Julian Zimmermann

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Zimmermann

First Name

Julian

ORCID

0000-0002-4784-1013

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Publications1 - 6 of 6

Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning
Zimmermann, Julian; Beguet, Fabien; Guthruf, Daniel; et al. (2023)
npj Computational Materials
Single-shot coherent diffraction imaging of isolated nanosized particles has seen remarkable success in recent years, yielding in-situ measurements with ultra-high spatial and temporal resolution. The progress of high-repetition-rate sources for intense X-ray pulses has further enabled recording datasets containing millions of diffraction images, which are needed for the structure determination of specimens with greater structural variety and dynamic experiments. The size of the datasets, however, represents a monumental problem for their analysis. Here, we present an automatized approach for finding semantic similarities in coherent diffraction images without relying on human expert labeling. By introducing the concept of projection learning, we extend self-supervised contrastive learning to the context of coherent diffraction imaging and achieve a dimensionality reduction producing semantically meaningful embeddings that align with physical intuition. The method yields substantial improvements compared to previous approaches, paving the way toward real-time and large-scale analysis of coherent diffraction experiments at X-ray free-electron lasers.
SPRING, an effective and reliable framework for image reconstruction in single-particle Coherent Diffraction Imaging
Colombo, Alessandro; Sauppe, Mario; Al Haddad, Andre; et al. (2025)
npj Computational Materials
Coherent Diffraction Imaging (CDI) is an experimental technique to image isolated structures by recording the scattered light. The sample density can be recovered from the scattered field through a Fourier Transform operation. However, the phase of the field is lost during the measurement and has to be algorithmically retrieved. Here we present SPRING, an analysis framework tailored to X-ray Free Electron Laser (XFEL) single-shot single-particle diffraction data that implements the Memetic Phase Retrieval method to mitigate the shortcomings of conventional algorithms. We benchmark the approach on data acquired in two experimental campaigns at SwissFEL and European XFEL. Results reveal unprecedented stability and resilience of the algorithm’s behavior on the input parameters, and the capability of identifying the solution in conditions hardly treatable with conventional methods. A user-friendly implementation of SPRING is released as open-source software, aiming at being a reference tool for the CDI community at XFEL and synchrotron facilities.
Laser-Induced Transient Opacity in Helium Nanodroplets Probed by Single-Shot Coherent Diffraction
Zimmermann, Julian; von Scheven, Tom; Colombo, Alessandro; et al. (2026)
Ultrafast Science
Single-shot coherent diffractive imaging with intense short-wavelength light pulses enables the structural characterization of individual nanoparticles in free flight with high spatial and temporal resolution. Conventional coherent diffractive imaging assumes that the target object exhibits a linear scattering response and static electronic properties. Here, we extend this approach to investigating transient-laser-driven modifications of the electronic structure in individual nanoparticles, imprinted in their time-resolved diffraction patterns. In the presence of a near-infrared laser pulse, we observe a pronounced reduction in the diffraction signal from helium nanodroplets when probed with ultrashort extreme ultraviolet pulses. This effect is attributed to a light-field-induced modification of the electronic structure of the droplets, which substantially increases their extreme ultraviolet absorption. Our results demonstrate the possibility to capture ultrafast light-driven electron dynamics in nanoscale systems with single-particle diffraction. This opens a pathway toward the spatiotemporal tracking of reversible changes in the electronic properties of nanoscale structures with potential applications in ultrafast x-ray optics, materials science, and all-optical signal processing.
Visualizing the strong field-induced molecular breakup of C60 via x-ray diffraction
Schnorr , Kirsten; Augustin, Sven; Saalmann , Ulf; et al. (2025)
Science Advances
