HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes

Bayesian optimization (BO), while proved highly effective for many black-box function optimization tasks, requires practitioners to carefully select priors that well model their functions of interest. Rather than specifying by hand, researchers have investigated transfer learning based methods to automatically learn the priors, e.g. multi-task BO (Swersky et al., 2013), few-shot BO (Wistuba and Grabocka, 2021) and HyperBO (Wang et al., 2022). However, those prior learning methods typically assume that the input domains are the same for all tasks, weakening their ability to use observations on functions with different domains or generalize the learned priors to BO on different search spaces. In this work, we present HyperBO+: a pre-training approach for hierarchical Gaussian processes that enables the same prior to work universally for Bayesian optimization on functions with different domains. We propose a two-step pre-training method and analyze its appealing asymptotic properties and benefits to BO both theoretically and empirically. On real-world hyperparameter tuning tasks that involve multiple search spaces, we demonstrate that HyperBO+ is able to generalize to unseen search spaces and achieves lower regrets than competitive baselines.Comment: Full version of the workshop paper at 2022 NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making System

Transfer Learning for Bayesian Optimization on Heterogeneous Search Spaces

Bayesian optimization (BO) is a popular black-box function optimization method, which makes sequential decisions based on a Bayesian model, typically a Gaussian process (GP), of the function. To ensure the quality of the model, transfer learning approaches have been developed to automatically design GP priors by learning from observations on "training" functions. These training functions are typically required to have the same domain as the "test" function (black-box function to be optimized). In this paper, we introduce MPHD, a model pre-training method on heterogeneous domains, which uses a neural net mapping from domain-specific contexts to specifications of hierarchical GPs. MPHD can be seamlessly integrated with BO to transfer knowledge across heterogeneous search spaces. Our theoretical and empirical results demonstrate the validity of MPHD and its superior performance on challenging black-box function optimization tasks

Emergence, Evolution and Scaling of Online Social Networks

This work was partially supported by AFOSR under Grant No. FA9550-10-1-0083, NSF under Grant No. CDI-1026710, NSF of China under Grants Nos. 61473060 and 11275003, and NBRPC under Grant No. 2010CB731403. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Algebraic quantification of an active region's contribution to the solar cycle

The solar dipole moment at cycle minimum is considered to be the most successful precursor for the amplitude of the subsequent cycle. Numerical simulations of the surface flux transport (SFT) model are widely used to effectively predict the dipole moment at cycle minimum. Recently an algebraic method has been proposed to quickly predict the contribution of an active region (AR) to the axial dipole moment at cycle minimum instead of SFT simulations. However, the method assumes a bipolar magnetic region (BMR) configuration of ARs. Actually most ARs are asymmetric in configuration of opposite polarities, or have more complex configurations. Such ARs evolve significantly differently from that of BMR approximations. We propose a generalized algebraic method to describe the axial dipole contribution of an AR with an arbitrary configuration, and evaluate its effectiveness compared to the BMR-based method. We employ mathematical deductions to obtain the generalized method. We compare the results of the generalized method with SFT simulations of observed ARs, artificially created BMRs, and ARs with more complex configurations. We also compare the results with that from the BMR-based method. The generalized method is equivalent to the SFT model, and precisely predicts the ARs' contributions to the dipole moment. The method has a much higher computational efficiency than SFT simulations. Although the BMR-based method has similar computational efficiency as the generalized method, it is only accurate for symmetric bipolar ARs. The BMR-based method systematically overestimates the dipole contributions of asymmetric bipolar ARs, and randomly miscalculate the contributions of more complex ARs. The generalized method provides a quick and precise quantification of an AR's contribution to the solar cycle evolution, which paves the way for the application into the physics-based solar cycle prediction.Comment: 9 pages, 5 figures. Accepted for publication in A&

