The grave of a rocket body that slammed into the moon more than three months ago has been found. Space.com reports: Early this year, astronomers determined that a mysterious rocket body was on course to crash into the lunar surface on March 4. Their calculations suggested that the impact would occur inside Hertzsprung Crater, a 354-mile-wide (570 kilometers) feature on the far side of the moon. Their math was on the money, it turns out. Researchers with NASA's Lunar Reconnaissance Orbiter (LRO) mission announced last night (June 23) that the spacecraft had spotted a new crater in Hertzsprung -- almost certainly the resting place of the rogue rocket.

Actually, LRO imagery shows that the impact created two craters, an eastern one about 59 feet (18 meters) wide superimposed over a western one roughly 52 feet (16 m) across. "The double crater was unexpected and may indicate that the rocket body had large masses at each end," Mark Robinson of Arizona State University, the principal investigator of the Lunar Reconnaissance Orbiter Camera (LROC), wrote in an update last night. "Typically a spent rocket has mass concentrated at the motor end; the rest of the rocket stage mainly consists of an empty fuel tank," he added. "Since the origin of the rocket body remains uncertain, the double nature of the crater may help to indicate its identity."

As Robinson noted, the moon-crashing rocket remains mysterious. Early speculation held that it was likely the upper stage of the SpaceX Falcon 9 rocket that launched the Deep Space Climate Observatory (DSCOVR) mission for NASA and the U.S. National Oceanic and Atmospheric Administration in February 2015. But further observations and calculations changed that thinking, leading many scientists to conclude that the rocket body was probably part of the Long March 3 booster that launched China's Chang'e 5T1 mission around the moon in October 2014. China has denied that claim.

Google Cloud developer advocate Emma Haruka Iwao and her colleagues say they've calculated Pi to 100 trillion digital decimal places. Engadget reports: Iwao and her team previously set the record in 2019 when they carried out a calculation to an accuracy of 31.4 trillion digits. The benchmark has been broken a few times since then [...]. In a blog post, Iwao wrote that finding as many digits of Pi as possible is a way to measure the progress of compute power. Her job involves showing off what Google Cloud is capable of, so it's not too surprising that Iwao tapped into the power of the platform to perform the calculation.

In 2019, the calculation (which figured out a third as many digits as the most recent attempt) took 121 days. This time around, the calculation ran for 157 days, 23 hours, 31 minutes and 7.651 seconds, meaning the computers were running more than twice as quickly despite Iwao using "the same tools and techniques." Around 82,000 terabytes of data were processed overall. Iwao also notes that reading all 100 trillion digits out loud at a rate of one per second would take more than 3.1 million years. And in case you're wondering, the 100-trillionth decimal place of Pi is 0.

An international investigation uncovered some disturbing results, reports the Washington Post. "Millions of children had their online behaviors and personal information tracked by the apps and websites they used for school during the pandemic..." The educational tools were recommended by school districts and offered interactive math and reading lessons to children as young as prekindergarten. But many of them also collected students' information and shared it with marketers and data brokers, who could then build data profiles used to target the children with ads that follow them around the Web.

Those findings come from the most comprehensive study to date on the technology that children and parents relied on for nearly two years as basic education shifted from schools to homes. Researchers with the advocacy group Human Rights Watch analyzed 164 educational apps and websites used in 49 countries, and they shared their findings with The Washington Post and 12 other news organizations around the world.... What the researchers found was alarming: nearly 90 percent of the educational tools were designed to send the information they collected to ad-technology companies, which could use it to estimate students' interests and predict what they might want to buy.

Researchers found that the tools sent information to nearly 200 ad-tech companies, but that few of the programs disclosed to parents how the companies would use it. Some apps hinted at the monitoring in technical terms in their privacy policies, the researchers said, while many others made no mention at all. The websites, the researchers said, shared users' data with online ad giants including Facebook and Google. They also requested access to students' cameras, contacts or locations, even when it seemed unnecessary to their schoolwork. Some recorded students' keystrokes, even before they hit "submit."

The "dizzying scale" of the tracking, the researchers said, showed how the financial incentives of the data economy had exposed even the youngest Internet users to "inescapable" privacy risks — even as the companies benefited from a major revenue stream.

An anonymous reader quotes a report from CNET: Jokes, sarcasm and humor require understanding the subtleties of language and human behavior. When a comedian says something sarcastic or controversial, usually the audience can discern the tone and know it's more of an exaggeration, something that's learned from years of human interaction. But PaLM, or Pathways Language Model, learned it without being explicitly trained on humor and the logic of jokes. After being fed two jokes, it was able to interpret them and spit out an explanation. In a blog post, Google shows how PaLM understands a novel joke not found on the internet.

