scientificamerican--2020-12-04--Coronavirus News Roundup: November 28-December 4

The items below are highlights from the free newsletter , “ Smart , useful , science stuff about COVID-19.
” To receive newsletter issues daily in your inbox , sign up here .
Canada has pre-ordered more doses per person of vaccines against SARS-CoV-2 than have any other countries and purchasing groups , reports freelance science journalist Asher Mullard for Nature ( 11/30/20 ) .
The U.S. and UK come in 2nd and 3rd .
The story includes 2 graphics that illustrate the pre-ordering landscape .
“ Many people in low-income countries might have to wait until 2023 or 2024 @ @ @ @ @ @ @ the Duke Global Health Innovation Center , ” Mullard writes .
The makers of three vaccines that look like they will be distributed widely in 2021 ( AstraZeneca , Moderna , and Pfizer/BioNTech ) forecast making an estimated total of 5.3 billion doses next year .
That would cover between 2.6 billion and 3.1 billion people , the story states .
Most of those doses are already spoken for by individual , largely affluent or middle-income countries , the story states , leaving little for low- and middle-income nations , “ most of @ @ @ @ @ @ @ from ” a joint venture called COVAX .
The purchasing and distribution group was formed to ensure equitable global access to vaccines against SARS-CoV-2 .
Virologist and vaccine researcher Shane Crotty at the La Jolla Institute for Immunology tweeted a thread on 11/27/20 discussing the safety of RNA vaccines ( like those being tested by Moderna and Pfizer/BioNTech on large numbers of people and expected to receive emergency-use approval soon by the U.S. Food and Drug Administration ) .
Crotty writes that RNA is analogous in some ways to expiring messages on social @ @ @ @ @ @ @ are “ temporary messages instructing cells to make one viral protein temporarily.
” He adds , “ It takes 25 different coronavirus proteins [ complex molecules ] to make a coronavirus , so there is no worry about the RNA making a virus.
” Below is an estimated timeline for SARS-CoV-2 vaccine distribution in the U.S. , based on a thread tweeted by Dr. Ashish Jha , dean of the Brown University School of Public Health , on 11/22/20 .
Jha drew the details in part from a televised interview between CNN ’ @ @ @ @ @ @ @ , chief scientific advisor to Operation Warp Speed ( the U.S. ’ s federally funded vaccine development effort ) : https : //threadreaderapp.com/thread/1330519144178085899.html • First public immunizations ( health care workers and long-term care facility residents , if U.S. Centers for Disease Control ’ s 12/2/20 recommendations are followed ) would start Dec. 11 or 12 ; • perhaps 20 million people in U.S. vaccinated by end of December ; • about 30 million more people in U.S. vaccinated by end of January 2021 , and combined with total people who have recovered @ @ @ @ @ @ @ slow spread , ” Jha writes ; • about 40 percent immunity in the U.S. population by February , bringing “ meaningfully slower ” spread of SARS-CoV-2 ; • vaccines widely available in U.S. by April/May 2021 Moderna says it will soon start testing its messenger-RNA vaccine against SARS-CoV-2 in 3,000 teenagers , reports Denise Grady at The New York Times ( 12/2/20 ) .
AstraZeneca and Pfizer/BioNTech already made similar announcements for testing their vaccines in children , the story states .
All three vaccine groups each recently announced that their vaccines @ @ @ @ @ @ @ , but “ no vaccine can be widely given to children until it has been tested in them , ” Grady writes .
“ Vaccines meant for both adults and children are generally tested first in adults to help make sure they are safe for pediatric trials [ experiments ] .
” Vaccines that work well in adults tend to also work well in children , with some dosing adjustments , according to Dr. Paul Offit , a vaccine researcher at Children ’ s Hospital of Philadelphia , Grady writes : https : @ @ @ @ @ @ @ wearing even an N95 mask during vigorous exercise did not result in workouts that felt harder or actually were more physiologically draining , writes Gretchen Reynolds at The New York Times ( 11/18/20 ) .
One of the studies found more carbon dioxide in the breath of N95-masked exercisers , but none of the subjects complained of headaches or breathing issues , the story states .
The results came as a surprise to the study subjects , Reynolds writes .
The studies were conducted on healthy , active adults , so it is @ @ @ @ @ @ @ the same in people who are less healthy or less active or who have breathing problems , the story states .
“ The findings suggest that anyone who hesitates to wear a mask during exercise should try one — although not an N95 mask , ” the story describes one of the study authors , an internal medicine physician at Rambam Health Care Campus , as saying .
Those masks slightly increase exercisers ’ carbon dioxide levels and should be reserved for health care workers anyway , states the story , which also @ @ @ @ @ @ @ , the U.S. Centers for Disease Control ( CDC ) released recommendations ( on 12/2/20 ) that include shortening the quarantine period from 14 days to as few as 7 days , at least for people who think they ’ ve could ’ ve been exposed to SARS-CoV-2 but then test negative , reports Colin Dwyer at NPR .
“ People should still watch closely for symptoms — such as a fever , a cough or a loss of taste or smell — for a full 14 days after possible exposure , ” @ @ @ @ @ @ @ manager for its COVID-19 response , Dwyer writes .
The change is meant to increase the odds that people will comply with the agency ’ s quarantine recommendations , the story states .
It also “ allows health officials to focus their efforts on the period of time that people are most likely to become contagious , ” the story quotes epidemiologist Jennifer Nuzzo of the Johns Hopkins Center for Health Security as saying ( 12/2/20 ) .
And if you ’ re confused about the meaning of quarantine versus isolation , or @ @ @ @ @ @ @ , and the like , check out this helpful piece , “ Clarifying COVID-19 terminology , ” by Lindsay Smith Rogers for Johns Hopkins Bloomberg School of Public Health ( 11/23/20 ) .
An 11/16/20 Q & A at Scientific American with Andrew Huberman , a Stanford University neuroscientist who studies the visual system , details how our vision and our breathing can “ offer us easy and accessible releases from stress , ” particularly in the context of the pandemic challenges and overall intensity of 2020 .
For instance , emerging research @ @ @ @ @ @ @ brain regions responsible for arousal and panic , writes freelance science journalist Jessica Wapner in the introduction to the Q & A .
And when we see stressful or exciting news , it increases our heart rate and breathing , Huberman says .
You don ’ t want to miss this section : Our eyes are “ not connected to the brain ; they are the brain , ” Huberman says .
“ During development , the eyes are part of the embryonic forebrain .
Your eyes get extruded from the skull during @ @ @ @ @ @ @ reconnect to the rest of the brain.
” One of the tips Huberman mentions : one can turn off their brain 's stress response by changing the way we are viewing our environment , specifically by taking on a panoramic view that allows you to see “ far into the periphery.
” Also , “ every time you exhale , you ’ re slowing down the heart rate , ” he says .
Check out Betsy Ladyzhets 's weekly “ COVID-19 Data Dispatch , a newsletter written to help people make sense of @ @ @ @ @ @ @ pandemic data sources .
The publication provides news on public health agencies , resources for understanding and communicating about the pandemic , context on how COVID-19 data experts are thinking about major issues , and occasional interviews or original analysis .
Ladyzhets is a data journalist and science writer who ’ s been managing her publication ’ s pandemic coverage and volunteering at the COVID Tracking Project since the spring .
All data sources featured in the newsletter since its July inception are compiled in a public Google spreadsheet , and Ladyzhets is @ @ @ @ @ @ @ be useful for journalists , community leaders , and data nerds alike .
You might enjoy , “ Ten reasons why my New York bodega is better than your 7-Eleven , ” by Caroline Ulwick for McSweeney ’ s .

