## Current quantum computers are to quantum computing what the ENIAC is to classical computing; the challenge is to get them to move as fast

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The ENIAC was awesome. intimidating. This computer, one of the first machines **general purpose** history, it weighed around 27 tons, occupied 167 square meters and used no less than 18,000 thermionic valves. John Mauchly and J. Presper Eckert, its designers, started it up to solve a real problem at the end of 1945, at the University of Pennsylvania, and it remained operational until 1955.

The development that classical computers have experienced since then has been amazing. And it has been marked above all by the arrival of a component: **the transistor**. He made his debut in 1947 at the hands of John Bardeen, William Shockley and Walter Brattain, three physicists at Bell Laboratories. A simple way to define it invites us to describe it as a semiconductor electronic device that is capable of responding to an input signal by giving us a certain output.

In any case, leaving their operating principle aside, what we are interested in remembering in this article is that transistors put an end to the hegemony of vacuum tubes in the world of electronics in general, and in the world of computing. in particular. His incursion started a wild race that caused computers to become smaller, more powerful and cheaper. **And also more popular**.

There is no doubt that without the invention of the transistor **we wouldn’t be where we are**. Computers and our electronic devices would not be as they are. If we reflect for a moment we can glimpse the parallelism that exists between current quantum computers and that gigantic ENIAC that left so many people stunned in the middle of the 20th century.

In some way, the prototypes of quantum machines that we have are like that pioneering computer, and this invites us to conclude that quantum computing is possibly awaiting the arrival of **its own “transistor effect”**.

## Quantum computing has it harder than classical

The development that quantum computing has experienced over the last two decades has been monumental. Little more than twenty-five years have passed since the Spanish physicist Ignacio Cirac and the veteran Austrian physicist Peter Zoller proposed **the theoretical foundations** of this discipline, but they have been enough so that we already have machines capable of solving some practical problems. Despite its still numerous limitations.

But there’s still a lot to do. Very much, actually. When transistors arrived the rudiments of classical computing **they were formalized** thanks to the work of mathematicians as colossal as Alan Turing or John von Neumann, among other famous scientists.

Some scientists, such as the Israeli mathematician and professor at Yale University, Gil Kalai, argue that we will never have fully functional error-correcting quantum computers.

Of course, in the middle of the 20th century there was still a lot to be done to develop the computers we have today, but it was more about **refine a technology** with whom we already felt comfortable flirting than solving great challenges.

Quantum computing, however, still poses enormous challenges. Titanic, actually. In fact, they are so challenging that some scientists, such as the Israeli mathematician and professor at Yale University, Gil Kalai, argue that we will never have fully functional quantum computers capable of correcting their own errors. And this is precisely one of the biggest challenges that researchers in quantum computing are working on: **bug fixes**.

The quantum superposition effect only holds up to the instant when we measure the value of a qubit. When we carry out this operation **the overlay collapses** and the qubit takes on a single value, which will be 0 or 1. The problem is that, given the very nature of quantum systems, it is very difficult to know whether or not an error has occurred.

An interesting strategy that researchers are working on to advance error correction is to **do not measure directly** the value of the qubits involved in a quantum logic operation so as not to cause the superposition to collapse.

The idea is to consult the value of other qubits coupled to the “main” qubits, but not involved in the calculations, to **knowing indirectly** the value of the latter. The pity is that this strategy has a major problem: for it to work we need to work with a lot of qubits.

Having higher quality qubits will allow us to extend the useful life of quantum information

And this brings us to the next big challenge: we need **higher quality qubits**. The quantum data with which quantum systems operate is destroyed in a short period of time, so having higher quality qubits will allow us to extend the useful life of quantum information and carry out more complex operations with it.

Currently the two lines of research in the development of qubits that are yielding the best results are **superconducting circuits**which is the path being followed by Google, IBM and Intel, among other companies, and **ions suspended in electric fields**. This latter strategy is also known as ion trapping, and is so far less developed than the fine-tuning of superconducting qubits.

The third great challenge that quantum computing has put before us is none other than the need to implement **new quantum algorithms** that they are able to help us tackle the problems that we cannot solve with the most powerful classical supercomputers that we have today. These algorithms are what will allow quantum computers to make a difference.

Many researchers are convinced that fully functional quantum computers will come

However, despite everything we have just discussed, we can be reasonably optimistic. Many researchers, and they are absolutely serious scientists committed to their work, are convinced that quantum computers **fully functional will arrive**. They will have hundreds or even thousands of qubits. And also bug fixes.

The road ahead of us is intimidating, but we have a significant technological arsenal and **a very solid scientific background** at our disposal. We just have to cross our fingers. And investigate more.

The ENIAC was awesome. intimidating. This computer, one of the first machines general purpose history, it weighed around 27 tons,…

The ENIAC was awesome. intimidating. This computer, one of the first machines general purpose history, it weighed around 27 tons,…