Recovering the seismic history of multiple segments within a fault system provides a spatiotemporal framework for the fault activity across the system. This kind of data is essential for improving our understanding of how faults interact during earthquake cycles and how they are distributed within a fault system. Bedrock fault scarps, reaching up to 10‐m height, are abundant across the Bet Kerem fault system, Galilee, northern Israel. Using the 36 Cl exposure dating method, we recovered the last 30 ka scarp exhumation history of three fault segments from the Bet Kerem fault system. Results indicate that the three faults were active simultaneously in at least three distinguished activity periods, during which a minimum of 1.2 m of surface rupturing occurred in each period. The synchronized activity and total surface rupture at each activity period suggest that the three dated segments were ruptured simultaneously by the same earthquake. That is, a multi‐segment rupture earthquake and that each activity period included a cluster of at least two large multi‐segment earthquakes. The results also indicate a recurrence interval between clusters of 3.5–4.5 ka and the existence of a seismic super cycle with a recurrence interval of about 13 ka.
Around 60% of households in Texas currently rely on electricity for space heating. As decarbonization efforts increase, non‐electrified households could adopt electric heat pumps, significantly increasing peak (highest) electricity demand in winter. Simultaneously, anthropogenic climate change is expected to increase temperatures, the potential for summer heat waves, and associated electricity demand for cooling. Uncertainty regarding the timing and magnitude of these concurrent changes raises questions about how they will jointly affect the seasonality of peak demand, firm capacity requirements, and grid reliability. This study investigates the net effects of residential space heating electrification and climate change on long‐term demand patterns and load shedding potential, using climate change projections, a predictive load model, and a direct current optimal power flow (DCOPF) model of the Texas grid. Results show that full electrification of residential space heating by replacing existing fossil fuel use with higher efficiency heat pumps could significantly improve reliability under hotter futures. Less efficient heat pumps may result in more severe winter peaking events and increased reliability risks. As heating electrification intensifies, system planners will need to balance the potential for greater resource adequacy risk caused by shifts in seasonal peaking behavior alongside the benefits (improved efficiency and reductions in emissions).
Extending Moore's law by augmenting complementary-metal-oxide semiconductor(CMOS) transistors with emerging nanotechnologies (X) has become increasinglyimportant. One important class of problems involve sampling-based Monte Carloalgorithms used in probabilistic machine learning, optimization, and quantumsimulation. Here, we combine stochastic magnetic tunnel junction (sMTJ)-basedprobabilistic bits (p-bits) with Field Programmable Gate Arrays (FPGA) tocreate an energy-efficient CMOS + X (X = sMTJ) prototype. This setup shows howasynchronously driven CMOS circuits controlled by sMTJs can performprobabilistic inference and learning by leveraging the algorithmicupdate-order-invariance of Gibbs sampling. We show how the stochasticity ofsMTJs can augment low-quality random number generators (RNG). Detailedtransistor-level comparisons reveal that sMTJ-based p-bits can replace up to10,000 CMOS transistors while dissipating two orders of magnitude less energy.Integrated versions of our approach can advance probabilistic computinginvolving deep Boltzmann machines and other energy-based learning algorithmswith extremely high throughput and energy efficiency.
Domain-specific hardware to solve computationally hard optimization problemshas generated tremendous excitement. Here, we evaluate probabilistic bit(p-bit) based Ising Machines (IM) on the 3-regular 3-Exclusive ORSatisfiability (3R3X), as a representative hard optimization problem. We firstintroduce a multiplexed architecture that emulates all-to-all networkfunctionality while maintaining highly parallelized chromatic Gibbs sampling.We implement this architecture in single Field-Programmable Gate Arrays (FPGA)and show that running the adaptive parallel tempering algorithm demonstratescompetitive algorithmic and prefactor advantages over alternative IMs byD-Wave, Toshiba, and Fujitsu. We also implement higher-order interactions thatlead to better prefactors without changing algorithmic scaling for the XORSATproblem. Even though FPGA implementations of p-bits are still not quite as fastas the best possible greedy algorithms accelerated on Graphics Processing Units(GPU), scaled magnetic versions of p-bit IMs could lead to orders of magnitudeimprovements over the state of the art for generic optimization.