Nabugu -

9 quantum computing challenges IT leaders should understand

While the theory of quantum mechanics is complex, the tech might offer practical uses for organizations. Learn about the challenges and opportunities of quantum computing.

Quantum computing may seem like a technology that belongs in the distant future, but there are potential real-world applications today. Still, in order to take advantage of those, organizations need to address the challenges quantum computing poses.

Many organizations are looking into practical use cases of quantum computing and for good reason. Quantum computing has the potential to solve computational problems significantly faster than existing classical computing approaches. Businesses might want to use quantum computing for optimizing investments, improving cybersecurity or discovering new paths for value creation.

Whereas classical computing encodes data into logical bits using transistors that can process information only one decision at a time, quantum computers encode problems into basic units of information called quantum bits (qubits) that can store multiple states of information at the same time. This encoding makes them perfect for complex optimization problems and cracking existing encryption codes.

Despite some excitement that quantum computing is better at solving some obscure problems faster than classical computers, enterprises need to address the existing challenges of quantum computing before they can broadly adopt practical tools and systems.

"Quantum computing has the potential to be seismically disruptive, and the businesses that are experimenting now stand to amplify business value and innovation," said Carl Dukatz, tech innovation strategy executive at Accenture, an IT services and consulting firm headquartered in Dublin. "Quantum could change the world, but there are numerous factors to consider in getting this right."

Here are nine quantum computing challenges business and IT leaders should understand.

1. Qubit's short life span

One major challenge to widespread quantum computing adoption is the qubit's fragile state.

Quantum computers encode information into qubits using ions, light or magnetic fields. Existing technologies can only keep the information in a quantum state for brief periods, limiting the duration of calculations.

Quantum computing has the potential to be seismically disruptive, and the businesses that are experimenting now stand to amplify business value and innovation.
Carl DukatzTech innovation strategy executive, Accenture

The slightest interference from outside the computer, such as radio waves, mechanical vibration or magnetic fields, can cause the field to break down. These types of interference further reduce the duration of calculations.

Decoherence is the process where qubits become entangled with their environment, leading to the loss of the delicate quantum properties used in quantum computing, said Shubham Munde, senior market research analyst at Market Research Future, a global market research company headquartered in Pune, Maharashtra, India. It's a drawback that limits their utility to small computational problems.

Researchers are exploring different designs that might be more resilient to noise or that can last longer. For example, light-based approaches are less susceptible to electrical noise but have yet to scale as quickly.

2. Current lack of scalability

Quantum computers need to be scalable to solve real-world challenges -- and researchers have a ways to go.

Quantum computers require specialized techniques and materials, which face challenges around fabrication precision, materials quality and minimizing defects.

Scalability can also require integrating multiple qubits, quantum gates and other components. Each of these components comes with different error rates, noise characteristics and operational requirements.

Qubits also need to interact with each other. But maintaining connectivity and enabling interactions between qubits are challenging.

This existing lack of scalability is a major challenge that requires new materials and technologies, Munde said. Special quantum gates operating in sequence are needed to manipulate qubits, and it's critical to control errors and decoherence as these processes are chained together.

The differences between classical computing vs. quantum computing

3. Inefficient error correction

Qubits are much more likely to suffer computational faults than classical computing built on transistors and traditional storage technology. The bits in a classical computer are relatively stable until the power goes off in a CPU and can last much longer when laid down into magnetic disks or solid-state drives.

However, current qubit technology tends to lose the coherence required for calculations relatively quickly, and there is no easy way to store them.

Researchers are developing technology to organize multiple groups of these physical qubits together to operate more reliably into what is called a logical qubit. This is akin to the way RAID in classical computers connects multiple physical drives to create one larger and more reliable logical drive. However, it's a bit more complicated with qubits than the classical bits stored in RAID.

There are many approaches for doing error correction in quantum computers, said James Sanders, principal analyst of cloud and quantum computing at CCS Insight, an industry analyst firm based in London.

One such example is a method called quantum error correction, which could minimize this drawback. In simple terms, the process involves joining multiple physical qubits into one longer-lived logical qubit.

Like RAID, logical qubits need more space to represent each logical qubit. In a RAID system, each logical bit is stored across two physical drives. Other RAID schemes optimized for speed or reliability may require three or more physical bits for each logic bit.

But current quantum error correction schemes fare much worse.

The most optimistic approaches suggest that it might be possible to transform 100 physical qubits into one logical qubit, Sanders said. Approaches that require 10,000 physical qubits to create one logical qubit are currently more realistic.

4. Demand for highly complex hardware

Quantum computing requires highly specialized computer hardware to successfully build qubits. The challenge here is that there aren't enough physical resources to quickly manufacture high-quality, quantum-ready components for enterprise usage at a reasonable cost.

