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Hotz, Ingrid, ProfessorORCID iD iconorcid.org/0000-0001-7285-0483
Alternative names
Publications (10 of 91) Show all publications
Laniel, D., Trybel, F., Yin, Y., Fedotenko, T., Khandarkhaeva, S., Aslandukov, A., . . . Doubrovinckaia, N. (2023). Aromatic hexazine [N6]4− anion featured in the complex structure of the high-pressure potassium nitrogen compound K9N56. Nature Chemistry, 15(5), 641-646
Open this publication in new window or tab >>Aromatic hexazine [N6]4− anion featured in the complex structure of the high-pressure potassium nitrogen compound K9N56
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2023 (English)In: Nature Chemistry, ISSN 1755-4330, E-ISSN 1755-4349, Vol. 15, no 5, p. 641-646Article in journal (Refereed) Published
Abstract [en]

The recent high-pressure synthesis of pentazolates and the subsequent stabilization of the aromatic [N-5](-) anion at atmospheric pressure have had an immense impact on nitrogen chemistry. Other aromatic nitrogen species have also been actively sought, including the hexaazabenzene N-6 ring. Although a variety of configurations and geometries have been proposed based on ab initio calculations, one that stands out as a likely candidate is the aromatic hexazine anion [N-6](4-). Here we present the synthesis of this species, realized in the high-pressure potassium nitrogen compound K9N56 formed at high pressures (46 and 61 GPa) and high temperature (estimated to be above 2,000 K) by direct reaction between nitrogen and KN3 in a laser-heated diamond anvil cell. The complex structure of K9N56-composed of 520 atoms per unit cell-was solved based on synchrotron single-crystal X-ray diffraction and corroborated by density functional theory calculations. The observed hexazine anion [N-6](4-) is planar and proposed to be aromatic.

Place, publisher, year, edition, pages
NATURE PORTFOLIO, 2023
National Category
Materials Chemistry
Identifiers
urn:nbn:se:liu:diva-192227 (URN)10.1038/s41557-023-01148-7 (DOI)000944103300001 ()36879075 (PubMedID)
Funder
German Research Foundation (DFG), LA-4916/1-1German Research Foundation (DFG), DU393-9/2German Research Foundation (DFG), DU954-11/1German Research Foundation (DFG), DU393-9/2Swedish Research Council Formas, 2019-05600
Note

Funding: Alexander von Humboldt Foundation; Deutsche Forschungsgemeinschaft (DFG) [LA-4916/1-1, DU 954-11/1, DU 393-9/2, DU 393-13/1]; UKRI Future Leaders Fellowship [MR/V025724/1]; Federal Ministry of Education and Research, Germany (BMBF) [05K19WC1]; Swedish Research Council (VR) [2019-05600]; Swedish Government Strategic Research Areas in Materials Science on Functional Materials at Linkoeping University [2009 00971]; SeRC; Knut and Alice Wallenberg Foundation (Wallenberg Scholar grant) [KAW-2018.0194]

Available from: 2023-03-07 Created: 2023-03-07 Last updated: 2024-03-19Bibliographically approved
Sharma, M., Masood, T. B., Sidwall Thygesen, S., Linares, M., Hotz, I. & Natarajan, V. (2023). Continuous Scatterplot Operators for Bivariate Analysis and Study of Electronic Transitions. IEEE Transactions on Visualization and Computer Graphics
Open this publication in new window or tab >>Continuous Scatterplot Operators for Bivariate Analysis and Study of Electronic Transitions
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2023 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506Article in journal (Refereed) Epub ahead of print
Abstract [en]

Electronic transitions in molecules due to the absorption or emission of light is a complex quantum mechanical process. Their study plays an important role in the design of novel materials. A common yet challenging task in the study is to determine the nature of electronic transitions, namely which subgroups of the molecule are involved in the transition by donating or accepting electrons, followed by an investigation of the variation in the donor-acceptor behavior for different transitions or conformations of the molecules. In this paper, we present a novel approach for the analysis of a bivariate field and show its applicability to the study of electronic transitions. This approach is based on two novel operators, the continuous scatterplot (CSP) lens operator and the CSP peel operator, that enable effective visual analysis of bivariate fields. Both operators can be applied independently or together to facilitate analysis. The operators motivate the design of control polygon inputs to extract fiber surfaces of interest in the spatial domain. The CSPs are annotated with a quantitative measure to further support the visual analysis. We study different molecular systems and demonstrate how the CSP peel and CSP lens operators help identify and study donor and acceptor characteristics in molecular systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Bivariate field analysis, Continuous scatterplot, Fiber surface, Control polygon, Visual analysis, Electronic transitions
National Category
Computer Sciences Human Computer Interaction Atom and Molecular Physics and Optics Materials Chemistry
Identifiers
urn:nbn:se:liu:diva-194721 (URN)10.1109/tvcg.2023.3237768 (DOI)2-s2.0-85147261210 (Scopus ID)
Available from: 2023-06-09 Created: 2023-06-09 Last updated: 2023-06-16Bibliographically approved
Yan, L., Masood, T. B., Rasheed, F., Hotz, I. & Wang, B. (2023). Geometry Aware Merge Tree Comparisons for Time-Varying Data with Interleaving Distances. IEEE Transactions on Visualization and Computer Graphics, 29(8), 3489-3506
Open this publication in new window or tab >>Geometry Aware Merge Tree Comparisons for Time-Varying Data with Interleaving Distances
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2023 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 29, no 8, p. 3489-3506Article in journal (Refereed) Published
Abstract [en]

