Related papers: Compressed Sensing of Compton Profiles for Fermi S…
Increasing the imaging speed is a central aim in photoacoustic tomography. This issue is especially important in the case of sequential scanning approaches as applied for most existing optical detection schemes. In this work we address this…
Neutron Compton scattering measurements have the potential to provide direct information about atomic momentum distributions and adiabatic energy surfaces in condensed matter. First applied to measuring the condensate fraction in superfluid…
The ability to completely characterize the state of a quantum system is an essential element for the emerging quantum technologies. Here, we present a compressed-sensing inspired method to ascertain any rank-deficient qudit state, which we…
The field of compressed sensing has shown that a sparse but otherwise arbitrary vector can be recovered exactly from a small number of randomly constructed linear projections (or samples). The question addressed in this paper is whether an…
In this study we develop dimension-reduction techniques to accelerate diffusion model inference in the context of synthetic data generation. The idea is to integrate compressed sensing into diffusion models (hence, CSDM): First, compress…
Compressed sensing is a technique for recovering an unknown sparse signal from a small number of linear measurements. When the measurement matrix is random, the number of measurements required for perfect recovery exhibits a phase…
Hard X-ray photons with energies in the range of hundreds of keV typically undergo Compton scattering when they are incident on a detector. In this process, an incident photon deposits a fraction of its energy at the point of incidence and…
We have observed the bulk Fermi surface (FS) in an overdoped ($x$=0.3) single crystal of La$_{2-x}$Sr$_x$CuO$_4$ by using Compton scattering. A two-dimensional (2D) momentum density reconstruction from measured Compton profiles yields a…
Monte Carlo simulations of neutronic systems are computationally intensive and demand significant memory resources for high-fidelity modeling. Compressed sensing enables accurate reconstruction of signals from significantly fewer samples…
Optimal sensor placement is a central challenge in the design, prediction, estimation, and control of high-dimensional systems. High-dimensional states can often leverage a latent low-dimensional representation, and this inherent…
The recent theory of compressive sensing leverages upon the structure of signals to acquire them with much fewer measurements than was previously thought necessary, and certainly well below the traditional Nyquist-Shannon sampling rate.…
We have carried out first-principles calculations of the Compton scattering spectra to demonstrate that the filling of the hole Fermi surface in LaO$_{1-x}$F$_{x}$FeAs produces a distinct signature in the Fourier transformed Compton…
Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal structure to efficiently reconstruct…
The soft MeV gamma-ray sky, from a few hundred keV up to several MeV, is one of the least explored regions of the electromagnetic spectrum. The most promising technology to access this energy range is a telescope that uses Compton…
Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement…
Here we show that compressive sensing allow 4-dimensional (4-D) STEM data to be obtained and accurately reconstructed with both high-speed and low fluence. The methodology needed to achieve these results compared to conventional 4-D…
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…
Fermi surfaces, three-dimensional (3D) abstract interfaces that define the occupied energies of electrons in a solid, are important for characterizing and predicting the thermal, electrical, magnetic, and optical properties of crystalline…
Compressive sensing (CS) combines data acquisition with compression coding to reduce the number of measurements required to reconstruct a sparse signal. In optics, this usually takes the form of projecting the field onto sequences of random…
Photons preferentially Compton scatter perpendicular to the plane of polarisation. This property can be exploited to design instruments to measure the linear polarisation of hard X-rays ($\sim$10 - 100 keV). Photons may undergo two…