A Mini Moon Rover from the Toy Company That Created Transformers

A Mini Moon Rover from the Toy Company That Created Transformers

Japan’s space agency, JAXA, hired Takara Tomy to design a rolling lunar robot called SORA-Q. It’s now in route to the moon.

By Matt Alt The New Yorker

The private museum of Takara Tomy, the Japanese toy company responsible for Transformers, Beyblade, and Zoids, is filled with playthings from Christmases past. In a lovingly curated room in the company’s Tokyo headquarters, a miniature B-29 bomber, faintly flecked with rust, sits at the ready in a glass display case. A squad of Micronauts action figures seems to have warped in from the seventies. An R2-D2-esque Omnibot, the remote-controlled robot that I begged my parents to buy in 1985, looks ready to roll. In the near future, these toys are likely to be joined by a very different sort of gadget: a small, spherical moon rover named SORA-Q, which Takara Tomy designed for the Japanese Aerospace Exploration Agency, or jaxa.

In recent years, numerous countries and companies have joined a new race to the moon, motivated not only by science and national prestige but also the potential to harvest lunar resources. nasa plans to return astronauts to the lunar surface after half a century; China wants to open a nuclear-powered base. Other entrants include the U.A.E., India, and a private Israeli effort. (The latter two each lost landers to malfunctions, in 2019.) Japan, for its part, will lend an astronaut to nasa’s upcoming Artemis moon missions. SORA-Q, however, is likely to get there first. On December 11th, Takara Tomy’s round rover hitched a ride on a SpaceX Falcon 9 rocket, which catapulted the world’s first commercial lunar lander, ispace’s Hakuto-R M1, toward the moon. Another SORA-Q will be carried aboard slim, a jaxa lander slated to touch down in 2023.

The M1 and slim missions will each follow a circuitous, months-long trajectory to the moon that consumes less fuel than a direct flight. If all goes according to plan, shortly before their main landers reach the lunar surface, they will eject various smaller probes, including SORA-Q. With its honeycombed aluminum-alloy shell, SORA-Q looks something like a metallic Wiffle ball and takes its name from sora, which means “sky” in Japanese; the “Q” is a homonym for the Japanese word meaning “sphere.” As the dust settles, SORA-Q will unfold like a Transformer: the sphere will split in half, exposing a pair of cameras and dividing its two hemispheres into wheels. In the case of M1, mission controllers will remotely instruct their SORA-Q to turn toward the main lunar lander and transmit images back to Earth. (One long-standing challenge of landing missions is that they generally can’t take selfies from a distance, so scientists can’t visually diagnose problems—and images of the landing can’t go viral.)

Takara Tomy’s headquarters is situated in Tokyo’s Katsushika ward, a low-slung downtown neighborhood on the easternmost edge of the city, a few train stops from the touristy Asakusa. The company neighbors Aoto Peace Park, an urban oasis of playgrounds and a memorial that contains debris from the bombings of Hiroshima and Nagasaki. In a Takara Tomy meeting room, Yōsuke Yoneda, an engineer who joined Tomy more than forty years ago, told me about the origins of the partnership. In 2015, jaxa launched a space-exploration innovation hub to strengthen connections with the private sector, and a Takara Tomy executive saw a jaxa booth at an expo in Tokyo. “The idea of making a design with the smallest number of motors, in reducing the number of components to the bare minimum—as a toy company, this is something we have been doing for a long time,” Yoneda said. “The initial idea, as we understood it from jaxa, was for a bug-like design that could move around on its own.”

Yoneda and his team showed me three toys that helped to inspire SORA-Q prototypes. The first, an iteration of Optimus Prime, was a Transformer. The second, a boxy little i-Sobot, could be remotely controlled and held a Guinness World Record for the smallest mass-produced humanoid robot. The third, a feline Zoid called Liger Zero, walked on battery power. The team quickly abandoned the idea of using legs, which seemed too complex and fragile, and instead focussed on a spherical design. SORA-Q vaguely resembles a “Star Wars” droid, but its appearance has more to do with physics than pop culture. “After exploring many options, we realized that a ball represented the smallest possible shape,” Yoneda told me.

Takara Tomy usually spends a year developing a new toy, but SORA-Q took six: the team revised its plans again and again, experimenting with rough and non-slip exteriors before settling on one with holes. Drawing on the toymaker’s engineering model, jaxa built a final version of the rover out of aerospace-grade aluminum and plastic, incorporating miniaturized electronics and optics from Sony. It chose materials and components that could meet stringent weight, size, and durability requirements. (Neither Takara Tomy nor jaxa would tell me how much the rover cost.) SORA-Q needs to survive stresses that even Sid, the bully in “Toy Story,” couldn’t dream up: the vibrations and g-forces of launch, the blunt impact of landing, and lunar temperatures that can range from two hundred and fifty degrees Fahrenheit in the sun to two hundred and eight degrees below zero at night.

Westerners have associated Japan with toys since some of their earliest visits there. “We do not know of any country in the world in which there are so many toy-shops, or so many fairs for the sale of things which delight children,” William Elliot Griffis, an American minister and educator who arrived in Japan in the eighteen-seventies, wrote. A few decades later, as Japan began to open up its economy after centuries of self-imposed isolation, its leaders encouraged toymakers to show off their porcelain dolls, paper umbrellas, and celluloid figurines to foreign buyers at World’s Fairs and expositions. By the early thirties, inexpensive Japanese toys were so successful that frustrated American toy companies were petitioning the U.S. government for tariffs.

During the Second World War, Imperial Japanese authorities froze the toy industry and repurposed its factories to make weapons. Then, on March 10, 1945, American B-29s firebombed Tokyo. Downtown factory areas, where former toymakers and their families were clustered, were among the targets. In the most destructive conventional bombing in history, more than a hundred thousand Tokyoites perished, most of them civilians.

After the war, one of the first toys manufactured in Japan was a miniature tin Army Jeep, which an enterprising toymaker made by scavenging discarded food and beer cans from American bases. It proved a huge hit, both among war-weary citizens and Allied occupiers, and American forces soon approved toys for export abroad. One toymaker, Eiichiro Tomiyama, designed a tin B-29 in 1951, and it was manufactured, ironically, in one of the very neighborhoods that the real planes had bombed. It was so successful that he was able to rebuild his factory and expand his business. In 1963, he shortened the company’s name to Tomy. (In 2006, Tomy merged with its competitor Takara; Takara Tomy is now chaired by Tomiyama’s grandson Kantaro.)

SORA-Q is not the first toy to make it into space. In the nineties, nasa sent a gyroscope, Slinky, and wind-up frog into orbit on the space shuttle so that astronauts could demonstrate zero-gravity physics to schoolchildren. In 2012, the Japanese astronaut Satoshi Furukawa assembled a Lego version of the International Space Station while aboard the real I.S.S. In 2014, Sanrio sent a Hello Kitty figurine into orbit aboard a Japanese satellite, to celebrate the character’s fortieth anniversary. And, in 2020, the crew of a SpaceX Dragon carried a plush Baby Yoda up to the I.S.S.

Toys have also inspired space engineers before. One of nasa’s newest heat-shield designs was inspired by the concentric loops of a baby’s stacking-ring toy; a prototype lander called Super Ball Bot was similarly inspired by a tensegrity toy, which is built from wooden rods and rubber bands to withstand handling by toddlers. But SORA-Q seems to represent the first time that a space program has tasked a toy company directly with designing equipment for its missions. “They incorporated new ideas, and new kinds of systems, that wouldn’t have occurred to us,” Daichi Hirano, an associate senior researcher at jaxa’s innovation hub, told me. “Creating small things that can expand into larger forms might be called the hallmark of Japanese toy companies.”