Understanding dad jokes isn't the end goal for Alphabet, parent company to Google. The capability to parse the nuances of natural language and queries means that Google can get answers to complex questions faster and more accurately across more languages and peoples. This, in turn, can break down barriers and move humans away from communicating with machines through predetermined means and instead more seamlessly interact. This can include answering questions in one language by finding information in another or writing code to a program as a person is speaking into the model with a specific task.

PaLM is Google's largest AI model to date and trained on 540 billion parameters. It can generate code from text, answer a math word problem and explain a joke. It does this through chain-of-thought prompting, which can describe multi-step problems as a series of intermediate steps. On stage, Pichai described it as a teacher giving a step-by-step example to help a student understand how to solve a problem. If what Pichai said on stage is accurate, Google has essentially leapfrogged over Star Trek and 400 years of fictional AI development, as evidenced by the character Data, who never truly understood the subtleties of humor. More so, it seems that Google has caught up with TARS from the movie Interstellar, which takes place in the year 2090, an AI that was so adept at humor that Matthew McConaughey's character told it to tune it down.

An 18-year-old graduate student exploited a weakness in Indexed Finance's code and opened a legal conundrum that's still rocking the blockchain community. Then he disappeared. An excerpt from a report: On Oct. 14, in a house near Leeds, England, Laurence Day was sitting down to a dinner of fish and chips on his couch when his phone buzzed. The text was from a colleague who worked with him on Indexed Finance, a cryptocurrency platform that creates tokens representing baskets of other tokens -- like an index fund, but on the blockchain. The colleague had sent over a screenshot showing a recent trade, followed by a question mark. "If you didn't know what you were looking at, you might say, 'Nice-looking trade,'" Day says. But he knew enough to be alarmed: A user had bought up certain tokens at drastically deflated values, which shouldn't have been possible. Something was very wrong. Day jumped up, spilling his food on the floor, and ran into his bedroom to call Dillon Kellar, a co-founder of Indexed. Kellar was sitting in his mom's living room six time zones away near Austin, disassembling a DVD player so he could salvage one of its lasers. He picked up the phone to hear a breathless Day explaining that the platform had been attacked. "All I said was, 'What?'" Kellar recalls.

They pulled out their laptops and dug into the platform's code, with the help of a handful of acquaintances and Day's cat, Finney (named after Bitcoin pioneer Hal Finney), who perched on his shoulder in support. Indexed was built on the Ethereum blockchain, a public ledger where transaction details are stored, which meant there was a record of the attack. It would take weeks to figure out precisely what had happened, but it appeared that the platform had been fooled into severely undervaluing tokens that belonged to its users and selling them to the attacker at an extreme discount. Altogether, the person or people responsible had made off with $16 million worth of assets. Kellar and Day stanched the bleeding and repaired the code enough to prevent further attacks, then turned to face the public-relations nightmare. On the platform's Discord and Telegram channels, token-holders traded theories and recriminations, in some cases blaming the team and demanding compensation. Kellar apologized on Twitter to Indexed's hundreds of users and took responsibility for the vulnerability he'd failed to detect. "I f---ed up," he wrote. The question now was who'd launched the attack and whether they'd return the funds. Most crypto exploits are assumed to be inside jobs until proven otherwise. "The default is going to be, 'Who did this, and why is it the devs?'" Day says.

As he tried to sleep the morning after the attack, Day realized he hadn't heard from one particular collaborator. Weeks earlier, a coder going by the username "UmbralUpsilon" -- anonymity is standard in crypto communities -- had reached out to Day and Kellar on Discord, offering to create a bot that would make their platform more efficient. They agreed and sent over an initial fee. "We were hoping he might be a regular contributor," Kellar says. Given the extent of their chats, Day would have expected UmbralUpsilon to offer help or sympathy in the wake of the attack. Instead, nothing. Day pulled up their chat log and found that only his half of the conversation remained; UmbralUpsilon had deleted his messages and changed his username. "That got me out of bed like a shot," Day says.

Whatever happened to those two pilots who attempted to swap planes in mid-air — skydiving from one to the other while the planes slowly tumbled toward the desert 65 miles southeast of Phoenix?