The items below are highlights from the free newsletter, “Smart, useful, science stuff about COVID-19.” To receive newsletter issues daily in your inbox, sign up here.
Canada has pre-ordered more doses per person of vaccines against SARS-CoV-2 than have any other countries and purchasing groups, reports freelance science journalist Asher Mullard for Nature (11/30/20). The U.S. and UK come in 2nd and 3rd. The story includes 2 graphics that illustrate the pre-ordering landscape. “Many people in low-income countries might have to wait until 2023 or 2024 for vaccination, according to estimates from the Duke Global Health Innovation Center,” Mullard writes. The makers of three vaccines that look like they will be distributed widely in 2021 (AstraZeneca, Moderna, and Pfizer/BioNTech) forecast making an estimated total of 5.3 billion doses next year. That would cover between 2.6 billion and 3.1 billion people, the story states. Most of those doses are already spoken for by individual, largely affluent or middle-income countries, the story states, leaving little for low- and middle-income nations, “most of which seem to be relying on contributions from” a joint venture called COVAX. The purchasing and distribution group was formed to ensure equitable global access to vaccines against SARS-CoV-2.
Virologist and vaccine researcher Shane Crotty at the La Jolla Institute for Immunology tweeted a thread on 11/27/20 discussing the safety of RNA vaccines (like those being tested by Moderna and Pfizer/BioNTech on large numbers of people and expected to receive emergency-use approval soon by the U.S. Food and Drug Administration). Crotty writes that RNA is analogous in some ways to expiring messages on social media platforms, and that RNA vaccines are “temporary messages instructing cells to make one viral protein temporarily.” He adds, “It takes 25 different coronavirus proteins [complex molecules] to make a coronavirus, so there is no worry about the RNA making a virus.”
Below is an estimated timeline for SARS-CoV-2 vaccine distribution in the U.S., based on a thread tweeted by Dr. Ashish Jha, dean of the Brown University School of Public Health, on 11/22/20. Jha drew the details in part from a televised interview between CNN’s Jake Tapper and Dr. Moncef Slaoui, chief scientific advisor to Operation Warp Speed (the U.S.’s federally funded vaccine development effort): https://threadreaderapp.com/thread/1330519144178085899.html
First public immunizations (health care workers and long-term care facility residents, if U.S. Centers for Disease Control’s 12/2/20 recommendations are followed) would start Dec. 11 or 12;
perhaps 20 million people in U.S. vaccinated by end of December;
about 30 million more people in U.S. vaccinated by end of January 2021, and combined with total people who have recovered from infections, “that’ll slow spread,” Jha writes;
about 40 percent immunity in the U.S. population by February, bringing “meaningfully slower” spread of SARS-CoV-2;
vaccines widely available in U.S. by April/May 2021
Moderna says it will soon start testing its messenger-RNA vaccine against SARS-CoV-2 in 3,000 teenagers, reports Denise Grady at The New York Times (12/2/20). AstraZeneca and Pfizer/BioNTech already made similar announcements for testing their vaccines in children, the story states. All three vaccine groups each recently announced that their vaccines are effective in large-scale experiments with adults, but “no vaccine can be widely given to children until it has been tested in them,” Grady writes. “Vaccines meant for both adults and children are generally tested first in adults to help make sure they are safe for pediatric trials [experiments].” Vaccines that work well in adults tend to also work well in children, with some dosing adjustments, according to Dr. Paul Offit, a vaccine researcher at Children’s Hospital of Philadelphia, Grady writes: https://www.nytimes.com/2020/12/02/health/Covid-Moderna-vaccine-children.html.
Two recent studies suggest that wearing even an N95 mask during vigorous exercise did not result in workouts that felt harder or actually were more physiologically draining, writes Gretchen Reynolds at The New York Times (11/18/20). One of the studies found more carbon dioxide in the breath of N95-masked exercisers, but none of the subjects complained of headaches or breathing issues, the story states. The results came as a surprise to the study subjects, Reynolds writes. The studies were conducted on healthy, active adults, so it is not clear if the findings would be the same in people who are less healthy or less active or who have breathing problems, the story states. “The findings suggest that anyone who hesitates to wear a mask during exercise should try one — although not an N95 mask,” the story describes one of the study authors, an internal medicine physician at Rambam Health Care Campus, as saying. Those masks slightly increase exercisers’ carbon dioxide levels and should be reserved for health care workers anyway, states the story, which also was published in Spanish.
As anticipated, the U.S. Centers for Disease Control (CDC) released recommendations (on 12/2/20) that include shortening the quarantine period from 14 days to as few as 7 days, at least for people who think they’ve could’ve been exposed to SARS-CoV-2 but then test negative, reports Colin Dwyer at NPR. “People should still watch closely for symptoms — such as a fever, a cough or a loss of taste or smell — for a full 14 days after possible exposure,” according to the CDC’s incident manager for its COVID-19 response, Dwyer writes. The change is meant to increase the odds that people will comply with the agency’s quarantine recommendations, the story states. It also “allows health officials to focus their efforts on the period of time that people are most likely to become contagious,” the story quotes epidemiologist Jennifer Nuzzo of the Johns Hopkins Center for Health Security as saying (12/2/20).
And if you’re confused about the meaning of quarantine versus isolation, or about the distinction between asymptomatic and presymptomatic, and the like, check out this helpful piece, “Clarifying COVID-19 terminology,” by Lindsay Smith Rogers for Johns Hopkins Bloomberg School of Public Health (11/23/20).
An 11/16/20 Q&A at Scientific American with Andrew Huberman, a Stanford University neuroscientist who studies the visual system, details how our vision and our breathing can “offer us easy and accessible releases from stress,” particularly in the context of the pandemic challenges and overall intensity of 2020. For instance, emerging research suggests that altering our breathing can alter brain regions responsible for arousal and panic, writes freelance science journalist Jessica Wapner in the introduction to the Q&A. And when we see stressful or exciting news, it increases our heart rate and breathing, Huberman says. You don’t want to miss this section: Our eyes are “not connected to the brain; they are the brain,” Huberman says. “During development, the eyes are part of the embryonic forebrain. Your eyes get extruded from the skull during the first trimester, and then they reconnect to the rest of the brain.” One of the tips Huberman mentions: one can turn off their brain's stress response by changing the way we are viewing our environment, specifically by taking on a panoramic view that allows you to see “far into the periphery.” Also, “every time you exhale, you’re slowing down the heart rate,” he says.
Check out Betsy Ladyzhets's weekly “COVID-19 Data Dispatch, a newsletter written to help people make sense of myriad unstandardized (and often untrustworthy) pandemic data sources. The publication provides news on public health agencies, resources for understanding and communicating about the pandemic, context on how COVID-19 data experts are thinking about major issues, and occasional interviews or original analysis. Ladyzhets is a data journalist and science writer who’s been managing her publication’s pandemic coverage and volunteering at the COVID Tracking Project since the spring. All data sources featured in the newsletter since its July inception are compiled in a public Google spreadsheet, and Ladyzhets is working on other supplemental resources that may be useful for journalists, community leaders, and data nerds alike.
You might enjoy, “Ten reasons why my New York bodega is better than your 7-Eleven,” by Caroline Ulwick for McSweeney’s.
.


scientificamerican--2020-12-03--Light-Based Quantum Computer Exceeds Fastest Classical Supercomputers

