Overview of the EU FP7-project HISTORIC

HISTORIC aims to develop and test complex photonic integrated circuits containing a relatively large number of digital photonic elements for use in e.g. all-optical packet switching. These photonic digital units are all-optical flip-flops based on ultra compact laser diodes, such as microdisk lasers and photonic crystal lasers. These lasers are fabricated making use of the heterogeneous integration of InP membranes on top of silicon on insulator (SOI) passive optical circuits. The very small dimensions of the lasers are, at least for some approaches, possible because of the high index contrast of the InP membranes and by making use of the extreme accuracy of CMOS processing. All-optical flip-flops based on heterogeneously integrated microdisk lasers with diameter of 7.5 mu m have already been demonstrated. They operate with a CW power consumption of a few mW and can switch in 60ps with switching energies as low as 1.8 fJ. Their operation as all-optical gate has also been demonstrated. Work is also on-going to fabricate heterogeneously integrated photonic crystal lasers and all-optical flip-flops based on such lasers. A lot of attention is given to the electrical pumping of the membrane InP-based photonic crystal lasers and to the coupling to SOI wire waveguides. Optically pumped photonic crystal lasers coupled to SOI wires have been demonstrated already. The all-optical flip-flops and gates will be combined into more complex photonic integrated circuits, implementing all-optical shift registers, D flip-flops, and other all-optical switching building blocks. The possibility to integrate a large number of photonic digital units together, but also to integrate them with compact passive optical routers such as AWGs, opens new perspectives for the design of integrated optical processors or optical buffers. The project therefore also focuses on designing new architectures for such optical processing or buffer chips

Design of variation-tolerant synchronizers for multiple clock and voltage domains

PhD ThesisParametric variability increasingly affects the performance of electronic circuits as the fabrication technology has reached the level of 32nm and beyond. These parameters may include transistor Process parameters (such as threshold voltage), supply Voltage and Temperature (PVT), all of which could have a significant impact on the speed and power consumption of the circuit, particularly if the variations exceed the design margins. As systems are designed with more asynchronous protocols, there is a need for highly robust synchronizers and arbiters. These components are often used as interfaces between communication links of different timing domains as well as sampling devices for asynchronous inputs coming from external components. These applications have created a need for new robust designs of synchronizers and arbiters that can tolerate process, voltage and temperature variations. The aim of this study was to investigate how synchronizers and arbiters should be designed to tolerate parametric variations. All investigations focused mainly on circuit-level and transistor level designs and were modeled and simulated in the UMC90nm CMOS technology process. Analog simulations were used to measure timing parameters and power consumption along with a “Monte Carlo” statistical analysis to account for process variations. Two main components of synchronizers and arbiters were primarily investigated: flip-flop and mutual-exclusion element (MUTEX). Both components can violate the input timing conditions, setup and hold window times, which could cause metastability inside their bistable elements and possibly end in failures. The mean-time between failures is an important reliability feature of any synchronizer delay through the synchronizer. The MUTEX study focused on the classical circuit, in addition to a number of tolerance, based on increasing internal gain by adding current sources, reducing the capacitive loading, boosting the transconductance of the latch, compensating the existing Miller capacitance, and adding asymmetry to maneuver the metastable point. The results showed that some circuits had little or almost no improvements, while five techniques showed significant improvements by reducing τ and maintaining high tolerance. Three design approaches are proposed to provide variation-tolerant synchronizers. wagging synchronizer proposed to First, the is significantly increase reliability over that of the conventional two flip-flop synchronizer. The robustness of the wagging technique can be enhanced by using robust τ latches or adding one more cycle of synchronization. The second approach is the Metastability Auto-Detection and Correction (MADAC) latch which relies on swiftly detecting a metastable event and correcting it by enforcing the previously stored logic value. This technique significantly reduces the resolution time down from uncertain synchronization technique is proposed to transfer signals between Multiple- Voltage Multiple-Clock Domains (MVD/MCD) that do not require conventional level-shifters between the domains or multiple power supplies within each domain. This interface circuit uses a synchronous set and feedback reset protocol which provides level-shifting and synchronization of all signals between the domains, from a wide range of voltage-supplies and clock frequencies. Overall, synchronizer circuits can tolerate variations to a greater extent by employing the wagging technique or using a MADAC latch, while MUTEX tolerance can suffice with small circuit modifications. Communication between MVD/MCD can be achieved by an asynchronous handshake without a need for adding level-shifters.The Saudi Arabian Embassy in London, Umm Al-Qura University, Saudi Arabi

