From advanced materials to atomic super sensors, A*STAR scientists are harnessing the power of quantum to the fullest, ushering in the next generation of trailblazing technologies.
While quantum computing promises supremacy over high-performance classical models, this advantage remains limited to the research and development stage. As full-scale quantum computers have yet to be realized, many opt for hybrid models combining quantum with classical algorithms. This allows developers to run simulations and explore the frontiers of quantum, executing the algorithms on noisy intermediate-scale quantum (NISQ) devices—so-called because they are still error-prone.
However, hybrid algorithms often demand a high number of measurements, driving up costs and slowing down performance. Meanwhile, current fixes to reduce these costs have yet to make a dent in solving larger problems that typically require adding more qubits as well as better fault tolerance. Given the limits of NISQ in correcting errors, these algorithms are often rendered unusable for commercially relevant applications.
“The ELF framework takes into account the depth and coherence of the quantum device implementing the quantum algorithm,” Dax Koh, Scientist at A*STAR's IHPC explained. Besides crucially running on NISQ devices, ELF is also adaptable, adjusting the algorithms’ parameters when transitioning to more fault-tolerant machinery."
“Quantum computer operations and quantum circuit executions can be viewed as the time-evolution of a many-body quantum system composed of coupled qubits,” Ye Jun, Senior Research Scientist at A*STAR's IHPC said. “One key area of research is to understand the role of various noises in affecting the dynamics of a quantum system.”
The A*STAR-affiliated researchers contributing to this research are from the Institute of Materials Research and Engineering (IMRE) and the Institute of High Performance Computing (IHPC).
Read the full article published on A*STAR Research