For the first time , a quantum computer made from photons—particles of light—has outperformed even the fastest classical supercomputers .
Physicists led by Chao-Yang Lu and Jian-Wei Pan of the University of Science and Technology of China ( USTC ) in Shanghai performed a technique called Gaussian boson sampling with their quantum computer , named Jiŭzhāng .
The result , reported in the journal Science , was 76 detected photons—far above and beyond the previous record of five detected photons and the capabilities of classical supercomputers .
Unlike a traditional computer built from silicon processors , Jiŭzhāng is an elaborate @ @ @ @ @ @ @ prisms and photon detectors .
It is not a universal computer that could one day send e-mails or store files , but it does demonstrate the potential of quantum computing .
Last year , Google captured headlines when its quantum computer Sycamore took roughly three minutes to do what would take a supercomputer three days ( or 10,000 years , depending on your estimation method ) .
In their paper , the USTC team estimates that it would take the Sunway TaihuLight , the third most powerful supercomputer in the world , a @ @ @ @ @ @ @ same calculation as Jiŭzhāng .
This is only the second demonstration of quantum primacy , which is a term that describes the point at which a quantum computer exponentially outspeeds any classical one , effectively doing what would otherwise essentially be computationally impossible .
It is not just proof of principle ; there are also some hints that Gaussian boson sampling could have practical applications , such as solving specialized problems in quantum chemistry and math .
More broadly , the ability to control photons as qubits is a prerequisite for any large-scale @ @ @ @ @ @ @ a quantum bit , analogous to the bits used to represent information in classical computing . )
“ It was not obvious that this was going to happen , ” says Scott Aaronson , a theoretical computer scientist now at the University of Texas at Austin who along with then-student Alex Arkhipov first outlined the basics of boson sampling in 2011 .
Boson sampling experiments were , for many years , stuck at around three to five detected photons , which is “ a hell of a long way ” from quantum primacy @ @ @ @ @ @ @ it up is hard , ” he says .
“ Hats off to them.
” Over the past few years , quantum computing has risen from an obscurity to a multibillion dollar enterprise recognized for its potential impact on national security , the global economy and the foundations of physics and computer science .
In 2019 , the the U.S. National Quantum Initiative Act was signed into law to invest more than $ 1.2 billion in quantum technology over the next 10 years .
The field has also garnered a fair amount of @ @ @ @ @ @ @ claims about quantum computers making classical computers entirely obsolete .
This latest demonstration of quantum computing ’ s potential from the USTC group is critical because it differs dramatically from Google ’ s approach .
Sycamore uses superconducting loops of metal to form qubits ; in Jiŭzhāng , the photons themselves are the qubits .
Independent corroboration that quantum computing principles can lead to primacy even on totally different hardware “ gives us confidence that in the long term , eventually , useful quantum simulators and a fault-tolerant quantum computer will become feasible @ @ @ @ @ @ @ quantum computers have enormous potential ?
Consider the famous double-slit experiment , in which a photon is fired at a barrier with two slits , A and B .
The photon does not go through A , or through B .
Instead , the double-slit experiment shows that the photon exists in a “ superposition , ” or combination of possibilities , of having gone through both A and B .
In theory , exploiting quantum properties like superposition allows quantum computers to achieve exponential speedups over their classical counterparts when applied to @ @ @ @ @ @ @ early 2000s were interested in exploiting the quantum properties of photons to make a quantum computer , in part because photons can act as qubits at room temperatures , so there is no need for the costly task of cooling one ’ s system to a few kelvins ( about –455 degrees Fahrenheit ) as with other quantum computing schemes .
But it quickly became apparent that building a universal photonic quantum computer was infeasible .
To even build a working quantum computer would require millions of lasers and other optical devices .
@ @ @ @ @ @ @ photons seemed out of reach .
Then , in 2011 , Aaronson and Arkhipov introduced the concept of boson sampling , showing how it could be done with a limited quantum computer made from just a few lasers , mirrors , prisms and photon detectors .
Suddenly , there was a path for photonic quantum computers to show that they could be faster than classical computers .
The setup for boson sampling is analogous to the toy called a bean machine , which is just a peg-studded board covered with a sheet of @ @ @ @ @ @ @ the rows of pegs from the top .
On their way down , they bounce off of the pegs and each other until they land in slots at the bottom .
Simulating the distribution of balls in slots is relatively easy on a classical computer .
Instead of balls , boson sampling uses photons , and it replaces pegs with mirrors and prisms .
Photons from the lasers bounce off of mirrors and through prisms until they land in a “ slot ” to be detected .
Unlike the classical balls , the @ @ @ @ @ @ @ an exponentially increasing number of possible distributions .
The problem boson sampling solves is essentially “ What is the distribution of photons ?
” Boson sampling is a quantum computer that solves itself by being the distribution of photons .
Meanwhile , a classical computer has to figure out the distribution of photons by computing what ’ s called the “ permanent ” of a matrix .
For an input of two photons , this is just a short calculation with a two-by-two array .
But as the number of photonic inputs and @ @ @ @ @ @ @ the array grows , exponentially increasing the problem ’ s computational difficulty .
Last year the USTC group demonstrated boson sampling with 14 detected photons—hard for a laptop to compute , but easy for a supercomputer .
To scale up to quantum primacy , they used a slightly different protocol , Gaussian boson sampling .
According to Christine Silberhorn , an quantum optics expert at the University of Paderborn in Germany and one of the co-developers of Gaussian boson sampling , the technique was designed to avoid the unreliable single photons used in @ @ @ @ @ @ @ ” boson sampling .
“ I really wanted to make it practical , ” she says “ It 's a scheme which is specific to what you can do experimentally.
” Even so , she acknowledges that the USTC setup is dauntingly complicated .
Jiŭzhāng begins with a laser that is split so it strikes 25 crystals made of potassium titanyl phosphate .
After each crystal is hit , it reliably spits out two photons in opposite directions .
The photons are then sent through 100 inputs , where they race through a @ @ @ @ @ @ @ mirrors .
Finally , the photons land in 100 slots where they are detected .
Averaging over 200 seconds of runs , the USTC group detected about 43 photons per run .
But in one run , they observed 76 photons—more than enough to justify their quantum primacy claim .
It is difficult to estimate just how much time would be needed for a supercomputer to solve a distribution with 76 detected photons—in large part because it is not exactly feasible to spend 2.5 billion years running a supercomputer to directly check it @ @ @ @ @ @ @ the time it takes to classically calculate for smaller numbers of detected photons .
At best , solving for 50 photons , the researchers claim , would take a supercomputer two days , which is far slower than the 200-second run time of Jiŭzhāng .
Boson sampling schemes have languished at low numbers of photons for years because they are incredibly difficult to scale up .
To preserve the sensitive quantum arrangement , the photons must remain indistinguishable .
Imagine a horse race where the horses all have to be released from the @ @ @ @ @ @ @ and finish at the same time as well .
Photons , unfortunately , are a lot more unreliable than horses .
As photons in Jiŭzhāng travel a 22-meter path , their positions can differ by no more than 25 nanometers .
That is the equivalent of 100 horses going 100 kilometers and crossing the finish line with no more than a hair ’ s width between them , Lu says .
The USTC quantum computer takes its name , Jiŭzhāng , from Jiŭzhāng Suànshù , or “ The Nine Chapters on the Mathematical @ @ @ @ @ @ @ with an impact comparable to Euclid ’ s Elements .
Quantum computing , too , has many twists and turns ahead .
Outspeeding classical computers is not a one-and-done deal , according to Lu , but will instead be a continuing competition to see if classical algorithms and computers can catch up , or if quantum computers will maintain the primacy they have seized .
Things are unlikely to be static .
At the end of October , researchers at the Canadian quantum computing start-up Xanadu found an algorithm that quadratically cut the @ @ @ @ @ @ @ experiments .
In other words , if 50 detected photons sufficed for quantum primacy before , you would now need 100 .
For theoretical computer scientists like Aaronson , the result is exciting because it helps give further evidence against the extended Church-Turing thesis , which holds that any physical system can be efficiently simulated on a classical computer .
“ At the very broadest level , if we thought of the universe as a computer , then what kind of computer is it ?
” Aaronson says .
“ Is it a @ @ @ @ @ @ @ quantum computer ?
” So far , the universe , like the computers we are attempting to make , seems to be stubbornly quantum .

