arXiv subjects

Mike Dunne

Publications and source records attributed to Mike Dunne.

15 recordsLinked to original sources

arXiv2025

femto-PIXAR: a neural network method for reconstruction of femtosecond X-ray free electron laser pulse energy

X-ray Free Electron Lasers (X\nobreakdash-FELs) operate in a wide range of lasing configurations for a broad variety of scientific applications at ultrafast time-scales such as structural biology, materials science, and atomic and molecular physics. Shot-by-shot characterization of the X-FEL pulses is crucial for analysis of many experiments as well as tuning the X-FEL performance. However, for the weak pulses found in advanced configurations, e.g. those needed for coherent, two-pulse studies of quantum materials, there is no current method for reliably resolving pulse profiles. Here we show that a physics-based U-net model can reconstruct the individual pulse power profiles for sub-picosecond pulse separation without the need for simulations. Using experimental data from weak X-FEL pulse pairs, we demonstrate we can learn the pulse characteristics on a shot-by-shot basis when conventional methods fail.

physics.acc-ph↗

arXiv2024

Dynamics of Nanoscale Phase Decomposition in Laser Ablation

Femtosecond laser ablation is a process that bears both fundamental physics interest and has wide industrial applications. For decades, the lack of probes on the relevant time and length scales has prevented access to the highly nonequilibrium phase decomposition processes triggered by laser excitation. Enabled by the unprecedented intense femtosecond X-ray pulses delivered by an X-ray free electron laser, we report here results of time-resolved small angle scattering measurements on the dynamics of nanoscale phase decomposition in thin gold films upon femtosecond laser-induced ablation. By analyzing the features imprinted onto the small angle diffraction patterns, the transient heterogeneous density distributions within the ablation plume as obtained from molecular dynamics simulations get direct experimental confirmation.

cond-mat.mtrl-sci↗

arXiv2023

Targeted materials discovery using Bayesian algorithm execution

Rapid discovery and synthesis of new materials requires intelligent data acquisition strategies to navigate large design spaces. A popular strategy is Bayesian optimization, which aims to find candidates that maximize material properties; however, materials design often requires finding specific subsets of the design space which meet more complex or specialized goals. We present a framework that captures experimental goals through straightforward user-defined filtering algorithms. These algorithms are automatically translated into one of three intelligent, parameter-free, sequential data acquisition strategies (SwitchBAX, InfoBAX, and MeanBAX). Our framework is tailored for typical discrete search spaces involving multiple measured physical properties and short time-horizon decision making. We evaluate this approach on datasets for TiO$_2$ nanoparticle synthesis and magnetic materials characterization, and show that our methods are significantly more efficient than state-of-the-art approaches.

cond-mat.mtrl-sci↗

arXiv2023

3D Heisenberg universality in the Van der Waals antiferromagnet NiPS$_3$

Van der Waals (vdW) magnetic materials are comprised of layers of atomically thin sheets, making them ideal platforms for studying magnetism at the two-dimensional (2D) limit. These materials are at the center of a host of novel types of experiments, however, there are notably few pathways to directly probe their magnetic structure. We report the magnetic order within a single crystal of NiPS$_3$ and show it can be accessed with resonant elastic X-ray diffraction along the edge of the vdW planes in a carefully grown crystal by detecting structurally forbidden resonant magnetic X-ray scattering. We find the magnetic order parameter has a critical exponent of $\beta\sim0.36$, indicating that the magnetism of these vdW crystals is more adequately characterized by the three-dimensional (3D) Heisenberg universality class. We verify these findings with first-principle density functional theory, Monte-Carlo simulations, and density matrix renormalization group calculations.

