Superconductors have intrigued physicists for decades. But these materials, which allow the perfect, lossless flow of electrons, usually only exhibit this quantum-mechanical peculiarity at temperatures so low — a few degrees above absolute zero — as to render them impractical.

A research team led by Professor of Physics and Applied Physics Philip Kim has demonstrated a new strategy for making and manipulating a widely studied class of higher-temperature superconductors, called cuprates, clearing a path to engineering new, unusual forms of superconductivity in previously unattainable materials.

Using a uniquely low-temperature device fabrication method, Kim and his team report in the journal Science a promising candidate for the world’s first high-temperature, superconducting diode — essentially, a switch that makes current flow in one direction — made out of thin cuprate crystals. Such a device could theoretically fuel fledging industries like quantum computing, which rely on fleeting mechanical phenomena that are difficult to sustain.

“High-temperature superconducting diodes are, in fact, possible, without application of magnetic fields, and opens new doors of inquiry toward exotic materials study,” Kim said.

Cuprates are copper oxides that, decades ago, upended the physics world by showing they become superconducting at much higher temperatures than theorists had thought possible, “higher” being a relative term (the current record for a cuprate superconductor is minus 225 Fahrenheit). But handling these materials without destroying their superconducting phases is extremely complex due to their intricate electronic and structural features.

The team’s experiments were led by S.Y. Frank Zhao, a former student in the Griffin Graduate School of Arts and Sciences and now a postdoctoral researcher at MIT. Using an air-free, cryogenic crystal manipulation method in ultrapure argon, Zhao engineered a clean interface between two extremely thin layers of the cuprate bismuth strontium calcium copper oxide, nicknamed BSCCO (“bisco”). BSCCO is considered a “high-temperature” superconductor because it starts superconducting at about minus 288 Fahrenheit — very cold by practical standards, but astonishingly high among superconductors, which typically must be cooled to about minus 400.

Zhao first split the BSCCO into two layers, each one-thousandth the width of a human hair. Then, at minus 130, he stacked the two layers at a 45-degree twist, like an ice cream sandwich with askew wafers, retaining superconductivity at the fragile interface.

The team discovered that the maximum supercurrent that can pass without resistance through the interface is different depending on the current’s direction. Crucially, the team also demonstrated electronic control over the interfacial quantum state by reversing this polarity. This control was what effectively allowed them to make a switchable, high-temperature superconducting diode — a demonstration of foundational physics that could one day be incorporated into a piece of computing technology, such as a quantum bit.

“This is a starting point in investigating topological phases, featuring quantum states protected from imperfections,” Zhao said.

The Harvard team worked with colleagues Marcel Franz at University of British Columbia and Jed Pixley at Rutgers University, whose teams previously performed theoretical calculations that accurately predicted the behavior of the cuprate superconductor in a wide range of twist angles. Reconciling the experimental observations also required new theory developments, performed by University of Connecticut’s Pavel A. Volkov.

The research was supported, in part, by the National Science Foundation, the Department of Defense, and the Department of Energy.

Freezing is one of the most common and debilitating symptoms of Parkinson’s disease, a neurodegenerative disorder that affects more than 9 million people worldwide. When individuals with Parkinson’s disease freeze, they suddenly lose the ability to move their feet, often mid-stride, resulting in a series of staccato stutter steps that get shorter until the person stops altogether. These episodes are one of the biggest contributors to falls among people living with Parkinson’s disease.

Today, freezing is treated with a range of pharmacological, surgical, or behavioral therapies, none of which are particularly effective.

What if there was a way to stop freezing altogether?

Researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and the Boston University Sargent College of Health & Rehabilitation Sciences have used a soft, wearable robot to help a person living with Parkinson’s walk without freezing. The robotic garment, worn around the hips and thighs, gives a gentle push to the hips as the leg swings, helping the patient achieve a longer stride.

The device completely eliminated the participant’s freezing while walking indoors, allowing them to walk faster and further than they could without the garment’s help.

A group of scientists, including several at Harvard, have dived deeper into the mammalian brain than ever before by categorizing and mapping at the molecular level all of its thousands of different cell types.

The researchers reported their work in Nature, through a series of 10 papers — six with Harvard affiliations. It’s part of the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies initiative, which so far has focused on mice; future phases will shift to humans and other primates.

Mammal brains house billions of cells, each defined by the genes they express. This complexity is why true understanding of many brain functions, including molecular mechanisms that underlie neurological diseases, remains so elusive.

