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Arquivo para a ‘circuits’ Categoria

Qutrit, teleportation and philosophy

12 Aug

Two teams independently managed to teleport quantum particles called QuTrit (quantum trit), with a few days difference that can be said to be simultaneous.
Both are awaiting review of the peer review process for their publications to come out and receive “invention” credits.
A qutrit is similar to the qubit (the well-known quantum bit), except that instead of binary beings (0 and 1) they are classic ternary systems, which because they have the possibility of a third state, say 0, 1 and 2 can transform more information than qubit.
This surpasses what in philosophy, especially the idealist in which we can have only A and B, and there can be no contradiction, in this case not exactly contradiction, but a third state.

The communication system used is the HD-BSM (High Density Bell State Measurement).

Although quantum systems are much less noisy (subject to change by the environment) than digital electronic systems, qutrit are even less noisy and thus more reliable.
Teleportation means that information goes from point to point without a “medium” meaning that it will be less subject to interception and thus more reliable in terms of quantum cryptography.
The two groups claiming to have a healthy scientific rivalry are the group led by physicist Guang-Can Guo of researchers from the University of Science and Technology of China, and the other led by Anton Zeilinger of the Austrian Academy of Sciences, and there is already a version in analysis of the articles on the subject, the so-called pre-print, and were published respectively on April 28 (preprint) and June 24 (preprint).

 

Industrial scale qubit chip

21 May

The quantum chip (qbit or quBit) can now go on an industrial scale, a team of researchers from Denmark and the US announced last month that the technology is ready.
The problem was to scale up in such a way that computers could use chips, so far the qubits’ quantum computing was not robust enough to operate in noisy environments on a full computer.
Another problem was scale production, out of specialized laboratory and produced in conventional factories, they had to work with the semiconductors and normal circuit boards, with a combination of the semiconductors of conventional chips with aluminum and aluminum arsenide, the part industrial revolution is solved.
The team is led by Professor Antonio Fornieri, who has built a quantum memory chip and promises that quantum computers can now be produced in scale. the most resilient qubits by a combination of a semiconductor, the Indian arsenide, with a superconductor, aluminum, in a planar device, called the so-called Josephson junction, capable of treating Majorana quasi-particles.
Majorana quasiparticles are zero-mode fermions, which emerge on the surface of topological superconductors, which function as fault-tolerant and noise-free qubits.
The teacher Fornieri said: “Our prototype is a significant first step in using this kind of system to make quantum bits that are protected against disturbances.” “We still need some adjustments at the moment – we can improve design and materials, but it’s a potentially perfect structure.”.
The article was published in Nature and is authored by Fornieri and his team: Antonio Fornieri, Alexander M. Whiticar, F. Setiawan, Elias Portolés, Asbjørn CC Drachmann, Anna Keselman, Sergei Gronin, Candice Thomas, Tian Wang, Ray Kallaher, Geoffrey C. Gardner, Erez Berg, Michael J. Manfra, Ady Stern, Charles M. Marcus, Fabrizio Nichele, Evidence of Topological Superconductivity in Planar Josephson Junctions. Nature Vol .: 569, pages 89-92.
The following video explains the who Qubits working:

 

Deep Mind Advanced Project

20 Sep

Projects that attempted to simulate brain synapses, communication between neurons, were formerly called neural or neural networks, and had a large development and applications.
Gradually these projects were moving to studies of the mind and the code was being directed to Machine Learning that now using neural networks happened to be called deep learning, an advanced project is Google Brain.
Basically it is a system for the creation and training of neural networks that detect and decipher patterns and correlations in applied systems, although analogous, only imitate the way humans learn and reason about certain patterns.
Deep Learning is a branch of Machine Learning that operates a set of algorithms used to model data in a deep graph (complex networks) with several layers of processing, and that, unlike the training of neural networks, operate with both linear and non-linear patterns .
One platform that works with this concept is Tensor Flow, originated from an earlier project called DistBelief, is now an open source system, released by the Apache 2.0 team in November 2015, Google Brain uses this platform.
In May 2016, Google announced to this system the TPU (Tensor Processing Unit), a programmable artificial intelligence program accelerator with high transfer rate ability for low precision arithmetic (8 bts), which runs models and does not more training as neural networks did, a Deep Compute Engine stage begins.
The second step of this process in Google Compute Engine, the second generation of TPUs achieves up to 180 teraflops (10 ^ 12 floating point operations), and mounted in clusters of 64 TPUs, work up to 11.5 petaflops. 

