Wednesday, July 1st, 2020

Time	Event
11:20a	What is the Covid-19 data tsunami telling policymakers? Uncertainty about the course of the Covid-19 pandemic continues, with more than 2,500,000 known cases and 126,000 deaths in the United States alone. How to contain the virus, limit its damage, and address the deep-rooted health and racial inequalities it has exposed are now urgent topics for policymakers. Earlier this spring, 300 data scientists and health care professionals from around the world joined the MIT Covid-19 Datathon to see what insights they might uncover. “It felt important to be a part of,” says Ashley O’Donoghue, an economist at the Center for Healthcare Delivery Science at Beth Israel Deaconess Medical Center. “We thought we could produce something that might make a difference.” Participants were free to explore five tracks: the epidemiology of Covid-19, its policy impacts, its disparate health outcomes, the pandemic response in New York City, and the wave of misinformation Covid-19 has spawned. After splitting into teams, participants were set loose on 20 datasets, ranging from county-level Covid-19 cases compiled by The New York Times to a firehose of pandemic-related posts released by Twitter.  The participants, and the dozens of mentors who guided them, hailed from 44 countries and every continent except for Antarctica. To encourage the sharing of ideas and validation of results, the event organizers — MIT Critical Data, MIT Hacking Medicine, and the Martin Trust Center for MIT Entrepreneurship — required that all code be made available. In the end, 47 teams presented final projects, and 10 were singled out for recognition by a panel of judges. Several teams are now writing up their results for peer-reviewed publication, and at least one team has posted a paper. “It’s really hard to find research collaborators, especially during a crisis,” says Marie-Laure Charpignon, a PhD student with MIT’s Institute for Data, Systems, and Society, who co-organized the event. “We’re hoping that the teams and mentors that found each other will continue to explore these questions.” In a pre-print on medRxiv, O’Donoghue and her teammates identify the businesses most at risk for seeding new Covid-19 infections in New York, California, and New England. Analyzing location data from SafeGraph, a company that tracks commercial foot traffic, the team built a transmission-risk index for businesses that in the first five months of this year drew the most customers, for longer periods of time, and in more crowded conditions, due to their modest size.  Comparing this risk index to new weekly infections, the team classified 16.3 percent of countywide businesses as “superspreaders,” most of which were restaurants and hotels. A 1 percent increase in the density of super-spreader businesses, they found, was linked to a 5 percent jump in Covid-19 cases. The team is now extending its analysis to all 50 states, drilling down to ZIP code-level data, and building a decision-support tool to help several hospitals in their sample monitor risk as communities reopen. The tool will also let policymakers evaluate a wide range of statewide reopening policies. “If we see a second wave of infections, we can determine which policies actually worked,” says O’Donoghue. The datathon model for collaborative research is the brainchild of Leo Anthony Celi, a researcher at MIT and staff physician at Beth Israel Deaconess Medical Center. The events are usually coffee-fueled weekend affairs. But this one took place over a work week, and amid a global lockdown, with teammates having to meet and collaborate over Slack and Zoom. With no coffee breaks or meals, they had fewer chances to network, says Celi. But the virtual setting allowed more people to join, especially mentors, who could participate without taking time off to travel. It also may have made teams more efficient, he says.  After analyzing communication logs from the event, he and his colleagues found evidence that the most-successful teams lacked a clear leader. Everyone seemed to chip in. “In face-to-face events, leaders and followers emerge as they project their expertise and personalities,” he says. “But on Slack, we saw less hierarchy. The most successful teams showed high levels of enthusiasm and conversational turn-taking.” Another advantage of the virtual setting is that teams straddling several time zones could work, literally, around the clock. “You could post a message on Slack and someone would see it an hour or two later,” says Jane E. Valentine, a biomedical engineer at the Johns Hopkins University Applied Physics Laboratory. “There was a constant sense of engagement. I might be sleeping and doing nothing, but the wheels were still turning.” Valentine collaborated with a doctor and three data scientists in Europe, the United States, and Canada to analyze anonymized medical data from 4,000 Covid-19 patients to build predictive models for how long a new patient might need to be hospitalized, and their likelihood of dying. “It’s really useful for a clinician to know if a patient is likely to stabilize or go downhill,” she says. “You may want to monitor or treat them more aggressively.” Hospital administrators can also decide whether to open up additional wards, she adds. Among their findings, the team found that a fever and shortness of breath were top symptoms for predicting both a long hospital stay and a high risk of death for patients, and that general respiratory symptoms were also a strong predictor of death. Valentine cautions that the results are preliminary, and based on incomplete data that the team is currently working to fill.  