arXiv subjects

David M. Paganin

Publications and source records attributed to David M. Paganin.

At least 19 recordsLinked to original sources

arXiv2026

Laser-induced phase shift of swift electrons

We revisit the calculation of the phase shift experienced by swift electrons on passing through the electromagnetic field of a laser. Such phase shifts are now utilized in the form of `laser phase plates' in transmission electron microscopes (TEMs), for example. We calculate the phase shift using three different methods, namely, perturbation theory applied to the Dirac equation, the Volkov solution to the Klein-Gordon equation, and the relativistic Hamilton-Jacobi equation. We find that all three methods are in agreement, and that the calculated phase shift is independent of the relative orientation of the electron and laser beams. The agreement between the quantum and classical theories is explained. The duality between the phase shifts experienced by electrons, photons and neutrons is described. Our Lorentz invariant result for the phase shift differs from certain results published in the literature.

physics.optics↗

arXiv2026

Efficiency limits in in-line imaging

In-line phase-contrast imaging, also known as propagation-based imaging or Gabor holography, is capable of delivering significant gains in image quality, compared to attenuation-based imaging at the same radiation dose. Image quality metrics, including signal-to-noise ratio and spatial resolution, are considered, and their relationship to the amount of Shannon information in the image is discussed. It is demonstrated that it is possible to increase the image quality gain by combining known phase retrieval methods with deconvolution of the point-spread function (PSF) of the imaging system, with the highest gain achieved using the Contrast Transfer Function correction method in combination with the PSF deconvolution. The ultimate limit of this gain is determined by the ratio of the real decrement to the imaginary part of the complex refractive index of the imaged sample. Analytical results for the image quality limits in in-line imaging are obtained using a Gaussian model for the detector PSF. A numerically simulated example confirming the theoretical results is also presented.

physics.optics↗

arXiv2026

Paraxial diffusion-field retrieval. II. Fokker-Planck generalization of the transport-of-intensity equation

The transport-of-intensity equation (TIE), namely the continuity equation associated with a coherent paraxial optical wavefield, is widely used for phase retrieval. It is a second-order partial differential equation which may be solved for the phase of a coherent paraxial field such as a monochromatic scalar optical beam, given the intensity and longitudinal intensity derivative in a plane perpendicular to the optical axis. We show how the coherent flow associated with the TIE may be augmented by a diffusive flow associated with a scalar or tensor diffusion field. Such diffusive flow can arise via scattering from unresolved spatially random microstructure in an illuminated sample, blurring effects of an extended chaotic source that illuminates the sample, the resolution-reducing effect of shot noise in detected intensity images of the sample, and the sharpening effect (negative diffusion) associated with scattering from sharp sample edges. Augmenting the TIE's modeling of coherent flow with a diffuse-flow channel leads to a Fokker-Planck extension to this equation. Two different augmentations are obtained, using several complementary derivations. The inverse problems of phase retrieval and diffusion-field retrieval are then considered, for defocus-based imaging and mask-based imaging. When symmetric overfocus and underfocus images are used for phase retrieval, the diffusive term drops out and our Fokker-Planck formalism implies that any ensuing TIE-based phase-retrieval method needs no modification in light of our formalism. However, the same focal-series dataset---typically an infocus image, a weakly overfocused image, and a weakly underfocused image---may also be employed to access the additional channel of information associated with the Fokker-Planck diffusion field. Our formalism is applicable to visible light, x-ray, electron, and neutron imaging.

physics.optics↗

arXiv2026

Generalized Zernike Phase-Contrast Imaging

Zernike phase-contrast imaging is unique among imaging techniques in that it enables the upper limit of Fisher information allowed by quantum mechanics. Here we show that, in a departure from an ideal setting, using an incident beam of finite width, and a $π/2$ phase plate having a finite cutoff, the technique can still deliver $>95\%$ of the quantum limit. We point out that the Zernike method is, in principle, applicable to any incident beam. As an example, we sketch an approximate implementation of the method for an incident speckle beam, and show that it too can deliver $>95\%$ of the quantum limit.

physics.optics↗

arXiv2026

On optimization of Paganin's method for propagation-based X-ray phase-contrast imaging and tomography