For the first time, a quantum computer made from photons—particles of light—has outperformed even the fastest classical supercomputers.
Physicists led by Chao-Yang Lu and Jian-Wei Pan, both at the University of Science and Technology of China (USTC) in Hefei, performed a technique called Gaussian boson sampling with their quantum computer, named Jiŭzhāng.* The result, reported in the journal Science, was 76 detected photons—far above and beyond the previous record of five detected photons and the capabilities of classical supercomputers.
Unlike a traditional computer built from silicon processors, Jiŭzhāng is an elaborate tabletop setup of lasers, mirrors, prisms and photon detectors. It is not a universal computer that could one day send e-mails or store files, but it does demonstrate the potential of quantum computing.
Last year, Google captured headlines when its quantum computer Sycamore took roughly three minutes to do what would take a supercomputer three days (or 10,000 years, depending on your estimation method). In their paper, the USTC team estimates that it would take the Sunway TaihuLight, the third most powerful supercomputer in the world, a staggering 2.5 billion years to perform the same calculation as Jiŭzhāng.
This is only the second demonstration of quantum primacy, which is a term that describes the point at which a quantum computer exponentially outspeeds any classical one, effectively doing what would otherwise essentially be computationally impossible. It is not just proof of principle; there are also some hints that Gaussian boson sampling could have practical applications, such as solving specialized problems in quantum chemistry and math. More broadly, the ability to control photons as qubits is a prerequisite for any large-scale quantum internet. (A qubit is a quantum bit, analogous to the bits used to represent information in classical computing.)
“It was not obvious that this was going to happen,” says Scott Aaronson, a theoretical computer scientist now at the University of Texas at Austin who along with then-student Alex Arkhipov first outlined the basics of boson sampling in 2011. Boson sampling experiments were, for many years, stuck at around three to five detected photons, which is “a hell of a long way” from quantum primacy, according to Aaronson. “Scaling it up is hard,” he says. “Hats off to them.”
Over the past few years, quantum computing has risen from an obscurity to a multibillion dollar enterprise recognized for its potential impact on national security, the global economy and the foundations of physics and computer science. In 2019, the the U.S. National Quantum Initiative Act was signed into law to invest more than $1.2 billion in quantum technology over the next 10 years. The field has also garnered a fair amount of hype, with unrealistic timelines and bombastic claims about quantum computers making classical computers entirely obsolete.
This latest demonstration of quantum computing’s potential from the USTC group is critical because it differs dramatically from Google’s approach. Sycamore uses superconducting loops of metal to form qubits; in Jiŭzhāng, the photons themselves are the qubits. Independent corroboration that quantum computing principles can lead to primacy even on totally different hardware “gives us confidence that in the long term, eventually, useful quantum simulators and a fault-tolerant quantum computer will become feasible,” Lu says.
A LIGHT SAMPLING
Why do quantum computers have enormous potential? Consider the famous double-slit experiment, in which a photon is fired at a barrier with two slits, A and B. The photon does not go through A, or through B. Instead, the double-slit experiment shows that the photon exists in a “superposition,” or combination of possibilities, of having gone through both A and B. In theory, exploiting quantum properties like superposition allows quantum computers to achieve exponential speedups over their classical counterparts when applied to certain specific problems.
Physicists in the early 2000s were interested in exploiting the quantum properties of photons to make a quantum computer, in part because photons can act as qubits at room temperatures, so there is no need for the costly task of cooling one’s system to a few kelvins (about –455 degrees Fahrenheit) as with other quantum computing schemes. But it quickly became apparent that building a universal photonic quantum computer was infeasible. To even build a working quantum computer would require millions of lasers and other optical devices. As a result, quantum primacy with photons seemed out of reach.
Then, in 2011, Aaronson and Arkhipov introduced the concept of boson sampling, showing how it could be done with a limited quantum computer made from just a few lasers, mirrors, prisms and photon detectors. Suddenly, there was a path for photonic quantum computers to show that they could be faster than classical computers.
The setup for boson sampling is analogous to the toy called a bean machine, which is just a peg-studded board covered with a sheet of clear glass. Balls are dropped into the rows of pegs from the top. On their way down, they bounce off of the pegs and each other until they land in slots at the bottom. Simulating the distribution of balls in slots is relatively easy on a classical computer.
Instead of balls, boson sampling uses photons, and it replaces pegs with mirrors and prisms. Photons from the lasers bounce off of mirrors and through prisms until they land in a “slot” to be detected. Unlike the classical balls, the photon’s quantum properties lead to an exponentially increasing number of possible distributions.
The problem boson sampling solves is essentially “What is the distribution of photons?” Boson sampling is a quantum computer that solves itself by being the distribution of photons. Meanwhile, a classical computer has to figure out the distribution of photons by computing what’s called the “permanent” of a matrix. For an input of two photons, this is just a short calculation with a two-by-two array. But as the number of photonic inputs and detectors goes up, the size of the array grows, exponentially increasing the problem’s computational difficulty.
Last year the USTC group demonstrated boson sampling with 14 detected photons—hard for a laptop to compute, but easy for a supercomputer. To scale up to quantum primacy, they used a slightly different protocol, Gaussian boson sampling.
According to Christine Silberhorn, an quantum optics expert at the University of Paderborn in Germany and one of the co-developers of Gaussian boson sampling, the technique was designed to avoid the unreliable single photons used in Aaronson and Arkhipov’s “vanilla” boson sampling.
“I really wanted to make it practical,” she says “It's a scheme which is specific to what you can do experimentally.”
Even so, she acknowledges that the USTC setup is dauntingly complicated. Jiŭzhāng begins with a laser that is split so it strikes 25 crystals made of potassium titanyl phosphate. After each crystal is hit, it reliably spits out two photons in opposite directions. The photons are then sent through 100 inputs, where they race through a track made of 300 prisms and 75 mirrors. Finally, the photons land in 100 slots where they are detected. Averaging over 200 seconds of runs, the USTC group detected about 43 photons per run. But in one run, they observed 76 photons—more than enough to justify their quantum primacy claim.
It is difficult to estimate just how much time would be needed for a supercomputer to solve a distribution with 76 detected photons—in large part because it is not exactly feasible to spend 2.5 billion years running a supercomputer to directly check it. Instead, the researchers extrapolate from the time it takes to classically calculate for smaller numbers of detected photons. At best, solving for 50 photons, the researchers claim, would take a supercomputer two days, which is far slower than the 200-second run time of Jiŭzhāng.
Boson sampling schemes have languished at low numbers of photons for years because they are incredibly difficult to scale up. To preserve the sensitive quantum arrangement, the photons must remain indistinguishable. Imagine a horse race where the horses all have to be released from the starting gate at exactly the same time and finish at the same time as well. Photons, unfortunately, are a lot more unreliable than horses.
As photons in Jiŭzhāng travel a 22-meter path, their positions can differ by no more than 25 nanometers. That is the equivalent of 100 horses going 100 kilometers and crossing the finish line with no more than a hair’s width between them, Lu says.
QUANTUM QUESTING
The USTC quantum computer takes its name, Jiŭzhāng, from Jiŭzhāng Suànshù, or “The Nine Chapters on the Mathematical Art,” an ancient Chinese text with an impact comparable to Euclid’s Elements.
Quantum computing, too, has many twists and turns ahead. Outspeeding classical computers is not a one-and-done deal, according to Lu, but will instead be a continuing competition to see if classical algorithms and computers can catch up, or if quantum computers will maintain the primacy they have seized.
Things are unlikely to be static. At the end of October, researchers at the Canadian quantum computing start-up Xanadu found an algorithm that quadratically cut the classical simulation time for some boson sampling experiments. In other words, if 50 detected photons sufficed for quantum primacy before, you would now need 100.
For theoretical computer scientists like Aaronson, the result is exciting because it helps give further evidence against the extended Church-Turing thesis, which holds that any physical system can be efficiently simulated on a classical computer.
“At the very broadest level, if we thought of the universe as a computer, then what kind of computer is it?” Aaronson says. “Is it a classical computer? Or is it a quantum computer?”
So far, the universe, like the computers we are attempting to make, seems to be stubbornly quantum.
*Editor’s Note (12/20/21): This sentence was edited after posting to correct the location of the University of Science and Technology of China.


scientificamerican--2020-12-03--Who Will Get COVID Vaccines First, and Who Will Have to Wait

