Microsoft is determined to explore the capabilities and limitations of quantum computers compared to classical computers. Their new study assumed the creation of a scaled quantum computer with 10,000 fast, error-corrected logical qubits – or approximately one million physical qubits to identify significant speedups that will handle large complex operations, including chemistry simulations.
The effectiveness of quantum computers in addressing specific problems arises from their unique characteristics, which differ from classical systems. However, creating a practical quantum advantage or quantum practicality remains relatively rare due to the specific properties that enable quantum computers to be effective.
Microsoft has successfully created a scaled quantum computer to help establish and determine quantum computing capabilities and limitations by comparing its hypothetical performance against a state-of-the-art GPU-equipped classical computer. Microsoft assumed that the scaled quantum computer comprises 10,000 fast, error-corrected logical qubits, or approximately one million physical qubits.
Their experimental design was based on a two-week break-even point, implying that a quantum computer’s performance is superior to a classical computer for problems that can be solved within two weeks. According to their analysis, when comparing the hypothetical future quantum computer to a currently available single classical GPU, it is evident that a speedup of more than quadratic, and ideally super-polynomial, is necessary.
Additionally, their framework found that activities such as simulating the interactions of a single chemical can be represented by a limited number of interaction strengths between electrons in their orbitals. Although many approximate calculations of their properties are regularly conducted, these operations are exponentially complex on classical computers.
In contrast, they are significantly more efficient on quantum computers, meeting the guidelines established by the evaluation framework. While solving the most complex chemistry and materials science problems will require scaled quantum computing, the study found that progress can be made today with Azure high-performance computing.
Quantum Speedup and Limited Bandwidth: Implications for Future Quantum Computing
Microsoft has also emphasized that the bandwidth available to quantum computers is limited due to the higher complexity of each operation. As a result, even a scaled quantum computer will only be capable of handling a fraction of the bandwidth of specialized computer processors, such as graphics processing units that are frequently used for machine learning.
Furthermore, quantum computers have limited capacity for processing data sizes, making it necessary for the “quantum speedup” to occur through relatively straightforward versions of the problem being addressed.
The boundaries of what current and future quantum systems can achieve are determined by combining specific algorithms that exhibit a significant quantum speedup and problems that can be expressed using a limited amount of data. By applying these optimistic assumptions to various application domains, it is possible to determine where quantum computers will have the most significant impact in the future.
Overall, comparing the hypothetical future quantum computer and a single classical GPU shows that speedup is required more than quadratic – and ideally super-polynomial. This discovery is especially significant because many proposed quantum computing applications rely on quadratic speedups of specific algorithms, such as Grover’s algorithm.
Read more about it here.
