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Chatzikiriakos","R. Strässer","F. Allgöwer","A. Iannelli" ], "authors": [ {"first" : "N.", "last" : "Chatzikiriakos"}, {"first" : "R.", "last" : "Strässer"}, {"first" : "F.", "last" : "Allgöwer"}, {"first" : "A.", "last" : "Iannelli"} ], "volume": "187","pages": "112908", "issn" : "0005-1098", "doi" : "https://doi.org/10.1016/j.automatica.2026.112908", "bibtexKey": "ist:chatzikiriakos2026a" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d61ac4ff294df0cf9b9ce586467fed47/simtechpuma", "tags" : [ "EXC2075","selected" ], "intraHash" : "d61ac4ff294df0cf9b9ce586467fed47", "interHash" : "248ee718b67ac04a232cadce1ab36b35", "label" : "A Sequence-Specific Theory for Charge-Regulating IDPs", "user" : "simtechpuma", "description" : "", "date" : "2026-04-13 14:54:39", "changeDate" : "2026-04-13 14:54:39", "count" : 5, "pub-type": "article", "publisher":"American Chemical Society (ACS)", "year": "2026", "url": "http://dx.doi.org/10.26434/chemrxiv.10001808/v1", "author": [ "David Beyer","Christian Holm","Zhen-Gang Wang" ], "authors": [ {"first" : "David", "last" : "Beyer"}, {"first" : "Christian", "last" : "Holm"}, {"first" : "Zhen-Gang", "last" : "Wang"} ], "doi" : "10.26434/chemrxiv.10001808/v1", "bibtexKey": "Beyer_2026" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2c091f0cf33ec38011d10b1cf1d23675d/simtechpuma", "tags" : [ "EXC2075","PN1","PN1-9","misc" ], "intraHash" : "c091f0cf33ec38011d10b1cf1d23675d", "interHash" : "a77ff59f6b35ff08d6fd1e5bf9199e23", "label" : "Weak-Strong Uniqueness and Relaxation Limit for a \nNavier-Stokes-Korteweg Model", "user" : "simtechpuma", "description" : "", "date" : "2026-02-16 15:04:58", "changeDate" : "2026-02-16 15:04:58", "count" : 5, "pub-type": "misc", "year": "2025", "url": "https://arxiv.org/abs/2512.09719", "author": [ "Nilasis Chaudhuri","Christian Rohde","Florian Wendt" ], "authors": [ {"first" : "Nilasis", "last" : "Chaudhuri"}, {"first" : "Christian", "last" : "Rohde"}, {"first" : "Florian", "last" : "Wendt"} ], "eprint" : "2512.09719", "archiveprefix" : "arXiv", "primaryclass" : "math.AP", "bibtexKey": "chaudhuri_rohde_wendt2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/29b091e58d887b01cc35e5307b50b35d3/simtechpuma", "tags" : [ "EXC2075","PN3","PN3-12","misc" ], "intraHash" : "9b091e58d887b01cc35e5307b50b35d3", "interHash" : "7a08336fac06bfd1654d2cf489cf0a8c", "label" : "MLIPX: Machine Learned Interatomic Potential eXploration", "user" : "simtechpuma", "description" : "", "date" : "2026-02-16 15:04:58", "changeDate" : "2026-02-16 15:04:58", "count" : 5, "pub-type": "article", "publisher":"American Chemical Society (ACS)", "year": "2025", "url": "http://dx.doi.org/10.26434/chemrxiv-2025-0v720", "author": [ "Fabian Zills","Sheena Agarwal","Tiago Goncalves","Srishti Gupta","Edvin Fako","Shuang Han","Imke Mueller","Christian Holm","Sandip De" ], "authors": [ {"first" : "Fabian", "last" : "Zills"}, {"first" : "Sheena", "last" : "Agarwal"}, {"first" : "Tiago", "last" : "Goncalves"}, {"first" : "Srishti", "last" : "Gupta"}, {"first" : "Edvin", "last" : "Fako"}, {"first" : "Shuang", "last" : "Han"}, {"first" : "Imke", "last" : "Mueller"}, {"first" : "Christian", "last" : "Holm"}, {"first" : "Sandip", "last" : "De"} ], "doi" : "10.26434/chemrxiv-2025-0v720", "bibtexKey": "Zills_2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d42fc0ab5d6a88c0cffb25979392ae21/simtechpuma", "tags" : [ "EXC2075","PN1","PN1-4","PN1-4(II)","misc" ], "intraHash" : "d42fc0ab5d6a88c0cffb25979392ae21", "interHash" : "758ce45c4c73dff3eb736709714dc18f", "label" : "Primary drainage experiments and fractal dimensions", "user" : "simtechpuma", "description" : "", "date" : "2026-02-16 15:04:58", "changeDate" : "2026-02-16 15:04:58", "count" : 6, "pub-type": "misc", "year": "2024", "url": "", "author": [ "Nikolaos Karadimitriou","Dongwon Lee","Samaneh Vahid Dastjerdi","Holger Steeb" ], "authors": [ {"first" : "Nikolaos", "last" : "Karadimitriou"}, {"first" : "Dongwon", "last" : "Lee"}, {"first" : "Samaneh", "last" : "Vahid