Variational quantum algorithms (VQAs) play a significant role in improving the efficiency and accuracy of quantum computers. However, they come with high noise levels, which degrade their performance. Even though current techniques can mitigate their noise, they involve excessive computational overhead, which limits their feasibility.
However, in a paper written for IEEE Transactions on Quantum Engineering, Yigal Ilin and Itai Arad propose incorporating dissipative operations to alleviate the effects of the noise that plagues traditional VQAs. They call them dissipative variational quantum algorithms (D-VQAs).
D-VQAs enable the preparation of mixed quantum states without forcing the use of additional ancilla qubits. As a result, D-VQAs conserve significant amounts of computing power, primarily because they leave quantum computers with more qubits to power their processes. This is key because quantum computers often only have a very limited number of qubits available initially.
Why Prepare Gibbs States in Quantum Computing?
If a researcher or engineer prepares Gibbs states, they can study how quantum computing systems behave at specific temperatures. Gibbs states describe quantum systems in terms of their thermal equilibrium. This involves two classifications:
Low-energy particles , which have less energy.
, which have less energy. High-energy particles, which have higher energy.
Preparing the Gibbs state helps a researcher determine the probability of finding particles in each energy state, given a certain temperature.
This is important because, once someone can prepare Gibbs states on a quantum computer, it is far easier to simulate real-world physical conditions and how they may impact quantum computing.
Limitations of Traditional VQAs in Thermal State Preparation
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