At Takara Tomy headquarters, Kenta Hashiba, a member of the engineering team, nestled a SORA-Q prototype into a tabletop sandbox. After a countdown from three, he pressed a button on a remote control; with an audible click, the ball split into two hemispheres, which were connected to a boxy core by independent axles. Atop the core were two cameras; trailing behind it was a curved metal “tail,” which works like a rudder and keeps the sphere upright as it rolls along.

When SORA-Q’s hemispheres rotate in synch, the rover rolls in a straight line. When they rotate independently, on their separate axles, it can steer clear of obstacles with a wiggle that resembles an army crawl. SORA-Q looks nothing like the boxy, wheeled research rovers that historical moon and Mars missions have trained us to expect; instead, its lifelike locomotion—and the herringbone-pattern trail it leaves behind—reminded me of a scuttling crustacean or desert dweller. “Giving it an animal-like gait,” Hashiba told me, as though reading my mind, “is how we were able to get it moving through the sand without getting caught up.” It also lent SORA-Q an inherent adorability, which the Japanese would call kawaii.

For the M1 and slim missions, and their pocket-size SORA-Q payloads, the stakes are high. A recent jaxa spacecraft, dubbed omotenashi and touted as the world’s smallest moon lander, was launched on nasa’s uncrewed Artemis 1, in November, but malfunctioned and had to be abandoned. “SPACE IS HARD Y’ALL,” Elizabeth Tasker, a British astrophysicist working at jaxa, lamented on Twitter. Since the sixties, more than a third of robotic lunar-landing attempts have ended in failure. Targeting a specific location on the moon’s surface, a jaxa employee told Spectra magazine, is “akin to slamming on the brakes while driving at maximum speed on an expressway and bringing the car to a neat stop in a specific parking space.” (slim, which stands for “Smart Lander for Investigating Moon,” relies on A.I. to make its landing more precise; its SORA-Q is designed to operate autonomously.)

In the coming decades, the moon may start to feel crowded. The Outer Space Treaty, created in 1966 during the Cold War, restricts its hundred and twelve signatories to peaceful activities on celestial bodies such as the moon. But peaceful does not mean conflict-free. The administrator of nasa, Bill Nelson, reportedly told the German newspaper Bild, “We must be very concerned about China landing on the moon and saying: It’s ours now, and you stay out.” In response, Chinese state media accused the U.S.-led Artemis program of “mimicking a space-based nato.” Japan may have chosen a coöperative and even playful approach to the space race, but it would be a mistake to attribute its miniature machines to small ambitions. The country has had a space program since the fifties, and, now that it has a seat on nasa’s Artemis missions, it could become the second nation to get boots on the lunar surface—even while it lacks the means to helm its own manned missions.

The small battery inside SORA-Q provides only enough energy for, at most, two hours of activity. After that, the rover will die. The design could live on, however, if SORA-Q succeeds. “For the future, we’re exploring decentralized systems, in which multiple robots of various sizes perform various tasks as a group,” Hirano told me. “SORA-Q might be one of those.” The rover also has a mission here on Earth, he said: “A major contribution of SORA-Q is helping to promote interest in space and science in general among children.” Many of us grew up playing with Japanese toys. Maybe a toymaker’s rover will inspire the next generation to shoot for the stars. ♦

What Comes Next for the Most Empty Downtown in America

What Comes Next for the Most Empty Downtown in America

By Conor Dougherty and Emma Goldberg New York Times 

On any given week in San Francisco, office buildings are at about 40 percent of their prepandemic occupancy.

Tech workers are still at home. The $17 salad place is expanding into the suburbs. So what is left in San Francisco?

On any given week in San Francisco, office buildings are at about 40 percent of their prepandemic occupancy.

Conor Dougherty, who covers housing, and Emma Goldberg, who covers the future of work, reported this story from San Francisco and Mill Valley.

The coffee rush. The lunch rush. The columns of headphone-equipped tech workers rushing in and out of train stations. The lanyard-wearing visitors who crowded the sidewalks when a big conference was in town.

There was a time three years ago when a walk through downtown San Francisco was a picture of what it meant for a city to be economically successful. Take the five-minute jaunt from the office building at 140 New Montgomery Street to a line-out-the-door salad shop nearby.

The 26-story building, an Art Deco landmark that was once the tallest in the city, began its life as the headquarters for the Pacific Telephone & Telegraph Company. Decades later, it served as the home of the local search company Yelp. The nearby salad store was part of a fast-growing chain called Mixt.

Yelp and Mixt had little more than proximity in common, which at that time was enough. Yelp was an idea that became billions of dollars in value on the internet. Mixt was a booming business serving lunchtime salads to the workers who traveled on electrified trains and skateboards to their jobs in downtown cubicles.

Their virtuous cycle of nearness, of new ideas becoming new companies, feeding other ideas that become other companies, was the template for urban growth. Businesses like Yelp took root in the high-energy, high-density city; chains like Mixt flourished alongside them as their workers ventured out for lunch. As downtowns have emptied out, their once-symbiotic relationship is coming undone.

“This area was always packed with people,” recalled Maria Cerros-Mercado, a Mixt manager who built her career in food service downtown. “People would get off the BART, buy coffee, buy this, buy that. There was always just so much walking.”

Today San Francisco has what is perhaps the most deserted major downtown in America. On any given week, office buildings are at about 40 percent of their prepandemic occupancy, while the vacancy rate has jumped to 24 percent from 5 percent since 2019. Occupancy of the city’s offices is roughly 7 percentage points below that of those in the average major American city, according to Kastle, the building security firm.

Yelp had its offices in this 26-story building at 140 New Montgomery Street in San Francisco but left after the pandemic began.

More ominous for the city is that its downtown business district — the bedrock of its economy and tax base — revolves around a technology industry that is uniquely equipped and enthusiastic about letting workers stay home indefinitely. In the space of a few months, Jeremy Stoppelman, the chief executive of Yelp, went from running a company that was rooted in the city to vacating Yelp’s longtime headquarters and allowing its roughly 4,400 employees to work from anywhere in their country.

“I feel like I’ve seen the future,” he said.

Decisions like that, played out across thousands of remote and hybrid work arrangements, have forced office owners and the businesses that rely on them to figure out what’s next. This has made the San Francisco area something of a test case in the multibillion-dollar question of what the nation’s central business districts will look like when an increased amount of business is done at home.

“Imagine a forest where an entire species suddenly disappears,” said Tracy Hadden Loh, a fellow at the Brookings Institution who studies urban real estate. “It disrupts the whole ecosystem and produces a lot of chaos. The same thing is happening in downtowns.”

The city’s chief economist, Ted Egan, has warned about a looming loss of tax revenue as vacancies pile up. Brokers have tried to counter that narrative by talking up a “flight to quality” in which companies upgrade to higher-end space. Business groups and city leaders hope to recast the urban core as a more residential neighborhood built around people as well as businesses but leave out that office rents would probably have to plunge for those plans to be viable.

Below the surface of spin is a downtown that is trying to adapt to what amounts to a three-day workweek. During a recent lunch at a Mixt location in the financial district, the company’s chief executive, Leslie Silverglide, pointed to the line of badge-holding workers and competition for outdoor tables.

