Sourcengine’s Tech Angle: Quantum Computing’s Effect on Components

The world is entering a new age of computing. While experts believe we are still several years away from the practical introduction of quantum computing, we are experiencing tremendous growth within this sector.  

Quantum computing isn’t a new topic of discussion within the tech industry. The idea has existed since the early 1900s, but the phrase “quantum computing” has been a rising star in news articles over the last few months. What changed?

Some are calling 2023 a breakthrough year for quantum computing. In February, researchers at the University of Sussex and Universal Quantum demonstrated for the first time that quantum bits (qubits) can “directly transfer between quantum computer microchips with record-breaking speed and accuracy.” According to ScienceDaily, the breakthrough resolves a significant challenge in building quantum computers large and powerful enough to tackle problems of critical importance to society.  

Professor Sasha Roseneil, Vice-Chancellor of the University of Sussex, said: "It's fantastic to see that the inspired work of the University of Sussex and Universal Quantum physicists has resulted in this phenomenal breakthrough, taking us a significant step closer to a quantum computer that will be of real societal use. These computers are set to have boundless applications.”  

In March, Yale researchers achieved another breakthrough within quantum computing by extending a qubit’s lifetime above its break-even point. The breakthrough could improve the viability of quantum computers.  

“With the feasibility of quantum error correction, better qubits, and better machines altogether, quantum computation will not only be possible but also more concretely useful for disciplines beyond science and math,” Luigi Frunzio, a senior research scientist in applied physics, said.  

But what do these recent breakthroughs within quantum computing mean? What do the effects have on the tech industry, and what do the results mean for the electronics industry?  

What is Quantum Computing?

The study of quantum mechanics and computing is not an inherently new concept. In the 1900s to 1920s, quantum mechanics was developed and evolved to become the cornerstone of chemistry, condensed matter physics, and various technologies ranging from computer chips to LED lighting. In the 1980s, Richard Feynman and Yuri Manin proposed the idea of quantum computers.  

The idea behind quantum computers and quantum computing is usually presented alongside an in-depth description of a system of electrons. This example is due to the nature of quantum computers, which exploit a type of quantum mechanical phenomena. Quantum computers leverage a specific behavior in which physical matter exhibits properties of both particles and waves.  

In classic computers--the computers we use today--store information in bits. Bits are a unit of information that can store a zero or a one, not both. In quantum computers, information is built on quantum bits or “qubits,” which can store zeroes and ones. Like waves and particles, qubits can represent any combination of zero and one simultaneously, called a superposition. This dual combination allows quantum computers to move beyond classic computer limitations. Where traditional computers must conduct new calculations every time a variable in a problem changes, quantum computers do not.  

Now, the nitty-gritty of quantum computing and quantum mechanics is far more complex than a simple description can fully illustrate. Qubits are exceedingly volatile due to their inherent superposition. When qubits change status, inputs can be lost or altered, lowering the accuracy of the results it presents. There are different types of enhanced quantum computing called parallel quantum processing and bling quantum processing. The former is multiple processors connected and simultaneously executing additional calculations for the same problem. The latter utilizes quantum communications to access remote, large-scale quantum computers in the cloud.  

There are more levels to the quantum computing rabbit hole. At its most basic level, quantum computing utilizes superposition and entanglement. Entanglement is where quantum particles, like qubits, have connected properties, and the actions of another can manipulate one particle's properties. Quantum computing uses these subatomic particles and their related phenomena to solve problems.

The study of quantum computing is not new, not by a long shot. However, recent developments within the field have resulted in a new push by tech and chip giants alike.

The first real breakthrough in quantum computing came in 2019 when Google announced its quantum computer solved a problem in 200 seconds. The same problem would have taken a classic computer 10,000 years. The catch, however, is that quantum computers aren’t replacing your desktop next year or even being utilized in any significant capacity because most previous breakthroughs, including 2019, are theoretical, not practical. The problem the quantum computer solved has no real-world use, thereby, no impact.  

Unlike classic computers, quantum computers do not deliver a single answer. Due to the ability to explore different paths when solving a problem simultaneously, quantum computers can provide a range of possible solutions. If given a limited scope, the range of answers can be narrowed and slightly more specific. Most quantum computers in existence today are limited in scale to compete with classic computers. However, scalability has proven to be a considerable hurdle for quantum computing development. Yale and Sussex researchers have only just recently found avenue toward possible scalability.  

Most quantum computers currently in operation utilize a specific number of qubits. According to an article by Mckinsey & Company, “quantum computers operating at the scale needed to deliver significant breakthroughs will potentially require millions of qubits to be connected.” Of the quantum computers that exist today, none are near that number. McKinsey’s report addresses that progress within quantum computing will be slow and that by 2030 only 5,000 quantum computers will be operational worldwide. Furthermore, most hardware and software capable of handling most complex problems might not exist until 2035.  

According to Forbes, the current race within quantum computing is to obtain quantum supremacy, where “a practical quantum device that can solve a problem that no classical computer can solve in any feasible amount of time. Speed—and sustainability—has always been the measure of the jump to the next stage of computing.”  

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How can Quantum Computing be Utilized?

While quantum computing’s abilities are primarily theoretical for the time being, the real-world applications for quantum computers will likely be immense. Quantum computers have four fundamental capabilities that separate them from today’s classic computers, according to McKinsey & Company, The Harvard Business Review, and IBM researchers.  

