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NASA NTRS2021

New giant planet beyond the snow line for an extended MOA exoplanet microlens sample

Characterizing a planet detected by microlensing is hard if the planetary signal is weak or the lens-source relative trajectory is far from caustics. However, statistical analyses of planet demography must include those planets to accurately determine occurrence rates. As part of a systematic modelling effort in the context of a >10-yr retrospective analysis of MOA’s survey observations to build an extended MOA statistical sample, we analyse the light curve of the planetary microlensing event MOA-2014-BLG-472. This event provides weak constraints on the physical parameters of the lens, as a result of a planetary anomaly occurring at low magnification in the light curve. We use a Bayesian analysis to estimate the properties of the planet, based on a refined Galactic model and the assumption that all Milky Way’s stars have an equal planet-hosting probability. We find that a lens consisting of a 1.9(+2.2,−1.2)M(J) giant planet orbiting a 0.31(+0.36,−0.19)Mꙩ host at a projected separation of 0.75±0.24au is consistent with the observations and is most likely, based on the Galactic priors. The lens most probably lies in the Galactic bulge, at 7.2(+0.6,−1.7)kpc from Earth. The accurate measurement of the measured planet-to-host star mass ratio will be included in the next statistical analysis of cold planet demography detected by microlensing.

Clément Ranc↗

DOE OSTI2025

Evaluating the limitations of Bayesian metabolic control analysis

AbstractBayesian Metabolic Control Analysis (BMCA) has emerged as a promising framework for inferring metabolic control coefficients in data-limited scenarios by integrating Bayesian inference with linlog rate laws. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCCs), and concentration control coefficients (CCCs) under varying data availability conditions using three synthetic metabolic network models. Our findings highlight the strengths and weaknesses of BMCA, guiding its application in metabolic engineering and emphasizing the need for methodological refinements.Author summaryUnderstanding how enzymes control metabolic pathways is crucial for optimizing biomanufacturing and synthetic biology applications. Bayesian Metabolic Control Analysis (BMCA) is a promising computational method that integrates Bayesian inference with metabolic control analysis to estimate key control parameters, even in cases with limited experimental data. However, the accuracy and limitations of BMCA remain unclear. In this study, we systematically evaluate BMCA using three synthetic metabolic networks to determine how different types of physiological data impact its predictive performance. We find that BMCA requires flux and enzyme concentration data for accurate predictions, while external metabolite concentrations contribute little. Additionally, BMCA fails to predict elasticity values beyond a magnitude of 1.5 and reliably infer allosteric regulation, even when strong regulatory interactions exist. In addition, BMCA does not accurately rank metabolic control points, which may limit its utility in identifying key enzymes in engineered pathways. Our work provides practical insights into when and how BMCA can be applied, guiding future research in metabolic modeling and control analysis.

Shin, Janis (ORCID:0000000216572455)↗

DOE OSTI2026

Prediction of non-intuitive metabolic targets with bayesian metabolic control analysis to improve 3-hydroxypropionic acid production in Aspergillus niger

Development of efficient bioconversion processes is limited by the ability to predictably improve metabolic flux. Here we deployed Bayesian Metabolic Control Analysis as a platform to integrate multi-omics data with metabolic modeling and evaluated its ability to predict genetic interventions that improve metabolic flux. Global Metabolomics and proteomics data was collected from 17 Aspergillus niger strains engineered to produce the platform biochemical 3-hydroxypropionic acid from which seven actional genetic interventions were predicted from significant flux control coefficients. Of the suggested genetic interventions, two were present within the intuitively designed strains used for training (malonic semialdehyde dehydrogenase and pyruvate carboxylase) while five predicted targets were present within non-intuitive areas of the metabolic network including 5-formyltetrahydrofolate deformylase and four mitochondrial enzymes, alcohol dehydrogenase, succinyl-CoA ligase, aspartate aminotransferase, and malate dehydrogenase. Six of the targets were validated in the highest performing 3-HP strain used for multi-omics data generation which contained a prior disruption of the highest scoring target malonic semialdehyde dehydrogenase. Predicted directional perturbation of five of the six tested targets significantly improved titer and rate of 3-HP production and two significantly improved yield. The greatest improvements were observed following disruption of the non-intuitive target succinyl-CoA ligase which increased titer by 39% and yield by 29% (to 20.4 g/L 3-HP and 0.31 g 3-HP/g glucose) over the strains used for training. This study demonstrates the utility of Bayesian Metabolic Control Analysis and highlights the ability to predict meaningful genetic targets in unexpected areas of metabolism to improve engineered strains for bioconversion.

