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Exploring the Potential of Quantum Computing for Protein Folding(medium.com)

233 points by quantumcode 1 year ago | flag | hide | 10 comments

  • quantum_researcher 1 year ago | next

    Fascinating article on using quantum computing for protein folding! I wonder if anyone has tried implementing this on real quantum hardware like the D-Wave systems?

    • classical_programmer 1 year ago | next

      I'm skeptical that quantum computers can provide any significant advantage for this problem over classical computers. I'd love to see some hard numbers on the potential speedups.

      • quantum_theorist 1 year ago | next

        There are actually several theoretical results that suggest quantum computers could provide a significant advantage for solving the protein folding problem. In particular, there are algorithms that can potentially solve this problem exponentially faster on a quantum computer compared to a classical computer.

      • simulated_annealing_expert 1 year ago | prev | next

        While I agree that it's important to be skeptical, it's also important to consider the potential benefits of quantum computing for protein folding. For example, simulated annealing algorithms have been used to model protein folding on classical computers for many years, but they can be prohibitively slow for large proteins. Quantum computers could potentially overcome this limitation.

        • physics_professor 1 year ago | next

          You're absolutely right that simulated annealing can be slow for large proteins. However, I'd be cautious about claiming that quantum computers can solve this problem exponentially faster. There are still many open questions about the computational complexity of quantum algorithms for protein folding.

      • machine_learning_engineer 1 year ago | prev | next

        Another potential application of quantum computing for protein folding is in machine learning. There are algorithms like quantum Boltzmann machines that can potentially be used to model the complex energy landscapes of proteins and predict their folding patterns.

        • deep_learning_researcher 1 year ago | next

          Quantum machine learning is definitely a promising area, but it's still in its infancy. There are a lot of challenges to be addressed before we can start using quantum computers for real-world applications like protein folding. For example, we need to develop more efficient algorithms for loading data onto quantum computers and designing quantum circuits that can handle large datasets.

    • quantum_hardware_engineer 1 year ago | prev | next

      I work on building quantum computers and I can confirm that we have seen some promising results for this type of application. However, there is still a lot of work to be done before we can fully harness the power of quantum computing for protein folding.

  • quantum_student 1 year ago | prev | next

    This is a really exciting application of quantum computing. I'm currently working on my PhD in quantum algorithms and I can't wait to see how this technology develops in the coming years.

  • biological_scientist 1 year ago | prev | next

    As a biologist, I'm very excited about the potential of quantum computing for protein folding. This could have a huge impact on drug discovery and other fields of biology. However, I'm also aware that this is a very complex problem and we still have a lot to learn about the fundamental physics of protein folding.