One of the pandemic’s cruel realities is that it has hit the poorest and most vulnerable people in society hardest. Datathon participants also examined Covid-19’s social impact, from analyzing the impact of releasing prisoners to devising tools for people to verify the flood of claims about the disease now circulating online.  Amber Nigam, a data scientist based in New Delhi, India, has watched conspiracy theories spread and multiply on social media as contagiously as Covid-19 itself. “There’s a lot of anxiety,” he says. “Even my parents have shown me news on WhatsApp and asked if it was true.”  As the head of AI for PeopleStrong, a predictive sales startup in San Francisco, California, Nigam is comfortable with natural language processing tools and interested in their potential for fighting fake news. During the datathon, he and his team crawled the web for conspiracy theories circulating in the United States, China, and India, among other countries, and used the data to build an automated fact-checker. If the tool finds the claim to be untrue, it sends the reader to the news source where the claim was first debunked.  “A lot of people in rural settings don’t have access to accurate sources of information,” he says. “It’s super critical for people to have the right facts at their disposal.” Another team looked at Covid-19’s disparate impact on people of color. Lauren Chambers, a technology fellow at the Massachusetts American Civil Liberties Union (ACLU), suggested the project and mentored the team that took it on. State by state, the team found disproportionate death rates among Black and Hispanic people, who are more likely to work “essential” service-industry jobs where they face greater exposure to people infected with the disease. The gap was greatest in South Carolina, where Black individuals account for about half of Covid-19 deaths, but only a third of residents. The team noted that the picture nationally is probably worse, given that 10 states still do not collect race-specific data.  The team also found that poverty and lack of health care access were linked to higher death rates among Black communities, and language barriers were linked to higher death rates among Hispanic individuals. Their findings suggest that economic interventions for Black Americans, and hiring more hospital translators for Hispanic Americans, might be effective policies to reduce inequities in health outcomes. The ACLU can’t afford to hire an army of data scientists to investigate every civil-rights violation the pandemic has brought to light, says Chambers. But collaborative events like this one give community advocates a chance to explore urgent questions they wouldn’t otherwise be able to, she says, and data scientists get to hear new perspectives, too. “There’s a dangerous tendency among data scientists to think that numbers are the beginning and end of any good analysis,” she says. “But data are subjective, and there’s all kinds of other expertise that communities hold.” The event was sponsored by Beth Israel Deaconess Medical Center Innovation Group, Google Cloud, Massachusetts ACLU, and the National Science Foundation’s West Big Data Innovation Hub. (Comment on this)
11:47a	TESS mission discovers massive ice giant The “ice giant” planets Neptune and Uranus are much less dense than rocky, terrestrial planets such as Venus and Earth. Beyond our solar system, many other Neptune-sized planets, orbiting distant stars, appear to be similarly low in density. Now, a new planet discovered by NASA’s Transiting Exoplanet Survey Satellite, TESS, seems to buck this trend. The planet, named TOI-849 b, is the 749th “TESS Object of Interest” identified to date. Scientists spotted the planet circling a star about 750 light years away every 18 hours, and estimate it is about 3.5 times larger than Earth, making it a Neptune-sized planet. Surprisingly, this far-flung Neptune appears to be 40 times more massive than Earth and just as dense. TOI-849 b is the most massive Neptune-sized planet discovered to date, and the first to have a density that is comparable to Earth. “This new planet is more than twice as massive as our own Neptune, which is really unusual,” says Chelsea Huang, a postdoc in MIT’s Kavli Institute for Astrophysics and Space Research, and a member of the TESS science team. “Imagine if you had a planet with Earth’s average density, built up to 40 times the Earth’s mass. It’s quite crazy to think what’s happening at the center of a planet with that kind of pressure.” The discovery is reported today in the journal Nature. The study’s authors include Huang and members of the TESS science team at MIT. A blasted Jupiter? Since its launch on April 18, 2018, the TESS satellite has been scanning the skies for planets beyond our solar system. The project is one of NASA’s Astrophysics Explorer missions and is led and operated by MIT. TESS is designed to survey almost the entire sky by pivoting its view every month to focus on a different patch of the sky as it orbits the Earth. As it scans the sky, TESS monitors the light from the brightest, nearest stars, and scientists look for periodic dips in starlight that may signal that a planet is crossing in front of a star. Data taken by TESS, in the form of a star’s light curve, or measurements of brightness, is first made available to the TESS science team, an international, multi-institute group of researchers led by scientists at MIT. These researchers get a first look at the