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After about 10 years of construction, the Vera Rubin Observatory (VRO) is scheduled to see its first light in January 2025. Once it’s up and running, it will begin its Legacy Survey of Space and Time (LSST), a decade-long effort to photograph the entire visible sky every few nights. It’ll study dark energy and dark matter, map the Milky Way, and detect transient astronomical events and small Solar System objects like Near Earth Objects (NEOs).

New research shows the LSST will detect about 130 NEOs per night in the first year of observations.

NEOs are small Solar System bodies, usually asteroids, that orbit the Sun and come within 1.3 astronomical units of the Sun. When a NEO crosses Earth’s orbit at some point, it’s considered a potentially hazardous object (PHO). NASA is currently cataloguing NEOs, and while they’ve made progress, there are many more left to find.

According to new research, the upcoming LSST will detect about 130 NEOs per night. The research is “Expected Impact of Rubin Observatory LSST on NEO Follow-up,” and it’s still in peer-review but available on the prepress site arxiv.org. The lead author is Tom Wagg, a PhD student at the DiRAC Institute and the Department of Astronomy at the University of Washington in Seattle.

“We simulate and analyze the contribution of the Rubin Observatory Legacy Survey of Space and
Time (LSST) to the rate of discovery of Near Earth Object (NEO) candidates,” the authors write. They also analyzed submission rates for the NEO Confirmation Page (NEOCP) and how that will affect the worldwide follow-up observation system for NEOs.

The problem with NEOs is that they don’t necessarily remain NEOs. A subset of them—about one-fifth—pass so close to Earth that even a small perturbation can send them on an intersecting path with Earth’s orbit. These are sources of potentially catastrophic collisions. A further subset of these are called Potentially Hazardous Asteroids (PHAs), and they’re massive enough to make it through Earth’s atmosphere and strike the planet’s surface. To be considered a PHA, an object has to be about 140 meters in diameter.

The Minor Planet Center maintains a database of NEOs, and more are being added constantly. New detections are recorded on the NEO confirmation page (NEOCP), but at first, they’re only candidates. Follow-up observations require resources to accurately determine a candidate’s orbit and size.

If the LSST contributes 130 more NEO detections each day, which is eight times the current detection rate, the survey will create an enormous amount of follow-up work. According to a standard computer algorithm named digest2 that evaluates them, NEOs are only considered candidates if they meet certain criteria, and that can only be determined by follow-up observations with other telescopes.

Illustration of a Near Earth Object. Credit: NASA/JPL-Caltech

But with so many more detections on the horizon, there could be problems.

“The aim of this paper is to quantify the impact of Rubin on the NEO follow-up community and consider possible strategies to mitigate this impact,” the authors write.

Most of the NEOs the LSST finds will be found using a method called “tracklet linking.” Tracklet linking is “a computational technique where at least three pairs of observations (“tracklets”) observed over a 15-night period are identified as belonging to the same object,” the authors explain. The problem is that the tracklet linking can take time and comes at a cost. “… the object is not identified as interesting until the third tracklet is imaged – at best, two nights after the first observation or, at worst, nearly two weeks later,” the authors write. This means that the system may miss interesting or hazardous objects until it’s too late to observe them for confirmation.

With other telescopes, there’s a way around this. They can capture several back-to-back images of tracklets to create more robust detections that can be immediately followed up on. However, the VRO can’t do that because the LSST is an automated survey.

What it can do is serendipitously capture three or more tracklets in smaller sections of the sky where its observing fields will overlap. “Such tracklets could be immediately identified and, assuming they meet the digest2 score criteria, submitted to the Minor Planet Centre and included on the NEOCP,” the authors write. Because of the scale, the authors say this process could be automated and would require no human vetting.

The researchers simulated LSST detections to test their idea and see if it could reduce the follow-up observation workload. “We present an algorithm for predicting whether LSST will later re-detect an object
given a single night of observations (therefore making community follow-up unnecessary),” they explain. They wanted to determine how effective it would be in reducing the number of objects that require follow-up observations.

They started by simulating almost 3600 days of the LSST, consisting of almost one billion observations.

This figure from the study shows the number of asteroids detected in one night of LSST simulations. About 350,000 asteroids were observed, including about 1,000 NEOs. The grey curved line represents the ecliptic. Image Credit: Wagg et al. 2024.

From their data, they selected observations that corresponded to tracklets. Single tracklets don’t determine an orbit, but they can constrain potential orbits when compared to known Solar System orbits. The digest2 algorithm works by comparing observed tracklets to a simulated catalogue of Solar System objects to estimate the probability that an object is a NEO. It takes all the data and estimates the possible orbits of the objects.