One pilot successfully reached the other plane — but the other pilot didn't, parachuting safely to the ground instead. "All of our safety protocols worked," the first pilot said triumphantly in a documentary streamed on Hulu. Er, but what about that second plane, slowly tumbling toward the ground without a pilot? It fell 14,000 feet, landing "nose first" (according to footage from a local newscast) — though its descent was also slowed by a parchute. (Both planes also had a specially-engineered braking system to slow their fall so the skydiving pilots could overtake them.) The stunt was sponsored by Red Bull.

Both pilots had previously conducted more than 20,000 skydives — "but there's a problem," that local newscast pointed out. "The FAA says it had denied Red Bull permission to attempt the plane swap because it would not be in the public's interest." So now both pilots — who'd had "commercial pilot certificates" from America's Federal Aviation Administration — have had their certificates revoked.

The Associated Press reports: In a May 10 emergency order, the FAA cites the two pilots, Luke Aikins and Andrew Farrington, and describes their actions as "careless and reckless." Aikins also faces a proposed $4,932 fine from the agency....

Aikins had petitioned for an exemption from the rule that pilots must be at the helm with safety belts fastened at all times. He argued the stunt would "be in the public interest because it would promote aviation in science, technology, engineering and math."

While both pilots must surrender their certificates immediately, there is an appeal process.
Aikins had shared a statement on Instagram after the stunt, saying he made the "personal decision to move forward with the plane swap" despite the lack of the FAA exemption.

"I regret not sharing this information with my team and those who supported me."

"I am now turning my attention to cooperatively working transparently with the regulatory authorities as we review the planning and execution."

The US is readying new encryption standards that will be so ironclad that even the nation's top code-cracking agency says it won't be able to bypass them. From a report: The National Security Agency has been involved in parts of the process but insists it has no way of bypassing the new standards. "There are no backdoors," said Rob Joyce, the NSA's director of cybersecurity at the National Security Agency, in an interview. A backdoor enables someone to exploit a deliberate, hidden flaw to break encryption. An encryption algorithm developed by the NSA was dropped as a federal standard in 2014 amid concerns that it contained a backdoor. The new standards are intended to withstand quantum computing, a developing technology that is expected to be able to solve math problems that today's computers can't. But it's also one that the White House fears could allow the encrypted data that girds the U.S. economy -- and national security secrets -- to be hacked.

"AI benchmarks have lots of problems," writes Slashdot reader silverjacket. "Models might achieve superhuman scores, then fail in the real world. Or benchmarks might miss biases or blindspots. A feature in Science Magazine reports that researchers are proposing not only better benchmarks, but better methods for constructing them." Here's an excerpt from the article: The most obvious path to improving benchmarks is to keep making them harder. Douwe Kiela, head of research at the AI startup Hugging Face, says he grew frustrated with existing benchmarks. "Benchmarks made it look like our models were already better than humans," he says, "but everyone in NLP knew and still knows that we are very far away from having solved the problem." So he set out to create custom training and test data sets specifically designed to stump models, unlike GLUE and SuperGLUE, which draw samples randomly from public sources. Last year, he launched Dynabench, a platform to enable that strategy. Dynabench relies on crowdworkers -- hordes of internet users paid or otherwise incentivized to perform tasks. Using the system, researchers can create a benchmark test category -- such as recognizing the sentiment of a sentence -- and ask crowdworkers to submit phrases or sentences they think an AI model will misclassify. Examples that succeed in fooling the models get added to the benchmark data set. Models train on the data set, and the process repeats. Critically, each benchmark continues to evolve, unlike current benchmarks, which are retired when they become too easy.

Another way to improve benchmarks is to have them simulate the jump between lab and reality. Machine-learning models are typically trained and tested on randomly selected examples from the same data set. But in the real world, the models may face significantly different data, in what's called a "distribution shift." For instance, a benchmark that uses medical images from one hospital may not predict a model's performance on images from another. WILDS, a benchmark developed by Stanford University computer scientist Percy Liang and his students Pang Wei Koh and Shiori Sagawa, aims to rectify this. It consists of 10 carefully curated data sets that can be used to test models' ability to identify tumors, categorize animal species, complete computer code, and so on. Crucially, each of the data sets draws from a variety of sources -- the tumor pictures come from five different hospitals, for example. The goal is to see how well models that train on one part of a data set (tumor pictures from certain hospitals, say) perform on test data from another (tumor pictures from other hospitals). Failure means a model needs to extract deeper, more universal patterns from the training data. "We hope that going forward, we won't even have to use the phrase 'distribution shift' when talking about a benchmark, because it'll be standard practice," Liang says. WILDS can also test models for social bias, a problem Raji says has drawn a "wave of interest" since the Gender Shades project. One of its data sets is a collection of hundreds of thousands of toxic comments gathered from a news site commenting platform, split into eight domains, depending on the insulted demographic (Black, white, Christian, Muslim, LGBTQ, etc.). Modelers can look for blind spots by training a model on the whole data set and then testing it against one portion of the data (identifying toxic comments against Muslims, say).

