Today, Microsoft is making available a new, extensive set of experimental data and simulations of our quantum devices. Now anyone can access the same data as our scientists to better understand Microsoft’s recent physics breakthrough and our approach to building a scalable, full-stack quantum machine. The results shown in this data are the first of their kind and follow more than two decades of research at Microsoft.
Laying the groundwork
The journey to this important milestone began back in the late 1990s when Microsoft decided to focus on quantum computing. Our goal at the time was the same as it is today: quantum computing at scale. We are laser-focused on engineering an industrial-scale machine that empowers innovators to make breakthroughs. Our vision is to build a system that can help solve the world’s most complex problems, such as removing climate-warming gases from the atmosphere, producing more food per hectare of land, and creating longer-lived batteries for tomorrow’s emission-free vehicles and power systems. Based on extensive research, we decided years ago that the most probable—and perhaps only—path to building a quantum machine capable of solving these seemingly intractable problems is to power it with topological qubits. We predicted that this type of qubit would have the requisite combination of stability, size, and speed to scale. Nevertheless, it was challenging to decide to build a machine with topological qubits because the fundamental building block of the topological qubit had not yet been identified. We were setting out to discover new physics.
For context, topology is a branch of mathematics describing those properties of shapes that remain unchanged as their geometry is bent, twisted, or stretched. When applied to quantum computing, topological properties create a level of protection that can, in principle, help a qubit retain quantum information despite what’s happening in the environment around it. Topological qubits will gain this protection by storing qubits in a highly non-local manner that is hidden away from the environment. We are focusing on a type of topological qubit in which this is done by splitting a qubit between two “Majorana zero modes,’’ or MZMs. An individual MZM does not contain any information about the state of a qubit—only by measuring two or more together can we extract information from a qubit. MZMs were predicted decades ago and since then, have been eagerly sought after by physicists. Observing MZMs enables us to identify the topological phase of the device—they are the fundamental building blocks of our topological qubit.
The reliability of a topological qubit is controlled by the so-called topological gap, which is roughly the energy that a topological qubit can absorb before it loses its integrity. When the topological gap is large compared to the temperature, the error rate will be low. A larger topological gap also makes it possible for the qubit to be small, so that a practical machine with many qubits does not exceed the size of a semiconductor wafer, allowing us to build a machine that fits in a closet rather than a squash court. A large topological gap also enables fast operation of the qubit, allowing the machine to solve complex problems in a matter of days or weeks instead of years or centuries.
Quantum device breakthrough
We had a significant scientific breakthrough a few months ago. For the first time in history, we engineered devices allowing us to induce and control a topological phase of matter with two MZMs—one at each end of the device. In other words, we found the recipe required to ensure that a topological qubit is built on a quantum device that can be tuned into the right state of matter, ultimately unlocking quantum computing at scale.
We’re confident in this discovery for three reasons. First, to prove that a topological phase bookended by MZMs had been achieved, and then to measure the phase’s stability, we developed a strict protocol of all the things we needed to see years ago. Think of it like a checklist. We then worked with experts on topological phases to improve and validate the checklist and codify those criteria in a data analysis routine called the Topological Gap Protocol (TGP). Second, we created checks and balances internally to validate results. For example, to ensure consistency and replicability we required numerous devices to pass the TGP protocol. In addition, entirely different Microsoft teams were involved. The team that fabricated the devices was different than the one that measured the devices’ results. Third, we engaged leading, independent condensed-matter physicists to review all our results in detail. It was only after all these procedures, tests, and retests were complete that we felt comfortable sharing our findings with the world. Since then, we’ve been running additional tests on our devices that revalidated the initial results. We’ve fabricated more devices that have passed the TGP and learned more about expanding the topological phase to create a better topological qubit.
Learn more about Microsoft’s quantum breakthroughs
We now are inviting anyone to examine our data and make their own assessments. That is why we recently published a preprint to the arXiv, and I also discussed our results at a webinar with leaders in the community earlier this summer. Today, we are taking another step forward in transparency by publicly publishing the raw data and analysis in interactive Jupyter notebooks on Azure Quantum. These notebooks provide the exact steps needed to reproduce all the data in our paper, as well as an in-depth walkthrough of both stages of the Topological Gap Protocol. Anyone can access the notebook on the Azure Quantum platform.
In time, we aim to bring Microsoft’s quantum machine to the Azure Quantum platform alongside a diverse portfolio of quantum computers from other hardware providers. The good news is that you don’t have to wait to learn and explore what’s possible with quantum computing. Get started for free today and stay tuned for more progress on Microsoft’s quantum machine.
