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Category: mapping

Study maps the time and energy patterns of electron pairs in ultrafast pulses

The ability to precisely study and manipulate electrons in electron microscopes could open new possibilities for the development of both ultrafast imaging techniques and quantum technologies.

Over the past few years, physicists have developed new experimental tools for studying the behavior of electrons not bounded to any material by utilizing the so-called nanoscale field emitters, tiny metallic tips that release electrons when exposed to strong electric fields.

Researchers at the Max Planck Institute for Multidisciplinary Sciences recently carried out a study aimed at shedding new light on how pairs of emitted electrons relate to each other and how their behavior unfolds over time.

Quantum imaging settles 20-year debate on gold surface electron spin direction

Researchers at the Institute for Molecular Science (IMS) have definitively resolved a two-decade-long controversy regarding the direction of electron spin on the surface of gold.

Using a state-of-the-art Photoelectron Momentum Microscope (PMM) at the UVSOR synchrotron facility, the team captured complete two-dimensional snapshots of the Au(111) Shockley surface state, mapping both the electron’s spin (its intrinsic magnetic property) and its orbital shape in a projection-based measurement. The work is published in the Journal of the Physical Society of Japan.

The experiment unambiguously confirmed the Rashba effect—where an electron’s motion is coupled to its spin—by assigning a clockwise (cw) spin texture to the outer electron band and a counterclockwise (ccw) texture to the inner band when viewed from the vacuum side.

Dark energy might be changing and so is the Universe

Dark energy may be alive and changing, reshaping the cosmos in ways we’re only beginning to uncover. New supercomputer simulations hint that dark energy might be dynamic, not constant, subtly reshaping the Universe’s structure. The findings align with recent DESI observations, offering the strongest evidence yet for an evolving cosmic force.

Since the early 20th century, scientists have gathered convincing evidence that the Universe is expanding — and that this expansion is accelerating. The force responsible for this acceleration is called dark energy, a mysterious property of spacetime thought to push galaxies apart. For decades, the prevailing cosmological model, known as Lambda Cold Dark Matter (ΛCDM), has assumed that dark energy remains constant throughout cosmic history. This simple but powerful assumption has been the foundation of modern cosmology. Yet, it leaves one key question unresolved: what if dark energy changes over time instead of remaining fixed?

Recent observations have started to challenge this long-held view. Data from the Dark Energy Spectroscopic Instrument (DESI) — an advanced project that maps the distribution of galaxies across the Universe — suggests the possibility of a dynamic dark energy (DDE) component. Such a finding would mark a significant shift from the standard ΛCDM model. While this points to a more intricate and evolving cosmic story, it also exposes a major gap in understanding: how a time-dependent dark energy might shape the formation and growth of cosmic structures remains unclear.

Mapping AI’s brain reveals memory and reasoning are not located in the same place

Researchers studying how large AI models such as ChatGPT learn and remember information have discovered that their memory and reasoning skills occupy distinct parts of their internal architecture. Their insights could help make AI safer and more trustworthy.

AI models trained on massive datasets rely on at least two major processing features. The first is memory, which allows the system to retrieve and recite information. The second is reasoning, solving new problems by applying generalized principles and learned patterns. But up until now, it wasn’t known if AI’s memory and general intelligence are stored in the same place.

So researchers at the startup Goodfire.ai decided to investigate the internal structure of large language and vision models to understand how they work.

Mapping chromatin structure at base-pair resolution unveils a unified model of cis-regulatory element interactions

Now online! Li et al. apply base-pair resolution Micro Capture-C ultra to map chromatin contacts between individual motifs within cis-regulatory elements and reveal a unified model of biophysically mediated enhancer-promoter communication.

Mapping a new frontier with AI-integrated geographic information systems

Over the past 50 years, geographers have embraced each new technological shift in geographic information systems (GIS)—the technology that turns location data into maps and insights about how places and people interact—first the computer boom, then the rise of the internet and data-sharing capabilities with web-based GIS, and later the emergence of smartphone data and cloud-based GIS systems.

Now, another is transforming the field: the advent of artificial intelligence (AI) as an independent “agent” capable of performing GIS functions with minimal human oversight.

In a study published in Annals of GIS, a multi-institutional team led by geography researchers at Penn State built and tested four AI agents in order to introduce a conceptual framework of autonomous GIS and examine how this shift is redefining the practice of GIS.

When speaking out feels risky: New study maps hidden dynamics of self-censorship

In an era when social media blurs the line between public and private speech, how do people decide whether to speak their minds or stay silent?

A new study from researchers at Arizona State University and the University of Michigan, published in the Proceedings of the National Academy of Sciences, offers a groundbreaking look at the strategic trade-offs individuals make when facing the threat of punishment for dissent.

The work, co-authored by Professor Stephanie Forrest and Assistant Professor Joshua J. Daymude in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at ASU, and Robert Axelrod from the University of Michigan, introduces a to explain when people choose to express dissent or self-censor.

Functional ultrasound neuroimaging reveals mesoscopic organization of saccades in the lateral intraparietal area

An amazing paper (link:) where functional ultrasound imaging (fUSI) is used to explore how brain activity in the lateral intraparietal cortex (LIP) can predict visual saccades (eye movements) in two monkeys. An impressive array of computational analyses are used to extract insights from the imaged regions. Indeed, predictive models developed by the authors remained fairly stable over the course of up to 900 days! I happen to know two of the authors (Sumner L Norman and Mikhail Shapiro): congratulations to them and their colleagues on this excellent publication!

Our results demonstrate that PPC contains subregions tuned to different directions. These tuned voxels were predominately within LIP and grouped into contiguous mesoscopic subpopulations. Multiple subpopulations existed within a given coronal plane, i.e., there were multiple preferred directions in each plane. A rough topography exists where anterior LIP had more voxels tuned to contralateral downwards saccades and posterior LIP had more voxels tuned to contralateral upwards saccades. These populations remained stable across more than 100–900 days.

We observed large effect sizes with changes in CBV on the order of 10–30% from baseline activity (Fig. 3). This is much larger than observed with BOLD fMRI where the effect size was ~0.4–2% on similar saccade-based event-related tasks27,32. Our results support a growing evidence base that establishes fUSI as a sensitive neuroimaging technique for detecting mesoscopic functional activity in a diversity of model organisms, including pigeons, rats, mice, nonhuman primates, ferrets, and infant and adult humans23,24,25,33,34,35,36,37,38,39,40.

Several studies have reported a patchiness in direction selectivity with many neighboring neurons tuned to approximately the same direction followed by an abruption to a patch of a different preferred direction13,14,41. These results match very closely with the results observed in this study where we found clusters within LIP tightly tuned to one direction with differently tuned clusters in close proximity within a given plane. These results further emphasize the high spatial resolution of fUSI for functional mapping of neuronal activity. These results also closely match a previous study that used fUSI to identify the tonotopic mapping of the auditory cortex and inferior colliculus in awake ferrets where the authors found a functional resolution of 100 µm for voxel responsiveness and 300 µm for voxel frequency tuning34.

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