What Are the Challenges of Building Quantum Computers?
What are the obstacles to developing quantum computers? The promise of quantum computing is revolutionary for many fields, yet several barriers confront it. From sheer technical intricacies to exorbitant expenses, comprehending these impediments is vital for any enterprise contemplating the leap into the quantum realm.
Understanding Quantum Computing
Principles that differ significantly from those of classical computers govern the operation of quantum computers. They use qubits, which can simultaneously represent both 0 and 1. This allows quantum computers to solve certain problems far more quickly and efficiently than classical systems. IBM estimates that by 2030, quantum computers could outperform classical computers by a factor of one million in specific tasks. Still, the road to practical quantum computing bristles with challenges.
What Are the Challenges of Building Quantum Computers?
Decoherence is a primary challenge in quantum computing. Qubits rapidly lose their quantum state because of interactions with their environment. This happens even in a surrounding condition that is supposedly “quiet.” Operations are complicated, and computations are stable only when the qubits can maintain a quantum state for some length of time—what is called coherence time.
Cohesion times today range from micro to seconds, depending on the tech used.
The ability to scale quantum systems efficiently is impeded by decoherence.
In addition, constructing a quantum computer mandates the use of cutting-edge error correction methods. Quantum systems are innately prone to mistakes. Conventional error correction methods cannot be directly used, and so we must devise new algorithms to do the same job. One such algorithm is the surface code, a promising approach that unfortunately requires a huge number of physical qubits—sometimes cited as a 100-to-1 ratio—just to represent one logical qubit.
High Costs and Technical Demands
Yet another fundamental hurdle to developing quantum computers is the barrier of finances. The creation and maintenance of quantum systems require an enormous investment of dollars. Development costs alone, estimates suggest, can run into the millions. And those costs do not account for the ongoing research and operational expenditures that such embryonic projects demand. Who foots the bill? The best answer seems to be that we, the public, do. And that’s a serious problem.
In addition, the talent required for the actual working with quantum systems is in short supply. Quantum computing requires not just one but three types of specialized knowledge: physics, computer science, and engineering. When businesses recruit for these positions, they find that the funnel of qualified candidates is almost dry. And so, around 70% of the companies interested in quantum technologies and recruiting for that area say talent shortages are a big barrier to progress.
Training and education investment is essential to bridge this gap.
Working together with academic institutions can help foster the talent we need.
Integration and Practical Applications
An additional challenge is that businesses must identify appropriate use cases where quantum computing can offer clear and immediate advantages. These ought to be problems that are really, truly hard to compute (hint: many of these problems also have some pretty important consequences if you get them right). For example, they are working on using quantum computing to solve hard optimization problems in logistics; to tackle the kinds of massively parallel calculations that are necessary for serious drug discovery in pharmaceuticals; and to do complex financial modeling.
Applying these use cases to real-world applications takes a lot of testing and research. For example, demonstrating that quantum computers can do some things better than regular computers—what we call “quantum supremacy”—is something that companies like Google have done, but these demonstrations occur in very limited and controlled environments. When we leave these proof-of-concept settings and try to use quantum computers in a business context, we face the hurdles of translation. And the first step in translation is using a clear evaluation strategy paired with realistic expectations.
The Future of Quantum Computing
Although the problems associated with constructing quantum computers are greatly demanding, the payoffs could be very rewarding. Firms are putting a lot of money into this endeavor. In 2020, investments in quantum technology worldwide amounted to $1 billion. And leading the charge on this front are some of the biggest names in the tech sector, including IBM and Microsoft.
To sum up, what are the difficulties associated with constructing quantum computers? They are many, and they elicit considerable concern from both industry and government. From fundamental science to technology and engineering, there are a host of problems that push the limits of tolerable performance. Among them are these three daunting issues:
- Decoherence and error correction: Decoherence refers to the loss of quantum coherence, meaning that a quantum system loses its ability to maintain a superposition of states; in a quantum computer, this would mean the qubits stop behaving like qubits (and begin to behave like classical bits).
- Financial constraints: Building a quantum computer is going to require a lot of money—many billions of dollars.
- Talent shortages: The workforce necessary to build a quantum computer doesn’t yet exist in sufficient numbers.
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