Google Charts Two-Dimensional Quantum Course

By Tiffany Trader

April 26, 2018

Quantum error correction, essential for achieving universal fault-tolerant quantum computation, is one of the main challenges of the quantum computing field and it’s top of mind for Google’s John Martinis. Delivering a presentation last week at the HPC User Forum in Tucson, Martinis, one of the world’s foremost experts in quantum computing, emphasized that building a useful quantum device is not just about the number of qubits; getting to 50 or 1,000 or 1,000,000 qubits doesn’t mean anything without quality error-corrected qubits to start with.

Martinis compares focusing on merely the number of qubits to wanting to buy a high-performance computer and only specifying the number of cores. How to create quality qubits is something that the leaders in the quantum space at this nascent stage are still figuring out. Google — as well as IBM, Intel, Rigetti, and Yale – are advancing the superconducting qubit approach to quantum computing. Microsoft, Delft, and UC Santa Barbara are involved in topological quantum computing. Photonic quantum computing and trapped ions are other approaches.

The reason quality is difficult in the first place is that qubits – the processing unit of the quantum system – are fundamentally sensitive to small errors, much more so than the classical bit. Martinis explains with a coin on the table analogy:

“If you want to think about classical bits – you can think of that as a coin on a table; we can represent classical information as heads or tails. Classical information is inherently stable. You have this coin on the table, there’s a restoring force, there’s dissipation so even if there’s a little bit of noise it’s going to be stable at zero or one. In a quantum computer you can represent [a quantum bit] not as a coin on a table but a coin in free space, where say zero is up, and one is down and rotated 90 degrees is zero plus one; and in fact you can have any amount of zero and one and it can rotate in this way to change something called quantum phase. You see since it’s kind of an analog system, it can point in any direction. This means that any small change in this is going to give you an error.

“Error correction in quantum systems is a little bit similar to what you see in classical systems where you have clocked logic so you have a memory source, where you have a clock and every clock period you can compute through some arithmetic logic and then you sequence through this and the clock timing kind of takes care of all the different delays you have in the logic. Similar here, you have kind of repetition of the error correction, based on taking the qubit and encoding it in many other qubits and doing parity measurements to see if you’re having both bit-flip errors going like this or phase flip errors going like that.”

The important thing to remember says Martinis is that if you want to have small errors, exponentially small errors, of 10-9 or 10-12, you need a lot of qubits, i.e., quantity, and pretty low error rates of about one error in one-thousand operations, i.e., quality.

In Martinis’s view, quantum computing is “a two-dimensional horse race,” where the tension between quality and quantity means you can’t think in terms of either/or; you have to think about doing both of them at the same time. Progress of the field can thus be charted on a two-dimensional plot.

The first thing to note when assessing the progress in the field are the limiting error rate and the number of qubits for a single device, says Martinis. The chart depicts, for a single device, the worst error rate, the limiting error rate, and the number of qubits. Google is aiming for an error correction of 10-3 in about 103 qubits.

“What happens, “says Martinis, “is as that error rate goes up the number of qubits you have to have to do error correction properly goes up and blows up at the error correction threshold of about 1 percent. I call this the error correction gain. It’s like building transistors with gain; if you want to make something useful you have to have an error correction that’s low enough. If the error correction is not good enough, it doesn’t matter if you have a billion qubits, you are never going to be able to make them more accurate.”

Up to 50 qubits is classically simulatable, but if the error rate is high it gets easier but it is not useful. Pointing to the lower half of the chart, Martinis says “we want to be down here and making lots of qubits. It’s only once you get down here [below the threshold] that talking quantity by itself makes sense.”

One of the challenges of staying under that error correction threshold is that scaling qubits itself can impede error correction, due to undesired cross-talk between qubits. Martinis says that the UC Santa Barbara technology it is working with was designed to reduce cross-talk to produce a scalable technology. For flux cross-talk, fledgling efforts were at 30-40 percent cross-talk. “The initial UC Santa Barbara device was between 1 percent to .1 percent cross-talk and now it’s 10-5,” says Martinis, adding “we barely can measure it.”

The solid black dot on the chart (above) represents that UC Santa Barbara chip. It is 9 qubits and dips just beneath the error correction threshold. Now with its follow-on Bristlecone chip architecture, Google is working to scale the UCSB prototype to >50 qubits to show quantum supremacy, the point at which it would be longer feasible to classically simulate it. The Google team is focused on improving error correction with the expectation that near-term applications will then be feasible. Martinis says the next step is to move out to ~1,000 qubits with exponentially small errors. The end goal is to scale up to a million-or-so qubits with low error rates to solve real-world problems that are intractable on today’s best supercomputers.