Vaccines against COVID-19 have arrived with unprecedented speed .
At least three candidates appear to be extremely effective and are likely to be approved in the U.S. in coming weeks .
By the end of December , the U.S. Centers for Disease Control and Prevention ( CDC ) estimates the U.S. will have enough vaccines to treat 20 million people .
Britain this week approved the vaccine made by Pfizer and BioNTech .
But for the first time in modern U.S. history , not everyone who wants a vaccine will be able to get one immediately .
Figuring out who @ @ @ @ @ @ @ and who has to wait is the job of an obscure CDC panel known as the Advisory Committee on Immunization Practices ( ACIP ) .
This week they announced their first official COVID vaccine distribution guidelines .
The committee makes such plans for all newly approved vaccines , but never before has ACIP had to work so fast .
In its December 1 meeting , the committee voted 13 to one that the approximately 21 million health care workers in the country should be the first to receive any new COVID vaccine , @ @ @ @ @ @ @ like nursing homes .
But deciding who comes second , and third , and even further back in the priority line , is trickier , as health experts weigh factors such as vulnerabilities of specific groups and whether immunizing others can have an outsize effect in stopping the harm to larger society caused by the disease .
Public health specialists who have worked on vaccine plans say the immense effects that COVID has had on the country make these decisions challenging .
“ We do n't have everything in place , because we @ @ @ @ @ @ @ ” says physician Helene Gayle , president and CEO of the Chicago Community Trust , who co-chaired a committee evaluating COVID vaccine priorities for the U.S. National Academies of Sciences , Engineering , and Medicine .
“ In my lifetime , there 's never been such a huge challenge to major swathes of the population that also has such societal impact.
” Lawrence Gostin , a health law expert at George Washington University , says there is virtually universal agreement that health care workers should get the vaccine first .
This group is @ @ @ @ @ @ @ the virus because of their exposure to infected patients .
Health care workers have put themselves at the front lines and their well-being ensures that other patients are treated .
This follows the recommendations of an October report from Gayle ’ s committee .
Still , when Britain approved the Pfizer/BioNTech vaccine , the country ’ s Joint Committee on Vaccination and Immunisation did not give health care workers the highest priority .
Instead , it recommended that long-term care residents receive the very first vaccines .
The committee cited this population ’ @ @ @ @ @ @ @ death ; in one study of four nursing homes , more than a quarter of residents died over the course of two months .
In the U.S. , nursing homes account for nearly half of all COVID deaths .
Still , including long-term care facility residents in the first group , known as phase 1a , was a more contentious point of discussion at the recent ACIP meeting .
Committee members questioned whether this population , which tends to have weaker immune systems , might not respond as well to a vaccine .
@ @ @ @ @ @ @ distribution plan , infectious disease expert Helen Keipp Talbot of Vanderbilt University , said she felt there was not enough data on the vaccine ’ s safety and efficacy in this group , and was concerned that U.S. federal agencies ’ surveillance systems weren ’ t sufficient to track these people ’ s outcomes .
Choosing the second group—people who could begin receiving vaccines in about a month—will present even more difficulties .
Current plans put forward by the CDC suggest essential workers—a population of about 87 million—will be in this category , @ @ @ @ @ @ @ phase , 1c , which could start in about three months , would include the approximately 153 million people who have high-risk medical conditions and those over age 65 .
But those plans are not final , and ACIP will continue to meet and hammer out details after the FDA approves each new vaccine and as more doses become available .
For now , the committee has to consider several factors , says Jeffrey Duchin , a former ACIP member who now directs public health efforts in Seattle and King County in Washington @ @ @ @ @ @ @ about which populations are most likely to spread the disease and who is most likely to have severe effects .
Epidemiological models suggest there is little difference in spread whether a vaccine is first given to high-risk adults , essential workers or people over the age of 65 .
Deciding among these groups , therefore , may come down to factors such as logistics and ethical principles like access to health care .
People from racial minority groups , for instance , comprise a high percentage of essential workers with a high chance @ @ @ @ @ @ @ historically had less access to health care and because COVID is far more likely to be fatal in nonwhite Americans , ethical principles might suggest such underserved populations be prioritized , Duchin says .
Others have argued that vaccines be specifically targeted to minority ethnic groups , regardless of whether they are essential workers , in order to make up for historical inequities .
“ I think there is a very strong ethical justification for giving considerable advantage to people who are socially vulnerable , and I would go further and give explicit @ @ @ @ @ @ @ says .
“ COVID has really amplified public concerns about racial and social injustice.
” But Gostin concedes that such a strategy would face political and legal risks .
Surveys have shown that Black Americans , for instance , are already skeptical about receiving a new COVID vaccine , reflecting a broader distrust of experimental treatments among minority populations .
And a conservative-leaning U.S. Supreme Court would be likely to strike down any plan based explicitly on race , if that plan were challenged in a lawsuit .
Targeting the vaccine to essential @ @ @ @ @ @ @ Gostin says , might be a more viable strategy .
One question that should be relatively easy to resolve is determining which health conditions put people in a high-risk group .
The CDC has amassed a large amount of data on conditions like diabetes and morbid obesity that increase the risk of severe COVID complications , and conditions like asthma that only slightly increase the risk .
This list , Gayle says , will allow public health officials to prioritize the people whose preexisting conditions put them at most risk .
Logistical issues @ @ @ @ @ @ @ well .
The Pfizer vaccine , for instance need to be stored at –70 degrees Celsius , a temperature generally only achievable at health care centers .
So getting this vaccine to rural populations could prove challenging .
Ultimately , the implementation of allocation decisions is not done by ACIP .
It comes down to state and local jurisdictions .
The federal advisory committee can recommend a vaccination triage scheme , but the CDC can ’ t force states to follow it .
Still , Sara Rosenbaum , a legal expert at George @ @ @ @ @ @ @ accept the plans .
“ I ’ d be surprised if they fought prioritization , ” she says , noting that , historically , local public health agencies have always followed federal vaccination guidelines .
But the CDC plans will need to allow local public health officials some flexibility in determining who is part of a particular group , for instance who qualifies as an essential worker or member of a disadvantaged population .
Gostin agrees that flexibility is necessary , but is concerned that “ it ’ s a recipe for hundred @ @ @ @ @ @ @ that during this year many state and local governments have failed to follow federal guidelines on COVID testing and mask requirements : “ We ’ ve seen American federalism fail spectacularly.
” For that reason , Duchin says that ACIP will need to carefully word its recommendations in order to ensure consistency .
“ If vaccination strategies differ in big ways , it will lead to confusion and potentially undermine confidence in the process , ” he says .
Read more about the coronavirus outbreak from Scientific American here .
And read coverage @ @ @ @ @ @ @ .

