@article{64086, abstract = {{Abstract This study aimed to develop and evaluate deep learning approaches for the classification of quantum emission signals from WS 2 monolayer nanobubbles across multiple spectral bands, addressing challenges in quantum materials characterization and spectral distinguishability assessment. We utilized a dataset of quantum emission signals ranging from 604 to 629 nm, emitted from WS₂ monolayer nanobubbles on gold substrates, categorized into four spectral bands (604.06–608.24 nm, 611.07–616.34 nm, 617.42–623.35 nm, and 624.16–636.57 nm). Our methodology involved signal preprocessing through normalization and moving average smoothing, followed by transformation into 128 × 128 RGB images using Continuous Wavelet Transform (CWT) with Complex Morlet wavelet. Three convolutional neural network architectures (ResNet50, VGG16, and Xception) were implemented and evaluated using fivefold cross-validation across six possible band pair combinations. All models demonstrated exceptional classification performance, with VGG16 achieving the highest overall mean accuracy of 99.4%, followed by Xception (99.1%) and ResNet50 (98.2%). Perfect classification accuracy (100%) was consistently achieved for spectrally distant band pairs, particularly Band 1 versus Band 4 (20.5 nm separation), while the most challenging classification involved adjacent bands (Band 2 vs. Band 3, 6.27 nm separation) with VGG16 achieving 96.5% accuracy. Statistical analysis using Friedman tests confirmed significant performance differences among models (χ 2  = 8.67, p  = 0.013). Xception demonstrated remarkable computational efficiency, achieving optimal convergence in as few as 2 epochs for certain band combinations while maintaining ultralow training loss values (8.23 × 10⁻ 6 ). Deep learning models, particularly when combined with CWT preprocessing, provide a robust framework for quantum emission signal classification with significant implications for quantum photonics, quantum cryptography, and quantum sensing applications. Our approach bridges the gap between classical machine learning and quantum materials characterization, establishing quantifiable metrics for evaluating spectral distinguishability in quantum information systems. The demonstrated ability to achieve high classification accuracy with minimal training through transfer learning addresses data scarcity challenges inherent to quantum systems, offering a promising direction for future quantum technology development. }}, author = {{Najafzadeh, Hossein and Raissi, Zahra and Golmohammady, Shole and Kaji, Parivash Safari and Esmaeili, Mahdad}}, issn = {{2045-2322}}, journal = {{Scientific Reports}}, number = {{1}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Deep learning for classifying quantum emission signals in WS2 monolayers using wavelet transform}}}, doi = {{10.1038/s41598-025-29120-0}}, volume = {{15}}, year = {{2025}}, } @article{64081, abstract = {{Abstract Graph states are a fundamental class of multipartite entangled quantum states with wide-ranging applications in quantum information and computation. In this work, we develop a systematic approach for constructing and analyzing χ-colorable graph states, deriving explicit closed-form expressions for arbitrary χ. For a broad family of two- and three-colorable graph states, the representations obtained using only local operations require a minimal number of terms in the Z-eigenbasis. We prove that every two-colorable graph state is local Clifford (LC) equivalent to a state expressible as a summation of rows of an orthogonal array (OA). For graph states with χ > 2, we show that they are LC-equivalent to quantum OAs, establishing a direct combinatorial connection between multipartite entanglement and structured quantum states. Furthermore, the upper and lower bounds of the Schmidt measure for graph states with arbitrary χ colorability are discussed, extending the results for an arbitrary local dimension. Our results offer an efficient and practical method for systematically constructing graph states, optimizing their representation in quantum circuits, and identifying structured forms of multipartite entanglement. This approach also connects graph states to k-uniform and absolutely maximally entangled states, motivating further exploration of the structure of entangled states and their applications in quantum networks, quantum error correction, and measurement based quantum computing.