A femtosecond pulse generator is realized using an electro-optic time-lens system integrated on a lithium niobate photonic chip, capable of tunable repetition rates and wavelengths.
Category: computing – Page 412
Simulations Using a Quantum Computer Show the Technology’s Current Limits
Quantum circuits still can’t outperform classical ones when simulating molecules.
Quantum computers promise to directly simulate systems governed by quantum principles, such as molecules or materials, since the quantum bits themselves are quantum objects. Recent experiments have demonstrated the power of these devices when performing carefully chosen tasks. But a new study shows that for problems of real-world interest, such as calculating the energy states of a cluster of atoms, quantum simulations are no more accurate than those of classical computers [1]. The results offer a benchmark for judging how close quantum computers are to becoming useful tools for chemists and materials scientists.
Richard Feynman proposed the idea of quantum computers in 1982, suggesting they might be used to calculate the properties of quantum matter. Today, quantum processors are available with several hundred quantum bits (qubits), and some can, in principle, represent quantum states that are impossible to encode in any classical device. The 53-qubit Sycamore processor developed by Google has demonstrated the potential to perform calculations in a few days that would take many millennia on current classical computers [2]. But this “quantum advantage” is achieved only for selected computational tasks that play to these devices’ strengths. How well do such quantum computers fare for the sorts of everyday challenges that researchers studying molecules and materials actually wish to solve?
An on-chip time-lens generates ultrafast pulses
Femtosecond pulsed lasers—which emit light in ultrafast bursts lasting a millionth of a billionth of a second—are powerful tools used in a range of applications from medicine and manufacturing, to sensing and precision measurements of space and time. Today, these lasers are typically expensive table-top systems, which limits their use in applications that have size and power consumption restrictions.
An on-chip femtosecond pulse source would unlock new applications in quantum and optical computing, astronomy, optical communications and beyond. However, it’s been a challenge to integrate tunable and highly efficient pulsed lasers onto chips.
Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a high-performance, on-chip femtosecond pulse source using a tool that seems straight out of science fiction: a time lens.
Apple plans to source chips from Arizona plant by 2024
It’s diversifying from its initial reliance on Taiwan-made chips.
Apple is diversifying its supply chain away from Taiwan as it has plans to buy some of its chips from a factory in Arizona, company CEO Tim Cook said last month at an internal meeting in Germany, according to a report by Bloomberg News.
Manufacturing A-series and M-series processors
All of the firm’s current processors are sourced from factories in Taiwan. Although Apple currently designs its own chips, the Taiwan Semiconductor Manufacturing Company (TSMC) is responsible for manufacturing the A-series and M-series processors that power the ever popular iPhones and Mac computers.
Computational Creativity
As part of its quest to develop cognitive systems, IBM Research is exploring whether a computer can be creative by designing a machine that can create surprising yet flavorful recipe ideas no cookbook has ever thought of in order to enhance human creativity.
http://www.research.ibm.com/cognitive-computing/computational-creativity.shtml
Researchers develop a material that mimics how the brain stores information
Universitat Autònoma de Barcelona (UAB) researchers have developed a magnetic material capable of imitating the way the brain stores information. The material makes it possible to emulate the synapses of neurons and mimic, for the first time, the learning that occurs during deep sleep.
Neuromorphic computing is a new computing paradigm in which the behavior of the brain is emulated by mimicking the main synaptic functions of neurons. Among these functions is neuronal plasticity: the ability to store information or forget it depending on the duration and repetition of the electrical impulses that stimulate neurons, a plasticity that would be linked to learning and memory.
Among the materials that mimic neuron synapses, memresistive materials, ferroelectrics, phase change memory materials, topological insulators and, more recently, magneto-ionic materials stand out. In the latter, changes in the magnetic properties are induced by the displacement of ions within the material caused by the application of an electric field.
The unimon, a new qubit to boost quantum computers for useful applications
A group of scientists from Aalto University, IQM Quantum Computers, and VTT Technical Research Center have discovered a new superconducting qubit, the unimon, to increase the accuracy of quantum computations. The team has achieved the first quantum logic gates with unimons at 99.9% fidelity—a major milestone on the quest to build commercially useful quantum computers. This research was just published in the journal Nature Communications.
Of all the different approaches to build useful quantum computers, superconducting qubits are in the lead. However, the qubit designs and techniques currently used do not yet provide high enough performance for practical applications. In this noisy intermediate-scale quantum (NISQ) era, the complexity of the implementable quantum computations is mostly limited by errors in single-and two-qubit quantum gates. The quantum computations need to become more accurate to be useful.
“Our aim is to build quantum computers which deliver an advantage in solving real-world problems. Our announcement today is an important milestone for IQM, and a significant achievement to build better superconducting quantum computers,” said Professor Mikko Möttönen, joint Professor of Quantum Technology at Aalto University and VTT, and also a Co-Founder and Chief Scientist at IQM Quantum Computers, who was leading the research.
Boltzmann Brains — Why The Universe is Most Likely a Simulation
Start learning today with Brilliant! https://brilliant.org/upandatom.
Watch Part 2 over on Isaac Arthur’s channel.
https://www.youtube.com/channel/UCZFipeZtQM5CKUjx6grh54g.
If you’d like to know more about Boltzmann Brains, here are some informative papers:
https://arxiv.org/abs/hep-th/0208013
https://arxiv.org/abs/0704.2630
https://arxiv.org/abs/hep-th/0611271
https://arxiv.org/abs/hep-th/0611043
https://arxiv.org/abs/1708.00449
https://arxiv.org/abs/1702.
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Computer scientists succeed in solving algorithmic riddle from the 1950s
For more than half a century, researchers around the world have been struggling with an algorithmic problem known as “the single source shortest path problem.” The problem is essentially about how to devise a mathematical recipe that best finds the shortest route between a node and all other nodes in a network, where there may be connections with negative weights.
Sound complicated? Possibly. But in fact, this type of calculation is already used in a wide range of the apps and technologies that we depend upon for finding our ways around—as Google Maps guides us across landscapes and through cities, for example.
Now, researchers from the University of Copenhagen’s Department of Computer Science have succeeded in solving the single source shortest path problem, a riddle that has stumped researchers and experts for decades.