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Category: computing – Page 438
Researchers at Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed (AQT) demonstrated that an experimental method known as randomized compiling (RC) can dramatically reduce error rates in quantum algorithms and lead to more accurate and stable quantum computations. No longer just a theoretical concept for quantum computing, the multidisciplinary team’s breakthrough experimental results are published in Physical Review X.
The experiments at AQT were performed on a four-qubit superconducting quantum processor. The researchers demonstrated that RC can suppress one of the most severe types of errors in quantum computers: coherent errors.
Akel Hashim, AQT researcher, involved in the experimental breakthrough and a graduate student at the University of California, Berkeley explained: “We can perform quantum computations in this era of noisy intermediate-scale quantum (NISQ) computing, but these are very noisy, prone to errors from many different sources, and don’t last very long due to the decoherence—that is, information loss—of our qubits.”
It is the highest resolution sensor of its type ever made.
Canon has developed an image sensor that is capable of capturing high-quality color photography even in the dark. The company says that it will be able to shoot clear photos even in situations where nothing is visible to the naked eye.
In a report from Nikkei, Canon says that it has developed a new type of light-receiving element called a single photon avalanche diode (SPAD) and is implementing it on a CMOS sensor. SPAD photodetector technology on its own isn’t new, and has been in use since the 1970s. However, Canon has managed to create a sensor with 3.2 million pixels, which it says is more than three times the resolution of conventional SPADs and makes it the highest-resolution sensor of its type ever made.
The sensor is designed to replace, or at least provide an alternative to, infrared night vision cameras. Infrared is useful for recognizing shapes and providing sight in the dark, but is not capable of recognizing colors. On the flipside, cameras that can see color in the dark only do so by leveraging high ISOs, which can work to a certain point but eventually lead to extremely noisy images in levels of extreme darkness.
A bigger deal than computational photography?
Samsung and Canon have both announced new camera sensors that are both innovative in very different ways. But how exciting are they?
Rare earth elements are essential for many of our modern day technologies. It’s used in rechargeable batteries, phones, fiber optics, wind turbines, televisions, dvd players and many others.
Some countries control majority of supply and use this as a means to pressure other countries.
It’s expected to become one of the issues at stake in the ongoing trade war between the #US and #China. Rare earth elements are crucial to manufacturing phones, computers and wind turbines. China currently controls 90 percent of their production, but the US is also determined to extract these precious #minerals and has just reopened a rare earth elements mine in California. Our France 2 colleagues report, with FRANCE 24’s James Vasina.
Microsoft has announced a new DirectX12 API for Windows which will offer a new way for apps to efficiently encode video using the GPU.
The Video Encode API is available to 3rd party apps and is native to Windows 11, and can efficiently encode video in the H264 and HEVC formats.
Microsoft says it offers a considerable number of configurable parameters are exposed by this API for the user to tweak different aspects of the encoding process and make them fit best for their scenarios such as: custom slices partitioning scheme, active (i.e. CBR, VBR, QBVR) and passive (Absolute/Delta custom QP maps) rate control configuration modes, custom codec encoding tools usage, custom codec block and transform sizes, motion vector precision limit, explicit usage of intra-refresh sessions, dynamic reconfiguration of video stream resolution/rate control/slices partitioning and more.
The future of computing may be analog.
The digital design of our everyday computers is good for reading email and gaming, but today’s problem-solving computers are working with vast amounts of data. The ability to both store and process this information can lead to performance bottlenecks due to the way computers are built.
The next computer revolution might be a new kind of hardware, called processing-in-memory (PIM), an emerging computing paradigm that merges the memory and processing unit and does its computations using the physical properties of the machine—no 1s or 0s needed to do the processing digitally.
Georgia Tech Research Institute (GTRI) scientists announced they’ve made significant advances toward creating a chip that can grow DNA strands in a tightly packed, ultra-dense format for large storage capacity at very low cost.
Police departments all over the world are warming up to electric vehicles and their findings after using EVs on a daily basis are encouraging.
Earlier this year, the Westport Police Department in Connecticut shared some interesting conclusions after buying a Tesla Model 3 in December 2019. They found the EV to be not only cheaper to buy than the Ford Explorer SUV they typically use but also more affordable to modify, maintain, and run, leading to savings of about $6,000 a year.
Now, new data is coming in from the UK, where several Tesla Model 3s custom built by Tesla UK as patrol cars have completed nine months of initial trials with the police. Max Toozs-Hobson, account manager and emergency services lead at Tesla, shared the findings on LinkedIn and said the Model 3 police cars have been “getting some great results.”
By Stina Andersson and Ellinor Wanzambi
Researchers have been working on quantum algorithms since physicists first proposed using principles of quantum physics to simulate nature decades. One important component in many quantum algorithms is quantum walks, which are the quantum equivalent of the classical Markov chain, i.e., a random walk without memory. Quantum walks are used in algorithms in areas such as searching, node ranking in networks, and element distinctness.
Consider the graph in Figure 1 and imagine that we randomly want to move between nodes A, B, C, and D in the graph. We can only move between nodes that are connected by an edge, and each edge has an associated probability that decides how likely we are to move to the connected node. This is a random walk. In this article, we are working only with Markov chains, also called the memory-less random walks, meaning that the probabilities are independent of the previous steps. For example, the probabilities of arriving at node A are the same no matter if we got there from node B or node D.