The Initial mass function of the first stars inferred from extremely metal-poor stars

This is an author-created, un-copyedited version of an article published in The Astrophysical Journal. The Version of Record is available online at https://doi.org/10.3847/1538-4357/aab3de.We compare the elemental abundance patterns of ~200 extremely metal-poor (EMP; [Fe/H] < −3) stars to the supernova yields of metal-free stars, in order to obtain insights into the characteristic masses of the first (Population III or Pop III) stars in the universe. The supernova yields are prepared with nucleosynthesis calculations of metal-free stars with various initial masses (M = 13, 15, 25, 40 and 100 M ⊙) and explosion energies (E 51 = E/1051[erg] = 0.5–60), to include low-energy, normal-energy, and high-energy explosions. We adopt the mixing-fallback model, to take into account possible asymmetry in the supernova explosions, and the yields that best fit the observed abundance patterns of the EMP stars are searched by varying the model parameters. We find that the abundance patterns of the EMP stars are predominantly best-fitted by the supernova yields with initial masses M < 40 M ⊙, and that more than than half of the stars are best-fitted by the M = 25 M ⊙ hypernova (E 51 = 10) models. The results also indicate that the majority of the primordial supernovae have ejected 10−2–10−1 M ⊙ of 56Ni, leaving behind a compact remnant (either a neutron star or a black hole), with a mass in the range of ~1.5–5 M ⊙. These results suggest that the masses of the first stars responsible for the first metal enrichment are predominantly <40 M ⊙. This implies that the higher-mass first stars were either less abundant, directly collapsed into a black hole without ejecting heavy elements, or a supernova explosion of a higher-mass first star inhibits the formation of the next generation of low-mass stars at [Fe/H] < −3.Peer reviewedFinal Accepted Versio

Origin of the anomalous mass renormalization in metallic quantum well states of correlated oxide SrVO3_3

$In$ $situ$ angle-resolved photoemission spectroscopy (ARPES) has been performed on SrVO$_3$ ultrathin films, which show metallic quantum well (QW) states, to unveil the origin of the anomalous mass enhancement in the QW subbands. The line-shape analysis of the ARPES spectra reveals that the strength of the electron correlation increases as the subband bottom energy approaches the Fermi level. These results indicate that the anomalous subband-dependent mass enhancement mainly arises from the quasi-one-dimensional character of confined V $3d$ states as a result of their orbital-selective quantization.Comment: 6 pages, 3 figure

Emergence of quantum critical behavior in metallic quantum-well states of strongly correlated oxides

Controlling quantum critical phenomena in strongly correlated electron systems, which emerge in the neighborhood of a quantum phase transition, is a major challenge in modern condensed matter physics. Quantum critical phenomena are generated from the delicate balance between long-range order and its quantum fluctuation. So far, the nature of quantum phase transitions has been investigated by changing a limited number of external parameters such as pressure and magnetic field. We propose a new approach for investigating quantum criticality by changing the strength of quantum fluctuation that is controlled by the dimensional crossover in metallic quantum well (QW) structures of strongly correlated oxides. With reducing layer thickness to the critical thickness of metal-insulator transition, crossover from a Fermi liquid to a non-Fermi liquid has clearly been observed in the metallic QW of SrVO$_3$ by \textit{in situ} angle-resolved photoemission spectroscopy. Non-Fermi liquid behavior with the critical exponent ${\alpha} = 1$ is found to emerge in the two-dimensional limit of the metallic QW states, indicating that a quantum critical point exists in the neighborhood of the thickness-dependent Mott transition. These results suggest that artificial QW structures provide a unique platform for investigating novel quantum phenomena in strongly correlated oxides in a controllable fashion.Comment: 6 pages, 3 figure

Machine learning detects multiplicity of the first stars in stellar archaeology data

In unveiling the nature of the first stars, the main astronomical clue is the elemental compositions of the second generation of stars, observed as extremely metal-poor (EMP) stars, in our Milky Way Galaxy. However, no observational constraint was available on their multiplicity, which is crucial for understanding early phases of galaxy formation. We develop a new data-driven method to classify observed EMP stars into mono- or multi-enriched stars with Support Vector Machines. We also use our own nucleosynthesis yields of core-collapse supernovae with mixing-fallback that can explain many of observed EMP stars. Our method predicts, for the first time, that $31.8\% \pm 2.3\%$ of 462 analyzed EMP stars are classified as mono-enriched. This means that the majority of EMP stars are likely multi-enriched, suggesting that the first stars were born in small clusters. Lower metallicity stars are more likely to be enriched by a single supernova, most of which have high carbon enhancement. We also find that Fe, Mg. Ca, and C are the most informative elements for this classification. In addition, oxygen is very informative despite its low observability. Our data-driven method sheds a new light on solving the mystery of the first stars from the complex data set of Galactic archaeology surveys.Comment: Accepted by ApJ, main results in Fig. 5, source code is available at https://gitlab.com/thartwig/emu-

