Quantum computing is drawing nearer and nearer to real practical applications. Hardware is advancing all the time, and with constant progress towards larger and more fault-tolerant quantum computers, it now seems very foreseeable that they'll soon find a role in many industries. There are many functions they'll never be well-suited to, and there'll probably never be a quantum computer in anyone's pocket, but they can handle some problems, like optimization tasks or simulation of quantum systems, much more quickly than classical computers ever could. One day, when large, error-corrected quantum computers are widely available, it seems likely that many parts of our lives will be sped up by a quantum computer handling the trickiest problems behind the scenes without us ever realising.
For now, though, while the hardware is still developing, there's a lot of value in considering what software it should run. More efficient quantum algorithms, that achieve the same results with less computational cost and without needing as many qubits, can allow quantum computers to start solving real-world problems sooner, by meeting the hardware in the middle rather than waiting for it to catch up.
The attached article (which reports on the Nature Communications paper here), describes how Phasecraft, a UK- and US-based quantum software company, has developed a quantum algorithm aptly named THRIFT with the goal of simulating dynamic quantum systems more quickly and with less computational expense. The algorithm is particularly designed for use on what they call noisy intermediate-scale quantum computers; that is, something closer to the still-developing quantum hardware of today rather than the more ideal systems we may one day have.
While quantum hardware tends to generate more interest and headlines, it's fascinating to watch progress on quantum software as well. Hopefully, as time goes on, we'll increasingly have good enough hardware, and simple enough software, that quantum computers can be of immediate real-world benefit rather than just future promise.
The new technique will enhance the scalability and practical utility of quantum simulations, helping researchers extract more useful physical insights with fewer hardware resources
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