## 1 Introduction  
Assessing the future of emergent technologies is not an easy task. Today there is a lively debate in the scientific community about whether classical or quantum computing will offer better performance in the coming future. At present, the field effect transistor is still the most efficient device to perform classical computations. The electronic industry is able to fit \(10^{10}\) transistors all together in a single chip, working at frequencies of a few GHz [1]. State-of-the-art transistors, with nanoscale dimensions, are quantum devices in the sense that their ability to convert the input into output information is based on quantum laws governing electron transport [2]. In digital binary classical computing, the logical state '1' is encoded into a value of a well-defined measurable physical property of the transistor, while the logic state '0' corresponds to a different value of such property. Usually the physical properties used in electron devices for classical computing are the electrical current or the voltage in different (input and output) terminals. It is important to notice that although the transistor is a quantum device whose performance is determined by the evolution of quantum states, these quantum states are not directly used to encode information in classical computing. In quantum computing [3], contrarily, the logical state '1' is directly encoded in a quantum state of the physical system, namely \(|1\rangle\rightarrow\psi_{1}(\vec{r},t)\) where \(\vec{r}\) represents the degrees of freedom of the system. Similarly, the logical state '0' corresponds to another quantum state \(|0\rangle\rightarrow\psi_{0}(\vec{r},t)\). Because of the quantum superposition principle, a sum of the two physical states, \(a|1\rangle+b|0\rangle\) where \(a\) and \(b\) are complex numbers, is also a valid physical state of the system. As a consequence, quantum mechanics offers the possibility of operating simultaneously on the logical states '1' and '0'. This opens classically inaccessible computing possibilities. Many companies and researchers are advocating for quantum computing. Among many others, for example, Google has said that its state-of-the-art quantum chip will be the first to perform calculations beyond the best existing classical supercomputers [4]. Other companies and researchers, on the contrary, understand quantum computing as an exciting discipline, with an unquestionable scientific interest, but argue that quantum technologies will not substitute our classical computing machines at home (because quantum computers are complex, expensive and built using a more immature technology) [5; 6]. In any case, without making any risky prediction, what seems clear today is that classical and quantum computing are both valuable research avenues. Any classical or quantum computation using quantum devices is implemented following three main steps: (i) initial preparation of the quantum state, (ii) unitary evolution of the state and (iii) the final measurement of the state. In this paper, we will focus on the last step for both classical and quantum computations. The measurement step is linked to the quantum uncertainty [7] that implies a practical inconvenience since it gives rise to quantum noise at the output of the device (The reader can argue that the uncertainty disappears when the quantum state is prepared as an eigenstate of the projective (measuring) operator. However, typically, the _preparation_ of the state of an electron being injected into the active device region from the contact (reservoir) is done by the contacts itself, which do not provide such eigenstates). Solid-sate quantum electron devices are unquestionably the best technology to implement classical computing. It is, however, not clear today which will be the best technology for quantum computing.