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NSF
Over the last century, quantum mechanics has driven transformative technological progress and reshaped the world through inventions such as lasers and semiconductors. In particular, quantum effects underpin intriguing phenomena defying classical intuition and unprecedented information processing capabilities, with an example being quantum computers. However, real-world quantum systems are inevitably coupled to their surrounding environment, which renders them essentially “open” and introduces decoherence and noise that usually obscure and destroy genuine quantum properties. Such impacts are especially detrimental for maintaining coherent control over large quantum systems with many particles, presenting a major challenge for advancing the frontiers of quantum technologies. This project aims to address this challenge by developing new protocols for preserving interesting quantum properties and unraveling associated quantum phenomena in open systems comprising many particles. The protocols will feature setups relevant to a number of existing and emerging quantum platforms. The proposed research will help enhance the capabilities for controlling quantum systems, which has applications ranging from quantum information processing to quantum metrology. In addition, the work conducted will enable advances in the physics of quantum systems subject to interactions with classical environments. In parallel with these research activities, this project incorporates a multi-layered educational component designed to engage students, inspire interest, and help prepare them for careers in quantum information science and engineering (QISE). This includes training and mentoring for graduate and undergraduate students, who will gain problem-solving skills and hands-on research experience in QISE. In addition, the project involves mini-workshops developed to provide students with focused learning opportunities on key quantum concepts and outreach activities aimed at engaging high school students, promoting general awareness of quantum research and fostering their interest in QISE. The overall goal of this project is to investigate quantum many-body systems interacting with an external environment and to develop protocols to prepare and preserve many-body correlated states in such systems, focusing on platforms relevant to current AMO experiments and near-term quantum processors. The adverse effects such as decoherence and noise arising from this interaction pose a major obstacle to advancing quantum technologies. The proposed project aims to tackle this challenge leveraging ideas from quantum optics and quantum information science. The research is structured around two interrelated thrusts. The first thrust aims to explore a variety of exotic many-body phenomena in dissipative AMO setups. The second thrust exploits the emerging capabilities offered by near-term quantum devices to engineer quantum correlated many-body states. A combination of analytical and advanced computational techniques will be employed to examine the resulting structure of many-body states, verify protocol designs that enhance the target quantum features, and elucidate the emergent behaviors across relevant parameter regimes. The expected project outcomes will advance knowledge at both foundational and practical levels. The systematic analysis of the many-body states in several classes of representative systems will expand the understanding of open quantum many-body systems. From a practical standpoint, the protocols developed will guide and facilitate the development of relevant quantum platforms for processing and protecting quantum information. The correlated many-body phenomena uncovered through these investigations will offer insights for engineering novel quantum matter in real systems, aiding in harnessing highly correlated quantum states for applications in quantum technologies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Up to $500K
2030-08-31
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