It was also, she noted, a Wednesday — what passes for rush hour. On Wednesdays, offices in San Francisco are at roughly 50 percent of their prepandemic levels; on Fridays, they’re not even at 30 percent.

The lunchtime business downtown is not, and may never be, what it used to be. But if workers aren’t going to return to buying their $17 salads downtown, Mixt will follow them home.

Which is why on a recent Wednesday morning, one of Mixt’s managers, Ms. Cerros-Mercado, 35, stood on a mostly empty sidewalk waiting for an Uber (another company that told most of its employees they can work half their time from home).

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Ms. Cerros-Mercado lives in San Francisco and used to walk downtown for work but now manages a Mixt branch in Mill Valley, a Marin County suburb that has 14,000 people and $2 million starter homes.

Many of the former office workers who live there have yet to return downtown en masse, but their purchases over the past three years have shown that they still want downtown perks and services like a freshly prepared lunch. Mixt opened the Mill Valley location this year as part of a push to generate more business in residential neighborhoods and suburbs.

Just before 7:30 a.m. on that recent Wednesday, Ms. Cerros-Mercado watched her Uber pull up outside a downtown Whole Foods so she could start her commute to the suburbs. It proceeded along the sleepy streets where she used to work — past coffee-shops and dim sum restaurants, past the glass towers and the boarded-up storefronts — and sped across the Golden Gate Bridge toward Marin.

The Creative Class

As it happens, Yelp was inspired by a flu.

Mr. Stoppelman, 45, contracted the virus shortly after returning to the Bay Area from business school. This was in 2004, back when the internet had enough information that you could find something about anything, yet was also still new enough that the information was rarely more detailed than what you could find in the Yellow Pages. When Mr. Stoppelman went online to find a doctor and was confronted by a bunch of phone and suite numbers but little about the actual physicians, it gave him an idea.

Yelp began as a word-of-mouth email service before morphing into the local review and directory site that is now worth about $2 billion. That he had a good idea was less important to the company’s success than the Bay Area’s tech ecosystem — the experience and social connections Mr. Stoppelman gained from his previous job at PayPal helped him procure $1 million in start-up funding.

Another factor, Mr. Stoppelman said, was a crucial decision, unusual at the time, to locate the company in a San Francisco office building instead of a Silicon Valley office park.

“I’m not sure that Yelp would have succeeded if we weren’t in the city,” he said. “When you’re in a city, there’s lots of places you might go, and an efficient way to sort through the possibilities is important. Yelp was a killer app for the city.”

San Francisco is about 40 miles from the heart of Silicon Valley, which for the most part consists of low-slung suburban cities that sit along U.S. 101 and have sprawling office campuses surrounded by acres of parking. Until fairly recently, however, the city was considered a subpar place for start-ups.

The downtown business district had historically revolved around banks and insurance companies. And the wave of tech companies that sprouted up in San Francisco during the dot-com boom of the late 1990s became symbols of that period’s delusions when they went out of business during the dot-com bust. Mr. Stoppelman said the surplus of fly-by-night companies gave credence to a joke that circulated around PayPal: Start-ups do better in the suburbs because their workers have less to do outside the office.

But the bust provided an opportunity in the form of cheap office space that proliferated through the city’s South of Market neighborhood, which sits next to the financial district. Besides, for a new generation of start-up founders like Mr. Stoppelman, who was in his 20s and single when Yelp started, the city just seemed more fun.

In San Francisco, and around the country, a growing preference for urban living was showing up in surveys, condo prices and pour-over coffee shops. Economists like Edward Glaeser at Harvard and Richard Florida at the University of Toronto distilled this movement into a sort of new urban theory that said cities were benefiting from several converging trends, including a more tech-driven economy, plunging crime rates and the bubble of young millennials entering the work force.

San Francisco is trying to adapt to what amounts to a three-day workweek. On Wednesdays, offices are at 50 percent of their prepandemic levels; on Fridays, they’re not even at 30 percent.

In his 2002 book, “Rise of the Creative Class,” Mr. Florida posited that instead of seeking lower taxes and operating costs or locating near suburban enclaves with good schools, companies like Yelp were sprouting in cities rich with the design and engineering workers their businesses needed to grow. He parlayed the book’s success into a consulting firm, the Creative Class Group, which advises cities on strategies for attracting young workers.

The advice — find educated workers, create dense fun neighborhoods and embrace social liberalism — could be reduced, effectively, to “become more like San Francisco.”

An irony of San Francisco’s emerging status as an economic bellwether was that until the Great Recession, when a plunge in tax revenue prompted the local government to go scrambling for ways to stimulate growth, the city had made no special effort to attract tech companies. In the wake of the downturn, however, the city altered its tax code to be more welcoming to start-ups, while office owners started offering the shorter leases start-ups desire and open floor plans that allow companies to cram more people together.

Less than a decade later, a city that was never more than a Silicon Valley satellite was the epicenter of a new boom, with companies like Twitter, Lyft, Uber, Dropbox, Reddit and Airbnb all setting up inside the city limits. And the employees who worked there needed lunch.

Ms. Cerros-Mercado, who grew up in the city, watched this unfold while building her career at Specialty’s, a local cafe and sandwich chain known for its giant cookies. She started working there for about $10 an hour and regarded it as a stopping off point that would help support her children as she went through college, with the hopes that she would later go to nursing school.

But she came to like it and rose from being a cashier to a kitchen manager and then general manager who made $80,000 with time off, along with dental and health benefits. The main location where she worked was downtown, next to a Mixt restaurant whose lines spilled onto the street.

The Creative Class and Its Discontents

For the optimized office worker looking for the trifecta of fast, healthy and filling, few meals are more efficient than a pile of veggies and some dressing swirled with tofu or grilled chicken. Unfortunately, the aspirations of a salad are often dashed by the difficulty of making one that is actually good. The ingredients come from every corner of the supermarket, and if they aren’t combined in the right proportions, or if they are made too far in advance, every bite is a drag.

Ms. Silverglide, 42, the chief executive of Mixt, tried to solve this problem with a setup in which customers proceeded down a counter and called out ingredients like grilled chicken and roasted brussels sprouts while stipulating exactly how much dressing they wanted. She said the naysayers of the time told her that there weren’t enough salad eaters to sustain her company, or that only women would eat there.

Instead, lines extended down the block, and Yelp’s users gave the business three and a half stars. People like Mike Ghaffary discovered a healthier kind of lunch in a restaurant where customization was encouraged.

Mr. Ghaffary is a former Yelp executive and serial optimizer who went to Mixt in search of a vegan meal that was high in protein and low in sugar. The salad he came up with paired lentils, chickpeas and quinoa with greens and a cilantro jalapeño vinaigrette.

Over the next several years, as Yelp grew and went public, Mixt thrived alongside it, adding a dozen locations through downtown and other city neighborhoods. Mr. Ghaffary became something of a Mixt evangelist (“He was very proud of the beany salad he came up with,” Mr. Stoppelman said) and ordered his vegetal concoction so frequently that the salad was added to the permanent menu and still sits on the board under the name “Be Well.”

In the city, however, well-being was taking a hit.

The tech companies that San Francisco had tried so hard to attract were now the target of regular protests, including some by demonstrators who at the end of 2013 began blocking commuter buses from Google and other companies to show their rage at rents that now sit at a median of $3,600. This was an opening gesture in what would become an ongoing debate about gentrification and the effect of tech companies on the city — a debate that played out in arguments over homeless camps, votes to stop development and countless more protests.

