The need for speed

Decoherence

Imperfect operations are one source for errors. However, noise within a quantum computer can come from various sources, such as the environment, imperfect hardware components, and even the way the algorithm is executed. The natural process that occurs as qubits interact with their environment is called decoherence. Essentially, when a qubit is measured or interacts with other particles, its state becomes entangled with the state of those other particles, leading to a loss of coherence. This can cause the qubit to deviate from its expected position on the Bloch sphere, which in turn can lead to unprecise or unexpected results.

Coherence time is the period during which a qubit can maintain its quantum state without being disrupted by external noise or loss of information.

Consequently, leveraging the window when qubits are insulated from environmental interactions is crucial. But it also means that we can only perform a limited number of operations within this window.

Up to 200 gates could be executed.

To exploit the full potential of quantum computing, operations must be performed quickly, within the coherence time. The better the ratio between coherence time and operation speed is, the more operations can be carried out.

Overall speed matters, too

However, even with extended coherence times, rapid operations remain crucial. Fast operation speeds are not just about avoiding decoherence. They are also about achieving a computational speedup over classical computers.

So, overall speed matters, too, particularly when considering the execution requirements of quantum circuits. It is crucial to recognize that quantum circuits are often executed multiple times to achieve the desired accuracy and reliability in results. This necessity becomes even more pronounced when we need to run a sequence of different circuits to perform a complex computation or to simulate a system.

Imagine a scenario where, instead of, let's say, 10 $\mu s$ it takes to execute one quantum circuit, a quantum circuits has an execution time of 10 $ms$. This difference might seem minor at first glance, but when we consider that for a lot of problems, we need to execute a large number of circuits, the impact becomes staggering as the increase translates to a thousandfold increase in the time required for each circuit's execution.

These numbers are not just theoretical. They are roughly based on the difference in current state quantum computing hardware (see table below). Ion-traps are another technology to realize qubits and quantum gates. They are known for their long coherence times, but they are slower in terms of gate speed. IQM produces superconducting quantum processors, which are faster in terms of gate speed, but have shorter coherence times.

Let's consider a concrete example next: in simulating a molecule, we might need to run 4 billion circuits. When applied to 4 billion circuits, this slower execution rate drastically elongates the overall computation time, transforming what could be a feasible computation time into one that is impractical for most applications.

Execution of 4 billion circuits would take 6 hour(s).