Quantum computers, like this IBM model, look like science fiction come to life.
(Credit: Graham Carlow for IBM) The massive intersection of Janes Avenue and East Boughton Road in Bolingbrook, Illinois, looks like many other crossroads in suburban America.
A drive-through Starbucks keeps watch over 15 lanes of turning and merging mid-size SUVs, most headed for the sprawling parking lots of the Promenade shopping mall to the south, a few others en route to the shooting gallery and gun shop across Interstate 355 to the east.
Few of the people in the SUVs realize they’re driving over part of America’s blossoming research into quantum information technology.
Beneath the interstate, entangled photons—quantum particles moving at the speed of light—are teleporting to and from the Argonne National Laboratory in the next town over, through repurposed fiber-optic cables that make up one of the longest land-based quantum networks in the nation.
(Photo credit: Yuichiro Chino/Getty) Researchers hope to use the 52-mile quantum test site in Bolingbrook and others like it to prove that you can trap information inside a quantum state of matter (like a photon) in one location, send it somewhere else, and access it completely intact on the other end.
They need to factor in the challenges of frozen ground, the sun’s radiation, and vibrations from all those vehicles traveling overhead, but if they can prove it, they’ll have invented a way of communicating that makes 5G seem quaint.
Researchers at other laboratories are simultaneously trying to feed algorithms into similar elementary states of matter, known as quantum bits, and have them come out transformed correctly at the end of the computation.
If that’s successful, they’ll have an entirely new type of computer on their hands.
It’s been clear to physicists for years that the long-established principles of quantum mechanics can revolutionize computing and the internet.
If quantum bits can be tamed, they could run algorithms in just a few seconds that would otherwise take years to complete.
Stable photons could transfer information across the world instantly in a way that likely could never be hacked while in transit, since any disturbance would destroy the information.
To the rest of us, the quantum revolution might seem as if it has just transformed from a sleepy scientific theory into the sharpest of bleeding edges.
It’s even possible that we’re currently experiencing something of a quantum bubble—and that it might be about to burst.
In 2017, most of the quantum test loops were just dormant fiber-optic cables, and no one had been able to get quantum bits to reliably process information in the same way classical computers can.
Now, there are more than a dozen functioning quantum computers around the world, a few of which any software developer can access via familiar services: say, an Amazon Web Services account.
Within the past two years, America has committed more than $1 billion in government funds to quantum information research, quantum computing startups have closed multiple venture funding rounds, and IBM announced that it is forging ahead with plans to build a computer with more than a million quantum bits, up from a maximum of around 60 today.
Despite advances coming at a breakneck pace, many of the people working in the nascent field of quantum information science acknowledge that quantum states are not yet reliable or understood well enough to replace traditional computing and the internet.
Some believe they never will be—that no one will ever buy a phone with quantum bits instead of an Apple A12 Bionic, and that quantum bits and other elementary particles will forever be relegated to scientific research.
What Is Quantum Computing?
A computer made up of quantum bits—qubits, for short—is really a collection of circuits.
As in a classical computer made up of bits, the input values proceed through a series of logic gates in the circuit, each of which modifies the value to produce an output.
The most important difference between quantum computing and classical computing is that bits are binary.
They are either up or down, open or closed, zero or one.
Qubits, on the other hand, can be entangled—present in multiple states at once, a so-called superposition.
(Watch the video above, from Rigetti Computing, for more details.)
If you’re trying to solve a complex algorithm, say, as part of a software application to run on a classical computer, you’ll need to string together multiple bits of zeros and ones.
But if you’re running an algorithm using qubits, you might need only a single qubit in a superposition to replace all those classical bits.
String multiple qubits together into a quantum circuit, and the possibilities are staggering.
Theoretically, you could run an algorithm so complex that there’s no analog to classical computing as we know it.
The most difficult problem to solve in improving quantum computing and communications is the fragility of the quantum state of matter.
