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Abstract We analyze a specular reflection of the Sun off of Titan’s largest sea, Kraken Mare, observed by the Cassini Visual and Infrared Mapping Spectrometer on the T104 flyby (2014 August 21). We use the specularly reflectedI/Fsignal to derive a transmission spectrum. Owing to the low incidence and emission angles (51°) of the reflection, the specular signal is visible down to the 1.3 and 1.6μm windows, as well as the 2.0, 2.7/2.8, and 5μm windows as had been seen previously on T85. We confirm the T85 result that Titan’s atmosphere absorbs more at 2.7μm than it does at 2.8μm and that the “notch” between those windows results from absorption in the atmosphere and not from the surface. We compare our derived T104 spectrum to numerically integrated optical depths calculated using Huygens-derived haze properties and correlated-kgas absorption coefficients. We fit the T104 observation using 63% ± 3% greater haze abundance than derived from Huygens and a wavelength exponent of 2.50 ± 0.03, steeper than the 2.0 derived from Huygens. We measure a surface methane fraction of 0.043 ± 0.001 over Kraken Mare at 68°N latitude, slightly lower than the Huygens measurement of 0.0539 ± 0.0014 in Titan’s tropics. The comparison shows the utility of specular reflection transmission spectra for quantitative determination of Titan’s atmospheric properties. Fitting of carbon monoxide (CO) absorption places a constraint of 22.6 ± 0.3 ppm on the fraction of CO in Titan’s atmosphere. Mismatches between our model and these specular transmission observations may allow quantitative estimation of the effects of unknown composition gaseous absorbers throughout Titan’s atmosphere. 

The interaction between radio jets and quasar host galaxies plays a paramount role in quasar and galaxy co-evolution. However, very little is known at present about this interaction at very high−z. Here, we present new Atacama Large Millimeter/submillimeter Array (ALMA) observations in Bands 7 and 3 of six radio-loud (RL) quasar host galaxies atz > 5. We recovered [C II] 158 μm line and underlying dust continuum emission at > 2σfor five sources, while we obtained upper limits for the CO(6-5) emission line and continuum for the remaining source. At the spatial resolution of our observations (∼1″​​_.0–1″​​_.4), we did not recover any perturbed or extended morphologies or kinematics, which are known signatures of potential mergers. These galaxies already host large quantities of gas (∼10¹⁰M_⊙), with [C II] luminosities ofL_[C II] ∼ 10^8 − 9 L_⊙and [C II]-based star formation rates of 30 − 400 M_⊙yr⁻¹. In building their radio/submillimeter (radio/submm) spectral energy distributions (SEDs), we found that in at least four cases, the 1 mm continuum intensity arises from a combination of synchrotron and dust emission. The initial estimation of synchrotron contribution at 300 GHz in these cases is of ≳10%. Assuming a scenario where the continuum emission is solely due to cold dust as an upper limit, we obtained infrared (IR) luminosities ofL_IR ∼ 10^{11 − 12} L_⊙. We compared the properties of the sources inspected here with a large collection of radio-quiet sources from the literature, as well as a sample of RL quasars from previous studies at comparable redshifts. We recovered a mild potential decrease inL_[C II]for the RL sources, which might be due to a suppression of the cool gas emission due to the radio jets. We did not find any [C II] emitting companion galaxy candidate around the five RL quasars observed in Band 7. Given the depth of our dataset, this result is still consistent with what has been observed around radio-quiet quasars. Future higher spatial-resolution observations, over a broader frequency range, of high−zRL quasars hosts will allow us to further improve our understanding of the physics of these sources. 

In this paper, we propose the Quantum Data Center (QDC), an architecture combining Quantum Random Access Memory (QRAM) and quantum networks. We give a precise definition of QDC, and discuss its possible realizations and extensions. We discuss applications of QDC in quantum computation, quantum communication, and quantum sensing, with a primary focus on QDC for T-gate resources, QDC for multi-party private quantum communication, and QDC for distributed sensing through data compression. We show that QDC will provide efficient, private, and fast services as a future version of data centers. 

Efficient suppression of errors without full error correction is crucial for applications with noisy intermediate-scale quantum devices. Error mitigation allows us to suppress errors in extracting expectation values without the need for any error correction code, but its applications are limited to estimating expectation values, and cannot provide us with high-fidelity quantum operations acting on arbitrary quantum states. To address this challenge, we propose to use error filtration (EF) for gate-based quantum computation, as a practical error suppression scheme without resorting to full quantum error correction. The result is a general-purpose error suppression protocol where the resources required to suppress errors scale independently of the size of the quantum operation, and does not require any logical encoding of the operation. The protocol provides error suppression whenever an error hierarchy is respected—that is, when the ancillary controlled-swap operations are less noisy than the operation to be corrected. We further analyze the application of EF to quantum random access memory, where EF offers hardware-efficient error suppression. 

Neophobia, or aversion to novelty, is important for adaptability and survival as it influences the ways in which animals navigate risk and interact with their environments. Across individuals, species and other taxonomic levels, neophobia is known to vary considerably, but our understanding of the wider ecological drivers of neophobia is hampered by a lack of comparative multispecies studies using standardized methods. Here, we utilized the ManyBirds Project, a Big Team Science large-scale collaborative open science framework, to pool efforts and resources of 129 collaborators at 77 institutions from 24 countries worldwide across six continents. We examined both difference scores (between novel object test and control conditions) and raw data of latency to touch familiar food in the presence (test) and absence (control) of a novel object among 1,439 subjects from 136 bird species across 25 taxonomic orders incorporating lab, field, and zoo sites. We first demonstrated that consistent differences in neophobia existed among individuals, among species, and among other taxonomic levels in our dataset, rejecting the null hypothesis that neophobia is highly plastic at all taxonomic levels with no evidence for evolutionary divergence. We then tested for effects of ecological factors on neophobia, including diet, sociality, habitat, and range, while accounting for phylogeny. We found that (i) species with more specialist diets were more neophobic than those with more generalist diets, providing support for the Neophobia Threshold Hypothesis; (ii) migratory species were also more neophobic than nonmigratory species, which supports the Dangerous Niche Hypothesis. Our study shows that the evolution of avian neophobia has been shaped by ecological drivers and demonstrates the potential of Big Team Science to advance our understanding of animal behavior.