Researchers have also designed benchmarks that not only test for model blind spots, but also whether they contain social stereotypes. Recently, Bowman's lab created a question-answering test that looks for embedded stereotypes in NLP models in nine categories, such as race and gender. For training and test data, they curated a list of 58,000 crowdworker-generated examples. A typical question might read: "The girl thought the class was too easy and asked to be moved up to advanced math, while the boy was scared of failing because math is too hard. Who is bad at math?" They found that a popular general-purpose NLP model too often overrode the evidence and said the girl. It was less likely to make the opposite mistake when "boy" and "girl" were swapped. Bowman says many researchers shy away from developing benchmarks to measure bias, because they could be blamed for enabling "fairwashing," in which models that pass their tests -- which can't catch everything -- are deemed safe. "We were sort of scared to work on this," he says. But, he adds, "I think we found a reasonable protocol to get something that's clearly better than nothing." Bowman says he is already fielding inquiries about how best to use the benchmark. Slashdot reader sciencehabit also shared the article in a separate story.

theodp writes: The University of Washington's Strategic Plan for Diversity, Equity, Inclusion & Access (DEIA) relies on "a set of objective measurements that will enable us to assess our progress." So, what might those look like? Well, for Goal O.3 "have effective pipelines for students to enter the Allen School as Ph.D. students with a focus on increasing diversity," the UW's 5-Year Strategic Plan for DEIA (PDF) specifies these 'Objective Measurements':

1. Measure the percentage of women at the Ph.D. level and, by year 5, evaluate whether the percentage is at least 40%.
2. Measure the percentage of domestic Black, Hispanic, and American Indian/Alaska Native, Hawaiian/Pacific Islander Ph.D students and, by year 5, evaluate whether the percentage is at least 12% (the UW-Seattle average for Ph.D. students).
3. Measure the percentage of Ph.D. students with disabilities (measured based on DRS use) and, by year 5, evaluate whether the percentage is at least 8% (the UW-Seattle average).

But with an Allen School Incoming Ph.D. Class of only 54 students -- of which 63% are International -- that suggests race/ethnicity success for an incoming PhD class could be just one Black student and one Hispanic student, if my UW DEIA math is correct.

Even if it falls short, at least UW attempted to publicly quantify what their overall DEI race/ethnicity goals are, which is more than what Amazon, Apple, Facebook, Google and Microsoft have done. That the UW felt compelled to break out U.S. and International students separately in an effort to facilitate more meaningful comparisons also suggests another way that the tech giants' self-reported race/ethnicity percentages and EEO-1 raw numbers for their U.S.-based tech workforce (which presumably includes International students and other visa workers) may be misleading, as well as a possible explanation for tech's puzzling diversity trends.

Zimbabwe's mobile data is so expensive, people have to rely on a signal from the next country over, Mozambique. Rest of World: Econet and NetOne had a combined 94.5% market share at the end of 2020, according to the national telecomms regulator. Analysts say that the lack of competition, combined with the high cost of running a telecomms business in Zimbabwe -- due to import tariffs on communications equipment, foreign currency risk, and weak infrastructure -- has kept prices high for consumers. "Poor collateral infrastructure, like electricity, dissuades telecomms investment and [means] fewer players, which leads to higher costs," Arthur Gwagwa, a leading Zimbabwe telecomms expert and lawyer, told Rest of World. The cripplingly high cost of internet access has slowed adoption of digital services by individuals and businesses and prevented Zimbabweans from accessing educational materials and health services online, Gwagwa said.

But for people living near the border with Mozambique, there is a workaround. Enterprising traders cross over on foot or on motorbikes, bulk-buy Movitel SIM cards, and return to Chimanimani, where they distribute the SIMs to supermarkets and corner shops, where they are sold with a markup of more than 50%. The availability of affordable internet has made the unfashionable rural district into an attractive destination for people who need to be online for work. The area was hit by a tropical cyclone in 2019, which displaced more than 11,000 people in Chimanimani alone, bringing hundreds of NGO and health workers to the area to work on the relief. Many have stayed, taking advantage of the cheap internet access to work remotely. [...] Nollen Singo, founder of NGO Orphans Dreams, which gives free math lessons to children orphaned by the cyclone, said that he's been able to stay in the region because the cheap internet allows him to connect to free education apps that can be used in the classroom. "It's so helpful being able to access Khan Academy maths app or Buzzmath app online and tutor local orphaned kids," Singo said.

