SPACE/COSMOS

FAST discovers a rare millisecond pulsar with an extremely circular orbit

Science China Press

LinkedInWeChatBlueskyMessageWhatsAppEmail

Pulsars are ultra-dense neutron stars left behind after massive stars explode. They spin at incredible speeds, emitting regular beams of electromagnetic radiation. When these beams sweep past Earth, astronomers detect periodic signals, much like flashes from a lighthouse.

Recently, China's Five-hundred-meter Aperture Spherical radio Telescope (FAST) — has discovered a new pulsar of significant research value, named PSR J1810−0623. This pulsar not only spins extremely fast, but its formation history also appears to record a long and complex "binary evolution story."

PSR J1810−0623 has a rotation period of just 4.55 milliseconds, meaning it spins about 220 times every second. Astronomers believe that the vast majority of millisecond pulsars are not born spinning this fast; rather, they are accelerated through long-term interactions with a companion star: material from the companion star falls onto the neutron star, transferring angular momentum and causing it to spin faster and faster. This process is known as "recycling." Through precise observations spanning six and a half years, the research team found that PSR J1810−0623 has undergone an extremely thorough recycling process. Not only is its rotation speed exceptionally high, but its surface magnetic field has also decayed to only about 100 million Gauss.

PSR J1810−0623 has a companion star, and the two orbit their common center of mass every 15.4 days. Based on observational calculations, this companion star has a mass of about 0.64 times that of the Sun and is likely a carbon-oxygen white dwarf. This clue reveals the origin of PSR J1810−0623: it was likely born in a "moderate-mass X-ray binary system". Over vast stretches of time, the companion star continuously transferred material to the neutron star, not only causing the latter to spin rapidly but also eventually depleting its own outer layers, leaving behind the white dwarf remnant we see today. This formation pathway is uncommon in the Milky Way, making such systems particularly valuable.

What particularly intrigues researchers is that the orbit of this binary system is nearly a perfect circle. The eccentricity of PSR J1810−0623's orbit is only about 0.000015, representing an orbit so close to circular that its elliptical shape is almost undetectable. Generally, long-term, stable mass transfer between binary stars gradually smooths out orbital irregularities, making the orbit increasingly circular. This characteristic is similar to a few known special systems, such as the famous PSR J1614−2230. However, the orbit of PSR J1810−0623 is even rounder, providing a new observational benchmark for testing binary evolution theories.

Beyond revealing binary evolution processes, this newly discovered pulsar can also help scientists study the Milky Way itself. The research team used the polarization properties of its radio signals to measure magnetic field information along the line of sight, thereby providing new data points for mapping the Galactic magnetic field structure.

In the future, as FAST and other radio telescopes continue long-term timing observations, scientists hope to further determine the true mass of this neutron star and even test gravitational theories through more precise orbital measurements. For studying pulsar recycling mechanisms, binary system evolution, and the structure of the Milky Way, PSR J1810−0623 will prove to be an immensely valuable "natural laboratory".

---

Journal

Science China Physics Mechanics and Astronomy

DOI

10.1007/s11433-026-2951-1 

Method of Research

Observational study

TRACERS uses speedy electrons to trace solar energy’s path to Earth

First published results from Iowa-led NASA mission reveal new details of sun-Earth interaction

University of Iowa

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

A University of Iowa-led research team has documented how energy from the sun interacts with Earth’s magnetic field and moves closer to our planet, using detailed electron measurements. In this image, speedy electrons act like messengers to convey information about those interactions, called magnetic reconnection, tens of thousands of miles from Earth’s surface.

view more 

Credit: Jasper Halekas lab, University of Iowa

Physicists led by the University of Iowa have documented in the finest detail to date how energy from the sun interacts with Earth’s magnetic field, which could yield greater insights into solar effects on Earth that drive space weather.

In a new study, the researchers measured the velocities and concentrations of electrons in low-Earth orbit at locations called cusps, which act like conduits for charged particles from the sun to enter Earth’s ionosphere, the upper reaches of our planet’s atmosphere. Through those detailed measurements, the researchers were able to more precisely map the travel pattern of solar energy from magnetic reconnection — solar energy’s first encounter with Earth’s magnetic field tens of thousands of miles from Earth’s surface — to its interactions at cusps a few hundred miles above our planet.

“With magnetic reconnection, we don't really know how it varies at a fine scale. We have a hunch that it’s either varying in time or varying spatially,” says Jasper Halekas, professor in the Department of Physics and Astronomy at Iowa and the study’s corresponding author. “Our electron edge measurements reveal for the first time how these processes vary on small time and spatial scales at the edge of the cusp, helping us to better understand the efficiency of the sun-Earth coupling.”

