Current quantum computing hardware faces several significant limitations that affect its practicality and broader application. One major issue is qubit coherence time, which refers to how long a qubit can maintain its quantum state before it decoheres due to environmental interference. Most current qubits are highly sensitive to surrounding noise, which leads to errors in quantum calculations. For instance, superconducting qubits, commonly used in many quantum systems, have coherence times in the range of tens to hundreds of microseconds, limiting the complexity of algorithms that can be reliably executed.
Another limitation is the scalability of quantum hardware. While there have been advancements in increasing the number of qubits in a system, interconnecting and controlling these qubits without introducing errors poses a significant challenge. For example, quantum processors from companies like IBM and Google have demonstrated systems with dozens of qubits, but expanding to thousands or millions of qubits, necessary for solving more complex problems, remains a hurdle. Each qubit added increases the complexity of the control circuitry and the potential for noise, which can lead to cumulative errors that may render computations unreliable.
Finally, the practical implementation of quantum error correction is another critical limitation. Although theoretically promising, the overhead required for error correction requires significantly more physical qubits than the logical qubits used for computations. Some estimates suggest that a logical qubit could require hundreds or even thousands of physical qubits to maintain its integrity during calculations. This need for extensive physical resources can make current quantum systems impractical for many intended applications. Therefore, while quantum computing holds lot of potential, these limitations must be addressed before it can be widely adopted for solving real-world problems.