We are starting to be able to protect traveling quantum particles against the effects of weather and road vibrations, but only in test loops—not over the thousands of miles required to replace the current internet.
Likewise, no one has yet figured out how to make qubits function reliably, even in a controlled laboratory setting.
IBM Quantum 27-qubit Falcon chip with quantum volume 64 (Photo credit: JIBM) They work well enough in small groups and confined to specific types of computations, as IBM demonstrated using a stable 27-qubit computer called Falcon earlier this year.
They’re mostly useful for testing purposes: Researchers can feed them problems with known solutions and then validate their answers.
But so far, qubits have proven too fragile to function reliably in larger groups, which effectively limits their ability to graduate from beta and accurately perform any computation a classical computer would.
“As we push on the number of qubits, you’re able to explore a much more varied set of quantum circuits,” says Jerry Chow, the senior manager of the Experimental Quantum Computing Group at IBM.
If only it were that simple.
The “lossy qubit” problem, as Chow puts it, means that parts of each quantum computer that exists today are dedicated just to resolving errors in their computations, instead of performing the computations themselves.
The quantum volume of a computer, a numerical value that describes its maximum potential to perform calculations, is always less than the number of qubits it contains.
Likewise, the number of photons that begin their journey intact at the beginning of a journey through a test loop is always greater than the number that return.
To circumvent this problem and unlock the full potential of quantum computing, some researchers are working on adding error-correcting codes, which are already implemented in some classical computers.
Others are exploring alternative methods of applying quantum physics to computing that don’t involve gates and circuits.
One possibility is tricking quantum particles into ignoring background noise—vibrations, temperature changes, and stray electromagnetic fields, for example—that causes them to break down.
A University of Chicago team announced in August that they had successfully performed this kind of trickery in a limited experiment.
Quantum annealing is another technique with potential.
It involves harnessing fluctuations in quantum states to perform calculations instead of sending them through gates in a circuit.
Some commercially available quantum computers from D-Wave, a small Canadian firm, use this method.
But they also suffer from errors, and so far, they’ve proved effective at solving only specific types of algorithms—as one example, those based on the “traveling salesman” problem, which seeks to find the shortest possible route between a set of points.
Volkswagen used D-Wave’s approach in an experiment last year to help buses in Lisbon, Portugal, escape traffic jams.
The experiment was declared a success, though it was limited to taking attendees of a technology conference from the airport to the convention center.
Jerry Chow, IBM researcher in the Experimental Quantum Computing group, prepares for a quantum experiment.
(Photo credit: Jon Simon/Feature Photo Service for IBM) The most infamous example of the lossy qubit problem surfaced in October 2019, when researchers at Google announced they had completed a benchmark test on a 53-qubit quantum computer in 200 seconds.
The test would have taken a classical supercomputer far longer—anywhere from a few days to 10,000 years, depending on its specifications.
On the basis of the experiment, nicknamed Sycamore, Google claimed to have achieved quantum supremacy, or proof that a quantum computer can handle an algorithm faster than a classical computer can without making any mistakes.
It’s something of a holy grail in the field of quantum information science, and Google CEO Sundar Pichai was quick to hail it as quantum computing’s “hello world” moment.
Soon after, though, researchers disputed whether the experiment was as significant as Google claimed, setting off a buzzworthy quarrel.
For Wiliam Oliver, a physicist at MIT who studies qubits, the larger problem with quantum supremacy isn’t whether or not it exists, but when it breaks down.
“Most people in the world think [Google] achieved it,” he said of Sycamore.
“But had they added a couple more qubits, then they wouldn’t have been able to do it.” Oliver thinks the benefits of quantum computing are more than just supremacy over classical computers.
The real holy grail, he says, is for quantum computing “to be able to run anything for any amount of time without error.”
Even a year later, Jerry Chow still thinks of the Google announcement as a footnote on the journey to create quantum computers that researchers and even regular people can actually use without worrying about their accuracy or stability.