All of this was rooted in the cost of housing, which had been expensive for decades but had morphed into a disaster. A local government that had all but begged tech companies to set up shop there was now pushing a raft of new taxes to deal with its spiraling affordable housing and homelessness problems. In 2017, the year the Salesforce Tower eclipsed the Transamerica Pyramid as the city’s tallest skyscraper, Mr. Florida published another book. It was called “The New Urban Crisis.”

An axiom of the post-Covid economy is that the pandemic didn’t create new trends so much as it accelerated trends already in place. Such is the case with Yelp, which long ago started moving employees in response to San Francisco’s rising cost of living, opening sales offices around the country and new engineering hubs in London and Toronto.

Still, it was hard to see how that might pose any kind of threat to the city, whose greatest challenge seemed to be dealing with the too many jobs it already had.

Expansions aside, Yelp was still ensconced in its headquarters at 140 New Montgomery, and by early 2020, it had every intention of signing a new lease. The company’s ties to San Francisco, the hold of the creative class and all that, were too strong to imagine anything in its place.

Headquartered in the Cloud

“Have you heard about Covid?”

Ms. Cerros-Mercado remembers asking a regional manager at Specialty’s that question sometime in February or early March of 2020. The virus had been in the news for weeks, but it didn’t seem like more than a seasonal bug until her 19-year-old daughter’s school trip to Spain was canceled. The manager she asked wasn’t so sure.

“He’s like, ‘Oh, it’s just a flulike virus; it will go away,’” she said. “And I’m looking at him and telling him, ‘No, this is actually really serious.’”

Ms. Cerros-Mercado described the following weeks as a blur of plunging sales and eerie moments like standing in a coffee shop with no customers or hearing from a janitor that the offices above them were clearing out. By May, Specialty’s had filed for Chapter 7 bankruptcy after a conference call in which she and other managers were thanked for their service and told they would be employed for three more days, during which they would deliver the news they had just received to the people who worked for them.

“One of the hardest conversations was having to talk to my team,” she said. “I had some team members that were crying because they weren’t sure where their income was going to come from.”

In that moment, the question was when life would return to how it was. But as Mr. Stoppelman discovered that he could run a publicly traded company from his home with no loss of business, he decided that for his company, anyway, the new normal was better. Yelp abandoned its headquarters when the lease at 140 New Montgomery lapsed, joining a growing list of tech companies that had replaced free cafeterias and Ping-Pong breakrooms — which for more than a decade had been rationalized by a belief that a social company was a more innovative company — with slogans like “headquartered in the cloud.”

Yelp ended up adding back about 50,000 feet for employees who want an occasional desk, but for the city that figure is even smaller than it seems. The new offices are one-third of its former footprint; Yelp subleased the space from Salesforce — the city’s largest private employer, which is also cutting back on local offices.

The emptying of American downtowns after Covid was followed by a boom in exurban housing and in cities like Austin and Spokane, trends reflected in where Yelp’s work force has landed. Cortney Ward, 41, a Yelp product designer, bought a home in Austin after leaving her one-bedroom apartment in San Francisco’s Nob Hill. Yelp workers also invented new habits and left holes in the businesses that relied on them. When Diego Waxemberg, 30, a software engineer, left the Bay Area for Charlotte, N.C., he started lunching on leftovers instead of sometimes buying a $17 Mixt salad with tri-tip steak. Mackenzie Bise, 30, who works in user operations, moved to the Sacramento area, and during a recent online search discovered that her favorite San Francisco lunch spot had gone out of business.

During the height of the pandemic, Ms. Cerros-Mercado went through a spell of unemployment before landing at another restaurant chain and later at Mixt. But downtown business was still somewhere between lagging and nonexistent. Mixt laid off hundreds of workers, closed most downtown stores for more than a year and subsisted on business from neighborhood and suburban stores.

“If we didn’t have the neighborhood restaurants, we wouldn’t have survived — point blank,” Ms. Silverglide said.

But for all the daily rhythms that were upended by home offices, the desire for a specially prepared lunch seems to have endured. Consider Mr. Ghaffary, creator of the Be Well salad, who used the pandemic as a challenge to recreate Mixt’s setup in the kitchen of his Marin County home. He started with fresh ingredients but got tired of his frequent trips to the grocery store and shifted to preparing them in bulk.

“I’d make like four or five days of Tupperware,” he said. “First I tried making the whole salad, and then it would get soggy. Then I made half the salad and would finish the rest at the end.”

“I was very proud of my streamlined production methods,” he continued. “And then I was kind of like, ‘I don’t want to be making these salads.’”

Mr. Ghaffary told this story over salad at Mixt’s Mill Valley store, the one Ms. Cerros-Mercado manages, which opened in July and had lines of customers in athleisure. Operations are slightly more difficult because some employees commute an hour or more to get there, most relying on buses and one sometimes trying to catch a ride in Ms. Cerros-Mercado’s Uber. When a worker misses the bus, Ms. Cerros-Mercado spends her morning trying to cover for holes in the setup line.

But the business was steady, and according to Ms. Silverglide it extends until 9 at night, catering to families and a growing salad-for-dinner segment that pairs plates of greens with the various wines and craft beers recently added to the menu. She is fairly confident that Mixt’s “neighborhood locations,” like the Mill Valley one, will drive the business’s expansion. Business in downtown San Francisco has been picking up — but it’s unclear how long that will last, or how close to prepandemic traffic it will ever reach. The offices, after all, haven’t even hit 50 percent.

Better Together

A wood reception desk that used to greet Yelp’s visitors sits empty in its former office. The mounted iPad where visitors once checked in is gone, along with the bright jars of candy and the rows of desks that sat beyond them. But there are still views.

“You can see that you get good natural light all around,” said Stacey Spurr, a regional director for Pembroke, which owns 140 New Montgomery, during a recent tour of the quiet and empty but still quite gorgeous building.

Ms. Spurr began the tour by pointing out the gold ceilings in the lobby before proceeding to the basement, where there are showers and bike racks. The empty floors upstairs are layered with boastful stickers like the one about the building’s A-plus air filtration system.

The nearly 160,000 square feet that Yelp left empty is about half of the building’s space, and about half of that has been re-leased. The good news for Pembroke seems less good for the city. Some of the new tenants are finance and venture capital firms that have clung to the gravitas of a physical office for client meetings and the occasional conference but are unlikely to contribute regular foot traffic, according to building owners across the city.

In a typical downturn, the turnaround is a fairly simple equation of rents falling far enough to attract new tenants and the economy improving fast enough to stimulate new demand. But now there’s a more existential question of what the point of a city’s downtown even is.

The city, and business groups like Advance SF, are trying to reframe the urban core as a more residential and entertainment district that draws from throughout the region and may in the future involve the conversion of office buildings to residential use. The motto is “Better Together,” and Advance SF recently hosted a forum with a guest economist to discuss new ideas for downtown. The guest was Richard Florida.

“When I started with the creative class, places didn’t care about young people, they were only trying to attract a family with children to the lovely suburbs, and I’m saying, ‘No, no, no, no, no,’” Mr. Florida said in an interview. “Twenty years later, people forgot about the families. And now here’s a whole generation leaving cities again, for metropolitan or virtual suburbs.”

The more businesses invest with that new reality in mind, the more likely that reality becomes self-fulfilling.