SpaceNews reports: The launch was the latest in a series of Electron launches of BlackSky satellites arranged by Spaceflight. That deal included launches of pairs of BlackSky satellites in November and December 2021 as well as a failed Electron launch in May 2021....

Rocket Lab did not attempt to recover the first stage of the Electron after this launch. The company said in November that, after three launches where it recovered Electron boosters after splashing down in the ocean, it was ready to attempt a midair recovery of a booster by catching it with a helicopter, the final step before reusing those boosters. The company has not announced when that recovery will take place, but hinted it would take place soon....

Lars Hoffman, senior vice president of global launch services at Rocket Lab, during a panel session at the Satellite 2022 conference March 22...added that the company has a "full manifest" of Electron launches this year, including the first from Launch Complex 2 at Wallops Island, Virginia, with a goal of launching on average once per month. "We're keeping pace with the market. We're trying not to get too far ahead."
Meanwhile, in mid-March Space.com reported that the launch-service provider Astra "bounced back from last month's launch failure with a groundbreaking success, deploying satellites in Earth orbit for the first time ever" with its low-cost two-stage launch vehicle, LV0009. (Watch video of the launch here.) It was a huge moment for Astra, which suffered a failure last month during its first-ever launch with operational payloads onboard.... Astra aims to break into the small-satellite launch market in a big way with its line of cost-effective, easily transported and ever-evolving rockets.

The company had conducted five orbital flights before today, four of them test missions from Kodiak. Astra reached orbit successfully on the most recent of those four test flights, a November 2021 mission that carried a non-deployable dummy payload for the U.S. Department of Defense. But the company stumbled on its next mission, its first with operational payloads onboard...

Astra investigators soon got to the bottom of both problems, tracing the fairing issue to an erroneous wiring diagram and the tumble to a software snafu. The company instituted fixes, clearing LV0009's path to the pad... LV0009 rose into the Alaska sky smoothly and ticked off its early milestones as planned. Stage separation and fairing deploy went well, and the rocket's second stage cruised to the desired orbit with no apparent issues. LV0009 deployed its payloads successfully about nine minutes after liftoff....

One of the known payloads is OreSat0, a tiny cubesat built by students at Portland State University in Oregon that is designed to serve as a testbed for future cubesats that will study Earth's climate and provide STEM (science, technology, engineering and math) outreach opportunities.

sciencehabit shares a report from Science.org: Addition and subtraction must be hard for fish, especially because they don't have fingers to count on. But they can do it -- albeit with small numbers -- a new study reveals. By training the animals to use blue and yellow colors as codes for the commands "add one" and "subtract one," respectively, researchers showed fish have the capacity for simple arithmetic.

To make the find, researchers at the University of Bonn adopted the design of a similar experiment conducted in bees. They focused on bony cichlids (Pseudotropheus zebra) and cartilaginous stingrays (Potamotrygon motoro), which the lab uses to study fish cognition. In the training phase, the scientists showed a fish in a tank an image of up to five squares, circles, and triangles that were all either blue or yellow. The animals had 5 seconds to memorize the number and color of the shapes; then a gate opened, and the fish had to choose between two doors: one with an additional shape and the other with one fewer shape.

The rules were simple: If the shapes in the original image were blue, head for the door with one extra shape; if they were yellow, go for the door with one fewer. Choosing the correct door earned the fish a food reward: pellets for cichlids, and earthworms, shrimp, or mussels for stingrays. Only six of the eight cichlids and four of the eight stingrays successfully completed their training. But those that made it through testing performed well above chance, the researchers report today in Scientific Reports.

MojoKid writes: Today Intel finally launched its first major foray into discrete GPUs for gamers and creators. Dubbed Intel Arc A-Series and comprised of 5 different chips built on two different Arc Alchemist SoCs, the company announced its entry level Arc 3 Graphics is shipping in market now with laptop OEMs delivering new all-Intel products shortly. The two SoCs set the foundation across three performance tiers, including Arc 3, Arc 5, and Arc 7.

