Q-Data is the 1st workshop, collocated with SIGMOD 2024, that explores the potential of quantum computing and quantum-inspired hardware accelerators for data processing and data management. Check out more details at http://qdataworkshop.com/.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following submission categories are welcome:

• Papers: we will accept full (up to 12 pages) and short (up to 6 pages) papers, with unlimited pages for references, in the following categories:

  • Algorithms: The primary contribution lies in algorithms that allow solving problems that are relevant to the database community on quantum computers or quantum-inspired accelerators. Long papers are expected to provide significant experimental or formal analysis results evaluating the proposed algorithm.

  • Systems: The primary contribution lies in proposing new architectures or frameworks that use quantum computing or quantum-inspired accelerators to address problems in data processing and management. Long papers are expected to evaluate the implementation of the proposed system thoroughly.

  • Experiments: The primary contribution lies in experimental analysis, quantifying properties of existing or novel algorithms that are at least partially executed on quantum computers or quantum-inspired accelerators (or use corresponding simulators). Long papers are expected to provide a more detailed experimental analysis.

• Abstracts: since the workshop focuses on a relatively new area, we will encourage the authors to submit a 1-page abstract about the preliminary findings of their ongoing projects or even raw ideas that are not fully explored. An abstract submission is expected to have a single author. Accepted abstracts will be included in the proceedings.

Details about the submission link and paper formats are at http://qdataworkshop.com/.

List of Topics

• Enhancing database system components (e.g., query optimizer, query scheduler, transaction scheduler, authentication and integrity manager) with quantum computing and quantum-inspired accelerators

• Data processing systems that integrate quantum-based and quantum-inspired accelerators

• Data processing systems that integrate both quantum and classical computing approaches

• Quantum machine learning for autonomous database management, database tuning, workload management, and learned indexes

• Approaches for data exploration, discovery, and integration based on quantum computing and quantum-inspired hardware accelerators

• Formal analysis and experimental evaluations assessing the potential of quantum computing for specific use cases in data processing and data management

• Vision papers describing novel database system designs and novel use cases in data processing and management enabled by quantum computing

• Quantum computing libraries and programming interfaces for database systems

• Quantum computing enhanced data exploration, discovery, and integration

• Domain-specific approaches exploiting quantum computers and quantum-inspired accelerators for data analysis (e.g., in finance or health care)

Organizing Committee

• Ibrahim Sabek (University of Southern California, USA)
• Immanuel Trummer (Cornell University, USA)
• Stefan Prestel (Quantum Brilliance, Germany)

Contact

Any questions about submissions and the conference, in general, should be emailed to sabek@usc.edu, it224@cornell.edu, and stefan.prestel@quantum-brilliance.com.