This figure from the research shows the variant orbits computed for one simulated NEO tracklet. The white arrow indicates the initial sight line for the observation. The blue dotted line indicates the orbit of the Earth. The background stars are included for illustrative purposes only. Image Credit: Wagg et al. 2024.

At this point, the number of candidate NEOs is still overwhelming. The candidate population is not a high-purity sample and still contains non-NEOs like main-belt asteroids.

Most of the impurity is caused by main-belt asteroids, and as these were recognized, the purity would rise. The simulations show that purity would continually rise, and after about five months, it would level off. A similar thing happens with submission rates. After about 150 nights, the submission rate reaches a steady state of about 95 per night.

The LSST repeatedly images the sky in overlapping fields. The researchers thought that if they could determine which tracklets were going to be re-observed by the LSST as it goes about its business, they could reduce the follow-up observation burden.

“If we could predict which objects will be followed up by LSST itself, this would reduce the load on the follow-up system and allow the community to focus on the ones that truly require external follow-up to be designated,” the authors explain. The researchers developed an algorithm for computing the ensemble of ranges and radial velocities of a single observed tracklet.

“We now examine the effect of applying the LSST detection probability algorithm to reduce the load on the NEOCP,” the authors write. The following image illustrates this.

This figure from the research shows the estimated probability of detection by the algorithm and the number of objects, with the dotted black line being the threshold for confirmation. On the right is a contingency matrix with two Truth columns and two Prediction rows. All in all, it shows that the algorithm detected 180 NEOs, with 400 being sent for confirmation needlessly, as the LSST will have confirmed them. Lost objects are objects that have been de-prioritized for follow-up observations but won’t receive adequate follow-ups by the Rubin itself. Image Credit: Wagg et al. 2024.

Overall, the algorithm predicted the correct outcome 68% of the time. Also, about 64 of the objects submitted to the NEOCP per night would require external follow-up, but only around 8.3%, or about five, of those objects would be NEOs. The algorithm would only improve accuracy minimally, but it would reduce the follow-up workload by a factor of two.

The researchers say that other tweaks to the algorithm can improve it and make LSST NEO detections more robust without the need for so many demanding follow-up observations.

In their conclusion, the authors write, “LSST contributions will increase the nightly NEOCP submission rate
by a factor of about 8 over the first year to an average of 129 objects per night.” However, the fraction that will be confirmed is low at about 8.3%, but will rise over time.

The LSST is expected to generate 200 petabytes of uncompressed data during its ten-year run, which is about 200 million gigabytes. This study shows that managing the amount of data that the LSST will generate requires new methods.

It may seem like a far-away concern, but understanding the threat to Earth posed by NEOs is critical. While efforts are being made to understand how we can protect the planet from them, cataloguing them all is important.

The post The Rubin Observatory Will Unleash a Flood of NEO Detections appeared first on Universe Today.

The largest sailing cargo ship in existence is on its maiden voyage across the Atlantic Ocean, demonstrating a carbon footprint 10 times smaller than that of a container ship

High-speed camera recordings show that springtails spin at up to 368 rotations per second when they jump away from danger

A new paper that looks at homeopathy in pharmacy education raises more questions than answers.

The post Homeopathy in Pharmacist Education first appeared on Science-Based Medicine.

The Polaris Dawn mission will include the first ever civilian spacewalk, and with a new spacesuit and no airlock, it may also be the most dangerous spacewalk ever

I am a lifelong dog owner, and like many dog owners am often impressed with how smart my dogs have been. They pick up on subtle body language and non-verbal cues, they seem to understand specific words, and they are capable of successfully communicating their wants and desires. My latest dog is an Australian shepherd, who is both smart and willful. Any attempt at training him to do what we want results in him equally training us to do what he wants. An of course we love them and the emotional connection is real and bidirectional. Dogs and humans have evolved a symbiotic relationship.

Still, I was very skeptical when I heard about a recent social media phenomenon – posting videos of dogs using a soundboard to communicate. After watching the videos I am completely unimpressed, and my skepticism has been supported. It turns out that this is mostly just the old “Clever Hans” effect, falling into the same trap that all attempts to teach animals to communicate have risked.

In the early 20th century, Wilhelm von Osten, who was a mystic and phrenologist (among other things) showcased his horse, Hans, who he claimed could not only do arithmetic, but could read, solve problems, track a calendar, and other tasks. Hans would communicate by tapping his hoof the correct number of times. Osten probably really believed in Hans’s abilities, and he showcased them far and wide. However, when psychologist Oskar Pfungst investigated Hans he found that the horse was simply responding to non-verbal cues from his owner, essentially noted when to stop on the correct answer. He initially removed the trainer from the area, but Hans was still able to perform. However, he then made sure that no one present knew the answer, and then Hans could not perform. Hans needed cues from people to know when to stop.

