Quantum Computing

Futurists and technologists have been discussing the promise of quantum computing on our lives for decades, but it has always seemed just beyond the grasp of real-world applications. This has changed immensely over the last 5 years, as the list of companies that are operating quantum computers continues to grow, including major new players like D-Wave and Rigetti as well as familiar names such as IBM and Honeywell. As these firms develop quantum systems, we are seeing an exponential jump in the number of qubits contained in each system, and the kinds of applications in which they can be utilized.


Constraint satisfaction and optimization is a broad class of computing that today’s quantum computers are able to solve using quantum annealing.  This quantum computing paradigm is leveraged by our  Tachyontm system developed by Polarisqb to revolutionize the world of drug discovery.  Quantum Annealing, like the work Polaris did with Fujitsu, can be thought of as a procedure that can test for multiple variables and is able to optimize the process for determining the most efficient solution from a massive library of potential solutions. By utilizing quantum fluctuation based computing rather than a traditional binary computer, the annealing process is able to perform the same combinatorial optimization in a fraction of the time and operations that it would take a classical supercomputer to solve the same optimization problem.


Polarisqb  is implementing quantum computing at the vanguard of computer aided drug design to perform protein targeting simulations that are many times faster than the current solutions available to biotech researchers and major pharmaceutical companies. Our Tachyontm system is able to optimize and find the best molecule from a billion molecules library in less than 5 minutes, narrowing the field of candidate molecules to find the promising lead candidates for a new drug or treatment.