data to identify promising planet candidates, or TESS Objects of Interest. These are shared publicly with the general scientific community along with the TESS data for further analysis. For the most part, astronomers focus their search for planets on the nearest, brightest stars that TESS has observed. Huang and her team at MIT, however, recently had some extra time to look over data during September and October of 2018, and wondered if anything could be found among the fainter stars. Sure enough, they discovered a significant number of transit-like dips from a star 750 light years away, and soon after, confirmed the existence of TOI-849 b. “Stars like this usually don’t get looked at carefully by our team, so this discovery was a happy coincidence,” Huang says. Follow-up observations of the faint star with a number of ground-based telescopes further confirmed the planet and also helped to determine its mass and density. Huang says that TOI-849 b’s curious proportions are challenging existing theories of planetary formation. “We’re really puzzled about how this planet formed,” Huang says. “All the current theories don’t fully explain why it’s so massive at its current location. We don’t expect planets to grow to 40 Earth masses and then just stop there. Instead, it should just keep growing, and end up being a gas giant, like a hot Jupiter, at several hundreds of Earth masses.” One hypothesis scientists have come up with to explain the new planet’s mass and density is that perhaps it was once a much larger gas giant, similar to Jupiter and Saturn — planets with more massive envelopes of gas that enshroud cores thought to be as dense as the Earth. As the TESS team proposes in the new study, over time, much of the planet’s gassy envelope may have been blasted away by the star’s radiation — not an unlikely scenario, as TOI-849 b orbits extremely close to its host star. Its orbital period is just 0.765 days, or just over 18 hours, which exposes the planet to about 2,000 times the solar radiation that Earth receives from the sun. According to this model, the Neptune-sized planet that TESS discovered may be the remnant core of a much more massive, Jupiter-sized giant. “If this scenario is true, TOI-849 b is the only remnant planet core, and the largest gas giant core known to exist,” says Huang. “This is something that gets scientists really excited, because previous theories can’t explain this planet.” This research was funded, in part, by NASA. (Comment on this)
12:06p	Quantum fluctuations can jiggle objects on the human scale The universe, as seen through the lens of quantum mechanics, is a noisy, crackling space where particles blink constantly in and out of existence, creating a background of quantum noise whose effects are normally far too subtle to detect in everyday objects. Now for the first time, a team led by researchers at MIT LIGO Laboratory has measured the effects of quantum fluctuations on objects at the human scale. In a paper published today in Nature, the researchers report observing that quantum fluctuations, tiny as they may be, can nonetheless “kick” an object as large as the 40-kilogram mirrors of the U.S. National Science Foundation’s Laser Interferometer Gravitational-wave Observatory (LIGO), causing them to move by a tiny degree, which the team was able to measure.  It turns out the quantum noise in LIGO’s detectors is enough to move the large mirrors by 10-20 meters — a displacement that was predicted by quantum mechanics for an object of this size, but that had never before been measured. “A hydrogen atom is 10-10 meters, so this displacement of the mirrors is to a hydrogen atom what a hydrogen atom is to us — and we measured that,” says Lee McCuller, a research scientist at MIT’s Kavli Institute for Astrophysics and Space Research. The researchers used a special instrument that they designed, called a quantum squeezer, to “manipulate the detector’s quantum noise and reduce its kicks to the mirrors, in a way that could ultimately improve LIGO’s sensitivity in detecting gravitational waves,” explains Haocun Yu, a physics graduate student at MIT.  “What’s special about this experiment is we’ve seen quantum effects on something as large as a human,” says Nergis Mavalvala, the Marble Professor and associate head of the physics department at MIT. “We too, every nanosecond of our existence, are being kicked around, buffeted by these quantum fluctuations. It’s just that the jitter of our existence, our thermal energy, is too large for these quantum vacuum fluctuations to affect our motion measurably. With LIGO’s mirrors, we’ve done all this work to isolate them from thermally driven motion and other forces, so that they are now still enough to be kicked around by quantum fluctuations and this spooky popcorn of the universe.” Yu, Mavalvala,  and McCuller are co-authors of the new paper, along with graduate student Maggie Tse and Principal Research Scientist Lisa Barsotti at MIT, along with other members of the LIGO Scientific Collaboration. A quantum kick LIGO is designed to detect gravitational waves arriving at the Earth from cataclysmic sources millions to billions of light years away. It comprises twin detectors, one in Hanford, Washington, and the other in Livingston, Louisiana. Each detector is an L-shaped interferometer made up of two 4-kilometer-long tunnels, at the end of which hangs a 40-kilogram mirror. To detect a gravitational wave, a laser located at the input of the LIGO interferometer sends a beam of light down each tunnel of the detector, where it reflects