3-hydroxypropionic acid↗

DOE OSTI2024

Emulating ab initio computations of infinite nucleonic matter

We construct efficient emulators for the computation of the infinite nuclear matter equation of state. These emulators are based on the subspace-projected coupled-cluster method for which we here develop a new algorithm called small-batch voting to eliminate spurious states that might appear when emulating quantum many-body methods based on a non-Hermitian Hamiltonian. The efficiency and accuracy of these emulators facilitate a rigorous statistical analysis within which we explore nuclear matter predictions for > 10 6 different parametrizations of a chiral interaction model with explicit Δ -isobars at next-to-next-to leading order. Constrained by nucleon-nucleon scattering phase shifts and bound-state observables of light nuclei up to He 4 , we use history matching to identify nonimplausible domains for the low-energy coupling constants of the chiral interaction. Within these domains we perform a Bayesian analysis using sampling and importance resampling with different likelihood calibrations and study correlations between interaction parameters, calibration observables in light nuclei, and nuclear matter saturation properties. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Cosmological neutrino mass: a frequentist overview in light of DESI

We derive constraints on the neutrino mass using a variety of recent cosmological datasets, including DESI BAO, the full-shape analysis of the DESI matter power spectrum and the one-dimensional power spectrum of the Lyman-α forest (P1D) from eBOSS quasars as well as the cosmic microwave background (CMB). The constraints are obtained in the frequentist formalism by constructing profile likelihoods and applying the Feldman-Cousins prescription to compute confidence intervals. This method avoids potential prior and volume effects that may arise in a comparable Bayesian analysis. Parabolic fits to the profiles allow one to distinguish changes in the upper limits from variations in the constraining power σ of the different data combinations. We find that all profiles in the ΛCDM model are cut off by the ∑m ν ≥ 0 bound, meaning that the corresponding parabolas reach their minimum in the unphysical sector. The most stringent 95% C.L. upper limit is obtained by the combination of DESI DR2 BAO, Planck PR4 and CMB lensing at 53 meV, below the minimum of 59 meV set by the normal ordering. The corresponding constraining power σ is 43 meV, which highlights the importance of the cut-off by negative values in the determination of the upper limit. Extending ΛCDM to non-zero curvature and w 0 w a CDM relaxes the constraints past 59 meV again, but only w 0 w a CDM exhibits profiles with a minimum at a positive value. Additionally, we extend the formalism to constrain the lightest neutrino mass. For DESI DR2 BAO, Planck PR4 and CMB lensing, we find confidence limits at 20 and 19 meV for normal and inverted ordering, respectively. Using a combination of DESI DR1 full-shape, BBN and eBOSS Lyman-α P1D, we successfully constrain the neutrino mass independently of the CMB. This combination yields m l ≤ 97 and 98 meV in the normal and inverted orderings, and total neutrino mass ∑m ν ≤ 285 meV (95% C.L.). The addition of DESI full-shape or Lyman-α P1D to CMB and DESI BAO results in small but noticeable improvement of the constraining power of the data. Lyman-α free-streaming measurements especially improve the constraint. Since they are based on eBOSS data, this sets a promising precedent for upcoming DESI data.

Frequentist statistics↗

NASA NTRS1997

Bayesian Blocks: A New Method to Analyze Photon Counting Data

A Bayesian analysis of photon-counting data leads to a new time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The raw counting data -- time-tag events (TTE), time-to-spill (TTS) data, or binned counts -- is converted to a maximum likelihood segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant -- i.e. has a fixed intensity without statistically significant variations. The resulting structures, Bayesian Blocks, can be thought of as bins with arbitrary spacing determined by the data. The method itself sets no lower limit to the time scale on which variability can be detected. We have applied the method to RXTE data on Cyg X-1, yielding information on this source's short-time-scale variability.

