arXiv subjects

H. Jeong

Publications and source records attributed to H. Jeong.

At least 19 recordsLinked to original sources

arXiv2026

Measurement of coherent elastic neutrino nucleus scattering on germanium by COHERENT

The COHERENT collaboration reports the most precise measurement of the coherent elastic neutrino-nucleus scattering cross section to date. This measurement was performed with COHERENT's germanium detector array, Ge-Mini, at the Spallation Neutron Source at Oak Ridge National Laboratory. A cumulative exposure of $4.68\times10^{22}$ protons on target yielded a total number of observed counts of $124^{+14}_{-12}$ and a flux-averaged cross section of $1.00 \pm 0.10 \mathrm{(statistical)} \pm 0.10 \mathrm{(systematic)}$ relative to the standard-model expectation of $5.9\times10^{-39} \mathrm{cm}^2$. The well-understood energy and timing distributions of the neutrino source allow for independent measurements of muon- and electron-neutrino scattering rates. This information is used to improve constraints on non-standard neutrino interactions mediated by heavy particles.

hep-ex↗

arXiv2026

The COHERENT Experiment: 2026 Update

The COHERENT experiment measures neutrino-induced recoils from coherent elastic neutrino-nucleus scattering (CEvNS) with multiple nuclear targets at the Spallation Neutron Source (SNS) at the Oak Ridge National Laboratory (ORNL), USA. Several successful CEvNS measurements have been achieved in recent years with tens-of-kg detector masses, with a CsI scintillating crystal, a liquid argon single-phase detector, and high-purity germanium spectrometers. For the next phase, COHERENT aims at high-statistics detection of CEvNS events for precision tests of the standard model of particle physics, and to probe new physics beyond-the-standard model. Percent-level precision can be achieved by lowering thresholds, reducing backgrounds, and by scaling up the detector masses. It goes hand in hand with benchmarking the neutrino flux from the SNS. Further detectors will measure CEvNS in additional nuclei, including lighter target nuclei such as sodium and neon, to continue to test the expected neutron-number-squared dependence of the cross section. COHERENT can furthermore study charged-current and neutral-current inelastic neutrino-nucleus cross sections on various nuclei at neutrino energies below $\sim$50 MeV. Many of these cross sections have never been measured before, but are critical input for the interpretation of core-collapse supernova detection in large-scale neutrino experiments such as DUNE, Super-K, Hyper-K, and HALO.

hep-ex↗

arXiv2025

Hector Galaxy Survey: Data Processing, Quality Control and Early Science

The Hector Galaxy Survey is a new optical integral field spectroscopy (IFS) survey currently using the AAT to observe up to 15,000 galaxies at low redshift ($z < 0.1$). The Hector instrument employs 21 optical fibre bundles feeding into two double-beam spectrographs to enable wide-field multi-object IFS observations of galaxies. To efficiently process the survey data, we adopt the data reduction pipeline developed for the SAMI Galaxy Survey, with significant updates to accommodate Hector's dual-spectrograph system. These enhancements address key differences in spectral resolution and other instrumental characteristics relative to SAMI, and are specifically optimised for Hector's unique configuration. We introduce a two-dimensional arc fitting approach that reduces the RMS velocity scatter by a factor of 1.2--3.4 compared to fitting arc lines independently for each fibre. The pipeline also incorporates detailed modelling of chromatic optical distortion in the wide-field corrector, to account for wavelength-dependent spatial shifts across the focal plane. We assess data quality through a series of validation tests, including wavelength solution accuracy, spectral resolution, throughput characterisation, astrometric precision, sky subtraction residuals, and flux calibration stability (4\% systematic offset when compared to Legacy Survey fluxes). We demonstrate that Hector delivers high-fidelity, science-ready datasets, supporting robust measurements of galaxy kinematics, stellar populations, and emission-line properties, and provide examples. Additionally, we address systematic uncertainties identified during the data processing and propose future improvements to enhance the precision and reliability of upcoming data releases. This work establishes a robust data reduction framework for Hector, delivering high-quality data products that support a broad range of extragalactic studies.

