The Climate Gap: Inequalities in How Climate Change Hurts Americans & How to Close the Gap

By now, virtually all Americans concur that climate change is real, and could pose devastating consequences for our nation and our children. Equally real is the "Climate Gap" -- the sometimes hidden and often-unequal impact climate change will have on people of color and the poor in the United States. This report helps to document the Climate Gap, connecting the dots between research on heat waves, air quality, and other challenges associated with climate change. But we do more than point out an urgent problem; we also explore how we might best combine efforts to both solve climate change and close the Climate Gap -- including an appendix focused on California's global warming policy and a special accompanying analysis of the federal-level American Clean Energy Security Act

Engineering local strain for single-atom nuclear acoustic resonance in silicon

Mechanical strain plays a key role in the physics and operation of nanoscale semiconductor systems, including quantum dots and single-dopant devices. Here, we describe the design of a nanoelectronic device, where a single nuclear spin is coherently controlled via nuclear acoustic resonance (NAR) through the local application of dynamical strain. The strain drives spin transitions by modulating the nuclear quadrupole interaction. We adopt an AlN piezoelectric actuator compatible with standard silicon metal-oxide-semiconductor processing and optimize the device layout to maximize the NAR drive. We predict NAR Rabi frequencies of order 200 Hz for a single 123Sb nucleus in a wide region of the device. Spin transitions driven directly by electric fields are suppressed in the center of the device, allowing the observation of pure NAR. Using electric field gradient-elastic tensors calculated by the density-functional theory, we extend our predictions to other high-spin group-V donors in silicon and to the isoelectronic 73Ge atom

IQRM: real-time adaptive RFI masking for radio transient and pulsar searches

In a search for short timescale astrophysical transients in time-domain data, radio-frequency interference (RFI) causes both large quantities of false positive candidates and a significant reduction in sensitivity if not correctly mitigated. Here we propose an algorithm that infers a time-variable frequency channel mask directly from short-duration ($\sim$1 s) data blocks: the method consists of computing a spectral statistic that correlates well with the presence of RFI, and then finding high outliers among the resulting values. For the latter task, we propose an outlier detection algorithm called Inter-Quartile Range Mitigation (IQRM), that is both non-parametric and robust to the presence of a trend in sequential data. The method requires no training and can in principle adapt to any telescope and RFI environment; its efficiency is shown on data from both the MeerKAT and Lovell 76-m radio telescopes. IQRM is fast enough to be used in a streaming search and has been integrated into the MeerTRAP real-time transient search pipeline. Open-source Python and C++ implementations are also provided.Comment: Accepted for publication in MNRAS, 11 pages, 9 figures. Minor corrections, improved clarity, additional analysis of impact on single pulse searches. IQRM implementations can be found at https://github.com/v-morello/iqrm (Python) and https://gitlab.com/kmrajwade/iqrm_apollo (C++

Magnetic dipolar ordering and relaxation in the high-spin molecular cluster compound Mn6

Few examples of magnetic systems displaying a transition to pure dipolar magnetic order are known to date, and single-molecule magnets can provide an interesting example. The molecular cluster spins and thus their dipolar interaction energy can be quite high, leading to reasonably accessible ordering temperatures, provided the crystal field anisotropy is sufficiently small. This condition can be met for molecular clusters of sufficiently high symmetry, as for the Mn6 compound studied here. Magnetic specific heat and susceptibility experiments show a transition to ferromagnetic dipolar order at T_{c} = 0.16 K. Classical Monte-Carlo calculations indeed predict ferromagnetic ordering and account for the correct value of T_{c}. In high magnetic fields we detected the contribution of the ^{55}Mn nuclei to the specific heat, and the characteristic timescale of nuclear relaxation. This was compared with results obtained directly from pulse-NMR experiments. The data are in good mutual agreement and can be well described by the theory for magnetic relaxation in highly polarized paramagnetic crystals and for dynamic nuclear polarization, which we extensively review. The experiments provide an interesting comparison with the recently investigated nuclear spin dynamics in the anisotropic single molecule magnet Mn12-ac.Comment: 19 pages, 11 eps figures. Contains extensive discussions on dipolar ordering, specific heat and nuclear relaxation in molecular magnet

Hyperfine spectroscopy and fast, all-optical arbitrary state initialization and readout of a single, ten-level 73{}^{73}Ge vacancy nuclear spin qudit

A high-spin nucleus coupled to a color center can act as a long-lived memory qudit in a spin-photon interface. The germanium vacancy (GeV) in diamond has attracted recent attention due to its excellent spectral properties and provides access to the 10-dimensional Hilbert space of the $I = 9/2$ ${}^{73}$Ge nucleus. Here, we observe the ${}^{73}$GeV hyperfine structure, perform nuclear spin readout, and optically initialize the ${}^{73}$Ge spin into any eigenstate on a $\mu$s-timescale and with a fidelity of up to $97 \pm 3\%$. Our results establish ${}^{73}$GeV as an optically addressable high-spin quantum platform for a high-efficiency spin-photon interface as well as for foundational quantum physics and metrology.Comment: 8 pages, 4 figure

Nephrops norvegicus in the Adriatic Sea: Connectivity modeling essential fish habitats and management area network

AbstractKnowledge of connectivity among subpopulations is fundamental in the identification of the appropriate geographical scales for stock status evaluation and management, the identification of areas with greater retention rates, and space‐based fisheries management. Here, an integration of hydrodynamic, biological, and habitat models results is used to assess connectivity and support the definition of essential fish habitats (EFH) in the Adriatic Sea, with reference to Nephrops norvegicus, an important benthic commercial resource, the recruitment of which is strongly related to larval dispersal from spawning to recruitment areas. We explored oceanographic and biological connectivity in the Adriatic Sea under a wide and representative variety of oceanographic conditions (winters 2006–2012) by tracking 3D trajectories of larvae released from different areas. We used a Lagrangian model that features a specific larval behavior module with explicit dependence on environmental parameters (i.e., temperature and sediment type) and that is driven by high‐resolution hydrodynamic and meteorological data. The results were used to partition the area in which Nephrops was observed into 20 homogenous management subareas; to assess the connection between spawning, recruitment, and harvesting grounds; and to identify potential subpopulation boundaries as well as the connectivity among the potential subpopulations. The results suggest the presence of at least three distinct subpopulations, which need to be independently managed and conserved, and confirms that the Jabuka‐Pomo pit is the most important spawning area, but alone it cannot sustain Nephrops populations throughout the Adriatic Sea. The results also show the importance to move from particle‐tracking to approaches based on integrated models