51 citations · 305 across the 30 of their papers we have counts for
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Code-agnostic bosonic noise suppression with hybrid rotations
Saurabh U. Shringarpure, Siheon Park, Sungjoo Cho +4
Physical-level noise on traveling bosonic modes remains a critical bottleneck for scalable quantum information processing. We show that for any single-mode bosonic code (qumode) co…
Efficient direct quantum state tomography using fan-out couplings
Jaekwon Chang, Guedong Park, Hyunseok Jeong +2
Characterizing quantum states is essential for validating quantum devices, yet conventional quantum state tomography becomes prohibitively expensive as system size grows. Direct to…
Sample- and Hardware-Efficient Fidelity Estimation by Stripping Phase-Dominated Magic
Guedong Park, Jaekwon Chang, Yosep Kim +2
Direct fidelity estimation (DFE) is a famous tool for estimating the fidelity with a target pure state. However, such a method generally requires exponentially many sampling copies…
Experimental Evidence-Based Sub-Rayleigh Source Discrimination
Saurabh U. Shringarpure, Yong Siah Teo, Hyunseok Jeong +5
We propose a Bayesian evidence-based inference framework based on relative belief ratios and apply it to discriminating between one and two incoherent optical point sources using s…
No-Go Theorem for Norm-Based Nonclassicality Certification with Linear Functionals
Soumyakanti Bose, Yong-Siah Teo, Hyukjoon Kwon +1
Despite various approaches to encode nonclassical light, most existing formulations either suffer from limited practicality or rely on optimization procedures that are computationa…
Ballistic bosonic noise suppression with hybrid qumode-qubit rotation gates
Saurabh U. Shringarpure, Siheon Park, Sungjoo Cho +4
Noise suppression is of paramount importance for reliable quantum information processing and computation. We show that for any single-mode bosonic code (qumode) corrupted by therma…
Photonic Hybrid Quantum Computing
Jaehak Lee, Srikrishna Omkar, Yong Siah Teo +4
Photons are a ubiquitous carrier of quantum information: they are fast, suffer minimal decoherence, and do not require huge cryogenic facilities. Nevertheless, their intrinsically…
Relative-belief inference in quantum information theory
Y. S. Teo, S. U. Shringarpure, H. Jeong +6
We introduce the framework of Bayesian relative belief that directly evaluates whether or not the experimental data at hand supports a given hypothesis regarding a quantum system b…
Error suppression in multicomponent cat codes with photon subtraction and teleamplification
Saurabh U. Shringarpure, Yong Siah Teo, Hyunseok Jeong
It is known that multiphoton states can be protected from decoherence due to a passive loss channel by applying noiseless attenuation before and noiseless amplification after the c…
Evidence-based certification of quantum dimensions
Y. S. Teo, H. Jeong, N. Prasannan +5
Identifying a reasonably small Hilbert space that completely describes an unknown quantum state is crucial for efficient quantum information processing. We introduce a general dime…
Resource-efficient shadow tomography using equatorial stabilizer measurements
Guedong Park, Yong Siah Teo, Hyunseok Jeong
We propose a resource-efficient shadow-tomography scheme using equatorial-stabilizer measurements generated from subsets of Clifford unitaries. For -qubit systems, equatorial-st…
Dequantizing quantum machine learning models using tensor networks
Seongwook Shin, Yong Siah Teo, Hyunseok Jeong
Ascertaining whether a classical model can efficiently replace a given quantum model -- dequantization -- is crucial in assessing the true potential of quantum algorithms. In this…
Virtual distillation with noise dilution
Yong Siah Teo, Seongwook Shin, Hyukgun Kwon +2
Virtual distillation is an error-mitigation technique that reduces quantum-computation errors without assuming the noise type. In scenarios where the user of a quantum circuit is r…
Parity-encoding-based quantum computing with Bayesian error tracking
Seok-Hyung Lee, Srikrishna Omkar, Yong Siah Teo +1
Measurement-based quantum computing (MBQC) in linear optical systems is promising for near-future quantum computing architecture. However, the nondeterministic nature of entangling…
Exponential data encoding for quantum supervised learning
S. Shin, Y. S. Teo, H. Jeong
Reliable quantum supervised learning of a multivariate function mapping depends on the expressivity of the corresponding quantum circuit and measurement resources. We introduce exp…
Repeated Extraction of Scrambled Quantum Data: Sustainability of the Hayden-Preskill Type Protocols
Seok Hyung Lie, Yong Siah Teo, Hyunseok Jeong
We introduce and study the problem of scrambler hacking, which is the procedure of quantum information extraction from and installation on a quantum scrambler given only partial ac…
All-photonic architectural roadmap for scalable quantum computing using Greenberger-Horne-Zeilinger states
Srikrishna Omkar, Seok-Hyung Lee, Yong Siah Teo +2
Linear optical quantum computing is beset by the lack of deterministic entangling operations besides photon loss. Motivated by advancements at the experimental front in determinist…
Modern compressive tomography for quantum information science
Yong Siah Teo, Luis L. Sanchez-Soto
This review serves as a concise introductory survey of modern compressive tomography developed since 2019. These are schemes meant for characterizing arbitrary low-rank quantum obj…
Universal compressive tomography in the time-frequency domain
J. Gil-Lopez, Y. S. Teo, S. De +4
We implement a compressive quantum state tomography capable of reconstructing any arbitrary low-rank spectral-temporal optical signal with extremely few measurement settings and wi…
Benchmarking quantum tomography completeness and fidelity with machine learning
Yong Siah Teo, Seongwook Shin, Hyunseok Jeong +8
We train convolutional neural networks to predict whether or not a set of measurements is informationally complete to uniquely reconstruct any given quantum state with no prior inf…
Highly accurate Gaussian process tomography with geometrical sets of coherent states
Yong Siah Teo, Kimin Park, Seongwook Shin +2
We propose a practical strategy for choosing sets of input coherent states that are near-optimal for reconstructing single-mode Gaussian quantum processes with output-state heterod…
Compressively certifying quantum measurements
I. Gianani, Y. S. Teo, V. Cimini +4
We introduce a reliable compressive procedure to uniquely characterize any given low-rank quantum measurement using a minimal set of probe states that is based solely on data colle…
Universal compressive characterization of quantum dynamics
Yosep Kim, Yong Siah Teo, Daekun Ahn +6
Recent quantum technologies utilize complex multidimensional processes that govern the dynamics of quantum systems. We develop an adaptive diagonal-element-probing compression tech…
Resource-efficient and fault-tolerant topological quantum computation with hybrid entanglement of light
S. Omkar, Y. S. Teo, H. Jeong
We propose an all-linear-optical scheme to ballistically generate a cluster state for measurement-based topological fault-tolerant quantum computation using hybrid photonic qubits…