Researcher Explores Phosphorus-And-Silicon Quantum Computer

By Nicole Hemsoth

November 24, 2006

A University of Utah physicist took a step toward developing a superfast computer based on the weird reality of quantum physics by showing it is feasible to read data stored in the form of the magnetic “spins” of phosphorus atoms.

“Our work represents a breakthrough in the search for a nanoscopic [atomic scale] mechanism that could be used for a data readout device,” says Christoph Boehme, assistant professor of physics at the University of Utah. “We have demonstrated experimentally that the nuclear spin orientation of phosphorus atoms embedded in silicon can be measured by very subtle electric currents passing through the phosphorus atoms.”

The study by Boehme and colleagues in Germany will be published in the December issue of the journal Nature Physics and released online Sunday, Nov. 19.

“We have resolved a major obstacle for building a particular kind of quantum computer, the phosphorus-and-silicon quantum computer,” says Boehme. “For this concept, data readout is the biggest issue, and we have shown a new way to read data.”

Boehme, who joined the University of Utah faculty earlier this year, conducted the study with Klaus Lips — a former colleague at the Hahn-Meitner Institute in Berlin — and with graduate students Andre Stegner and Hans Huebl and physicists Martin Stutzmann and Martin S. Brandt of the Technical University of Munich.

A Bit about Quantum Computing

In modern digital computers, information is transmitted by flowing electricity in the form of electrons, which are negatively charged subatomic particles. Transistors in computers are electrical switches that store data as “bits,” in which “off” (no electrical charge) and “on” (charge is present) represent one bit of information: either 0 or 1.

For example, with three bits, there are eight possible combinations of 1 or 0: 1-1-1, 0-1-1, 1-0-1, 1-1-0, 0-0-0, 1-0-0, 0-1-0 and 0-0-1. But three bits in a digital computer can store only one of those eight combinations at a time.

Quantum computers, which have not been built yet, would be based on the strange principles of quantum mechanics, in which the smallest particles of light and matter can be in different places at the same time.

In a quantum computer, one “qubit” — quantum bit — could be both 0 and 1 at the same time. So with three qubits of data, a quantum computer could store all eight combinations of 0 and 1 simultaneously. That means a three-qubit quantum computer could calculate eight times faster than a three-bit digital computer.

Typical personal computers today calculate 64 bits of data at a time. A quantum computer with 64 qubits would be 2 to the 64th power faster, or about 18 billion billion times faster.

Researchers are exploring many approaches to storing and processing information in nanoscopic form — on the scale of molecules and atoms, or one billionth of a meter in size — for quantum computing. They include optical quantum computers that would hold data in the form of on-off switches made of light, ions (electrically charged atoms), the size or energy state of an electron's orbit around an atom, so-called “quantum dots” of material and the “spins” or magnetic orientation of the centers or nuclei of atoms.

A New Spin on Quantum Computers

Boehme's new study deals with an approach to a quantum computer proposed in 1998 by Australian physicist Bruce Kane in a Nature paper titled “A silicon-based nuclear spin quantum computer.” In such a computer, silicon — the semiconductor used in digital computer chips — would be “doped” with atoms of phosphorus, and data would be encoded in the “spins” of those atoms' nuclei. Externally applied electric fields would be used to read and process the data stored as “spins.”

Spin is difficult to explain. A simplified way to describe spin is to imagine that each particle — like an electron or proton in an atom — contains a tiny bar magnet, like a compass needle, that points either up or down to represent the particle's spin. Down and up can represent 0 and 1 in a spin-based quantum computer, in which one qubit could have a value of 0 and 1 simultaneously.

In the new study, Boehme and colleagues used silicon doped with phosphorus atoms. By applying an external electrical current, they were able to “read” the net spin of 10,000 of the electrons and nuclei of phosphorus atoms near the surface of the silicon.

A real quantum computer would need to read the spins of single particles, not thousands of them. But previous efforts, which used a technique called magnetic resonance, were able to read only the net spins of the electrons of 10 billion phosphorus atoms combined, so the new study represents a million-fold improvement and shows it is feasible to read single spins — something that would take another 10,000-fold improvement, Boehme says.