The results come from TRACERS, the approximately $170 million mission funded by NASA and the largest external research award in University of Iowa history. Launched in July 2025, twin satellites swoop through low-Earth orbit, sampling electrons, ions, plasma, and other elements part of the interactions between the sun and the Earth. 

“This is important because magnetic reconnection is how the energy from the sun gets into Earth’s system,” Halekas says. “It’s important to know the duty cycle of that reconnection — is it happening continuously, or is it sort of turning on and off?”

Electrons are key to better understanding magnetic reconnection events and how they reverberate closer to Earth. Because of their nearly nonexistent mass and high energies, think of them as ultra-speedy messengers, delivering the first news about magnetic reconnection some 30,000 miles away at the edges of Earth’s magnetic bubble and portending the ripple effects at cusps farther downstream in Earth’s ionosphere.

“The electrons are saying, magnetic reconnection is taking place way out here, and we’re letting you know that there’s going to be this wave of mass and energy coming to us,” Halekas explains.

The researchers cataloged 149 cusp encounters by one of the TRACERS spacecraft; 57 of those encounters showed characteristic electron dispersion signatures at the equatorward edge. The observations came from data collected by the Analyzer for Cusp Electrons instrument (ACE), designed and built at Iowa.

“The equatorward edge is the leading edge of the cusp, where the solar wind energy and plasma can first reach the ionosphere,” says Halekas, principal investigator for the ACE instrument. “The electron and ion signatures we see there are the proof we’re seeing the effects of magnetic reconnection.” 

The study, “Electron dispersion at the electron edge of the Earth’s magnetospheric cusp,” was published online May 19 in the journal Geophysical Research Letters.

Contributing authors from Iowa are Sarah Henderson, Scott Bounds, Aidan Moore, Ivar Christopher, David Miles, Connor Feltman, George Hospodarsky, Allison Jaynes, Brendan Powers, and Shirsh Soni.

Other authors are Suranga Ruhunusiri and Karlheinz Trattner, from the University of Colorado-Boulder; John Bonnell and Marit Øieroset, from the University of California-Berkeley; Brandon Burkholder, from the University of Maryland-Baltimore County and NASA Goddard Space Flight Center; Iver Cairns, from the University of Sydney in Australia; Li-Jen Chen, Hyunju Connor, and John Dorelli, from NASA Goddard Space Flight Center; Ian DesJardin and Dibyendu Sur, from Catholic University of America and NASA Goddard Space Flight Center; Stephen Fuselier, from Southwest Research Institute and the University of Texas-San Antonio; Katherine Goodrich, from West Virginia University; James Labelle, from Dartmouth College; Steven Petrinec, from Lockheed Martin Advanced Technology Center, in Palo Alto, California; and Robert Strangeway, from the University of California-Los Angeles.

---

Journal

Geophysical Research Letters

DOI

10.1029/2026GL122699 

Method of Research

Observational study

Subject of Research

Not applicable

Article Title

Electron Dispersion at the Electron Edge of the Earth's Magnetospheric Cusp

 

UMBC-led research uses NASA PACE satellite to track fall colors with new precision

University of Maryland Baltimore County

Facebook

XLinkedInWhatsAppEmail

 

image: 

This figure from a paper published May 18, 2026 in Remote Sensing Letters uses data from NASA's PACE satellite to show how the presence of anthocyanins (which cause leaves to appear red in the fall) increased from the first to the third weeks of October in the eastern United States in 2024. (Courtesy of Fred Huemmrich, lead author on the new study)

view more 

Credit: Courtesy of Fred Huemmrich

Researchers have developed a new approach using data from NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite to observe the timing and progression of fall colors across landscapes.

The study, published in Remote Sensing Letters and led by Karl F. Huemmrich, a research professor at UMBC’s Goddard Earth Sciences Technology and Research (GESTAR) II center, focuses on detecting changes in leaf pigments including chlorophylls (greens), anthocyanins (reds), and carotenoids (yellows and oranges).

PACE’s advanced sensors capture fine details of light reflected from leaves, with near-daily global coverage. The research team used indices that associate the reflectance data with the presence of various pigments, allowing them to produce detailed leaf color maps and track color changes throughout the fall. These maps could help support the multi-billion-dollar leaf-peeping tourism economy by directing visitors to peak viewing areas in real time and helping communities manage visitor flows.

Traditional greenness indices, such as the Normalized Difference Vegetation Index (NDVI), primarily show a gradual decline in green leaves. The PACE-based indices improve on those methods by allowing scientists to identify more precise markers of the end of the growing season, including dates of peak fall color. Over time, the data could also yield insights into plant stress from drought or insect damage—with potential benefits for agriculture—and help improve models that predict fall color timing based on environmental conditions.

