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  1. Reduced-nitrogen compounds (RNC), such as ammonia and amines, play important roles in atmospheric aerosol nucleation, secondary organic aerosol (SOA), and cloud formation processes. Fast measurements of ammonia and amines are made with a chemical ionization mass spectrometer (CIMS). Clusters containing RNC are measured with an atmospheric pressure interface time of flight mass spectrometer (APi-TOF) or chemical ionization APi-TOF (CI-APi-TOF). Aerosol-phase amines can be detected with a single particle mass spectrometer at real-time, or with offline chemical analytical methods using filter samples. However, the application of these instruments in real atmospheric measurements is still very limited. This perspective article highlights recentmore »measurements of RNC in the atmosphere and discusses their implications in new particle formation (NPF).« less
    Free, publicly-accessible full text available April 6, 2023
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  5. ABSTRACT We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r = 23.6 versus r = 22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314 000 galaxies. 140 000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars,more »and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314 000 galaxies. We use active learning to focus our volunteer effort on the galaxies which, if labelled, would be most informative for training our ensemble. When measured against confident volunteer classifications, the trained networks are approximately 99 per cent accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve.« less
    Free, publicly-accessible full text available December 3, 2022
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  7. Free, publicly-accessible full text available June 1, 2022
  8. Tessaro, Stefano (Ed.)
    A Proof of Sequential Work (PoSW) allows a prover to convince a resource-bounded verifier that the prover invested a substantial amount of sequential time to perform some underlying computation. PoSWs have many applications including time-stamping, blockchain design, and universally verifiable CPU benchmarks. Mahmoody, Moran, and Vadhan (ITCS 2013) gave the first construction of a PoSW in the random oracle model though the construction relied on expensive depth-robust graphs. In a recent breakthrough, Cohen and Pietrzak (EUROCRYPT 2018) gave an efficient PoSW construction that does not require expensive depth-robust graphs. In the classical parallel random oracle model, it is straightforward tomore »argue that any successful PoSW attacker must produce a long ℋ-sequence and that any malicious party running in sequential time T-1 will fail to produce an ℋ-sequence of length T except with negligible probability. In this paper, we prove that any quantum attacker running in sequential time T-1 will fail to produce an ℋ-sequence except with negligible probability - even if the attacker submits a large batch of quantum queries in each round. The proof is substantially more challenging and highlights the power of Zhandry’s recent compressed oracle technique (CRYPTO 2019). We further extend this result to establish post-quantum security of a non-interactive PoSW obtained by applying the Fiat-Shamir transform to Cohen and Pietrzak’s efficient construction (EUROCRYPT 2018).« less