The Bristlecone chip consists of 72 qubits, arranged in 2D array. The device has been made and is now undergoing testing to make sure it is operating correctly. Google uses its Qubit Speckle algorithm to validate its quantum supremacy experiments.

Martinis reports that progress on quantum algorithms is also advancing. One of the most compelling applications for quantum computers is quantum chemistry. It’s a natural application for quantum computing, says Martinis. The algorithm though is exponentially hard. In 2011, Microsoft’s quantum computing group documented an O(n11) quantum chemistry algorithm, which would take the age of the universe to run. Work has since progressed and recently the Google theory group showed an algorithm that is Õ(N2.67) for the exact solution and O(N) for the approximate. “[The exact implementation] would take about 100 logical qubits, requiring a million physical qubits,” Martinis notes. “It’s beyond what we can do now, but now the numbers are reasonable so we can think about doing it.”

In closing, Martinis points out that the metrics for assessing the progress of quantum computing in addition to quality and quantity also include speed and connectivity. In different technologies, there can be a factor of 105 or so different speeds. For networking, he says you need at least 2D nearest neighbor corrections to do the error correction properly. Referring to the chart on Google’s key metrics (at left), Martinis says the company isn’t ready to talk about Bristlecone’s error-correction or speed yet but it anticipates good numbers and hopes to show quantum supremacy “very soon.”

Link to slides: https://www.hpcuserforum.com/presentations/tuscon2018/QCOverview_Google_UFTucson2018.pdf

Subscribe to HPCwire's Weekly Update!

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

What’s After Exascale? The Internet of Workflows Says HPE’s Nicolas Dubé

July 29, 2021

With the race to exascale computing in its final leg, it’s natural to wonder what the Post Exascale Era will look like. Nicolas Dubé, VP and chief technologist for HPE’s HPC business unit, agrees and shared his visi Read more…

How UK Scientists Developed Transformative, HPC-Powered Coronavirus Sequencing System

July 29, 2021

In November 2020, the COVID-19 Genomics UK Consortium (COG-UK) won the HPCwire Readers’ Choice Award for Best HPC Collaboration for its CLIMB-COVID sequencing project. Launched in March 2020, CLIMB-COVID has now result Read more…

KAUST Leverages Mixed Precision for Geospatial Data

July 28, 2021

For many computationally intensive tasks, exacting precision is not necessary for every step of the entire task to obtain a suitably precise result. The alternative is mixed-precision computing: using high precision wher Read more…

Oak Ridge Supercomputer Enables Next-Gen Jet Turbine Research

July 27, 2021

Air travel is notoriously carbon-inefficient, with many airlines going as far as to offer purchasable carbon offsets to ease the guilt over large-footprint travel. But even over just the last decade, major aircraft model Read more…

IBM and University of Tokyo Roll Out Quantum System One in Japan

July 27, 2021

IBM and the University of Tokyo today unveiled an IBM Quantum System One as part of the IBM-Japan quantum program announced in 2019. The system is the second IBM Quantum System One assembled outside the U.S. and follows Read more…

AWS Solution Channel

Data compression with increased performance and lower costs

Many customers associate a performance cost with data compression, but that’s not the case with Amazon FSx for Lustre. With FSx for Lustre, data compression reduces storage costs and increases aggregate file system throughput. Read more…

Intel Unveils New Node Names; Sapphire Rapids Is Now an ‘Intel 7’ CPU

July 27, 2021

What's a preeminent chip company to do when its process node technology lags the competition by (roughly) one generation, but outmoded naming conventions make it seem like it's two nodes behind? For Intel, the response w Read more…

What’s After Exascale? The Internet of Workflows Says HPE’s Nicolas Dubé

July 29, 2021

With the race to exascale computing in its final leg, it’s natural to wonder what the Post Exascale Era will look like. Nicolas Dubé, VP and chief technologi Read more…

How UK Scientists Developed Transformative, HPC-Powered Coronavirus Sequencing System

July 29, 2021

In November 2020, the COVID-19 Genomics UK Consortium (COG-UK) won the HPCwire Readers’ Choice Award for Best HPC Collaboration for its CLIMB-COVID sequencing Read more…

Intel Unveils New Node Names; Sapphire Rapids Is Now an ‘Intel 7’ CPU

July 27, 2021

What's a preeminent chip company to do when its process node technology lags the competition by (roughly) one generation, but outmoded naming conventions make i Read more…

Will Approximation Drive Post-Moore’s Law HPC Gains?