“PACE is the first mission that can measure these pigment indices over large areas, and repeatedly, so we can look at change through the fall,” Huemmrich says. The indices he and Caplan used were developed in the early 2000s, but the new paper applied them at a global scale for the first time. Huemmrich adds, “I anticipate that as we accumulate more years of PACE data, we will be able to observe changes in the timing of peak color, which may be related to climate change.”

Opening frontiers in ecosystem science

Study co-author Skye Caplan, a NASA data scientist, expressed enthusiasm about the broader research potential unlocked by PACE. “I’m excited about observing fall colors with PACE, because I think it’s the beginning of a real exploratory period for global hyperspectral leaf pigment measurements,” she says. “I’m hoping we get to see folks read the paper, see how PACE observes these metrics like relative chlorophyll, anthocyanin, and carotenoid content, and apply those observations to their own work.”

“Working with PACE data is really fun, because you get to see the world in so many different ways,” Caplan adds. “It doesn’t just offer observations of the oceans, but also characterizations of the atmosphere and land—and all of these domains as a system, rather than as separate entities. I think that is critical and a real advantage of PACE.”

For example, Huemmrich previously published research that used PACE data to assess ecosystem productivity, and the UMBC-designed and -built HARP2 instrument flying on PACE is contributing to atmospheric chemistry studies. 

Plus, PACE observations aren’t only for scientists: Caplan notes that the public can access NASA Worldview, an interactive site for browsing satellite images from many different NASA missions. “Sometimes I like to pull up PACE data on NASA Worldview and just scroll around to see what the world looked like on any given day,” she says. “I often find something interesting and worth exploring.”

---

Journal

Remote Sensing Letters

DOI

10.1080/2150704X.2026.2673540 

Method of Research

Observational study

Subject of Research

Not applicable

Article Title

Observing fall foliage with PACE pigment indices

 

Scientist creates ‘mini‑universe’ to measure time without a clock

University of Birmingham

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

Part of the apparatus to trap and cool rubidium atoms close to absolute zero  (~-273.15 degrees Celsius).  

view more 

Credit: University of Birmingham

Images available here.  

 

New experiment provides powerful testbed for ideas in quantum cosmology and gravity - theories relating to the early universe can now be tested in the laboratory. 

 

A University of Birmingham scientist has built a 'mini universe' that takes a step towards answering one of science’s biggest questions: ‘what is time?’ 

Publishing his findings today in Physical Review Research, Professor Giovanni Barontini shows how it is possible to measure the flow of time without using a clock at all. The new findings provide a scientific model where a version of time emerges from the experiment itself. 

Some theories of physics, such as the Wheeler–DeWitt equation suggest that, at its deepest level, the universe has no built‑in time, but exists as a single, unchanging quantum state where particles exhibit both wave-like and particle-like properties. It treats the universe as a whole with no external clock, and any sense of time must emerge from internal relationships between parts. 

Professor Barontini used a cloud of 24,000 ultracold atoms - just a few billionths of a degree above absolute zero - to create a hermetically sealed quantum system that mimics a simple ‘universe’. The particles were trapped and divided with a thin barrier formed with two laser beams of different frequency to create an observed (‘bright’) and an unobserved (‘dark’) region. 

The ‘bright’ sector repeatedly expands and collapses, experiencing something like a Big Bang and a Big Crunch - a hypothetical scenario where the expansion of the cosmos eventually reverses. The experiment allows the sequence of events to be reconstructed from within the mini universe itself, without any reference to an external laboratory clock. 

The experiment demonstrated that time could emerge from changes happening inside a quantum system, rather than existing as something external that ticks along independently.  

Using the ‘mini universe’ demonstrated that ‘time’ could be created from the disorder or spread (entropy) of atoms and how they behaved in a system. Atoms could move between ‘bright’ and ‘dark’ regions, but the system was otherwise isolated from the outside world.  

When the spread of particles in the bright sector increased or decreased as atoms moved in or out, the system was ‘moving forward in time’. When this distribution of atoms did not change, time effectively stopped. Professor Barontini called this process ‘entropic time’, after finding that this version of time: 

• Flows in one consistent direction, giving a clear ‘arrow of time’ 

• Correctly orders events, even in a system expanding and contracting like a mini cosmos 

• Speeds up or slows down depending on how entropy moves around 

Professor Barontini said: “In some theories of the universe, especially quantum gravity, time doesn’t appear as a built‑in feature. Yet in everyday life, time flows from past to future – why is this so, when most basic laws of physics work the same way forwards and backwards?  

“This study provides the first controlled experimental evidence that ‘time’ can be defined by changes within a system rather than as the external ‘ticking clock’ we think of as time. It offers new insight into the nature of time in quantum gravity that could be used to describe dynamics just as effectively as conventional time.”  

