Quantum computing roadmap for solving scientific challenges
Although quantum computing is still relatively nascent, IBM and partners are strongly urging organizations to begin discussing the issues they have that quantum could solve and think about investing in the technology now.
Already, industries, universities, and governments around the world are making important contributions to scientific research toward practical quantum computing applications, according to scientists from IBM, Maastricht University, the European Organization for Nuclear Research (CERN), and quantum startup Qu & Co., during an IBM-sponsored virtual roundtable on Thursday.
The speakers provided insight into their research efforts and the current quantum computing landscape. They also discussed scientific challenges, such as Qu & Co.’s quantum chemistry application research; the IBM-Maastricht University-CERN collaboration to address the computational needs of the future Einstein Telescope; and the LHCb detector at the High-Luminosity Large Hadron Collider at CERN.
Quantum is entering the mainstream of the computing world because “today’s powerful computers are not enough,” said Heike Riel, IBM Fellow and lead IBM Research Quantum Europe & Africa.
Quantum computing can help solve some of the world’s biggest problems, including research and development in agriculture (feeding people), climate change (dealing with the CO2 problem), transportation (developing zero emissions), and healthcare (understanding certain diseases and finding the right treatments), Riel said.
Classical computers cannot do the necessary simulations to tackle these issues, she said. Quantum computers use quantum bits and calculate on the basis of quantum physics and are needed to solve challenges, Riel said.
The road ahead
IBM’s roadmap for quantum has gone from 27 qubit chips in 2019 to 65 qubits in 2020. Next year’s goal is to break 100 the quantum barrier and demonstrate a 127 chip called Eagle, Riel said. In 2022, the expectation is 433 qubits and a chip called Osprey, as well as more miniaturization of components and integration, she said.
By the end of 2023, the goal is to break the 1,000 qubit barrier to allow for more applications, and “lead us to a path of one million qubits, which will require new infrastructure and quantum error correction,” Riel said.
Gideon Koekoek, an assistant professor at Maastricht University, said the challenge they are working on with IBM is how to speed up finding the right gravitational wave to deal with enormous amounts of data in the coming Einstein Telescope, “which, in theory, will make it possible to explore the universe as far back as the Big Bang,” according to the university. “We’re going to have much more data that won’t be able to scale up using traditional techniques,” Koekoek said.
Storing the data isn’t the problem; filtering it will take a lot of time, he added.