“That was an interesting academic work, to push that type of problem,” Chow says of Sycamore.
Show Me the VC and Government Money
David Awschalom (center) discussing quantum research with Department of Energy Under Secretary for Science Paul M.
Dabbar, second from left (Photo credit: Argonne National Laboratory) If there is a quantum bubble, it’s inflated both by the new flurry of Sycamore-type academic work and a simultaneous push from private corporations to develop real-world quantum applications, like avoiding traffic jams, as a form of competitive advantage.
We’ve known about the advantages that quantum physics can offer computing since at least the 1980s, when Argonne physicist Paul Benioff described the first quantum mechanical model of a computer.
But the allure of the technology seems to have just now bitten enterprising businesspeople from the tiniest of startups to the largest of conglomerates.
“My personal opinion is there’s never been a more exciting time to be in quantum,” says William Hurley.
Strangeworks, the startup he founded in 2018, serves as a sort of community hub for developers working on quantum algorithms.
Hurley, a software systems analyst who has worked for both Apple and IBM, says that more than 10,000 developers have signed up to submit their algorithms and collaborate with others.
Among the collaborators—Austin-based Strangeworks refers to them as “friends and allies”—is Bay Area startup Rigetti Computing, which supplies one of the three computers that Amazon Web Services customers can access to test out their quantum algorithms.
That service, called Amazon Braket, made its debut in August and counts Volkswagen and Fidelity Investments among its customers.
Quantum information tech is so appealing that conglomerates are now carving out entire research divisions to explore it as a way to stay competitive.
The JPMorgan Chase bank has researchers developing quantum algorithms for every arm of its business, from encryption and security to options trading.
“We’re completely in a research mode right now,” says Rob Matles, the director of JPMorgan’s Future Lab for Applied Research and Engineering.
“We want to be ready when quantum supremacy is met.” Matles is optimistic in particular about how quantum computing can improve options trading, an area of finance in which speed and accuracy is critically important.
Cristiano Malossi, Manager of the AI Automation group at the IBM Research Europe (Photo credit: Jon Simon/Feature Photo Service for IBM) All this activity is both supported and incentivized by the promise of taxpayer funding in the US and abroad.
Established in 2018, America’s National Quantum Initiative is expansive in scope (it calls for a 10-year plan to “accelerate the development of quantum information science and technology applications”) and generosity ($1 billion has been authorized so far).
There’s also plenty of support from the military: The Defense Advanced Research Projects Agency (DARPA) has granted nearly $20 million so far this year to spur the development of quantum computers, with no requirement that they have an advantage over classical ones.
Rigetti, which claims to have the only dedicated quantum integrated circuit foundry in the US, is a magnet for government funding and venture capital.
It secured $9 million from DARPA in March, then closed a $79 million series C, and in August announced plans to build its second quantum computer in the UK as part of a consortium funded by a £10 million (around $13 million) grant from the British government.
Governments and militaries are particularly interested in building a quantum internet, and they have a special affinity for the quantum test loops like the one at Argonne.
“We now have the blueprint to make this quantum internet a reality,” Department of Energy Undersecretary for Science Paul Dabbar announced in July.
Eventually, the department plans to build quantum test loops at all 17 national laboratories and connect them together to create a rudimentary nationwide quantum communications network.
IBM quantum computer (Photo credit: Graham Carlow for IBM) For all of the investment and optimism, however, there’s also a very real sense that the uncertainty of quantum’s capabilities represents a gamble.
“Quantum isn’t ready to solve real-world problems,” Matles admits.
JPMorgan started its quantum research about three years ago, and since then he’s watched advancements such as the Sycamore experiment with interest.
But he insists that the company is still in an optimism phase and isn’t ready to speculate about the specific improvements quantum computing might offer or how long it might take to be ready.
“We’re still in the world of simulation,” Hurley says of quantum information technology.
“These things aren’t computers.
They’re great equipment for exploiting the quantum...
