In the fourth episode of Quantum Computing in Practice, Olivia discusses how we decide which types of problems to tackle with today’s quantum computers.
In the first part, she teaches broad guidelines for selecting problems based on computational complexity theory and more practical considerations. Then, she walks us through three example use-cases based on recent work done in the community.
Associated chapter: https://learning.quantum.ibm.com/course/quantum-computing-in-practice/what-problems-are-quantum-computers-good-for
Papers discussed:
Quantum Simulations of Hadron Dynamics in the Schwinger Model using 112 Qubits:
arXiv: 2401.08044
Bias-field digitized counterdiabatic quantum optimization:
arXiv:2405.13898
mRNA secondary structure prediction using utility-scale quantum computers:
arXiv:2405.20328v1