To create the first molecularly defined cell atlas of the whole mouse brain, a team led by Harvard’s Xiaowei Zhuang identified and spatially mapped thousands of unique cell types, most of which had never previously been characterized.

“We identified 5,000 transcriptionally distinct cell populations,” said Zhuang, the David B. Arnold Professor of Science and a Howard Hughes medical investigator. “Suffice it to say that the level of diversity we identified is really extraordinary.”

The brain-wide atlas of cell types cataloging cells, their distribution, and interactions could serve as a starting point for scientists studying certain brain functions or diseases. Someday the basic outlines of the atlas could be applied to the human brain, 1,000 times larger than the mouse brain.

“It gives me real excitement to see things that were not visible before. I am also thrilled when our technology is used by so many labs,” said Zhuang, referring to Multiplexed Error-Robust Fluorescence in situ Hybridization (MERFISH), a genome-scale imaging technology developed in her lab.

In collaboration with scientists at the Allen Institute for Brain Science, Zhuang and her team used MERFISH together with single-cell RNA sequencing data to not only identify each cell type, but to image them in situ. Their work provides new information about the molecular signatures of these cell types, as well as where they are located in the brain. The result is a stunningly detailed picture of the mouse brain’s full complement of cells, their gene-expression activity, and their spatial relationships.

In their Nature paper, the researchers used MERFISH to determine gene-expression profiles of approximately 10 million cells by imaging a panel of 1,100 genes, selected using single-cell RNA sequencing data provided by Allen Institute collaborators.

Retina findings could boost glaucoma research

In a separate paper in the Nature series, Joshua Sanes, the Jeff C. Tarr Professor of Molecular and Cellular Biology, co-led a team that captured new insights into the evolutionary history of the vertebrate retina.

A part of the brain encased in the eye, the retina boasts complex neural circuits that receive visual information, which they then transmit to the rest of the brain for further processing. The retina is functionally very different from species to species — for example, human hunter-gatherers evolved sharp daytime vision, whereas mice possess better night vision than humans do; some animals see in color, while others see predominantly in black and white.

But at molecular levels, how different are retinas, really? Sanes, in collaboration with researchers at the University of California, Berkeley, and the Broad Institute, performed a new comparative analysis of retinal cell types across 17 species, including humans, fish, mice, and opossums. Using single-cell RNA sequencing, which allowed them to differentiate types of retinal cells by their genetic expression profiles, the researchers’ findings upended some long-held views about how certain species’ visual systems evolved.

One striking discovery involved so-called “midget retinal ganglion cells,” which, in humans, carry 90 percent of the information from the eye to the brain. These cells give humans their fine-detail vision, and changes to them are associated with eye diseases such as glaucoma. No related cells had ever been found in mice, so they had been assumed to be unique to primates.

In their analysis, Sanes and team identified for the first time clear relatives of midget retinal ganglion cells in many other species, including mice, albeit in much smaller proportions. Since mice are a common model animal to study glaucoma, being able to pinpoint these cells is a potentially crucial insight.

“I think we can make a very compelling case that if you want to study these important human retinal ganglion cells in a mouse, these are the cells you want to be studying,” Sanes said.

Other Harvard-affiliated researchers, at Harvard Medical School, Boston Children’s Hospital, and the Broad, also contributed findings to the NIH’s cell census network, including a molecular cytoarchitecture of the adult mouse brain, and a transcriptomic taxonomy of mouse brain-wide spinal projecting neurons.

Harvard researchers have realized a key milestone in the quest for stable, scalable quantum computing, an ultra-high-speed technology that will enable game-changing advances in a variety of fields, including medicine, science, and finance.

The team, led by Mikhail Lukin, the Joshua and Beth Friedman University Professor in physics and co-director of the Harvard Quantum Initiative, has created the first programmable, logical quantum processor, capable of encoding up to 48 logical qubits, and executing hundreds of logical gate operations, a vast improvement over prior efforts.

Published in Nature, the work was performed in collaboration with Markus Greiner, the George Vasmer Leverett Professor of Physics; colleagues from MIT; and QuEra Computing, a Boston company founded on technology from Harvard labs.

The system is the first demonstration of large-scale algorithm execution on an error-corrected quantum computer, heralding the advent of early fault-tolerant, or reliably uninterrupted, quantum computation.

Lukin described the achievement as a possible inflection point akin to the early days in the field of artificial intelligence: the ideas of quantum error correction and fault tolerance, long theorized, are starting to bear fruit.

“I think this is one of the moments in which it is clear that something very special is coming,” Lukin said. “Although there are still challenges ahead, we expect that this new advance will greatly accelerate the progress toward large-scale, useful quantum computers.”