Quantum computers, like this IBM model, look like science fiction come to life.
(Credit: Graham Carlow for IBM) The massive intersection of Janes Avenue and East Boughton Road in Bolingbrook, Illinois, looks like many other crossroads in suburban America.
A drive-through Starbucks keeps watch over 15 lanes of turning and merging mid-size SUVs, most headed for the sprawling parking lots of the Promenade shopping mall to the south, a few others en route to the shooting gallery and gun shop across Interstate 355 to the east.
Few of the people in the SUVs realize they’re driving over part of America’s blossoming research into quantum information technology.
Beneath the interstate, entangled photons—quantum particles moving at the speed of light—are teleporting to and from the Argonne National Laboratory in the next town over, through repurposed fiber-optic cables that make up one of the longest land-based quantum networks in the nation.
(Photo credit: Yuichiro Chino/Getty) Researchers hope to use the 52-mile quantum test site in Bolingbrook and others like it to prove that you can trap information inside a quantum state of matter (like a photon) in one location, send it somewhere else, and access it completely intact on the other end.
They need to factor in the challenges of frozen ground, the sun’s radiation, and vibrations from all those vehicles traveling overhead, but if they can prove it, they’ll have invented a way of communicating that makes 5G seem quaint.
Researchers at other laboratories are simultaneously trying to feed algorithms into similar elementary states of matter, known as quantum bits, and have them come out transformed correctly at the end of the computation.
If that’s successful, they’ll have an entirely new type of computer on their hands.
It’s been clear to physicists for years that the long-established principles of quantum mechanics can revolutionize computing and the internet.
If quantum bits can be tamed, they could run algorithms in just a few seconds that would otherwise take years to complete.
Stable photons could transfer information across the world instantly in a way that likely could never be hacked while in transit, since any disturbance would destroy the information.
To the rest of us, the quantum revolution might seem as if it has just transformed from a sleepy scientific theory into the sharpest of bleeding edges.
It’s even possible that we’re currently experiencing something of a quantum bubble—and that it might be about to burst.
In 2017, most of the quantum test loops were just dormant fiber-optic cables, and no one had been able to get quantum bits to reliably process information in the same way classical computers can.
Now, there are more than a dozen functioning quantum computers around the world, a few of which any software developer can access via familiar services: say, an Amazon Web Services account.
Within the past two years, America has committed more than $1 billion in government funds to quantum information research, quantum computing startups have closed multiple venture funding rounds, and IBM announced that it is forging ahead with plans to build a computer with more than a million quantum bits, up from a maximum of around 60 today.
Despite advances coming at a breakneck pace, many of the people working in the nascent field of quantum information science acknowledge that quantum states are not yet reliable or understood well enough to replace traditional computing and the internet.
Some believe they never will be—that no one will ever buy a phone with quantum bits instead of an Apple A12 Bionic, and that quantum bits and other elementary particles will forever be relegated to scientific research.
What Is Quantum Computing?
A computer made up of quantum bits—qubits, for short—is really a collection of circuits.
As in a classical computer made up of bits, the input values proceed through a series of logic gates in the circuit, each of which modifies the value to produce an output.
The most important difference between quantum computing and classical computing is that bits are binary.
They are either up or down, open or closed, zero or one.
Qubits, on the other hand, can be entangled—present in multiple states at once, a so-called superposition.
(Watch the video above, from Rigetti Computing, for more details.)
If you’re trying to solve a complex algorithm, say, as part of a software application to run on a classical computer, you’ll need to string together multiple bits of zeros and ones.
But if you’re running an algorithm using qubits, you might need only a single qubit in a superposition to replace all those classical bits.
String multiple qubits together into a quantum circuit, and the possibilities are staggering.
Theoretically, you could run an algorithm so complex that there’s no analog to classical computing as we know it.
The most difficult problem to solve in improving quantum computing and communications is the fragility of the quantum state of matter.