But the point of the study, he adds, is that it demonstrates it is possible to use electrical methods to detect or “read” data stored as not only electron spins but as the more stable spins of atomic nuclei.

“We discovered a mechanism that will allow us to measure the spins of the nuclei of individual phosphorus atoms in a piece of silicon when the phosphorus is close [within about 50 atoms] to the surface,” Boehme says. With improved design, it should be possible to build a much smaller device that “lets us read a single phosphorus nucleus.”

Details of the Experiment

The researchers used a piece of silicon crystal about 300 microns thick — about three times the width of a human hair — less than 3 inches long and about one-tenth of an inch wide. The silicon crystal was doped with phosphorus atoms. Phosphorus atoms were embedded in silicon because too many phosphorus atoms too close together would interact with each other so much that they couldn't store information. The concept is that the nuclear spin from one atom of phosphorus would store one qubit of information.

The scientists used lithography to print two gold electrical contacts onto the doped silicon. Then they placed an extremely thin layer of silicon dioxide — about two billionths of a meter thick — onto the silicon between the gold contacts. As a result, the device's surface had tiny spots where the spins of phosphorus atoms could be detected.

The scientists applied a tiny voltage to the gold contacts, creating an electrical current perhaps 10,000 times smaller than that produced by an AA-size battery, Boehme says. When the current was measured during 100 millionths of a second, it stayed constant, indicating the spins of the phosphorus atoms in the silicon were random, with half pointing up and half pointing down.

Then the device was chilled with liquid helium to 452 degrees below zero Fahrenheit. That made most of the phosphorus spins point down. Next, the researchers applied a magnetic field and microwave radiation to the sample, which makes the phosphorus spins constantly flop up and down in concert for a few billionths of a second.

As a result, the electrical current fluctuated up and down.

“That is basically a readout of phosphorus electron spins,” which, in turn, also can be used to determine the spins of the phosphorus atoms' nuclei based on a previously known relationship between electron spins and nuclear spins, Boehme says.

While Boehme is excited by this advance, numerous obstacles remain before quantum computing becomes a reality.

“If you want to compare the development of quantum computers with classical computers, we probably would be just before the discovery of the abacus,” he says. “We are very early in development.”

—–

Source: University of Utah

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Mystery Solved: Intel’s Former HPC Chief Now Running Software Engineering Group 

April 15, 2024

Last year, Jeff McVeigh, Intel's readily available leader of the high-performance computing group, suddenly went silent, with no interviews granted or appearances at press conferences.  It led to questions -- what's Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Institute for Human-Centered AI (HAI) put out a yearly report to t Read more…

Crossing the Quantum Threshold: The Path to 10,000 Qubits

April 15, 2024

Editor’s Note: Why do qubit count and quality matter? What’s the difference between physical qubits and logical qubits? Quantum computer vendors toss these terms and numbers around as indicators of the strengths of t Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips are available off the shelf, a concern raised at many recent Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announced its second fund targeting €200 million. The very idea th Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. In a way, Nvidia is the new Intel IDF, the hottest chip show Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it Read more…

Computational Chemistry Needs To Be Sustainable, Too

April 8, 2024

A diverse group of computational chemists is encouraging the research community to embrace a sustainable software ecosystem. That's the message behind a recent Read more…

Hyperion Research: Eleven HPC Predictions for 2024

April 4, 2024

HPCwire is happy to announce a new series with Hyperion Research  - a fact-based market research firm focusing on the HPC market. In addition to providing mark Read more…

Google Making Major Changes in AI Operations to Pull in Cash from Gemini

April 4, 2024

Over the last week, Google has made some under-the-radar changes, including appointing a new leader for AI development, which suggests the company is taking its Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

Leading Solution Providers

Contributors

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

Intel’s Xeon General Manager Talks about Server Chips 

January 2, 2024

Intel is talking data-center growth and is done digging graves for its dead enterprise products, including GPUs, storage, and networking products, which fell to Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire