Do Quantum Computers Exist? The Evolution of Quantum Computing
Unraveling the Enigma of Quantum Computers
Yes, quantum computers exist and are a testament to humanity's boundless curiosity and innovation. These advanced machines harness the principles of quantum mechanics to process information in ways that classical computers cannot emulate.
Despite their existence being a reality, quantum computers are still in their early stages, with ongoing research focused on overcoming technical challenges and harnessing their potential. As quantum computers evolve, they promise to revolutionize industries, solve complex problems and pave the way for a new era of computational power.
In a world where technology constantly pushes boundaries, the concept of quantum computers has emerged as both a marvel and a mystery. With their immense processing potential, quantum computers have the power to revolutionize various industries. But a question lingers: do quantum computers truly exist? Let's embark on a journey through the evolution of quantum computing to uncover the truth behind their existence.
Evolution of Quantum Computing: A Glimpse into the Past
In this section, we'll take a step back in time to understand how quantum computing evolved from theoretical concepts to tangible advancements.
Theoretical Foundations of Quantum Computers
In the early 1900s, physicists of the time believed we had discovered all that could be discovered in the field. However, they were soon proved incorrect as Max Planck and Albert Einstein delved deeper into relativity and classical action. By the early 1920s, the term “quantum mechanics” was in use, and by 1925, quantum science as we know it was born.
Experiments and proofs continued, and as quantum mechanics grew in popularity, more questions arose. By 1935, Schrödinger had published his now-famous thought experiment, Schröndinger’s Cat, and coined the term “quantum entanglement.”
In 1980, Paul Benioff published a paper on the first possibility of quantum computing at the Argonne National Laboratory. This was followed by increasing interest in quantum and quantum computing, and in 1981, Richard Feynman from CalTech argued that a quantum computer could, theoretically, create simulations of physical phenomena that would never be possible with classical computing. This, along with other theories and insights by Feynman, inspired quantum researchers and continues to do so today.
While Feynman was working on his quantum theories, a British physicist named David Deutsch was developing the concept of a “quantum Turing machine,” which expanded the classical Turing machine model of computation to include quantum mechanics. With this, Deutsch laid the groundwork for quantum computing.
Deutsch also developed one of the earliest quantum algorithms and the concept of quantum parallelism, one of the fundamental concepts of quantum computing. Quantum parallelism harnesses the unique attributes of quantum bits (qubits) and allows quantum computers to work on multiple tasks or discover multiple solutions to a problem at the same time. It is the combination of superposition and entanglement, which are the basic properties of qubits.
Milestones in Quantum Bits
In 1992, a computational physics conference in Dallas, Texas, focused on a key issue with quantum computers: their accuracy. Benjamin Schumacher proposed a way to solve the lack of accurate results from quantum computers. As a joke to a colleague, Schumacher invented the term “qubits” as a new name for quantum bits of information. However, after careful consideration, Schumacher realized it wasn’t funny at all. In fact, it was a good idea – which he discovered in the summer of 1992 when he proved a theorem about using qubits to quantify quantum information. Schumacher’s paper wasn’t published for three more years, but afterward, the term qubit stuck and is used in every discussion of quantum today.
Things quickly got faster for qubits from there, as the first working 2-qubit quantum computer was demonstrated in 1998. By 2001, we had a 7-qubit working quantum computer, and in 2005, the first quantum byte (qubyte) was created at the University of Innsbruck in Austria.
Quantum Supremacy
Besides qubits, another quantum term that appears everywhere is “quantum supremacy.” But what is quantum supremacy, and why does it matter?
In essence, quantum supremacy is the ability of a quantum computer to perform a specific task better than a classical computer could. This can mean performing it faster or more accurately or taking over a task that isn’t practical for classical computers because of storage or computational power limitations. This is an important milestone for quantum computing because it proves its viability.
In 2019, Google and NASA announced that a joint partnership between the entities, along with Oak Ridge National Laboratory, had demonstrated quantum supremacy. Classical computers and quantum computers were pitted against each other to compute random circuits, a task that takes a significant amount of calculating power. At some point in the testing, the random circuits became too complex for the classical supercomputer. Google’s quantum computer was able to compute beyond this limit, achieving quantum supremacy for the first time.
Current State of Quantum Computers: Separating Fact from Fiction
This section aims to provide an accurate assessment of the present state of quantum computers, addressing misconceptions, and highlighting real-world applications.
Types of Quantum Computers
Although many articles present quantum computers as a monolith, there are actually multiple types of quantum computers, just as there are multiple types of classical computers. The three types of quantum computers:
- Quantum Annealer: The least powerful of quantum computers, this type offers very few benefits over classical computers. Quantum annealer computers easily produce all three types but can only perform one specific function. The main use of this type of quantum computer will likely be optimization.
- Analog Quantum: This type of quantum computer is much more powerful than quantum annealer computers. Analog Quantum offers promise over classical computers. With applications ranging from optimization to dynamics to chemistry, analog quantum computers are predicted to help solve many mysteries in the field of physics.
- Universal Quantum: This type of quantum computer is the biggest challenge in quantum, but also the most promising. It outstrips other forms of quantum computing in both power and general application. Estimated to need more than 100,000 physical qubits, universal quantum computers have not yet been built. However, researchers and experts across industries anticipate the impacts universal quantum will have. Universal quantum computers will be able to help with machine learning and other algorithmic issues, expand cybersecurity, and be used for many unsolved issues in physical sciences.