We are starting to be able to protect traveling quantum particles against the effects of weather and road vibrations, but only in test loops—not over the thousands of miles required to replace the current internet.
Likewise, no one has yet figured out how to make qubits function reliably, even in a controlled laboratory setting.
IBM Quantum 27-qubit Falcon chip with quantum volume 64 (Photo credit: JIBM) They work well enough in small groups and confined to specific types of computations, as IBM demonstrated using a stable 27-qubit computer called Falcon earlier this year.
They’re mostly useful for testing purposes: Researchers can feed them problems with known solutions and then validate their answers.
But so far, qubits have proven too fragile to function reliably in larger groups, which effectively limits their ability to graduate from beta and accurately perform any computation a classical computer would.
“As we push on the number of qubits, you’re able to explore a much more varied set of quantum circuits,” says Jerry Chow, the senior manager of the Experimental Quantum Computing Group at IBM.
If only it were that simple.
The “lossy qubit” problem, as Chow puts it, means that parts of each quantum computer that exists today are dedicated just to resolving errors in their computations, instead of performing the computations themselves.
The quantum volume of a computer, a numerical value that describes its maximum potential to perform calculations, is always less than the number of qubits it contains.
Likewise, the number of photons that begin their journey intact at the beginning of a journey through a test loop is always greater than the number that return.
To circumvent this problem and unlock the full potential of quantum computing, some researchers are working on adding error-correcting codes, which are already implemented in some classical computers.
Others are exploring alternative methods of applying quantum physics to computing that don’t involve gates and circuits.
One possibility is tricking quantum particles into ignoring background noise—vibrations, temperature changes, and stray electromagnetic fields, for example—that causes them to break down.
A University of Chicago team announced in August that they had successfully performed this kind of trickery in a limited experiment.
Quantum annealing is another technique with potential.
It involves harnessing fluctuations in quantum states to perform calculations instead of sending them through gates in a circuit.
Some commercially available quantum computers from D-Wave, a small Canadian firm, use this method.
But they also suffer from errors, and so far, they’ve proved effective at solving only specific types of algorithms—as one example, those based on the “traveling salesman” problem, which seeks to find the shortest possible route between a set of points.
Volkswagen used D-Wave’s approach in an experiment last year to help buses in Lisbon, Portugal, escape traffic jams.
The experiment was declared a success, though it was limited to taking attendees of a technology conference from the airport to the convention center.
Jerry Chow, IBM researcher in the Experimental Quantum Computing group, prepares for a quantum experiment.
(Photo credit: Jon Simon/Feature Photo Service for IBM) The most infamous example of the lossy qubit problem surfaced in October 2019, when researchers at Google announced they had completed a benchmark test on a 53-qubit quantum computer in 200 seconds.
The test would have taken a classical supercomputer far longer—anywhere from a few days to 10,000 years, depending on its specifications.
On the basis of the experiment, nicknamed Sycamore, Google claimed to have achieved quantum supremacy, or proof that a quantum computer can handle an algorithm faster than a classical computer can without making any mistakes.
It’s something of a holy grail in the field of quantum information science, and Google CEO Sundar Pichai was quick to hail it as quantum computing’s “hello world” moment.
Soon after, though, researchers disputed whether the experiment was as significant as Google claimed, setting off a buzzworthy quarrel.
For Wiliam Oliver, a physicist at MIT who studies qubits, the larger problem with quantum supremacy isn’t whether or not it exists, but when it breaks down.
“Most people in the world think [Google] achieved it,” he said of Sycamore.
“But had they added a couple more qubits, then they wouldn’t have been able to do it.” Oliver thinks the benefits of quantum computing are more than just supremacy over classical computers.
The real holy grail, he says, is for quantum computing “to be able to run anything for any amount of time without error.”
Even a year later, Jerry Chow still thinks of the Google announcement as a footnote on the journey to create quantum computers that researchers and even regular people can actually use without worrying about their accuracy or stability.