A year after being consumed by bankruptcy, Specialty’s, the cafe chain where Ms. Cerros-Mercado began her career, was reincarnated. The first new store sits in the Silicon Valley town of Mountain View, and as the company plots its next expansion it is eschewing the office-adjacent locations on which the original company was built for a more delivery-centric business that has a world of half-empty buildings in mind.

Back at 140 New Montgomery, the owners are experimenting with new ideas to get office workers to come in. The building has been hosting gatherings like an Oktoberfest celebration that included a raffle to win a beer stein with the building’s logo.

On the afternoon of the Oktoberfest party, a cluster of workers from a software company stood around eating sausages and soft pretzels.

“We hear a lot of buzz about this building,” said Veronica Arvizu, a senior property manager at the real estate company CBRE. “We hear it’s the busiest in the city.”

A few feet away from her, another group of young workers was playing Jenga. One by one, they took blocks away from the structure, making way for the inevitable collapse.

Conor Dougherty is an economics reporter and the author of “Golden Gates: Fighting for Housing in America.” His work focuses on the West Coast, real estate 

Race to Develop the Quantum Computer

Annals of Technology

The World-Changing Race to Develop the Quantum Computer

Such a device could help address climate change and food scarcity, or break the Internet. Will the U.S. or China get there first?

Stephen Witt The New Yorker

On the outskirts of Santa Barbara, California, between the orchards and the ocean, sits an inconspicuous warehouse, its windows tinted brown and its exterior painted a dull gray. The facility has almost no signage, and its name doesn’t appear on Google Maps. A small label on the door reads “Google AI Quantum.” Inside, the computer is being reinvented from scratch.

In September, Hartmut Neven, the founder of the lab, gave me a tour. Neven, originally from Germany, is a bald fifty-seven-year-old who belongs to the modern cast of hybridized executive-mystics. He talked of our quantum future with a blend of scientific precision and psychedelic glee. He wore a leather jacket, a loose-fitting linen shirt festooned with buttons, a pair of jeans with zippered pockets on the legs, and Velcro sneakers that looked like moon boots. “As my team knows, I never miss a single Burning Man,” he told me.

In the middle of the warehouse floor, an apparatus the size and shape of a ballroom chandelier dangled from metal scaffolding. Bundles of cable snaked down from the top through a series of gold-plated disks to a processor below. The processor, named Sycamore, is a small, rectangular tile, studded with several dozen ports. Sycamore harnesses some of the weirdest properties of physics in order to perform mathematical operations that contravene all human intuition. Once it is connected, the entire unit is placed inside a cylindrical freezer and cooled for more than a day. The processor relies on superconductivity, meaning that, at ultracold temperatures, its resistance to electricity all but disappears. When the temperature surrounding the processor is colder than the deepest void of outer space, the computations can begin.

Classical computers speak in the language of bits, which take values of zero and one. Quantum computers, like the ones Google is building, use qubits, which can take a value of zero or one, and also a complex combination of zero and one at the same time. Qubits are thus exponentially more powerful than bits, able to perform calculations that normal bits can’t. But, because of this elemental change, everything must be redeveloped: the hardware, the software, the programming languages, and even programmers’ approach to problems.

On the day I visited, a technician—whom Google calls a “quantum mechanic”—was working on the computer with an array of small machine tools. Each qubit is controlled by a dedicated wire, which the technician, seated on a stool, attached by hand.

The quantum computer before us was the culmination of years of research and hundreds of millions of dollars in investment. It also barely functioned. Today’s quantum computers are “noisy,” meaning that they fail at almost everything they attempt. Nevertheless, the race to build them has attracted as dense a concentration of genius as any scientific problem on the planet. Intel, I.B.M., Microsoft, and Amazon are also building quantum computers. So is the Chinese government. The winner of the race will produce the successor to the silicon microchip, the device that enabled the information revolution.

A full-scale quantum computer could crack our current encryption protocols, essentially breaking the Internet. Most online communications, including financial transactions and popular text-messaging platforms, are protected by cryptographic keys that would take a conventional computer millions of years to decipher. A working quantum computer could presumably crack one in less than a day. That is only the beginning. A quantum computer could open new frontiers in mathematics, revolutionizing our idea of what it means to “compute.” Its processing power could spur the development of new industrial chemicals, addressing the problems of climate change and food scarcity. And it could reconcile the elegant theories of Albert Einstein with the unruly microverse of particle physics, enabling discoveries about space and time. “The impact of quantum computing is going to be more profound than any technology to date,” Jeremy O’Brien, the C.E.O. of the startup PsiQuantum, said recently. First, though, the engineers have to get it to work.

Imagine two pebbles thrown into a placid lake. As the stones hit the surface, they create concentric ripples, which collide to produce complicated patterns of interference. In the early twentieth century, physicists studying the behavior of electrons found similar patterns of wavelike interference in the subatomic world. This discovery led to a moment of crisis, since, under other conditions, those same electrons behaved more like individual points in space, called particles. Soon, in what many consider the most bizarre scientific result of all time, the physicists realized that whether an electron behaved more like a particle or more like a wave depended on whether or not someone was observing it. The field of quantum mechanics was born.

In the following decades, inventors used findings from quantum mechanics to build all sorts of technology, including lasers and transistors. In the early nineteen-eighties, the physicist Richard Feynman proposed building a “quantum computer” to obtain results that could not be calculated by conventional means. The reaction from the computer-science community was muted; early researchers had trouble getting slots at conferences. The practical utility of such a device was not demonstrated until 1994, when the mathematician Peter Shor, working at Bell Labs in New Jersey, showed that a quantum computer could help crack some of the most widely used encryption standards. Even before Shor published his results, he was approached by a concerned representative of the National Security Agency. “Such a decryption ability could render the military capabilities of the loser almost irrelevant and its economy overturned,” one N.S.A. official later wrote.

Shor is now the chair of the applied-mathematics committee at the Massachusetts Institute of Technology. I visited him there in August. His narrow office was dominated by a large chalkboard spanning one wall, and his desk and his table were overflowing with scratch paper. Cardboard boxes sat in the corner, filled to capacity with Shor’s scribbled handiwork. One of the boxes was from the bookseller Borders, which went out of business eleven years ago.

Shor wears oval glasses, his belly is rotund, his hair is woolly and white, and his beard is unkempt. On the day I met him, he was drawing hexagons on the chalkboard, and one of his shoes was untied. “He looks exactly like the man who would invent algorithms,” a comment on a video of one of his lectures reads.

An algorithm is a set of instructions for calculation. A child doing long division is following an algorithm; so is a supercomputer simulating the evolution of the cosmos. The formal study of algorithms as mathematical objects only began in the twentieth century, and Shor’s research suggests that there is much we don’t understand. “We are probably, when it comes to algorithms, at the level the Romans were vis-à-vis numbers,” the experimental physicist Michel Devoret told me. He compared Shor’s work to the breakthroughs made with imaginary numbers in the eighteenth century.

Shor can be obsessive about algorithms. “I think about them late at night, in the shower, everywhere,” he said. “Interspersed with that, I scribble funny symbols on a piece of paper.” Sometimes, when a problem is especially engrossing, Shor will not notice that other people are talking to him. “It’s probably very annoying for them,” he said. “Except for my wife. She’s used to it.” Neven, of Google, recalled strolling with Shor through Cambridge as he expounded on his latest research. “He walked right through four lanes of traffic,” Neven said. (Shor told me that both of his daughters have been diagnosed with autism. “Of course, I have some of those traits myself,” he said.)

