Theoretical and computational developments unlocking new possibilities for quantum sensing

The National Science Foundation Division of Chemistry awarded $491,790 to the Research Foundation of The City University of New York (doing business as RFCUNY - Queens College) on August 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to support theoretical and computational research on quantum sensing led by Seogjoo J. Jang at Queens College.

The project develops fundamental theories and computational methods to advance quantum sensing, which uses quantum properties to detect and measure physical or environmental properties with unprecedented sensitivity. Jang's group will advance quantum estimation theory to determine theoretical precision limits of quantum sensing and identify new protocols; develop reinforcement learning methods for practical design of control and sensing approaches; conduct detailed quantum calculations for defect centers used in quantum sensing; and develop quantum dynamics methods to guide experimental development and interpretation of results. The research will also create new theories of quantum sensing that exploit quantum coherence effects of electronic excited states to enable more accurate determination of molecular properties at nanometer length scales. Jang will complete a new edition of a quantum chemistry textbook and develop enhanced teaching and mentoring methods.

Performance occurs in Flushing, New York. The award runs from August 1, 2026, through July 31, 2029, with $491,790 obligated.

Abstract

Seogjoo J. Jang of the city university of new york ? Queens college is supported to conduct theoretical and computational research on quantum sensing (QS). QS utilizes the sensitivity of quantum properties for new and unprecedented ways to detect and measure physical or environmental properties. QS has recently made significant progress but promises to deliver even greater outcomes of substantial impacts while employing currently available technology. This project is aimed at realizing this potential by both advancing fundamental theories and computational methods in a synergistic manner. These developments will include incorporating state-of-the art machine learning methods into the domain of quantum dynamics methods. Outcomes of the project will contribute to the progress of QS in a comprehensive manner, by offering new ideas and more accurate computational tools for QS. Through this project, jang and his group will advance quantum estimation theory so as to help determine ultimate theoretical precision limits of QS and guide identifying new QS protocols, and will develop new quantum dynamics methods and models to assist experimental development of more accurate or new protocols of QS. To be more specific, jang?S group will develop reinforcement learning (RL) methods for practical design of control and sensing methods important for QS, will conduct detailed quantum calculations for defect centers used for QS, which then can be combined with developed quantum dynamics calculation methods for reliable guidance and interpretation of experimental results. Jang?S group will also develop new theories of QS that can actively utilize quantum coherence effects of electronic excited states for more accurate determination of molecular properties at nanometer length scale. Jang will also complete a new edition of quantum chemistry textbook, develop more effective teaching and mentoring methods for future generations of students by incorporating advanced AI tools. Finally, jang will continue organizing workshops on theoretical and computational chemistry to facilitate exchange of ideas within related fields and to promote new interdisciplinary efforts. The newly developed quantum estimation theory for QS will elevate the quantum foundation theory to the level of a practical guiding principle for exploring new QS methods and determining ultimate theoretical precision limit. The theory will also help understand implications of recent advances in quantum thermodynamics for QS of realistic molecular systems. More efficient methods for open system quantum dynamics with general time dependent fields will be developed to help understand how time dependent driving and environmental effects can be combined to produce novel quantum phenomena. Application of the RL approach will help unlock new types of quantum states and control mechanisms that are both experimentally realizable and sensitive to small changes of environmental properties. Quantum dynamics modeling of defect centers will help gain more general understanding of how loose electrons in confined environments behave and interact with their surroundings. Theories of QS actively utilizing quantum coherence effects of electronic excitations will elucidate new and robust ways to determine molecular properties at nanometer length scale. More broadly, outcomes of this research project will provide new ideas and methods for technological innovations of QS devices such as nanoscale and high precision electromagnetic sensors, temperature sensors, and BIO-imaging tools. New theoretical advances in quantum estimation theory will help establish key connections between computational molecular sciences and foundational quantum theories. 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.- subawards are not planned for this award.