Sunspot tilt angles revisited: Dependence on the solar cycle strength

The tilt angle of sunspot groups is crucial in the BL type dynamo. Some studies have shown that the tilt coefficient is anti-correlated with the cycle strength. If the anti-correlation exists, it will be shown to act as an effective nonlinearity of the BL-type dynamo to modulate the solar cycle. However, some studies have shown that the anti-correlation has no statistical significance. We aim to investigate the causes behind the controversial results of tilt angle studies and to establish whether the tilt coefficient is indeed anti-correlated with the cycle strength. We first analyzed the tilt angles from DPD. Based on the methods applied in previous studies, we took two criteria to select the data, along with the linear and square-root functions to describe Joy's law, and three methods to derive the tilt coefficients for cycles 21-24. This allowed us to evaluate different methods based on comparisons of the differences among the tilt coefficients and the tilt coefficient uncertainties. Then we utilized Monte Carlo experiments to verify the results. Finally, we extended these methods to analyze the separate hemispheric DPD data and the tilt angle data from Kodaikanal and Mount Wilson. The tilt angles exhibit an extremely wide scatter due to both the intrinsic mechanism for its generation and measurement errors, for instance, the unipolar regions included in data sets. Different methods to deal with the uncertainties are mainly responsible for the controversial character of the previous results. The linear fit to the tilt-latitude relation of sunspot groups with $\Delta s>2.5$ of a cycle carried out without binning the data can minimize the effect of the tilt scatter on the uncertainty of the tilt coefficient. Based on this method the tilt angle coefficient is anti-correlated with the cycle strength with strong statistical significance.Comment: 14 pages, 7 figures, 8 Tables, Accepted for publication in A&

Nuclear β\beta spectrum from projected shell model (I): allowed one-to-one transition

Nuclear $\beta$ spectrum and the corresponding (anti-)neutrino spectrum play important roles in many aspects of nuclear astrophysics, particle physics, nuclear industry and nuclear data. In this work we propose a projected shell model (PSM) to calculate the level energies as well as the reduced one-body transition density (ROBTD) by the Pfaffian algorithm for nuclear $\beta$ decays. The calculated level energies and ROBTD are inputed to the Beta Spectrum Generator (BSG) code to study the high precision $\beta$ spectrum of allowed one-to-one transitions. When experimental level energies are adopted, the calculated $\beta$ spectrum by ROBTD of the PSM deviates from the one by the extreme simple particle evaluation of the BSG by up to $10\%$, reflecting the importance of nuclear many-body correlations. When calculated level energies are adopted, the calculated $\beta$ spectrum shows sensitive dependence on the reliability of calculated level energies. The developed method for ROBTD by the PSM will also be useful for study of the first-forbidden transitions, the isovector spin monopole resonance etc. in a straightforward way

Quantum mechanical photon-count formula derived by entangled state representation

By introducing the thermo entangled state representation, we derived four new photocount distribution formulas for a given density operator of light field. It is shown that these new formulas, which is convenient to calculate the photocount, can be expressed as such integrations over Laguree-Gaussian function with characteristic function, Wigner function, Q-function, and P-function, respectively.Comment: 5 pages, no figur

A broken "α\alpha-intensity" relation caused by the evolving photosphere emission and the nature of the extraordinarily bright GRB~230307A

GRB~230307A is one of the brightest gamma-ray bursts detected so far. With the excellent observation of GRB~230307A by Fermi-GBM, we can reveal the details of the prompt emission evolution. As found in high-time-resolution spectral analysis, the early low-energy spectral indices ($\alpha$) of this burst exceed the limit of synchrotron radiation ($\alpha=-2/3$), and gradually decreases with the energy flux ($F$). A tight $E_{\rm p}\propto F^{0.54}$ correlation anyhow holds within the whole duration of the burst, where $E_{\rm p}$ is the spectral peak energy. Such evolution pattern of $\alpha$ and $E_{\rm p}$ with intensity is called ``double tracking". For the $\alpha-F$ relation, we find a log Bayes factor $\sim$ 210 in favor of a smoothly broken power-law function over a linear function in log-linear space. We call this particular $\alpha-F$ relation as broken ``$\alpha$-intensity", and interpret it as the evolution of the ratio of thermal and non-thermal components, which is also the evolution of the photosphere. We also show that GRB 230307A with a duration of $\sim 35~\rm s$, if indeed at a redshift of $z=0.065$, is likely a neutron star merger event (i.e., it is intrinsically ``short"). Intriguingly, different from GRB 060614 and GRB 211211A, this long event is not composed of a hard spike followed by a soft tail, suggesting that the properties of the prompt emission light curves are not a good tracer of the astrophysical origins of the bursts. The other possibility of $z=3.87$ would point toward very peculiar nature of both GRB 230307A and its late time thermal-like emission.Comment: 14 pages, 6 figures, 1 table. We have excluded the GBM instrument pile-up time interval in the data analysis and also discussed the nature of this even