These four capabilities are quantum simulation, optimization and search, quantum artificial intelligence (AI), and prime factorization. The specifics of each can be further narrowed down when applied to specific industry requirements. Though it’s important to note that quantum computing will be years away from widespread commercial application, the implications of its use within various industries are being studied. For example, pharmaceuticals, chemicals, automotive, and finance are the four industries that stand to gain the most from quantum computing.  

Therefore, quantum computing’s four fundamental capabilities are already well recognized for how they could aid industries in practical use.

Quantum simulation is the ability of quantum computers to model complex molecules, which could reduce development time for pharmaceutical and chemical companies. Today’s computers cannot provide accurate simulations of atom interaction, something scientists must do when formulating a new drug. McKinsey reports that quantum computers could be powerful enough to model even the most complex molecules within the human body.

Regarding optimization and search, organizations must make “one complicated calculation after another” in a time-consuming and costly process to address all variables of a particular situation. Quantum computers can work with multiple variables simultaneously, as it is one of their most natural capabilities. It can present a range of answers to users to help determine the most efficient solution.  

Quantum AI would be imperative for both the development of the metaverse and truly autonomous vehicles. Quantum AI could perform multiple complex calculations with many variables, such as receiving video and image data through complicated neural networks within a system, to train AI systems faster. This could bring the age of self-driving vehicles that do not need human intervention far faster than classic computer-trained AI, which could still require human intervention for decision-making.  

Finally, quantum computing’s ability to use algorithms to solve complex prime numbers, known as prime factorization, would bring a new era of online encryption technologies to secure online sites. Prime factorization use of quantum computing is the first tool scientists could soon bring to practical use. McKinsey estimates that quantum computers powerful to perform prime factorization could be available by the late 2020s at the earliest.  

Forbes’s article “Quantum Computing Could Make Today’s Encryption Defenseless” addresses how quickly quantum technology changes the landscape within all industries, including cybersecurity. Classic encryption relies on complex mathematical problems that take traditional computers an immense amount of time to solve. Again, classic computers cannot handle changing variables simultaneously.  

Encryption algorithms make it difficult to reverse-engineer data without knowing the key to encrypt it. Classic computers would have to test every key to determine which is correct, which takes them lots of time. With their multi-variable analyzing capability, quantum computers would reduce that time and render encryption methods vulnerable to attack. Since prime factorization is the fastest capability in development with quantum computers, discovering a new way to secure private information must become a top priority for defense and other security industries.

For now, most projects are simply to build a practical quantum computer.  

Australia recently set a goal to build an error-corrected quantum computer within the next decade, putting the country at the forefront of the new tech frontier. The federal government recently set aside $1 billion to invest in critical technologies like quantum computing. No one has developed a large quantum computer with error correction, despite several companies–Google among them–having created computers that can string together multiple qubits.  

Though Australia is hardly the only country or company with a similar ambition. In March, the British government committed $4.6 billion to quantum research for the next decade. In California, the University of Southern California (USC) announced a $1 billion-plus initiative for computing research, including quantum computing.  

As a top producer of tech talent within the country, USC’s initiative is a multi-level approach to continue pushing the barriers in tech development. Australia, the U.K., and California’s USC are only the most recently announced initiatives. Throughout the last few years, thanks to the rising importance of the semiconductor industry, similar programs are likely to follow.  

How will Quantum Computing Change the Semiconductor Industry?

The practical use of quantum computing might be a decade out by some estimates, but that doesn’t mean original component manufacturers (OCMs) and others are waiting for that day to arrive. With declarations by governments and universities alike striving toward quantum computing breakthroughs, OCMs and original equipment manufacturers (OEMs) are bringing quantum capabilities to electronics now.  

A group of researchers from the Microsoft and Scalable Parallel Computing Laboratory recently announced that current developments in hardware and software could put future quantum systems to shame. Specifically, within their experiment, the research team pitted a hypothetical quantum system with 10,000 error-correcting qubits against a classic computer equipped with a single Nvidia A100 GPU.  

“For our analysis, we set a break-even point of two weeks, meaning a quantum computer should be able to perform better than a classical computer on problems that would take a quantum computer no more than two weeks to solve,” said Microsoft’s Matthias Troyer. “Our research revealed that applications that rely on large datasets are better served by classical computing because the bandwidth is too low on quantum systems to allow for applications such as searching databases or training machine learning models on large datasets.”

Using quantum computers for most small data problems might never be practical. Quantum computers can only solve big data problems, often found in chemical or material sciences, rather than industry workloads. Quantum computers could help discover better and more efficient battery chemistries for electric vehicles (EVs), Troyer said. Classic computers and their chips, like Nvidia’s A100 GPU, are already quite capable of solving small data problems at the same speeds quantum computers flaunt.

Find Your Next Generation Components on Sourcengine

Quantum computers might take some time to get here, but according to the experts, the theoretical capabilities of quantum computing are already available in some cases. For those ready to bring quick optimization capabilities to their products, Sourcengine can help you find the perfect component.  

As one of the largest e-commerce sites for electronic components, Sourcengine has over 1 billion part offers from over 3,500 suppliers. As a franchised partner of Nvidia, our engineering team can help you design an agile product with end-to-end surfaces if you want to utilize Nvidia’s quantum computer-beating GPUs. Contact our team if you’re ready to put that idea into action.  

If you have a part in mind but don’t see a current offer, send our global team an RFQ.