-shower radio arrays
The study of the ultra-high energy cosmic rays, neutrinos and gamma rays is
one of the most important challenges in astrophysics. The low fluxes of these
particles do not allow one to detect them directly. The detection is performed
by the measuring of the air-showers produced by the primary particles in the
Earth's atmosphere. A radio detection of ultra-high energy air-showers is a
cost-effective technique that provides a precise reconstruction of the
parameters of primary particle and almost full duty cycle in comparison with
other methods. The main challenge of the modern radio detectors is the
development of efficient self-trigger technology, resistant to high-level
background and radio frequency interference. Most of the modern radio detectors
receive trigger generated by either particle or optical detectors. The
development of the self trigger for the radio detector will significantly
simplify the operation of existing instruments and allow one to access the main
advantages of the radio method as well as open the way to the construction of
the next generation of large-scale radio detectors. In the present work we
discuss our progress in the solution of this problem, particularly the
classification of broadband pulses.Comment: 6 pages, 1 figur
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