Scargle, Jeffrey D.↗

NASA NTRS2016

Discovery of a Gas Giant Planet in Microlensing Event Ogle-2014-BLG-1760

We present the analysis of the planetary microlensing event OGLE-2014-BLG-1760, which shows a strong light-curve signal due to the presence of a Jupiter mass ratio planet. One unusual feature of this event is that the source star is quite blue, with V-I = 1.48 +/- 0.08. This is marginally consistent with a source star in the Galactic bulge, but it could possibly indicate a young source star on the far side of the disk. Assuming a bulge source, we perform a Bayesian analysis assuming a standard Galactic model, and this indicates that the planetary system resides in or near the Galactic bulge at D(sub L) = 6.9 +/- 1.1 kpc. It also indicates a host-star mass of M(sub *) = 0.51(sup + 0.44/sub -0.28) M(sub theta), a planet mass of m(sub p ) = 0.56(sup +0.34/sub -0.26) M(sub J), and a projected star-planet separation of a(perpendicular) = 1.75(sup +0.33/sub -0.34) au. The lens-source relative proper motion is micro(sub rel) = 6.5 +/- 1.1mas per yr. The lens (and stellar host star) is estimated to be very faint compared to the source star, so it is most likely that it can be detected only when the lens and source stars start to separate. Due to the relatively high relative proper motion, the lens and source will be resolved to about approximately 46 mas in 6-8 yr after the peak magnification. So, by 2020-2022, we can hope to detect the lens star with deep, high-resolution images.

Galactic bulge↗

NASA NTRS1992

Estimating high mosquito-producing rice fields using spectral and spatial data

The cultivation of irrigated rice provides ideal larval habitat for a number of anopheline vectors of malaria throughout the world. Anopheles freeborni, a potential vector of human malaria, is associated with the nearly 240,000 hectares of irrigated rice grown annually in Northern and Central California; therefore, this species can serve as a model for the study of rice field anopheline population dynamics. Analysis of field data revealed that rice fields with early season canopy development, that are located near bloodmeal sources (i.e., pastures with livestock) were more likely to produce anopheline larvae than fields with less developed canopies located further from pastures. Remote sensing reflectance measurements of early-season canopy development and geographic information system (GIS) measurements of distanes between rice fields and pastures with livestock were combined to distinguish between high and low mosquito-producing rice fields. Using spectral and distance measures in either a discriminant or Bayesian analysis, the identification of high mosquito-producing fields was made with 85 percent accuracy nearly two months before anopheline larval populations peaked. Since omission errors were also minimized by these approaches, they could provide a new basis for directing abatement techniques for the control of malaria vectors.

Wood, B. L.↗

NASA NTRS2022

Ogle-2018-BLG-0799lb: A Q ∼ 2.7 × 10(−3) Planet With Spitzer Parallax

We report the discovery and analysis of a planet in the microlensing event OGLE-2018-BLG-0799. The planetary signal was observed by several ground-based telescopes, and the planet-host mass ratio is q = (2.65 ± 0.16) × 10(−3). The ground-based observations yield a constraint on the angular Einstein radius θE, and the microlensing parallax vector πE, is strongly constrained by the Spitzer data. However, the 2019 Spitzer baseline data reveal systematics in the Spitzer photometry, so there is ambiguity in the magnitude of the parallax. In our preferred interpretation, a full Bayesian analysis using a Galactic model indicates that the planetary system is composed of an Mplanet = 0.26+0.22 −0.11M(J) planet orbiting an Mhost = 0.093+0.082 −0.038 Mʘ , at a distance of DL = 3.71+3.24 −1.70 kpc. An alternate interpretation of the data shifts the localization of the minima along the arc-shaped microlens parallax constraints. This, in turn, yields a more massive host with median mass of 0.13 Mʘ at a distance of 6.3 kpc. This analysis demonstrates the robustness of the osculating circles formalism, but shows that further investigation is needed to assess how systematics affect the specific localization of the microlens parallax vector and, consequently, the inferred physical parameters.

gravitational lensing↗

NASA NTRS2019

OGLE-2015-BLG-1649Lb: A Gas Giant Planet around a Low-mass Dwarf

We report the discovery of an exoplanet from the analysis of the gravitational microlensing event OGLE-2015-BLG-1649 that challenges the core accretion model of planet formation and appears to support the disk instability model. The planet/host-star mass ratio is q = 7.2 × 10^(−3) and the projected separation normalized to the angular Einstein radius is s = 0.9. We conducted high-resolution follow-up observations using the Infrared Camera and Spectrograph (IRCS) camera on the Subaru telescope and are able to place an upper limit on the lens flux. From these measurements we are able to exclude all host stars greater than or equal in mass to a G-type dwarf. We conducted a Bayesian analysis with these new flux constraints included as priors resulting in estimates of the masses of the host star and planet. These are ML = 0.34 ± 0.19 M⊙ and M(p)=2.5 (+1.5,-1.4) M(Jup), respectively. The distance to the system is D(L)=4.23 (+1.51, -1.64) kpc. The projected star–planet separation is a(┴)=2.07 (+0.65,-0.77) au. The estimated relative lens-source proper motion, ~7.1 mas/yr, is fairly high and thus the lens can be better constrained if additional follow-up observations are conducted several years after the event.