astro-ph.GA↗

arXiv2025

Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights

This review examines the current state of research on microscale cellular changes during the drying of plant-based food materials (PBFM), with particular emphasis on computational modelling approaches. The review addresses the critical need for advanced computational methods in microscale investigations. We systematically analyse experimental studies in PBFM drying, highlighting their contributions and limitations in capturing cellular-level phenomena, including challenges in data acquisition and measurement accuracy under varying drying conditions. The evolution of computational models for microstructural investigations is thoroughly examined, from traditional numerical methods to contemporary state-of-the-art approaches, with specific focus on their ability to handle the complex, nonlinear properties of plant cellular materials. Special attention is given to the emergence of data-driven models and their limitations in predicting microscale cellular behaviour during PBFM drying, particularly addressing challenges in dataset acquisition and model generalization. The review provides an in-depth analysis of Physics-Informed Machine Learning (PIML) frameworks, examining their theoretical foundations, current applications in related fields, and unique advantages in combining physical principles with neural network architectures. Through this comprehensive assessment, we identify critical gaps in existing methodologies, evaluate the trade-offs between different modelling approaches, and provide insights into future research directions for improving our understanding of cellular-level transformations during PBFM drying processes. The review concludes with recommendations for integrating experimental and computational approaches to advance the field of food preservation technology.

cs.LG↗

arXiv2024

Linear-optical protocols for mitigating and suppressing noise in bosonic systems

Quantum-information processing and computation with bosonic qubits are corruptible by noise channels. Using interferometers and photon-subtraction gadgets (PSGs) accompanied by linear amplification and attenuation, we establish linear-optical methods to mitigate and suppress bosonic noise channels. We first show that by employing amplifying and attenuating PSGs respectively at the input and output of either a thermal or random-displacement channel, probabilistic error cancellation (PEC) can be carried out to mitigate errors in expectation-value estimation. We also derive optimal physical estimators that are properly constrained to improve the sampling accuracy of PEC. Next, we prove that a purely-dephasing channel is coherently suppressible using a multimode Mach--Zehnder interferometer and conditional vacuum measurements (VMZ). In the limit of infinitely-many ancillas, with nonvanishing success rates, VMZ using either Hadamard or two-design interferometers turns any dephasing channel into a phase-space-rotated linear-attenuation channel that can subsequently be inverted with (rotated) linear amplification without Kerr nonlinearity. Moreover, for weak central-Gaussian dephasing, the suppression fidelity increases monotonically with the number of ancillas and most optimally with Hadamard interferometers. We demonstrate the performance of these linear-optical mitigation and suppression schemes on common noise channels (and their compositions) and popular bosonic codes. While the theoretical formalism pertains to idling noise channels, we also provide numerical evidence supporting mitigation and suppression capabilities with respect to noise from universal gate operations.

quant-ph↗

arXiv2024

Evidence of Coherent Elastic Neutrino-Nucleus Scattering with COHERENT's Germanium Array

We report the first detection of coherent elastic neutrino-nucleus scattering (CEvNS) on natural germanium, measured at the Spallation Neutron Source at Oak Ridge National Laboratory. The Ge-Mini detector of the COHERENT collaboration employs large-mass, low-noise, high-purity germanium spectrometers, enabling excellent energy resolution, and an analysis threshold of 1.5 keV electron-equivalent ionization energy. We observe a on-beam excess of 20.6 +7.1 -6.3 counts with a total exposure of 10.22 GWhkg and we reject the no-CEvNS hypothesis with 3.9 sigma significance. The result agrees with the predicted standard model of particle physics signal rate within 2 sigma.

hep-ex↗

arXiv2024

Relative-belief inference in quantum information theory

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 by directly comparing the prior and posterior probabilities for the hypothesis. In model-dimension certification tasks, we show that the relative belief procedure typically chooses Hilbert spaces that are never smaller in dimension than those selected from optimizing a broad class of information criteria, including Akaike's criterion. As a concrete and focused exposition of this powerful evidence-based technique, we apply the relative belief procedure to an important application: state reconstruction of imperfect quantum sources. In particular, just by comparing prior and posterior probabilities based on data, we demonstrate its capability of tracking multiphoton emissions using (realistically lossy) single-photon detectors in order to assess the actual quality of photon sources without making ad hoc assumptions, thereby reliably safeguarding source integrity for general quantum-information and communication tasks with Bayesian reasoning. Finally, we discuss how relative belief can be exploited to carry out parametric model certification and estimate the total dimension of the quantum state for the combined (measured) physical and interacting external systems described by the Tavis--Cummings model.

