Lifeboat Foundation

Only theoretical now but someday this could lead to lag free and error free quantum computers.

Quantum gates built out of braid group elements form the building blocks of topological quantum computation. They have been extensively studied in SUk quantum group theories, a rich source of examples of non-Abelian anyons such as the Ising (k = 2), Fibonacci (k = 3) and Jones-Kauffman (k = 4) anyons. We show that the fusion spaces of these anyonic systems can be precisely mapped to the product state zero modes of certain Nicolai-like supersymmetric spin chains. As a result, we can realize the braid group in terms of the product state zero modes of these supersymmetric systems. These operators kill all the other states in the Hilbert space, thus preventing the occurrence of errors while processing information, making them suitable for quantum computing.

Atom Computing has created the first quantum computer to surpass 1,000 qubits, which could improve the accuracy of the machines.

By Alex Wilkins

How many qubits do we have to have in a quantum computer and accessble to a wide market to trully have something scfi worthy?

Today, a startup called Atom Computing announced that it has been doing internal testing of a 1,180 qubit quantum computer and will be making it available to customers next year. The system represents a major step forward for the company, which had only built one prior system based on neutral atom qubits—a system that operated using only 100 qubits.

The error rate for individual qubit operations is high enough that it won’t be possible to run an algorithm that relies on the full qubit count without it failing due to an error. But it does back up the company’s claims that its technology can scale rapidly and provides a testbed for work on quantum error correction. And, for smaller algorithms, the company says it’ll simply run multiple instances in parallel to boost the chance of returning the right answer.

Continue reading “Atom Computing is the first to announce a 1,000+ qubit quantum computer” »

face_with_colon_three This looks awesome :3.

There is great interest in using quantum computers to efficiently simulate a quantum system’s dynamics as existing classical computers cannot do this. Little attention, however, has been given to quantum simulation of a classical nonlinear continuum system such as a viscous fluid even though this too is hard for classical computers. Such fluids obey the Navier–Stokes nonlinear partial differential equations, whose solution is essential to the aerospace industry, weather forecasting, plasma magneto-hydrodynamics, and astrophysics. Here we present a quantum algorithm for solving the Navier–Stokes equations. We test the algorithm by using it to find the steady-state inviscid, compressible flow through a convergent-divergent nozzle when a shockwave is (is not) present.

Stupendous paper on a new spatial transcriptomic atlas of mouse brain by Shi et al. from Xiao Wang’s group at MIT. They leverage their in situ sequencing method “STARmap PLUS” to profile 1,022 genes in 3D and map 1.09 million cells across the adult mouse brain and spinal cord. While they did not use the whole brain, instead opting for a series of thick sections at regular intervals, they still covered a lot of ground! Furthermore, they employed graph-theoretic computational methods to predict wider gene expression profiles of cells in their dataset, imputing single-cell expression profiles of 11,844 genes. This dataset/resource will serve the neurobiology community in elucidating the mechanistic workings of the brain!

In situ spatial transcriptomic analysis of more than 1 million cells are used to create a 200-nm-resolution spatial molecular atlas of the adult mouse central nervous system and identify previously unknown tissue architectures.

New research on information entropy may offer evidence for the theory that our universe is a sophisticated simulation, with deep implications for various fields, from biology to cosmology.

The simulated universe theory implies that our universe, with all its galaxies, planets and life forms, is a meticulously programmed computer simulation. In this scenario, the physical laws governing our reality are simply algorithms. The experiences we have are generated by the computational processes of an immensely advanced system.

While inherently speculative, the simulated universe theory has gained attention from scientists and philosophers due to its intriguing implications. The idea has made its mark in popular culture, across movies, TV shows, and books – including the 1999 film The Matrix.

An international research team led by scientists at the Hudson Institute of Medical Research has found a way to determine which species of gut microbiota are important in certain diseases, and how they interact with other microorganisms to create a healthy microbiome.

The team developed a computational metabolite exchange scoring system to identify microbial cross feeding relationships—the use of metabolites produced by one microorganism as an essential nutrients by another—and how these may be altered in disease. The researchers suggest that understanding such relationships could point to therapeutic approaches for a range of disorders including inflammatory bowel disease, infections, autoimmune diseases and cancer.

“There are roughly 1,000 different bacterial species in a healthy gut—it’s a microscopic multicultural community with over a trillion individual members,” said research lead Samuel Forster, PhD. “Bacteria in our microbiomes exist as communities that rely on each other to produce and share key nutrients between them … We have developed a new computational way to understand these dependencies and their role in shaping our microbiome. This new method unlocks our understanding of the gut microbiome and provides a foundation for new treatment options that selectively remodel microbial communities.”

Strings of atoms create qubits that interact via superatoms.

An international team of interdisciplinary researchers has successfully created a method for better 3D modeling of complex cancers. The University of Waterloo-based team combined cutting-edge bioprinting techniques with synthetic structures or microfluidic chips. The method will help lab researchers more accurately understand heterogeneous tumors: tumors with more than one kind of cancer cell, often dispersed in unpredictable patterns.

The research, “Controlled tumor heterogeneity in a co-culture system by 3D bio-printed tumor-on-chip model,” appears in Scientific Reports.

Traditionally, medical practitioners would biopsy a patient’s tumor, extract cells, and then grow them in flat petri dishes in a lab. “For 50 years, this was how biologists understood tumors,” said Nafiseh Moghimi, an applied mathematics post-doctoral researcher and the lead author of the study. “But a decade ago, repeated treatment failures in human trials made scientists realize that a 2D model does not capture the real tumor structure inside the body.”