Quantum Engineering in the NISQ Era

Please join us for the opening event in our 2024-2025 Benjamin Banneker Lecture series! Dr. Thomas Searles (Associate Professor, ECE at University of Illinois Chicago) will be presenting on Quantum Engineering and and emerging Quantum information technology. This event is sponsored by the UCOP Advancing Faculty Diversity program and the Office of Diversity, Equity and Inclusion.

Abstract
Quantum information technology is emerging and expected to disrupt current critical communications, computing, and sensing infrastructure. Importantly, each of the near-term applications of quantum information are recognized globally as challenging in both a scientific and technological sense.

In the first part of his talk, Dr. Searles will present recent examples of quantum engineering research that show adaptation of a black-box quantum algorithm (Deutsch-Josza) based on a metamaterial-based graded-index lens for operation in the THz regime [1]. Then, he will present the temperature dependence and characterization of single photon outputs from a fiber-based entangled photon source expected for applications in a quantum-enabled internet [2,3]. He will present a quantum state tomography framework where state reconstruction is directly obtained from a set of measurements (both from optical and near-term intermediate scale superconducting qubit-based quantum hardware) and features enhanced application performance from a suite of artificial intelligence tools [4-7].

In the second part of his talk, Dr. Searles will detail his efforts to create a nation-wide quantum mechanics and quantum computer training programs between HBCU’s and PWI's to create a pipeline for a skilled, diverse workforce to bring ideas central to quantum information to real-world application outside of the laboratory [8]. As such, we will detail present activities at UIC to update an ABET-accredited Engineering Physics curricula and encourage students to gain experience and knowledge in quantum engineering.

References
1. A. N. Blackwell, R. Yahiaoui, Y. Chen, P. Y. Chen, T. A. Searles, and Z. A. Chase, " Emulating the Deutsch-Josza algorithm with an inverse-designed terahertz gradient-index lens," Optics Express, accepted (2023).
2. S. Lohani, J. M. Lukens, A. A. Davis, A. Khannejad*, S. Regmi, D. E. Jones, R. T. Glasser,
T. A. Searles, and B. T. Kirby, “Demonstration of machine-learning-enhanced Bayesian quantum state estimation” New Journal of Physics 25, 083009 (2023). *Undergrad Author
3. S. Lohani, S. Regmi, J.M. Lukens, R. T. Glasser, T. A. Searles and B. T. Kirby, “Dimension-adaptive machine-learning-based quantum state reconstruction”, Quantum Machine Intelligence 5, 1 (2023).
4. S. Lohani, J. M. Lukens, D. A. Jones, R. T. Glasser, T. A. Searles, and B. T. Kirby, “Data-centric machine learning in quantum information science”, Machine Learning Science & Technology 3, 04LT01 (2022).
5. S. Lohani, J. Lukens, D. Jones, T. A. Searles, B. T. Kirby and R. T. Glasser, “Improving application performance with biased distributions of quantum states”, Phys. Rev. Research 3, 043145 (2021).
6. S. Lohani, T. A. Searles, B. T. Kirby and R. T. Glasser, “On the experimental feasibility of quantum state estimation via machine learning”, IEEE Trans. on Quantum Engineering 2, 2103410 (2021).
7. S. Lohani, et al. Machine Learning Science & Technology 3, 04LT01 (2022).
8. A. Asfaw et. al, IEEE Trans. on Education 65, 220 (2022).

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