A5018297324- Particle physics theoretical and experimental studies
- Quantum Computing Algorithms and Architecture
- Particle Detector Development and Performance
- Forecasting Techniques and Applications
- Statistical Mechanics and Entropy
- Complex Systems and Time Series Analysis
- Dark Matter and Cosmic Phenomena
- Algorithms and Data Compression
University of Latvia
2022
To investigate the fundamental nature of matter and its interactions, particles are accelerated to very high energies collided inside detectors, producing a multitude other that scattered in all directions. As charged traverse detector, they leave signals their passage. The problem track reconstruction is recover original trajectories from these signals. This challenging data analysis task will become even more demanding as luminosity future accelerators increases, leading collision events...
Time-series forecasting is essential for strategic planning and resource allocation. In this work, we explore two quantum-based approaches time-series forecasting. The first approach utilizes a Parameterized Quantum Circuit (PQC) model. second employs Variational Linear Regression (VQLS), enabling by encoding the problem as system of linear equations, which then solved using quantum optimization techniques. We compare results these methods to evaluate their effectiveness potential advantages...