QuEra Computing has laid out a specific roadmap to deliver fault-tolerant quantum computers by 2028, moving away from the industry's obsession with raw qubit counts toward a focus on error-corrected operations that actually work. The company's plan hinges on a fundamental insight: what matters is not how many qubits you have, but how many error-free operations you can run.

What's the Difference Between a Megaquop and a Gigaquop?

QuEra introduced two new terms to frame the quantum computing challenge. A megaquop represents roughly one million error-free operations, while a gigaquop represents roughly one billion. The distinction matters because an algorithm's complexity determines how many operations it needs to solve a problem. On a quantum computer, the limiting factor is not the total number of qubits but rather the number of reliable operations the system can perform before errors accumulate.

Individual qubits are fragile and pick up errors from their environment. Useful quantum computation depends on logical qubits, which are groups of physical qubits arranged so errors can be caught and corrected as they happen. Reaching gigaquop scale requires two simultaneous achievements: lowering the error rate of each qubit and deploying more efficient error-correction codes.

"An algorithm's complexity decides how many operations it needs. What limits a quantum computer is the number of operations it can run, not its raw qubit count," explained Yuval Boger, Chief Commercial Officer at QuEra Computing.

Yuval Boger, Chief Commercial Officer at QuEra Computing

Why Neutral Atoms Could Change the Game?

QuEra's approach relies on neutral-atom hardware, which offers structural advantages over competing qubit technologies. Atoms are identical by nature, which eliminates the per-unit calibration and manufacturing variability that plague other qubit types. They also carry no electrical charge, so they bypass the dilution refrigeration systems that superconducting quantum computers require.

The physical footprint difference is striking. A superconducting quantum setup can fill a stadium-scale space and draw tens of megawatts of power. A neutral-atom equivalent fits on roughly two dining tables and runs on tens of kilowatts. But the structural advantage runs deeper: neutral-atom qubits can be physically moved during computation. Two atoms interact only when brought close together, turning a calculation into a choreography where atoms move into position, interact, then move apart. Nothing is locked to a fixed chip layout.

This flexibility solves a critical problem in quantum error correction. On a fixed-connectivity chip, information passed qubit to qubit degrades like a message whispered down a line of fifteen children. On a neutral-atom system, the first child simply walks the message to the fifteenth, reducing hops and the chances to introduce errors. The same flexibility allows QuEra's architecture to support multiple error-correction code families rather than being stuck with a single scheme etched into a fixed chip.

How to Prepare Your Organization for Quantum Computing

• Start Early with Cloud Access: QuEra's Aquila system has been available on Amazon Braket since 2022, and the fault-tolerant Libra system is set to follow in 2028. Organizations of any size can experiment with quantum algorithms years before needing to own hardware.
• Engage in Co-Design Before Hardware Arrives: QuEra recommends a staged process through programs like the FTQC Founder's Circle that begins by scoping a real business problem and moves through joint algorithm exploration before any code touches hardware. Waiting until 2028 risks missing competitive advantages.
• Focus on Quantum-Native Problems: Chemistry and materials science sit closest to measurable value since their behavior is governed by quantum mechanics. Optimization and finance are in active exploration, but starting with quantum-native domains increases the odds of finding practical applications.

The Physical-to-Logical Qubit Ratio That Changes Everything

The single most important input to QuEra's roadmap is the ratio of physical to logical qubits. Industry assumptions had pegged this ratio near 1,000 to 1, meaning 500 logical qubits (enough to beat classical simulation) would require roughly 500,000 physical qubits. High-rate quantum low-density parity check (QLDPC) codes are rewriting that equation.

QuEra's Libra system, planned for Amazon Braket in 2028, is designed to deliver 256 error-corrected logical qubits from just over 10,000 physical qubits, operating at a logical error rate of 10-6. A gigaquop-class system targeted for 2028 or 2029 is designed for 1,000 or more logical qubits from roughly 20,000 physical qubits, at a 10-9 error rate. Every building block behind those targets has already appeared in peer-reviewed research, according to QuEra.

How Quantum and AI Are Becoming Interdependent?

QuEra's roadmap reveals a symbiotic relationship between quantum computing and artificial intelligence. Quantum computers will augment classical infrastructure, not replace it. One practical example is decoding, the job of reading error signals off a logical qubit and correcting them. QuEra's published work with NVIDIA uses machine learning to make decoding faster, which cuts time to solution directly.

The relationship runs both ways. AI speeds up quantum error correction and system design, while quantum systems can generate training data in fields like chemistry that classical AI cannot easily produce on its own. This interdependence suggests that organizations investing in quantum computing will need expertise in both domains.

"Quantum computers will augment classical infrastructure, not replace it," Boger stated, emphasizing that the future involves hybrid systems where quantum and classical computing work together.

Yuval Boger, Chief Commercial Officer at QuEra Computing

The most practical takeaway from QuEra's roadmap is about timing. Organizations should not wait until 2028 to start preparing. The companies best positioned when fault-tolerant quantum computers arrive will be the ones that began exploring quantum algorithms and problem-scoping years earlier. Cloud access makes this possible without requiring upfront hardware investment, lowering the barrier to entry for enterprises of any size.