Funding and Partnerships Edge Quantum Computing to Realization

Quantum computing is advancing rapidly, with several companies making significant strides in hardware and scalability. Different approaches are emerging, each with unique advantages in error correction, qubit stability, and system integration. Here’s a look at three recent developments from AIST, QuEra, and Alice & Bob, showcasing their latest efforts in pushing quantum computing toward real-world applications.

AIST and Intel Partner on Silicon Quantum Computers

AIST and Intel have signed a Memorandum of Understanding to advance silicon quantum computing. Their goal is to develop a system with tens of thousands of qubits for industrial use by the early 2030s. The collaboration focuses on overcoming current scalability and reliability challenges in quantum computing.

An artist’s render of the G-QuAT center. Image used courtesy of AIST

AIST, a Japanese research institution, is contributing its expertise through its Quantum-AI Fusion Technology Business Development Global Research Center (G-QuAT). This center provides an evaluation testbed and device manufacturing functions to support the project. Intel brings its advanced semiconductor processes, leveraging decades of experience in chip manufacturing.

This partnership plans to optimize component materials, develop implementation technologies, improve refrigeration for large-scale quantum computers, integrate qubits, and advance cryoelectronics for qubit control. By combining AIST’s manufacturing and evaluation capabilities with Intel’s semiconductor advancements, this collaboration aims to push quantum computing closer to practical, large-scale applications in fields like cryptography, drug discovery, financial modeling, and complex system optimization.

QuEra Raises $230 Million for Neutral-Atom Quantum Computing

QuEra has secured $230 million in funding to accelerate the development of large-scale, fault-tolerant quantum computers. The company, founded from research at Harvard and MIT, specializes in neutral-atom quantum computing, a technology that offers unique scalability advantages.

Neutral-atom systems have the potential to scale to thousands of qubits, making them suitable for real-world applications. They enable dynamic qubit reconfiguration, improving efficiency and performance. The company aims to develop fault-tolerant quantum computers that can reliably handle complex calculations.

With this new funding, QuEra plans to expand its team, increase build and test capacity, and enhance collaborations with Fortune 500 companies, research institutions, and government programs. Backed by investors such as SoftBank Vision Fund, QuEra is positioning itself as a key player in the quantum computing industry, aiming to make neutral-atom quantum computers commercially viable in the near future.

Alice & Bob Secure $104 Million to Advance Cat Qubit Technology

Alice & Bob have raised $104 million in series B funding to advance its fault-tolerant quantum computing efforts. Founded in 2020, the company has quickly established itself as a leader in quantum computing, raising a total of $135 million and demonstrating experimental results that surpass those of Google and IBM.

Alice & Bob founders Théau Peronnin and Raphael Lescanne. Image (modified) used courtesy of Alice & Bob

Alice & Bob specializes in cat qubits, a technology designed to suppress bit-flip errors, one of the most common quantum computing errors. This approach reduces hardware requirements, potentially allowing useful quantum computers to be built with thousands instead of millions of qubits. It also aligns with sustainability goals by improving energy efficiency.

With this funding, Alice & Bob plan to accelerate development, with the goal of building the first useful quantum computer by 2030. It also intends to scale operations, refine its cat qubit technology, and expand collaborations with research institutions and industry partners. The company's progress could lead to breakthroughs in fields such as materials science, cryptography, and large-scale optimization problems.