off the mirror at the far end, to arrive back at its starting point. In the absence of a gravitational wave, the lasers should return at the same exact time. If a gravitational wave passes through, it would briefly disturb the position of the mirrors, and therefore the arrival times of the lasers. Much has been done to shield the interferometers from external noise, so that the detectors have a better chance of picking out the exceedingly subtle disturbances created by an incoming gravitational wave. Mavalvala and her colleagues wondered whether LIGO might also be sensitive enough that the instrument might even feel subtler effects, such as quantum fluctuations within the interferometer itself, and specifically, quantum noise generated among the photons in LIGO’s laser. “This quantum fluctuation in the laser light can cause a radiation pressure that can actually kick an object,” McCuller adds. “The object in our case is a 40-kilogram mirror, which is a billion times heavier than the nanoscale objects that other groups have measured this quantum effect in.” Noise squeezer To see whether they could measure the motion of LIGO’s massive mirrors in response to tiny quantum fluctuations, the team used an instrument they recently built as an add-on to the interferometers, which they call a quantum squeezer. With the squeezer, scientists can tune the properties of the quantum noise within LIGO’s interferometer. The team first measured the total noise within LIGO’s interferometers, including the background quantum noise, as well as “classical” noise, or disturbances generated from normal, everyday vibrations. They then turned the squeezer on and set it to a specific state that altered the properties of quantum noise specifically. They were able to then subtract the classical noise during data analysis, to isolate the purely quantum noise in the interferometer. As the detector constantly monitors the displacement of the mirrors to any incoming noise, the researchers were able to observe that the quantum noise alone was enough to displace the mirrors, by 10-20 meter. Mavalvala notes that the measurement lines up exactly with what quantum mechanics predicts. “But still it’s remarkable to see it be confirmed in something so big,” she says. Going a step further, the team wondered whether they could manipulate the quantum squeezer to reduce the quantum noise within the interferometer. The squeezer is designed such that when it set to a particular state, it “squeezes” certain properties of the quantum noise, in this case, phase and amplitude. Phase fluctuations can be thought of as arising from the quantum uncertainty in the light's travel time, while amplitude fluctuations impart quantum kicks to the mirror surface. “We think of the quantum noise as distributed along different axes, and we try to reduce the noise in some specific aspect,” Yu says. When the squeezer is set to a certain state, it can for example squeeze, or narrow the uncertainty in phase, while simultaneously distending, or increasing the uncertainty in amplitude. Squeezing the quantum noise at different angles would produce different ratios of phase and amplitude noise within LIGO’s detectors. The group wondered whether changing the angle of this squeezing would create quantum correlations between LIGO’s lasers and its mirrors, in a way that they could also measure. Testing their idea, the team set the squeezer to 12 different angles and found that, indeed, they could measure correlations between the various distributions of quantum noise in the laser and the motion of the mirrors. Through these quantum correlations, the team was able to squeeze the quantum noise, and the resulting mirror displacement, down to 70 percent its normal level. This measurement, incidentally, is below what’s called the standard quantum limit, which, in quantum mechanics, states that a given number of photons, or, in LIGO’s case, a certain level of laser power, is expected to generate a certain minimum of quantum fluctuations that would generate a specific “kick” to any object in their path. By using squeezed light to reduce the quantum noise in the LIGO measurement, the team has made a measurement more precise than the standard quantum limit, reducing that noise in a way that will ultimately help LIGO to detect fainter, more distant sources of gravitational waves. This research was funded, in part, by the National Science Foundation. (Comment on this)
4:30p	Universal musical harmony Many forms of Western music make use of harmony, or the sound created by certain pairs of notes. A longstanding question is why some combinations of notes are perceived as pleasant while others sound jarring to the ear. Are the combinations we favor a universal phenomenon? Or are they specific to Western culture? Through intrepid research trips to the remote Bolivian rainforest, researchers in the McDermott lab at the McGovern Institute for Brain Research have found that aspects of the perception of note combinations may be universal, even though the aesthetic evaluation of note combination as pleasant or unpleasant is culture-specific. “Our work has suggested some universal features of perception that may shape musical behavior around the world,” says MIT associate professor of brain and cognitive sciences Josh McDermott, who is also an associate investigator at the McGovern Institute and senior author of the Nature Communications study. “But it also indicates the rich interplay with cultural influences that give rise to the experience of music.” Remote learning Questions about