IBM researchers have found a way to double the size of quantum simulations while using half as many qubits on a quantum computer, through a process called entanglement forging.
The tech company’s researchers said this technique can run larger problems on a quantum processor than previously possible – allowing larger circuits on smaller hardware.
In a paper first published last April in Cornell University and recently published in review journal PRX Quantum, the team managed to create an accurate simulation of the ground state energy of a water molecule, representing 10 spin-orbitals on five qubits of an IBM quantum processor.
In an accompanying blog, the IBM team said entanglement forging technique takes a circuit operating on 2N qubits, and separates that circuit into two N-qubit halves.
Usually, if researchers wanted to simulate 10 spin-orbitals of a water molecule, they would need to use at least 10 qubits, as most quantum simulation techniques require one qubit for each relevant “feature” of the systems they simulate.
With entanglement forging, the IBM researchers were able to split the problem in half, by separating the 10 spin-orbitals into two groups of five, and then processing each group using just five qubits.
The team said that entanglement forging is scalable and has a broad application across a variety of problem structures, meaning it could expand the computational power of quantum systems
“We demonstrated a method that in many cases will allow you to run larger problems on your quantum processor than you otherwise could,” lead author of the study Andrew Eddins said. “Entanglement forging provides an efficient method of bringing classical computational resources to bear on quantum problems in a way that, in one respect, doubles your capability. It effectively increases your qubit number by a factor of two, which is really remarkable.”
Co-author of the paper Sarah Sheldon said entanglement forging represents an important addition to a family of quantum computational techniques known as “circuit knitting”.
“Other groups have worked on similar ideas of breaking up circuits into smaller pieces, either by qubits or in time — like breaking up gates — to do larger problems. Entanglement forging is a particularly scalable method, at least for problems with weak entanglement that have this structure that’s amenable to it,” Sheldon said.
As IBM’s quantum computers are being set up across the world, the tech company has been working hard to prove what these machines can do. In a research paper last July, its researchers showed quantum machine learning was able to discern patterns where classical computers missed the signal in the noise.
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