NetworkTigers explores how quantum computing hardware is advancing fast, with software already accessible online but scalability challenges slowing its full potential.
You might be waiting for quantum computers like 20th-century citizens were waiting for air travel – the technology came around much sooner than anyone thought it would. Quantum computing sounds like the stuff of science fiction, but through software, it is already accessible online. However, when considering the scalability of quantum computing hardware, the issue becomes much more nuanced.
What is quantum computing?
Quantum computing leverages the quantum states of subatomic particles, expressed through quantum mathematics, to store and process data. While ordinary computers process data as a series of either 0s or 1s, a quantum computer can process data using superposition. This means that a qubit, or bit of data in a quantum computer, can simultaneously exist as a 0 and a 1. This makes quantum computing well-suited to solving problems with many variables.
You can understand quantum computing, classical computing, and AI as three different approaches to solving a maze. If you asked a classic computer how to escape from a maze, it would run a series of codes exploring every way out before it found the correct one. This takes a great deal of time, as the classic computer needs to test every possible combination one at a time. Advances in AI attempt to use modeling based on human predictive patterns, processing each option in layers. AI might predict which way out from the maze is most likely based on swiftly calculating patterns it spots in data sets that it has been fed from prior mazes.
Meanwhile, quantum computing takes another approach entirely. A quantum computer functions more like the regular classic computer, except it can try every possible way out of the maze at the same time. It does not need to run one option at a time to assess its viability due to its ability to process multiple possibilities at once via quantum networks.
Is quantum computing the same as AI?
Quantum computing is different from AI. However, one of the most promising areas for quantum computing hardware is cooperating with AI software to hone its capabilities. Quantum computing may be able to make AI run more swiftly and address more complicated problems. It may also remove one of the main limitations of AI, which is the data size it can currently process.
Assessing quantum computing hardware potential
IBM estimates that quantum computers can shave thousands of years off of the time it takes for a classical computer to solve specific issues. Quantum computing, when fully operational, is expected to outpace the capabilities of even supercomputers.
According to McKinsey, approximately 5,000 quantum computers are expected to be operational as soon as 2030. However, the firm also estimates that the hardware and software required for quantum computing hardware to run at the highest level of operations will not be available to businesses and the general public until at least 2035.
The main issue with quantum computing at the moment is its scalability. The hardware involved in quantum computing must be cooled to near absolute zero and entirely isolated from interference from electricity, thermal activity, and magnetic fields around it. This and its reliance on pure silicon chips make it difficult to mass produce and replicate effectively.
Early business investment in quantum computing hardware
Despite issues with quantum computing hardware, businesses are racing to invest in the potential that it unlocks. As of 2022, some companies have invested at least $15 million annually in quantum computing. Additionally, Fortune Business Insights projects that the quantum computing market will reach $6.5 billion by 2030 at a compound annual growth rate of 32.1%.
Who will be best served by the development of quantum computing hardware? The question cannot be solved fully until these computers reach a state of “quantum advantage.” This is understood as the point when a quantum computer is the best solution to solve a problem based on the overlap of three main factors:
- Feasibility: The hardware used in quantum computing exists and is powerful enough to solve the problem at hand.
- Scalability: The hardware for the quantum computer is accessible to the industry.
- Economics: It becomes less expensive to use a quantum computer than a classic one to solve the issue.
Quantum computing hardware is expected to best suit larger industries and businesses seeking to run large-scale data processing. Some of the sectors expected to benefit the most from quantum computing are:
- Logistics: Quantum computers at the Technical University of Denmark were tested during the coronavirus pandemic to solve a logistics problem with many variables. The Italian football league contacted them to understand how to schedule their matches so that each team came into contact with each other as infrequently as possible, to reduce the risk of infection. Additionally, each team player needed to set their travel schedule to reach the game with as few transfers as possible and without air transport. This puzzle is ideally suited to quantum computing, which can handle additional variables that classical computing traditionally cannot.
- Finance: Risk analysis, portfolio optimization, and cryptocurrency are all predicted to be served by quantum computing. Stock performance and other variable factors may more easily be run through quantum computers than traditional ones.
- Cybersecurity: Quantum computing may be the most potent in cybersecurity and data encryption. Quantum key distribution (QKD) may be able to offer near-perfect encryption, which is unparalleled by current methodology. Likewise, the ability of quantum computing to enhance AI capabilities means that it may be able to detect and report otherwise indecipherable patterns.
- Healthcare: Pharmaceutical research and development is already well underway with quantum computing. Quantum simulations can be used to predict the outcomes of certain experiments, such as how drug molecules will bind to proteins used to treat Alzheimer’s as well as certain cancers. Additionally, interpreting test results and diagnostic imaging may be vastly improved with the help of quantum computing.
Forging through the silicon chip shortage in quantum hardware
Supply issues have recently hampered nearly all major silicon chip manufacturers, causing delays in classical computer production and development. Most of the world’s classic computer chips are made in Taiwan, representing 68% of the global market share. This is due to skilled labor, industry expertise, and national investment. However, over the past few years, classic computing has run into a series of chip shortages worldwide that are only expected to continue. The COVID-19 pandemic shut down production and tangled supply chains, but managing the crisis did not necessarily solve the larger issue around silicon chip availability. Taiwan’s electrical grid is 83% dependent on fossil fuels, mainly coal and natural gas. Meanwhile, Taiwan’s fossil fuels are imported entirely by sea. This leaves the island nation at the mercy of climate change, energy availability issues, potential political unrest, Chinese blockades, and international price fluctuations.
COVID-19 and Taiwan’s energy dependence are far from the only concerns with chip shortages. While the Biden Administration offered generous tax cuts and incentives to American chip manufacturers, approximately 40% of the largest US manufacturing projects funded under the CHIPS and Science Act have been delayed or temporarily halted. Companies are not eligible to receive the full value of the funding until they meet certain milestones, according to a report from the Financial Times. Many US businesses cite issues finding skilled labor, overproduction from China, and political uncertainty as reasons for the continued delays in silicon chip production.
All this is to say that classic computer chip production is a strained industry that may soon be reaching its natural limits. Quantum computing hardware may be able to power the necessary breakthrough. Quantum computing also requires silicon chips, building on existing knowledge available. However, breakthroughs from the Universities of Melbourne and Manchester show that quantum computing is best run on ultra-pure silicon to avoid computing errors. A new method of combining qubits of phosphorus atoms implanted into crystals of pure, stable silicon could extend the duration of quantum coherence. This would solve one of the most challenging problems with quantum computing errors and provide a path forward for troubled silicon chip production. Purified silicon chips have the potential to expand quantum computing hardware, solve some of the scalability issues, and get ahead of the many delays in classical computing chip production.
Looking ahead in quantum computing
Quantum computing presents nearly boundless potential, but several issues currently hamper its hardware. At the moment, quantum computers are primarily accessible online, such as through the IBM Quantum Platform. While quantum computing remains largely cloud-based for the average user, there may come a day sooner than we think when quantum computing hardware becomes available and even mainstream.
About NetworkTigers
NetworkTigers is the leader in the secondary market for Grade A, seller-refurbished networking equipment. Founded in January 1996 as Andover Consulting Group, which built and re-architected data centers for Fortune 500 firms, NetworkTigers provides consulting and network equipment to global governmental agencies, Fortune 2000, and healthcare companies. www.networktigers.com.
