A Conditionally Chaotic Physically Unclonable Function Design Framework with High Reliability

Physically Unclonable Function (PUF) circuits are promising low-overhead hardware security primitives, but are often gravely susceptible to machine learning–based modeling attacks. Recently, chaotic PUF circuits have been proposed that show greater robustness to modeling attacks. However, they often suffer from unacceptable overhead, and their analog components are susceptible to low reliability. In this article, we propose the concept of a conditionally chaotic PUF that enhances the reliability of the analog components of a chaotic PUF circuit to a level at par with their digital counterparts. A conditionally chaotic PUF has two modes of operation: bistable and chaotic , and switching between these two modes is conveniently achieved by setting a mode-control bit (at a secret position) in an applied input challenge. We exemplify our PUF design framework for two different PUF variants—the CMOS Arbiter PUF and a previously proposed hybrid CMOS-memristor PUF, combined with a hardware realization of the Lorenz system as the chaotic component. Through detailed circuit simulation and modeling attack experiments, we demonstrate that the proposed PUF circuits are highly robust to modeling and cryptanalytic attacks, without degrading the reliability of the original PUF that was combined with the chaotic circuit, and incurs acceptable hardware footprint.

Topographic connectivity and cellular profiling reveal detailed input pathways and functionally distinct cell types in the subthalamic nucleus

SummaryThe subthalamic nucleus (STN) controls psychomotor activity and is an efficient therapeutic deep brain stimulation target in Parkinson’s disease patients. Despite evidence indicating position-dependent therapeutic effects and distinct functions within the STN, input circuit and cellular profile in the STN remain largely unclear. Using advanced neuroanatomical techniques, we constructed a comprehensive connectivity map of the indirect and hyperdirect pathways in both the mouse and human STN. Our detailed circuit- and cellular-level connectivity revealed a topographically graded organization with three convergent types of indirect and hyperdirect-pathways. Furthermore, we identified two functional types of glutamatergic STN neurons (parvalbumin, PV +/- neurons) segregated with a topographical distribution. Glutamatergic PV+ STN neurons contribute to burst firing. We confirmed synaptic connectivity from indirect and hyperdirect pathways to both PV+ and PV-. These data suggest a complex interplay of information integration within the basal ganglia underlying coordinated movement control and therapeutic effects.

Compact Modeling of a 3.3 kV SiC MOSFET Power Module for Detailed Circuit-Level Electrothermal Simulations Including Parasitics

In this paper, an advanced electrothermal simulation strategy is applied to a 3.3 kV silicon carbide MOSFET power module. The approach is based on a full circuital representation of the module, where use is made of the thermal equivalent of the Ohm’s law. The individual transistors are described with subcircuits, while the dynamic power-temperature feedback is accounted for through an equivalent thermal network enriched with controlled sources enabling nonlinear thermal effects. A synchronous step-up DC-DC converter and a single-phase inverter, both incorporating the aforementioned power module, are simulated. Good accuracy was ensured by considering electromagnetic effects due to parasitics, which were experimentally extracted in a preliminary stage. Low CPU times are needed, and no convergence issues are encountered in spite of the high switching frequencies. The impact of some key parameters is effortlessly quantified. The analysis witnesses the efficiency and versatility of the approach, and suggests its adoption for design, analysis, and synthesis of high-frequency power converters in wide-band-gap semiconductor technology.

Ultrastructural readout of in vivo synaptic activity for functional connectomics.

Large-volume ultrastructural mapping approaches yield detailed circuit wiring diagrams but lack an integrated synaptic activity readout which is essential for functional interpretation of the connectome. Here we resolve this limitation by combining functional synaptic labelling in vivo with focused ion-beam scanning electron microscopy (FIBSEM) and machine learning-based segmentation. Our approach generates high-resolution near-isotropic three-dimensional readouts of activated vesicle pools across large populations of individual synapses in a volume of tissue, opening the way for detailed functional connectomics studies. We apply this method to measure presynaptic activity in an ultrastructural context in synapses activated by sensory input in primary visual cortex in awake head-fixed mice, showing that the numbers of recycling and non-recycling vesicles approximate to a lognormal distribution across a large number of synapses. We also demonstrate that neighbouring boutons of the same axon, which share the same spiking activity, can differ greatly in their presynaptic release probability.

