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Open access publications by faculty, postdocs, and graduate students in the Department of Physics and Astronomy.

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    Direct detection of ultralight dark matter bound to the Sun with space quantum sensors
    (Nature Astronomy, 2022-12-05) Tsai, Yu-Dai; Eby, Joshua; Safronova, Marianna S.
    Recent advances in quantum sensors, including atomic clocks, enable searches for a broad range of dark matter candidates. The question of the dark matter distribution in the Solar system critically affects the reach of dark matter direct detection experiments. Partly motivated by the NASA Deep Space Atomic Clock and the Parker Solar Probe, we show that space quantum sensors present new opportunities for ultralight dark matter searches, especially for dark matter states bound to the Sun. We show that space quantum sensors can probe unexplored parameter space of ultralight dark matter, covering theoretical relaxion targets motivated by naturalness and Higgs mixing. If a two-clock system were able to make measurements on the interior of the solar system, it could probe this highly sensitive region directly and set very strong constraints on the existence of such a bound-state halo in our solar system. We present sensitivity projections for space-based probes of ultralight dark matter, which couples to electron, photon and gluon fields, based on current and future atomic, molecular and nuclear clocks.
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    Detection of astrophysical tau neutrino candidates in IceCube
    (The European Physical Journal C, 2022-11-15) IceCube Collaboration; Abbasi, R.; Ackermann, M.; Adams, J.; et al.
    High-energy tau neutrinos are rarely produced in atmospheric cosmic-ray showers or at cosmic particle accelerators, but are expected to emerge during neutrino propagation over cosmic distances due to flavor mixing. When high energy tau neutrinos interact inside the IceCube detector, two spatially separated energy depositions may be resolved, the first from the charged current interaction and the second from the tau lepton decay. We report a novel analysis of 7.5 years of IceCube data that identifies two candidate tau neutrinos among the 60 “High-Energy Starting Events” (HESE) collected during that period. The HESE sample offers high purity, all-sky sensitivity, and distinct observational signatures for each neutrino flavor, enabling a new measurement of the flavor composition. The measured astrophysical neutrino flavor composition is consistent with expectations, and an astrophysical tau neutrino flux is indicated at 2.8σ significance.
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    Resonances and near field heat transfer of finite structures
    (European Physical Society Letters, 2022-12-02) Chui, S. T.; Lin, Zhifang; Zi, Jian
    We describe a formulation for near field heat transfer for a finite size system so that the heat conductance can be expressed as sums of contributions from the resonances of the combined structure of the “receiver” and the “source”. Our work opens the door to investigating near field heat transfer between finite systems and in particular metamaterials whose resonances have been well studied. We illustrated our results with an analytically tractable example of energy transfer between two split ring resonantors separated by a distance d on top of each other. When the cuts of the two rings are opposite each other, the heat conductance is smaller than when the cuts of the two rings are on top of each other. This result can only come from a finite system calculation.
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    Predicting band gaps and band-edge positions of oxide perovskites using density functional theory and machine learning
    (Physical Review B, 2022-10-28) Li, Wei; Wang, Zigeng; Xiao, Xia; Zhang, Zhiqiang; Janotti, Anderson; Rajasekaran, Sanguthevar; Medasani, Bharat
    Density functional theory (DFT) within the local or semilocal density approximations, i.e., the local density approximation (LDA) or generalized gradient approximation (GGA), has become a workhorse in the electronic structure theory of solids, being extremely fast and reliable for energetics and structural properties, yet remaining highly inaccurate for predicting band gaps of semiconductors and insulators. The accurate prediction of band gaps using first-principles methods is time consuming, requiring hybrid functionals, quasiparticle GW, or quantum Monte Carlo methods. Efficiently correcting DFT-LDA/GGA band gaps and unveiling the main chemical and structural factors involved in this correction is desirable for discovering novel materials in high-throughput calculations. In this direction, we use DFT and machine learning techniques to correct band gaps and band-edge positions of a representative subset of ABO3 perovskite oxides. Relying on the results of HSE06 hybrid functional calculations as target values of band gaps, we find a systematic band-gap correction of ∼1.5 eV for this class of materials, where ∼1eV comes from downward shifting the valence band and ∼0.5eV from uplifting the conduction band. The main chemical and structural factors determining the band-gap correction are determined through a feature selection procedure.
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    Reliable crystal structure predictions from first principles
    (Nature Communications, 2022-06-02) Nikhar, Rahul; Szalewicz, Krzysztof
    An inexpensive and reliable method for molecular crystal structure predictions (CSPs) has been developed. The new CSP protocol starts from a two-dimensional graph of crystal’s monomer(s) and utilizes no experimental information. Using results of quantum mechanical calculations for molecular dimers, an accurate two-body, rigid-monomer ab initio-based force field (aiFF) for the crystal is developed. Since CSPs with aiFFs are essentially as expensive as with empirical FFs, tens of thousands of plausible polymorphs generated by the crystal packing procedures can be optimized. Here we show the robustness of this protocol which found the experimental crystal within the 20 most stable predicted polymorphs for each of the 15 investigated molecules. The ranking was further refined by performing periodic density-functional theory (DFT) plus dispersion correction (pDFT+D) calculations for these 20 top-ranked polymorphs, resulting in the experimental crystal ranked as number one for all the systems studied (and the second polymorph, if known, ranked in the top few). Alternatively, the polymorphs generated can be used to improve aiFFs, which also leads to rank one predictions. The proposed CSP protocol should result in aiFFs replacing empirical FFs in CSP research.
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