Will Quantum Computing Make Our Laptops Obsolete? | by Yasmeen Naseer | Jan, 2023
There’s no doubt that computers have helped move humanity forward at record pace. And most people — myself included — couldn’t really imagine a world without them.
Computers have allowed us to communicate with people regardless of where in the world they are at the click of a button; they’ve allowed us to make breakthroughs in science and medicine by helping us analyze quantities of data that would’ve impossible without them and they’ve also, quite literally, put the world in our pocket. With increasingly humanoid computer applications and robots cropping up all around us — think Sophia, the first robot Innovation Ambassador for the UNDP and ChatGPT by Open AI — it’s also hard to imagine that computers might truly have their limits.
But for some scenarios, the classical computers we’ve always known, simply fall short. This is especially true for complex problems. These include, for example, determining the optimal routes for tankers in a global shipping network — a complex problem given the multitude of variables such as weather conditions and traffic that any solution must account for, and simulating the impact of global warming on climate and environmental conditions around the world.
Quantum computing is a relatively new and rapidly developing field that aims to harness the seemingly strange principles of quantum mechanics — a branch of physics that deals with the behavior of matter and energy at the atomic and subatomic level — to easily perform computations that are either impossible , or extremely difficult, on classical computers. Quantum computers can do this because they store and process data in a fundamentally different way than classical machines do. Where classical computers use binary digits or bits that can only assume one of two states, 0 or 1, to represent and process information; quantum computers use quantum bits or qubits that don’t have this limitation and can exist in either 1 or 0, or in a state of superposition that allows them to be in both states simultaneously.
In addition to assuming multiple states, qubits can also become entangled — correlated in a way such that the state of one is dependent on the state of other qubits regardless of the distance that separates them. This makes it impossible to determine the state of one qubit without disturbing the state of the other.
These features of quantum systems can allow us to perform computations such as quantum teleportation — a technique for transferring quantum information from a sender to a receiver some distance away, and quantum cryptography — which allows us to encrypt data in an un-hackable way, that are not possible on classical computers.
They also allow quantum computers to store more data and represent and process multiple pieces of information at the same time so they are able to perform complex computations exponentially faster than classical computers and also perform some that are simply impossible for classical computers to perform. These include classic problems such as Shor’s algorithm for factoring large integers, breaking encryption, and quantum simulation, ie, the simulation of quantum systems such as atoms and molecules that classical computers cannot do in an efficient way. This makes quantum computers valuable for a wide range of industries such as finance, healthcare, and energy.
However, the principles that make quantum computing so useful for some applications are also the principles that make it extremely difficult. Due to the very nature of quantum mechanics, the behavior of qubits is difficult to control and stabilize and is also extremely sensitive to the environment so quantum computers need to be operated in extremely clean spaces at temperatures just above absolute zero. Quantum systems are also difficult to scale up as increasing the number of qubits also increases the system’s propensity for errors.
“The main problem with Google’s entangled qubits is that they are not “fault-tolerant.” The Sycamore processor will, on average, make an error every thousand steps. But a typical experiment requires far more than a thousand steps, so, to obtain meaningful results, researchers must run the same program tens of thousands of times, then use signal-processing techniques to refine a small amount of valuable information from a mountain of data . The situation might be improved if programmers could inspect the state of the qubits while the processor is running, but measuring a superpositioned qubit forces it to assume a specific value, causing the calculation to deteriorate. Such “measurements” need not be made by a conscious observer; any number of interactions with the environment will result in the same collapse.“Getting quiet, cold, dark places for qubits to live is a fundamental part of getting quantum computing to scale,” Giustina said. Google’s processors sometimes fail when they encounter radiation from outside our solar system.” —The New Yorker
Despite these challenges however, researchers and scientists are making significant progress in the field. New techniques are being developed to control and stabilize qubits alongside technologies such as quantum error correction codes, that will allow for the scaling up of quantum systems.
So while quantum computing is still somewhat a field in its infancy, will it eventually replace classical computers completely? Not necessarily. For starters, a lot of what quantum computers can do is still theoretical. Second, given the extreme conditions that the machines require to work, they’re unlikely to ever be portable and will probably mostly be used remotely for specialized applications by academics and businesses. They’re also notoriously difficult to operate — the best quantum computers right now have 50 qubits, which are enough to make them extremely powerful since each qubit translates into an exponential increase in processing capacity, but this also means that they presently have very high error rates for reasons already discussed.
Lastly, and perhaps most importantly, your good old laptop is still darn good at a lot of things — quantum systems only fare better than classical ones when it comes to solving a particularly hard set of problems categorized as non-polynomial, or NP — a class of computational problems that presently have no efficient algorithmic solution. The most likely scenario then is that classical and quantum computers will co-exist and complement each other, allowing us to add yet another tool in our toolkit for solving difficult problems.