cond-mat.str-el↗

arXiv2023

On Ultrafast X-ray Methods for Magnetism

With the introduction of x-ray free electron laser sources around the world, new scientific approaches for visualizing matter at fundamental length and time-scales have become possible. As it relates to magnetism and "magnetic-type" systems, advanced methods are being developed for studying ultrafast magnetic responses on the time-scales at which they occur. We describe three capabilities which have the potential to seed new directions in this area and present original results from each: pump-probe x-ray scattering with low energy excitation, x-ray photon fluctuation spectroscopy, and ultrafast diffuse x-ray scattering. By combining these experimental techniques with advanced modeling together with machine learning, we describe how the combination of these domains allows for a new understanding in the field of magnetism. Finally, we give an outlook for future areas of investigation and the newly developed instruments which will take us there.

cond-mat.mtrl-sci↗

arXiv2023

Capturing dynamical correlations using implicit neural representations

The observation and description of collective excitations in solids is a fundamental issue when seeking to understand the physics of a many-body system. Analysis of these excitations is usually carried out by measuring the dynamical structure factor, S(Q, $\omega$), with inelastic neutron or x-ray scattering techniques and comparing this against a calculated dynamical model. Here, we develop an artificial intelligence framework which combines a neural network trained to mimic simulated data from a model Hamiltonian with automatic differentiation to recover unknown parameters from experimental data. We benchmark this approach on a Linear Spin Wave Theory (LSWT) simulator and advanced inelastic neutron scattering data from the square-lattice spin-1 antiferromagnet La$_2$NiO$_4$. We find that the model predicts the unknown parameters with excellent agreement relative to analytical fitting. In doing so, we illustrate the ability to build and train a differentiable model only once, which then can be applied in real-time to multi-dimensional scattering data, without the need for human-guided peak finding and fitting algorithms. This prototypical approach promises a new technology for this field to automatically detect and refine more advanced models for ordered quantum systems.

cond-mat.str-el↗

arXiv2023

MHD simulations of formation, sustainment and loss of Quiescent H-mode in the all-tungsten ASDEX Upgrade

Periodic edge localized modes (ELMs) are the non-linear consequences of pressure-gradient-driven ballooning modes and current-driven peeling modes becoming unstable in the pedestal region of high confinement fusion plasmas. In future tokamaks like ITER, large ELMs are foreseen to severely affect the lifetime of wall components as they transiently deposit large amounts of heat onto a narrow region at the divertor targets. Several strategies exist for avoidance, suppression, or mitigation of these instabilities, such as the naturally ELM-free quiescent H-mode (QH-mode). In the present article, an ASDEX Upgrade equilibrium that features a QH-mode is investigated through non-linear extended MHD simulations covering the dynamics over tens of milliseconds. The equilibrium is close to the ideal peeling limit and non-linearly develops saturated modes at the edge of the plasma. A dominant toroidal mode number of $n=1$ is found, for which the characteristic features of the edge harmonic oscillation are recovered. The saturated modes contribute to heat and particle transport preventing pedestal build-up to the ELM triggering threshold. The non-linear dynamics of the mode, in particular its interaction with the evolution of the edge safety factor is studied, which suggest a possible new saturation mechanism for the QH-mode. The simulations show good qualitative and quantitative agreement to experiments in AUG. In particular, the processes leading to the termination of QH-mode above a density threshold is studied, which results in the transition into an ELM regime. In the vicinity of this threshold, limit cycle oscillations are observed.

physics.plasm-ph↗

arXiv2022

Femtosecond-Terawatt Hard X Ray Pulse Generation with Chirped Pulse Amplification on a Free Electron Laser

Advances of high intensity lasers have opened up the field of strong field physics and led to a broad range of technological applications. Recent x ray laser sources and optics development makes it possible to obtain extremely high intensity and brightness at x ray wavelengths. In this paper, we present a system design that implements chirped pulse amplification for hard x ray free electron lasers. Numerical modeling with realistic experimental parameters show that near-transform-limit single-femtosecond hard x ray laser pulses with peak power exceeding 1 TW and brightness exceeding $4\times10^{35}~$s$^{-1}$mm$^{-2}$mrad$^{-2}$0.1\%bandwdith$^{-1}$ can be consistently generated. Realization of such beam qualities is essential for establishing systematic and quantitative understanding of strong field x-ray physics and nonlinear x ray optics phenomena.