Paganin's method for image reconstruction in propagation-based phase-contrast X-ray imaging and tomography has enjoyed broad acceptance in recent years, with over one thousand publications citing its use. The present paper discusses approaches to optimization of the method with respect to simple image quality metrics, such as signal-to-noise ratio and spatial resolution, as well as a reference-based metric corresponding to the relative mean squared difference between the reconstructed image and the "ground truth" image that would be obtained in a setup with perfect spatial resolution and no noise. The problem of optimization of the intrinsic regularization parameter of Paganin's method with respect to spatial resolution in the reconstructed image is studied in detail. It is also demonstrated that a combination of Paganin's method with a Tikhonov-regularized deconvolution of the point-spread function of the imaging system can provide significantly higher image quality compared to the standard version of the method. Analytical expressions for some relevant image quality metrics are obtained and compared with results of numerical simulations. Advantages and shortcomings of optimization approaches using a number of different image quality metrics are discussed. The results of this study are expected to be useful in practical X-ray imaging and training of deep machine learning models for image denoising and segmentation.

physics.med-ph↗

arXiv2025

Active wave-particle clusters

Active particles are non-equilibrium entities that uptake energy and convert it into self-propulsion. A dynamically rich class of inertial active particles having features of wave-particle coupling and wave memory are walking/superwalking droplets. Such classical, active wave-particle entities (WPEs) have previously been shown to exhibit hydrodynamic analogs of many single-particle quantum systems. Inspired by the rich dynamics of strongly interacting superwalking droplets in experiments, we numerically investigate the dynamics of WPE clusters using a stroboscopic model. We find that several interacting WPEs self-organize into a stable bound cluster, reminiscent of an atomic nucleus. This active cluster exhibits a rich spectrum of collective excitations, including shape oscillations and chiral rotating modes, akin to vibrational and rotational modes of nuclear excitations, as the spatial extent of the waves and their temporal decay rate (memory) are varied. Dynamically distinct excitation modes create a common time-averaged collective wave field potential, bearing qualitative similarities with the nuclear shell model and the bag model of hadrons. For high memory and rapid spatial decay of waves, the active cluster becomes unstable and disintegrates; however, within a narrow regime of the parameter space, the cluster ejects single particles whose decay statistics follow exponential laws, reminiscent of radioactive nuclear decay. Our study uncovers a rich spectrum of dynamical behaviors in clusters of active particles, opening new avenues for exploring hydrodynamic quantum analogs in active matter systems.

cond-mat.soft↗

arXiv2025

Quantitative Stain Mapping in X-ray Virtual Histology

Virtual histology is an emerging field in biomedicine that enables three-dimensional tissue visualization using X-ray micro-computed tomography. However, the method still lacks the specificity of conventional histology, in which parts of the tissue are selectively highlighted using targeted stains. Though some first X-ray stains have been developed to address this issue, their precise location and quantity inside the tissue volume remain largely unknown. In this work, we present a novel approach to virtual histology that simultaneously captures electron number density and X-ray attenuation values through modulation-based X-ray imaging with a structured phase modulator. These complementary measurements enable decomposition of tissue volumes into basis materials, which allows the extraction of three-dimensional maps of molar contrast agent distribution alongside morphological details on the micrometer scale -- here demonstrated on murine kidneys. The concentration values are validated against the established method of K-edge subtraction imaging. We also create a direct bridge from X-ray to visible light imaging by detecting the same stain both using classical histology and our proposed X-ray approach. Our methodology opens new possibilities for biomedical research into disease progression by providing quantitative three-dimensional stain mapping across entire tissue volumes alongside high-contrast morphology, enabling deeper insights into disease mechanisms.

physics.med-ph↗

arXiv2025

Demonstrating a family of X-ray dark-field retrieval approaches on a common set of samples