Merge trees, a type of topological descriptor, serve to identify and summarize the topological characteristics associated with scalar fields. They present a great potential for the analysis and visualization of time-varying data. First, they give compressed and topology-preserving representations of data instances. Second, their comparisons provide a basis for studying the relations among data instances, such as their distributions, clusters, outliers, and periodicities. A number of comparative measures have been developed for merge trees. However, these measures are often computationally expensive since they implicitly consider all possible correspondences between critical points of the merge trees. In this paper, we perform geometry-aware comparisons of merge trees. The main idea is to decouple the computation of a comparative measure into two steps: a labeling step that generates a correspondence between the critical points of two merge trees, and a comparison step that computes distances between a pair of labeled merge trees by encoding them as matrices. We show that our approach is general, computationally efficient, and practically useful. Our general framework makes it possible to integrate geometric information of the data domain in the labeling process. At the same time, it reduces the computational complexity since not all possible correspondences have to be considered. We demonstrate via experiments that such geometry-aware merge tree comparisons help to detect transitions, clusters, and periodicities of a time-varying dataset, as well as to diagnose and highlight the topological changes between adjacent data instances.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Merge trees, merge tree metrics, topological data analysis, topology in visualization
National Category
Computer Sciences Human Computer Interaction Geometry
Identifiers
urn:nbn:se:liu:diva-194719 (URN)10.1109/tvcg.2022.3163349 (DOI)001022080200004 ()35349444 (PubMedID)2-s2.0-85127499657 (Scopus ID)
Note

Funding: DOE [DE-SC0021015]; NSF [IIS 1910733]; Swedish e-Science Research Center (SeRC); Excellence Center at Linkoping - Lund in Information Technology (ELLIIT); Swedish Research Council [2019-05487]; Wallenberg AI, Autonomous Systems and Software Program (WASP)

Available from: 2023-06-09 Created: 2023-06-09 Last updated: 2023-08-30Bibliographically approved
Sidwall Thygesen, S., Abrikosov, A. I., Steneteg, P., Masood, T. B. & Hotz, I. (2023). Level of Detail Visual Analysis of Structures in Solid-State Materials. In: Thomas Hoellt, Wolfgang Aigner, and Bei Wang (Ed.), EuroVis 2023 - Short Papers: . Paper presented at EuroVis 2023. The Eurographics Association
Open this publication in new window or tab >>Level of Detail Visual Analysis of Structures in Solid-State Materials
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2023 (English)In: EuroVis 2023 - Short Papers / [ed] Thomas Hoellt, Wolfgang Aigner, and Bei Wang, The Eurographics Association , 2023Conference paper, Published paper (Refereed)
Abstract [en]

We propose a visual analysis method for the comparison and evaluation of structures in solid-state materials based on the electron density field using topological analysis. The work has been motivated by a material science application, specifically looking for new so-called layered materials whose physical properties are required in many modern technological developments. Due to the incredibly large search space, this is a slow and tedious process, requiring efficient data analysis to characterize and understand the material properties. The core of our proposed analysis pipeline is an abstract bar representation that serves as a concise signature of the material, supporting direct comparison and also an exploration of different material candidates.

