UNSW's proposed quantum chip module architectureThe University of New South Wales (UNSW), a leading quantum computing research university from Australia, proposed an architecture for a silicon-based quantum computer processor based on complementary metal-oxide-semiconductor (CMOS) technology, which should make it easier to integrate quantum and classical chips.
Quantum Computers Are Coming
IBM and Google have already promised us commercial-ready quantum computers in the next few years that should reach quantum supremacy (faster to solve a given problem than any supercomputer on Earth) for a number of tasks. Other large companies such as Intel and Microsoft, as well as a number of governments, have shown interested in developing quantum computers.
However, the first quantum computers won’t exactly be pocketable, or even desk-ready. They will require extreme cooling or advanced lasers to work, because that’s currently the best way to maintain qubit coherence (necessary for computation to work) for even short amounts of time.
Although these methods should suffice in bringing us quantum computers that can have millions of qubits, it won’t be easy to interface them with our classical computers--which will be necessary if we want to make real use of quantum computers.
For the next decade or two after achieving quantum supremacy, quantum computers won’t be of much use on their own. Although quantum computing could in theory speed up problems that would otherwise would take an exponential amount of time to solve on classical computers, you still need a good number of qubits in order to do that.
For instance, we likely won’t be able to simulate the entire human body at atom-scale with just a few hundred qubits. Even if quantum computers follow a Moore’s Law of sorts and can double their number of qubits every two years or so, much like D-Wave’s quantum annealer has done, it should still be a few decades before we have millions of qubits.
Even then, not all problems will be solvable on quantum computers, so we'll still need to use our classical computers. Quantum chips will more likely be used as “accelerators” for classical computers, just like we use GPUs to power rich graphical interfaces efficiently on our PCs, or how we’re starting to use machine learning accelerators in smartphones, data centers, and elsewhere.
Bringing Quantum And Classical Chips Together
The engineers at UNSW have proposed the first practical architecture for parallel addressing of silicon spin qubits. Silicon spin qubits promise to have a higher stability rate compared to competing quantum computing architectures, while also promising to bring quantum computers to existing manufacturing processes.
The researchers said that this type of chip could be built on upcoming 7nm process technologies, although the smaller the transistors, the easier it will be to build a powerful quantum computer. However, once we reach 480 qubits, which can be implemented into a DRAM-like 20x24 qubit array chip, we could just multiply the 480-qubit modules to scale the quantum chip.
The researchers also said that they will need error-correction code employing multiple real qubits to build one “logical qubit,” a method that’s also currently used by most other quantum computing developers. They added that they developed a new type of error-correcting code that should work across millions of qubits in the future. This method is the first of its type that can be integrated in silicon.
The UNSW quantum computing team has received $83 million in funding from the university, the Australian government, and a few other companies, to develop a 10-qubit silicon quantum chip by 2022.
We may see a handful of commercial quantum computers by then that could be used mainly in the data center, with researchers having cloud access. However, the silicon quantum chip proposed by the UNSW may make its way into our regular computers in a few years. It may not be as powerful as the ones from IBM and Google, which may have hundreds of qubits by then, but it could pave the way to everyone having their own quantum computers to power up their personal AI assistant of the future.