The advance offers a way to characterize a fundamental resource needed for EQuS) group have developed techniques using microwave technology to precisely control a quantum processor composed of superconducting circuits. In addition to these control techniques, the methods introduced in this work enable the processor to efficiently generate highly entangled states and shift those states from one type of entanglement to another — including between types that are more likely to support quantum speed-up and those that are not.
“Here, we are demonstrating that we can utilize the emerging quantum processors as a tool to further our understanding of physics. While everything we did in this experiment was on a scale which can still be simulated on a classical computer, we have a good roadmap for scaling this technology and methodology beyond the reach of classical computing,” says Amir H. Karamlou ’18, MEng ’18, PhD ’23, the lead author of the paper.
The senior author is William D. Oliver, the Henry Ellis Warren professor of electrical engineering and computer science and of physics, director of the Center for Quantum Engineering, leader of the EQuS group, and associate director of the Research Laboratory of Electronics. Karamlou and Oliver are joined by Research Scientist Jeff Grover, postdoc Ilan Rosen, and others in the departments of Electrical Engineering and Computer Science and of Physics at MIT, at MIT Lincoln Laboratory, and at Wellesley College and the University of Maryland. The research was published recently in the journal Nature.
Assessing Entanglement
In a large quantum system comprising many interconnected qubits, one can think about entanglement as the amount of quantum information shared between a given subsystem of qubits and the rest of the larger system.
The entanglement within a quantum system can be categorized as area-law or volume-law, based on how this shared information scales with the geometry of subsystems. In volume-law entanglement, the amount of entanglement between a subsystem of qubits and the rest of the system grows proportionally with the total size of the subsystem.
On the other hand, area-law entanglement depends on how many shared connections exist between a subsystem of qubits and the larger system. As the subsystem expands, the amount of entanglement only grows along the boundary between the subsystem and the larger system.
In theory, the formation of volume-law entanglement is related to what makes quantum computing so powerful.
“While have not yet fully abstracted the role that entanglement plays in quantum algorithms, we do know that generating volume-law entanglement is a key ingredient to realizing a quantum advantage,” says Oliver.
However, volume-law entanglement is also more complex than area-law entanglement and practically prohibitive at scale to simulate using a classical computer.
“As you increase the complexity of your quantum system, it becomes increasingly difficult to simulate it with conventional computers. If I am trying to fully keep track of a system with 80 qubits, for instance, then I would need to store more information than what we have stored throughout the history of humanity,” Karamlou says.
The researchers created a quantum processor and control protocol that enable them to efficiently generate and probe both types of entanglement.
Their processor comprises superconducting circuits, which are used to engineer artificial atoms. The artificial atoms are utilized as qubits, which can be controlled and read out with high parallel publication published in Nature in 2023,” says Peter Zoller, a professor of theoretical physics at the University of Innsbruck, who was not involved with this work.
“Quantifying entanglement in large quantum systems is a challenging task for classical computers but a good example of where quantum simulation could help,” says Pedram Roushan of Google, who also was not involved in the study. “Using a 2D array of superconducting qubits, Karamlou and colleagues were able to measure entanglement entropy of various subsystems of various sizes. They measure the volume-law and area-law contributions to entropy, revealing crossover behavior as the system’s quantum state energy is tuned. It powerfully demonstrates the unique insights quantum simulators can offer.”
In the future, scientists could utilize this technique to study the thermodynamic behavior of complex quantum systems, which is too complex to be studied using current analytical methods and practically prohibitive to simulate on even the world’s most powerful supercomputers.
“The experiments we did in this work can be used to characterize or benchmark larger-scale quantum systems, and we may also learn something more about the nature of entanglement in these many-body systems,” says Karamlou.
Reference: “Probing entanglement in a 2D hard-core Bose–Hubbard lattice” by Amir H. Karamlou, Ilan T. Rosen, Sarah E. Muschinske, Cora N. Barrett, Agustin Di Paolo, Leon Ding, Patrick M. Harrington, Max Hays, Rabindra Das, David K. Kim, Bethany M. Niedzielski, Meghan Schuldt, Kyle Serniak, Mollie E. Schwartz, Jonilyn L. Yoder, Simon Gustavsson, Yariv Yanay, Jeffrey A. Grover and William D. Oliver, 24 April 2024, Nature.
DOI: 10.1038/s41586-024-07325-z
Additional co-authors of the study are Sarah E. Muschinske, Cora N. Barrett, Agustin Di Paolo, Leon Ding, Patrick M. Harrington, Max Hays, Rabindra Das, David K. Kim, Bethany M. Niedzielski, Meghan Schuldt, Kyle Serniak, Mollie E. Schwartz, Jonilyn L. Yoder, Simon Gustavsson, and Yariv Yanay.
This research is funded, in part, by the U.S. Department of Energy, the U.S. Defense Advanced Research Projects Agency, the U.S. Army Research Office, the National Science Foundation, the STC Center for Integrated Quantum Materials, the Wellesley College Samuel and Hilda Levitt Fellowship,