arXiv subjects

Harry M. Quiney

Publications and source records attributed to Harry M. Quiney.

At least 19 recordsLinked to original sources

arXiv2026

Fast Patient-Specific Breast CT Dosimetry: 22-Fold Acceleration of Monte Carlo MGD Estimation

Accurate patient-specific mean glandular dose (MGD) estimation in breast computed tomography (BCT) requires anatomically realistic models, but high-resolution patient-derived phantoms impose high computational demands on Monte Carlo (MC) dosimetry. We previously developed and validated an EGSnrc-based framework for synchrotron propagation-based phase-contrast BCT (PB-PCT) for the first-in-human study at the Australian Synchrotron. With participant imaging commencing, this study aimed to optimize phantom spatial resolution and MC efficiency while maintaining MGD accuracy, for a rapid patient-specific dosimetry. Four patient-specific heterogeneous breast phantoms with varying volume and glandularity were generated from PB-PCT images of mastectomy specimens acquired at 35 keV. The highest-resolution phantom for each specimen served as the reference. Phantoms were downsampled by increasing in-plane voxel size and slice thickness, and MGD was recalculated using EGSnrc/DOSXYZnrc. A 4.5% difference from reference MGD was adopted as the accuracy criterion. Primary photon histories were then reduced to determine the minimum required for acceptable MC precision. A common voxel size of 0.30 x 0.30 x 3.00 mm3 maintained MGD within 4.5% of reference for all four phantoms while reducing voxel number by approximately 20-31-fold. MGD was more sensitive to in-plane voxel size than slice thickness, supporting anisotropic downsampling. Reduced-resolution phantoms enabled a 15-fold reduction in photon histories to 2 x 10^8 while maintaining acceptable statistical uncertainty. Combined optimization reduced computation time from approximately 1600 to 72 min, a 22-fold acceleration. Patient-specific phantoms can be substantially downsampled while maintaining MGD accuracy and markedly reducing computational burden. This optimization provides a foundation for future real-time patient-specific BCT dosimetry.

physics.med-ph↗

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

Reduced density matrix approach to one-dimensional ultracold bosonic systems

The variational determination of the two-boson reduced density matrix is described for a one-dimensional system of $N$ (where $N$ ranges from $2$ to $10^4$) harmonically trapped bosons interacting via contact interaction. The ground-state energies are calculated, and compared to existing methods in the field, including the analytic case (for $N=2)$ and mean-field approaches such as the one-dimensional Gross-Pitaevskii equation and its variations. Structural properties including the density and correlation functions are also derived, including the behaviour of the correlation function when boson coordinates coincide, collectively demonstrating the capacity of the reduced density matrix method to accurately calculate ground-state properties of bosonic systems comprising few to many bosons, including the cross-over region between these extremes, across a large range of interaction strengths.

cond-mat.quant-gas↗

arXiv2026

Development and Validation of Patient-Specific Monte Carlo Dosimetry for Synchrotron Breast Phase-Contrast CT

This study develops and validates a patient-specific Monte Carlo (MC) dosimetry framework for propagation-based phase-contrast breast CT (BCT) at the Imaging and Medical Beamline (IMBL), ANSTO Australian Synchrotron, for accurate mean glandular dose (MGD) estimation. BCT provides 3D imaging without breast compression, improving comfort and visualization of internal structures for cancer detection. Propagation-based phase contrast improves soft-tissue contrast at equal or lower dose than conventional systems. Accurate dosimetry remains essential for safety and optimisation. Most MC-based MGD studies use non-patient-specific phantoms that ignore anatomical variability, while existing patient-specific methods lack a unified framework. Here, a voxel-based MC framework using EGSnrc was implemented to compute MGD in realistic anthropomorphic breast phantoms derived from synchrotron BCT images. IMBL beam characteristics were used as source inputs. Homogeneous phantoms were also generated to compute air Kerma to MGD conversion coefficients (DgN) for comparison with heterogeneous models. Simulations covered breast height, skin thickness, and photon energies (28 to 38 keV). Results show MGD depends strongly on anatomy and energy. Higher glandular density reduces MGD, while larger breast volume increases dose. A 2 mm increase in skin thickness reduces MGD by 10%. Differences between heterogeneous and homogeneous phantoms show variations in DgN, highlighting the need for anatomical realism. The framework provides a robust basis for patient-specific dosimetry in synchrotron phase-contrast BCT, enabling precise MGD estimation and supporting safe, optimised clinical imaging. This supports improved protocol design and contributes to standardised patient-specific dosimetry for clinical translation across varying breast anatomies and imaging conditions within synchrotron BCT applications.