 

Material can help quantum chips

08 Aug

Researchers at the University of Central Florida (UCF) have discovered a type of material that could be used as a “building block” of quantum chips, consisting of hafnium, tellurium and phosphorus, Hf2Te2P.
According to UFC researcher Madabe Neupane, “Our discovery takes us one step closer to the application of quantum materials and helps us gain a deeper understanding of the interactions between various quantum phases.”
The material has more than one electron pattern that develops within its electronic structure, giving it a range of quantum properties. Neupane says that this material will increase computing power for large volumes of data on new devices and will considerably reduce the amount of power needed for power electronics.
The discovery has already attracted companies that are investing in research, Microsoft for example invested in its project called Station Q, the laboratory that is dedicated to the field of topological quantum computing, and Google has teamed up with NASA in an investment that works with quantum computing and artificial intelligence.
Because quantum phenomena need to be better understood so that electronics are totally replaced by photonics and quantum computation, computational scenario changes tend to change rapidly and continuously.
The discovery of Neupane’s lab is published in Nature Communications, and is a big step forward for this change of scenario.

 

Personal assistants arrive at the office

27 Jun

In some doctors’ offices already use Google Home, Assistant and Translate, in addition to the indispensable Agend, whoever starts using it does not leave it any more, it avoids scheduling conflicts and warns forgetfulness, but the idea now is to integrate these environments into “Medical Digital Assit “, developed by the doctor Steven Lin of Stanford University made next to the CNBC.

According to CNBC site, the project is in the health group of the daring Google Brain project, part of Google’s division in artificial intelligence, having as its “ambitious goal” to deploy external health care trials before the end of 2018.

The main goal, however, is to assist physicians in their reports and medicals records, before beginning the studies the Stanford School of Medicine made a survey where they found that doctors lose 6 to 11 hours of their daily work to document the histories patients’ clinics, so it is often easier questions, but patient responses may be inaccurate or ignore relevant data.

The problem of accuracy is key, the CNBC website explains the difference between an interpretation and “hipo” or “hyper” can be fatal, hypoglycemia is exactly the opposite of hypoglycemia if the doctor does not check this carefully.

The first phase of this study is expected to conclude in August, Lin said both parties plan to renew collaboration for the second phase for at least a year.

Microsoft and Amazon are also reportedly developing systems similar to artificial intelligence, and the main focus remains on developing clinical reports

 

Intel Hardware Insecurity

15 Jan

The storage of data had 3 levels: the external memory (HDs), the memory aMemoryKernelof the computer (the RAMs) and the many internal ones before called Register and today is the Kernel Memory, are in the kernel of the computer and are the faster, but can also be windows for data theft, today there is a fourth level which is the external stores in clouds, computing center scattered around the world selling these stores.
An error in the production of Intel’s chips, which make up almost 90 percent of the world’s computer chips (smartphones are very different), has just been caught in a design flaw that gives data vulnerability.
AMD, a competitor of Intel, took the opportunity to point out that its Kernel memory (computer core memories) are unaffected by hacker attacks, and does not allow access to passwords and other sensitive machine data, through which data from a computer can be stolen.
According to Paul Kocher, president of security company Rambus for the New York Times, the problem could be bigger if access was in the clouds, where large parts of the data are already being stored today, this is because the sharing of machines this sharing of core memories) can be made, even if considering the security protocol that avoids access to other memory levels.
Security issues with the giants Amazon, Microsoft and Google, in addition to the chipmaker Intel may rock the market, in addition to AMD other Eastern competitors should be on the lookout, we alerted to the key problem.

 

Autonomous robots?

03 Oct

Autonomous robots are a denomination for those who are within the environmentalautonomousRobot limits, can achieve the desired goals (by humans or by tasks organized in an algorithm) in these unstructured environments without a human help, by this they are in certain levels.
For example, within a factory where mechanical tasks are performed, to avoid accidents, their geographic space is limited and deficient to detect the defect that can be fulfilled by a forged task, since a space robot should have fewer limits and be the most autonomous autonomous, for being without possibility of direct human action and having communication difficulties due to a distance.
The project called SWARM, funded by the European Union and we have already made a post, now has the first multi-robot system of autonomous assembly that has sensory-motor coordination observing similar robots around them, they will vary in shape and height in white according to a task and / or work environment.
A central “cerebral” central coordinating system, all of us, through a system called MNS (Mergeable Nervous System), and thus are reconfigured observing different capacities but combined by a single central controller.
They can also split up and perform self-repair tasks, eliminating defective body parts, including a brain unit with some defect, of course, one can define which are defeats and self-repairs.
In autonomous robots, learning and strategy according to the environment, what you can do with your autonomy increases, but for what you can print, the article is still not the case.
The current model has 10 units, and the authors point out without paper published in Nature Communications, claim that the Project is scalable, both in terms of computational resources for robotic control and time of reaction to stimulus, whithin the system.

 

How are cyber-brain searches?