Dastjerdi"}, {"first" : "Holger", "last" : "Steeb"} ], "abstract": "The current repository contains raw data in the shape of images collected during a systematic laboratory study, examining the usability of the fractal dimension in the characterization of the flow regime. The study is presented in the paper by Karadimitriou et al., 2024. The two fluids were the wetting phase (WP), FluorinertTM, FC-43, and the non-wetting phase (NWP), deionized water mixed with ink, and occasionally with a specific amount of Glycerol. The wetting phase was initially introduced into the pore space of a Poly-Di-Methyl-Siloxane (PDMS) micromodel, fully saturating it. Then, primary drainage scenarios were realized with the introduction of the non-wetting phase under controlled-flux conditions. The objective of the study was to investigate the usability of the fractal dimension of various geometrical entities, like the interfaces between phases, and the bulk non-wetting phase occupancy of the pore space, in the characterization of the flow regime. Main data: The dataset is populated with the raw images acquired during a primary drainage process. Every drainage process took place under a fixed boundary volumetric flux, which is depicted in the title of each file, in terms of the corresponding capillary number. Additionally, the title of each file also includes the viscosity ratio between the invading and the defending phase. A typical file name is in the form Ca=***,M=***.tar. In the images, the non-wetting phase, namely water, shows as dark, and the wetting phase, namely Fluorinert, shows as transparent within the boundaries of the pore network. Flow takes place from right to left. Procedure followed for each constant Ca and M experiment: The term \u201Cexperiment\u201D pertains to the breakthrough of the non-wetting phase from its own inlet to the outlet, at a constant boundary flux. For every experiment, a fixed capillary number value, Cai, i = 1,2,3, is maintained, whereas the viscosity ratio between the invading and the defending phase remains the same through a single experiment. In order for the viscosity ratio to be fixed on demand, Glycerol was added to water at specific concentrations, so as to achieve the desired viscosity of water. The Ca used were 10-2, 10-3, 10-4, and 10-5. The viscosity ratios used were 0.2, 1, and 10. The flow network has overall dimensions of 15 by 20 millimeters, with a mean pore size of 410 microns, and a depth of 100 microns. It is an exact replication of the network used in the work of Sivanesapillai et al., 2018. The micromodel is initially saturated with the wetting phase. Then, the non-wetting phase is injected into the microfluidic pore network. The non-wetting phase is injected at a fixed volumetric flux to maintain a constant value of the capillary number, Ca, during the entire experiment. The wetting phase is getting passively displaced during this process. Even though the experiment, for the needs of the corresponding publication, concludes at breakthrough, some more images are acquired for future purposes.", "affiliation" : "Karadimitriou, Nikolaos/University of Stuttgart, Lee, Dongwon/University of Stuttgart, Vahid Dastjerdi, Samaneh/University of Stuttgart, Steeb, Holger/University of Stuttgart", "orcid-numbers" : "Karadimitriou, Nikolaos/0000-0002-9461-6214, Lee, Dongwon/0000-0003-4826-1632, Vahid Dastjerdi, Samaneh/0000-0003-0315-4067, Steeb, Holger/0000-0001-7602-4920", "doi" : "10.18419/darus-4114", "bibtexKey": "karadimitriou2024primary" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/234069d20ab6c202113bf77f9459017de/simtechpuma", "tags" : [ "EXC2075","selected" ], "intraHash" : "34069d20ab6c202113bf77f9459017de", "interHash" : "f4fe87ded4a090956c4461f9a32db0af", "label" : "Optimized Predictive Coverage by Averaging Time-Windowed Bayesian Distributions", "user" : "simtechpuma", "description" : "", "date" : "2026-02-16 15:04:58", "changeDate" : "2026-02-16 15:04:58", "count" : 8, "pub-type": "article", "journal": "Water Resources Research","publisher":"Wiley", "year": "2024", "url": "", "author": [ "Han-Fang Hsueh","Anneli