Quantum Computing

Researchers Mine Sampling Bosons For A Quantum Blockchain Approach


Insider Summary

  • Most experts believe that boson sampling has no practical purpose other than serving as a yardstick of quantum superiority.
  • A research team suggests that boson sampling tasks serve as the backbone for a quantum blockchain scheme.
  • As well as being faster, this method can also consume less energy, one of the criticisms against using Bitcoin.

When news of quantum superiority in boson sampling started sweeping the scientific press a few years ago, the main knock on the experiment was that it seemed to have no practical use for esoteric tasks.

Now a team of scientists, including assistance from quantum security startup researcher BTQ Technologies, reports that boson sampling can serve as a proof of work (PoW) scheme for blockchain consensus that relies on quantum computing techniques to validate consensus, a key aspect of many blockchain protocols.

According to the research, which is posted on the pre-print server ArXiv, the authors report the system, beyond a scientifically compelling demonstration of the practical use of boson sampling, offers several benefits compared to traditional methods for solving computational puzzles for consensus. The current algorithm used to solve these puzzles is slow and requires a lot of computational resources to solve them, according to the researchers.

Boson sampling is considered a special problem in quantum computing that explores the behavior of photons – particles of light – as they pass through complex networks of optical elements such as beam splitters and detectors. In boson sampling, the goal is to sample the distribution of the output photons after they have been subjected to interference in an optical circuit. This sampling problem is challenging to simulate on a classical computer because the number of possible outcomes grows exponentially with the number of photons and optical elements involved.

The task primarily serves as a yardstick for evaluating the potential advantages of quantum computers over classical computers in performing certain tasks and most scientists consider the tasks unsuitable for general purpose computing.

The researchers used a boson sampling approach called coarse-grained boson sampling, or CGBS.

In this method, users in the network depend on specific inputs that are affected by the current block information. They share their results with the network. Then, the CGBS strategy was decided. This strategy is used to check if the results shared are valid and to reward miners who have successfully completed tasks. By rewarding honest miners who share accurate results and punishing those who share wrong results, a balanced situation is created that encourages everyone to be honest.

The team reports that the approach has two main benefits: it significantly speeds up the process and saves energy compared to using a traditional computer.

They write: “Whereas classic PoW schemes like Bitcoin are notoriously energy-inefficient, our boson sample-based PoW schemes offer a much more energy-efficient alternative when implemented on quantum hardware. Quantum gain has a compounding effect: as more and more quantum miners enter the network, the problem difficulty will increase to maintain consistent block mining times, further encouraging quantum miner participation.”

The technique is applicable to today’s quantum hardware and is scalable, according to the researchers.

The research institutions involved in this research include: the Center for Quantum Computing & Communication Technologies, located in Australia; School of Mathematics & Physics at The University of Queensland, also in Australia; School of Physics at the University of Melbourne, Center for Engineered Quantum Systems, BTQ Technologies, based in Vancouver, Canada; Center for Quantum Software & Information at the University of Technology Sydney and the Hearne Institute for Theoretical Physics, which is part of the Department of Physics & Astronomy at Louisiana State University in the United States.


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