M. Nagakane↗

NASA NTRS2020

OGLE-2018-BLG-1700L: Microlensing Planet in Binary Stellar System

We report a planet in a binary that was discovered from the analysis of the microlensing event OGLE-2018-BLG-1700. We identify the triple nature of the lens from the fact that the anomaly pattern can be decomposed into two parts produced by two binary-lens events, in which one binary pair has a mass ratio of ∼0.01 between the lens components and the other pair has a mass ratio of ∼0.3. We find two sets of degenerate solutions, in which one solution has a projected separation between the primary and its stellar companion less than the angular Einstein radius θ(E) (close solution), while the other solution has a separation greater than θ(E) (wide solution). From the Bayesian analysis with the constraints of the event timescale and angular Einstein radius, we find that the planet has a mass of 4.4(sup +3.0, sub -2.0) M(J) and the stellar binary components have masses of 0.42 (sup +0.29, sub -0.19) M(ʘ) and 0.12 (sup +0.08, sub -0.05) M(ʘ) , respectively, and the distance to the lens is D(L) = 7.6 (sup +1.2, sub -0.9) kpc. The planet is a circumstellar planet according to the wide solution, while it is a circumbinary planet according to the close solution.

Cheongho Han↗

NASA NTRS2020

One Planet or Two Planets? The Ultra-sensitive Extreme-magnification Microlensing Event KMT-2019-BLG-1953

We present the analysis of a very high-magnification (A ~ 900) microlensing event KMT-2019-BLG-1953. A single-lens single-source (1L1S) model appears to approximately delineate the observed light curve, but the residuals from the model exhibit small but obvious deviations in the peak region. A binary-lens (2L1S) model with a mass ratio of q ~ 2 × 10^−3 improves the fits by Δχ2 = 181.8, indicating that the lens possesses a planetary companion. From additional modeling by introducing an extra planetary lens component (3L1S model) and an extra source companion (2L2S model), it is found that the residuals from the 2L1S model further diminish, but claiming these interpretations is difficult due to the weak signals with Δχ2 = 16.0 and 13.5 for the 3L1S and 2L2L models, respectively. From a Bayesian analysis, we estimate that the host of the planets has a mass of M(host)=0.31 (+0.37, -0.17) Mꙩ and that the planetary system is located at a distance of D9L)=7.04 (+1.10, -1.33) kpc toward the Galactic center. The mass of the securely detected planet is M(p)=0.64 (+0.76, -0.35) M(J). The signal of the potential second planet could have been confirmed if the peak of the light curve had been more densely observed by follow-up observations, and thus the event illustrates the need for intensive follow-up observations for very high-magnification events even in the current generation of high-cadence surveys.

Cheongho Han↗

NASA NTRS2019

OGLE-2017-BLG-1186: First Application of Asteroseismology and Gaussian Processes to microlensing

We present the analysis of the event OGLE-2017-BLG-1186 from the 2017 Spitzer microlensing campaign. This is a remarkable microlensing event because its source is photometrically bright and variable, which makes it possible to perform an asteroseismic analysis using ground-based data. We find that the source star is an oscillating red giant with average timescale of ∼9 d. The asteroseismic analysis also provides us source properties including the source angular size (∼27 μas) and distance (∼11.5 kpc), which are essential for inferring the properties of the lens. When fitting the light curve, we test the feasibility of Gaussian processes (GPs) in handling the correlated noise caused by the variable source. We find that the parameters from the GP model are generally more loosely constrained than those from the traditional χ(exp 2) minimization method. We note that this event is the first microlensing system for which asteroseismology and GPs have been used to account for the variable source. With both finite-source effect and microlens parallax measured, we find that the lens is likely a ∼0.045 Mʘ brown dwarf at distance ∼9.0 kpc, or a ∼0.073 Mʘ ultracool dwarf at distance ∼9.8 kpc. Combining the estimated lens properties with a Bayesian analysis using a Galactic model, we find a ∼ 35 per cent probability for the lens to be a bulge object and ∼ 65 per cent to be a background disc object.