Sensitive to scattering from unresolved sample structures, the dark-field channel in full-field X-ray imaging provides complementary information to that offered by conventional attenuation and phase-contrast methods. A range of experimental dark-field techniques and retrieval algorithms have been recently developed to extract this signal by directly resolving dark-field-associated local image blurring with a high-resolution camera. While the underlying physical mechanism that generates dark-field contrast is generally defined similarly across the methods, no comparison of these dark-field techniques using identical samples has been conducted. In this paper, dark-field imaging data from two samples were acquired using three emerging dark-field setups at a synchrotron: propagation-based, single-grid, and speckle-based X-ray imaging. Dark-field images were then reconstructed using a variety of retrieval algorithms--some requiring only a single sample exposure, others multiple; some performing local, pixel-wise analysis, and others operating globally on entire images. We find that the dominant contribution to dark-field contrast--arising from diffuse scattering from unresolved microstructures or multiple refractions through larger, potentially resolved structures--is consistently recovered across all approaches, demonstrating mutual agreement. However, some differences emerge for structures that are spatially varying. We attribute these differences to the idea that each technique has a different internal ruler, a sensitivity scale for dark-field retrieval influenced by both the experimental design and algorithmic assumptions of the technique. This study is intended to guide dark-field imaging users in selecting the most appropriate technique for their imaging goals and to motivate future research into dark-field sensitivity and sources of dark-field contrast across different methods.

physics.optics↗

arXiv2025

Ghost projection via focal-field diffraction catastrophes

Ghost projection is the reversed process of computational classical ghost imaging that allows any desired image to be synthesized using a linear combination of illuminating patterns. Typically, physical attenuating masks are used to produce these illuminating patterns. A mask-free alternative form of ghost projection is explored here, where the illuminations are a set of caustic-laden diffraction patterns known as diffraction catastrophes. These are generated by focusing a coherent beam with spatially modulated phase having random Zernike-polynomial aberrations. We demonstrate, via simulation, that a suitable linear combination of such random focal-field intensity patterns can be used as a basis to synthesize arbitrary images. In our proof-of-concept ghost-projection synthesis, the positive weighting coefficients in the decomposition are proportional to exposure times for each focal-field diffraction catastrophe. Potential applications include dynamic on-demand beam shaping of focused fields, aberration correction and lithography.

physics.optics↗

arXiv2025

Neutron Beam Shaping by Ghost Projection

We present a method to shape a neutron beam and project any specified target image using a single universal patterned mask that is transversely displaced. The method relies on ``ghost projection'', which is a reversed form of classical ghost imaging. A set of sub-mask regions that combine to construct the required beam shape is computed; illumination of each region with the determined exposure time projects the shaped beam. We demonstrate this method experimentally, using the Dingo neutron imaging beamline at the OPAL nuclear research reactor (Australia). The ability to shape a neutron beam ``on demand'' allows selective dose delivery away from sensitive areas of samples, such as in cultural heritage artifacts. It also benefits irradiation techniques, e.g., in testing resilience of electronic components for space and defense technologies or neutron therapies.

physics.med-ph↗

arXiv2024

In vivo 4D x-ray dark-field lung imaging in mice

X-ray dark-field imaging is well-suited to visualizing the health of the lungs because the alveoli create a strong dark-field signal. However, time-resolved and tomographic (i.e., 4D) dark-field imaging is challenging, since most x-ray dark-field techniques require multiple sample exposures, captured while scanning the position of crystals or gratings. Here, we present the first in vivo 4D x-ray dark-field lung imaging in mice. This was achieved by synchronizing the data acquisition process of a single-exposure grid-based imaging approach with the breath cycle. The short data acquisition time per dark-field projection made this approach feasible for 4D x-ray dark-field imaging by minimizing the motion-blurring effect, the total time required and the radiation dose imposed on the sample. Images were captured from a control mouse and from mouse models of muco-obstructive disease and lung cancer, where a change in the size of the alveoli was expected. This work demonstrates that the 4D dark-field signal provides complementary information that is inaccessible from conventional attenuation-based CT images, in particular, how the size of the alveoli from different parts of the lungs changes throughout a breath cycle, with examples shown across the different models. By quantifying the dark-field signal and relating it to other physical properties of the alveoli, this technique could be used to perform functional lung imaging that allows the assessment of both global and regional lung conditions where the size or expansion of the alveoli is affected.

