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Can Quantum Computing Help Fight the COVID-19 Pandemic


Worldwide, several researchers are exploring Quantum computing to fight COVID-19 Pandemic. Read on to know more…

In the fight against coronavirus outbreak, Quantum computing has joined the force of disruptive technologies at the service to better pandemic control. Quantum computing, long a subject of theoretical speculation, has in recent years been solving practical, real-world problems.

Identifying Small-Molecule Compounds
The world’s mightiest supercomputer, IBM Summit is being deployed by researchers to identify chemical compounds that could contribute to the fight against coronavirus. Researchers were afforded emergency computation time on the machine, which performs analysis at an unrivaled pace. Summit reportedly generated results within 1-2 days, as opposed to the months it would have taken standard computing systems to produce equivalent results. To date, the quantum computer has helped researchers identify 77 small-molecule compounds worth investigating further as institutions around the world scramble to develop a coronavirus cure.

Summit boasts a maximum processing power of 200 petaflops, thanks to 4,608 server nodes, each equipped with two IBM POWER9 CPUs and six Nvidia Tensorcore V100 GPUs. The computer-simulated thousands of compounds in search of those most likely to bind to the coronavirus protein that allows the virus to infect host cells. Jeremy Smith, Director of the ORNL Center for Molecular Biophysics, was enthusiastic about the progress made with the help of IBM’s supercomputer, but also sought to temper expectations.

Drug Discovery
Quantum Machine Learning, an emerging field that combines Machine Learning and Quantum Physics, is the focus of research to discover possible treatments for COVID-19, according to Penn State researchers led by Swaroop Ghosh, the Joseph R. and Janice M. Monkowski Career Development Assistant Professor of Electrical Engineering and Computer Science and Engineering. The researchers believe that this method could be faster and more economical than the current methods used for drug discovery.

Seed funding from the Penn State Huck Institutes of the Life Sciences, as part of their rapid-response seed funding for research across the University to address COVID-19, is supporting this work. According to Ghosh, using the existing drug-discovery pipeline can take five to ten years from initial idea to market approval, and cost billions of dollars. “Discovering any new drug that can cure a disease is like finding a needle in a haystack,” Ghosh said.

Airlines Example
Last month, D-Wave Systems has offered free cloud computing time on its quantum computer to COVID-19 researchers. The offer, unveiled last month, applies to work toward vaccines and therapies as well as epidemiology, supply distribution, hospital logistics, and diagnostics. The free quantum computing consulting services D-Wave is arranging include quantum programming expertise in scientific computing as well as in planning, management, and operations for front-line workers.

To illustrate the difference between “sparsely connected” variables and “fully connected” variables,  Alan Baratz, CEO of D-Wave, describes a sample problem. For instance — an airline, say, has a fleet of 100 planes spread out over 25 airports, with 500 crew members who are either flying the plane or servicing the passengers or on the ground servicing the planes. The optimum set of schedules for those planes and staff members involves both the raw parameters above as well as real-world constraints on the planes (maintenance schedules, weather, and number of berths available at any given airport) and on the crew (home bases, certification levels on various aircrafts, work and vacation schedules). Those constraints would be programmed into a D-Wave algorithm as degrees and kinds of connectedness between the variables.


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