Q-Data 2025
The second workshop on Quantum Computing and Quantum-Inspired Technology for Data-Intensive Systems and Applications (Q-Data 2025) is a half-day workshop, collocated with SIGMOD 2025, that explores the potential of quantum computing and quantum-inspired hardware accelerators for data processing and data management.
Motivation
Whereas quantum computing started out as a purely theoretical concept, the last few years have seen a “Cambrian explosion” of first-generation commercial quantum hardware culminating from decades of foundational research. Players, including the likes of Google, IBM, and Intel, as well as startup companies like IQM, D-Wave, IonQ, and Rigetti, are now producing hardware devices that implement quantum computing using various technologies. At the same time, the recent advances in quantum computing have inspired a new generation of classical hardware accelerators, offered commercially by providers such as Fujitsu, Toshiba, and 1Qubit, that mirror the interfaces and take inspiration from internal processes of quantum computers. These accelerators, including digital annealers, as well as GPU- and FPGA-based simulators of quantum computation, obtain approximate solutions for extremely large, combinatorial optimization problems quickly.
Using quantum computing and related technologies has become convenient and possible with standard IT interfaces. Several software frameworks have recently appeared that make solving a diverse range of problems using quantum computers easier. At the same time, multiple cloud providers nowadays offer quantum computing as a service, making the technology accessible to broad shares of the population. Taken together, these developments have recently spawned a flurry of research in various communities, ranging from operations research to machine learning, and aimed at analyzing the transformative potential of quantum computing for specific use cases.
The primary objective of the Q-Data workshop is to explore how quantum computing and related technologies can enhance data processing, data management, data analysis systems, and techniques. It also focuses on hybrid approaches that integrate both quantum and classical computing methodologies to enhance such data systems and techniques. This workshop will spur new research efforts in this emerging field and pave the way for building next-generation data-intensive systems with quantum computing support.
Topics of Interest
Topics of interest for the workshop include (but are not limited to):
- 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)
Important Dates
All deadlines are 11:59 PM Pacific Time:
- Submissions: April 27, 2025
April 20, 2025 - Notifications: May 7, 2025
May 4, 2025 - Camera-Ready: June 1, 2025
- Workshop Date: June 22, 2025
Submission Instructions
Submissions must be formatted according to the ACM Primary Article Template (for Latex users, use the “sigconf” template) and submitted using EasyChair here. Authors are responsible for entering all conflicts of interest according to the Conflict of Interest Policy for ACM Publications before the submission deadline. We will impose a triple-blind submission and review policy. In addition to the traditional double-blind submission that hides the authors’ and referees’ names from each other, the triple-blind reviewing goes further and hides the referee names among referees during paper discussions before their acceptance decisions.
We accept three kinds of papers:
- Full papers with a length of up to 12 pages (excluding references)
- Short papers with a length of up to 6 pages (excluding references)
- Abstracts with a length of one single page (including references)
For long and short papers, we consider 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.
For abstracts, each abstract submission is expected to have a single author and should describe ideas and projects at very early stages.
Accepted papers and abstracts will be included in the proceedings and receive presentation slots at the workshop (5 minutes for abstracts, 15 minutes for short papers, and 25 minutes for long papers).
Organization
Workshop Chairs
- Ibrahim Sabek (University of Southern California, USA)
- Immanuel Trummer (Cornell University, USA)
Steering Committee
- Jiaheng Lu (University of Helsinki, Finland)
- Le Gruenwald (University of Oklahoma, USA)
- Sven Groppe (University of Lübeck, Germany)
- Wolfgang Mauerer (Technical University of Applied Sciences Regensburg, Germany)
Program Committee
- Federico Spedalieri (ISI at University of Southern California, USA)
- Johanna Barzen (University of Stuttgart, Germany)
- Manuel Schönberger (Technical University of Applied Sciences Regensburg, Germany)
- Sebastian Feld (TU Delft, Netherlands)
- Shaukat Ali (Simula Research Laboratory, Norway)
- Stuart Hadfield (Quantum AI Lab at NASA Ames Research Center, USA)
- Valter Uotila (University of Helsinki, Finland)
Program Schedule
TBD
Keynote “D-Wave Quantum Optimization Realized”
Abstract
Quantum computing promises to accelerate computational power in a variety of application spaces. D-Wave Quantum Inc. has targeted optimization problems with its quantum annealing hardware, hybrid quantum-classical software, and services. In this talk, we will explore the different use cases tackled by D-Wave’s technology, including areas of scheduling, allocation, and querying. An introduction to quantum computing will be provided, as well as an example of how research using quantum optimization has expanded as the technology has improved over the past 10 years.
Speaker
Dr. Catherine Potts is a technical advisor at D-Wave Quantum Inc., assisting clients in building quantum optimization applications for commercial and research use. She has a PhD in applied mathematics from Montana State University, focused on adapting machine learning algorithms to scientific imaging. Since 2020, she’s been focused on building quantum computing applications for different types of quantum hardware, including D-Wave’s quantum annealing and hybrid technology.