Denise Caldwell of the National Science Foundation agrees.

“This breakthrough is a tour de force of quantum engineering and design,” said Caldwell, acting assistant director of the Mathematical and Physical Sciences Directorate, which supported the research through NSF’s Physics Frontiers Centers and Quantum Leap Challenge Institutes programs. “The team has not only accelerated the development of quantum information processing by using neutral atoms, but opened a new door to explorations of large-scale logical qubit devices, which could enable transformative benefits for science and society as a whole.”

It’s been a long, complex path.

In quantum computing, a quantum bit or “qubit” is one unit of information, just like a binary bit in classical computing. For more than two decades, physicists and engineers have shown the world that quantum computing is, in principle, possible by manipulating quantum particles — be they atoms, ions, or photons — to create physical qubits.

But successfully exploiting the weirdness of quantum mechanics for computation is more complicated than simply amassing a large-enough number of qubits, which are inherently unstable and prone to collapse out of their quantum states.

The real coins of the realm are so-called logical qubits: bundles of redundant, error-corrected physical qubits, which can store information for use in a quantum algorithm. Creating logical qubits as controllable units — like classical bits — has been a fundamental obstacle for the field, and it’s generally accepted that until quantum computers can run reliably on logical qubits, the technology can’t really take off.

To date, the best computing systems have demonstrated one or two logical qubits, and one quantum gate operation — akin to just one unit of code — between them.

The Harvard team’s breakthrough builds on several years of work on a quantum computing architecture known as a neutral atom array, pioneered in Lukin’s lab. It is now being commercialized by QuEra, which recently entered into a licensing agreement with Harvard’s Office of Technology Development for a patent portfolio based on innovations developed by Lukin’s group.

The key component of the system is a block of ultra-cold, suspended rubidium atoms, in which the atoms — the system’s physical qubits — can move about and be connected into pairs — or “entangled” — mid-computation.

Entangled pairs of atoms form gates, which are units of computing power. Previously, the team had demonstrated low error rates in their entangling operations, proving the reliability of their neutral atom array system.

With their logical quantum processor, the researchers now demonstrate parallel, multiplexed control of an entire patch of logical qubits, using lasers. This result is more efficient and scalable than having to control individual physical qubits.

“We are trying to mark a transition in the field, toward starting to test algorithms with error-corrected qubits instead of physical ones, and enabling a path toward larger devices,” said paper first author Dolev Bluvstein, a Griffin School of Arts and Sciences Ph.D. student in Lukin’s lab.

The team will continue to work toward demonstrating more types of operations on their 48 logical qubits and to configure their system to run continuously, as opposed to manual cycling as it does now.

The work was supported by the Defense Advanced Research Projects Agency through the Optimization with Noisy Intermediate-Scale Quantum devices program; the Center for Ultracold Atoms, a National Science Foundation Physics Frontiers Center; the Army Research Office; and QuEra Computing.

Some dogs love to play fetch, while others watch the tennis ball roll by with little interest. Some run circles around their owners, herding them, during walks, while others stop to sniff everything in their path.

It begs the question — why do dogs behave so differently, even within their own breeds?

Erin Hecht, assistant professor of human evolutionary biology at Harvard, is seeking answers through The Canine Brains Project, part of the University’s Brain Science Initiative. She recently gave a talk on the emerging field of canine neuroscience, and what we know so far about our furry friends.

Dogs, according to Hecht, have the potential to teach us a lot about brain development, having been domesticated roughly 20,000 to 40,000 years ago — a blip on the evolutionary timeline. For context, modern humans emerged roughly 300,000 years ago. Because domestication was relatively recent, modern dog breeds live alongside ancient breeds, making comparison possible.

“Darwin saw dogs as a window on mechanisms of evolution,” Hecht said. “When we’re looking at dogs, as a natural experiment and brain behavior evolution all we have to do is look at their brains and see what evolution did in order to satisfy those selection requirements.”

Hecht’s lab performs MRI scans on nearly 100 canine brains a year and conducts owner surveys looking at dogs’ working skills, like hunting, herding, and guarding, compared to skull shape, body size, and breed.

The lab looks at domesticated breeds like Great Danes or other hunting dogs or designer dogs — a practice that took really took hold during the Victorian era — as well as ancient dogs like huskies and “village dogs.”

“About 80 percent of the dogs living on the planet today are what’s known as village dogs. These are free-ranging animals that live as human commensals. So they’re living within human society, but they’re not pets,” Hecht said.

