New tool on AWS makes it easier to develop quantum error correction

Google just moved up its timeline for quantum computers to 2029 because of improvements in quantum computer hardware, quantum error correction, and algorithms. In 2019, Google estimated it would take 20 million qubits to break RSA encryption. By May of 2025, Google revised those estimates down to 1 million. This February, researchers at Australia’s Iceberg Quantum said in a pre-print report that only 100,000 physical qubits were needed. Then, this Monday, Caltech researchers said that it could take as few as 10,000 qubits to break traditional encryption. And, on Tuesday (it’s been quite a week) Google announced that elliptic curve cryptography—the kind that protects cryptocurrencies—can be broken with less than 1,200 logical qubits. The term “logical qubit” is significant. A logical qubit is not the same as a regular old physical qubit. Physical qubits are prone to errors and instability. So, quantum computer manufacturers double up on the physical qubits, or triple up—or group 1,000 of them together—so that they can compensate for the errors and instability. The better the quantum error correction, the fewer physical qubits you need to make one usable, logical qubit, and the closer you get to a practical quantum computer. And now we get to today’s announcement. This morning, Quantum Elements and AWS announced a codeveloped tool called Constellation that researchers can use to test their quantum error correction methods on a digital twin of a quantum computer—even quantum computers that haven’t been built yet. This is similar to the digital twin that Quantum Elements announced last month, except that the previous one was designed to help researchers create physical qubits that have fewer errors in them to start with. Constellation is available via Quantum Elements and runs on AWS, says Izhar Medalsy, co-founder and CEO at Quantum Elements. And it is designed to help quantum researchers develop and test error correction strategies. Alternatives, such as the popular Stim simulator from Google Quantum AI, don’t simulate all the potential sources of errors, says Medalsy. “Stim uses a lot of approximations, which makes it very fast,” adds Tong Shen, research scientist at Quantum Elements, who worked on Constellation. “It’s low latency. But it’s just inaccurate.” “Imagine you’re a captain of a boat, and you want to train your team to get from point A to point B,” Medalsy says. If the training simulator doesn’t account for ocean currents or wind conditions, the team won’t be able to navigate once they hit the real world. Currently, he says, Constellation has modeled computers of up to 97 qubits, and it can be used to go even higher. “We know how to make qubits work,” he says. “Now we see it as the engineering task to increase the number of qubits and reduce the noise.” And with a digital twin, researchers can experiment with error-correction techniques even before the physical computers are ready. “You can solve the problem so once the hardware is ready, you plug it in, and you’re good to go,” he says. Medalsy declined to say how much the service costs other than that it is “extremely affordable.” In addition, he says, early users can get a month’s free trial to test it out.