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Outline

Mystery, Myth, Reality and Truth about quantum computer

Abstract
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This paper discusses the current state of quantum computing, focusing on its potential to replace silicon chips and its advantages in efficiency and speed. It highlights the importance of reversible computing and energy reduction through controlled transitions in quantum circuits, referencing key theories like Landauer's principles on energy dissipation and Toffoli's work on reversible logic. The complex design of quantum algorithms is also examined, emphasizing the unique challenges posed by quantum mechanics.

Key takeaways
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  1. Reversibility is crucial for reducing power consumption in quantum circuits, but not the only condition.
  2. Landauer's principle requires energy dissipation of at least 3 x 10^-21 joules per erased bit.
  3. Toffoli's reversible gate is key to advancing reversible logic circuits and systems.
  4. Current quantum computing faces challenges in scalability despite prototypes of simple elements.
  5. Only Shor's algorithm has shown significant quantum speedup over classical methods so far.

References (2)

  1. Quantum Computing , First published Sun Dec 3, 2006; substantive revision Mon Feb 26, 2007
  2. Reversible Logic Circuit Synthesis, Vivek V. Shende, Aditya K. Prasad, Igor L. Markov, and John P. Hayes, Advanced Computer Architecture Laboratory, University of Michigan

FAQs

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What conditions are essential for reducing power consumption in quantum circuits?add

The research indicates that to reduce power consumption effectively, circuits must prevent devices from turning ON with potential differences and ensure gradual energy transfer during operations.

How does reversible logic contribute to energy efficiency in quantum computing?add

The findings suggest reversible logic can minimize energy dissipation by maintaining a copy of the output state, allowing non-dissipative transitions during computations.

What does Landauer's principle state regarding logical irreversibility in computing?add

Landauer’s principle posits that erasing information results in entropy generation, necessitating a minimum energy dissipation of approximately 3 x 10^-21 joules per erased bit.

Why is energy loss due to irreversibility a concern for nanotechnologies?add

Current energy losses from irreversibility heavily outweigh overall power dissipation, but as technology advances, this could become more significant for nanotechnology applications.

What unique challenge does quantum algorithm design present?add

Quantum algorithm design is intricate due to the need to leverage quantum mechanics for computational problem-solving, with Shor's algorithm being the only significant breakthrough to date.