02 Oct

There is a lot of research mapping the brains, and investigating aspects of how certain aPreSinapseEnfunctions work such as: motor function, vision, and in a very special way the
Cognitive Neuroscience studies the cognitive ability (knowledge) of a person, such as reasoning, memory and learning.
A recent study by the Universities of Exeter and Oxford of the United Kingdom, in conjunction with the University of Munster in Germany, has developed photonic microchips that immitate the synapses of the human brain using light and no longer electricity, as in other chips.
The chips is manufactured using the frequency phenomenon, but from the combined phase shift in the integrated photonic circuits designed for this, with synapses can operate at 1,000 times the speed of humans, which does not mean they do the same.
The researchers say that it is a fundamental step in machines capable of functioning and in the way of thinking in a way similar to the brain since the photon is fast and low energy consumption.
David Wright told the University of Exeter website that the project addresses two important issues in electronic computing, both speed and efficiency and capacity problems in parallel processing, the fastest of now: ” not only by developing…new brain-like computer architectures, but also by working in the optical domain to leverage the huge speed and power advantages of the upcoming silicon photonics revolution “

On-chip photonic synapse by Zengguang Cheng, Carlos Rios, Wolfram Pernice, C David Wright and Harish Bhaskaran is published in Science Advances.

 

What they say of the iPhone 8 and plus

20 Sep

I do not know if they have said anything before, but I was able to read theaImagemIphone8 first comments yesterday from Hi Phone 8 and the plus model, Mathew Panzarino from TechCrunch highlights the camera “with augmented reality and computer vision emerging as competitors in the next big wave of development platforms, the camera system will be an [important] input mechanism, a communication system and a declaration of intent. ”

Another important technology site is Engadget, Chris Velazco wondered how ARKit-like apps would work and enjoyed the augmented reality experience and said that rendering virtual objects on physical planes made them “stick to surfaces better than similar Tango apps “.

Another strong site in the area is The Verge, Nilay Patel’s comment was: “Just like on Samsung, the iPhone’s images are now more saturated by default, although Apple says it’s still aiming for realism instead of saturated colors and smoothing the S8 “and said later that taking pictures with an iPhone 8, a Pixel XL, an S8 and an iPhone 7” in the automatic, and the iPhone 8 produced the most consistent and rich images of the group.

The novelty in the software was due to the feature Portrait Lighting, which allows light effects with the front camera, the battery lasts about 11 hours warns another review,

Lastly, but the most important tech site David Pierce of Wired said that “the phones are very good and impressive, and yet they are not the best Apple devices. The iPhone X represents the vision of the future of Apple, as well as Samsung, Essential, Huawei and many others. ”

It is expected much more and more from cameras and graphics treatment Apps, performance and memory seem to be important, but are getting in the background, TechCrunch site for example notes that “the A11 chip from Apple has a performance that is compatible with the Core i5 of MacBook Pro. ”

With the importance of graphics and image processing OLED screens of higher definition will be importante.

 

Unknown Stories of Computing

21 Aug

Charles Babbage built two machines called Analytical Engine and Diferential EngineMEMEX, these machines, their systematizations and thoughts would not have arrived until we were not working patiently Ada de Lovelace (1815-1852), daughter of Lord Byron who compiled and organized the work of this Pioneer, making it understandable to mathematicians of the time.

Later David Hilbert (1862-1943) listed 23 mathematical problems at the time without solutions, one of which was to organize an algebraic system in order to solve the problem computability problem by algorithms, Kurt Gödel thinking about this problem creates a paradox about Completeness of systems, stating that it can not prove having proof by an assertion within the system, then consistency problems weaken such systems.

Thus it was necessary that logic, besides being constructed with good properties, had consistency (no contradictions), completeness (any proposition would be either truth or false exclusively) and the systems were decidable (existence of a method allowing to establish if any formula whether the formula was true or false).

This latter property was called by Hilbert as the “entcheidungsproblem”, or problem of “decision”.

Alan Turing and Claude Shannon working on coding machines (for US government messages) and decoding (a machine called Enigma was captured from Hitler’s army), as both projects were secret, found in meals and work breaks as indicated The book by James Gleick and talk about the problem proposed by Hilbert and not solved by Gödel, a secret document proves this passage of Turing, who was English, by Bell Laboratories, where he worked on deciphering the Enigma machine code.

Shannon at that time worked as a monitor at MIT in Vannevar Bush’s laboratory, who had proposed a “read” machine called MEMEX (it appeared in TIME magazine) was not a computer itself, but a machine to cross information from books.

Vannevar Bush suggested to Claude Shannon Boole’s Algebra..

Later using the model of the mathematician Alonzo Church that finalized the design of Alain Turing, and the call Turing Machine is actually based on Turing / Church model.
Norbert Wiener’s model were electronic models of feedback machines, although he founded Cybernetics, the idea was to create models for movements and turn them into problem-solving models, they were contemporary with Vannevar Bush of MIT