Materials challenges and opportunities for quantum computing hardware
Abstract
Combatting noise on the platform The potential of quantum computers to solve problems that are intractable for classical computers has driven advances in hardware fabrication. In practice, the main challenge in realizing quantum computers is that general, many-particle quantum states are highly sensitive to noise, which inevitably causes errors in quantum algorithms. Some noise sources are inherent to the current materials platforms. de Leon et al. review some of the materials challenges for five platforms for quantum computers and propose directions for their solution. Science, this issue p. eabb2823 BACKGROUND The past two decades have seen intense efforts aimed at building quantum computing hardware with the potential to solve problems that are intractable on classical computers. Several hardware platforms for quantum information processing (QIP) are under active development. To realize large-scale systems based on these technologies, we must achieve error rates much lower than have been demonstrated thus far in a scalable platform, or devise a new platform entirely. These activities will require major advances in materials science and engineering, new fabrication and synthesis techniques, and new measurement and materials analysis techniques. We identify key materials challenges that currently limit progress in five quantum computing hardware platforms, propose how to tackle these problems, and discuss some new areas for exploration. Addressing these materials challenges…
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.