In quantum computing, the challenge is to keep qubits isolated to prevent decoherence, which can be achieved through various techniques, including using vacuum chambers and ion traps.

The decoherence time, which is the duration a qubit can maintain its quantum state, is crucial for quantum computing, with ion traps achieving significantly longer coherence times compared to other methods.

The challenge in quantum computing lies in scaling; while achieving high fidelity with a small number of qubits is possible, creating a robust system that consistently performs well with a larger number of qubits is a significant engineering problem.

Network approaches to quantum computing enable any qubit to link with any other qubit, enhancing connectivity and power, despite the increased risk of errors if not managed correctly.

The coherence time of a qubit, which indicates how long it can interact with the outside world, has improved significantly, increasing about tenfold every three years over the past 15 years.

The key to making quantum algorithms work lies in the concept of interference, where the wrong answers cancel each other out, enhancing the correct answer. Designing a quantum algorithm to achieve this interference is not automatic; it requires careful planning.

To be genuinely useful, a quantum computer needs to exceed 50 qubits, as tasks requiring fewer qubits can still be efficiently simulated by classical computers, making them less impactful.

Improving the reliability of quantum gates and reducing error rates will be crucial for scaling quantum computers and enabling them to solve more complex problems.

Achieving high fidelity in qubit operations is crucial; the Oxford team has reached a fidelity of 99.9%, which is essential for reliable quantum computing operations.