Use Case
Quantum Algorithms Supporting Predictive Analytics
Quantum Algorithms to Enhance Linear Regression and Predictive Analytics in Support of Advanced Analytical Techniques Across Various Markets, Including Energy & Utilities.
Where: Italy
Where: Italy
Mission
Learning to harness the computational advantage that quantum technology will offer—as soon as quantum hardware becomes available. The goal is to support the business by enhancing the effectiveness of data analysis techniques and significantly accelerating results and decision-making as problem complexity increases, with a direct impact on process optimization.
Solution
Quantum algorithms and approaches, particularly the Harrow-Hassidim-Lloyd (HHL) algorithm for efficient solution of linear systems, enhance certain ML techniques and analytical methods by introducing a new computational paradigm capable of addressing problems of scale and complexity that are currently intractable. This is especially relevant given the exponential growth of data, such as in the Energy sector.
These capabilities can enable new applications in Finite Element Method (FEM) computations, advanced correlation analysis, and the optimization of complex neural networks, significantly accelerating processing and expanding the range of solvable problems beyond the limits of classical hardware.
The generalization of the algorithm, enabled through integrated Python development tools (Qiskit Framework) and the AWS cloud, makes it possible to manage problems of arbitrary complexity.
Digital Ecosystem
Actions
Digital Ecosystem
- Analysis of business needs and definition of medium- to long-term objectives;
- Alignment of internal competencies on quantum technology;
- Establishment of collaborations with technology partners to develop use cases and the creation of an interdisciplinary team, including machine learning experts, quantum algorithm developers, system engineers, and business specialists with deep knowledge of data and enterprise requirements.
Expected results
Rapid analysis of complex issues, such as energy supply management on smart grids or renewable energy sources
Optimization of supply and resource management
Impacts
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