Place, publisher, year, edition, pages
The Eurographics Association, 2023
Keywords
Visualization, solid-state materials, charge density, topological data analysis
National Category
Computer Sciences Human Computer Interaction
Identifiers
urn:nbn:se:liu:diva-196474 (URN)10.2312/evs.20231043 (DOI)
Conference
EuroVis 2023
Funder
Swedish Research Council, 2019-05487Swedish e‐Science Research CenterELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsWallenberg AI, Autonomous Systems and Software Program (WASP)
Available from: 2023-08-08 Created: 2023-08-08 Last updated: 2023-08-08
Nilsson, E., Lukasczyk, J., Engelke, W., Masood, T. B., Svensson, G., Caballero, R., . . . Hotz, I. (2022). Exploring Cyclone Evolution with Hierarchical Features. In: 2022 IEEE WORKSHOP ON TOPOLOGICAL DATA ANALYSIS AND VISUALIZATION (TOPOINVIS 2022): . Paper presented at IEEE VIS Workshop on Topological Data Analysis and Visualization (TopoInVis), Oklahoma City, OK, oct 17, 2022 (pp. 92-102). IEEE
Open this publication in new window or tab >>Exploring Cyclone Evolution with Hierarchical Features
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2022 (English)In: 2022 IEEE WORKSHOP ON TOPOLOGICAL DATA ANALYSIS AND VISUALIZATION (TOPOINVIS 2022), IEEE , 2022, p. 92-102Conference paper, Published paper (Refereed)
Abstract [en]

The problem of tracking and visualizing cyclones is still an active area of climate research, since the nature of cyclones varies depending on geospatial location and temporal season, resulting in no clear mathematical definition. Thus, many cyclone tracking methods are tailored to specific datasets and therefore do not support general cyclone extraction across the globe. To address this challenge, we present a conceptual application for exploring cyclone evolution by organizing the extracted cyclone tracks into hierarchical groups. Our approach is based on extrema tracking, and the resulting tracks can be defined in a multi-scale structure by grouping the points based on a novel feature descriptor defined on the merge tree, so-called crown features. Consequently, multiple parameter settings can be visualized and explored in a level-of-detail approach, supporting experts to quickly gain insights on cyclonic formation and evolution. We describe a general cyclone exploration pipeline that consists of four modular building blocks: (1) an extrema tracking method, (2) multiple definitions of cyclones as groups of extrema, including crown features, (3) the correlation of cyclones based on the underlying tracking information, and (4) a hierarchical visualization of the resulting feature tracks and their spatial embedding, allowing exploration on a global and local scale. In order to be as flexible as possible, our pipeline allows for exchanging every module with different techniques, such as other tracking methods and cyclone definitions.

Place, publisher, year, edition, pages
IEEE, 2022
Keywords
Human-centered computing; Visualization; Visualization design and evaluation methods; Human-centered computing; Visualization; Visualization application domains; Scientific visualization
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-191881 (URN)10.1109/TopoInVis57755.2022.00016 (DOI)000913326500010 ()9781665493543 (ISBN)9781665493550 (ISBN)
Conference
IEEE VIS Workshop on Topological Data Analysis and Visualization (TopoInVis), Oklahoma City, OK, oct 17, 2022
Note

Funding Agencies|SeRC (Swedish e-Science Research Center); ELLIIT environment for strategic research in Sweden; Swedish Research Council (VR) [2019-05487]

Available from: 2023-02-22 Created: 2023-02-22 Last updated: 2023-06-09
Klötzl, D., Krake, T., Zhou, Y., Hotz, I., Wang, B. & Weiskopf, D. (2022). Local bilinear computation of Jacobi sets. The Visual Computer, 38, 3435-3448
Open this publication in new window or tab >>Local bilinear computation of Jacobi sets
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2022 (English)In: The Visual Computer, ISSN 0178-2789, E-ISSN 1432-2315, Vol. 38, p. 3435-3448Article in journal (Refereed) Published
Abstract [en]

We propose a novel method for the computation of Jacobi sets in 2D domains. The Jacobi set is a topological descriptor based on Morse theory that captures gradient alignments among multiple scalar fields, which is useful for multi-field visualization. Previous Jacobi set computations use piecewise linear approximations on triangulations that result in discretization artifacts like zig-zag patterns. In this paper, we utilize a local bilinear method to obtain a more precise approximation of Jacobi sets by preserving the topology and improving the geometry. Consequently, zig-zag patterns on edges are avoided, resulting in a smoother Jacobi set representation. Our experiments show a better convergence with increasing resolution compared to the piecewise linear method. We utilize this advantage with an efficient local subdivision scheme. Finally, our approach is evaluated qualitatively and quantitatively in comparison with previous methods for different mesh resolutions and across a number of synthetic and real-world examples.

