Design and Evaluation of Flip-Flops for eFPGA Configuration Hardening
This work presents designs for rad-hard flip flops and some of their heavy-ion and proton test results.
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This work presents designs for rad-hard flip flops and some of their heavy-ion and proton test results.
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Chemical reactivity at the air–water interface is governed by the interfacial solvation of reactive species. For instance, during aqueous amino acid-based CO 2 absorption, water reorganizes around the reactive sites and couples dynamically with reaction pathways, facilitating the reaction. In this context, surface-sensitive vibrational sum-frequency generation (vSFG) spectroscopy can probe the OH stretch vibrations of interfacial water and determine the solvation structures around reactants and products, thereby furthering our understanding of the role of interfacial solvation. However, vSFG spectra of the air–water interface in the presence of charged species can be remarkably complex; key species-bound local water structures with distinct orientations may be hidden beneath prominent vSFG peaks arising from water–water hydrogen bonds and remain difficult to resolve. Here, we measure and compute vSFG spectra of the water OH stretch at air–water interfaces decorated with amino acids in their zwitterionic and anionic forms, as well as equimolar mixtures of these forms with bicarbonate. The latter represents post-CO 2 -absorption conditions. We find that computing depth- and frequency-dependent spectral densities—decomposed into contributions from water molecules hydrogen-bonded exclusively to other water molecules, exclusively to amines, exclusively to carboxylates, or shared between these polar/charged groups—is indispensable for accurate interpretation of the vSFG spectra. Key findings include orientational flip-flop in water sub-layers, strong carboxylate-water H-bonding, and water orientational ordering extending into the bulk aqueous phase induced by anionic amino acids. Here, this study provides a computational spectroscopic platform for improved understanding of interfacial solvation relevant to interfacial reactivity.
Developing telecom-compatible spin-photon interfaces is essential towards scalable quantum networks. Erbium ions (Er 3+ ) exhibit a unique combination of a telecom (1.5 mu m) optical transition and an effective spin-1=2 ground state, but identifying a host that enables heterogeneous device integration while preserving long optical and spin coherence remains an open challenge. In this work, we explore the potential of Er 3+ :CeO 2 films on silicon and study the Er 3+ spin coherence, offering low nuclear spin density and the potential for on-chip integration. We demonstrate a 38.8 mu s spin coherence, which can be extended to 176.4 mu s with dynamical decoupling. Pairing experiments with cluster correlation expansion calculations, we identify spectral diffusion induced by bath Er 3+ spin flip-flops as the dominant decoherence mechanism and provide pathways to millisecond-scale coherence.
Laser-driven Compton backscattering (CBS) has been proposed as method for controlling the intensity of colliding bunches in the FCC-ee so as to avoid the flip-flop instability caused by intensity asymmetry in colliding bunches. Laser-based collimation has also been proposed as an indestructible collimator for high-intensity electron beams. We have initiated a laboratory-based test program of these concepts with the E344 experiment at FACET-II. In this paper, we describe simulations of laser–beam interactions at FACET-II and the relevant scaling for FCC-ee. We also describe the experimental setup and diagnostics that will be used to make the measurements at FACET-II.
Random variations in microelectronic circuit structures represent the source of entropy for physical unclonable functions (PUFs). In this paper, we investigate delay variations that occur through the routing network and switch matrices of a field-programmable gate array (FPGA). The delay variations are isolated from other components of the programmable logic, e.g., look-up tables (LUTs), flip-flops (FFs), etc., using a feature of Xilinx FPGAs called dynamic partial reconfiguration (DPR). A set of partial designs is created to fix the placement of a time-to-digital converter (TDC) and supporting infrastructure to enable the path delays through the target interconnect and switch matrices to be extracted by subtracting out common-mode delay components. Delay variations are analyzed in the different levels of routing resources available within FPGAs, i.e., local routing and across-chip routing. Data are collected from a set of Xilinx Zynq 7010 devices, and a statistical analysis of within-die variations in delay through a set of the randomly-generated and hand-crafted interconnects is presented.
Laser-driven Compton backscattering (CBS) has been proposed as method for controlling the intensity of colliding bunches in the FCC-ee so as to avoid the flip-flop instability caused by intensity asymmetry in colliding bunches. Laser-based collimation has also been proposed as an indestructible collimator for high-intensity electron beams. We have initiated a laboratory-based test program of these concepts with the E344 experiment at FACET-II. In this paper, we describe simulations of laser-beam interactions at FACET-II and the relevant scaling for FCC-ee. We also describe the experimental setup and diagnostics that will be used to make the measurements at FACET-II.
Neural architecture search (NAS) is a powerful approach for automating model design, but existing methods often optimize for accuracy alone or rely on proxy metrics such as bit operations (BOPs) that correlate poorly with hardware cost. This gap is particularly large for FPGA deployment, where cost is dominated by a multi-dimensional budget of lookup tables, DSPs, flip-flops, BRAM, and latency. We present the Surrogate Neural Architecture Codesign Package (SNAC-Pack), an open-source AutoML framework for hardware-aware neural architecture codesign and end-to-end FPGA deployment. SNAC-Pack runs a multi-objective global search with Optuna and NSGA-II, loading trials to a shared SQLite store that enables parallel workers across compute nodes. A hardware surrogate model outputs per-trial resource and latency estimates, avoiding the synthesis cost that would otherwise dominate the search loop. A local search stage then applies quantization-aware training (QAT) together with iterative magnitude pruning in a combined compression loop, after which the final model is synthesized to FPGA firmware via the hls4ml Python library. A YAML configuration and an optional agentic frontend let users run the pipeline on new datasets without modifying the framework. We demonstrate SNAC-Pack on jet classification at the Large Hadron Collider and superconducting qubit readout, discovering compact architectures that match or exceed strong baselines on the task metric while reducing FPGA resource utilization and, in the qubit readout case, reducing the design space exploration process from months of manual fine-tuning to hours of automated search.