How close are we really to quantum computing?

11 Tem 03:44

Richard Feynman, renowned for his equations, proposed in 1982 that "classical computers are inadequate for simulating quantum systems," a perspective that is now becoming a reality. Today's quantum computers—judged by the Quantum Volume metric of brands like IBM, Google, IonQ, or Rigetti—are in the "Noisy Intermediate-Scale Quantum" (NISQ) phase. This means they are not yet fully error-tolerant but can deliver faster results than classical supercomputers for certain specialized tasks. For instance, last year, Google's Sycamore processor demonstrated a tangible advantage of quantum hierarchy in a chemical simulation, solving a calculation that would take months in just a few days. Imagine solving a classic game with a supercomputer: you sift through every possible move and probability over long computation times. Quantum computers tackle optimization problems in a similar way but attempt to find the best solution by "testing all possibilities at once." They could revolutionize fields like drug research—simulating protein folding—or material science, aiding in the search for superconductivity. However, industrial-level cooling systems and error-correction algorithms are still not fully mature. For now, quantum computers are akin to the early digital cameras of the 1980s, which, compared to today's professional cameras, were flashy toys—capable of revolutionizing specific areas but far from being a magical cure-all.