Place, publisher, year, edition, pages
Springer, 2022
Keywords
Jacobi set; Topological data analysis; Multi-fields; Visualization techniques
National Category
Media Engineering
Identifiers
urn:nbn:se:liu:diva-187499 (URN)10.1007/s00371-022-02557-4 (DOI)000819263900001 ()
Note

Funding Agencies|Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [DFG 270852890-GRK 2160/2, DFG 251654672-TRR 161]; Swedish Research Council (VR) [2019-05487]; U.S. Department of Energy (DOE) [DOE DE-SC0021015]; National Science Foundation (NSF) [NSF IIS-1910733]

Available from: 2022-08-25 Created: 2022-08-25 Last updated: 2023-02-28Bibliographically approved
Rasheed, F., Jönsson, D., Nilsson, E., Masood, T. B. & Hotz, I. (2022). Subject-Specific Brain Activity Analysis in fMRI Data Using Merge Trees. In: 2022 IEEE WORKSHOP ON TOPOLOGICAL DATA ANALYSIS AND VISUALIZATION (TOPOINVIS 2022): . Paper presented at IEEE VIS Workshop on Topological Data Analysis and Visualization (TopoInVis), Oklahoma City, OK, oct 17, 2022 (pp. 113-123). IEEE
Open this publication in new window or tab >>Subject-Specific Brain Activity Analysis in fMRI Data Using Merge Trees
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2022 (English)In: 2022 IEEE WORKSHOP ON TOPOLOGICAL DATA ANALYSIS AND VISUALIZATION (TOPOINVIS 2022), IEEE , 2022, p. 113-123Conference paper, Published paper (Refereed)
Abstract [en]

We present a method for detecting patterns in time-varying functional magnetic resonance imaging (fMRI) data based on topological analysis. The oxygenated blood flow measured by fMRI is widely used as an indicator of brain activity. The signal is, however, prone to noise from various sources. Random brain activity, physiological noise, and noise from the scanner can reach a strength comparable to the signal itself. Thus, extracting the underlying signal is a challenging process typically approached by applying statistical methods. The goal of this work is to investigate the possibilities of recovering information from the signal using topological feature vectors directly based on the raw signal without medical domain priors. We utilize merge trees to define a robust feature vector capturing key features within a time step of fMRI data. We demonstrate how such a concise feature vector representation can be utilized for exploring the temporal development of brain activations, connectivity between these activations, and their relation to cognitive tasks.

Place, publisher, year, edition, pages
IEEE, 2022
Keywords
fMRI data analysis; data abstraction; temporal data; feature detection; merge tree; computational topology-based techniques
National Category
Signal Processing Computer Sciences Human Computer Interaction
Identifiers
urn:nbn:se:liu:diva-191883 (URN)10.1109/TopoInVis57755.2022.00018 (DOI)000913326500012 ()9781665493543 (ISBN)9781665493550 (ISBN)
Conference
IEEE VIS Workshop on Topological Data Analysis and Visualization (TopoInVis), Oklahoma City, OK, oct 17, 2022
Note

Funding Agencies|Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; SeRC (Swedish e-Science Research Center); ELLIIT environment for strategic research in Sweden; Swedish Research Council (VR) [2019-05487]

Available from: 2023-02-23 Created: 2023-02-23 Last updated: 2023-06-09
Nilsson, E., Lukasczyk, J., Masood, T. B., Garth, C. & Hotz, I. (2022). Towards Benchmark Data Generation for Feature Tracking in Scalar Fields. In: 2022 IEEE WORKSHOP ON TOPOLOGICAL DATA ANALYSIS AND VISUALIZATION (TOPOINVIS 2022): . Paper presented at IEEE VIS Workshop on Topological Data Analysis and Visualization (TopoInVis), Oklahoma City, OK, oct 17, 2022 (pp. 103-112). IEEE
Open this publication in new window or tab >>Towards Benchmark Data Generation for Feature Tracking in Scalar Fields
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2022 (English)In: 2022 IEEE WORKSHOP ON TOPOLOGICAL DATA ANALYSIS AND VISUALIZATION (TOPOINVIS 2022), IEEE , 2022, p. 103-112Conference paper, Published paper (Refereed)
Abstract [en]

We describe a benchmark data generator for tracking methods for two- and three-dimensional time-dependent scalar fields. More and more topology-based tracking methods are presented in the visualization community, but the validation and evaluation of the tracking results are currently limited to qualitative visual approaches. We present a pipeline for creating different ground truth features that support evaluating tracking methods based on quantitative measures. In short, our approach randomly simulates a temporal point cloud with birth, death, split, merge, and continuation events, where the points are then used to derive a scalar field whose topological features correspond to the points. These scalar fields can be used as the input for different tracking methods, where the computed tracks can be compared against the ground truth feature evolution. This approach facilitates directly comparing the results of different tracking methods, independent of the initial feature characterization.

