Whurley, founder and CEO of Strangeworks, a quantum computing startup based in Austin, TX was a keynote speaker at the 2020 IEEE Rising Stars Conference. He pointed out that the number of qubits (quantum bits) in quantum computers has increased considerably with up to 160 qubit machines (IonQ) by the end of 2019 as shown below.
He spoke about the promise of Quantum Computing and the opportunity for younger technologists to get starting in the quantum computing industry. In particular, he pointed out the need to be able to program quantum computers and the need for people to learn to program these devices. His company, Strangeworks, has on on-line site where people can access existing quantum computing programs and create new programs that can be run on simulations of existing quantum computers.
The simulation of quantum computers requires modeling computations that simultaneously involve multiple simultaneous states. In a sense, a real quantum computer solves many problems simultaneously and this allows it to solve problems faster (in principal) than conventional digital computers. An example that Whurley showed was having a quantum computer solve a maze puzzle by effectively exploring all paths in the maze at once.
In 2019 Google claimed that it was able to demonstrate the solution of a problem with a quantum computer in much less time than would have been required by a conventional digital computer. IBM disputed just how much faster the Google quantum computer was than a conventional computer, but it is clear that there are problems that tomorrow’s quantum computers can solve that would be practically impossible with conventional machines.
Doing these quantum computing simulations required memory to keep track of the expanding simultaneous states in a quantum machine. The chart below, from his Rising Stars presentation show how the memory requirements double for every additional qubit. Simulating the Google quantum computer required 500 GB of memory. The Strangeworks simulation use about 69 GB of memory.
It appears that practical quantum computing will be used to solve some types of problems that are difficult for conventional digital computers to solve. At least in the near term these machines are likely to complement rather than replace conventional computers. Note also that quantum computers generally operate in very low cryogenic environments and thus are considerably more expensive (and complicated) to operate than conventional computers.
Quantum computers may be used for many applications. One of the more famous ones is breaking the encryption codes currently in wide use. New types of encryption codes, resistant to quantum computers will be needed to replace conventional AES encryption to protect data as quantum computer become more available. In addition, quantum computers could speed solution of some artificial intelligence (AI) applications and various optimization problems.
The use of simulation tools for quantum computers in a software development environment, like that provided by Strangeworks may help develop the next generation of quantum computing software engineers. The simulations use considerable memory to represent the growing number of simultaneous states that increasing number of qubit quantum computers would contain.
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