Shor’s most famous algorithm proposes using qubits to “factor” very large numbers into smaller components. I asked him to explain how it works, and he erased the hexagons from the chalkboard. The key to factoring, Shor said, is identifying prime numbers, which are whole numbers divisible only by one and by themselves. (Five is prime. Six, which is divisible by two and by three, is not.) There are twenty-five prime numbers between one and a hundred, but as you count higher they become increasingly rare. Shor, drawing a series of compact formulas on the chalkboard, explained that certain sequences of numbers repeat periodically along the number line. The distances between these repetitions grow exponentially, however, making them difficult to calculate with a conventional computer.

Shor then turned to me. “O.K., here is the heart of my discovery,” he said. “Do you know what a diffraction grating is?” I confessed that I did not, and Shor’s eyes grew wide with concern. He began drawing a simple sketch of a light beam hitting a filter and then diffracting into the colors of the rainbow, which he illustrated with colored chalk. “Each color of light has a wavelength,” Shor said. “We’re doing something similar. This thing is really a computational diffraction grating, so we’re sorting out the different periods.” Each color on the chalkboard represented a different grouping of numbers. A classical computer, looking at these groupings, would have to analyze them one at a time. A quantum computer could process the whole rainbow at once.

The challenge is to realize Shor’s theoretical work with physical hardware. In 2001, experimental physicists at I.B.M. tried to implement the algorithm by firing electromagnetic pulses at molecules suspended in liquid. “I think that machine cost about half a million dollars,” Shor said, “and it informed us that fifteen equals five times three.” Classical computing’s bits are relatively easy to build—think of a light switch, which can be turned either “on” or “off.” Quantum computing’s qubits require something like a dial, or, more accurately, several dials, each of which must be tuned to a specific amplitude. Implementing such precise controls at the subatomic scale remains a fiendish problem.

Still, in anticipation of the day that security experts call Y2Q , the protocols that safeguard text messaging, e-mail, medical records, and financial transactions must be torn out and replaced. ​Earlier this year, the Biden Administration announced that it was moving toward new, quantum-proof encryption standards that offer protection from Shor’s algorithm. Implementing them is expected to take more than a decade and cost tens of billions of dollars, creating a bonanza for cybersecurity experts. “The difference between this and Y2K is we knew the actual date when Y2K would occur,” the cryptographer Bruce Schneier told me.

In anticipation of Y2Q , spy agencies are warehousing encrypted Internet traffic, hoping to read it in the near future. “We are seeing our adversaries do this—copying down our encrypted data and just holding on to it,” Dustin Moody, the mathematician in charge of U.S. post-quantum encryption standards, said. “It’s definitely a real threat.” (When I asked him if the U.S. government was doing the same, Moody said that he didn’t know.) Within a decade or two, most communications from this era will likely be exposed. The Biden Administration’s deadline for the cryptography upgrade is 2035. A quantum computer capable of running a simple version of Shor’s algorithm could appear as early as 2029.

At the root of quantum-computing research is a scientific concept known as “quantum entanglement.” ​​Entanglement is to computing what nuclear fission was to explosives: a strange property of the subatomic world that could be harnessed to create technology of unprecedented power. If entanglement could be enacted at the scale of everyday objects, it would seem like a magic trick. Imagine that you and a friend flip two entangled quarters, without looking at the results. The outcome of the coin flips will be determined only when you peek at the coins. If you inspect your quarter, and see that it came up heads, your friend’s quarter will automatically come up tails. If your friend looks and sees that her quarter shows heads, your quarter will now show tails. This property holds true no matter how far you and your friend travel from each other. If you were to travel to Germany—or to Jupiter—and look at your quarter, your friend’s quarter would instantaneously reveal the opposite result.

If you find entanglement confusing, you are not alone: it took the scientific community the better part of a century to begin to understand its effects. Like so many concepts in physics, entanglement was first described in one of Einstein’s Gedankenexperiments. Quantum mechanics dictated that the properties of particles assumed fixed values only once they were measured. Before that, a particle existed in a “superposition” of many states at once, which were described using probabilities. (A famous thought experiment, proposed by the physicist Erwin Schrödinger, imagined a cat trapped in a box with a quantum-activated vial of poison, the cat superpositioned in a state between life and death.) This disturbed Einstein, who spent his later years formulating objections to the “new physics” of the generation that had succeeded him. In 1935, working with the physicists Boris Podolsky and Nathan Rosen, he revealed an apparent paradox in quantum mechanics: if one took the implications of the discipline seriously, it should be possible to create two entangled particles, separated by any distance, that could somehow interact faster than the speed of light. “No reasonable definition of reality could be expected to permit this,” Einstein and his colleagues wrote. In subsequent decades, however, the other predictions of quantum mechanics were repeatedly verified in experiments, and Einstein’s paradox was ignored. “Because his views went against the prevailing wisdom of his time, most physicists took Einstein’s hostility to quantum mechanics to be a sign of senility,” the historian of science Thomas Ryckman wrote.

Mid-century physicists focussed on particle accelerators and nuclear warheads; entanglement received little attention. In the early sixties, the Northern Irish physicist John Stewart Bell, working alone, reformulated Einstein’s thought experiment into a five-page mathematical argument. He published his results in the obscure journal Physics Physique Fizika in 1964. During the next four years, his paper was not cited a single time.

In 1967, John Clauser, a graduate student at Columbia University, came across Bell’s paper while paging through a bound volume of the journal at the library. Clauser had struggled with quantum mechanics, taking the course three times before receiving an acceptable grade. “I was convinced that quantum mechanics had to be wrong,” he later said. Bell’s paper provided Clauser with a way to put his objections to the test. Against the advice of his professors—including Richard Feynman—he decided to run an experiment that would vindicate Einstein, by proving that the theory of quantum mechanics was incomplete. In 1969, Clauser wrote a letter to Bell, informing him of his intentions. Bell responded with delight; no one had ever written to him about his theorem before.

Clauser moved to the Lawrence Berkeley National Laboratory, in California, where, working with almost no budget, he created the world’s first deliberately entangled pair of photons. When the photons were about ten feet apart, he measured them. Observing an attribute of one photon instantly produced opposite results in the other. Clauser and Stuart Freedman, his co-author, published their findings in 1972. From Clauser’s perspective, the experiment was a disappointment: he had definitively proved Einstein wrong. Eventually, and with great reluctance, Clauser accepted that the baffling rules of quantum mechanics were, in fact, valid, and what Einstein considered a grotesque affront to human intuition was merely the way the universe works. “I confess even to this day that I still don’t understand quantum mechanics,” Clauser said, in 2002.

But Clauser had also demonstrated that entangled particles were more than just a thought experiment. They were real, and they were even stranger than Einstein had thought. Their weirdness attracted the attention of the physicist Nick Herbert, a Stanford Ph.D. and LSD enthusiast whose research interests included mental telepathy and communication with the afterlife. Clauser showed Herbert his experiment, and Herbert proposed a machine that would use entanglement to communicate faster than the speed of light, enabling the user to send messages backward through time. Herbert’s blueprint for a time machine was ultimately deemed unfeasible, but it forced physicists to start taking entanglement seriously. “Herbert’s erroneous paper was a spark that generated immense progress,” the physicist Asher Peres recalled, in 2003.

