You may have heard that a qubit in superposition isboth 0 and 1 at the same time. Thats not quite true and also not quite false. The qubit in superposition has someprobability of being 1 or 0, but it represents neither state, just like our quarter flipping into the air is neither heads nor tails, but some probability of both. In the simplified and, dare we say, perfect world of this explainer, the important thing to know is that the math of a superposition describes the probability of discovering either a 0 or 1 when a qubit is read out. The operation of reading a qubits value crashes it out of a mix of probabilities into a single clear-cut state, analogous to the quarter landing on the table with one side definitively up. A quantum computer can use a collection of qubits in superpositions to play with different possible paths through a calculation. If done correctly, the pointers to incorrect paths cancel out, leaving the correct answer when the qubits are read out as 0s and 1s. <\/p>\n
For some problems that are very time-consuming for conventional computers, this allows a quantum computer to find a solution in far fewer steps than a conventional computer would need. Grovers algorithm, a famous quantum search algorithm, could find you in a phone book of 100 million names with just 10,000 operations. If a classical search algorithm just spooled through all the listings to find you, it would require 50 million operations, on average. For Grovers and some other quantum algorithms, the bigger the initial problemor phone bookthe further behind a conventional computer is left in the digital dust. <\/p>\n
The reason we dont have useful quantum computers today is that qubits are extremely finicky. The quantum effects they must control are very delicate, and stray heat or noise can flip 0s and 1s or wipe out a crucial superposition. Qubits have to be carefully shielded, and operated at very cold temperaturessometimes only fractions of a degree above absolute zero. A major area of research involves developing algorithms for a quantum computer to correct its own errors, caused by glitching qubits. So far, it has been difficult to implement these algorithms because they require so much of the quantum processors power that little or nothing is left to crunch problems. Some researchers, most notably at Microsoft, hope to sidestep this challenge by developing a type of qubit out of clusters of electrons known asa topological qubit. Physicists predict topological qubits to be more robust to environmental noise and thus less error-prone, but so far theyve struggled to make even one. After announcing a hardware breakthrough in 2018, Microsoft researchersretracted their work in 2021 after other scientists uncovered experimental errors. <\/p>\n
Still, companies have demonstrated promising capability with their limited machines. In 2019, Google useda 53-qubit quantum computer to generate numbers that follow a specific mathematical pattern faster than a supercomputer could. The demonstration kicked off a series of so-called quantum advantage experiments, which saw an academic group in Chinaannouncing their own demonstration in 2020 and Canadian startup Xanaduannouncing theirs in 2022. (Although long known as quantum supremacy experiments, many researchers have opted tochange the name to avoid echoing white supremacy.) Researchers have been challenging each quantum advantage claim by developing better classical algorithms that allow conventional computers to work on problems more quickly,in a race that propels both quantum and classical computing forward. <\/p>\n
Meanwhile, researchers havesuccessfully simulatedsmall molecules using a few qubits. These simulations dont yet do anything beyond the reach of classical computers, but they might if they were scaled up, potentially helping the discovery of new chemicals and materials. While none of these demonstrations directly offer commercial value yet, they have bolstered confidence and investment in quantum computing. After having tantalized computer scientists for 30 years, practical quantum computing may not exactly be close, but it has begun to feel a lot closer. <\/p>\n
What the Future Holds for Quantum Computing <\/p>\n
Error-prone but better than supercomputers at a cherry-picked task, quantum computers have entered their adolescence. Its not clear how long this awkward phase will last, and like human puberty it can sometimes feel like it will go on forever. Researchers in the field broadly describe todays technology as Noisy Intermediate-Scale Quantum computers, putting the field in the NISQ era (if you want to be popular at parties, know that its pronounced nisk). Existing quantum computers are too small and unreliable to execute the fields dream algorithms, such as Shors algorithm for factoring numbers. <\/p>\n
The question remains whether researchers can wrangle their gawky teenage NISQ machines into doing something useful. Teams in both the public and private sector are betting so, as Google, IBM, Intel, and Microsoft have all expanded their teams working on the technology, with a growing swarm of startups such as Xanadu and QuEra in hot pursuit. The US, China, and the European Union each have new programs measured in the billions of dollars to stimulate quantum R&D. Some startups, such as Rigetti and IonQ, have even begun trading publicly on the stock market bymerging with a so-calledspecial-purpose acquisition company, or SPACa trick to quickly gain access to cash. Their values havesince plummeted, in some cases by much more than the pandemic correction seen more broadly across tech companies. Its not quite clear what the first killer apps of quantum computing will be, or when they will appear. But theres a sense that whichever company is first to make these machines useful will gain big economic and national security advantages. <\/p>\n
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