Vaccines against COVID-19 have arrived with unprecedented speed. At least three candidates appear to be extremely effective and are likely to be approved in the U.S. in coming weeks. By the end of December, the U.S. Centers for Disease Control and Prevention (CDC) estimates the U.S. will have enough vaccines to treat 20 million people. Britain this week approved the vaccine made by Pfizer and BioNTech.
But for the first time in modern U.S. history, not everyone who wants a vaccine will be able to get one immediately. Figuring out who gets the first shots in that country and who has to wait is the job of an obscure CDC panel known as the Advisory Committee on Immunization Practices (ACIP). This week they announced their first official COVID vaccine distribution guidelines.
The committee makes such plans for all newly approved vaccines, but never before has ACIP had to work so fast. In its December 1 meeting, the committee voted 13 to one that the approximately 21 million health care workers in the country should be the first to receive any new COVID vaccine, along with residents of long-term care facilities like nursing homes. But deciding who comes second, and third, and even further back in the priority line, is trickier, as health experts weigh factors such as vulnerabilities of specific groups and whether immunizing others can have an outsize effect in stopping the harm to larger society caused by the disease.
Public health specialists who have worked on vaccine plans say the immense effects that COVID has had on the country make these decisions challenging. “We don't have everything in place, because we've just never faced this before,” says physician Helene Gayle, president and CEO of the Chicago Community Trust, who co-chaired a committee evaluating COVID vaccine priorities for the U.S. National Academies of Sciences, Engineering, and Medicine. “In my lifetime, there's never been such a huge challenge to major swathes of the population that also has such societal impact.”
Lawrence Gostin, a health law expert at George Washington University, says there is virtually universal agreement that health care workers should get the vaccine first. This group is one of the most likely to acquire the virus because of their exposure to infected patients. Health care workers have put themselves at the front lines and their well-being ensures that other patients are treated. This follows the recommendations of an October report from Gayle’s committee.
Still, when Britain approved the Pfizer/BioNTech vaccine, the country’s Joint Committee on Vaccination and Immunisation did not give health care workers the highest priority. Instead, it recommended that long-term care residents receive the very first vaccines. The committee cited this population’s very high risk of infection and death; in one study of four nursing homes, more than a quarter of residents died over the course of two months.
In the U.S., nursing homes account for nearly half of all COVID deaths. Still, including long-term care facility residents in the first group, known as phase 1a, was a more contentious point of discussion at the recent ACIP meeting. Committee members questioned whether this population, which tends to have weaker immune systems, might not respond as well to a vaccine. The lone dissenting vote on the initial distribution plan, infectious disease expert Helen Keipp Talbot of Vanderbilt University, said she felt there was not enough data on the vaccine’s safety and efficacy in this group, and was concerned that U.S. federal agencies’ surveillance systems weren’t sufficient to track these people’s outcomes.
Choosing the second group—people who could begin receiving vaccines in about a month—will present even more difficulties. Current plans put forward by the CDC suggest essential workers—a population of about 87 million—will be in this category, known as phase 1b. The following phase, 1c, which could start in about three months, would include the approximately 153 million people who have high-risk medical conditions and those over age 65.
But those plans are not final, and ACIP will continue to meet and hammer out details after the FDA approves each new vaccine and as more doses become available. For now, the committee has to consider several factors, says Jeffrey Duchin, a former ACIP member who now directs public health efforts in Seattle and King County in Washington State. Foremost is the scientific evidence about which populations are most likely to spread the disease and who is most likely to have severe effects. Epidemiological models suggest there is little difference in spread whether a vaccine is first given to high-risk adults, essential workers or people over the age of 65.
Deciding among these groups, therefore, may come down to factors such as logistics and ethical principles like access to health care. People from racial minority groups, for instance, comprise a high percentage of essential workers with a high chance of exposure. Because these groups have historically had less access to health care and because COVID is far more likely to be fatal in nonwhite Americans, ethical principles might suggest such underserved populations be prioritized, Duchin says.
Others have argued that vaccines be specifically targeted to minority ethnic groups, regardless of whether they are essential workers, in order to make up for historical inequities. “I think there is a very strong ethical justification for giving considerable advantage to people who are socially vulnerable, and I would go further and give explicit priority to racial minorities,” Gostin says. “COVID has really amplified public concerns about racial and social injustice.”
But Gostin concedes that such a strategy would face political and legal risks. Surveys have shown that Black Americans, for instance, are already skeptical about receiving a new COVID vaccine, reflecting a broader distrust of experimental treatments among minority populations. And a conservative-leaning U.S. Supreme Court would be likely to strike down any plan based explicitly on race, if that plan were challenged in a lawsuit. Targeting the vaccine to essential workers and people in underserved communities, Gostin says, might be a more viable strategy.
One question that should be relatively easy to resolve is determining which health conditions put people in a high-risk group. The CDC has amassed a large amount of data on conditions like diabetes and morbid obesity that increase the risk of severe COVID complications, and conditions like asthma that only slightly increase the risk. This list, Gayle says, will allow public health officials to prioritize the people whose preexisting conditions put them at most risk.
Logistical issues may dictate some of the allocation as well. The Pfizer vaccine, for instance need to be stored at –70 degrees Celsius, a temperature generally only achievable at health care centers. So getting this vaccine to rural populations could prove challenging.
Ultimately, the implementation of allocation decisions is not done by ACIP. It comes down to state and local jurisdictions. The federal advisory committee can recommend a vaccination triage scheme, but the CDC can’t force states to follow it. Still, Sara Rosenbaum, a legal expert at George Washington University, expects that states will accept the plans. “I’d be surprised if they fought prioritization,” she says, noting that, historically, local public health agencies have always followed federal vaccination guidelines.
But the CDC plans will need to allow local public health officials some flexibility in determining who is part of a particular group, for instance who qualifies as an essential worker or member of a disadvantaged population. Gostin agrees that flexibility is necessary, but is concerned that “it’s a recipe for hundred different responses across America.” He notes that during this year many state and local governments have failed to follow federal guidelines on COVID testing and mask requirements: “We’ve seen American federalism fail spectacularly.”
For that reason, Duchin says that ACIP will need to carefully word its recommendations in order to ensure consistency. “If vaccination strategies differ in big ways, it will lead to confusion and potentially undermine confidence in the process,” he says.
Read more about the coronavirus outbreak from Scientific American here. And read coverage from our international network of magazines here.


scientificamerican--2020-12-08--Acknowledging Reality Is an Excellent Way to Function within It

Back in 2010 , we celebrated the life of Martin Gardner , who died that year at the age of 95 .
He wrote the Mathematical Games column for Scientific American magazine for nearly 25 years , and he remains the gold standard for this publication 's columnists .
Upon Gardner 's death , I interviewed his friend and protégé Douglas Hofstadter , the Pulitzer Prize–winning author of Gödel , Escher , Bach : An Eternal Golden Braid .
The book came out in 1979 , when Hofstadter was 34 .
Which meant that in 2010 he was 65 .
@ @ @ @ @ @ @ take much longer to go from 34 to 65 than a mere 31 years .
It really should take more like 50 years to go from being 34 to 65 , I thought , even though the arithmetic regarding that transition was inarguably ironclad .
In a somewhat related vein , this issue of Scientific American marks 25 years since the first appearance of Anti Gravity .
In 1995 I was 37 years old and in my salad days , when I was green in judgment .
And in only 25 years I @ @ @ @ @ @ @ I 'm still green , but now it 's because of digestive issues .
Horror movie maven David Cronenberg captured the weirdness of this fast-forwarding in the introduction to a 2014 English translation of Franz Kafka 's The Metamorphosis : “ I woke up one morning recently to discover that I was a seventy-year-old man .
Is this different from what happens to Gregor Samsa in The Metamorphosis ?
He wakes up to find that he 's become a near-human-sized beetle ... .
Our reactions , mine and Gregor 's , are very @ @ @ @ @ @ @ , and think that it 's a momentary delusion ... .
These two scenarios , mine and Gregor 's , seem so different , one might ask why I even bother to compare them .
The source of the transformations is the same , I argue : we have both awakened to a forced awareness of what we really are , and that awareness is profound and irreversible ; in each case , the delusion soon proves to be a new , mandatory reality , and life does not continue as it did.
@ @ @ @ @ @ @ of throat clearing is to set up the announcement that I 'm hanging up my spikes .
Well , in truth I hung up the spikes a very long time ago , when other kids my age started throwing breaking pitches .
So let 's say I 'm hanging up my keyboard .
I 'll still be making bad puns and snide remarks , of course , and I 'll be ranting about antiscience politicians , but it 'll mostly be just for the benefit , if you can call it that , @ @ @ @ @ @ @ it 's not impossible that I may return to these pages from time to time when said wife and cats inform me that I really should share my golden nuggets of insight with a wider audience if that will get me out of the living room .
By the way , I 'd be remiss if I did n't note that the greatest commentary on The Metamorphosis occurs in Mel Brooks 's 1967 movie The Producers , when the title characters are looking for the worst play in the world in order to @ @ @ @ @ @ @ most of the million dollars they raise rather than spend it on the production .
Max Bialystock , brilliantly played by Zero Mostel , opens one of the hundreds of manuscripts around him and says , “ ‘ Gregor Samsa awoke one morning to discover that he had been transformed into a giant cockroach.
’ It 's too good.
” Which in fact it was .
Back to Cronenberg and his “ mandatory reality.
” In 2002 a White House official scoffed at journalist Ron Suskind for being in “ the reality-based community.
@ @ @ @ @ @ @ Suskind , “ We 're an empire now , and when we act , we create our own reality.
” I had two responses to that anecdote and attitude then that I hold to today , as the current White House 's relationship with reality seems literally psychotic .
First , Scientific American is the voice of the reality-based community .
Second , if you think you create your own reality , real reality will come back to bite you in the ass .