physics.med-ph↗

arXiv2024

Deep Learning in Classical X-ray Ghost Imaging for Dose Reduction

Ghost imaging (GI) is an unconventional technique that combines information from two correlated patterned light fields to compute an image of the object of interest. GI can be performed with visible light as well as penetrating radiation such as x-rays, electrons, etc. Penetrating radiation is usually ionizing and damages biological specimens; therefore, minimising the dose of this radiation in a medical or biological imaging context is important. GI has been proposed as a potential way to achieve this. With prior knowledge of the object of interest, such as sparsity in a specific basis (e.g., Fourier basis) or access to a large dataset for neural network training, it is possible to reconstruct an image of the object with a limited number of measurements. However, low sampling does not inherently equate to low dose. Here, we specifically explore the scenario where reduced sampling corresponds to low-dose conditions. In this simulation-based paper, we examine how deep learning (DL) techniques could reduce dose in classical x-ray GI. Since GI is based on illumination patterns, we start by exploring optimal sets of patterns that allow us to reconstruct the image with the fewest measurements, or lowest sampling rate, possible. We then propose a DL neural network that can directly reconstruct images from GI measurements even when the sampling rate is extremely low. We demonstrate that our deep learning-based GI (DLGI) approach has potential in image reconstruction, with results comparable to direct imaging (DI) at the same dose. However, given the same prior knowledge and detector quantum efficiency, it is very challenging for DLGI to outperform DI under low-dose conditions. We discuss how it may be achievable due to the higher sensitivity of bucket detectors over pixel detectors.

physics.optics↗

arXiv2024

High-resolution x-ray scanning with a diffuse, Huffman-patterned probe to minimise radiation damage

Scanning objects with a more tightly focused beam (for example of photons or electrons) can provide higher-resolution images. However the stronger localisation of energy deposition can damage tissues in organic samples or may rearrange the chemical structure or physical properties of inorganic materials. Scanning an object with a broad beam can deliver an equivalent probe energy but spreads it over a much wider footprint. Sharp images can be reconstructed from the diffuse implanted signal when a decoding step can recover a delta-like impulse response. Huffman sequences, by design, have the optimal delta-like autocorrelation for aperiodic (non-cyclic) convolution and are well-conditioned. Here we adapt 1D Huffman sequences to design 2D Huffman-like discrete arrays that have spatially broad, relatively thin and uniform intensity profiles that retain excellent aperiodic autocorrelation metrics. Examples of broad shaped diffuse beams were developed for the case of x-ray imaging. A variety of masks were fabricated by the deposition of finely structured layers of tantalum on a silicon oxide wafer. The layers form a pattern of discrete pixels that modify the shape of an incident uniform beam of low energy x-rays as it passes through the mask. The intensity profiles of the x-ray beams after transmission through these masks were validated, first by acquiring direct-detector x-ray images of the masks, and second by raster scanning a pinhole over each mask pattern, pixel-by-pixel, collecting "bucket" signals as applied in traditional ghost imaging. The masks were then used to raster scan the shaped x-ray beam over several simple binary and "gray" test objects, again producing bucket signals, from which sharp reconstructed object images were obtained by deconvolving their bucket images.

physics.optics↗

arXiv2024

Separating edges from microstructure in X-ray dark-field imaging: Evolving and devolving perspectives via the X-ray Fokker-Planck equation

A key contribution to X-ray dark-field (XDF) is X-ray diffusion by sample structures smaller than the imaging system's spatial resolution. However, some XDF techniques report that resolvable sample edges also generate XDF. Speckle-based X-ray imaging (SBXI) extracts XDF by analyzing sample-imposed changes to a reference speckle pattern's visibility. We present an algorithm for SBXI (a variant of our Multimodal Intrinsic Speckle-Tracking (MIST) algorithm) capable of separating these two distinct XDF contrast mechanisms. The algorithm uses the 'devolving' X-ray Imaging Fokker-Planck equation as its forward model and then solves the associated multimodal inverse problem, to retrieve sample attenuation, phase, and XDF. Previous MIST variants were based on the evolving Fokker-Planck equation, which considers how a reference-speckle image is modified by introducing a sample. The devolving perspective instead considers how the image collected in the presence of the sample and speckle membrane optically flows in reverse, to generate the reference-speckle image when the sample is removed from the system. We compare single- and multiple-exposure multimodal retrieval algorithms from the two Fokker-Planck perspectives. We demonstrate that the devolving perspective can distinguish between two physically different XDF contrast mechanisms; unresolved microstructure- and sharp-edge-induced XDF. This was verified by applying the retrieval algorithms to two experimental data sets. We anticipate that this work will be useful in: Yielding a pair of complementary XDF images that separate sharp-edge diffuse scatter from unresolved microstructure diffuse scatter. XDF computed tomography, where the strong edge XDF can lead to tainting streaking artefacts. Sample preparation, as samples will not need to be embedded since the strong XDF edge signal seen between the sample and air can be separated out.

