Fast-forward quantum calculations are about the time constraints imposed by decoherence that plague today’s machines.
A new algorithm that can quickly increase simulations ahead of time can increase the use of current and near quantum computers, providing the opportunity for applications to run past strict time constraints that hamper many quantum calculations.
“Quantum computers have a limited amount of time to perform calculations before their useful quantum markets, which we call coherence, break,” said Andrew Sornborger of the Department of Computer, Computer and Statistical Sciences at the Los Alamos National Laboratory and senior author. a paper said. the announcement of the research. “With a new algorithm we have developed and tested, we will be able to do quantum simulations quickly in advance to solve problems that were previously out of reach.”
Computers built from quantum components, also known as qubits, can solve extremely difficult problems that exceed the capabilities of even the most powerful modern supercomputers. Applications include faster analysis of large datasets, drug development and unraveling the mysteries of superconductivity, to name a few of the possibilities that could lead to major technological and scientific breakthroughs in the near future.
Recent experiments have shown the potential for quantum computers to solve problems within seconds that will take the best conventional computer millennia to complete. However, the challenge remains to ensure that a quantum computer can perform meaningful simulations before quantum coherence expires.
“We use machine learning to create a quantum trajectory that can approach a large number of quantum simulations at once,” Sornborger said. “The result is a quantum simulator that replaces a series of calculations with a single quick operation that can complete before the quantum correlation breaks down.”
The Variational Fast Forwarding (VFF) algorithm developed by the Los Alamos researchers is a hybrid combination of aspects of classical and quantum calculation. Although well-established statements exclude the potential of general speed transmission with absolute fidelity for arbitrary quantum simulations, the researchers circumvent the problem by tolerating small computational errors for intervals to provide useful, if slightly imperfect, predictions.
In principle, the approach allows scientists to simulate a system quantum mechanically for as long as they want. Practically speaking, the errors that build up as simulation times limit potential calculations. Nevertheless, the algorithm allows simulations far beyond the time scales that quantum computers can achieve without the VFF algorithm.
One feature of the process is that it takes twice as many receipts to speed up a calculation as the quantum computer that is fast forwarding would make up. In the recently published article, for example, the research group confirmed their approach by implementing a VFF algorithm on a two-kwbit computer to quickly advance the calculations that would be performed in a quantum simulation of one kwbit.
In future work, the Los Alamos researchers plan to explore the limits of the VFF algorithm by increasing the number of qubits they rapidly increase going forward, and examining the extent to which their systems can prosper. The research was published in the journal on 18 September 2020 npj Quantum Information.
Reference: “Variational Fast Forwarding for Quantum Simulation Beyond the Coherence Time” by Cristina Cîrstoiu, Zoë Holmes, Joseph Iosue, Lukasz Cincio, Patrick J. Coles and Andrew Sornborger, 18 September 2020, npj Quantum Information.
DOI: 10.1038 / s41534-020-00302-0
The research was supported by funding from the Los Alamos National Laboratory Information Science & Technology Institute, Department of Energy Advanced Scientific Computing Beyond Moore’s Law Program, and the Los Alamos National Laboratory Directed Research and Development Program.