QIS Group

Ninnat Dangniam (PI) · Quantum Information Science, Institute for Fundamental Study (IF), Naresuan University

Research

The fermion-sampling scheme: fed by magic input states, a generic fermionic linear optical circuit \(U_{FLO}\) outputs bistrings whose distribution \(p(\bf{x})\) is hard to sample classically. Below, the same \(U_{FLO}\) is built from nearest-neighbour Givens rotations in two different layouts.

Quantum computational advantage

Sampling advantage Fermionic linear optics Many-body dynamics Trainability

How do you show that an information-processing device is doing something beyond classical reach? We build sampling-based advantage schemes—proposals in which a quantum device produces an output distribution provably hard to reproduce classically. One of them, Fermion Sampling, carries average-case hardness guarantees on the same footing as random circuit sampling, and can be certified indirectly, by efficiently learning the fermionic-linear-optical circuit that produced the output samples. We are also interested in what anti-concentration, a necessary ingredient of such proof, implies beyond hardness.

Talk slides: Quantum sampling advantage: How to prove it and does it matter? (2023)

• J. Tangpanitanon et al., Signatures of a sampling quantum advantage in driven quantum many-body systems, Quantum Science and Technology 8, 025019 (2023).
• M. Oszmaniec, N. Dangniam, M. E. S. Morales and Z. Zimborás, Fermion sampling: A robust quantum computational advantage scheme using fermionic linear optics and magic input states, PRX Quantum 3, 020328 (2022).
• S. Thanasilp et al., Quantum supremacy and quantum phase transitions, Physical Review B 103, 165132 (2021).
• J. Tangpanitanon et al., Expressibility and trainability of parametrized analog quantum systems for machine learning applications, Physical Review Research 2, 043364 (2020).

The spectral gap versus number of modes \(d\) for several families of fermionic Gaussian states. The inverse spectral gap quantifies both the certification efficiency and the relaxation time to equilibrium of a certain random walk, the connection we use to establish the ultimate bound \(2/d(d-1)\).

Quantum estimation and certification

State estimation Verification Quantum tomography Fermionic Gaussian states

With the potential of quantum information processing comes the challenge of verifying that the quantum devices indeed give the correct results. We design measurement strategies and estimators that pin down a state or a process from as few copies and as few trusted assumptions as possible, with provable guarantees on how the sample cost scales. Our recent work certifies fermionic Gaussian states, important reference states for quantum simulations of electronic structure and many-body physics, in a highly efficient manner.

• N. Dangniam, L. Premcharoen, M. Sripech and T. Chotibut, Certifying fermionic Gaussian states (and a little more) with optimal precision dependence, arXiv:2609.28233 (2026).
• M. Oszmaniec, N. Dangniam, M. E. S. Morales and Z. Zimborás, Fermion sampling: A robust quantum computational advantage scheme using fermionic linear optics and magic input states, PRX Quantum 3, 020328 (2022).
• N. Dangniam, Y-G. Han and H. Zhu, Optimal verification of stabilizer states, Physical Review Research 2, 043323 (2020).
• J. A. Gross, N. Dangniam, C. Ferrie and C. M. Caves, Novelty, efficacy, and significance of weak measurements for quantum tomography, Physical Review A 92, 062133 (2015).

The complete publication list is on Google Scholar.

Students

Current

Laphas Premcharoen Ph.D.
QTFT scholar

Metrasit Sripech M.S.

Past

Matachan Oupatam M.S.
DPST scholar · Thesis: Evaluating quantum state verification for \(d\)-level graph states (2026)