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Researchers develop all-optical approach to pumping chip-based nanolasers

Researchers have developed a new all-optical method for driving multiple highly dense nanolaser arrays. The approach could enable chip-based optical communication links that process and move data faster than today’s electronic-based devices.

“The development of optical interconnects equipped with high-density nanolasers would improve information processing in the that move information across the internet,” said research team leader Myung-Ki Kim from Korea University.

“This could allow streaming of ultra-high-definition movies, enable larger-scale interactive online encounters and games, accelerate the expansion of the Internet of Things and provide the fast connectivity needed for big data analytics.”

Record-breaking chip can transmit entire internet’s traffic per second

The speed record for data transmission using a single light source and optical chip has been shattered once again. Engineers have transmitted data at a blistering rate of 1.84 petabits per second (Pbit/s), almost twice the global internet traffic per second.

It’s hard to overstate just how fast 1.84 Pbit/s really is. Your home internet is probably getting a few hundred megabits per second, or if you’re really lucky, you might be on a 1-gigabit or even 10-gigabit connection – but 1 petabit is a million gigabits. It’s more than 20 times faster than ESnet6, the upcoming upgrade to the scientific network used by the likes of NASA.

Even more impressive is the fact this new speed record was set using a single light source and a single optical chip. An infrared laser is beamed into a chip called a frequency comb that splits the light into hundreds of different frequencies, or colors. Data can then be encoded into the light by modulating the amplitude, phase and polarization of each of these frequencies, before recombining them into one beam and transmitting it through optical fiber.

Scientists create living smartwatch powered by slime mold

Devices such as cellphones, laptops and smartwatches are constant companions for most people, spending days and nights in their pocket, on their wrist, or otherwise close at hand.

But when these technologies break down or a newer model hits stores, many people are quick to toss out or replace their device without a second thought. This disposability leads to rising levels of electronic waste—the fastest-growing category of waste, with 40 million tons generated each year.

University of Chicago scientists Jasmine Lu and Pedro Lopes wondered if they could change that fickle relationship by bringing devices to life—literally.

Brain Implants are Here: Blackrock’s Neuroport & Synchron’s Stentrode

Neurotechnology and Brain-Computer Interfaces are advancing at a rapid pace and may soon be a life-changing technology for those with limited mobility and/or paralysis. There are already two brain implants, Blackrock Neurotech’s NeuroPort and Synchron’s Stentrode, that have been approved to start clinical trials under an Investigational Device Exemption. In this video, we compare these devices on the merits of safety, device specifications, and capability.

Thanks to Blackrock Neurotech for sponsoring this video. The opinions expressed in this video are that of The BCI Guys and should be taken as such.

——–ABOUT US:——-

Harrison and Colin (The BCI Guys) are neurotech researchers and entrepreneurs dedicated to creating a brain-controlled future! Neurotechnology and brain-computer interfaces are devices that allow users to control machines with their thoughts and interact with technology in new ways. This revolutionary technology will change life as we know it, and soon will be as common as the touchscreen on your smartphone. Join us in learning about the brain-controlled future!

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Particles of light may create fluid flow, data-theory comparison suggests

A new computational analysis by theorists at the U.S. Department of Energy’s Brookhaven National Laboratory and Wayne State University supports the idea that photons (a.k.a. particles of light) colliding with heavy ions can create a fluid of “strongly interacting” particles. In a paper just published in Physical Review Letters, they show that calculations describing such a system match up with data collected by the ATLAS detector at Europe’s Large Hadron Collider (LHC).

As the paper explains, the calculations are based on the hydrodynamic particle flow seen in head-on collisions of various types of ions at both the LHC and the Relativistic Heavy Ion Collider (RHIC), a DOE Office of Science user facility for research at Brookhaven Lab. With only modest changes, these calculations also describe seen in near-miss collisions, where that form a cloud around the speeding ions collide with the ions in the opposite beam.

“The upshot is that using the same framework we use to describe -lead and proton-lead collisions, we can describe the data of these ultra-peripheral collisions where we have a photon colliding with a lead nucleus,” said Brookhaven Lab theorist Bjoern Schenke, a co-author of the paper. “That tells you there’s a possibility that in these photon-ion collisions, we create a small dense strongly interacting medium that is well described by hydrodynamics—just like in the larger systems.”

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

Year 2018 😗


State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10% of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Modern neuroscience has established numerical simulation as a third pillar supporting the investigation of the dynamics and function of neuronal networks, next to experimental and theoretical approaches. Simulation software reflects the diversity of modern neuroscientific research with tools ranging from the molecular scale to investigate processes at individual synapses (Wils and De Schutter, 2009) to whole-brain simulations at the population level that can be directly related to clinical measures (Sanz Leon et al., 2013). Most neuronal network simulation software, however, is based on the hypothesis that the main processes of brain function can be captured at the level of individual nerve cells and their interactions through electrical pulses. Since these pulses show little variation in shape, it is generally believed that they convey information only through their timing or rate of occurrence.