*Over decades, the density of transistors in integrated circuits and hence computation efficiencies doubled approximately every two years. With chip features now below 10nm, semiconductor device fabrication enters the regime of quantum mechanics where, for example, spurious tunneling effects make it harder and harder to progress further by miniaturization. In order to keep thriving, we need to leave traditional routes and develop novel computing devices that exploit quantum physics instead of regarding it as a nuisance. This new and rapidly expanding branch of physics is a clear priority of both Trinity College and the Pratt School of Engineering, and provides important intellectual opportunities which impact traditional quantum physics as well.*

Quantum computers are qualitatively different and will allow us to solve problem classes that are impenetrable using classical computers. Currently, different physical realizations for quantum computing architectures such as superconducting electronic circuits, trapped ions, and quantum dots are being developed and investigated. All require an exquisite control of quantum degrees of freedom. Beyond the hardware, different paradigms of quantum computation are under investigation such as the quantum circuit model, measurement-based and adiabatic quantum computation, or topological computation.

The design of such novel quantum information processing architectures confronts us with many challenges ranging from engineering problems to fundamental questions in quantum physics, but many other interesting applications have little to do with actually building a quantum computer. Tools from quantum information theory are now employed to unravel the structure of quantum correlations, identify relevant efficient degrees of freedom, and to study the information theoretic complexity of physical systems, for example in quantum matter ranging from the study of condensed matter to the physics of black holes. In some ways, the most interesting promise of quantum computing is the ability to perceive complex quantum mechanical problems from a different perspective. Most of the challenges confronting implementations of such computers relate to core concepts in AMO physics, such as the distinction between coherence, correlation, and entanglement. The dynamics of systems with small numbers of discrete, coupled energy levels have been extensively explored for decades in multiple branches of molecular spectroscopy, most notably magnetic resonance. Experimental implementations are generally at the interface between quantum mechanics and statistical mechanics, limited by relaxation (what is called “decoherence”) and thermal population distributions. The quest to produce a usable number of “qubits” is a complexity challenge closely related to the underlying issues in most of the other Big Questions; two-level systems are very well understood, but N bits in N two-level systems give 2^{N} energy levels, and the dynamics quickly becomes extensive.

At Duke, we work on the realization of scalable quantum computers and employ insights from quantum information theory to unveil properties of condensed matter systems. Our experimental efforts for the construction of scalable quantum computers focus on systems of atomic ions which are trapped in free space using electromagnetic fields. Quantum information is stored in internal electronic states of the ions and elementary computational operations, so-called gates, are implemented through application of lasers and collective vibrational motions. Quantum gates have been realized with very high accuracy. Challenges are to retain accuracies and control errors when the system is scaled up, and to build networks of photonically interconnected ion traps. We also work on novel quantum algorithms for different tasks with the goal of demonstrating the supremacy of quantum computation over classical computation. With respect to interconnections between quantum computing devices, we develop schemes for strong matter-light interactions. Coupling with the environment generally leads to decoherence in quantum systems. As it is hence a natural adversary of quantum information processing, we seek for a deep understanding of decoherence and examine for example its ability to drive phase transitions, ways to attenuate its effect by engineering the system-environment interactions, or to protect against it through topological order. We further apply tools of quantum information theory to characterize the complexity of condensed matter systems, compare different phases of quantum matter, and identify reduced sets of relevant degrees of freedom to enable a simulation on classical computers where it is possible.