Exponential parallelism in practice: a comparative feature on quantum computing and instantaneous noise-based logic

TL;DR

This paper compares quantum computing and Instantaneous Noise-based Logic (INBL), highlighting their exponential parallelism capabilities, practical strengths, limitations, and potential for efficient problem-solving, especially in search tasks.

Contribution

It provides a practical comparison of QC and INBL, emphasizing INBL's simpler hardware and potential for exponential speedups in specific applications.

Findings

INBL achieves exponential speedup in search tasks like phonebook lookup.

Quantum computing attains universality, while INBL is limited to Boolean logic.

INBL hardware is simpler and avoids quantum decoherence issues.

Abstract

Exponential parallelism, a defining principle of advanced computational systems, holds promise for transformative impacts across several scientific and industrial domains. This feature paper provides a comparative overview of Quantum Computing (QC) and Instantaneous Noise-based Logic (INBL), focusing on their practical strengths, limitations, and applications rather than exhaustive technical depth. Both paradigms leverage exponentially large Hilbert spaces: quantum computing achieves this via quantum superposition, while INBL realizes it through the product space of classical noise processes. Quantum computers attain universality for all computational operations, whereas current INBL frameworks are universal only for Boolean logic; notably, essential superposition operations-such as AND and OR gates-are absent, precluding implementations of algorithms like Shor's. However, for certain problem classes where full universality is not required, INBL and quantum computing can offer equivalent time and hardware complexity, as observed with the Deutsch-Jozsa algorithm. Remarkably, for search tasks such as phonebook lookup, Grover's quantum algorithm provides a quadratic O(n^0.5) speedup compared to the classical approach, while INBL achieves an exponential speedup, requiring only logarithmic time in the size n of the phonebook O(log n). Such INBL algorithms could, in principle, be adapted to quantum hardware to attain similar performance. Importantly, INBL hardware is considerably simpler, being implementable with modest modifications to conventional PC architectures equipped with a true random number generator, and it inherently avoids the decoherence and error correction challenges of quantum systems.