MEASUREMENT OF ANTIOXIDANT POWER OF MOUTHWASHES INDICATED IN STOMATITIS

ABSTRACTObjective: Hospital formulations containing allopurinol and rebamipide are used in the prophylactic and therapeutic management of stomatitis,owing to their antioxidant powers. The objective of this study was to measure the antioxidant powers of Zyloric® tablets (allopurinol), Mucosta®tablets (rebamipide), different hospital formulations indicated in the management of stomatitis (allopurinol and rebamipide mouthwashes), andAzulene® 0.4% for Gargle (sodium azulene sulfonate).Methods: We measured the antioxidant powers of Zyloric® and Mucosta® tablets, all hospital formulations indicated in the management of stomatitis(allopurinol and rebamipide mouthwashes), and the widely used Azulene® 0.4% for Gargle by employing the biological antioxidant potential test. Wecompared the efficacy of each of these drugs in the management of stomatitis.Results: Azulene® 0.4% for Gargle was found to have stronger antioxidant power than Zyloric® (100 mg) and Mucosta® (100 mg) tablets dissolved inwater. The antioxidant power of the solvent used in hospital formulations was similar to that of the prepared hospital formulation. Antioxidant powerof the drugs themselves was not observed in both the allopurinol and rebamipide mouthwashes.Conclusion: The antioxidant power of the drugs was not observed in both the allopurinol and rebamipide mouthwashes; therefore, hospitalformulations used as antioxidants were found to be less effective in the treatment of stomatitis. However, Azulene® 0.4% for Gargle was found to beuseful in the prophylactic and therapeutic management of stomatitis, owing to its antioxidant, and anti-inflammatory effects.Keywords: Stomatitis, Bone alkaline phosphatase-test, Allopurinol mouthwash, Rebamipide mouthwash, Azulene® 0.4% for Gargle, Antioxidant powe

Quantum computing quantum Monte Carlo with hybrid tensor network toward electronic structure calculations of large-scale molecular and solid systems

Quantum computers are expected to solve the problems for quantum chemistry and materials science with higher accuracy than classical computers. Quantum computing quantum Monte Carlo (QC-QMC) is a method that can be combined with quantum algorithms such as variational quantum eigensolver (VQE) to obtain the ground state with fewer quantum resources and higher accuracy than either VQE or QMC alone. In this study, we propose an algorithm combining QC-QMC with hybrid tensor network (HTN) to extend the applicability of QC-QMC for the system beyond the size of a single quantum device, and we named the algorithm HTN+QMC. For HTN with the structure of a two-layer quantum-quantum tree tensor, the proposed algorithm for an $O(n^2)$-qubit reference wave function (trial wave function) in QMC can be performed by using only a $n$-qubit device excluding ancilla qubits. Full configuration interaction QMC is adopted as an example of QMC, and the proposed algorithm is applied to the Heisenberg chain model, the graphite-based Hubbard model, the hydrogen plane model, and MonoArylBiImidazole (MABI). The results show that the algorithm can achieve energy accuracy several orders of magnitude higher than either VQE or QMC alone. In addition, the energy accuracy of HTN+QMC is as same as QC-QMC when the system is appropriately decomposed. These results pave the way to electronic structure calculation for large systems with high accuracy on current quantum devices.Comment: 27pages, 19 figures, 5 table

Balance Measures Derived from Insole Sensor Differentiate Prodromal Dementia with Lewy Bodies

Dementia with Lewy bodies is the second most common type of neurodegenerative dementia, and identification at the prodromal stage$-$i.e., mild cognitive impairment due to Lewy bodies (MCI-LB)$-$is important for providing appropriate care. However, MCI-LB is often underrecognized because of its diversity in clinical manifestations and similarities with other conditions such as mild cognitive impairment due to Alzheimer's disease (MCI-AD). In this study, we propose a machine learning-based automatic pipeline that helps identify MCI-LB by exploiting balance measures acquired with an insole sensor during a 30-s standing task. An experiment with 98 participants (14 MCI-LB, 38 MCI-AD, 46 cognitively normal) showed that the resultant models could discriminate MCI-LB from the other groups with up to 78.0% accuracy (AUC: 0.681), which was 6.8% better than the accuracy of a reference model based on demographic and clinical neuropsychological measures. Our findings may open up a new approach for timely identification of MCI-LB, enabling better care for patients

Mapping of panda plumage color locus on the microsatellite linkage map of the Japanese quail

BACKGROUND: Panda (s) is an autosomal recessive mutation, which displays overall white plumage color with spots of wild-type plumage in the Japanese quail (Coturnix japonica). In a previous study, the s locus was included in the same linkage group as serum albumin (Alb) and vitamin-D binding protein (GC) which are mapped on chicken (Gallus gallus) chromosome 4 (GGA4). In this study, we mapped the s locus on the microsatellite linkage map of the Japanese quail by linkage analysis. RESULTS: Segregation data on the s locus were obtained from three-generation families (n = 106). Two microsatellite markers derived from the Japanese quail chromosome 4 (CJA04) and three microsatellite markers derived from GGA4 were genotyped in the three-generation families. We mapped the s locus between GUJ0026 and ABR0544 on CJA04. By comparative mapping with chicken, this locus was mapped between 10.0 Mb and 14.5 Mb region on GGA4. In this region, the endothelin receptor B subtype 2 gene (EDNRB2), an avian-specific paralog of the mammalian endothelin receptor B gene (EDNRB), is located. Because EDNRB is responsible for aganglionic megacolon and spot coat color in mouse, rat and equine, EDNRB2 is suggested to be a candidate gene for the s locus. CONCLUSION: The s locus and the five microsatellite markers were mapped on CJA04 of the Japanese quail. EDNRB2 was suggested to be a candidate gene for the s locus