Neuromorphic Learning towards Nano Second Precision

Temporal coding is one approach to representing information in spiking neural networks. An example of its application is the location of sounds by barn owls that requires especially precise temporal coding. Dependent upon the azimuthal angle, the arrival times of sound signals are shifted between both ears. In order to deter- mine these interaural time differences, the phase difference of the signals is measured. We implemented this biologically inspired network on a neuromorphic hardware system and demonstrate spike-timing dependent plasticity on an analog, highly accelerated hardware substrate. Our neuromorphic implementation enables the resolution of time differences of less than 50 ns. On-chip Hebbian learning mechanisms select inputs from a pool of neurons which code for the same sound frequency. Hence, noise caused by different synaptic delays across these inputs is reduced. Furthermore, learning compensates for variations on neuronal and synaptic parameters caused by device mismatch intrinsic to the neuromorphic substrate.Comment: 7 pages, 7 figures, presented at IJCNN 2013 in Dallas, TX, USA. IJCNN 2013. Corrected version with updated STDP curves IJCNN 201

Synthetic in vitro transcriptional oscillators

The construction of synthetic biochemical circuits from simple components illuminates how complex behaviors can arise in chemistry and builds a foundation for future biological technologies. A simplified analog of genetic regulatory networks, in vitro transcriptional circuits, provides a modular platform for the systematic construction of arbitrary circuits and requires only two essential enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H, to produce and degrade RNA signals. In this study, we design and experimentally demonstrate three transcriptional oscillators in vitro. First, a negative feedback oscillator comprising two switches, regulated by excitatory and inhibitory RNA signals, showed up to five complete cycles. To demonstrate modularity and to explore the design space further, a positive-feedback loop was added that modulates and extends the oscillatory regime. Finally, a three-switch ring oscillator was constructed and analyzed. Mathematical modeling guided the design process, identified experimental conditions likely to yield oscillations, and explained the system's robust response to interference by short degradation products. Synthetic transcriptional oscillators could prove valuable for systematic exploration of biochemical circuit design principles and for controlling nanoscale devices and orchestrating processes within artificial cells

Utilising noise to improve an interictal spike detector

Accepted versio

Stochastic timing in gene expression for simple regulatory strategies

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to reach in a precise time a threshold level of expression that triggers a specific downstream process. However, gene expression is subject to stochastic fluctuations, naturally inducing an uncertainty in this threshold-crossing time with potential consequences on biological functions and phenotypes. Here, we consider such "timing fluctuations", and we ask how they can be controlled. Our analytical estimates and simulations show that, for an induced gene, timing variability is minimal if the threshold level of expression is approximately half of the steady-state level. Timing fuctuations can be reduced by increasing the transcription rate, while they are insensitive to the translation rate. In presence of self-regulatory strategies, we show that self-repression reduces timing noise for threshold levels that have to be reached quickly, while selfactivation is optimal at long times. These results lay a framework for understanding stochasticity of endogenous systems such as the cell cycle, as well as for the design of synthetic trigger circuits.Comment: 10 pages, 5 figure

Synthesis of Biological and Mathematical Methods for Gene Network Control

abstract: Synthetic biology is an emerging field which melds genetics, molecular biology, network theory, and mathematical systems to understand, build, and predict gene network behavior. As an engineering discipline, developing a mathematical understanding of the genetic circuits being studied is of fundamental importance. In this dissertation, mathematical concepts for understanding, predicting, and controlling gene transcriptional networks are presented and applied to two synthetic gene network contexts. First, this engineering approach is used to improve the function of the guide ribonucleic acid (gRNA)-targeted, dCas9-regulated transcriptional cascades through analysis and targeted modification of the RNA transcript. In so doing, a fluorescent guide RNA (fgRNA) is developed to more clearly observe gRNA dynamics and aid design. It is shown that through careful optimization, RNA Polymerase II (Pol II) driven gRNA transcripts can be strong enough to exhibit measurable cascading behavior, previously only shown in RNA Polymerase III (Pol III) circuits. Second, inherent gene expression noise is used to achieve precise fractional differentiation of a population. Mathematical methods are employed to predict and understand the observed behavior, and metrics for analyzing and quantifying similar differentiation kinetics are presented. Through careful mathematical analysis and simulation, coupled with experimental data, two methods for achieving ratio control are presented, with the optimal schema for any application being dependent on the noisiness of the system under study. Together, these studies push the boundaries of gene network control, with potential applications in stem cell differentiation, therapeutics, and bio-production.Dissertation/ThesisDoctoral Dissertation Biomedical Engineering 201