Guthke","Thomas Wöhling","Wolfgang Nowak" ], "authors": [ {"first" : "Han-Fang", "last" : "Hsueh"}, {"first" : "Anneli", "last" : "Guthke"}, {"first" : "Thomas", "last" : "Wöhling"}, {"first" : "Wolfgang", "last" : "Nowak"} ], "volume": "60","number": "5","pages": "e2022WR033280", "language" : "eng", "issn" : "1944-7973 and 0043-1397", "doi" : "10.1029/2022WR033280", "bibtexKey": "hsueh2024optimized" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2092846c63dd93a995bc518498e3282ce/simtechpuma", "tags" : [ "EXC2075","PN8","PN8-3","misc" ], "intraHash" : "092846c63dd93a995bc518498e3282ce", "interHash" : "ba34e41c75ec5ddd320cf4594272c194", "label" : "Quantum vs. classical: A comprehensive benchmark study for predicting time series with variational quantum machine learning", "user" : "simtechpuma", "description" : "", "date" : "2026-02-16 15:04:58", "changeDate" : "2026-02-16 15:04:58", "count" : 5, "pub-type": "article", "journal": "Machine Learning: Science and Technology", "year": "2026", "url": "https://doi.org/10.1088/2632-2153/ae365f", "author": [ "Tobias Fellner","David Kreplin","Samuel Tovey","Christian Holm" ], "authors": [ {"first" : "Tobias", "last" : "Fellner"}, {"first" : "David", "last" : "Kreplin"}, {"first" : "Samuel", "last" : "Tovey"}, {"first" : "Christian", "last" : "Holm"} ], "abstract": "Variational quantum machine learning algorithms have been proposed as promising tools for time series prediction, with the potential to handle complex sequential data more effectively than classical approaches. However, their practical advantage over established classical methods remains uncertain. In this work, we present a comprehensive benchmark study comparing a range of variational quantum algorithms and classical machine learning models for time series forecasting. We evaluate their predictive performance on three chaotic systems across 27 time series prediction tasks of varying complexity, and ensure a fair comparison through extensive hyperparameter optimization. Our results indicate that, in many cases, quantum models struggle to match the accuracy of simple classical counterparts of comparable complexity. Furthermore, we analyze the predictive performance relative to the model complexity and discuss the practical limitations of variational quantum algorithms for time series forecasting.", "eprint" : "2504.12416", "archiveprefix" : "arXiv", "primaryclass" : "quant-ph", "doi" : "10.1088/2632-2153/ae365f", "bibtexKey": "Fellner_2026" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2925b63c636fac32711b8933dd38dc992/simtechpuma", "tags" : [ "EXC2075","PN3","PN3A-1","selected" ], "intraHash" : "925b63c636fac32711b8933dd38dc992", "interHash" : "bc7a090cbd1692c4438fb1083794df8c", "label" : "SwarmRL: building the future of smart active systems", "user" : "simtechpuma", "description" : "SwarmRL: building the future of smart active systems | The European Physical Journal E", "date" : "2026-02-16 15:04:58", "changeDate" : "2026-02-16 15:04:58", "count" : 5, "pub-type": "article", "journal": "The European Physical Journal E", "year": "2025", "url": "https://doi.org/10.1140/epje/s10189-025-00477-4", "author": [ "Samuel Tovey","Christoph Lohrmann","Tobias Merkt","David Zimmer","Konstantin Nikolaou","Simon Koppenhöfer","Anna Bushmakina","Jonas Scheunemann","Christian Holm" ], "authors": [ {"first" : "Samuel", "last" : "Tovey"}, {"first" : "Christoph", "last" : "Lohrmann"}, {"first" : "Tobias", "last" : "Merkt"}, {"first" : "David", "last" : "Zimmer"}, {"first" : "Konstantin", "last" : "Nikolaou"}, {"first" : "Simon", "last" : "Koppenhöfer"}, {"first" : "Anna", "last" : "Bushmakina"}, {"first" : "Jonas", "last" : "Scheunemann"}, {"first" : "Christian", "last" : "Holm"} ], "volume": "48","number": "4","pages": "16","abstract": "This work introduces SwarmRL, a Python package designed to study intelligent active particles. SwarmRL provides an easy-to-use interface for developing models to control microscopic colloids using classical control and deep reinforcement learning approaches. These models may be deployed in