Lifeboat Foundation

Though not a new technology, new advancements have progressed this field significantly.

An ordered pattern of atomic spins with possible uses in computing can become more ordered if shaken at the right frequency.

New research has established a reversible framework for quantum entanglement, aligning it with the principles of thermodynamics and paving the way for improved manipulation and understanding of quantum resources.

Bartosz Regula from the RIKEN Center for Quantum Computing and Ludovico Lami from the University of Amsterdam have demonstrated through probabilistic calculations the existence of an “entropy” rule for quantum entanglement. This discovery could enhance our understanding of quantum entanglement, a crucial resource underpinning the potential of future quantum computers. Although quantum entanglement has been a research focus in quantum information science for decades, optimal methods for its effective utilization remain largely unknown.

The second law of thermodynamics, which says that a system can never move to a state with lower “entropy”, or order, is one of the most fundamental laws of nature and lies at the very heart of physics. It is what creates the “arrow of time,” and tells us the remarkable fact that the dynamics of general physical systems, even extremely complex ones such as gases or black holes, are encapsulated by a single function, its “entropy.”

New research has revealed that the lag observed in organic electrochemical transistors (OECTs) when switched on is due to a two-step activation process, providing crucial insights for designing more effective and customizable OECTs for various technological and biological applications.

Researchers who want to bridge the divide between biology and technology spend a lot of time thinking about translating between the two different “languages” of those realms.

“Our digital technology operates through a series of electronic on-off switches that control the flow of current and voltage,” said Rajiv Giridharagopal, a research scientist at the University of Washington. “But our bodies operate on chemistry. In our brains, neurons propagate signals electrochemically, by moving ions — charged atoms or molecules — not electrons.”

Nanotransfection is very useful and could be used as a way to heal oneself on a smartphone in one touch with cell reprogramming and much more like gene transfer.

Tissue nanotransfection (TNT), a cutting-edge technique of in vivo gene therapy, has gained substantial attention in various applications ranging from in vivo tissue reprogramming in regenerative medicine, and wound healing to cancer treatment. This technique harnesses the advancements in the semiconductor processes, facilitating the integration of conventional transdermal gene delivery methods—nanoelectroporation and microneedle technologies. TNT silicon chips have demonstrated considerable promise in reprogramming fibroblast cells of skin in vivo into vascular or neural cells in preclinical studies to assist in the recovery of injured limbs and damaged brain tissue. More recently, the application of TNT chips has been extended to the area of exosomes, which are vital for intracellular communication to track their functionality during the wound healing process.

Trained on 1.5 million whole-slide images from 100,000 patients, a pathology foundation model is shown to improve performance of specialized models in detection of rare cancers.

Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Jue Zhang, Qingwei Lin, Gong Cheng, Dongmei Zhang, Saravan Rajmohan, Qi Zhang Nanjing University & Microsoft 2024 https://huggingface.co/papers/2407.

- the vision of autonomic computing…

Join the discussion on this paper page.

Chip design can rapidly and efficiently test for multiple pathogens simultaneously, potentially reducing foodborne illness. Researchers have developed a new method for detecting foodborne pathogens that is faster, cheaper, and more effective than existing methods. Their microfluidic chip uses light to detect multiple types of pathogens simultaneously and is created using 3D printing, making it easy to fabricate in large amounts and modify to target specific pathogens. The researchers hope their technique can improve screening processes and keep contaminated food out of the hands of consumers.

Every so often, a food product is recalled because of some sort of contamination. For consumers of such products, a recall can trigger doubt in the safety and reliability of what they eat and drink. In many cases, a recall will come too late to keep some people from getting ill.

In spite of the food industry’s efforts to fight pathogens, products are still contaminated and people still get sick. Much of the problem stems from the tools available to screen for harmful pathogens, which are often not effective enough at protecting the public.

Implementing error correction in a quantum computer requires putting together a lot of different things. Of course, you want to start with good physical qubits that have as low a physical error rate that you can achieve. You want to add in an error correction algorithm, like the surface code, color code, q-LDPC, or others that can be implemented in your architecture, and you need a fast real time error decoder that can look at the circuit output and very quickly determine what the error is so it can be corrected. The error decoder portion doesn’t get as much attention in the media as the other things, but it is a very critical portion of the solution. Riverlane is concentrating on providing products for this with a series of solutions they name Deltaflow which consists of both a classical ASIC chip along with software. The Deltaflow solution consists of a powerful error decoding layer for identifying errors and sending back corrective instructions, a universal interface that communicates with the computer;s control system, and a orchestration layer for coordinating activities.

Riverlane has released its Deltaflow Error Correction Stack Roadmap that show yearly updates to the technology to support an increase in the number of QuOps (error free Quantum Operations) by 10X every year. We reported last year on a chip called DD1 that is part of their Deltaflow 1 solution that is capable of supporting 1,000 QuOps using a surface code error correction algorithm. And now, Riverlane is defining solutions that will achieve 10,000 QuOps with Deltaflow 2 later this year, 100,000 QuOps with Deltaflow 3 in 2025, and 1,000,000 QuOps, also called MegaQuops in 2026, with their Deltaflow Mega solution.

One characteristic that Riverlane is emphasizing in these designs is to perform the decoding in real time in order to keep the latencies low. Although it is fine for an academic paper to send the ancilla data off to a classical computer and have it determine the error, it might take milliseconds for the operation to complete. That won’t cut it in a production environment running real jobs. With their Deltaflow chips, these operations can be performed at megahertz rates and Riverlane has implemented techniques such as a streaming, sliding window, and parallized decoding approaches to increase the throughput of the decoder chips as much as possible. In future chips they will be implementing “fast logic” capabilities for Clifford gates using approaches including lattice surgery and transversal CZ gates.