
Au-delà du classique : comprendre l'informatique quantique
Guide de l'informatique quantique et de ses différences avec l'informatique classique
For decades, classical computers have been the foundation of technological advancement, relying on binary bits (0 or 1) to process data. While this logic powers modern supercomputing, specific high-complexity problems remain computationally prohibitive.
Pasqal is a quantum computing company developing neutral-atom quantum processors designed to scale toward industrial applications. The company focuses on integrating quantum computing into HPC and cloud environments to support emerging use cases in optimization, simulation, and targeted AI-related workloads. By leveraging the principles of quantum mechanics, we are engineering systems to process information differently, mapping solutions for complex networks, advanced materials, and energy grids.

The Physics of Computation

The qubit
Classical bits exist in binary states: 0 or 1. A quantum bit, or qubit, introduces properties derived from quantum physics—superposition and entanglement—enabling multidimensional data processing.

Superposition
Qubits can exist in a linear combination of states. This allows quantum processors to evaluate a vast spectrum of possibilities simultaneously. Upon measurement, the qubit resolves to a definitive state, providing the computational output.

Enchevêtrement
Entanglement links qubits so that the state of one is fundamentally correlated to the state of another. This allows quantum systems to model highly correlated, complex variables—such as molecular interactions or financial risk portfolios—more natively than classical architectures.
Industrial Impact
Pasqal’s analog and digital architecture is designed to harness these properties to augment classical HPC.

Broad Parameter Exploration
Evaluate multiple systemic variables simultaneously via superposition.
Complex Correlation Modeling:
Map intricate network relationships utilizing qubit entanglement.
Targeted Acceleration:
Engineered to pursue computational advantage over classical systems in specific, high-value simulation and optimization workloads.
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