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Quantum Computing Targets Grid and Materials

Context

Energy challenges span grid operations and the materials that carry power. Classical methods can struggle with large optimization and simulation problems in both areas.

Overview

ARPA-E selected Infleqtion for a $6.2 million grid optimization program and $3.9 million project focused on superconductivity and new energy materials.

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Key Problem

Grid operators need better optimization as demand rises, while materials researchers need new ways to understand superconductivity and identify conductors with zero losses.

$6.2M

ENCODE grid optimization award
$3.9M

QC3 materials funding
1,600

Physical-qubit array demonstrated
12

Logical qubits with error detection

Two Energy Programs

ENCODE applies quantum-enhanced methods to grid optimization. The QC3 project uses a neutral-atom quantum computer and a new algorithm to study superconductivity.

A Full-Stack Approach

ENCODE - Grid scheduling and optimization.
QC3 - Superconductors and energy materials.
Hardware - Neutral-atom quantum computing.
Software - Quantum algorithms and Superstaq.

Key Results and Findings

Infleqtion executed the $6.2 million ENCODE contract and began development with energy-sector collaborators. ARPA-E also selected the company for $3.9 million in QC3 funding for chemistry and materials research.

Implications

ENCODE aims to improve the accuracy or speed of grid optimization. The QC3 project aims to improve understanding of superconductivity and discover previously unknown superconducting materials.