Ultimately, the resolution to Einstein’s paradox was not that the particles could signal faster than light; instead, once entangled, they ceased to be distinct objects, and functioned as one system that existed in two parts of the universe at the same time. (This phenomenon is called nonlocality.) Since the eighties, research into entanglement has led to continuing breakthroughs in both theoretical and experimental physics. In October, Clauser shared the Nobel Prize in Physics for his work. In a press release, the Nobel committee described entanglement as “the most powerful property of quantum mechanics.” Bell did not live to see the revolution completed; he died in 1990. Today, his 1964 paper has been cited seventeen thousand times.

At Google’s lab in Santa Barbara, the objective is to entangle many qubits at once. Imagine hundreds of coins, arranged into a network. Manipulating these coins in choreographed sequences can produce astonishing mathematical effects. One example is Grover’s algorithm, developed by Lov Grover, Shor’s colleague at Bell Labs in the nineties. “Grover’s algorithm is about unstructured search, which is a nice example for Google,” Neven, the founder of the lab, said. “I like to think about it as a huge closet with a million drawers.” One of the drawers contains a tennis ball. A human rooting around in the closet will, on average, find the ball after opening half a million drawers. “As amazing as this may sound, Grover’s algorithm could do it in just one thousand steps,” Neven said. “I think the whole magic of quantum mechanics can essentially be seen here.”

Neven has had a peripatetic career. He originally majored in economics, but switched to physics after attending a lecture on string theory. He earned a Ph.D. focussing on computational neuroscience, and was hired as a professor at the University of Southern California. While he was at U.S.C., his research team won a facial-recognition competition sponsored by the U.S. Department of Defense. He started a company, Neven Vision, which developed the technology used in social-media face filters; in 2006, he sold the company to Google, for forty million dollars. At Google, he worked on image search and Google Glass, switching to quantum computing after hearing a story about it on public radio. His ultimate objective, he told me, is to explore the origins of consciousness by connecting a quantum computer to someone’s brain.

Neven’s contributions to facial-analysis technology are widely admired, and if you have ever pretended to be a dog on Snapchat you have him to thank. (You may thank him for the more dystopian applications of this technology as well.) But, in the past few years, in research papers published in the world’s leading scientific journals, he and his team have also unveiled a series of small, peculiar wonders: photons that bunch together in clumps; identical particles whose properties change depending on the order in which they are arranged; an exotic state of perpetually mutating matter known as a “time crystal.” “There’s literally a list of a dozen things like this, and each one is about as science fictiony as the next,” Neven said. He told me that a team led by the physicist Maria Spiropulu had used Google’s quantum computer to simulate a “holographic wormhole,” a conceptual shortcut through space-time—an achievement that recently made the cover of Nature.

Google’s published scientific results in quantum computing have at times drawn scrutiny from other researchers. (One of the Nature paper’s authors called their wormhole the “smallest, crummiest wormhole you can imagine.” Spiropulu, who owns a dog named Qubit, concurred. “It’s really very crummy, for real,” she told me.) “With all these experiments, there’s still a huge debate as to what extent are we actually doing what we claim,” Scott Aaronson, a professor at the University of Texas at Austin who specializes in quantum computing, said. “You kind of have to squint.” Nor will quantum computing replace the classical approach anytime soon. “Quantum computers are terrible at counting,” Marissa Giustina, a research scientist at Google, said. “We got ours to count to four.”

Giustina is one of the world’s leading experts on entanglement. In 2015, while working in the laboratory of the Austrian professor Anton Zeilinger, she ran an updated version of Clauser’s 1972 experiment. In October, Zeilinger was named a Nobel laureate, too. “After that, I got a bunch of pings saying, ‘Congratulations on winning your boss the Nobel Prize,’ ” Giustina said. She talked with some frustration about a machine that may soon model complex molecules but for now can’t do basic arithmetic. “It’s antithetical to what we experience in our everyday lives,” she said. “That’s what’s so annoying about it, and so beautiful.”

The main problem with Google’s entangled qubits is that they are not “fault-tolerant.” The Sycamore processor will, on average, make an error every thousand steps. But a typical experiment requires far more than a thousand steps, so, to obtain meaningful results, researchers must run the same program tens of thousands of times, then use signal-processing techniques to refine a small amount of valuable information from a mountain of data. The situation might be improved if programmers could inspect the state of the qubits while the processor is running, but measuring a superpositioned qubit forces it to assume a specific value, causing the calculation to deteriorate. Such “measurements” need not be made by a conscious observer; any number of interactions with the environment will result in the same collapse. “Getting quiet, cold, dark places for qubits to live is a fundamental part of getting quantum computing to scale,” Giustina said. Google’s processors sometimes fail when they encounter radiation from outside our solar system.

In the early days of quantum computing, researchers worried that the measurement problem was intractable, but in 1995 Peter Shor showed that entanglement could be used to correct errors, too, ameliorating the high fault rate of the hardware. Shor’s research attracted the attention of Alexei Kitaev, a theoretical physicist then working in Moscow. In 1997, Kitaev improved on Shor’s codes with a “topological” quantum-error-correction scheme. John Preskill, a theoretical physicist at Caltech, spoke of Kitaev, who is now a professor at the school, with something approaching awe. “He’s very creative, and he’s technically very deep,” Preskill said. “He’s one of the few people I know that I can call, without any hesitation, a genius.”

I met Kitaev in his spacious office at Caltech, which was almost completely empty. He was wearing running shoes. After spending the day thinking about particles, Kitaev told me, he walks for about an hour to clear his mind. On hard days, he might walk for longer. A few miles north of Caltech sits Mt. Wilson, where, in the nineteen-twenties, Edwin Hubble used what was then the world’s largest telescope to deduce that the universe was expanding. “I’ve been on Mt. Wilson maybe a hundred times,” Kitaev said. When a problem is really tough, Kitaev skips Mt. Wilson, and instead hikes nearby Mt. Baldy, a ten-thousand-foot peak that is often covered in snow.

Quantum computing is a Mt. Baldy problem. “I made a prediction, in 1998, that the computers would be realized in thirty years,” Kitaev said. “I’m not sure we’ll make it.” Kitaev’s error-correction scheme is one of the most promising approaches to building a functional quantum computer, and, in 2012, he was awarded the Breakthrough Prize, the world’s most lucrative science award, for his work. Later, Google hired him as a consultant. So far, no one has managed to implement his idea.

Preskill and Kitaev teach Caltech’s introductory quantum-computing course together, and their classroom is overflowing with students. But, in 2021, Amazon announced that it was opening a large quantum-computing laboratory on Caltech’s campus. Preskill is now an Amazon Scholar; Kitaev remained with Google. The two physicists, who used to have adjacent offices, today work in separate buildings. They remain collegial, but I sensed that there were certain research topics on which they could no longer confer.

In early 2020, scientists at Pfizer began producing hundreds of experimental pharmaceuticals intended to treat covid-19. That July, they synthesized seven milligrams of a research chemical labelled PF-07321332, one of twenty formulations the company produced that week. PF-07321332 remained an anonymous vial in a laboratory refrigerator until September, when experiments showed that it was effective at suppressing covid-19 in rats. The chemical was subsequently combined with another substance and rebranded as Paxlovid, a drug cocktail that reduces covid-19-related hospitalizations by some ninety per cent. Paxlovid is a lifesaver, but, with the assistance of a quantum computer, the laborious process of trial and error that led to its development might have been shortened. “We are just guessing at things that can be directly designed,” the venture capitalist Peter Barrett, who is on the board of the startup PsiQuantum, told me. “We’re guessing at things which our civilization entirely depends on—but that is by no means optimal.”