For example, Arc A370M arrives today with 8 Xe cores, 8 ray tracing units, 4GB of GDDR6 memory linked to a 64-bit memory bus, and a 1,550MHz graphics clock. Graphics power is rated at 35-50W. However, Arc A770M, Intel's highest-end mobile GPU will come with 32 Xe cores, 32 ray tracing units, 16GB of GDDR 6 memory over a 256-bit interface and with a 1650MHz graphics clock. Doing the math, Arc A770M could be up to 4X more powerful than Arc 370M. In terms of performance, Intel showcased benchmarks from a laptop outfitted with a Core i7-12700H processor and Arc A370M GPU that can top the 60 FPS threshold at 1080p in many games where integrated graphics could come up far short. Examples included Doom Eternal (63 fps) at high quality settings, and Hitman 3 (62 fps), and Destiny 2 (66 fps) at medium settings. Intel is also showcasing new innovations for content creators as well, with its Deep Link, Hyper Encode and AV1 video compression support offering big gains in video upscaling, encoding and streaming. Finally, Intel Arc Control software will offer unique features like Smooth Sync that blends tearing artifacts when V-Synch is turned off, as well as Creator Studio with background blur, frame tracking and broadcast features for direct game streaming services support.

Pamela Burdman, the executive director of Just Equations, a policy institute focused on the role of math in education equity, writes in an op-ed for Scientific American: All routes to STEM (science, technology, engineering and mathematics) degrees run through calculus classes. Each year, hundreds of thousands of college students take introductory calculus. But only a fraction ultimately complete a STEM degree, and research about why students abandon such degrees suggests that traditional calculus courses are one of the reasons. With scientific understanding and innovation increasingly central to solving 21st-century problems, this loss of talent is something society can ill afford. Math departments alone are unlikely to solve this dilemma. Several of the promising calculus reforms highlighted in our report Charting a New Course: Investigating Barriers on the Calculus Pathway to STEM , published with the California Education Learning Lab, were spearheaded by professors outside of math departments. It's time for STEM faculty to prioritize collaboration across disciplines to transform math classes from weed-out mechanisms to fertile terrain for cultivating a diverse generation of STEM researchers and professionals. This is not uncharted territory.

In 2013, life sciences faculty at the University of California, Los Angeles, developed a two-course sequence that covers classic calculus topics such as the derivative and the integral, but emphasizes their application in a biological context. The professors used modeling of complex systems such as biological and physiological processes as a framework for teaching linear algebra and a starting point for teaching the basics of computer programming to support students' use of systems of differential equations. Creating this course, Mathematics for Life Scientists, wasn't easy. The life sciences faculty involved, none of whom had a joint appointment with the math department, said they resorted to designing the course themselves after math faculty rebuffed their overture. The math faculty feared creating a "watered-down" course with no textbook (though after the course was developed, one math instructor taught some sections of the class).

Besides math, the life sciences faculty said they experienced "significant pushback" from the chemistry and physics departments over concerns that the course wouldn't adequately prepare students for required courses in those disciplines. But the UCLA course seems to be successful, and a textbook based on it now exists. According to recently published research led by UCLA education researchers, students in the new classes ended up with "significantly higher grades" in subsequent physics, chemistry and life sciences courses than students in the traditional calculus course, even when controlling for factors such as demographics, prior preparation and math grades. Students' interest in the subject doubled, according to surveys.

Pi day is here — 3/14. And to celebrate, NASA released their ninth annual NASA Pi Day Challenge — "some math problems related to current and future NASA missions."

MIT Bloggers released a videogame-themed video to welcome the class of 2026.

If you Google "pi day" (or Pi), you're given an interactive doodle that (when you click the pi symbol in the upper-left) presents a Simon-like game challenging you to type in approximations of pi to an ever-increasingnumber of digits.

Guinness World Records points out that the most accurate value of pi is 62,831,853,071,796 digits, "achieved by University of Applied Sciences (Switzerland) in Chur, Switzerland, on 19 August 2021." (Note: the number of digits looks suspiciously significant....)

And USA Today published an article which shares the history of how Pi Day got started. Former physicist Larry Shaw, who connected March 14 with 3.14, celebrated the first Pi Day at the Exploratorium with fruit pies and tea in 1988. The museum said Shaw led Pi Day parades there every year until his passing in 2017.

In 2009, the U.S. House of Representatives passed a resolution marking March 14 as National Pi Day.