Retinal Mechanisms for Motion Detection

Motion is a key feature of the sensory experience of visual animals. The mammalian retina has evolved a number of diverse motion sensors to detect and parse visual motion into behaviorally relevant neural signals. Extensive work has identified retinal outputs encoding directional and nondirectional motion, and the intermediate circuitry underlying this tuning. Detailed circuit mechanism investigation has established retinal direction selectivity in particular as a model system of neural computation.

Fast-Scale Instability and Stabilization by Adaptive Slope Compensation of a PV-Fed Differential Boost Inverter

Numerical simulations reveal that a single-stage differential boost AC module supplied from a PV module under an Maximum Power Point Tracking (MPPT) control at the input DC port and with current synchronization at the AC grid port might exhibit bifurcation phenomena under some weather conditions leading to subharmonic oscillation at the fast-switching scale. This paper will use discrete-time approach to characterize such behavior and to identify the onset of fast-scale instability. Slope compensation is used in the inner current loop to improve the stability of the system. The compensation slope values needed to guarantee stability for the full range of operating duty cycle and leading to an optimal deadbeat response are determined. The validity of the followed procedures is finally validated by a numerical simulations performed on a detailed circuit-level switched model of the AC module.

Modified asymmetrical 13-level inverter topology with reduce power semiconductor devices

This paper introduces a modified multilevel inverter topology with asymmetrical dc sources combination. The significant features of the proposed circuit are the reduced number of switches and low total standing voltage (TSV). Proposed topology utilizes ten switches to produce 13 level output with per unit TSVp.u of 5.33. An additional feature of the proposed topology is the inherent negative level generation as there is no requirement of an H-bridge for the polarity reversals. Nearest level control (NLC) technique is used as the modulation strategy. Performance of the proposed topology is validated through extensive analysis using Simulink and PLECS software. Detailed circuit analysis and its power loss, as well as efficiency studies, have been carried out under constant and dynamic load conditions. Results obtained shows that the proposed topology is working well, producing an output of 13-level with total harmonic distortion of 6.36% and inverter efficiency of 98.8%. The topology is extended to n-level structure, and its generalized expressions for different parameters were formulated. The comparison of the generalized structure with other existing topology is carried out, and it is found that the proposed topology outperform other topologies on many parameters.

Efficient Quantum Walk Circuits for Metropolis-Hastings Algorithm

We present a detailed circuit implementation of Szegedy's quantization of the Metropolis-Hastings walk. This quantum walk is usually defined with respect to an oracle. We find that a direct implementation of this oracle requires costly arithmetic operations. We thus reformulate the quantum walk, circumventing its implementation altogether by closely following the classical Metropolis-Hastings walk. We also present heuristic quantum algorithms that use the quantum walk in the context of discrete optimization problems and numerically study their performances. Our numerical results indicate polynomial quantum speedups in heuristic settings.

Bidirectional Power Flow Control of a Multi Input Converter for Energy Storage System

The objective of this paper is to propose a multi-input DC-DC converter with bidirectional power flow control capability. Compared to the traditional power converter, the multi-input converter (MIC) can save on the number of components and the circuit cost. Under normal conditions, the MIC is able to transfer energy from different input sources to the load. However, if the battery module is adopted, both the charging or discharging features should be considered. Therefore, the bidirectional power flow control of the MIC is necessary. On the other hand, because of the inconsistency characteristics of batteries, unbalanced circuit operation might occur whereby the circuit and the battery might be damaged. Therefore, dynamic current regulation strategies are developed for the MIC. Consequently, the proposed MIC circuit is able to achieve the bidirectional power flow control capability as well as control the input currents independently. Detailed circuit analysis and comprehensive mathematical derivation and of the proposed MIC will be presented in this paper. Finally, both simulation and experimental results obtained from a 500 W prototype circuit verify the performance and feasibility of the proposed bidirectional multi-input converter.