Lifeboat Foundation

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.

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Watch Part 2 over on Isaac Arthur’s channel.

Continue reading “Boltzmann Brains — Why The Universe is Most Likely a Simulation” »

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.

Yes, conceivably. And if/when we achieve the levels of technology necessary for simulation, the universe will become our playground.

Circa 2016 face_with_colon_three

A transistor laser (TL)^1,2,3, having the structure of a transistor with multi-quantum wells (MQWs) near its base region, bridges the functionality gap between lasers and transistors. From a TL, an electrical signal can be outputted simultaneously with a light signal by inputting one electrical signal, making it suitable for future high performance optoelectronic integrated device applications⁴. As a new kind of semiconductor laser or transistor, TLs have aroused many interests since its invention. For example, in 2006, the paper² reporting the first room temperature operation of TLs was voted as one of the five most important papers published by Applied Physics Letters in over 40 years⁵. Because of the transistor structure, many interesting characters have been demonstrated, including resonance free frequency response, large direct modulation band width⁶, voltage controlled mode of operation⁷, low relative intensity noise (RIN) close to the shot-noise limit⁸ and low 3rd order intermodulation distortion (IMD)⁹.

However, light emission for all the TLs reported up to now is produced at the expense of current gain. Taking npn TLs as an example, in the devices, electrons injected from the emitter into the base layer first recombine with holes radiatively before the left being collected by the collector⁴. The majority of the electrons are consumed by stimulated light emissions, leading to a current gain which is a lot lower than the gain of a traditional transistor. The common emitter (CE) mode current gain (collector current/base current) is lower than 5 for most, if not all, of the TLs studied, either experimentally^{1,2,3,6,7,8,9,10} or numerically^11,12,13. The low current gain may limit the performance of systems that use TLs. For example, it is much easier to integrate monolithically a heterojunction bipolar transistor (HBT) and a TL than to integrate an HBT with a laser diode (LD) because of the dual functionality of TLs. For such applications, a large current gain of TL (used as HBT) is desired for the amplification of electrical signal to drive the laser.

Continue reading “High current gain transistor laser” »

Organic electronic-based gas sensors hold great potential for portable healthcare-and environment-monitoring applications. It has recently been shown that introducing a porous structure into an organic semiconductor (OSC) film is an efficient way to improve the gas-sensing performance because it facilitates the interaction between the gaseous analyte and the active layer. Although several methods have been used to generate porous structures, the development of a robust approach that can facilely engineer the porous OSC film with a uniform pore pattern remains a challenge. Here, we demonstrate a robust approach to fabricate porous OSC films by using a femtosecond laser-processed porous dielectric layer template. With this laser-assisted strategy, various polymeric OSC layers with controllable pore size and well-defined pore patterns were achieved.

Circa 2021 face_with_colon_three

“Optical accelerator” devices could one day soon turbocharge tailored applications.

“You can think of curiosity as a kind of reward which the agent generates internally on its own, so that it can go explore more about its world,” Agrawal said. This internally generated reward signal is known in cognitive psychology as “intrinsic motivation.” The feeling you may have vicariously experienced while reading the game-play description above — an urge to reveal more of whatever’s waiting just out of sight, or just beyond your reach, just to see what happens — that’s intrinsic motivation.

Humans also respond to extrinsic motivations, which originate in the environment. Examples of these include everything from the salary you receive at work to a demand delivered at gunpoint. Computer scientists apply a similar approach called reinforcement learning to train their algorithms: The software gets “points” when it performs a desired task, while penalties follow unwanted behavior.