Fault-tolerant quantum computers should be able to simulate the molecular behavior of industrial chemicals with unprecedented precision, guiding scientists to faster results. In 2019, researchers predicted that, with just a thousand fault-tolerant qubits, a method for producing ammonia for agricultural use, called the Haber-Bosch process, could be accurately modelled for the first time. An improvement to this process would lead to a substantial decrease in carbon-dioxide emissions. Lithium, the primary component of batteries for electric cars, is a simple element with an atomic number of three. A fault-tolerant quantum computer, even a primitive one, might show how to expand its capacity to store energy, increasing vehicle range. Quantum computers could be used to develop biodegradable plastics, or carbon-free aviation fuel. Another use, suggested by the consulting company McKinsey, was “simulating surfactants to develop a better carpet cleaner.” “We have good reason to believe that a quantum computer would be able to efficiently simulate any process that occurs in nature,” Preskill wrote, a few years ago.

The world we live in is the macroscopic scale. It is the world of ordinary kinetics: billiard balls and rocket ships. The world of subatomic particles is the quantum scale. It is the world of strange effects: interference and uncertainty and entanglement. At the boundary of these two worlds is what scientists call the “nanoscopic” scale, the world of molecules. For the most part, molecules behave like billiard balls, but if you zoom in close enough you begin to notice quantum effects. It is at the nanoscopic scale that researchers expect quantum computing to solve its first meaningful problems, in pharmaceuticals and materials design, perhaps with just a few hundred fault-tolerant qubits. And it is in this discipline—quantum molecular chemistry—that analysts expect the first real money in quantum computing to be made. Quantum physics wins the Nobel. Quantum chemistry will write the checks.

The potential windfall from licensing royalties has excited investors. In addition to the tech giants, a raft of startups are trying to build quantum computers. The Quantum Insider, an industry trade publication, has tallied more than six hundred companies in the sector, and another estimate suggests that thirty billion dollars has been invested in developing quantum technology worldwide. Many of these businesses are speculative. IonQ , based in College Park, Maryland, went public last year, despite having almost no sales. Researchers there compute with qubits obtained using the “trapped ion” approach, arranging atoms of the rare-earth element ytterbium into a tidy row, then manipulating them with a laser. Jungsang Kim, IonQ’s C.T.O., told me that his ion traps maintain entanglement better than Google’s processors, but he admitted that, as more qubits are added, the laser system gets more complicated. “Improving the controller, that’s kind of our sticking point,” he said.

At PsiQuantum, in Palo Alto, engineers are making qubits from photons, the weightless particles of light. “The advantage of this approach is that we use preëxisting silicon-fabrication technology,” Pete Shadbolt, the company’s chief scientific officer, said. “Also, we can operate at somewhat higher temperatures.” PsiQuantum has raised half a billion dollars. There are other, weirder approaches. Microsoft, building on Kitaev’s work, is attempting to construct a “topological” qubit, which requires synthesizing an elusive particle in order to work. Intel is trying the “silicon spin” approach, which embeds qubits in semiconductors. The competition has led to bidding wars for talent. “If you have an advanced degree in quantum physics, you can go out into the job market and get five offers in three weeks,” Kim said.

Even the most optimistic analysts believe that quantum computing will not earn meaningful profits in the next five years, and pessimists caution that it could take more than a decade. It seems likely that a lot of expensive equipment will be developed with little durable purpose. “You walk down the hall at the Computer History Museum, in Mountain View, and you see a mercury delay line,” Shadbolt said, referring to an obsolete contraption from the nineteen-forties that stored information using sound waves. “I love thinking about the guys who built that.”

It is difficult, even for insiders, to determine which approach is currently in the lead. “ ‘Pivot’ is the Silicon Valley word for a near-death experience,” Neven said. “But if one day we see that superconducting qubits are outcompeted by some other technology, like photonics, I would pivot in a heartbeat.” Neven actually seemed relieved by the competition. His laboratory is expensive, and quantum computing is the kind of moon-shot project that thrived during the era of low interest rates. “Because of the present financial situation, startups in our field have more difficulties finding investors,” Devoret, the experimental physicist, told me. But, as long as Amazon is investing in quantum computing, it’s a good bet that Google will keep funding it, too. There is also the tacit support of the state—the U.S. intelligence apparatus has made quantum decryption a priority, regardless of market fluctuations. In fact, Neven’s stiffest competition comes not from the private sector but from the Chinese Communist Party. John Martinis, a former head of quantum computing at Google, said, “In terms of making high-quality qubits, one could say the Chinese are in the lead.”

At the campuses of the University of Science and Technology of China, four competing quantum-computing technologies are being developed in parallel. In a paper published in Science, in 2020, a team led by the scientists Lu Chao-Yang and Pan Jian-Wei announced that their processor had solved a computational task millions of times faster than the best supercomputer. Pan is one of the most daring researchers in quantum entanglement. In 2017, his team ran an experiment that entangled two photons at an observatory in Tibet, and transmitted one of them to an orbiting satellite. The scientists then transferred attributes from a third photon on Earth to the one in space, using the technique of “quantum teleportation.”

Lu and I spoke by video earlier this year. He joined the call late and was covered in sweat, having sprinted home from a mandatory covid test. Lu immediately began debunking claims made by his competitors, and even claims made about his own effort. One widely reported figure stated that China has invested fifteen billion dollars in developing a quantum computer. “I have no idea how that was started,” Lu said. “The actual money is maybe twenty-five per cent of that.”

Jiuzhang, Lu’s photonic quantum computer, is undoubtedly one of the world’s fastest, but Lu has repeatedly chided his colleagues for overhyping the technology. On our call, he pulled up a video clip of a woman attempting to arrange ten kittens in a line. “Here is the problem we face,” he said. A kitten scurried to the back and the woman raced to grab it. “You want to control multiple qubits with high precision,” Lu said, “but they should be very well isolated from the environment.” As the woman replaced the first kitten, several others fled.

Lu cautioned that quantum computers faced stiff competition from ordinary silicon chips. The earliest electronic computers, from the forties, had to beat only humans. Quantum computers must prove their superiority to supercomputers that can run a quintillion calculations per second. “We see fairly few quantum algorithms where there is proof of exponential speedup,” he said. “In many cases, it’s not clear that it wouldn’t be better to use a regular computer.” Lu also disputed Martinis’s contention that China was making the best qubits. “Actually, I think Google’s in the lead,” he said.

Neven agreed. “Sometime in the next year, I think we will make the first fully fault-tolerant qubit,” he said. From there, Google plans to scale up its computing effort by chaining processors together. Adjacent to the warehouse I visited was a second, bigger space, where sunshine streamed into a dusty construction site. There, Google plans to build a computer that will require a freezer as large as a one-car garage. A thousand fault-tolerant qubits should be enough to run accurate simulations of molecular chemistry. Ten thousand fault-tolerant qubits could begin to unlock new findings in particle physics. From there, researchers could start to run Shor’s algorithm at full power, exposing the secrets of our era. “It’s quite possible that I will die before it happens,” Shor, who is sixty-three, told me. “But I would really like to see it happen, and I think it’s also quite possible that I will live long enough to see it.” ♦

Published in the print edition of the December 19, 2022, issue, with the headline “The Future of Everything.”