RESEARCH INTERESTS at the Quantum Information Science Theory Group (QuIST)
The non-exhaustive list below summarizes the main research interests at QuIST in Sejong University.
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Noise mitigation and suppression of quantum systems
The protection of quantum information encoded in states of affairs of physical systems against noise is of paramount importance to ensure the performance reliablity of quantum processors. Quantum states of light are important examples of states of affairs of systems (e.g. multi-photonic and time-frequency modes in optical platforms, phononic modes in trapped-ion platforms, orbital-angular-momentum modes in structured light, etc.) described by an infinite-dimensional Hilbert space. These systems are therefore adequate for storing quantum information and are often coined bosonic or continuous-variable (CV) systems. Popular classes of states include superpositions of "cat" states and those of the Gottesman–Kitaev–Preskill (GKP) states. The ability to encode with these codes permits quantum error correction to bring logical errors down to 1e-15 (fault tolerance), in principle, so that encoded quantum information remains almost error free after gate operations.
Error correction with surface-GKP codes: Phys. Rev. A 101, 012316 (2020).
Generating GKP states in a photonic chip: Nature 642, 587–591 (2025).
These bosonic codes, however, are susceptible to noise themselves and techniques like error mitigation and suppression are employed to improve the quality (fidelity) of the codes. The former cancels noise on the data collected after a measurement and the latter preserves the system and its quantum state. The latter, however, generally requires nonlinear resources and recent studies have shown that entangling the bosonic modes with qubits (discrete-variable or DV), for instance, can offer powerful error suppression capabilities. Such CV-DV entanglement, known since the times of Jaynes and Cummings, is now an important resource in our exploration of noise suppression for more complex quantum systems.
Mitigating photon loss with photon-subtraction gadgets: Quantum Sci Technol. 10, 035003 (2025).
Suppressing dephasing errors with beam splitters and phase shifters: Quantum Sci Technol. 10, 035003 (2025).
Suppression of photon-loss and thermal noise using CV-DV entangling rotation gates, implementable in an optical cavity: arXiv:2511.04888 (2025).
References:
S. U. Shringarpure, S. Park, S. Cho, YST, H. Kwon, S. Omkar, and H. Jeong, arXiv:2511.04888 (2025).
YST, S. U. Shringarpure, S. Cho, and H. Jeong, Quantum Sci. Technol. 10, 035003 (2025).
H. Aghaee Rad et al., Nature 638, 912 (2025).
General quantum tomography
In modern terms, "quantum tomography" refers to an arsenal of tools required to characterize any aspect of a physical system that is described by quantum mechanics, which can either be a quantum state (or density operator) describing the system that could be photons or particles, a quantum process such as a unitary gate or more generally a completely-positive and trace-preserving map, or a set of measurement detectors mathematically described by a positive operator-valued measure or POVM. For a given size of quantum system (e.g. n-qubit system) that defines its dimension, full characterization can be performed with quadratically less measurement settings with modern compressive tomography if the state is nearly pure, or if the process is nearly unitary, or if the detector is nearly rank-one (pure projectors).
As systems become more complex, people look at other tasks that partially characterize them. These typiclly involve the estimation of observable expectation values associated to the quantum state. Given an unknown state, techniques such as fidelity estimation and, more generally, shadow tomography may be used to achieve a certain estimation accuracy using poly(n) sampling-copy scaling for very large n. This forms the basis for more sophisticated estimation techniques (equivalently coined "learning" in the computer-science and mathematics community).
Shadow tomography with a sub-Clifford set of measurement settings: Phys. Rev. Research 7, 033097 (2025).
Constant sampling-complexity fidelity estimation for special n-qubit target states called phase states (incl. GHZ states): arXiv:2602.09710 (2026).
Harking back to full tomography, it is still interesting to find out how this can be done feasibly for large systems. Preliminary results suggest that exponential speed up is still possible in practical situations! Efforts in developing novel tomography methods of general kinds that are resource-efficient form a research focus.
References:
G. Park, YST, and H. Jeong, Phys. Rev. Research 7, 033097 (2025).
J. Gil-Lopez, YST, S. De, B. Brecht, H. Jeong, C. Silberhorn, and L. L. Sanchez-Soto, Optica 8, 1296 (2021).
I. Gianani, YST, V. Cimini, H. Jeong, G. Leuchs, M. Barbieri, and L. L. Sanchez-Soto, PRX Quantum 1, 020307 (2020).
Y. Kim, YST, D. Ahn, D.-G. Im, Y.-W. Cho, G. Leuchs, L. L. Sanchez-Soto, H. Jeong, and Y.-H. Kim, Phys. Rev. Lett. 124, 210401 (2020).
[Featured in Physics] D. Ahn, YST, H. Jeong, F. Bouchard, F. Hufnagel, E. Karimi, D. Koutny, J. Rehacek, Z. Hradil, G. Leuchs, L. L. Sanchez-Soto, Phys. Rev. Lett. 122, 100404 (2019).
Bayesian-inspired relative belief in quantum information processing
Quantum information processing, which includes tasks relying on the machinery of quantum mechanics, naturally necessitates correct statistical inference. Proper techniques for analyzing given measurement data to assess hypotheses of physical quantum systems are therefore crucial, more so in the current age where the field of hypothesis assessment is plagued with a myriad of ad hoc (widely-accepted) criteria that often only work in certain cases.
To this end, one should ask the basic question: "How do the measurement data provide evidence in favor/against a scientific hypothesis (which can be an average energy value, an effective dimension of the Hilbert space describing the system, specific number of photons emitted by a light source, et cetera)?"
Michael Evans and his book on measuring statistical evidence with relative belief.