“That was an interesting academic work, to push that type of problem,” Chow says of Sycamore.
Show Me the VC and Government Money
David Awschalom (center) discussing quantum research with Department of Energy Under Secretary for Science Paul M.
Dabbar, second from left (Photo credit: Argonne National Laboratory) If there is a quantum bubble, it’s inflated both by the new flurry of Sycamore-type academic work and a simultaneous push from private corporations to develop real-world quantum applications, like avoiding traffic jams, as a form of competitive advantage.
We’ve known about the advantages that quantum physics can offer computing since at least the 1980s, when Argonne physicist Paul Benioff described the first quantum mechanical model of a computer.
But the allure of the technology seems to have just now bitten enterprising businesspeople from the tiniest of startups to the largest of conglomerates.
“My personal opinion is there’s never been a more exciting time to be in quantum,” says William Hurley.
Strangeworks, the startup he founded in 2018, serves as a sort of community hub for developers working on quantum algorithms.
Hurley, a software systems analyst who has worked for both Apple and IBM, says that more than 10,000 developers have signed up to submit their algorithms and collaborate with others.
Among the collaborators—Austin-based Strangeworks refers to them as “friends and allies”—is Bay Area startup Rigetti Computing, which supplies one of the three computers that Amazon Web Services customers can access to test out their quantum algorithms.
That service, called Amazon Braket, made its debut in August and counts Volkswagen and Fidelity Investments among its customers.
Quantum information tech is so appealing that conglomerates are now carving out entire research divisions to explore it as a way to stay competitive.
The JPMorgan Chase bank has researchers developing quantum algorithms for every arm of its business, from encryption and security to options trading.
“We’re completely in a research mode right now,” says Rob Matles, the director of JPMorgan’s Future Lab for Applied Research and Engineering.
“We want to be ready when quantum supremacy is met.” Matles is optimistic in particular about how quantum computing can improve options trading, an area of finance in which speed and accuracy is critically important.
Cristiano Malossi, Manager of the AI Automation group at the IBM Research Europe (Photo credit: Jon Simon/Feature Photo Service for IBM) All this activity is both supported and incentivized by the promise of taxpayer funding in the US and abroad.
Established in 2018, America’s National Quantum Initiative is expansive in scope (it calls for a 10-year plan to “accelerate the development of quantum information science and technology applications”) and generosity ($1 billion has been authorized so far).
There’s also plenty of support from the military: The Defense Advanced Research Projects Agency (DARPA) has granted nearly $20 million so far this year to spur the development of quantum computers, with no requirement that they have an advantage over classical ones.
Rigetti, which claims to have the only dedicated quantum integrated circuit foundry in the US, is a magnet for government funding and venture capital.
It secured $9 million from DARPA in March, then closed a $79 million series C, and in August announced plans to build its second quantum computer in the UK as part of a consortium funded by a £10 million (around $13 million) grant from the British government.
Governments and militaries are particularly interested in building a quantum internet, and they have a special affinity for the quantum test loops like the one at Argonne.
“We now have the blueprint to make this quantum internet a reality,” Department of Energy Undersecretary for Science Paul Dabbar announced in July.
Eventually, the department plans to build quantum test loops at all 17 national laboratories and connect them together to create a rudimentary nationwide quantum communications network.
IBM quantum computer (Photo credit: Graham Carlow for IBM) For all of the investment and optimism, however, there’s also a very real sense that the uncertainty of quantum’s capabilities represents a gamble.
“Quantum isn’t ready to solve real-world problems,” Matles admits.
JPMorgan started its quantum research about three years ago, and since then he’s watched advancements such as the Sycamore experiment with interest.
But he insists that the company is still in an optimism phase and isn’t ready to speculate about the specific improvements quantum computing might offer or how long it might take to be ready.
“We’re still in the world of simulation,” Hurley says of quantum information technology.
“These things aren’t computers.
They’re great equipment for exploiting the quantum...
