Focusing grating couplers for radio-frequency surface ion traps

We present a photonic integrated circuit design with multiple focusing grating couplers that can be used in a surface ion trap. This system allows transferring laser radiation from different laser sources to the ion trapped 240 μm above the surface for further manipulations.

Wideband ring mixer for band #1 of MB-OFDM systems in 180 nm CMOS technology

A wideband down conversion ring mixer is proposed for multi band orthogonal frequency division multiplexing (MB-OFDM) system in 180 nm CMOS technology. The mixer is essentially used in a heterodyne wireless receiver to enhance the selectivity of the system. Being a nonlinear system, the mixer dominates the overall performance of the system. The design of down conversion mixer is the most challenging part of a receive chain. Wideband impedance matching always remains a challenge in any radio frequency integrated circuit design. This paper presents the design of a ring mixer with high linearity, wideband impedance matching using differential resistive impedance matching and without using any DC bias. The proposed mixer is tuned for a frequency of 3.432 GHz of band 1 of the MB-OFDM system. Mixer core is based on the FET ring mixer topology. The mixer is implemented in 180 nm CMOS technology. The mixer achieves the minimum conversion loss of 10.49 dB, 1 dB compression point (P1) of 12.40 dBm, third order input intercept point (IIP3) of 12.01 dBm, a minimum SSB noise figure of 8.99 dB, and S 11 of less than -10 dB over the frequency range of 0 to 13.61 GHz . The layout of the mixer records an active area of 183.75 μm 2 .

Digital integrated circuit design : "ASIC implementation of an adaptive digital predistorter for lasers on ROF

Radio over fiber has become one of the most useful technologies for providing extended coverage of wireless communications services. ROF uses analog fiber optic links to distribute wireless radio signals from a central location to multiple remote locations where the added desired antennas are placed for stronger signal coverage. The adaptive predistortion technique of a LASER ROF chip is implemented using the digital IC design flow. The design flow can be separated into two main parts, namely the RTL design / synthesis and the generation of the actual chip. The first part in the design flow consists of generating the proper logical functionality of the IC using a hardware description language (HDL), namely VHDL or Verilog, and synthesizing the code to ensure proper operation. The second part in the design flow consists of floorplanning and physical layout of the ASIC.

Digital integrated circuit design : "ASIC implementation of an adaptive digital predistorter for lasers on ROF

Radio over fiber has become one of the most useful technologies for providing extended coverage of wireless communications services. ROF uses analog fiber optic links to distribute wireless radio signals from a central location to multiple remote locations where the added desired antennas are placed for stronger signal coverage. The adaptive predistortion technique of a LASER ROF chip is implemented using the digital IC design flow. The design flow can be separated into two main parts, namely the RTL design / synthesis and the generation of the actual chip. The first part in the design flow consists of generating the proper logical functionality of the IC using a hardware description language (HDL), namely VHDL or Verilog, and synthesizing the code to ensure proper operation. The second part in the design flow consists of floorplanning and physical layout of the ASIC.

Challenging the Security of Logic Locking Schemes in the Era of Deep Learning: A Neuroevolutionary Approach

Logic locking is a prominent technique to protect the integrity of hardware designs throughout the integrated circuit design and fabrication flow. However, in recent years, the security of locking schemes has been thoroughly challenged by the introduction of various deobfuscation attacks. As in most research branches, deep learning is being introduced in the domain of logic locking as well. Therefore, in this article we present SnapShot, a novel attack on logic locking that is the first of its kind to utilize artificial neural networks to directly predict a key bit value from a locked synthesized gate-level netlist without using a golden reference. Hereby, the attack uses a simpler yet more flexible learning model compared to existing work. Two different approaches are evaluated. The first approach is based on a simple feedforward fully connected neural network. The second approach utilizes genetic algorithms to evolve more complex convolutional neural network architectures specialized for the given task. The attack flow offers a generic and customizable framework for attacking locking schemes using machine learning techniques. We perform an extensive evaluation of SnapShot for two realistic attack scenarios, comprising both reference combinational and sequential benchmark circuits as well as silicon-proven RISC-V core modules. The evaluation results show that SnapShot achieves an average key prediction accuracy of 82.60% for the selected attack scenario, with a significant performance increase of 10.49 percentage points compared to the state of the art. Moreover, SnapShot outperforms the existing technique on all evaluated benchmarks. The results indicate that the security foundation of common logic locking schemes is built on questionable assumptions. Based on the lessons learned, we discuss the vulnerabilities and potentials of logic locking uncovered by SnapShot. The conclusions offer insights into the challenges of designing future logic locking schemes that are resilient to machine learning attacks.