Innovations in Sciences, IT, Computers, Robotics and Nanotechnology

[pib] Breakthrough in Quantum Noise Research

Why in the News?

Researchers at the Raman Research Institute (RRI) found that quantum noise—usually seen as a problem—can sometimes help connect particles in a special way called entanglement, which is important for future quantum technologies.

What is Quantum Noise?

  • Overview: Quantum noise refers to random disturbances that affect quantum systems, often causing loss of coherence or decoherence.
  • Traditional View: It is typically seen as harmful, especially for quantum entanglement, which is crucial for quantum computing and communication.
  • Entanglement Concept: It is a phenomenon where particles are so correlated that the state of one instantly affects the state of another, even at a distance.
  • Effect of Decoherence: Noise-induced decoherence breaks this entanglement, thereby reducing the efficiency of quantum technologies.

Key Findings:

  • Observation: Found that quantum noise can generate or revive entanglement, contrary to its typical reputation as destructive.
  • Focus Area: Studied intraparticle entanglement, which involves internal properties (like spin and path) of a single particle.
  • Contrast with Interparticle Entanglement: Unlike interparticle entanglement (between separate particles), intraparticle entanglement showed resilience under noise.
  • Types of Noise Studied:
    • Amplitude Damping: Energy loss
    • Phase Damping: Loss of phase information
    • Depolarizing Noise: Random changes in quantum state
  • Major Observation: Under amplitude damping, intraparticle entanglement showed delayed decay, revival, and even creation from unentangled states.
  • Interparticle Comparison: In contrast, interparticle entanglement exhibited steady decay with no revival or generation.

Scientific Implications:

  • New Perspective: Challenges the assumption that quantum noise is purely harmful, showing it can be a resource in certain contexts.
  • Technological Potential: Intraparticle entanglement is more noise-resilient, making it valuable for stable quantum devices.
  • Application Areas: Findings are relevant to quantum communication, QKD (quantum key distribution), quantum computing, and quantum sensing.
  • Predictive Advantage: The new formula allows precise prediction of entanglement behavior, aiding the design of robust systems.
  • Platform Independence: Results are platform-agnostic, applicable to photons, neutrons, trapped ions, etc.
[UPSC 2025] Consider the following statements:

I. It is expected that Majorana 1 chip will enable quantum computing. II. Majorana 1 chip has been introduced by Amazon Web Services (AWS). III. Deep learning is a subset of machine learning.

Which of the statements given above are correct?

(a) I and only I (b) II and III only (c) I and III only * (d) I, II and III

 

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