}}, author = {{Revis, Konstantinos-Rafail and Zakaryan, Hrachya and Raissi, Zahra}}, issn = {{1751-8113}}, journal = {{Journal of Physics A: Mathematical and Theoretical}}, number = {{35}}, publisher = {{IOP Publishing}}, title = {{{χ-colorable graph states: closed-form expressions and quantum orthogonal arrays}}}, doi = {{10.1088/1751-8121/adfe45}}, volume = {{58}}, year = {{2025}}, } @article{64078, author = {{Zakaryan, Hrachya and Revis, Konstantinos-Rafail and Raissi, Zahra}}, issn = {{2469-9926}}, journal = {{Physical Review A}}, number = {{3}}, publisher = {{American Physical Society (APS)}}, title = {{{Nonsymmetric Greenberger-Horne-Zeilinger states: Weighted hypergraph and controlled-unitary graph representations}}}, doi = {{10.1103/7zxj-jp34}}, volume = {{112}}, year = {{2025}}, } @unpublished{64089, author = {{Revis, Konstantinos-Rafail and Zakaryan, Hrachya and Raissi, Zahra}}, booktitle = {{https://arxiv.org/pdf/2506.05478}}, title = {{{Orbit classification and analysis of qutrit graph states under local complementation and local scaling}}}, year = {{2025}}, } @unpublished{64091, author = {{ Bl ̈omer, Johannes and Xiao, Yinzi and Raissi, Zahra and Soltan, Stanislaw }}, booktitle = {{https://arxiv.org/pdf/2509.10183}}, title = {{{Symplectic Lattices and GKP Codes - Simple Randomized Constructions from Cryptographic Lattices}}}, year = {{2025}}, } @article{63745, abstract = {{Multimode squeezed light is an increasingly popular tool in photonic quantum technologies, including sensing, imaging, and computation. Meanwhile, the existing methods of its characterization are technically complicated, which reduces the level of squeezing, and mostly deal with a single mode at a time. Here, for the first time, to the best of our knowledge, we employ optical parametric amplification to characterize multiple squeezing eigenmodes simultaneously. We retrieve the shapes and squeezing degrees of all modes at once through direct detection followed by modal decomposition. This method is tolerant to inefficient detection and does not require a local oscillator. For a spectrally and spatially multimode squeezed vacuum, we characterize eight strongest spatial modes, obtaining squeezing and anti-squeezing values of up to −5.2 ± 0.2 dB and 8.6 ± 0.3 dB, respectively, despite the 50% detection loss. This work, being the first exploration of an optical parametric amplifier’s multimode capability for squeezing detection, paves the way for the real-time detection of multimode squeezing.}}, author = {{Barakat, Ismail and Kalash, Mahmoud and Scharwald, Dennis and Sharapova, Polina and Lindlein, Norbert and Chekhova, Maria}}, issn = {{2837-6714}}, journal = {{Optica Quantum}}, number = {{1}}, publisher = {{Optica Publishing Group}}, title = {{{Simultaneous measurement of multimode squeezing through multimode phase-sensitive amplification}}}, doi = {{10.1364/opticaq.524682}}, volume = {{3}}, year = {{2025}}, } @misc{63871, author = {{Vochatzer, Stefanie}}, booktitle = {{H-Soz-Kult}}, isbn = {{9781350269248}}, title = {{{Rezension zu: Wasmuth, Helge; Sauerbrey, Ulf; Winkler, Michael: Finding Froebel. The Man Who Invented Kindergarten. New York 2023 }}}, year = {{2025}}, } @inproceedings{62285, abstract = {{The sliding square model is a widely used abstraction for studying self-reconfigurable robotic systems, where modules are square-shaped robots that move by sliding or rotating over one another. In this paper, we propose a novel distributed algorithm that enables a group of modules to reconfigure into a rhombus shape, starting from an arbitrary side-connected configuration. It is connectivity-preserving and operates under minimal assumptions: one leader module, common chirality, constant memory per module, and visibility and communication restricted to immediate neighbors. Unlike prior work, which relaxes the original sliding square move-set, our approach uses the unmodified move-set, addressing the additional challenge of handling locked configurations. Our algorithm is sequential in nature and operates with a worst-case time complexity of O(n^2) rounds, which is optimal for sequential algorithms. To improve runtime, we introduce two parallel variants of the algorithm. Both rely on a spanning tree data structure, allowing modules to make decisions based on local connectivity. Our experimental results show a significant speedup for the first variant, and a linear average runtime for the second variant, which is worst-case optimal for parallel algorithms.}}, author = {{Kostitsyna, Irina and Liedtke, David Jan and Scheideler, Christian}}, booktitle = {{Stabilization, Safety, and Security of Distributed Systems}}, editor = {{Bonomi, Silvia and Mandal, Partha Sarathi and Robinson, Peter and Sharma, Gokarna and Tixeuil, Sebastien}}, isbn = {{9783032111265}}, issn = {{0302-9743}}, location = {{Kathmandu}}, pages = {{325--342}}, publisher = {{Springer Nature Switzerland}}, title = {{{Invited Paper: Distributed Rhombus Formation of Sliding Squares}}}, doi = {{10.1007/978-3-032-11127-2_26}}, year = {{2025}}, } @article{64098, author = {{Scheideler, Christian and Padalkin, Andreas and Kumar, Manish}}, journal = {{Reconfiguration and locomotion with joint movements in the amoebot model. Auton. Robots 49(3): 22 (2025)}}, title = {{{Reconfiguration and locomotion with joint movements in the amoebot model. Auton. Robots 49(3): 22 (2025)}}}, year = {{2025}}, } @inproceedings{64094, author = {{Scheideler, Christian and Artmann, Matthias and Maurer, Tobias and Padalkin, Andreas and Warner, Daniel}}, title = {{{AmoebotSim 2.0: A Visual Simulation Environment for the Amoebot Model with Reconfigurable Circuits and Joint Movements (Media Exposition). }}}, year = {{2025}}, } @inproceedings{64096, author = {{Scheideler, Christian and Dou, Jinfeng and Götte, Thorsten and Hillebrandt, Henning and Werthmann, Julian}}, title = {{{Distributed and Parallel Low-Diameter Decompositions for Arbitrary and Restricted Graphs. }}}, year = {{2025}}, } @book{64099, editor = {{Scheideler, Christian and Meeks, Kitty}}, title = {{{4th Symposium on Algorithmic Foundations of Dynamic Networks.