The Race is on to Find the Quantum Advantage

Published on INFORMS Analytics Magazine (Joseph Byrum)

Daily progress suggests the goal is closer than many may think.

The race is on to find the quantum computing advantage, and businesses will need to be ready before anyone reaches the finishing line.

Many dismiss the possibility of this happening within our lifetime. Naysayers eagerly recite lists of very real technical hurdles that, thus far, have kept us from unlocking the potential of subatomic particles in accelerating the simulation of highly complex processes.

Others, instead of talking, are doing. Quantware, a European startup, announced it would sell a mass-produced 5-qubit quantum computing chip. A California startup, PsiQuantum, partnered with GlobalFoundries [1], the fourth largest semiconductor maker, to set up a facility for the mass production of quantum computing chips that are still in development. Their intention is to use silicon photonics to construct a 1-million qubit device. That goal may be a bit ambitious, but the world’s chipmakers are currently backlogged like never before [2] – they wouldn’t waste effort on a fantasy project.

On the algorithm side, mathematicians and engineers are finding ways to make the limited capacity of today’s primitive quantum machines deliver more impressive results. Yet another startup, Phasecraft, published a method for modeling electrons (part of a broader category known as fermions) that’s more efficient than other techniques [3]. A team in China, meanwhile, claimed [4] it had succeeded in creating a quantum machine with 66 qubits that can do in a little more than an hour what a conventional computer would need eight years to compute. When Google made a similar assertion in 2019, however, IBM – which is working on its own approach to quantum computing – insisted this was quite an exaggeration [5]. Even so, the claims of results are becoming more common.

Instead of wondering whether the naysayers are right, consider what happens if the naysayers are wrong. We use public-key encryption to keep unauthorized individuals from snooping on our emails and online transactions. If the digital keys securing these transactions became vulnerable to snooping, we’d lose the foundation of our $2 trillion digital economy [6]. Key lengths vary, but to break a key that’s 256 bits long using brute force methods would require guessing 2²⁵⁶ possibilities. Our sun would run out of energy and head into retirement long before you could try out all of the combinations – a number that reaches 78-digits [7] even with the world’s fastest conventional machines working around the clock to crack it.

Public-key encryption exploits the difficulty of prime factorization to conceal messages within massive prime numbers. If you can figure out the two primes that multiply together to create that very large prime number, you’ll be able to decode the message.

Shor’s Algorithm

We already know that quantum computers are perfect for the task of finding those factors using what’s known as Shor’s algorithm [8]. Named for MIT mathematician Peter Shor, this algorithm shows how, with enough qubits in a quantum computer, the factors of a prime number can be found exponentially faster than would be possible with a traditional computer. Researchers in 2012 demonstrated that Shor’s mathematics are correct by factoring the number 21 into 7 and 3 [9] using a device that only had a handful of qubits. Obviously, that’s not particularly impressive. But consider what happens if the startups mentioned above succeed in creating the 1-million qubit quantum machine.

That’s enough power to trigger a nightmare scenario for privacy, as such a machine could become a skeleton key able to open any digital lock that relies upon conventional encryption methods. If we’re not ready with replacement encryption techniques that don’t rely on primes, our economy is in big trouble. Fortunately, new security systems are in the works [10], and next-gen techniques may even take advantage of quantum principles.

Being ready for the quantum revolution is just as important, if not more important, in the business world. Like cryptographers, entrepreneurs are going to want to exploit the possibilities of subatomic particles to gain as big an advantage as possible over the competition. Imagine running a port or other complex logistics operation with only paper, pens and filing cabinets when the competition has real-time data collection and the latest computer hardware and control algorithms. That’s roughly the magnitude of change that the quantum revolution can bring throughout the economy.

The techniques of modern data analytics can take uncertain, incomplete or seemingly random data and attempt to make sense of the situation with statistical sampling and estimation. Given the current limits of processing power, it’s simply not possible to do more than fashion approximate answers within a range of uncertainty for any given problem. The real world consists of far too many variables, each one interacting with the other, with an impact on the final result.

AI Decision-Support Systems

Data analytics, as used today, can calculate the odds for various courses of action and help executives decide which path is most likely to succeed. These systems are far from perfect, but they provide just enough of an edge to add millions of dollars to the bottom lines of companies that take advantage of optimization [11]. This is the best that can be done within today’s computational limits.

Once quantum machines are powerful enough, the data analytics techniques won’t have to rely on statistical shortcuts anymore. Quantum hardware excels at making simultaneous calculations involving hundreds or thousands of interacting variables. Performing more direct calculations at blazing speeds would create such a leap in accuracy and timeliness when evaluating real-world scenarios that the “millions” saved annually by today’s optimization research will be replaced with, “How many millions did I save in the last hour?”

The work being done by quantum computing pioneers today is also laying the foundation for the intelligent enterprise of the future. The promised hardware advances will make it possible for a company to be built from the ground up with this level of optimization in mind. Artificial intelligence (AI) algorithms running on quantum hardware would be deployed at every level of the company. These AI decision-support systems would guide new employees, managers and executives alike in making choices, more often than not, that would be the right call.

Success comes to those armed with the right tools for the job at hand. Exploring the possibilities of quantum computing today can help reduce the risk of being caught without tomorrow’s most important tool.

References

1. https://psiquantum.com/news/psiquantum-and-globalfoundries-to-build-the-worlds-first-full-scale-quantum-computer
2. Ian King, 2021, “Intel CEO Says Chip Shortage to Hit Bottom in Second Half,” Bloomberg, June 25, https://www.bloomberg.com/news/articles/2021-06-25/intel-ceo-says-chip-shortage-to-hit-bottom-in-second-half.
3. Derby, C., Klassen, J., Bausch, J., and Cubitt, T., 2021, “Compact fermion to qubit mappings, Physical Review B, Vol. 104, No.3, 035118, https://journals.aps.org/prb/abstract/10.1103/PhysRevB.104.035118.
4. Wu, Y., Bao, W. S., Cao, S., Chen, F., Chen, M. C., Chen, X., et al., 2021, “Strong quantum computational advantage using a superconducting quantum processor,” arXiv:2106.14734.
5. Pednault, E., Gunnels, J., Maslov, D., and Gambetta, J., 2019, “On ‘Quantum Supremacy,’” Oct. 21, https://www.ibm.com/blogs/research/2019/10/on-quantum-supremacy/.
6. https://internetassociation.org/publications/measuring-us-internet-sector-2019/
7. https://www.wolframalpha.com/input/?i=2%5E256
8. Shor, P. W., 1999, “Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer,” SIAM Review, Vol. 41, No.2, pp. 303-332, https://doi.org/10.1137/S0036144598347011.
9. Martín-López, E., Laing, A., Lawson, T., Alvarez, R., Zhou, X-Q., O’Brien, J. L., 2012, “Experimental realization of Shor’s quantum factoring algorithm using qubit recycling,” Nature Photonics, Vol. 6, pp. 773–776, https://doi.org/10.1038/nphoton.2012.259.
10. https://openquantumsafe.org/
11. INFORMS has documented $292 billion in cumulative savings from a relatively small sample of the best projects, https://www.informs.org/Recognizing-Excellence/INFORMS-Prizes/Franz-Edelman-Award.