quant-ph↗

arXiv2024

Evidence-based certification of quantum dimensions

Identifying a reasonably small Hilbert space that completely describes an unknown quantum state is crucial for efficient quantum information processing. We introduce a general dimension-certification protocol for both discrete and continuous variables that is fully evidence-based, relying solely on the experimental data collected and no other unjustified assumptions whatsoever. Using the Bayesian concept of relative belief, we take the effective dimension of the state as the smallest one such that the posterior probability is larger than the prior, as dictated by the data. The posterior probabilities associated with the relative-belief ratios measure the strength of the evidence provide by these ratios so that we can assess whether there is weak or strong evidence in favor or against a particular dimension. Using experimental data from spectral-temporal and polarimetry measurements, we demonstrate how to correctly assign Bayesian plausible error bars for the obtained effective dimensions. This makes relative belief a conservative and easy-to-use model-selection method for any experiment.

quant-ph↗

arXiv2023

Exponential data encoding for quantum supervised learning

Reliable quantum supervised learning of a multivariate function mapping depends on the expressivity of the corresponding quantum circuit and measurement resources. We introduce exponential-data-encoding strategies that are hardware-efficient and optimal amongst all non-entangling Pauli-encoded schemes, which is sufficient for a quantum circuit to express general functions having very broad Fourier frequency spectra using only exponentially few encoding gates. We show that such an encoding strategy not only reduces the quantum resources, but also exhibits practical resource advantage during training in contrast with known efficient classical strategies when polynomial-depth training circuits are also employed. When computation resources are constrained, we numerically demonstrate that even exponential-data-encoding circuits with single-layer training modules can generally express functions that lie outside the classically-expressible region, thereby supporting the practical benefits of such a resource advantage. Finally, we illustrate the performance of exponential encoding in learning the potential-energy surface of the ethanol molecule and California's housing prices

quant-ph↗

arXiv2022

Nonlinear Photoelasticity to Explicate Acoustic Dephasing Dynamics

Detection and controlling of acoustic (AC) phonon phase have been strenuous tasks although such capability is crucial for further manipulating thermal properties. Here, we present a versatile formalism for tracing AC nanowaves with arbitrary strain compositions by incorporating the nonlinear photoelasticity (PE) into ultrafast acoustics where broad AC spectrum encompassing thermally important THz frequency range should be collected far beyond Brillouin frequency. The initial AC phase upon displacive carrier generation could be inherently varied depending on the bipolar AC compositions by implementing externally biased piezoelectric diodes. The importance of adopting nonlinear PE is then manifested from the transient phase shift either abrupt at the point of diffuse surface scattering or gradual during phonon-phonon or phonon-electron scattering events based on which the ratio of nonlinear to linear PE coefficient is experimentally extracted as a function of the detection probe energy, reaching 0.98 slightly below the bandgap. As the probing energy is rather set away from the bandgap, AC phase is completely invariant with any scattering events, exhibiting the conventional trend at Brillouin frequency in linear regime. Under potent influence of nonlinear PE, the AC dephasing time during the propagation are quantified as a function of AC wavepacket size and further correlated with intrinsic and extrinsic AC scattering mechanisms in electron reservoir.

physics.app-ph↗

arXiv2022

Emulation of quantum measurements with mixtures of coherent states

We propose a methodology to emulate quantum phenomena arising from any non-classical quantum state using only a finite set of mixtures of coherent states. This allows us to successfully reproduce well-known quantum effects using resources that can be much more feasibly generated in the laboratory. We present a simple procedure to experimentally carry out quantum-state emulation with coherent states, illustrate it emulating multi-photon NOON states with few phase-averaged coherent states, and demonstrate its capabilities in observing fundamental quantum-mechanical effects, such as the Hong-Ou-Mandel effect, violating Bell inequalities and witnessing quantum non-classicality.

quant-ph↗

arXiv2021

Universal compressive tomography in the time-frequency domain

We implement a compressive quantum state tomography capable of reconstructing any arbitrary low-rank spectral-temporal optical signal with extremely few measurement settings and without any \emph{ad hoc} assumptions about the initially unknown signal. This is carried out with a quantum pulse gate, a device that flexibly implements projections onto arbitrary user-specified optical modes. We present conclusive experimental results for both temporal pulsed modes and frequency bins, which showcase the versatility of our randomized compressive method and thereby introduce a universal optical reconstruction framework to these platforms.

quant-ph↗

arXiv2020

Highly photon loss tolerant quantum computing using hybrid qubits

We investigate a scheme for topological quantum computing using optical hybrid qubits and make an extensive comparison with previous all-optical schemes. We show that the photon loss threshold reported by Omkar {\it et al}. [Phys. Rev. Lett. 125, 060501 (2020)] can be improved further by employing postselection and multi-Bell-state-measurement based entangling operation to create a special cluster state, known as Raussendorf lattice for topological quantum computation. In particular, the photon loss threshold is enhanced up to $5.7\times10^{-3}$, which is the highest reported value given a reasonable error model. This improvement is obtained at the price of consuming more resources by an order of magnitude, compared to the scheme in the aforementioned reference. Neverthless, this scheme remains resource-efficient compared to other known optical schemes for fault-tolerant quantum computation.