Some initial findings from the lab include the discovery of neurological differences in dog breeds, including that premodern dogs on a whole have larger amygdala — the part of the brain that controls emotional processing and memory. Such heightened environmental-monitoring skills would come in handy for dogs deciding which humans to steal scraps from and which to avoid.

Modern dogs have a bigger neocortex — the part of the brain that controls motor function, perception, and reasoning. It may play a part in modern dogs’ increased behavioral flexibility, or ability to adapt to new environments.

Hecht’s lab connects personality and skill differences in dogs to six different parts of the brain: the regions controlling drive and reward; olfaction and taste; spatial navigation; social communication and coordination; fight or flight; and olfaction and vision. While breeds we see in our homes today share similarities in these pathways, Hecht’s research suggests the traits can be attributed more to selective breeding than ancestral DNA.

“There has been very strong recent specific selection in individual breeds rather than founding effects in ancestral founding populations,” Hecht said. “So then we can look at behavior and ask whether the types of behaviors that different lineages have been selected for historically … [explain] each dog’s anatomy and these six brain networks. And it seems like there are some interesting relationships here.”

More than breed itself, pathways are impacted by a dog’s head shape and size. For example, Hecht’s lab has found that bigger dogs have larger neocortices than their smaller counterparts, and therefore generally are more trainable and less anxious. Dogs bred for their narrow skulls may see that impact their behavior.

“It stands to reason that if you’re manipulating the shape of a skull, you’re going to be manipulating the shape of the brain,” Hecht said. “But this confirms that dogs with these extreme skull morphotypes have impacts on their brain anatomy that likely affects behavior.”

In conjunction with the MRI scanning, Hecht’s lab measures dogs’ behavior with an assessment called C-BARQ, the Canine Behavioral Assessment and Research Questionnaire. The survey, which is filled out by the dog’s owner, assesses behaviors such as aggression, trainability, and rivalry, to name a few.

“There was one study that collected C-BARQ data on 32,000 dogs from 82 different breeds and then performed clustering on the survey responses. And the data clustered more on the body height of the dogs than on breed relatedness. So size was a better predictor than breed in predicting temperament scores on this C-BARQ assessment,” Hecht said.

She added that just because certain dogs have brain makeups that suggest a certain disposition, it doesn’t lock them into those behaviors. That goes especially for working skills.

“Training is almost always necessary. I have yet to hear of any particular breed of working dog, where it’s just born knowing how to do its job,” Hecht said.

But whether you have a pit bull that acts like a chihuahua or a Yorkie that likes to run with the big dogs, a look inside their brain might help explain why they are the way they are.

Find out more about the work happening in the Hecht lab or see if your dog is a study candidate.

Humans have been considered unique for their ability to form relationships for mutual benefit not just within immediate kin groups but across and between them, even with total strangers.

It turns out that one of our closest living relatives, bonobos, are also able to think outside the group.

These were the findings of a Harvard study that involved two years of data collection in the deep forests of the Democratic Republic of Congo, where up to 20,000 of the endangered apes make their only home. The ability to engage in such “out-group” cooperation is the foundation on which humans have created societies and cultures through trade and knowledge-sharing.

“Our work with bonobos is showing that cooperation beyond social borders, without immediate payoff between unrelated individuals, is not uniquely human,” said senior author Martin Surbeck, assistant professor in the Department of Human Evolutionary Biology, who has researched bonobos for 20 years. The study was published in Science with lead author Liran Samuni, a former Harvard research associate who works at the German Primate Center in Göttingen.

A previous study, based on the same bonobo communities, found that the primates maintained distinct, stable social borders, so called “communities.” In their latest analysis, Samuni and Surbeck found evidence of cooperation between members of different communities, facilitated by an assortment of key individuals. These certain few consistently engaged in behaviors such as grooming and food-sharing and acted as links between groups — think ape ambassadors. Within each behavior, individuals cooperated with specific counterparts who were also good cooperators in that domain.

When animals of two different species mate, their hybrid offspring can be unhealthy or sterile. Often, only one sex is affected.

Sexual differences in fertility follow a pattern known as Haldane’s Rule, which states that hybrids are afflicted more when they inherit two different sex chromosomes. In mammals, males have XY sex chromosomes, so male “ligers” and “tigons” (offspring between tigers and lions) are sterile, while females, which have two X chromosomes, tend to be more fertile. But in butterflies as well as birds, females have ZW sex chromosomes while males have ZZ, so according to Haldane’s Rule, it is females that are sterile.

