Lifeboat Foundation

Circa 2016 face_with_colon_three

The Deutsche Physikalische Gesellschaft (DPG) with a tradition extending back to 1,845 is the largest physical society in the world with more than 61,000 members. The DPG sees itself as the forum and mouthpiece for physics and is a non-profit organisation that does not pursue financial interests. It supports the sharing of ideas and thoughts within the scientific community, fosters physics teaching and would also like to open a window to physics for all those with a healthy curiosity.

Did you know there’s a silent war going on inside your home? Alternating current (AC) electricity comes in from the grid, but many of your appliances and lighting run on direct current (DC). Every time you plug in a TV, computer or cell phone charger, power must be individually converted from AC to DC — a costly and inefficient process. Purdue University researchers have proposed a solution to the problem by retrofitting an entire house to run on its own efficient DC-powered nano-grid.

The project to transform a 1920s-era West Lafayette home into the DC Nanogrid House began in 2017 under the direction of Eckhard Groll, the William E. and Florence E. Perry Head of Mechanical Engineering, and member of Purdue’s Center for High Performance Buildings. “We wanted to take a normal house and completely retrofit it with DC appliances and DC architecture,” Groll said. “To my knowledge, no other existing project has pursued an experimental demonstration of energy consumption improvements using DC power in a residential setting as extensively as we have.”

A new optical device measures photon indistinguishability—an important property for future light-based quantum computers.

Photons can be used to perform complex computations, but they must be identical or close to identical. A new device can determine the extent to which several photons emitted by a source are indistinguishable [1]. Previous methods only gave a rough estimate of the indistinguishability, but the new method offers a precise measurement. The device—which is essentially an arrangement of interconnected waveguides—could work as a diagnostic tool in a quantum optics laboratory.

In optical quantum computing, sequences of photons are made to interact with each other in complex optical circuits (see Synopsis: Quantum Computers Approach Milestone for Boson Sampling). For these computations to work, the photons must have the same frequency, the same polarization, and the same time of arrival in the device. Researchers can easily check if two photons are indistinguishable by sending them through a type of interferometer in which two waveguides—one for each photon—come close enough that one photon can hop into the neighboring waveguide. If the two photons are perfectly indistinguishable, then they always end up together in the same waveguide.

so-called qubits, to perform computations much faster than any classical computer ever could.

While multiple frontrunner startups have explored various technology platforms, from superconducting qubits and ion trap systems to diamond-based quantum accelerators, scaling the number of qubits from a few dozen to hundreds, thousands, and eventually millions of qubits has remained notoriously difficult. But this might change with photonic quantum computing.

The startup ORCA Computing builds photonic quantum computers that use photons, the fundamental particles of light, as qubits. Using quantum memories and established telecommunications technology, it can scale its devices more easily and integrate with existing computing infrastructure e.g. in data centers. Based on the core memory technology developed by Kris Kaczmarek, ORCA was officially co-founded by Ian Walmsley, Richard Murray, Josh Nunn, and Cristina Escoda in Oxford in the fall of 2019. This summer 2022, it has raised a $15M Series A led by Octopus Ventures and joined by Oxford Science Enterprises, Quantonation, and Verve Ventures, with additional, project-based funding provided by Innovate UK. Previous investors also include Atmos Ventures and Creative Destruction Lab.

Neural Radiance Fields (NeRF) were first developed, greatly enhancing the quality of new vision synthesis. It was first suggested as a way to rebuild a static picture using a series of posed photographs. However, it has been swiftly expanded to include dynamic and uncalibrated scenarios. With the assistance of sizable controlled datasets, recent work additionally concentrate on animating these human radiance field models, thereby broadening the application domain of radiance-field-based modeling to provide augmented reality experiences. In this study, They are focused on the case when just one video is given. They aim to rebuild the human and static scene models and enable unique posture rendering of the person without the need for pricey multi-camera setups or manual annotations.

Neural Actor can create inventive human poses, but it needs several films. Even with the most recent improvements in NeRF techniques, this is far from a simple task. The NeRF models must be trained using many cameras, constant lighting and exposure, transparent backgrounds, and precise human geometry. According to the table below, HyperNeRF cannot be controlled by human postures but instead creates a dynamic scene based on a single video. ST-NeRF uses many cameras to rebuild each person using a time-dependent NeRF model, although the editing is only done to change the bounding box. HumanNeRF creates a human model from a single video with masks that have been carefully annotated; however, it does not demonstrate generalization to novel postures.

With a model trained on a single video, Vid2Actor can produce new human poses, but it cannot model the surroundings. They solve these issues by proposing NeuMan, a system that can create unique human stances and novel viewpoints while reconstructing the person and the scene from a single in-the-wild video. Figure 1’s high-quality pose-driven rendering is made possible by NeuMan, a cutting-edge framework for training NeRF models for both the human and the scene. They first estimate the camera poses, the sparse scene model, the depth maps, the human stance, the human form, and the human masks from a moving camera’s video.

Synopsis: How can we think rigorously about the far future, and use this to guide near-term projects? In this talk I will outline my “grand futures” project of mapping the limits of what advanced civilizations can achieve – in terms of survival, expanding in space, computation, mastery over matter and energy, and so on – and how this may interact with different theories about what truly has value.

For some fun background reading, see ‘What is the upper limit of value?‘which Anders Sandberg co-authored with David Manheim.

Continue reading “Anders Sandberg — Grand Futures — Thinking Truly Long Term” »

Computers could transmit highly confidential data even without internet, Wi-Fi or Bluetooth by using their speakers to transmit ultrasonic noise that vibrates nearby smartphones.

Some of us, when we hear the word quantum (plural quanta, from the German word Quanten), might think of health supplements, a sports car, or even the television show Quantum Leap. More recently, in Marvel Studios movies such as Ant-Man, Doctor Strange, and Avengers: Endgame, “the quantum realm” is presented where time flows differently from our ordinary reality and the Avengers may use the subatomic world “to go back in time”, a world that “is smaller than a single atom” (Woodward, 2019, para.20)

We might have also seen or known the meaning of words such as quantum mechanics, quantum computing, and quantum entanglement, but what is a quantum and how does it relate to our ordinary realm?

A quantum is a word that refers to “how much”; it is a specific amount. For example, if the speed of your car happens to be quantized in increments of 10 mph, then as you accelerate your car from 10 mph, the speed will jump to 20 mph, without passing through any speed between 10 mph and 20 mph. A speed of 12 mph or 19 mph is excluded because the speed of your car can only exist in those increments of 10 mph.

Oxford quantum physicist Nikita Gourianov tore into the quantum computing industry this week, comparing the “fanfare” around the tech to a financial bubble in a searing commentary piece for the Financial Times.

In other words, he wrote, it’s far more hype than substance.

It’s a scathing, but also perhaps insightful, analysis of a burgeoning field that, at the very least, still has a lot to prove.