}}}, year = {{2025}}, } @inproceedings{64097, author = {{Scheideler, Christian and Artmann, Matthias and Padalkin, Andreas}}, title = {{{On the Shape Containment Problem Within the Amoebot Model with Reconfigurable Circuits. }}}, year = {{2025}}, } @inproceedings{64095, author = {{Scheideler, Christian and Augustine , John and Werthmann, Julian}}, title = {{{Supervised Distributed Computing. }}}, year = {{2025}}, } @inproceedings{64112, author = {{Jalil, Farjana and Awais, Muhammad and Ahmed, Qazi Arbab and Mohammadi, Hassan Ghasemzadeh and Jungeblut, Thorsten and Platzner, Marco}}, booktitle = {{2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)}}, publisher = {{IEEE}}, title = {{{Deep&Wide: Achieving Area Efficiency in Scalable Approximate Accelerators}}}, doi = {{10.1109/dsn-w65791.2025.00048}}, year = {{2025}}, } @inproceedings{64113, author = {{Hadipour, Amir Hossein and Jafari, Atousa and Awais, Muhammad and Platzner, Marco}}, booktitle = {{2025 IEEE 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)}}, publisher = {{IEEE}}, title = {{{A Two-Stage Approximation Methodology for Efficient DNN Hardware Implementation}}}, doi = {{10.1109/ddecs63720.2025.11006769}}, year = {{2025}}, } @article{61825, abstract = {{Abstract Industrial x-ray computed tomography (CT) systems with high geometric flexibility are increasingly utilized for large-scale measurement objects or challenging measurement tasks. To maintain high accuracy when deviating from the established circular scan trajectory, trajectory calibration methods using multi-sphere reference objects with known marker positions are commonly employed. These multi-sphere objects can either be scanned together with the measurement object (online trajectory calibration) or in a separate scan (offline trajectory calibration). While offline calibration increases machine time, it generally results in higher scan quality. However, a sufficient pose repeatability is necessary to ensure comparable or even superior accuracy to online calibration. In this contribution, we present a straightforward procedure to compare both types of trajectory calibration in a way that the differences of the results can directly be traced back to the influence of the pose repeatability. The multi-sphere reference object is not only used for trajectory calibration, but simultaneously as a measurement object for repeated measurements. The methodology is tested on both a twin robotic CT system and a conventional CT system that is additionally equipped with a hexapod manipulator for adaptive object tilting. Results showed, independent from the type of trajectory calibration, systematic measurement errors in the order of 10−5–10−4 of measured sphere distances and sphericity values below 50 μ m . For sphere distances, random errors were increased by a factor of 5 due to the offline trajectory calibration, but were still low ( < 1 μ m ) in comparison to systematic errors and the spread of different measurement features. Overall, both investigated systems demonstrated sufficient positioning repeatability for offline trajectory calibration. The method is in general also applicable to any other types of manipulator systems used for CT devices. It provides a workflow for the decision which type of trajectory calibration is preferable for a given CT system.}}, author = {{Butzhammer, Lorenz and Handke, Niklas and Wittl, Simon and Herl, Gabriel and Hausotte, Tino}}, issn = {{0957-0233}}, journal = {{Measurement Science and Technology}}, number = {{2}}, publisher = {{IOP Publishing}}, title = {{{Direct assessment of the influence of pose repeatability on the accuracy of dimensional measurements for computed tomography systems with high degrees of freedom}}}, doi = {{10.1088/1361-6501/ada05a}}, volume = {{36}}, year = {{2025}}, } @inproceedings{64145, author = {{Newberry, Melissa and Jonas-Ahrend, Gabriela and Rizvi, Meher and van der Want, Anna}}, location = {{Glasgow}}, title = {{{The Dynamics of Geographic Space when working with International Teacher Educators in Collaborative Research}}}, year = {{2025}}, } @inproceedings{64143, author = {{Guberman, Ainat and Jonas-Ahrend, Gabriela and Arvif-Elyashiv, Rinat and Ben-Yehduah, Gal and Cyprus, Dominik}}, location = {{Belgrad}}, title = {{{Career Changing STEM Teachers` Motivation over Time: Lessons from Israel and Germany}}}, year = {{2025}}, } @inproceedings{64142, author = {{Ratnam, Tara and Jonas-Ahrend, Gabriela and Newberry, Melissa}}, location = {{Denver/CO, USA}}, title = {{{The presence of an Invisible College in the knowledge network of ISATT}}}, year = {{2025}}, }