For any hypothesis value of interest, the prior and posterior probability for this value represents the beliefs before and after the experiment. The relative magnitudes then naturally reflect the relative convictions as to whether the hypothesis value is plausible or not.
A straightforward answer was advocated by Prof. Michael Evans of the University of Toronto: For any hypothesis value associated to the quantum system, one may conceive of a prior probability for this value before the experiment. After the experiment, the data collected give us the corresponding posterior probability. Although these two probabilities are standard fare in Bayesian statistics, it now depends on how we use these two information---the only real direct information one acquires from the experiment. Accordingly, if one interprets the prior and posterior probabilities as the respective belief strengths before and after the experiment about the hypothesis, then the ratio of the latter to the former (relative-belief or RB ratio) tells us that the hypothesis is plausible (supported by the data) if it is larger than one, and implausible (unsupported by the data) if it is smaller than one. In Michael's book, the comprehensive formalism and machineries of relative belief, including the concept of evidence strength (how strongly is the hypothesis supported by the data) and discussions concerning its application in daily statistical contexts, are discussed.
It was not until Prof. Berthold-Georg Englert (now Chair Professor at BIT, Beijing) and his team in the Centre for Quantum Technologies (Singapore) introduced this direct evidence-measuring paradigm to quantum information theory, first applied to Bayesian error-region (generalized "error bars") constructions in quantum parameter estimation and quantum-state tomography [assorted error-bar and error-region pictures of shown below are taken from New J. Phys. 15 123026 (2013), Phys. Rev. A 94, 062112 (2016), and Phys. Rev. A 100, 022333 (2019)] and the refutation of local hidden-variable models in favor of quantum mechanics [Phys. Rev. A 99, 022112 (2019)] based on real quantum-optical experimental data from leading international groups.
Recently, we applied the RB paradigm to quantum tomography in order to certify the plausible dimension a CV system (say a coherent state with moderate average photon numbers) occupies in the infinite-dimensional Hilbert space. Interestingly, this method chooses plausible dimensions that are never smaller than dimensions chosen using conventional model-selection criteria using Akaike's or Schwarz's information criteria [pictures below extracted from Phys. Rev. Lett. 133, 050204 (2024) and Phys. Rev. A 110, 012231 (2024)].
Most recently, we also extended the RB paradigm to the discrimination of source origins of optical signals, which, for instance, is especially important for NASA in determining whether a light source is emitted from a binary star or not. With LKB, Sorbonne (Prof. Nicolas Treps), experiments in Hermite-Gaussian modes were conducted and RB was used to successfully and minimalistically pick the plausible hypothesis that would tell us, solely based on the detection data, whether the signal is produced by one source or two sources. General multiparameter source tomography is also possible with plausible regions [arXiv:2601.13972 (2025)].
Extending this powerful statistical evidence-measuring paradigm to many more quantum information tasks constitutes yet another important item in the research agenda.
References:
YST, S. U. Shringarpure, H. Jeong, N. Prasannan, B. Brecht, C. Silberhorn, M. Evans, D. Mogilevtsev, and L. L. Sanchez-Soto, Phys. Rev. Lett. 133, 050204 (2024).
YST, S. U. Shringarpure, H. Jeong, N. Prasannan, B. Brecht, C. Silberhorn, M. Evans, D. Mogilevtsev, and L. L. Sanchez-Soto, Phys. Rev. A 110, 012231 (2024).
S. U. Shringarpure, YST, H. Jeong, M. Evans, L. L. Sanchez-Soto, A. Grateau, A. Boeschoten, and N. Treps, arXiv:2601.13972 (2025).
General quantum information theory
Other interesting problems concerning quantum information can certainly be part of the research agenda.
Selected publications:
YST, S. U. Shringarpure, S. Cho, and H. Jeong, Linear-optical protocols for mitigating and suppressing noise in bosonic systems, Quantum Sci. Technol. 10, 035003 (2025).
H. Aghaee Rad, T. Ainsworth, R. N. Alexander, ..., J. F. Tasker, YST, R. B. Then et al., Scaling and networking a modular photonic quantum computer, Nature 638, 912 (2025).
YST, S. U. Shringarpure, H. Jeong, N. Prasannan, B. Brecht, C. Silberhorn, M. Evans, D. Mogilevtsev, and L. L. Sanchez-Soto, Evidence-Based Certification of Quantum Dimensions, Phys. Rev. Lett. 133, 050204 (2024).
YST, Optimized numerical gradient and Hessian estimation for variational quantum algorithms, Phys. Rev. A 107, 042421 (2023),
J. Gil-Lopez, YST, S. De, B. Brecht, H. Jeong, C. Silberhorn, and L. L. Sanchez-Soto, Universal compressive tomography in the time-frequency domain, Optica 8, 1296 (2021).
I. Gianani, YST, V. Cimini, H. Jeong, G. Leuchs, M. Barbieri, and L. L. Sanchez-Soto, Compressively Certifying Quantum Measurements, PRX Quantum 1, 020307 (2020).
Y. Kim, YST, D. Ahn, D.-G. Im, Y.-W. Cho, G. Leuchs, L. L. Sanchez-Soto, H. Jeong, and Y.-H. Kim, Universal Compressive Characterization of Quantum Dynamics, Phys. Rev. Lett. 124, 210401 (2020).
C. Oh, YST, and H. Jeong, Probing Bayesian credible regions intrinsically: a feasible error certification for physical systems, Phys. Rev. Lett. 123, 040602 (2019).
[Featured in Physics] D. Ahn, YST, H. Jeong, F. Bouchard, F. Hufnagel, E. Karimi, D. Koutny, J. Rehacek, Z. Hradil, G. Leuchs, L. L. Sanchez-Soto, Adaptive compressive tomography with no a priori information, Phys. Rev. Lett. 122, 100404 (2019).
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