Perhaps a more complex example is Koko the gorilla, who his trainer claimed could use 1,000 signs and understand 2,000 spoken words. The evidence presented to backup these claims is mainly in the form of videos. But if you watch these videos you notice that Koko’s communication is very hit or miss, and requires a lot of clever interpretation on the part of the trainer. So much so that it is possible to conclude that most if not all of the communication is happening in the mind of the trainer.

Since Koko is not making full coherent sentences, just stringing together 1-3 words, a lot is left up to interpretation. Is Koko really combining words logically to convey new meaning, or just signing until they get what they want. It does seem that Koko has associated some signs with physical objects or with actions. But is this association really language? Sometimes Koko makes mistakes, and has to keep going until the trainer gives them positive feedback. Sometimes they are “kidding” when they get things wrong, and sometimes you have to infer what they might mean.

There is no questions gorillas are very smart animals, and have an ability to learn a lot of information. But the evidence simply did not convince the scientific world that they possess that level of human-like language. Koko turned into a cautionary tale that has hung over animal language research ever since. Again – I am not saying that animals have no language. They clearly do. Dogs and primates in particular have been shown to understand words spoken by humans, not just intonation and body language. The real question is – can they use words to communicate, and can they string words together logically? So far, the scientific community is not convinced.

Let’s get back to the dog videos – what I see in them is a clear Clever Hans / Koko phenomenon. Copper in particular is unimpressive. When asked a question he puts his paw out and hits whatever button is right in front of him, without even looking at the buttons (shades of facilitated communication). Also, there is a very limited set of buttons, and everything relates to doggy interests. So the dog could hit literally any button and the owner could make sense of it. In the “Bunny” video the dog hits the button for “home” several times and the owner says – “Yes, we are home.” What’s that button even there for? When at home, the owner concludes the dog is telling them they are home, and if not at home I presume they would conclude the dog wants to go home. It doesn’t seem like there is any possible wrong answer.

This is a pretty clear example of wishful thinking, and the videos are certainly not compelling evidence that actual communication is going on. At most these dogs are learning to associate certain actions with getting a reward of some kind. There is also likely a selection bias going on in terms of which videos segments are uploaded to social media – it’s reasonable to conclude we are seeing the best evidence there is.

This all may seem harmless and fun, but the underlying phenomenon can get very serious and have profound consequences. Similar methods are used to communicate with non-verbal people, and suffer all of the problems of animal language research. It is very easy for the communicator or facilitator to impose their own mental processes onto their client. Far from giving a voice to a non-verbal person, they are stealing their voice (even if they mean well). Sometimes this can also lead to very dark places, such as using such methods to make serious accusations against others.

I suspect this is a lesson we will have to learn over and over again. More than a century after Clever Hans and the true phenomenon underlying his performance was revealed, it’s happening all over again.

The post Dog Soundboards first appeared on NeuroLogica Blog.

The orange mould Neurospora intermedia can grow on a wide range of waste products without producing toxins, and the results are being served in Michelin-starred restaurants

Meanwhile, in Dobrzyn, Hili is still queen of the hill:

A: What are you doing?
Hili: Some call it deterrence.

Ja: Co ty robisz?
Hili: Niektórzy nazywają to odstraszaniem.

 

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Researchers have used vinegar vapor to dramatically improve UV sensors in a cheap, room-temperature process leading to better wearable devices.

Researchers have used vinegar vapor to dramatically improve UV sensors in a cheap, room-temperature process leading to better wearable devices.

A recently developed block copolymer could help push the limits of integration and miniaturization in semiconductor manufacturing, report scientists. Chemically tailored for reliable directed self-assembly, the proposed compound can arrange itself into perpendicular lamellar structures whose half-pitch width is less than 10 nanometers, outperforming conventional and widely used block copolymers.

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The system combines an activated carbon filter with a special, patented catalyst that traps harmful chemicals and breaks them down into harmless components on the filter material.

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Engineers have developed a device that noninvasively stimulates deep brain regions, potentially disrupting the faulty signals that lead to chronic pain. Preliminary trials show the therapy relieves pain after a single treatment.

Supermassive black holes typically take billions of years to form. But the James Webb Space Telescope is finding them not that long after the Big Bang -- before they should have had time to form. Astrophysicists have discovered that if dark matter decays, the photons it emits keep the hydrogen gas hot enough for gravity to gather it into giant clouds and eventually condense it into a supermassive black hole. In addition to explaining the existence of very early supermassive black holes, the finding lends support for the existence of a kind of dark matter capable of decaying into particles such as photons.

Researchers have developed new analytical methods to rapidly analyze fuels and complex petroleum products by using high-resolution mass spectrometry.