Adjunct Assistant Professor

3100F Atlantic Building

(301) 314-1899

Nicole Yunger Halpern is a NIST physicist and Adjunct Assistant Professor of Physics and IPST at the University of Maryland.

Yunger Halpern reenvisions 19th-century thermodynamics for the 21st century, using the mathematical toolkit of quantum information (QI) theory. She applies QI thermodynamics as a lens through which to view the rest of science, gaining new perspectives on atomic, molecular and optical physics, condensed matter, chemistry, high-energy physics, and biophysics. Yunger Halpern calls this research “quantum steampunk,” after the steampunk genre of art and literature that juxtaposes Victorian settings with futuristic technologies. Go here for an overview.

She received her doctorate in physics from Caltech in 2018. Yunger Halpern's thesis won the international Ilya Prigogine Prize for a thermodynamics dissertation. She is continuing in her post as an ITAMP Postdoctoral Fellow at Harvard University until summer 2021.

Go here to view Yunger Halpern's academic publications on Google Scholar. Her blog can be found here.

“Non-Abelian eigenstate thermalization hypothesis”, Phys. Rev. Lett., vol. 130, 2023. ,

“Experimental Observation of Thermalization with Noncommuting Charges”, PRX Quantum, vol. 4, 2023. ,

“Non-Abelian symmetry can increase entanglement entropy”, Physical Review B, vol. 107, 2023. ,

“Negative Quasiprobabilities Enhance Phase Estimation in Quantum-Optics Experiment”, Phys. Rev. Lett., vol. 128, p. 220504, 2022. ,

“Linear growth of quantum circuit complexity”, Nat. Phys., 2022. ,

“Resource theory of quantum uncomplexity”, Physical Review A, vol. 106, 2022. ,

“Experimentally Measuring Rolling and Sliding in Three-Dimensional Dense Granular Packings”, Phys. Rev. Lett., vol. 129, no. 4, p. 048001, 2022. ,

“How to build Hamiltonians that transport noncommuting charges in quantum thermodynamics”, npj Quantum Inf, vol. 8, no. 10, 2022. ,

“Entangled quantum cellular automata, physical complexity, and Goldilocks rules”, Quantum Science and Technology, vol. 6, p. 045017, 2021. ,

“Machine learning outperforms thermodynamics in measuring how well a many-body system learns a drive”, Scientific Reports, vol. 11, 2021. ,

“Noncommuting conserved charges in quantum many-body thermalization”, Phys. Rev. E , vol. 101, no. 042117, 2020. ,