Entanglement is a key feature of quantum mechanics, allowing connected qubits to interact. In one example, using a qubit for, say, a measurement can reveal information about other connected qubits.
Superposition is another key characteristic. A qubit exists as a combination of all possible states simultaneously. Entanglement and superposition give quantum computers extra processing power not possible with traditional binary computers.
Maintaining qubit entanglement is another technical challenge. When entanglement is lost, quantum calculations are no longer valid.
There are multiple techniques for maintaining entanglement. Qubit isolation from environmental noise is the first step. Operating qubits at superconducting temperature reduces environmental noise dramatically. Fault tolerance is another strategy at the system level.
Some quantum technologies have built-in tolerance to environmental noise. The trapped-ion approach appears to outperform superconducting technology in this area.
The entanglement noise problem is often called decoherence. Decoherence occurs when a quantum computer loses information to the surrounding environment since the system is loosely coupled to the active state of its surroundings. Qubits must maintain coherence for quantum machines to operate properly.
Decoherence remains a challenge for quantum implementation due to reliance on the undisturbed evolution of the qubit state. The preservation of coherence, and mitigation of decoherence effects, are related to the concept of quantum error correction. It is generally agreed that error correction is needed for meaningful deployments supporting a range of quantum applications.
Further, quantum information cannot be copied, and measurement disrupts information, preventing implementation of classical error correction techniques. Quantum error correction techniques have been demonstrated but are challenging to implement. Error correction procedures are applied to many error-prone physical qubits. Those quantum procedures are combined with traditional processing techniques to create systems that simulate a robust, stable qubit—known as a logical qubit.
Current quantum platforms also exhibit slow I/O data rates. Future quantum computers will require faster data rates to support demanding quantum apps. Slow I/O rates would diminish overall utilization rates, and the value of quantum computing would therefore decline in areas such as cloud services.
Minimizing decoherence requires operation close to absolute zero, initially limiting quantum deployments for enterprise IT applications. Quantum technologies that operate near room temperature will help expand deployments.
At least six different quantum technologies are in use or development, with others on the horizon. Technology battles are seldom good for nurturing new industry segments, creating market uncertainties. Potential users often delay deployments until a clear winner emerges. The nascent quantum industry would benefit with the emergence of one or two leading technologies.
The current qubit fabrication infrastructure and supply chain is limited. Thousands of physical qubits will be needed per machine, growing to hundreds of thousands of qubits by 2025. By 2030, state-of-the-art machines may include 1 million or more physical qubits.
Developers investing in manufacturing and supply chains for physical qubits will emerge as leaders in quantum application deployments. Superconducting specialists may have an advantage if they can leverage semiconductor industry fab capacity once current chip shortages recede.
Quantum computers also will require an extensive ecosystem across many software platforms at multiple levels, including quantum algorithms and applications. Software development kits to develop, test and verify quantum applications will be needed. Additional requirements include quantum-centric languages, compilers and other development tools focused on unique and demanding quantum applica
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