Back in 2010, we celebrated the life of Martin Gardner, who died that year at the age of 95. He wrote the Mathematical Games column for Scientific American magazine for nearly 25 years, and he remains the gold standard for this publication's columnists.
Upon Gardner's death, I interviewed his friend and protégé Douglas Hofstadter, the Pulitzer Prize–winning author of Gödel, Escher, Bach: An Eternal Golden Braid. The book came out in 1979, when Hofstadter was 34. Which meant that in 2010 he was 65. And it struck me that it should take much longer to go from 34 to 65 than a mere 31 years. It really should take more like 50 years to go from being 34 to 65, I thought, even though the arithmetic regarding that transition was inarguably ironclad.
In a somewhat related vein, this issue of Scientific American marks 25 years since the first appearance of Anti Gravity. In 1995 I was 37 years old and in my salad days, when I was green in judgment. And in only 25 years I've turned into an alte kaker. I'm still green, but now it's because of digestive issues.
Horror movie maven David Cronenberg captured the weirdness of this fast-forwarding in the introduction to a 2014 English translation of Franz Kafka's The Metamorphosis: “I woke up one morning recently to discover that I was a seventy-year-old man. Is this different from what happens to Gregor Samsa in The Metamorphosis? He wakes up to find that he's become a near-human-sized beetle.... Our reactions, mine and Gregor's, are very similar. We are confused and bemused, and think that it's a momentary delusion.... These two scenarios, mine and Gregor's, seem so different, one might ask why I even bother to compare them. The source of the transformations is the same, I argue: we have both awakened to a forced awareness of what we really are, and that awareness is profound and irreversible; in each case, the delusion soon proves to be a new, mandatory reality, and life does not continue as it did.”
The previous more than 300 words of throat clearing is to set up the announcement that I'm hanging up my spikes. Well, in truth I hung up the spikes a very long time ago, when other kids my age started throwing breaking pitches. So let's say I'm hanging up my keyboard.
I'll still be making bad puns and snide remarks, of course, and I'll be ranting about antiscience politicians, but it'll mostly be just for the benefit, if you can call it that, of my wife and cats. Although it's not impossible that I may return to these pages from time to time when said wife and cats inform me that I really should share my golden nuggets of insight with a wider audience if that will get me out of the living room.
By the way, I'd be remiss if I didn't note that the greatest commentary on The Metamorphosis occurs in Mel Brooks's 1967 movie The Producers, when the title characters are looking for the worst play in the world in order to guarantee a flop so they can keep most of the million dollars they raise rather than spend it on the production. Max Bialystock, brilliantly played by Zero Mostel, opens one of the hundreds of manuscripts around him and says, “‘Gregor Samsa awoke one morning to discover that he had been transformed into a giant cockroach.’ It's too good.” Which in fact it was.
Back to Cronenberg and his “mandatory reality.” In 2002 a White House official scoffed at journalist Ron Suskind for being in “the reality-based community.” The official explained, according to Suskind, “We're an empire now, and when we act, we create our own reality.”
I had two responses to that anecdote and attitude then that I hold to today, as the current White House's relationship with reality seems literally psychotic. First, Scientific American is the voice of the reality-based community. Second, if you think you create your own reality, real reality will come back to bite you in the ass.


scientificamerican--2020-12-08--Does the Nose Talk to the Womb?

Does the Nose Talk to the Womb?

To be an expectant mother , or the anxious partner of one , is to be keenly , even agonizingly aware of how chemicals affect a developing life .
The basic advice is well known , and obsessively followed : Alcohol in strict moderation , and no nicotine at all .
Don ’ t mess with mercury .
Folic acid is your friend .
More protein and less caffeine .
Stay away from BPA , PBCs and PFA , and generally make an enemy of the unpronounceable .
But , if we take the results of a provocative recent paper @ @ @ @ @ @ @ , and deeply underappreciated chemical influence at work : a man ’ s odor .
The research , by a team headed by Noam Sobel of the Weizmann Institute of Science , suggests that there is a relationship between women ’ s response to “ social odors ” contained in male sweat and the heartbreaking condition of unexplained repeated pregnancy loss ( uRPL ) .
Specifically , in blind smell-tests , these scientists observed that women who had experienced uRPL were significantly better at identifying their spouse ’ s odor than age-matched controls @ @ @ @ @ @ @ to nonspouse odors and they displayed unique olfactory neuroanatomy .
Taken in the context of a large body of literature on chemosignaling in nonhuman animals , these results make it conceivable that the human nose could also communicate with the womb and may even influence a pregnancy .
So far , the results are strictly correlative , and in no way point to male odor as some kind of pheromonal smoking gun that explains pregnancy loss .
Hypothetically , it could also be true that women experiencing uRPL have , on average , @ @ @ @ @ @ @ their eyes , thinner wrists and a proclivity for wearing purple socks .
None of these would give one pause or prompt a serious search for some kind of causal link to pregnancy loss .
Yet this particular link between smell and pregnancy loss is intriguing because of how prevalent and robust it is in other mammals , including primates .
Many miscarriages still have unexplained causes , which makes any lead , correlative or not , a particularly interesting and worthwhile area of research .
The phenomenon of pregnancy block was first @ @ @ @ @ @ @ in the 1950s .
After the first signs of pregnancy , Bruce housed female mice with either the original “ stud male ” ( the father ) , or a “ strange male ” that had not been encountered before .
All the females housed with stud males carried their pregnancies to term , but a striking 30 percent of pregnancies were blocked in females housed with the strange male .
The factor producing the block was likely related to the hormonal state of the males , since the incidence of block decreased @ @ @ @ @ @ @ males were castrated .
In later studies that carefully controlled and isolated the potential ways that males could be influencing a pregnancy ( presenting physical contact or damaging the brain ’ s olfactory centers ) it was found that odor was both necessary and sufficient for what is now known as “ the Bruce effect.
” The most likely reason for this mysterious effect is that it ’ s an efficient , if merciless , mechanism for maximizing reproductive fitness : there ’ s no point investing in a resource-intensive pregnancy if the @ @ @ @ @ @ @ male mouse is only going to kill the offspring .
Similar controlled experiments can ’ t , of course , be ethically replicated in humans , so instead Sobel ’ s group set out to investigate changes in olfactory identification of mates for women who had already experienced pregnancy loss .
If this Bruce-type effect existed in humans , we might expect it to show up as a difference in the detection or recognition of mate odor that could persist after pregnancy loss .
In the main experiment , the uRPL group was @ @ @ @ @ @ @ soiled T-shirt by smell from a lineup including a stranger ’ s soiled T-shirt and a “ blank ” unsoiled shirt .
The uRPL group performed significantly above chance in the task , and the experimenters noted , anecdotally , that many participants spontaneously offered remarks like “ Oh , this is my spouse.
” In contrast , an age-matched control group that had not experienced rUPL performed at only chance levels on this task .
Although this result could in principle be explained by a more acute sense of smell , without @ @ @ @ @ @ @ seemed to rule out this possibility .
When tested with a battery of general odor detection and identification tasks , the rUPL women performed no differently from the controls , indicating that the group ’ s heightened olfactory identification was mate-specific .
If there is a link between smell and pregnancy loss , then the neural events that mediate this are of considerable interest .
In mice , the brain ’ s sorting of “ studs ” from “ strangers ” involves the vomeronasal system , an olfactory subsystem that was once called @ @ @ @ @ @ @ is now seen as even richer and more complex .
Scientists have proposed a wide range of mechanisms to account for the “ Bruce effect ” in mice , including changes in neurogenesis ( the birth and incorporation of new neurons ) .
But , the most likely theory is the formation of a template memory in the vomeronasal system .
In the same way that your brain learns to “ subtract out ” your own smell ( effectively recognizing the self as a nonthreatening or uninteresting stimulus ) , the pregnant mouse @ @ @ @ @ @ @ mate ’ s smell .
Naturally , the neural mechanisms of mate identification can not be studied in humans with anything close to the control , precision and granularity that are possible in mice .
Still , Sobel ’ s group has made some interesting observations about social odor processing using fMRI that may hint at a neurological basis for the observed phenomenon .
At a gross structural level , uRPL subjects tended to have smaller olfactory bulbs than their control counterparts ( the olfactory bulb is an early and critical brain structure @ @ @ @ @ @ @ nose ) .
In another experiment designed to monitor real-time neural responses to social odors , subjects were placed in a scanner while being shown arousing videos and smelling nonspousal odors presented at concentrations well below conscious detection .
Interestingly , the scientists didn ’ t just observe a difference in the amount of stimulus-evoked brain activity between the two groups .
Rather , they found a difference in the direction of the groups ’ responses , with activity in the hypothalamus—a key regulator of basic physiological functions including sexual behavior and menstruation—decreasing @ @ @ @ @ @ @ the uRPL group .
Sobel ’ s studies show that something is noticeably different about social odor perception in women with repeated miscarriages , and that these differences influence how their brains process social odors .
While this could potentially hint at a “ Bruce-like effect ” in humans , there are still many questions left unanswered .
The main one is that because of the experimental design ( driven by the ethical constraints of working with humans ) we don ’ t know in what direction the arrow of causality points .
@ @ @ @ @ @ @ nothing to do with smell , and caused downstream changes in olfactory processing , in a sort of “ backwards ” Bruce effect , for example .
And , even if odor does prove to be causal , it may also turn out that the effect owes more to the uniqueness of certain male odors than a difference in certain female brains .
Regardless of the end result , we are sure to learn something new and important about how we communicate using our most underappreciated sense .