physics.med-ph↗

arXiv2026

Wichmann-Kroll vacuum polarization correction to lithium-like systems in a Gaussian basis set

Recent developments have seen the application of finite Gaussian basis sets to the $α(Zα)^{n\geq3}$ vacuum polarization. The energy shift for $s$ and $p$ electron states have been tabulated and their convergence investigated. In this work, we extend this problem to the multi-electron case. Hartee-Fock potentials obtained self-consistently are used to treat the vacuum polarization for lithium-like systems and are found to be in good agreement with comparable results in the literature. The results presented in this work demonstrate the use of Gaussian basis sets for atomic potentials whose Green's functions expressions cannot be simply obtained via analytic or numerical methods.

physics.atom-ph↗

arXiv2026

Quantum Jacobi-Davidson Method

Computing electronic structures of quantum systems is a key task underpinning many applications in photonics, solid-state physics, and quantum technologies. This task is typically performed through iterative algorithms to find the energy eigenstates of a Hamiltonian, which are usually computationally expensive and suffer from convergence issues. In this work, we develop and implement the Quantum Jacobi-Davidson (QJD) method and its quantum diagonalization variant, the Sample-Based Quantum Jacobi-Davidson (SBQJD) method, and demonstrate their fast convergence for ground state energy estimation. We assess the intrinsic algorithmic performance of our methods through exact numerical simulations on a variety of quantum systems, including 8-qubit diagonally dominant matrices, 12-qubit one-dimensional Ising models, and a 10-qubit water molecule (H$_2$O) Hamiltonian. Our results show that both QJD and SBQJD achieve significantly faster convergence and require fewer Pauli measurements compared to the recently reported Quantum Davidson method, with SBQJD further benefiting from optimized reference state preparation. These findings establish the QJD framework as an efficient general-purpose subspace-based technique for solving quantum eigenvalue problems, providing a promising foundation for sparse Hamiltonian calculations on future fault-tolerant quantum hardware.

quant-ph↗

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

Moments-based quantum computation of the electric dipole moment of molecular systems

With rapid progress being made in the development of platforms for quantum computation, there has been considerable interest in whether present-day and near-term devices can be used to solve problems of relevance. A commonly cited application area is the domain of quantum chemistry. While most experimental demonstrations of quantum chemical calculations on quantum devices have focused on the ground-state electronic energy of the system, other properties of the ground-state, such as the electric dipole moment, are also of interest. Here we employ the quantum computed moments (QCM) method, based on the Lanczos cluster expansion, to estimate the dipole moment of the water molecule on an IBM Quantum superconducting quantum device. The noise-mitigated results agree with full configuration interaction (FCI) calculations to within 0.03 $\pm$ 0.007 debye (2% $\pm$ 0.5%), compared to direct expectation value determination (i.e. VQE) with errors on the order of 0.07 debye (5%), even when the VQE calculation is performed without noise. This demonstrates that moments-based energy estimation techniques can be adapted to noise-robust evaluation of non-energetic ground-state properties of chemical systems.