physics.optics↗

arXiv2022

Testing the data framework for an AI algorithm in preparation for high data rate X-ray facilities

The advent of next-generation X-ray free electron lasers will be capable of delivering X-rays at a repetition rate approaching 1 MHz continuously. This will require the development of data systems to handle experiments at these type of facilities, especially for high throughput applications, such as femtosecond X-ray crystallography and X-ray photon fluctuation spectroscopy. Here, we demonstrate a framework which captures single shot X-ray data at the LCLS and implements a machine-learning algorithm to automatically extract the contrast parameter from the collected data. We measure the time required to return the results and assess the feasibility of using this framework at high data volume. We use this experiment to determine the feasibility of solutions for `live' data analysis at the MHz repetition rate.

physics.data-an↗

arXiv2022

CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images

Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in structural biology, helping us understand the basic building blocks of life. The algorithmic challenge of cryo-EM is to jointly estimate the unknown 3D poses and the 3D electron scattering potential of a biomolecule from millions of extremely noisy 2D images. Existing reconstruction algorithms, however, cannot easily keep pace with the rapidly growing size of cryo-EM datasets due to their high computational and memory cost. We introduce cryoAI, an ab initio reconstruction algorithm for homogeneous conformations that uses direct gradient-based optimization of particle poses and the electron scattering potential from single-particle cryo-EM data. CryoAI combines a learned encoder that predicts the poses of each particle image with a physics-based decoder to aggregate each particle image into an implicit representation of the scattering potential volume. This volume is stored in the Fourier domain for computational efficiency and leverages a modern coordinate network architecture for memory efficiency. Combined with a symmetrized loss function, this framework achieves results of a quality on par with state-of-the-art cryo-EM solvers for both simulated and experimental data, one order of magnitude faster for large datasets and with significantly lower memory requirements than existing methods.

cs.CV↗

arXiv2022

A machine learning photon detection algorithm for coherent X-ray ultrafast fluctuation analysis

X-ray free electron laser (XFEL) experiments have brought unique capabilities and opened new directions in research, such as creating new states of matter or directly measuring atomic motion. One such area is the ability to use finely spaced sets of coherent x-ray pulses to be compared after scattering from a dynamic system at different times. This enables the study of fluctuations in many-body quantum systems at the level of the ultrafast pulse durations, but this method has been limited to a select number of examples and required complex and advanced analytical tools. By applying a new methodology to this problem, we have made qualitative advances in three separate areas that will likely also find application to new fields. As compared to the `droplet-type' models which typically are used to estimate the photon distributions on pixelated detectors to obtain the coherent X-ray speckle patterns, our algorithm pipeline achieves an order of magnitude speedup on CPU hardware and two orders of magnitude improvement on GPU hardware. We also find that it retains accuracy in low-contrast conditions, which is the typical regime for many experiments in structural dynamics. Finally, it can predict photon distributions in high average-intensity applications, a regime which up until now, has not been accessible. Our AI-assisted algorithm will enable a wider adoption of x-ray coherence spectroscopies, by both automating previously challenging analyses and enabling new experiments that were not otherwise feasible without the developments described in this work.

physics.data-an↗

arXiv2022

Generation of highly mutually coherent hard x-ray pulse pairs with an amplitude-splitting delay line

Beam splitters and delay lines are among the key building blocks of modern-day optical laser technologies. Progress in x-ray free electron laser source development and applications over the past decade is calling for their counter part operating in the Angstrom wavelength regime. Recent efforts in x-ray optics development have demonstrated relatively stable delay lines that most often adopted the division of wavefront approach for the beam splitting and recombination configuration. However, the two recombined beams have yet to achieve sufficient mutual coherence to enable applications such as interferometry, correlation spectroscopy, and nonlinear spectroscopy. We present the first experimental realization of the generation of highly mutually coherent pulse pairs using an amplitude-split delay line design based on transmission grating beam splitters and channel-cut crystal optic delay lines. The performance of the prototype system was analyzed in the context of x-ray coherent scattering and correlation spectroscopy, where we obtained nearly identical high-contrast speckle patterns from both branches. We show in addition the high level of dynamical stability during continuous delay scans, a capability essential for high sensitivity ultra-fast measurements.

