Scientists from Harvard announced a breakthrough in the field of quantum calculations. Researchers financed by the agency of advanced defense research projects of the United States (DARPA) and headed by scientists from Harvard with the support of Quera Computing, Massachusetts Institute of Technology, Princeton, National Institute of Standards and Technologies of the University of Maryland, argue that they have created a unique processor capable of revolutionizing calculations.
The industry talks about the future where quantum computers will be able to solve problems inaccessible to classic binary computers – this is the so-called “quantum advantage.” To achieve it, quantum computers should be stable enough to increase scale and capabilities. The main obstacle to the scalability of quantum systems is the noise.
Scientists from Harvard in their work entitled “logical quantum processor based on overstrown atomic arrays”, describe a method that allows them to conduct quantum calculations with resistance to errors and the ability to overcome noise. 
Researchers talk about the occurrence of an era of early correction of errors in quantum calculations and indicate the path to creating large-scale logical processors. Now quantum calculations are in the so-called era of “noisy quantum computers of medium-sized” (NISQ), characterized by the presence of less than 1000 cubes (quantum analogues of bits), which are mainly “noisy”.
Noisy cubes are problematic because they are prone to errors. The Harvard team claims that it has reached the “early correction of errors in quantum calculations”, overcoming the noise at the world level. However, according to their study, complete correction of errors has not yet been achieved.
Quantum calculations are complex because, unlike a classic bit, the cubes lose their information when measured. The only way to learn about the presence of an error in the calculations of the cube is to measure it. Full correction of errors involves the development of a quantum system that can identify and correct errors in the calculation process. So far, such techniques are difficult to scale.
Harvard’s team processor, instead of correcting errors during calculations, adds a post-cutting phase to detect errors, allowing them to identify and reject incorrect results. This, according to the study, opens up a new, possibly accelerated path to
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