/Materials challenges and opportunities for quantum computing hardware (via Qpute.com)
Materials challenges and opportunities for quantum computing hardware

Materials challenges and opportunities for quantum computing hardware (via Qpute.com)


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

Structured Abstract

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 will necessitate interdisciplinary approaches from scientists and engineers beyond the current boundaries of the quantum computing field.

ADVANCES

This Review constitutes a roadmap of the current challenges and opportunities for materials science in quantum information processing. We provide a comprehensive review of materials issues in each physical platform by describing the evidence that has led to the current understanding of each problem. For each platform, we present reasons for particular material choices, survey the current understanding of sources of noise and dissipation, describe materials limitations to scaling, and discuss potential new material platforms. Despite major differences among physical implementations in each hardware technology, there are several common themes: Material selection is driven by heterogeneity, impurities, and defects in available materials. Poorly controlled and characterized surfaces lead to noise and dissipation beyond limits imposed by bulk properties. Scaling to larger systems gives rise to new materials problems that are not evident in single-qubit measurements.

OUTLOOK

We identify three principal materials research frontiers of interest in this context. First, understanding the microscopic mechanisms that lead to noise, loss, and decoherence is crucial. This would be accelerated by developing high-throughput methods for correlating qubit measurement with direct materials spectroscopy and characterization. Second, relatively few material platforms for solid-state QIP have been explored thus far, and the discovery of a new platform is often serendipitous. It is thus important to develop materials discovery pipelines that exploit directed, rational material searches in concert with high-throughput characterization approaches aimed at rapid screening for properties relevant to QIP. Third, there are several materials issues that do not affect single-qubit operations but appear as limitations in scaling to larger systems. Many problems faced by these platforms are reminiscent of some that have been addressed over the past five decades for complementary metal-oxide semiconductor electronics and other areas of the semiconductor industry, and approaches and solutions adopted by that industry may be applicable to QIP platforms. Materials issues will be critical to address in the coming years as we transition from noisy intermediate-scale systems to large-scale, fault-tolerant systems. Quantum computing began as a fundamentally interdisciplinary effort involving computer science, information science, and quantum physics; the time is now ripe for expanding the field by including new collaborations and partnerships with materials science.

Five quantum computing hardware platforms.

From top left: Optical image of an IBM superconducting qubit processor (inset: cartoon of a Josephson junction); SEM image of gate-defined semiconductor quantum dots (inset: cartoon depicting the confining potential); ultraviolet photoluminescence image showing emission from color centers in diamond (inset: atomistic model of defects); picture of a surface-electrode ion trap (inset: cartoon of ions confined above the surface); false-colored SEM image of a hybrid semiconductor/superconductor [inset: cartoon of an epitaxial superconducting Al shell (blue) on a faceted semiconducting InAs nanowire (orange)].

IBM IMAGE, CC BY-ND 2.0; SEM IMAGE COURTESY OF S. NEYENS AND M. A. ERIKSSON; PHOTOLUMINESCENCE IMAGE COURTESY OF N. P. DE LEON; FALSE-COLORED SEM IMAGE COURTESY OF C. MARCUS, P. KROGSTRUP, AND D. RAZMADZE

Abstract

Quantum computing hardware technologies have advanced during the past two decades, with the goal of building systems that can solve problems that are intractable on classical computers. The ability to realize large-scale systems depends on major advances in materials science, materials engineering, and new fabrication 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 will require scientists and engineers to work together to create new, interdisciplinary approaches beyond the current boundaries of the quantum computing field.


This is a syndicated post. Read the original post at Source link .