physics.optics↗

arXiv2024

Quantum and classical Fisher information in four-dimensional scanning transmission electron microscopy

We analyze the quantum limit of sensitivity in four-dimensional scanning transmission electron microscopy (4D-STEM), which has emerged as a favored technique for imaging the structure of a wide variety of materials, including biological and other radiation-sensitive materials. 4D-STEM is an indirect (computational) imaging technique, which uses a scanning beam, and records the scattering distribution in momentum (diffraction) space for each beam position. We find that, in measuring a sample's electrostatic potential, the quantum Fisher information from 4D-STEM can match that from real-space phase-contrast imaging. Near-optimum quantum Fisher information is achieved using a delocalized speckled probe. However, owing to the detection in the diffraction plane, 4D-STEM ultimately enables only about half of the quantum limit, whereas Zernike phase-contrast imaging enables the quantum limit for all spatial frequencies admitted by the optical system. On the other hand, 4D-STEM can yield information on spatial frequencies well beyond those accessible by phase-contrast TEM. Our conclusions extend to analogous imaging modalities using coherent scalar visible light and x-rays.

physics.optics↗

arXiv2024

Single-exposure elemental differentiation and texture-sensitive phase-retrieval imaging with a neutron counting micro-channel plate detector

Micro-channel plate (MCP) detectors, when used at pulsed-neutron-source instruments, offer the possibility of high spatial resolution and high contrast imaging with pixel-level spectroscopic information. Here we demonstrate the possibility of multimodal analysis including total neutron cross-section spectra measurements, quantitative material differentiation imaging and texture-sensitive in-line phase imaging, from a single exposure using an MCP detector. This multimodal approach operates in full-field imaging mode, with the neutron transmission spectra acquired at each individual detector pixel. Due to the polychromatic nature of the beam and spectroscopic resolving capability of the detector, no energy scanning is required. Good agreement with the library reference data is demonstrated for neutron cross-section spectra measurements. Two different images corresponding to two selected energy bandwidths are used for elemental differentiation imaging. Moreover, the presence of changes in texture, i.e., preferred grain orientation, in the sample is identified from our phase-retrieval imaging results.

cond-mat.mtrl-sci↗

arXiv2023

Paraxial diffusion-field retrieval

Unresolved spatially-random microstructure, in an illuminated sample, can lead to position-dependent blur when an image of that sample is formed. For a small propagation distance, between the exit surface of the sample and the entrance surface of a position-sensitive detector, the paraxial approximation implies that the blurring influence of the sample may be modeled using an anomalous-diffusion field. This diffusion field may have a scalar or tensor character, depending on whether the random microstructure has an autocorrelation function that is rotationally isotropic or anisotropic, respectively. Partial differential equations are written down and then solved, in a closed-form manner, for several variants of the inverse problem of diffusion-field retrieval given suitable intensity images. Both uniform-illumination and structured-illumination schemes are considered. Links are made, between the recovered diffusion field and certain statistical properties of the unresolved microstructure. The developed theory -- which may be viewed as a crudely parallel form of small-angle scattering under the Guinier approximation -- is applicable to a range of paraxial radiation and matter fields, such as visible light, x rays, neutrons, and electrons.

physics.optics↗

arXiv2023

Universal mask for hard X rays

The penetrating power of X rays underpins important applications such as medical radiography. However, this same attribute makes it challenging to achieve flexible on-demand patterning of X-ray beams. One possible path to this goal is ``ghost projection'', a method which may be viewed as a reversed form of classical ghost imaging. This technique employs multiple exposures, of a single illuminated non-configurable mask that is transversely displaced to a number of specified positions, to create any desired pattern. An experimental proof-of-concept is given for this idea, using hard X rays. The written pattern is arbitrary, up to a tunable constant offset, and its spatial resolution is limited by both (i) the finest features present in the illuminated mask and (ii) inaccuracies in mask positioning and mask exposure time. In principle, the method could be used to make a universal lithographic mask in the hard-X-ray regime. Ghost projection might also be used as a dynamically-configurable beam-shaping element, namely the hard-X-ray equivalent of a spatial light modulator. The underpinning principle can be applied to gamma rays, neutrons, electrons, muons, and atomic beams. Our flexible approach to beam shaping gives a potentially useful means to manipulate such fields.

eess.IV↗