quant-ph↗

arXiv2025

Symmetry-Checking in Band Structure Calculations on a Noisy Quantum Computer

Band crossings in electronic band structures play an important role in determining the electronic, topological, and transport properties in solid-state systems, making them central to both condensed matter physics and materials science. The emergence of noisy intermediate-scale quantum (NISQ) processors has sparked great interest in developing quantum algorithms to compute band structure properties of materials. While significant research has been reported on computing ground state and excited state energy bands in the presence of noise that breaks the degeneracy, identifying the symmetry at crossing points using quantum computers is still an open question. In this work, we propose a method for identifying the symmetry of bands around crossings and anti-crossings in the band structure of bilayer graphene with two distinct configurations on a NISQ device. The method utilizes eigenstates at neighbouring $\mathbf{k}$ points on either side of the touching point to recover the local symmetry by implementing a character-checking quantum circuit that uses ancilla qubit measurements for a probabilistic test. We then evaluate the performance of our method under a depolarizing noise model, using four distinct matrix representations of symmetry operations to assess its robustness. Finally, we demonstrate the reliability of our method by correctly identifying the correct band crossings of AA-stacked bilayer graphene around $K$ point, using the character-checking circuit implemented on a noisy IBM quantum processor $ibm\_marrakesh$.

quant-ph↗

arXiv2025

Heavy-element damage seeding in proteins under XFEL illumination

Serial femtosecond X-ray crystallography (SFX) captures the structure and dynamics of biological macromolecules at high spatial and temporal resolutions. The ultrashort pulse produced by an X-ray free electron laser (XFEL) 'outruns' much of the radiation damage that impairs conventional crystallography. However, the rapid onset of 'electronic damage' due to ionization limits this benefit. Here, we distinguish the influence of different atomic species on the ionization of protein crystals by employing a plasma code that tracks the unbound electrons as a continuous energy distribution. The simulations show that trace quantities of heavy atoms (Z > 10) contribute a substantial proportion of global radiation damage by rapidly seeding electron ionization cascades. In a typical protein crystal, sulfur atoms and solvated salts induce a substantial fraction of light-atom ionization. In further modeling of various targets, global ionization peaks at photon energies roughly 2 keV above inner-shell absorption edges, as sub-2 keV photoelectrons ejected from these shells initiate ionization cascades that are briefer than the XFEL pulse. These results indicate that relatively small quantities of heavy elements can substantially affect global radiation damage in XFEL experiments.

physics.plasm-ph↗

arXiv2025

Towards order of magnitude X-ray dose reduction in breast cancer imaging using phase contrast and deep denoising

Breast cancer is the most frequently diagnosed human cancer in the United States at present. Early detection is crucial for its successful treatment. X-ray mammography and digital breast tomosynthesis are currently the main methods for breast cancer screening. However, both have known limitations in terms of their sensitivity and specificity to breast cancers, while also frequently causing patient discomfort due to the requirement for breast compression. Breast computed tomography is a promising alternative, however, to obtain high-quality images, the X-ray dose needs to be sufficiently high. As the breast is highly radiosensitive, dose reduction is particularly important. Phase-contrast computed tomography (PCT) has been shown to produce higher-quality images at lower doses and has no need for breast compression. It is demonstrated in the present study that, when imaging full fresh mastectomy samples with PCT, deep learning-based image denoising can further reduce the radiation dose by a factor of 16 or more, without any loss of image quality. The image quality has been assessed both in terms of objective metrics, such as spatial resolution and contrast-to-noise ratio, as well as in an observer study by experienced medical imaging specialists and radiologists. This work was carried out in preparation for live patient PCT breast cancer imaging, initially at specialized synchrotron facilities.

physics.med-ph↗

arXiv2024

Comparison of three reconstruction algorithms for low-dose phase-contrast computed tomography of the breast with synchrotron radiation

