arXiv subjects

Stefan Böttcher

Publications and source records attributed to Stefan Böttcher.

8 recordsLinked to original sources

arXiv2026

Compressing Hypergraphs using Suffix Sorting

Hypergraphs model complex, non-binary relationships like co-authorships, social group memberships, and recommendations. Like traditional graphs, hypergraphs can grow large, posing challenges for storage, transmission, and query performance. We propose HyperCSA, a novel compression method for hypergraphs that maintains support for standard queries over the succinct representation. HyperCSA achieves compression ratios of 26% to 79% of the original file size on real-world hypergraphs - outperforming existing methods on all large hypergraphs in our experiments. Additionally, HyperCSA scales to larger datasets than existing approaches. Furthermore, for common real-world hypergraphs, HyperCSA evaluates neighbor queries 6 to 40 times faster than both standard data structures and other hypergraph compression approaches.

cs.DS↗

arXiv2025

String Partition for Building Long Burrows-Wheeler Transforms

Constructing the Burrows-Wheeler transform (BWT) for long strings poses significant challenges regarding construction time and memory usage. We use a prefix of the suffix array to partition a long string into shorter substrings, thereby enabling the use of multi-string BWT construction algorithms to process these partitions fast. We provide an implementation, partDNA, for DNA sequences. Through comparison with state-of-the-art BWT construction algorithms, we show that partDNA with IBB offers a novel trade-off for construction time and memory usage for BWT construction on real genome datasets. Beyond this, the proposed partitioning strategy is applicable to strings of any alphabet.

cs.DS↗

arXiv2025

IBB: Fast Burrows-Wheeler Transform Construction for Length-Diverse DNA Data

The Burrows-Wheeler transform (BWT) is integral to the FM-index, which is used extensively in text compression, indexing, pattern search, and bioinformatic problems as de novo assembly and read alignment. Thus, efficient construction of the BWT in terms of time and memory usage is key to these applications. We present a novel external algorithm called Improved-Bucket Burrows-Wheeler transform (IBB) for constructing the BWT of DNA datasets with highly diverse sequence lengths. IBB uses a right-aligned approach to efficiently handle sequences of varying lengths, a tree-based data structure to manage relative insert positions and ranks, and fine buckets to reduce the necessary amount of input and output to external memory. Our experiments demonstrate that IBB is 10% to 40% faster than the best existing state-of-the-art BWT construction algorithms on most datasets while maintaining competitive memory consumption.

cs.DS↗

arXiv2024

ITR: Grammar-based Graph Compression Supporting Fast Triple Queries

Neighborhood queries and triple queries are the most common queries on graphs; thus, it is desirable to answer them efficiently on compressed data structures. We present a compression scheme called Incidence-Type-RePair (ITR) for graphs with labeled nodes and labeled edges based on RePair and apply the scheme to network, version, and RDF graphs. We show that ITR performs neighborhood queries and triple queries within only a few milliseconds and thereby outperforms existing RePair-based solutions on graphs while providing a compression size comparable to existing graph compressors.

cs.DB↗

arXiv2020

Simulation computation in grammar-compressed graphs

Like [1], we present an algorithm to compute the simulation of a query pattern in a graph of labeled nodes and unlabeled edges. However, our algorithm works on a compressed graph grammar, instead of on the original graph. The speed-up of our algorithm compared to the algorithm in [1] grows with the size of the graph and with the compression strength.

cs.DS↗

arXiv2019

Electronic structure and magnetic properties of the graphene/Ni3Mn/Ni(111) trilayer

Experimental and theoretical studies of manganese deposition on graphene/Ni(111) shows that a thin ferromagnetic Ni3Mn layer, which is protected by the graphene overlayer, is formed upon Mn intercalation. The electronic bands of graphene are affected by Ni3Mn interlayer formation through a slight reduction of n-type doping compared to graphene/Ni(111) and a suppression of the interface states characteristic of graphene/Ni(111). Our DFT-based theoretical analysis of interface geometric, electronic, and magnetic structure gives strong support to our interpretation of the experimental scanning tunneling microscopy, low energy electron diffraction, and photoemission results, and shows that the magnetic structure of graphene is strongly influenced by Ni3Mn formation.

cond-mat.mtrl-sci↗

arXiv2018

The graphene/n-Ge(110) interface: structure, doping, and electronic properties

The implementation of graphene in semiconducting technology requires the precise knowledge about the graphene-semiconductor interface. In our work the structure and electronic properties of the graphene/$n$-Ge(110) interface are investigated on the local (nm) and macro (from $μ\mathrm{m}$ to mm) scales via a combination of different microscopic and spectroscopic surface science techniques accompanied by density functional theory calculations. The electronic structure of freestanding graphene remains almost completely intact in this system, with only a moderate $n$-doping indicating weak interaction between graphene and the Ge substrate. With regard to the optimization of graphene growth it is found that the substrate temperature is a crucial factor, which determines the graphene layer alignment on the Ge(110) substrate during its growth from the atomic carbon source. Moreover, our results demonstrate that the preparation routine for graphene on the doped semiconducting material ($n$-Ge) leads to the effective segregation of dopants at the interface between graphene and Ge(110). Furthermore, it is shown that these dopant atoms might form regular structures at the graphene/Ge interface and induce the doping of graphene. Our findings help to understand the interface properties of the graphene-semiconductor interfaces and the effect of dopants on the electronic structure of graphene in such systems.

cond-mat.mtrl-sci↗

arXiv2013

Efficient XML Keyword Search based on DAG-Compression

In contrast to XML query languages as e.g. XPath which require knowledge on the query language as well as on the document structure, keyword search is open to anybody. As the size of XML sources grows rapidly, the need for efficient search indices on XML data that support keyword search increases. In this paper, we present an approach of XML keyword search which is based on the DAG of the XML data, where repeated substructures are considered only once, and therefore, have to be searched only once. As our performance evaluation shows, this DAG-based extension of the set intersection search algorithm[1], [2], can lead to search times that are on large documents more than twice as fast as the search times of the XML-based approach. Additionally, we utilize a smaller index, i.e., we consume less main memory to compute the results.

cs.DB↗