arXiv subjects

Peter Norreys

Publications and source records attributed to Peter Norreys.

9 recordsLinked to original sources

arXiv2025

Search for black hole super-radiance using gravito-optic hetrodyne detection

Gravitational-wave astronomy plays a crucial role in early universe cosmology, dark matter detection, and black-hole merger studies. It is shown here that the heterodyne detection of the gravito-optic effect (employing an enhanced Fabry-P\'erot cavity) presents a novel broad band approach to gravitational wave detection, with favorable length and frequency scalings. It is demonstrated that such a device is well suited for detecting gravitational waves generated by the annihilation of bosons around black holes, enabling the exploration of a mass range from $ 2.40 \times 10^{-12} \, \mathrm{eV} $ to $ 4.54 \times 10^{-7} \, \mathrm{eV} $. Furthermore, due to the unique coherent nature of gravitational waves generated by boson annihilation any coherent gravitational waves detected above $ 1.23 \times 10^5 \, \mathrm{Hz} $ may be indicative of the existence of black holes of primordial origin.

gr-qc↗

arXiv2024

CoordGate: Efficiently Computing Spatially-Varying Convolutions in Convolutional Neural Networks

Optical imaging systems are inherently limited in their resolution due to the point spread function (PSF), which applies a static, yet spatially-varying, convolution to the image. This degradation can be addressed via Convolutional Neural Networks (CNNs), particularly through deblurring techniques. However, current solutions face certain limitations in efficiently computing spatially-varying convolutions. In this paper we propose CoordGate, a novel lightweight module that uses a multiplicative gate and a coordinate encoding network to enable efficient computation of spatially-varying convolutions in CNNs. CoordGate allows for selective amplification or attenuation of filters based on their spatial position, effectively acting like a locally connected neural network. The effectiveness of the CoordGate solution is demonstrated within the context of U-Nets and applied to the challenging problem of image deblurring. The experimental results show that CoordGate outperforms conventional approaches, offering a more robust and spatially aware solution for CNNs in various computer vision applications.

cs.CV↗

arXiv2023

Gravitational waves from high-power twisted light

Recent advances in high-energy and high-peak-power laser systems have opened up new possibilities for fundamental physics research. In this work, the potential of twisted light for the generation of gravitational waves in the high frequency regime is explored for the first time. Focusing on Bessel beams, novel analytic expressions and numerical computations for the generated metric perturbations and associated powers are presented. Compelling evidence is provided that the properties of the generated gravitational waves, such as frequency, polarisation states and direction of emission, are controllable by the laser pulse parameters and optical arrangements.

gr-qc↗

arXiv2023

Hyperspectral Compressive Wavefront Sensing

Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot. A deep unrolling algorithm is utilised for the snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative to other methods, potentially allowing for online reconstruction. The algorithm's regularisation term is represented using neural network with 3D convolutional layers, to exploit the spatio-spectral correlations that exist in laser wavefronts. Compressed sensing is not typically applied to modulated signals, but we demonstrate its success here. Furthermore, we train a neural network to predict the wavefronts from a lateral shearing interferogram in terms of Zernike polynomials, which again increases the speed of our technique without sacrificing fidelity. This method is supported with simulation-based results. While applied to the example of lateral shearing interferometry, the methods presented here are generally applicable to a wide range of signals, including Shack-Hartmann-type sensors. The results may be of interest beyond the context of laser wavefront characterization, including within quantitative phase imaging.

physics.optics↗

arXiv2020

Nonlinear wakefields and electron injection in cluster plasma

Laser and beam driven wakefields promise orders of magnitude increases in electric field gradients for particle accelerators for future applications. Key areas to explore include the emittance properties of the generated beams and overcoming the dephasing limit in the plasma. In this paper, the first in-depth study of the self-injection mechanism into wakefield structures from non-homogeneous cluster plasmas is provided using high-resolution two dimensional particle-in-cell simulations. The clusters which are typical structures caused by ejection of gases from a high-pressure gas jet have a diameter much smaller than the laser wavelength. Conclusive evidence is provided for the underlying mechanism that leads to particle trapping, comparing uniform and cluster plasma cases. The accelerated electron beam properties are found to be tunable by changing the cluster parameters. The mechanism explains enhanced beam charge paired with large transverse momentum and energy which has implications for the betatron x-ray flux. Finally, the impact of clusters on the high-power laser propagation behavior is discussed.

physics.plasm-ph↗

arXiv2018

Three dimensional spectrometer

We present a novel design of 3D spectrometer that can retrieve 3D spectral profile in a single measurement. The 3D spectrometer design is built upon the concept of compressed sensing to make it possible to retrieve 3D information from 2D data from a screen/camera. In contrast to common spectrometers, the 3D spectrometer uses a wide slit instead of a narrow slit and retrieve the 3D datacube that consists of 2D spatial and 1D spectral information. Numerical tests were performed to simulate the retrieval of spectral profiles. The results show that the retrieved profiles match well the original profiles. It is also shown that the retrieved signal from the 3D spectrometer is robust enough for a further post-processing analysis.

physics.ins-det↗

arXiv2017

Quantitative shadowgraphy and proton radiography for large intensity modulations

Shadowgraphy is a technique widely used to diagnose objects or systems in various fields in physics and engineering. In shadowgraphy, an optical beam is deflected by the object and then the intensity modulation is captured on a screen placed some distance away. However, retrieving quantitative information from the shadowgrams themselves is a challenging task because of the non-linear nature of the process. Here, a novel method to retrieve quantitative information from shadowgrams, based on computational geometry, is presented for the first time. This process can be applied to proton radiography for electric and magnetic field diagnosis in high-energy-density plasmas and has been benchmarked using a toroidal magnetic field as the object, among others. It is shown that the method can accurately retrieve quantitative parameters with error bars less than 10%, even when caustics are present. The method is also shown to be robust enough to process real experimental results with simple pre- and post-processing techniques. This adds a powerful new tool for research in various fields in engineering and physics for both techniques.

physics.comp-ph↗

arXiv2016

Machine learning applied to proton radiography

Proton radiography is a technique extensively used to resolve magnetic field structures in high energy density plasmas, revealing a whole variety of interesting phenomena such as magnetic reconnection and collisionless shocks found in astrophysical systems. Existing methods of analyzing proton radiographs give mostly qualitative results or specific quantitative parameters such as magnetic field strength, and recent work showed that the line-integrated transverse magnetic field can be reconstructed in specific regimes where many simplifying assumptions were needed. Using artificial neural networks, we suggest a novel 3-D reconstruction method that works for a more general case. A proof of concept is presented here, with mean reconstruction errors of less than 5 percent even after introducing noise. We demonstrate that over the long term, this approach is more computationally efficient compared to other techniques. We also highlight the need for proton tomography because (i) certain field structures cannot be reconstructed from a single radiograph and (ii) errors can be further reduced when reconstruction is performed on radiographs generated by proton beams fired in different directions.

physics.comp-ph↗

arXiv2014

A robust plasma-based laser amplifier via stimulated Brillouin scattering

It is shown here that Brillouin amplification can be used to produce picosecond pulses of petawatt power. Brillouin amplification is far more resilient to fluctuations in the laser and plasma parameters than Raman amplification, making it an attractive alternative to Raman amplification. Through analytic theory and multi-dimensional computer simulations, a novel, well-defined parameter regime has been found, distinct from that of Raman amplification, where pump-to-probe compression ratios of up to 100 and peak laser fluences over 1 kJ/cm$^2$ with 30\% efficiency have been achieved. High pulse quality has been maintained through control of parasitic instabilities.

physics.plasm-ph↗