For hundreds of years, our understanding of the properties of matter and energy were based on mathematical equations formulated by Newton, Gauss, Maxwell and others by observing nature. These laws provide a useful model of motion, force, heat, electricity, and magnetism, and enabled us to build engines, power generators, computers, and communication devices.
In the 20th century, as we began to observe nature on atomic and subatomic scales, it became clear that the classical model was not sufficient to predict properties at small distances. Instead, a quantum model was necessary, introducing implausible features that were eventually verified in nature:
- The classical model can describe systems of particles or waves, but these are distinct phenomena. In the quantum model, matter exhibits properties of both waves and particles. This behavior allows a system such as a magnet, which has two classical directions of polarization (say “up” or “down”), to be in a quantum superposition of states, simultaneously polarized both “up” and “down.”
- states of multipartite systems can be “entangled,” exhibiting correlations that are stronger than classical theory allows.
In the 20th century, we used the quantum model to design new technologies, such as the transistor and the laser, that radically changed our lives. Now, in the 21st century, we are beginning to exploit quantum properties to build new computers and new communication devices. This requires a completely different way of thinking about how to solve problems with computers, and especially about how hard some problems are to solve.
These are deep questions with practical significance. Cryptography, which allows us to maintain secrecy in messages containing sensitive information such as financial or health data, is based on requiring anyone other than an authorized person to perform a very difficult computation in order to steal the information. Our current notions of difficulty are based on the classical model. In the quantum world, many computations that are classically difficult are in fact easy.
One of the immediate applications of quantum devices will be in modeling nature by computing the properties and behavior of chemical systems and physical devices at the quantum level. These are among the most difficult simulations done currently on classical computers. Quantum computers could be game changers, enabling more realistic modeling on a practical timescale. Such simulations could have broad impact, for example, on drug design, sustainable power generation, and development of new materials.
The mission of QuICS is to understand the consequences of representing and processing information quantum mechanically. A key reason to build a center on quantum information and computer science as part of an institute for computer studies is to better connect physicists, focused on how to build quantum devices, with computer scientists, asking how the devices can be used to solve problems.
The University of Maryland has top-ranked programs in computer science, physics, applied mathematics, and other related areas. With partners on campus, in the Joint Quantum Institute and the Quantum Engineering Center, and off-campus, at the National Institute of Standards and Technology, the Laboratory for Telecommunication Sciences, the Laboratory for Physical Sciences, and other government and industrial organizations, QuICS is uniquely positioned to bring the best minds together to explore the frontiers of quantum information science.