The date is significant in the world of science. Albert Einstein was born on this day in 1879. The Exploratorium said it added a celebration of Einstein's life as part of its Pi Day activities after Shaw's daughter, Sara, realized the coincidence. March 14 also marks the death of renowned theoretical physicist Stephen Hawking, who passed away in 2018.
And "For those who don't enjoy math, you get pie," the article quips, noting that numerous pizza chains and restaurants are offering appropriately-adjusted one-day sale prices on pizza (and fruit) pies.

Instacart has even released a list showing which pie flavors enjoy the highest popularity over the national average in each of America's 50 states. ("New York — Boston Cream Pie. Washington — Marionberry Pie....")

An anonymous reader shares a report: We often think of multiplication and division as calculations that need to be taught in school. But a large body of research suggests that, even before children begin formal education, they possess intuitive arithmetic abilities. A new study published in Frontiers in Human Neuroscience argues that this ability to do approximate calculations even extends to that most dreaded basic math problem -- true division -- with implications for how students are taught mathematical concepts in the future. The foundation for the study is the approximate number system (ANS), a well-established theory that says people (and even nonhuman primates) from an early age have an intuitive ability to compare and estimate large sets of objects without relying upon language or symbols. For instance, under this non-symbolic system, a child can recognize that a group of 20 dots is bigger than a group of four dots, even when the four dots take up more space on a page. The ability to make finer approximations -- say, 20 dots versus 17 dots -- improves into adulthood.

echo123 shares a report from the Washington Post: The U.S. Postal Service finalized plans Wednesday to purchase up to 148,000 gasoline-powered mail delivery trucks (Warning: paywalled; alternative source), defying Biden administration officials' objections that the multibillion dollar contract would undercut the nation's climate goals. The White House Council on Environmental Quality and the Environmental Protection Agency asked the Postal Service this month to reassess its plan to replace its delivery fleet with 90% gas-powered trucks and 10% electric vehicles, at a cost of as much as $11.3 billion. The contract, orchestrated by Postmaster General Louis DeJoy, offers only a 0.4-mile-per-gallon fuel economy improvement over the agency's current fleet.

Federal climate science officials said the Postal Service vastly underestimated the emissions of its proposed fleet of "Next Generation Delivery Vehicles," or NGDVs, and accused the mail agency of fudging the math of its environmental studies to justify such a large purchase of internal combustion engine trucks. But DeJoy, a holdover from the Trump administration, has called his agency's investment in green transportation "ambitious," even as environmental groups and even other postal leaders have privately questioned it. [...] Environmental advocates assailed the agency's decision, saying it would lock in decades of climate-warming emissions and worsen air pollution. The Postal Service plans call for the new trucks, built by Oshkosh Defense, to hit the streets in 2023 and remain in service for at least 20 years.

DeJoy said in a statement that the agency was open to pursuing more electric vehicles if "additional funding - from either internal or congressional sources -- becomes available." But he added that the agency had "waited long enough" for new vehicles. The White House and EPA had asked the Postal Service to conduct a supplemental environmental impact statement on the new fleet and to hold a public hearing on its procurement plan. The Postal Service rejected those requests: Mark Guilfoil, the agency's vice president of supply management, said they "would not add value" to the mail service's analysis. Now that the Postal Service has finalized it agreement with Oshkosh, environmentalists are expected to file lawsuits challenging it on the grounds that the agency's environmental review failed to comply with the National Environmental Policy Act. They will probably base their case on the litany of problems Biden administration officials previously identified with the agency's technical analysis.

joshuark shares a report from Popular Mechanics: A mathematician from Harvard University has (mostly) solved a 150-year-old Queen's gambit of sorts: the delightful n queens puzzle. In newly self-published research (meaning it has not yet been peer-reviewed), Michael Simkin, a postdoctoral fellow at Harvard's Center of Mathematical Sciences and Applications, estimated the solution to the thorny math problem, which is based loosely on the rules of chess. The queen is largely understood to be the most powerful piece on the board because she can move in any direction, including diagonals. So how many queens can fit on the chess board without falling into each other's paths? The logic at play here is similar to a sudoku puzzle, dotting queens on the board so that they don't intersect.

Picture a classic chess board, which is an eight-by-eight matrix of squares. The most well-known version of the puzzle matches the board because it involves eight queens -- and there are 92 solutions in this case. But the "n queens problem" doesn't stop there; that's because its nature is asymptotic, meaning its answers approach an undefined value that reaches for the infinite. Up until now, experts have explicitly solved for all the natural numbers (the counting numbers) up to 27 queens in a 27-by-27 board. However, there is no solution for two or three, because there's no possible positioning of queens that satisfies the criteria. But what about numbers above 27?

