NISQ-Computer: Quantum entanglement can be a double-edged sword
There is now great interest in quantum computers, fueled by the hope that they can perform certain computational tasks substantially faster than classical computers. However, building a quantum computer is a monumentally hard task, and we are still years away from building quantum computers that can perform perfect noiseless computations, which is the goal. Nevertheless, there have been impressive experimental advances in quantum hardware recently which grew access to small noisy quantum computers. They are called NISQ computers in short for Noisy Intermediate-Scale Quantum Computers. However, while NISQ computers need quantum entanglement as a key resource to perform computations, the presence of entanglement can also in some cases be a threat to their accuracy, like a recent paper shows. NISQ devices are not full-fledged quantum computers, since they have considerable noise levels and possess only a small number of qubits. They are therefore not capable of running most quantum algorithms. Nevertheless, it is believed that they possess capabilities that go beyond that of classical computers for certain tasks, such as sampling from some probability distributions. However, it remains a big open question whether they can outperform classical computers in problems of practical interest such as in chemistry, artificial intelligence or financial systems, because the noise levels in these devices place serious limitations on what they can achieve. The applications for which NISQ devices are being studied include optimization problems, quantum simulation, or machine learning, among others. Specifically, classical optimization problems are of interest to industry and academia alike, because they are very hard problems that appear often in real world situations. This means that they take considerable computational resources and can often be intractable in practice, as it would take too long to find the solution. An example of these problems is finding the fastest route for drivers delivering parcels or other practical optimization problems in engineering, economics or computer science. It is hoped that NISQ devices might offer a speed-up for these problems, but so far, NISQ devices have shown no evidence of outperforming classical computers for classical optimization problems, and it is unknown whether they will in the future.
In a recent work published in the journal PRX Quantum, Guillermo Gonzalez and Rahul Trivedi, a team of theorists from the Max Planck Institute of Quantum Optics lead by Ignacio Cirac, theoretically analyzed the impact of noise on the quality of the solution obtained by NISQ devices for classical optimization problems. Their findings propose that the errors in NISQ devices might be even more harmful to the computation than what was previously calculated. This comes as a consequence of entanglement, which is an indispensable ingredient for the power of quantum computers. When two qubits are entangled, there exists a powerful correlation between them, and changing the state of one of the qubits will instantaneously affect the other. Without entanglement, there would be no quantum computation. However, they have found that quantum entanglement might also be a double-edged sword: while it is necessary to unlock the power of quantum computers, the mechanisms to create entanglement in a quantum circuit can also propagate the errors of NISQ devices through the circuit. In their work, the group proposes a model based on random circuits which shows that, in the presence of entanglement, an error in one qubit can spread rapidly to the others and possibly to an extent that quantum circuits could lose their advantage over known classical algorithms. It would therefore be important to make efforts to limit the propagation of errors if we want to make use of NISQ devices, and to better understand in which situations does the fast propagation of errors arise, in order to find circuits that present a milder propagation.
In summary, the group found that the propagation of errors can pose a big problem for NISQ devices, and it is a consequence of the presence of entanglement. The analysis in their work suggests that the propagation of errors should be considered when designing quantum algorithms for NISQ devices, as it might guide us to design better circuits, even with current hardware constraints. Reference Error Propagation in NISQ Devices for Solving Classical Optimization Problems
Guillermo González-García, Rahul Trivedi, and J. Ignacio Cirac
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