Laser-driven dynamics in polyatomic molecules poses a complex many-body problem. Understanding intense light-matter interaction is crucial for steering intramolecular quantum dynamical processes. Here, we record time-resolved x-ray diffraction images of C₆₀ molecules during and after their interaction with intense near-infrared fields, giving direct access to structural changes of the molecules and their fragmentation in real time. Tuning the intensity of the excitation pulses, we uncover a transition from a weak-field regime of excited but stable molecules to a high-field regime dominated by Coulomb explosion. In the transition region, the molecules expand by up to 50% of their initial size within just 140 fs, with major fragmentation only setting in afterward. This work demonstrates that x-ray diffractive imaging is capable of retrieving time-resolved structural information of large molecules reshaped by intense laser fields. Laser-driven fragmentation is a first step toward observing molecular processes modified by laser fields of increasing intensity.
The Scatman: an approximate method for fast wide-angle scattering simulations
Colombo, Alessandro; Zimmermann, Julian; Langbehn, Bruno; et al. (2022)
arXiv
Single-shot Coherent Diffraction Imaging (CDI) is a powerful approach to characterize the structure and dynamics of isolated nanoscale objects such as single viruses, aerosols, nanocrystals or droplets. Using X-ray wavelengths, the diffraction images in CDI experiments usually cover only small scattering angles of few degrees. These small-angle patterns repre sent the magnitude of the Fourier transform of the two-dimensional projec tion of the sample’s electron density, which can be reconstructed efficiently but lacks any depth information. In cases where the diffracted signal can be measured up to scattering angles exceeding ∼ 10 ◦ , i.e. in the wide angle regime, three-dimensional morphological information of the target is contained in a single-shot diffraction pattern. However, the extraction of the 3D structural information is no longer straightforward and defines the key challenge in wide-angle CDI. So far, the most convenient approach relies on iterative forward fitting of the scattering pattern using scatter ing simulations. Here we present the Scatman, an approximate and fast numerical tool for the simulation and iterative fitting of wide-angle scat tering images of isolated samples. Furthermore, we publish and describe in detail our Open Source software implementation of the Scatman algo rithm, PyScatman. The Scatman approach, which was alreadin previous works for forward-fitting-based shape retrieval, adopts the Multi-Slice Fourier Transform method. The effects of optical properties are partially included, yielding quantitative results for weakly scattering samples. PyScatman is capable of computing wide-angle scattering pat terns in few milliseconds even on consumer-level computing hardware. The high computational efficiency of PyScatman enables effective data analysis based on model fitting, thus representing an important step to wards a systematic application of 3D Coherent Diffraction Imaging from single wide-angle diffraction patterns in various scientific communities.
The Scatman: an approximate method for fast wide-angle scattering simulations
Colombo, Alessandro; Zimmermann, Julian; Langbehn, Bruno; et al. (2022)
Journal of Applied Crystallography
Single-shot coherent diffraction imaging (CDI) is a powerful approach to characterize the structure and dynamics of isolated nanoscale objects such as single viruses, aerosols, nanocrystals and droplets. Using X-ray wavelengths, the diffraction images in CDI experiments usually cover only small scattering angles of a few degrees. These small-angle patterns represent the magnitude of the Fourier transform of the 2D projection of the sample's electron density, which can be reconstructed efficiently but lacks any depth information. In cases where the diffracted signal can be measured up to scattering angles exceeding ∼10°, i.e. in the wide-angle regime, some 3D morphological information of the target is contained in a single-shot diffraction pattern. However, the extraction of the 3D structural information is no longer straightforward and defines the key challenge in wide-angle CDI. So far, the most convenient approach relies on iterative forward fitting of the scattering pattern using scattering simulations. Here the Scatman is presented, an approximate and fast numerical tool for the simulation and iterative fitting of wide-angle scattering images of isolated samples. Furthermore, the open-source software implementation of the Scatman algorithm, PyScatman, is published and described in detail. The Scatman approach, which has already been applied in previous work for forward-fitting-based shape retrieval, adopts the multi-slice Fourier transform method. The effects of optical properties are partially included, yielding quantitative results for small, isolated and weakly interacting samples. PyScatman is capable of computing wide-angle scattering patterns in a few milliseconds even on consumer-level computing hardware, potentially enabling new data analysis schemes for wide-angle coherent diffraction experiments.

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Julian Zimmermann

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