quant-ph↗

arXiv2020

Compressively certifying quantum measurements

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 collected from the unknown measurement itself. The procedure is most compressive when the measurement constitutes pure detection outcomes, requiring only an informationally complete number of probe states that scales linearly with the system dimension. We argue and provide numerical evidence showing that the minimal number of probe states needed is even generally below the numbers known in the closely-related classical phase-retrieval problem because of the quantum constraint. We also present affirmative results with polarization experiments that illustrate significant compressive behaviors for both two- and four-qubit detectors just by using random product probe states.

quant-ph↗

arXiv2020

Resource-efficient and fault-tolerant topological quantum computation with hybrid entanglement of light

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 entangled in a continuous-discrete domain. Availability of near-deterministic Bell-state measurements on hybrid qubits is exploited for the purpose. In the presence of photon losses, we show that our scheme leads to a significant enhancement in both tolerable photon-loss rate and resource overheads. More specifically, we report a photon-loss threshold of $\sim3.3\times 10^{-3}$, which is higher than those of known optical schemes under a reasonable error model. Furthermore, resource overheads to achieve logical error rate of $10^{-6} (10^{-15})$ is estimated to be $\sim8.5\times10^{5} (1.7\times10^{7})$ which is significantly less by multiple orders of magnitude compared to other reported values in the literature.

quant-ph↗

arXiv2019

Objective Compressive Quantum Process Tomography

We present a compressive quantum process tomography scheme that fully characterizes any rank-deficient completely-positive process with no a priori information about the process apart from the dimension of the system on which the process acts. It uses randomly-chosen input states and adaptive output von Neumann measurements. Both entangled and tensor-product configurations are flexibly employable in our scheme, the latter which naturally makes it especially compatible with many-body quantum computing. Two main features of this scheme are the certification protocol that verifies whether the accumulated data uniquely characterize the quantum process, and a compressive reconstruction method for the output states. We emulate multipartite scenarios with high-order electromagnetic transverse modes and optical fibers to positively demonstrate that, in terms of measurement resources, our assumption-free compressive strategy can reconstruct quantum processes almost equally efficiently using all types of input states and basis measurement operations, operations, independent of whether or not they are factorizable into tensor-product states.

quant-ph↗

arXiv2019

Efficient Bayesian credible-region certification for quantum-state tomography

Standard Bayesian credible-region theory for constructing an error region on the unique estimator of an unknown state in general quantum-state tomography to calculate its size and credibility relies on heavy Monte~Carlo sampling of the state space followed by sample rejection. This conventional method typically gives negligible yield for very small error regions originating from large datasets. We propose an operational reformulated theory to compute both size and credibility from region-average quantities that in principle convey information about behavior of these two properties as the credible-region changes. We next suggest the accelerated hit-and-run Monte~Carlo sampling, customized to the construction of Bayesian error-regions, to efficiently compute region-average quantities, and provide its complexity estimates for quantum states. Finally by understanding size as the region-average distance between two states in the region (measured for instance with either the Hilbert-Schmidt, trace-class or Bures distance), we derive approximation formulas to analytically estimate both distance-induced size and credibility under the pseudo-Bloch parametrization without resorting to any Monte~Carlo computation.

quant-ph↗

arXiv2019

Probing Bayesian credible regions intrinsically: a feasible error certification for physical systems

Computing size and credibility of Bayesian credible regions for certifying the reliability of any point estimator of an unknown parameter (such as a quantum state, channel, phase, \emph{etc.}) relies on rejection sampling from the entire parameter space that is practically infeasible for large datasets. We reformulate the Bayesian credible-region theory to show that both properties can be obtained solely from the average of log-likelihood over the region itself, which is computable with direct region sampling. Neither rejection sampling nor any geometrical knowledge about the whole parameter space is necessary, so that general error certification now becomes feasible. We take this region-average theory to the next level by generalizing size to the average $l_p$-norm distance $(p>0)$ between a random region point and the estimator, and present analytical formulas for $p=2$ to estimate distance-induced size and credibility for any physical system and large datasets, thus implying that asymptotic Bayesian error certification is possible without any Monte~Carlo computation. All results are discussed in the context of quantum-state tomography.

quant-ph↗