S.-S. Li↗

NASA NTRS2019

OGLE-2018-BLG-1011Lb,c: Microlensing Planetary System with Two Giant Planets Orbiting a Low-mass Star

We report a multiplanetary system found from the analysis of microlensing event OGLE-2018-BLG-1011, for which the light curve exhibits a double-bump anomaly around the peak. We find that the anomaly cannot be fully explained by the binary-lens or binary-source interpretations and its description requires the introduction of an additional lens component. The 3L1S (three lens components and a single source) modeling yields three sets of solutions, in which one set of solutions indicates that the lens is a planetary system in a binary, while the other two sets imply that the lens is a multiplanetary system. By investigating the fits of the individual models to the detailed light curve structure, we find that the multiple-planet solution with planet-to-host mass ratios ∼9.5 X 10(exp −3) and ∼15 X 10(eap −3) are favored over the other solutions. From the Bayesian analysis, we find that the lens is composed of two planets with masses 1.8 (sup +3.4, sub -1.1) M(J) and 2.8 (sup +5.8, sub -1.7) M(J) around a host with a mass 0.18 (sup +0.33,sub - 0.10) M(ʘ) and located at a distance 7.1(sup +1.1, sub -1.5) kpc. The estimated distance indicates that the lens is the farthest system among the known multiplanetary systems. The projected planet–host separations are a(⊥,2) = 1.8 (sup +2.1, sub -1.5)au (0.8 (sup +0.9,sub -0.6 au) and a(⊥,3) = 0.8 (sup +0.9, sub -0.6)au , where the values of a(⊥,2) inside and outside the parenthesis are the separations corresponding to the two degenerate solutions, indicating that both planets are located beyond the snow line of the host, as with the other four multiplanetary systems previously found by microlensing.

Cheongho Han↗

DOE OSTI2025

A Bayesian framework to investigate radiation reaction in strong fields

Recent experiments aiming to measure phenomena predicted by strong-field quantum electrodynamics (SFQED) have done so by colliding relativistic electron beams and high-power lasers. In such experiments, measurements of collision parameters are not always feasible. However, precise knowledge of these parameters is required to accurately test SFQED. Here, we present a novel Bayesian inference procedure that infers collision parameters that could not be measured on-shot. This procedure is applicable to all-optical non-linear Compton scattering experiments investigating radiation reaction. The framework allows multiple diagnostics to be combined self-consistently and facilitates the inclusion of known information pertaining to the collision parameters. Using this Bayesian analysis, the relative validity of the classical, quantum-continuous and quantum-stochastic models of radiation reaction was compared for several test cases, which demonstrates the accuracy and model selection capability of the framework and highlight its robustness if the experimental values of fixed parameters differ from their values in the models.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Bayesian inference of nuclear incompressibility from collective flow in mid-central Au+Au collisions at 400–1500 MeV/nucleon

The incompressibility K of symmetric nuclear matter (SNM) is determined through a Bayesian analysis of collective flow data from Au + Au collisions at beam energies $E = 400 -1500$ MeV/nucleon. This analysis utilizes a Gaussian process (GP) emulator applied to the isospin-dependent quantum molecular dynamics (IQMD) model for heavy-ion collisions, both with and without incorporating the momentum dependence of the single-nucleon potentials. Specifically, at the 68% confidence level, using rapidity and transverse velocity dependence of proton elliptic flow data with and without consideration of the momentum dependence, the inferred incompressibility values are $K=188.9^{+2.9}_{-4.5}$ MeV and $256.1^{+8.2}_{-8.7}$ MeV at $E = 400$ MeV/nucleon, respectively. When the transverse momentum dependence of proton-like directed flow data is included, the inferred incompressibility values become $K=222.3^{+9.0}_{-9.9}$ MeV and $K=285.5^{+6.7}_{-7.3}$ MeV, respectively. Furthermore, we found that the value of K derived from observables of proton elliptic flow increases with beam energy. Finally, this indicates that the equation of state (EoS) of nuclear matter hardens at higher densities and temperatures in reactions with higher beam energies.

Bayesian inference↗

DOE OSTI2025

Testing T2K’s Bayesian constraints with priors in alternate parameterisations

Bayesian analysis results require a choice of prior distribution. In long-baseline neutrino oscillation physics, the usual parameterisation of the mixing matrix induces a prior that privileges certain neutrino mass and flavour state symmetries. Here we study the effect of privileging alternate symmetries on the results of the T2K experiment. We find that constraints on the level of CP violation (as given by the Jarlskog invariant) are robust under the choices of prior considered in the analysis. On the other hand, the degree of octant preference for the atmospheric angle depends on which symmetry has been privileged.

Bayesian Inference↗

DOE OSTI2024

Copacabana: a probabilistic membership assignment method for galaxy clusters

Cosmological analyses using galaxy clusters in optical/near-infrared photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for all galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89 per cent membership accuracy with a mild dependence on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass–cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities (⁠μ * ⁠) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation at low redshift for a Legacy Survey of Space and Time type survey. These results indicate the potential of Copacabana and μ * to be used in cosmological analyses of optically selected clusters in the future.

79 ASTRONOMY AND ASTROPHYSICS↗