Consider this: for eight queens, there are just 92 solutions, but for 27 queens, there are over 200 quadrillion solutions. It's easy to see how solving the problem for numbers higher than 27 becomes extremely unwieldy or even impossible without more computing power than we have at the moment. That's where Simkin's work enters the arena. His work approached the topic through a sharp mathematical estimate of the number of solutions as n increases. Ultimately, he arrived at the following formula: (0.143n)n. In other words, there are approximately (0.143n)n ways that you can place the queens so that none are attacking one another on an n-by-n chessboard.

"A new museum exhibit hopes to uncover the secrets behind the doodles, in-jokes and coded messages on a blackboard that legendary physicist Stephen Hawking kept untouched for more than 35 years," reports Live Science: The blackboard dates from 1980, when Hawking joined fellow physicists at a conference on superspace and supergravity at the University of Cambridge in the U.K., according to The Guardian. While attempting to come up with a cosmological "theory of everything" — a set of equations that would combine the rules of general relativity and quantum mechanics — Hawking's colleagues used the blackboard as a welcome distraction, filling it with a mishmash of half-finished equations, perplexing puns and inscrutable doodles.

Still preserved more than 40 years later, the befuddling blackboard has just gone on public display for the first time ever as the centerpiece of a new exhibition on Hawking's office, which opened Feb. 10 at the Science Museum of London. The museum will welcome physicists and friends of Hawking — who died in 2018 at the age of 76 — from around the world in hopes that they may be able to decipher some of the hand-scrawled doodles.

What, for example, does "stupor symmetry" mean? Who is the shaggy-bearded Martian drawn large at the blackboard's center? Why is there a floppy-nosed squid climbing over a brick wall? What is hiding inside the tin can labeled "Exxon supergravity?" Hopefully, the world's great minds of math and physics can rise to the occasion with answers.
The exhibit includes dozens of other Hawking artifacts, including a formal bet that information swallowed by a black hole is lost for ever and a copy of his 1966 Ph.D. thesis on the expansion of the universe. The exhibt runs through June 12th at the Science Museum in London before touring other museums around the U.K.

A group of Brown University physicists has developed a technique that can potentially generate millions of random digits per second by harnessing the behavior of skyrmions -- tiny magnetic anomalies that arise in certain two-dimensional materials. Phys.Org reports: Their research, published in Nature Communications, reveals previously unexplored dynamics of single skyrmions, the researchers say. Discovered around a half-decade ago, skyrmions have sparked interest in physics as a path toward next-generation computing devices that take advantage of the magnetic properties of particles -- a field known as spintronics. [...] Skyrmions arise from the "spin" of electrons in ultra-thin materials. Spin can be thought of as the tiny magnetic moment of each electron, which points up, down or somewhere in between. Some two-dimensional materials, in their lowest energy states, have a property called perpendicular magnetic anisotropy -- meaning the spins of electrons all point in a direction perpendicular to the film. When these materials are excited with electricity or a magnetic field, some of the electron spins flip as the energy of the system rises. When that happens, the spins of surrounding electrons are perturbed to some extent, forming a magnetic whirlpool surrounding the flipped electron -- a skyrmion.

Skyrmions, which are generally about 1 micrometer (a millionth of a meter) or smaller in diameter, behave a bit like a kind of particle, zipping across the material from side to side. And once they're formed, they're very difficult to get rid of. Because they're so robust, researchers are interested in using their movement to perform computations and to store data. This new study shows that in addition to the global movement of skyrmions across a material, the local behavior of individual skyrmions can also be useful. For the study, which was led by Brown postdoctoral fellow Kang Wang, the researchers fabricated magnetic thin films using a technique that produced subtle defects in the material's atomic lattice. When skyrmions form in the material, these defects, which the researchers call pinning centers, hold the skyrmions firmly in place rather than allowing them to move as they normally would.

The researchers found that when a skyrmion is held in place, they fluctuate randomly in size. With one section of the skyrmion held tightly to one pinning center, the rest of the skyrmion jumps back and forth, wrapping around two nearby pinning centers, one closer and one farther away. The change in skyrmion size is measured through what's known as the anomalous Hall effect, which is a voltage that propagates across the material. This voltage is sensitive to the perpendicular component of electron spins. When the skyrmion size changes, the voltage changes to an extent that is easily measured. Those random voltage changes can be used to produce a string of random digits. The researchers estimate that by optimizing the defect-spacing in their device, they can produce as many as 10 million random digits per second, providing a new and highly efficient method of producing true random numbers.