The study also demonstrates that a version of the main equation in quantum mechanics (Schrödinger) can still be written using entropic time – enabling predictions of how the ‘probability cloud’ of a quantum system will change over time.  

The experiment addresses a long-standing question in physics - in some theories of the universe, there is no built‑in clock so how do you tell what comes ‘before’ and ‘after’ without external time?  

Professor Barontini showed that the system follows the standard equations of quantum physics and demonstrates that deep questions about the nature of time - usually discussed only in theories about the universe as a whole - can be tested in controlled laboratory experiments.  

The experiment provides a powerful testbed for ideas in quantum cosmology and gravity, meaning that ideas relating to the early universe can now be tested experimentally in the lab.  

The approach could be extended to more complex systems, potentially allowing researchers to probe the physics of the Big Bang and the ‘Big Crunch’. It could also be used to simulate black holes in the lab or test competing theories about how time emerges in the universe. 

ENDS 

 

The 'cloud' inside the glass cell is a magneto-optical trap of rubidium atoms at a temperature of ~0.0001 degrees above absolute zero. It is only the first step to "build" the mini-universe.   

 

The University of Birmingham experiment to trap and cool rubidium atoms close to absolute zero.  

 

Giovanni Barontini, Professor of Physics, at the University of Birmingham, using the apparatus to trap and cool rubidium atoms. 

 

Giovanni Barontini, Professor of Physics, at the University of Birmingham, using the apparatus to trap and cool rubidium atoms. 

 

Optics to deliver the lasers on the atoms.   

Credit

University of Birmingham

---

Journal

Physical Review Research

DOI

10.1103/1h9j-df4k 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Testing the problem of time with cold atoms

Article Publication Date

11-Jun-2026

Reversing the arrow of time in heat transfer: A novel operator learning framework for thermal retrodiction

Science China Press

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

Experimental thermal field retrodiction evolution of the 3D-printed sample.

view more 

Credit: ©Science China Press

Thermal diffusion—a fundamental physical process pervasive in applications ranging from electronics to industrial systems—is inherently irreversible under the second law of thermodynamics. As temperature gradients spontaneously smooth out over time, crucial information regarding the initial thermal state is permanently lost due to entropy increase. This fundamental information loss leads to a severe ill-posedness in inverse thermal problems, where infinitesimal errors in the final observation can cause enormous uncertainties in the reconstructed initial state.

Recently, a collaborative research team led by Prof. Ying Li and Prof. Hongsheng Chen from Zhejiang University, alongside Prof. Jiping Huang from Fudan University, has made a significant breakthrough in tackling this longstanding challenge. Published in National Science Review and co-first-authored by master’s graduate Hanqi Chen, as well as PhD students Qiang-Kai-Lai Huang and Yanxiang Wang from Prof. Ying Li’s research group at Zhejiang University, the paper titled “Learning to reverse thermal diffusion” introduces a deep learning framework for inverse diffusion capable of deducing initial thermal states based on final-state observations.

The proposed methodology overcomes the limitations of conventional computational methods, particularly when analyzing heterogeneous materials, by employing two synergistic deep learning components. First, the team introduced the Thermal Field Evolution Network (TE-Net), a finite-difference-based convolutional architecture that accurately estimates spatial material properties—specifically thermal diffusivity—from time-dependent cooling data.

Crucially, this accurately derived diffusivity serves as essential physical prior knowledge for the framework’s core innovation: the Time-Reversal Operator (TRO). Drawing inspiration from generative diffusion models and Fourier Neural Operators, the TRO learns mappings between function spaces rather than relying on traditional point-wise solutions. By synergizing analytical eigenbasis decomposition with frequency-domain operator learning, the TRO effectively filters high-frequency noise and directly projects the final-state thermal field back to its initial distribution.

The research team rigorously validated their approach through comprehensive simulations and real-world infrared imaging experiments using 3D-printed structures and practical semiconductor chips. The operator-driven method demonstrated exceptional performance, achieving a thermal diffusivity estimation error of less than 10% and an astonishing retrodiction numerical error below 0.1%.

This breakthrough establishes a high-fidelity paradigm for spatiotemporal thermal analysis. It holds broad implications for advanced non-destructive testing, defect detection in densely integrated circuits, and next-generation thermal management, with potential applications extending to a wider class of physical phenomena such as mass and charge diffusion.

---

Journal

National Science Review

DOI

10.1093/nsr/nwag287 

 

Figure 1: Schematic of the diffusion and retrodictive diffusion processes, along with the overall deep learning architecture.

 

Figure 2: Experimental thermal field retrodiction evolution of the 3D-printed sample and the chip.

Credit

©Science China Press