simulations or real-world environments under a common framework. We explain the structure of the software and its key features and demonstrate how it can be used to accelerate research. With SwarmRL, we aim to streamline research into micro-robotic control while bridging the gap between experimental and simulation-driven sciences. SwarmRL is available open-source on GitHub at https://github.com/SwarmRL/SwarmRL.", "issn" : "1292-895X", "doi" : "10.1140/epje/s10189-025-00477-4", "bibtexKey": "Tovey2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/24f6272dacff0a8b7d70a21c5cab4bb0d/simtechpuma", "tags" : [ "EXC2075","PN1","PN1-4","PN1-4(II)","misc" ], "intraHash" : "4f6272dacff0a8b7d70a21c5cab4bb0d", "interHash" : "9ed24f75b1aa449f6d403b7ae80c2b77", "label" : "In situ micro-XRCT data set of an open-cell polyurethane foam sample under uniaxial compression load", "user" : "simtechpuma", "description" : "", "date" : "2026-02-16 15:04:58", "changeDate" : "2026-02-16 15:04:58", "count" : 6, "pub-type": "misc", "year": "2024", "url": "", "author": [ "Matthias Ruf","Holger Steeb" ], "authors": [ {"first" : "Matthias", "last" : "Ruf"}, {"first" : "Holger", "last" : "Steeb"} ], "note": "Related to: Ruf, M., Steeb, H., & Karadimitriou, N. (2023). Visualization of the uniaxial compression of open-cell foams. In Médici, E.F., & Otero, A.D. (eds.): Album of Porous Media, Springer International Publishing, Cham, Switzerland, 117-117. doi: 10.1007/978-3-031-23800-0_97","abstract": "This dataset contains seven micro X-Ray Computed Tomography (micro-XRCT) scan data sets (projection, reconstructed, and segmented images, respectively) of an open-cell reticulated Polyurethane (PUR) foam specimen with 10 pores per inch under different uniaxial deformation states. The initial diameter and length of the unloaded cylindrical sample are 52 mm and 50 mm. The sample was glued on two aluminum sample holders. Scans of the sample were performed for seven successive time steps (t0, t1, t2, t3, t4, t5, t6) under uniaxial displacements of 0, 5, 10, 15, 20, 25, 0 mm imposed at the bottom part of the sample (fixed upper sample holder). Before starting the image acquisition at the different deformation states, the sample was relaxed for 20 min each time. The relaxation curves (including relaxation during the scan) are provided in the files \"t*_utm_data.csv\". The scans were performed displacement-controlled.The image data sets are labeled according to the time step the micro-XRCT scan was performed (t0, t1, t2, t3, t4, t5, t6) followed by a specification of the image data set (\"_projections\", \"_reconstructed\", \"_segmented\"). Due to an eccentricity error between the upper and lower rotational table, compensation in the reconstruction was necessary. That was restricted to the foam part and not to the sample holders. Besides the projection images and the 3d reconstructed images, segmented images (into foam skeleton and void space) are provided. To reduce the data size, the foam sample was extracted by a cylinder of 52.36 diameter. Due to strong beam hardening in the aluminum sample holders, superimposed with cone-beam angle artifacts in those areas, and additional contaminated foam by the used glue in the transition region, only 44.26 mm in the axial direction of the foam sample at t0 (undeformed state) is given. For all other deformation states, the first and last slices of the segmented image stacks correspond roughly to them.After the image acquisition and a sufficiently long relaxation of the sample, a uniaxial compression test up to 30 mm maximum displacement was performed using the same sample. Loading/unloading was performed displacement controlled with |0.5| mm/s. The data is provided in the file \"utm_data.csv\".", "affiliation" : "Ruf, Matthias/University of Stuttgart, Institute of Applied Mechanics (CE), Steeb, Holger/University of Stuttgart, Institute of Applied Mechanics (CE) & SC SimTech", "orcid-numbers" : "Ruf, Matthias/0000-0003-0299-5921, Steeb, Holger/0000-0001-7602-4920", "doi" : "10.18419/darus-3010", "bibtexKey": "ruf2024microxrct" } ] }