physics.optics↗

arXiv2021

Nanoscale heterogeneous dynamics probed by nanosecond x-ray speckle visibility spectroscopy

We report observations of nanosecond nanometer scale heterogeneous dynamics in a free flowing colloidal jet revealed by ultrafast x-ray speckle visibility spectroscopy. The nanosecond double-bunch mode of the Linac Coherent Light Source free electron laser enabled the production of pairs of femtosecond coherent hard x-ray pulses. By exploring the anisotropic summed speckle visibility which relates to the correlation functions, we are able to evaluate not only the average particle flow rate in a colloidal nanoparticle jet, but also the heterogeneous flow field within. The reported methodology presented here establishes the foundation for the study of nano- and atomic-scale heterogeneous fluctuations in complex matter using x-ray free electron laser sources.

cond-mat.soft↗

arXiv2020

Realizing split-pulse x-ray photon correlation spectroscopy to measure ultrafast dynamics in complex matter

Split-pulse x-ray photon correlation spectroscopy has been proposed as one of the unique capabilities made possible with the x-ray free electron lasers. It enables characterization of atomic scale structural dynamics that dictates the macroscopic properties of various disordered material systems. Central to the experimental concept are x-ray optics that are capable of splitting individual coherent femtosecond x-ray pulse into two distinct pulses, introduce an adjustable time delay between them, and then recombine the two pulses at the sample position such that they generate two coherent scattering patterns in rapid succession. Recent developments in such optics showed that, while true 'amplitude splitting' optics at hard x-ray wavelengths remains a technical challenge, wavefront and wavelength splitting are both feasible, able to deliver two micron sized focused beams to the sample with sufficient relative stability. Here, we however show that the conventional approach to speckle visibility spectroscopy using these beam splitting techniques can be problematic, even leading to a decoupling of speckle visibility and material dynamics. In response, we discuss the details of the experimental approaches and data analysis protocols for addressing issues caused by subtle beam dissimilarities for both wavefront and wavelength splitting setups. We also show that in some scattering geometries, the Q-space mismatch can be resolved by using two beams of slightly different incidence angle and slightly different wavelengths at the same time. Instead of measuring the visibility of weak speckle patterns, the time correlation in sample structure is encoded in the 'side band' of the spatial autocorrelation of the summed speckle patterns, and can be retrieved straightforwardly from the experimental data. We demonstrate this with a numerical simulation.

physics.ins-det↗

arXiv2019

Numerical study of tearing mode seeding in tokamak X-point plasma

A detailed understanding of island seeding is crucial to avoid (N)TMs and their negative consequences like confinement degradation and disruptions. In the present work, we investigate the growth of 2/1 islands in response to magnetic perturbations. Although we use externally applied perturbations produced by resonant magnetic perturbation (RMP) coils for this study, results are directly transferable to island seeding by other MHD instabilities creating a resonant magnetic field component at the rational surface. Experimental results for 2/1 island penetration from ASDEX Upgrade are presented extending previous studies. Simulations are based on an ASDEX Upgrade L-mode discharge with low collisionality and active RMP coils. Our numerical studies are performed with the 3D, two fluid, non-linear MHD code JOREK. All three phases of mode seeding observed in the experiment are also seen in the simulations: first a weak response phase characterized by large perpendicular electron flow velocities followed by a fast growth of the magnetic island size accompanied by a reduction of the perpendicular electron velocity, and finally the saturation to a fully formed island state with perpendicular electron velocity close to zero. Thresholds for mode penetration are observed in the plasma rotation as well as in the RMP coil current. A hysteresis of the island size and electron perpendicular velocity is observed between the ramping up and down of the RMP amplitude consistent with an analytically predicted bifurcation. The transition from dominant kink/bending to tearing parity during the penetration is investigated.

physics.plasm-ph↗