An emerging computing technology, “probabilistic computers” are seen as a possible bridge between the gap of classical and quantum computing. The researchers’ demonstration presents a device that serves as a basis for building probabilistic computers that could more efficiently solve problems in areas such as drug research, encryption and cybersecurity, financial services, data analysis, and supply chain logistics.
While today’s computers store and use information in the form of zeros and ones (called bits) and quantum computers use qubits that can be both zero and one at the same time, a probabilistic computer uses “p-bits” that can be either zero or one at any given time and fluctuate rapidly between the two.
“There is a useful subset of problems solvable with qubits that can also be solved with p-bits,” says Supriyo Datta, the university’s Thomas Duncan Distinguished Professor of Electrical and Computer Engineering. “You might say that a p-bit is a ‘poor man’s qubit.'”
While qubits need extremely cold temperatures in which to operate, p-bits – like today’s electronics – work at room temperature, so existing hardware could be adapted to build a probabilistic computer, say the researchers. Following on this idea, the engineers built a device that is a modified version of magnetoresistive random-access memory – or MRAM – that some types of computers use today to store information. The technology uses the orientation of magnets to create states of resistance corresponding to zero or one.
Tohoku University researchers altered an MRAM device making it intentionally unstable to better facilitate the ability of p-bits to fluctuate, while the Purdue researchers combined the device with a transistor to build a three-terminal unit whose fluctuations could be controlled. Eight such p-bit units were interconnected to build a probabilistic computer.
The circuit, say the researchers, successfully solved what is often considered a “quantum” problem: breaking down, or factoring, numbers such as 35,161 and 945 into smaller numbers – a calculation known as integer factorization. These calculations are well within the capabilities of today’s classical computers, say the researchers, but the probabilistic approach demonstrated would take up much less space and energy.
“On a chip, this circuit would take up the same area as a transistor, but perform a function that would have taken thousands of transistors to perform,” says Ahmed Zeeshan Pervaiz, a Ph.D. student in electrical and computer engineering at Purdue. “It also operates in a manner that could speed up calculation through the parallel operation of a large number of p-bits.”
While hundreds of p-bits would be needed to solve bigger problems, say the researchers, that’s not too far off.
“In the near future,” says Kerem Camsari, a Purdue postdoctoral associate in electrical and computer engineering, “p-bits could better help a machine to learn like a human does or optimize a route for goods to travel to market.”
A patent application for this technology has been filed through the Purdue Research Foundation Office of Technology Commercialization.
For more, see “Integer factorization using stochastic magnetic tunnel junctions“
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