To be an expectant mother, or the anxious partner of one, is to be keenly, even agonizingly aware of how chemicals affect a developing life. The basic advice is well known, and obsessively followed: Alcohol in strict moderation, and no nicotine at all. Don’t mess with mercury. Folic acid is your friend. More protein and less caffeine. Stay away from BPA, PBCs and PFA, and generally make an enemy of the unpronounceable.
But, if we take the results of a provocative recent paper seriously, there may be another important, and deeply underappreciated chemical influence at work: a man’s odor. The research, by a team headed by Noam Sobel of the Weizmann Institute of Science, suggests that there is a relationship between women’s response to “social odors” contained in male sweat and the heartbreaking condition of unexplained repeated pregnancy loss (uRPL). Specifically, in blind smell-tests, these scientists observed that women who had experienced uRPL were significantly better at identifying their spouse’s odor than age-matched controls. Additionally, their brains responded differently to nonspouse odors and they displayed unique olfactory neuroanatomy. Taken in the context of a large body of literature on chemosignaling in nonhuman animals, these results make it conceivable that the human nose could also communicate with the womb and may even influence a pregnancy.
So far, the results are strictly correlative, and in no way point to male odor as some kind of pheromonal smoking gun that explains pregnancy loss. Hypothetically, it could also be true that women experiencing uRPL have, on average, larger middle toes, larger whites of their eyes, thinner wrists and a proclivity for wearing purple socks. None of these would give one pause or prompt a serious search for some kind of causal link to pregnancy loss. Yet this particular link between smell and pregnancy loss is intriguing because of how prevalent and robust it is in other mammals, including primates. Many miscarriages still have unexplained causes, which makes any lead, correlative or not, a particularly interesting and worthwhile area of research.
The phenomenon of pregnancy block was first documented in mice by Hilda Bruce, in the 1950s. After the first signs of pregnancy, Bruce housed female mice with either the original “stud male” (the father), or a “strange male” that had not been encountered before. All the females housed with stud males carried their pregnancies to term, but a striking 30 percent of pregnancies were blocked in females housed with the strange male. The factor producing the block was likely related to the hormonal state of the males, since the incidence of block decreased by about 50 percent once the strange males were castrated. In later studies that carefully controlled and isolated the potential ways that males could be influencing a pregnancy (presenting physical contact or damaging the brain’s olfactory centers) it was found that odor was both necessary and sufficient for what is now known as “the Bruce effect.” The most likely reason for this mysterious effect is that it’s an efficient, if merciless, mechanism for maximizing reproductive fitness: there’s no point investing in a resource-intensive pregnancy if the father is not around and a new male mouse is only going to kill the offspring.
Similar controlled experiments can’t, of course, be ethically replicated in humans, so instead Sobel’s group set out to investigate changes in olfactory identification of mates for women who had already experienced pregnancy loss. If this Bruce-type effect existed in humans, we might expect it to show up as a difference in the detection or recognition of mate odor that could persist after pregnancy loss. In the main experiment, the uRPL group was asked to identify their spouse’s soiled T-shirt by smell from a lineup including a stranger’s soiled T-shirt and a “blank” unsoiled shirt. The uRPL group performed significantly above chance in the task, and the experimenters noted, anecdotally, that many participants spontaneously offered remarks like “Oh, this is my spouse.” In contrast, an age-matched control group that had not experienced rUPL performed at only chance levels on this task.
Although this result could in principle be explained by a more acute sense of smell, without any mate-specific olfactory alchemy, additional experiments seemed to rule out this possibility. When tested with a battery of general odor detection and identification tasks, the rUPL women performed no differently from the controls, indicating that the group’s heightened olfactory identification was mate-specific.
If there is a link between smell and pregnancy loss, then the neural events that mediate this are of considerable interest. In mice, the brain’s sorting of “studs” from “strangers” involves the vomeronasal system, an olfactory subsystem that was once called “the social nose” but which is now seen as even richer and more complex. Scientists have proposed a wide range of mechanisms to account for the “Bruce effect” in mice, including changes in neurogenesis (the birth and incorporation of new neurons). But, the most likely theory is the formation of a template memory in the vomeronasal system. In the same way that your brain learns to “subtract out” your own smell (effectively recognizing the self as a nonthreatening or uninteresting stimulus), the pregnant mouse brain could do the same for a mate’s smell.
Naturally, the neural mechanisms of mate identification cannot be studied in humans with anything close to the control, precision and granularity that are possible in mice. Still, Sobel’s group has made some interesting observations about social odor processing using fMRI that may hint at a neurological basis for the observed phenomenon. At a gross structural level, uRPL subjects tended to have smaller olfactory bulbs than their control counterparts (the olfactory bulb is an early and critical brain structure that receives direct sensory inputs from the nose). In another experiment designed to monitor real-time neural responses to social odors, subjects were placed in a scanner while being shown arousing videos and smelling nonspousal odors presented at concentrations well below conscious detection. Interestingly, the scientists didn’t just observe a difference in the amount of stimulus-evoked brain activity between the two groups. Rather, they found a difference in the direction of the groups’ responses, with activity in the hypothalamus—a key regulator of basic physiological functions including sexual behavior and menstruation—decreasing in the control group and increasing in the uRPL group.
Sobel’s studies show that something is noticeably different about social odor perception in women with repeated miscarriages, and that these differences influence how their brains process social odors. While this could potentially hint at a “Bruce-like effect” in humans, there are still many questions left unanswered. The main one is that because of the experimental design (driven by the ethical constraints of working with humans) we don’t know in what direction the arrow of causality points. It could be that pregnancy loss has nothing to do with smell, and caused downstream changes in olfactory processing, in a sort of “backwards” Bruce effect, for example. And, even if odor does prove to be causal, it may also turn out that the effect owes more to the uniqueness of certain male odors than a difference in certain female brains. Regardless of the end result, we are sure to learn something new and important about how we communicate using our most underappreciated sense.