Existing Quantum Computers
Quantum computers have existed in labs for quite a while, but are starting to enter the commercial presence. D-Wave, a pioneer in the quantum industry and the first commercial quantum computer company, premiered their Orion system in 2007.
They later launched the world’s first commercially available quantum computer in 2022. A competitor, IonQ, has been producing quantum systems for commercial use since 2019 and launched their first quantum computer commercially not long after D-Wave. Other companies working in the quantum computing space include IBM, Google, and Inte
Challenges and Limitations of Quantum Computers
Although quantum computers are currently in production from multiple companies, there are still many issues that must be worked out to achieve the full potential of quantum computing. One of these limitations is that many pieces of quantum infrastructure cannot be run at room temperature. Due to their need for super-cooling, quantum computers and networks can require vast amounts of energy to run and are currently very large.
Another issue with quantum computing is decoherence. As qubits interact with their environment, they lose superposition and become less stable. This can lead to errors in the calculations and programs run by quantum computers. Many scientists believe that we must solve the issues with decoherence before quantum computing becomes more useful than classical computing for most applications.
The expense involved with creating, building, testing, and using quantum systems remains a deterrent to quantum development. However, continued investments from government entities and private companies have helped ease the way for more quantum computers to be created.
Applications and Potential of Quantum Computers
Despite the issues remaining with quantum development, quantum is in use and here to stay – with exciting developments promising to revolutionize industries well beyond IT. For example, quantum key distribution is a potential application of quantum computing that will significantly improve key distribution, enhancing cybersecurity.
Another application of quantum computing is optimization. Optimization is a key aspect of industries ranging from machining to finance. Current algorithms may take a significant amount of time to run, limiting their usefulness; the ability of quantum computers to reduce time spent processing these algorithms will allow improvements in optimization across industries.
Exploring the Quantum Computers' Impact on Industries
This section focuses on the potential disruptive impact of quantum computers across various industries.
Cryptography and Security
Although quantum computing is lauded for cybersecurity due to the potential impacts of quantum key distribution and enhanced quantum algorithms, it also brings risks. One of these risks is the potential for a threat actor with a quantum computer or access to other quantum technology to easily decrypt current algorithms protecting classical computers. However, many governments and private entities are taking steps to mitigate this threat.
Machine Learning and Optimization
Machine learning is a hot topic in computing due to its ability to solve complex problems and make accurate predictions. However, machine learning can require massive amounts of data storage and computing power.
Quantum computing, with its ability to reach multiple solutions at once, will likely improve the accuracy of machine learning and reduce the time it takes to solve complex problems. Quantum computing may help with common issues in machine learning, such as underfitting and overfitting.
Scientific Discoveries
Quantum computing is highly anticipated by many scientific communities as well as those in industry. This is because there are many scientific problems, especially those relying on the behavior of quantum information, which we cannot currently solve for. By observing phenomena such as superposition, quantum computing can help answer enduring questions about the universe.
Unveiling the Future of Quantum Computing
The future holds exciting possibilities for quantum computing. In this section, we'll explore the potential trajectory and challenges that lie ahead.
Scaling Up Quantum Computers
Quantum computers currently must use short algorithms due to the risk of decoherence. Issues with the need to keep components super-cooled also affect the ability to maintain quantum computing on a large scale. Finding ways to run quantum computers at room temperature, as well as solving for decoherence and enabling larger algorithms to be run, will be required before quantum computing can be feasible on a broader scale.
Hybrid Approaches on Quantum computers
Quantum computers, while revolutionary, are not suitable for every computing task. Due to this, hybrid approaches that combine the power of classical and quantum computing will be required to bring quantum computing into the future. Discovering the best balance between classical and quantum computing will help us make the most of quantum’s power and ability.
Beyond Binary Quantum computers
Classical computing will likely never go away completely. Quantum supremacy is the ability of quantum computers to do certain tasks better than classical computers, but not all tasks are suited for quantum.
However, for tasks like simulating quantum physics, encryption and the infamous traveling salesman problem, quantum computing promises significant benefits over classical computing. As quantum develops further over the next few years, it is likely we will begin to see even more potential applications and benefits.
Navigating the Quantum Landscape
Quantum computing is making headlines with new research released nearly every day. With promises of new career fields, improvements across industries and new discoveries, it’s time to get excited about quantum. While we don’t expect to see classical computing disappear, quantum computing will continue to grow as an industry, especially as more of its applications move from theory to reality.
An important element of quantum computing that allows quantum computing and other developments to be tested and proven is quantum networking. Find out more about how EPB Quantum Network® is helping make quantum a reality by visiting this link.
The first commercially available quantum network, EPB Quantum Network, will allow companies to test and develop their quantum processors and other quantum equipment with lower developmental cost and lower go-to-market time. With more companies in the quantum game than ever, it’s impossible to understate the importance of quantum networking.
As we conclude our exploration of the existence and evolution of quantum computers, one thing becomes clear: the journey from theoretical concepts to real-world impact has been both remarkable and challenging. While quantum computers do indeed exist, their potential is still unfolding, promising breakthroughs that could reshape the technological landscape in ways we can only begin to comprehend.