What insights could this natural phenomenon hold for speciation, the process in which different biological lineages split? James Mallet, professor of organismic and evolutionary biology in residence and associate of population genetics in the Museum of Comparative Zoology, and senior author of a new study in Proceedings of the National Academy of Sciences, takes a stab at the “why” behind Haldane’s Rule, using butterfly genetics as a guide.

Designed and led by former graduate student Tianzhu Xiong, the study investigated hybrid sterility in butterflies, creating hybrid crosses of different species to determine which particular genes were responsible for the phenotype.

According to analysis by Xiong, now a postdoctoral researcher at Cornell, the sterility trait in hybrid butterflies is probably tied to many genes scattered across the Z chromosome. Thus understanding all the genetic mechanisms behind it will require further study.

For the research, Xiong and colleagues created hybrids of Papilio swallowtail butterflies. They found that problems associated with hybrids, such as low pupal weight and ovary malformation in the females, happened because of uneven mixing, or “introgression,” between the Z sex chromosome and all the other chromosomes. This observation points to many genes working together to produce a balance within each species.

The balance between the Z chromosome and the rest of the chromosomes is disturbed when the former is inherited from only one species, as in female ZW hybrids. The W chromosome characteristic of female butterflies carries very few genes and is not involved. Furthermore, Xiong showed that female hybrids of another butterfly, Heliconius, studied by Neil Rosser and colleagues, also followed the same multigene pattern on the Z chromosome.

“Initially, I was in a mindset of hoping to find a major gene that causes the phenotype,” Xiong said. “But it turns out that the answer is more mathematical than expected, and that a very large number of genes actually explain the pattern better.”

The analysis shows that hybrid sterility may be like height in humans — polygenic, or involving multiple genes. “Tianzhu has shown it is the fraction of the Z chromosome that matters, not whether you’ve got a particular problem on one region of the chromosome,” Mallet said.

The work was supported in part by the National Science Foundation.

The warming climate is having ripple effects across ecosystems, including plants, which have evolved clever mechanisms to conserve water when stressed by drought.

But are plants likelier to defend themselves against dry air or dry soil? This question is hotly debated among climate scientists, and the distinction matters: While there’s consensus on the trajectory of temperature rise over coming decades, less is known about how global warming will affect soil moisture. Understanding this dynamic may help decide the most effective ways to ensure the survival of robust plant life.

A team led by Kaighin McColl, assistant professor in the Department of Earth and Planetary Sciences and the John A. Paulson School of Engineering and Applied Sciences, have new research in Nature Water indicating that plant drought-defense mechanisms, which involve closing tiny pores on leaves called stomata to limit photosynthesis and conserve water, are more likely triggered by dry soil than by dry air.

Their results challenge recently held views and were derived from a place with no plants at all — the barren salt flats of Utah and Nevada.

Previous research had found that plants are likelier to have closed stomata in the presence of dry air, rather than dry soils, so it was assumed that aridity triggered the drought response. But McColl and colleagues suspected these results did not tell the whole story about plant vulnerability to drier environments.

“The problem with this argument is that correlation does not imply causation; when plants close their stomata, that could actually be causing the air to get drier, rather than the other way around,” McColl said.

To investigate their opposing hypothesis, McColl and lead author Lucas Vargas Zeppetello, a Harvard postdoctoral researcher who starts at the University of California, Berkeley, in January, used as their natural laboratory one of the only places on Earth that has a vigorous water cycle but doesn’t grow any plants — salt flats in the Western U.S. desert.

Using salt flats data provided by collaborators in Nevada and Utah, the researchers reproduced other researchers’ studies that had calculated the relationship between air dryness and moisture flux, or movement (in this case through evaporation), from the land surface and had attributed those values to plants closing their stomata to conserve water. The Harvard team found their calculations lined up almost perfectly with those previous studies, but with no plants in the salt flats, they knew there had to be another explanation.

In that plant-free environment, evaporation responds only to soil dryness. McColl and Vargas Zeppetello concluded that plant responses to lack of humidity may have been exaggerated in previous studies. They think instead that plants respond most acutely to dry soil, an environmental stressor that is known to reduce transpiration and photosynthesis.

What does this mean? Soil dryness matters more than air dryness when it comes to global plant ecosystems.

“Our findings put emphasis on projections for water in the future,” Vargas Zeppetello said. “People talk about consensus on climate change, but that really has to do with global temperatures. There’s much less of a consensus on what regional changes to the water cycle are going to look like.”

The research was supported in part by the National Science Foundation.