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Deep below the ground, radioactive elements disintegrate water molecules, producing ingredients that can fuel subterranean life. This process, known as radiolysis, has sustained bacteria in isolated, water-filled cracks and rock pores on Earth for millions to billions of years. Now a study published in Astrobiology contends that radiolysis could have powered microbial life in the Martian subsurface.
Dust storms, cosmic rays and solar winds ravage the Red Planet’s surface. But belowground, some life might find refuge. “The environment with the best chance of habitability on Mars is the subsurface,” says Jesse Tarnas, a planetary scientist at NASA’s Jet Propulsion Laboratory and the new study’s lead author. Examining the Martian underground could help scientists learn whether life could have survived there—and the best subsurface samples available today are Martian meteorites that have crash-landed on Earth.
Tarnas and his colleagues evaluated the grain sizes, mineral makeup and radioactive element abundance in Martian meteorites and estimated the Martian crust’s porosity using satellite and rover data. They plugged these attributes into a computer model that simulated radiolysis to see how efficiently the process would have generated hydrogen gas and sulfates: chemical ingredients that can power the metabolism of underground bacteria. The researchers report that if water was present, radiolysis in the Martian subsurface could have sustained microbial communities for billions of years—and perhaps still could today.
This is interesting. 😃
A new discovery in rats shows that the brain responds differently in immersive virtual reality environments versus the real world. The finding could help scientists understand how the brain brings together sensory information from different sources to create a cohesive picture of the world around us. It could also pave the way for “virtual reality therapy” for learning and memory-related disorders ranging including ADHD, Autism, Alzheimer’s disease, epilepsy and depression.
Mayank Mehta, PhD, is the head of W. M. Keck Center for Neurophysics and a professor in the departments of physics, neurology, and electrical and computer engineering at UCLA. His laboratory studies a brain region called the hippocampus, which is a primary driver of learning and memory, including spatial navigation. To understand its role in learning and memory, the hippocampus has been extensively studied in rats as they perform spatial navigation tasks.
When rats walk around, neurons in this part of the brain synchronize their electrical activity at a rate of 8 pulses per second, or 8 Hz. This is a type of brain wave known as the “theta rhythm,” and it was discovered more than six decades ago.
This looks like a really big breakthrough.
A decades-old problem about how to reliably control millions of qubits in a silicon quantum computer chip has now been solved.
Posted in computing, neuroscience | Leave a Comment on Brain-Computer Interfaces Aim to Bring New Therapeutical Advances to Treating Neural Conditions, Paralysis, Speech Problems
Eight months in, 2,021 has already become a record year in brain-computer interface (BCI) funding, tripling the $97 million raised in 2019.
Quantum engineers from UNSW Sydney have removed a major obstacle that has stood in the way of quantum computers becoming a reality. They discovered a new technique they say will be capable of controlling millions of spin qubits—the basic units of information in a silicon quantum processor.
Until now, quantum computer engineers and scientists have worked with a proof-of-concept model of quantum processors by demonstrating the control of only a handful of qubits.
But with their latest research, published today in Science Advances, the team have found what they consider “the missing jigsaw piece” in the quantum computer architecture that should enable the control of the millions of qubits needed for extraordinarily complex calculations.
In this work, we introduce a classical variational method for simulating QAOA, a hybrid quantum-classical approach for solving combinatorial optimizations with prospects of quantum speedup on near-term devices. We employ a self-contained approximate simulator based on NQS methods borrowed from many-body quantum physics, departing from the traditional exact simulations of this class of quantum circuits.
We successfully explore previously unreachable regions in the QAOA parameter space, owing to good performance of our method near optimal QAOA angles. Model limitations are discussed in terms of lower fidelities in quantum state reproduction away from said optimum. Because of such different area of applicability and relative low computational cost, the method is introduced as complementary to established numerical methods of classical simulation of quantum circuits.
Classical variational simulations of quantum algorithms provide a natural way to both benchmark and understand the limitations of near-future quantum hardware. On the algorithmic side, our approach can help answer a fundamentally open question in the field, namely whether QAOA can outperform classical optimization algorithms or quantum-inspired classical algorithms based on artificial neural networks48,49,50.
Wirelessly powered microchips, which have an ~1 GHz electromagnetic transcutaneous link to an external telecom hub, can be used for multichannel in vivo neural sensing, stimulation and data acquisition.
