Quantum Algorithms vs. Quantum-Inspired Algorithms

In a recent article published in The New Stack, Pedro Lopes from QuEra delves into the differences between quantum algorithms and quantum-inspired algorithms.

Categorizing quantum algorithms

Quantum-inspired algorithms can be categorized into two types: (i) classical algorithms based on linear algebra methods, often known as tensor networks, and (ii) methods that use classical computers to emulate quantum behavior. While these quantum-inspired algorithms offer performance improvements in classical computing, they are not a substitute for real quantum computing solutions. The article suggests that organizations should carefully consider their goals when deciding between adopting quantum-inspired solutions or preparing for quantum computing. It also notes that new analog quantum computers are emerging that offer real quantum coherence and scale at hundreds of qubits, providing value in specific applications.

Food for quantum thought

1. Quantum Readiness: If your organization's goal is to be quantum-ready, should you invest in quantum-inspired algorithms or focus on real quantum computing solutions?
2. Performance vs. Authenticity: Quantum-inspired algorithms offer performance improvements but are not true quantum solutions. Is the trade-off between performance and authenticity worth it for your business?
3. Future-Proofing: As analog quantum computers with hundreds of qubits are entering the market, how should organizations adapt their strategies to be future-proof?

Read the full article here.

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