Three different computed tomography (CT) reconstruction algorithms: Filtered Back Projection (FBP), Unified Tomographic Reconstruction (UTR) and customized Simultaneous Algebraic Reconstruction Technique (cSART), have been systematically compared and evaluated using experimental data from CT scans of ten fresh mastectomy samples collected at the Imaging and Medical beamline of the Australian Synchrotron. All the scans were collected at the mean glandular dose of 2 mGy, using monochromatic X-rays with 32 keV energy, flat-panel detectors with 0.1 mm pixels and 6 meter distance between the rotation stage and the detector. Paganin's phase retrieval method was used in conjunction with all three CT reconstruction algorithms. The reconstructed images were compared in terms of the objective image quality characteristics, including spatial resolution, contrast, signal-to-noise, and contrast-to-noise ratios. The images were also evaluated by seven experienced medical imaging specialists, rating perceptible contrast, sharpness of tissue interfaces, image noise, calcification visibility and overall image quality. Of the three compared algorithms, cSART was clearly superior to UTR and FBP in terms of most measured objective image quality characteristics. At the same time, the results of the subjective quality evaluation consistently favoured the images reconstructed by FBP, followed by UTR, with cSART receiving lower scores on average. We argue that this apparent disagreement between the objective and subjective assessments of image quality can be explained by the importance assigned to image contrast in the subjective assessment, while the signal-to-noise ratio seemed to receive relatively low weighting. This study was conducted in preparation for phase-contrast breast CT imaging of live patients at Australian Synchrotron (Melbourne, Australia).

physics.med-ph↗

arXiv2024

Full Band Structure Calculation of Semiconducting Materials on a Noisy Quantum Processor

Quantum chemistry is a promising application in the era of quantum computing since the unique effects of quantum mechanics that take exponential growing resources to simulate classically are controllable on quantum computers. Fermionic degrees of freedom can be encoded efficiently onto qubits and allow for algorithms such as the Quantum Equation-of-Motion method to find the entire energy spectrum of a quantum system. In this paper, we propose the Reduced Quantum Equation-of-Motion method by reducing the dimensionality of its generalized eigenvalue equation, which results in half the measurements required compared to the Quantum Equation-of-Motion method, leading to speed up the algorithm and less noise accumulation on real devices. In particular, we analyse the performance of our method on two noise models and calculate the excitation energies of a bulk Silicon and Gallium Arsenide using our method on an IBM quantum processor. Our method is fully robust to the uniform depolarizing error and we demonstrate that the selection of suitable atomic orbital complexity could increase the robustness of our algorithm under real noise. We also find that taking the average of multiple experiments tends towards the correct energies due to the fluctuations around the exact values. Such noise resilience of our approach could be used on current quantum devices to solve quantum chemistry problems.

quant-ph↗

arXiv2023

Precise predictions and new insights for atomic ionisation from the Migdal effect

The scattering of neutral particles by an atomic nucleus can lead to electronic ionisation and excitation through a process known as the Migdal effect. We revisit and improve upon previous calculations of the Migdal effect, using the Dirac-Hartree-Fock method to calculate the atomic wavefunctions. Our methods do not rely on the use of the dipole approximation, allowing us to present robust results for higher nuclear recoil velocities than was previously possible. Our calculations provide the theoretical foundations for future measurements of the Migdal effect using neutron sources, and searches for dark matter in direct detection experiments. We show that multiple ionisation must be taken into account in experiments with fast neutrons, and derive the semi-inclusive probability for processes that yield a hard electron above a defined energy threshold. We present results for the noble elements up to and including xenon, as well as carbon, fluorine, silicon and germanium. The transition probabilities from our calculations are publicly available.

hep-ph↗

arXiv2022

Fast unified reconstruction algorithm for conventional, phase-contrast and diffraction tomography