Place, publisher, year, edition, pages
IEEE, 2022
Keywords
Human-centered computing; Visualization; Visualization design and evaluation methods; Human-centered computing; Visualization; Visualization application domains; Scientific visualization
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-191882 (URN)10.1109/TopoInVis57755.2022.00017 (DOI)000913326500011 ()9781665493543 (ISBN)9781665493550 (ISBN)
Conference
IEEE VIS Workshop on Topological Data Analysis and Visualization (TopoInVis), Oklahoma City, OK, oct 17, 2022
Note

Funding Agencies|SeRC (Swedish e-Science Research Center); ELLIIT environment for strategic research in Sweden; Swedish Research Council (VR) [2019-05487]

Available from: 2023-02-22 Created: 2023-02-22 Last updated: 2023-06-09
Skånberg, R., Falk, M., Linares, M., Ynnerman, A. & Hotz, I. (2022). Tracking Internal Frames of Reference for Consistent Molecular Distribution Functions. IEEE Transactions on Visualization and Computer Graphics, 28(9), 3126-3137
Open this publication in new window or tab >>Tracking Internal Frames of Reference for Consistent Molecular Distribution Functions
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2022 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 28, no 9, p. 3126-3137Article in journal (Refereed) Published
Abstract [en]

In molecular analysis, Spatial Distribution Functions (SDF) are fundamental instruments in answering questions related to spatial occurrences and relations of atomic structures over time. Given a molecular trajectory, SDFs can, for example, reveal the occurrence of water in relation to particular structures and hence provide clues of hydrophobic and hydrophilic regions. For the computation of meaningful distribution functions, the definition of molecular reference structures is essential. Therefore we introduce the concept of an internal frame of reference (IFR) for labeled point sets that represent selected molecular structures, and we propose an algorithm for tracking the IFR over time and space using a variant of Kabschs algorithm. This approach lets us generate a consistent space for the aggregation of the SDF for molecular trajectories and molecular ensembles. We demonstrate the usefulness of the technique by applying it to temporal molecular trajectories as well as ensemble datasets. The examples include different docking scenarios with DNA, insulin, and aspirin.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC, 2022
Keywords
Distribution functions, Trajectory, Visualization, Graphical models, Numerical models, Shape, Periodic structures
National Category
Chemical Sciences Mathematics Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-174336 (URN)10.1109/TVCG.2021.3051632 (DOI)000833767700005 ()33444141 (PubMedID)
Note

Funding agencies: Excellence Center at Linkoping and Lund in Information Technology (ELLIIT); Swedish e-Science Research Centre (SeRC)

Available from: 2021-03-20 Created: 2021-03-20 Last updated: 2023-01-13
Friederici, A., Falk, M. & Hotz, I. (2021). A Winding Angle Framework for Tracking and Exploring Eddy Transport in Oceanic Ensemble Simulations. In: Workshop on Visualisation in Environmental Sciences (EnvirVis): . Paper presented at EnvirVis: Workshop on Visualisation in Environmental Sciences (EnvirVis2021). The Eurographics Association
Open this publication in new window or tab >>A Winding Angle Framework for Tracking and Exploring Eddy Transport in Oceanic Ensemble Simulations
2021 (English)In: Workshop on Visualisation in Environmental Sciences (EnvirVis), The Eurographics Association , 2021Conference paper, Published paper (Refereed)
Abstract [en]

Oceanic eddies, which are highly mass-coherent vortices traveling through the earth's waters, are of special interest for their mixing properties. Therefore, large-scale ensemble simulations are performed to approximate their possible evolution. Analyzing their development and transport behavior requires a stable extraction of both their shape and properties of water masses within. We present a framework for extracting the time series of full 3D eddy geometries based on an winding angle criterion. Our analysis tools enables users to explore the results in-depth by linking extracted volumes to extensive statistics collected across several ensemble members. The methods are showcased on an ensemble simulation of the Red Sea. We show that our extraction produces stable and coherent geometries even for highly irregular eddies in the Red Sea. These capabilities are utilized to evaluate the stability of our method with respect to variations of user-defined parameters. Feedback gathered from domain experts was very positive and indicates that our methods will be considered for newly simulated, even larger data sets.

Place, publisher, year, edition, pages
The Eurographics Association, 2021
Keywords
Eddy extraction, Tracking, Visual exploration, Oceanic ensemble simulation
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-177625 (URN)10.2312/envirvis.20211079 (DOI)
Conference
EnvirVis: Workshop on Visualisation in Environmental Sciences (EnvirVis2021)
Funder
Swedish Foundation for Strategic Research, BD15-0082
Available from: 2021-06-30 Created: 2021-06-30 Last updated: 2024-01-02
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ORCID iD: ORCID iD iconorcid.org/0000-0001-7285-0483

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