The current crop of quantum computers also requires ultracool temperatures to maintain their quantum state. The complexities of this process negatively affect any enterprise's long-term environmental, social and governance strategy.

However, some academical labs are beginning to experiment with utilizing different types of existing computer hardware that minimize these challenges.

There are dozens of ways to build qubits in academia, Sanders said.

Early commercially available quantum systems would likely rely on superconducting. Superconductivity is when certain materials conduct an electric current with minimal resistance.

Another possibility is a trapped-ion quantum computer, where the qubits are ions trapped by electric fields and manipulated with lasers. Trapped ions have longer coherence times, which means longer-lived qubits.

Further examples include Intel's experimentation with building qubits on top of the company's existing investment in semiconductor technology. There are startups exploring other approaches that build qubits from cold atoms, electrons on helium and photons.

"These [different] systems show great promise in qubit fidelity and system scalability, which will significantly aid in the quality and total capacity of commercially available quantum computers," Sanders said.

5. Limited availability of digital infrastructure

Many organizations might balk at the initial investment required for a single quantum computer. Company leaders might decide that the better move is to find a service provider that grants access to a quantum computer's capabilities.

Although vendors are beginning to offer remote access to the latest quantum computing hardware, widespread availability remains limited.

Cloud services, such as Amazon Braket and Azure Quantum, provide early access to quantum computers from multiple vendors. These cloud services also offer interfaces to store algorithms and results calculated by a quantum computer in the same environment enterprises might already use for high-performance computing in the cloud.

Cloud vendors are also starting to provide access to quantum simulators for developing quantum algorithms that run on classical computers but at a much lower speed.

Enterprises should think about experimenting with different types of quantum computers via these cloud services to find the best fit for their applications and goals, Sanders said.

6. Inadequate availability of software

You don't need to be a quantum physicist to write programs for quantum computers. But there's a considerable lack of available software for quantum computing systems.

This scarcity also means that there's almost no cross-compatible software that works well between quantum computers. Quantum algorithms might need fine-tuning to work effectively on different or similar types of quantum computers from other vendors.

Industry groups, like the QIR Alliance, are developing intermediate representations for quantum software.

This would make it easier to port quantum software between systems, Sanders said.

7. Limited scope for strategic implementation

Organizations must have a tactical roadmap before adopting quantum computing for the enterprise.

"Quantum computing has such vast potential that it can be difficult to know where to start," Dukatz said.

A haphazard enterprise approach to quantum computing only produces innovative sparks with no lasting value. Some potential actions could include researching only a single use case or deploying quantum computing in pockets across the enterprise.

A much better approach would be to analyze how quantum computing could affect the enterprise broadly across industries, functions, R&D, IT and security practices. Such an approach could help guide discussions across business and IT teams to lay the foundations for integrating existing enterprise data and services with new quantum cloud services.

8. Few workers with quantum computing skills

The task of finding potential employees with specific skills in quantum computing remains a key issue.

Research labs and academic institutions conducted early quantum research. However, quantum research skills had limited usage outside of those specific settings.

A talent shortage to harness quantum capabilities exists now that quantum is moving into the mainstream, Dukatz said. Currently, the talent gap goes unnoticed because few companies have started their quantum journey.

Companies should start experimenting now and get the right talent in place because quantum skills take time to develop.

Building a continuous learning program to upskill quantum scientists, data scientists, software engineers and others on quantum hardware, algorithms and use cases can help enterprises to stay ahead of the curve, Dukatz said.

9. Ineffective security protocols

There are potential security threats that quantum computing systems pose to existing data protection systems. For example, quantum computers have the processing power to crack most existing encryption schemes and security protocols that secure modern business systems and communications.

"There is real concern that current cryptography solutions won't hold up to future quantum computing, making everyone vulnerable to 'steal now, decrypt later' attacks," Dukatz said.

To combat this, researchers are developing new quantum cryptography techniques. As enterprise usage of quantum computers matures, employing quantum algorithms to secure sensitive data from potential threats and risks can address the challenge.

The World Economic Forum predicted that 20 billion digital devices must be upgraded or replaced with new post-quantum cryptography. NIST has started selecting such quantum-safe protocols but hasn't finalized the most efficient and secure approaches.

Enterprises should develop crypto-agility infrastructure that helps quickly switch among algorithms, cryptographic primitives and other encryption mechanisms as they become available, Dukatz said.

Next Steps

AI and climate change: The mixed impact of machine learning

Dig Deeper on Digital transformation

Cloud Computing
Mobile Computing
Data Center
and ESG