the universality of musical perception are difficult to answer, in part because of the challenge in finding people with little exposure to Western music. McDermott, who is also an investigator in the Center for Brains, Minds, and Machines, has found a way to address this problem. His colleagues have performed a series of studies with the participation of an Indigenous population, the Tsimane’, who live in relative isolation from Western culture and have had little exposure to Western music. Accessing the Tsimane’ villages is challenging, as they are scattered throughout the rainforest and only reachable during the dry part of the year. “When we enter a village there is always a crowd of curious children to greet us,” says Malinda McPherson, a graduate student in the lab and lead author of the study. “Tsimane’ are friendly and welcoming, and we have visited some villages several times, so now many people recognize us.” In a study published in 2019, McDermott’s team found evidence that the brain’s ability to detect musical octaves is not universal, but is gained through cultural experience. And in 2016 they published findings suggesting that the preference for consonance over dissonance is culture-specific. In their new study, the team decided to explore whether aspects of the perception of consonance and dissonance might nonetheless be universally present across cultures. Music lessons In Western music, harmony is the sound of two or more notes heard simultaneously. Think of the Leonard Cohen song, "Hallelujah," where he sings about harmony ("the fourth, the fifth, the minor fall and the major lift"). A combination of two notes is called an interval, and intervals that are perceived to be the most pleasant (or consonant, like the fourth and the fifth, for example) to the Western ear are generally represented by smaller integer ratios. "Intervals that are related by low integer ratios have fascinated scientists for centuries," McPherson explains. "Such intervals are central to Western music, but are also believed to be a common feature of many musical systems around the world. So intervals are a natural target for cross-cultural research, which can help identify aspects of perception that are and aren’t independent of cultural experience.” Scientists have been drawn to low integer ratios in music, in part because they relate to the frequencies in voices and many instruments, known as overtones. Overtones from sounds like voices form a particular pattern known as the harmonic series. As it happens, the combination of two concurrent notes related by a low integer ratio partially reproduces this pattern. Because the brain presumably evolved to represent natural sounds, such as voices, it has seemed plausible that intervals with low integer ratios might have special perceptual status across cultures. Since the Tsimane’ do not generally sing or play music together, meaning they have not been trained to hear or sing in harmony, McPherson and her colleagues were presented with a unique opportunity to explore whether there is anything universal about the perception of musical intervals. Taking notes In order to probe the perception of musical intervals, McDermott and colleagues took advantage of the fact that ears accustomed to Western musical harmony often have difficulty picking apart two “consonant” notes when they are played at the same time. This auditory confusion is known as “fusion” in the field. By contrast, two “dissonant” notes are easier to hear as separate. The tendency of “consonant” notes to be heard by Westerners as fused could reflect their common occurrence in Western music. But it could also be driven by the resemblance of low-integer-ratio note combinations to the harmonic series. This similarity of consonant intervals to the acoustic structure of typical natural sounds raises the possibility that the human brain is biologically tuned to “fuse” consonant notes. To explore this question, the team ran identical sets of experiments on two participant groups: U.S. non-musicians residing in the Boston metropolitan area and Tsimane’ residing in villages in the Amazon rainforest. Listeners heard two concurrent notes separated by a particular musical interval (consonant or dissonant), and were asked to judge whether they heard one or two sounds. The experiment was performed with both synthetic and natural sounds. They found that, like the Boston cohort, the Tsimane’ were more likely to mistake two notes as a single sound if they were consonant than if they were dissonant. “I was surprised by how similar some of the results in Tsimane’ participants were to those in U.S. participants,” says McPherson, “particularly given the striking differences that we consistently see in preferences for musical intervals.” When it came to whether consonant intervals were more pleasant than dissonant intervals, the results told a very different story. While the U.S. study participants found consonant intervals more pleasant than dissonant intervals, the Tsimane’ showed no preference, implying that our sense of what is pleasant is shaped by culture. “The fusion results provide an example of a perceptual effect that could influence musical systems, for instance by creating a natural perceptual contrast to exploit,” explains McDermott. “Hopefully our work helps to show how one can conduct rigorous perceptual experiments in the field and learn things that would be hidden if we didn’t consider populations in other parts of the world.” (Comment on this)

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