A unified method for three-dimensional reconstruction of objects from transmission images collected at multiple illumination directions is described. The method may be applicable to experimental conditions relevant to absorption-based, phase-contrast or diffraction imaging using X-rays, electrons and other forms of penetrating radiation or matter waves. Both the phase retrieval (also known as contrast transfer function correction) and the effect of Ewald sphere curvature (in the cases with a shallow depth of field and significant in-object diffraction) are incorporated in the proposed algorithm and can be taken into account. Multiple scattering is not treated explicitly, but can be mitigated as a result of angular averaging that constitutes an essential feature of the method. The corresponding numerical algorithm is based on three-dimensional gridding which allows for fast computational implementation, including a straightforward parallelization. The algorithm can be used with any scanning geometry involving plane-wave illumination. A software code implementing the proposed algorithm has been developed, tested on simulated and experimental image data and made publicly available.

physics.med-ph↗

arXiv2022

Reduced density matrix approach to ultracold few-fermion systems in one dimension

The variational determination of the two-fermion reduced density matrix is described for harmonically trapped, ultracold few-fermion systems in one dimension with equal spin populations. This is accomplished by formulating the problem as a semi-definite program, with the two-fermion reduced density matrix being subject to well-known $N$-representability conditions. The ground-state energies, as well as the density, pair-correlation function, and lower-order eigenvalues of the two-fermion reduced density matrix of various fermionic systems are found by utilising an augmented Lagrangian method for semi-definite programming. The ground-state energies are found to match well to those determined by full-configuration interaction and coupled-cluster calculations and the density, pair-correlation function, and eigenvalue results demonstrate that the salient features of these systems are well-described by this method. These results collectively demonstrate the utility of the reduced density matrix method firstly in describing strong correlation arising from short-range interactions, suggesting that the well-known N-representability conditions are sufficient to model ultracold fermionic systems, and secondly in illustrating the prospect of treating larger systems currently out of the reach of established methods.

cond-mat.quant-gas↗

arXiv2020

Ptychographic X-ray Speckle Tracking

We present a method for the measurement of the phase gradient of a wavefront by tracking the relative motion of speckles in projection holograms as a sample is scanned across the wavefront. By removing the need to obtain an un-distorted reference image of the sample, this method is suitable for the metrology of highly divergent wavefields. Such wavefields allow for large magnification factors, that, according to current imaging capabilities, will allow for nano-radian angular sensitivity and nano-scale sample projection imaging. Both the reconstruction algorithm and the imaging geometry are nearly identical to that of ptychography, except that the sample is placed downstream of the beam focus and that no coherent propagation is explicitly accounted for. Like other x-ray speckle tracking methods, it is robust to low-coherence x-ray sources making is suitable for lab based x-ray sources. Likewise it is robust to errors in the registered sample positions making it suitable for x-ray free-electron laser facilities, where beam pointing fluctuations can be problematic for wavefront metrology. We also present a modified form of the speckle tracking approximation, based on a second-order local expansion of the Fresnel integral. This result extends the validity of the speckle tracking approximation and may be useful for similar approaches in the field.

physics.optics↗

arXiv2020

speckle-tracking: a Software Suite for Ptychographic X-ray Speckle Tracking

In recent years, x-ray speckle tracking techniques have emerged as viable tools for wavefront metrology and sample imaging applications. These methods are based on the measurement of near-field images. Thanks to the simple experimental set-up, high angular sensitivity and compatibility with low coherence sources these methods have been actively developed for use with synchrotron and laboratory light sources. Not only do speckle-tracking techniques give the potential for high resolution imaging, but they also provide rapid and robust characterisation of aberrations of x-ray optical elements, focal spot profiles and the sample position and transmission properties. In order to realise these capabilities, we require software implementations that are equally rapid and robust. To address this need, a software suite has been developed for the "ptychographic x-ray speckle tracking technique" -- an x-ray speckle based method suitable for highly divergent wavefields. The software suite is written in Python 3, with an OpenCL back end for GPU and multi-CPU core processing. It is accessible as a Python module, through the command line or through a graphical user interface and is available as source code under version 3 or later of the GNU General Public License.

eess.IV↗