July 26, 2021

“Hardware-based improvements are going to get more and more difficult,” said Neil Thompson, an innovation scholar at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL). “I think that’s something that this crowd will probably, actually, be already familiar with.” Thompson, speaking... Read more…

With New Owner and New Roadmap, an Independent Omni-Path Is Staging a Comeback

July 23, 2021

Put on a shelf by Intel in 2019, Omni-Path faced a uncertain future, but under new custodian Cornelis Networks, OmniPath is looking to make a comeback as an independent high-performance interconnect solution. A "significant refresh" – called Omni-Path Express – is coming later this year according to the company. Cornelis Networks formed last September as a spinout of Intel's Omni-Path division. Read more…

Chameleon’s HPC Testbed Sharpens Its Edge, Presses ‘Replay’

July 22, 2021

“One way of saying what I do for a living is to say that I develop scientific instruments,” said Kate Keahey, a senior fellow at the University of Chicago a Read more…

Summer Reading: “High-Performance Computing Is at an Inflection Point”

July 21, 2021

At last month’s 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART), a group of researchers led by Martin Schulz of the Leibniz Supercomputing Center (Munich) presented a “position paper” in which they argue HPC architectural landscape... Read more…

PEARC21 Panel: Wafer-Scale-Engine Technology Accelerates Machine Learning, HPC

July 21, 2021

Early use of Cerebras’ CS-1 server and wafer-scale engine (WSE) has demonstrated promising acceleration of machine-learning algorithms, according to participa Read more…

AMD Chipmaker TSMC to Use AMD Chips for Chipmaking

May 8, 2021

TSMC has tapped AMD to support its major manufacturing and R&D workloads. AMD will provide its Epyc Rome 7702P CPUs – with 64 cores operating at a base cl Read more…

Intel Launches 10nm ‘Ice Lake’ Datacenter CPU with Up to 40 Cores

April 6, 2021

The wait is over. Today Intel officially launched its 10nm datacenter CPU, the third-generation Intel Xeon Scalable processor, codenamed Ice Lake. With up to 40 Read more…

Berkeley Lab Debuts Perlmutter, World’s Fastest AI Supercomputer

May 27, 2021

A ribbon-cutting ceremony held virtually at Berkeley Lab's National Energy Research Scientific Computing Center (NERSC) today marked the official launch of Perlmutter – aka NERSC-9 – the GPU-accelerated supercomputer built by HPE in partnership with Nvidia and AMD. Read more…

Ahead of ‘Dojo,’ Tesla Reveals Its Massive Precursor Supercomputer

June 22, 2021

In spring 2019, Tesla made cryptic reference to a project called Dojo, a “super-powerful training computer” for video data processing. Then, in summer 2020, Tesla CEO Elon Musk tweeted: “Tesla is developing a [neural network] training computer called Dojo to process truly vast amounts of video data. It’s a beast! … A truly useful exaflop at de facto FP32.” Read more…

Google Launches TPU v4 AI Chips

May 20, 2021

Google CEO Sundar Pichai spoke for only one minute and 42 seconds about the company’s latest TPU v4 Tensor Processing Units during his keynote at the Google I Read more…

CentOS Replacement Rocky Linux Is Now in GA and Under Independent Control

June 21, 2021

The Rocky Enterprise Software Foundation (RESF) is announcing the general availability of Rocky Linux, release 8.4, designed as a drop-in replacement for the soon-to-be discontinued CentOS. The GA release is launching six-and-a-half months after Red Hat deprecated its support for the widely popular, free CentOS server operating system. The Rocky Linux development effort... Read more…

CERN Is Betting Big on Exascale

April 1, 2021

The European Organization for Nuclear Research (CERN) involves 23 countries, 15,000 researchers, billions of dollars a year, and the biggest machine in the worl Read more…

Iran Gains HPC Capabilities with Launch of ‘Simorgh’ Supercomputer

May 18, 2021

Iran is said to be developing domestic supercomputing technology to advance the processing of scientific, economic, political and military data, and to strengthen the nation’s position in the age of AI and big data. On Sunday, Iran unveiled the Simorgh supercomputer, which will deliver.... Read more…

Leading Solution Providers

Contributors

HPE Launches Storage Line Loaded with IBM’s Spectrum Scale File System

April 6, 2021

HPE today launched a new family of storage solutions bundled with IBM’s Spectrum Scale Erasure Code Edition parallel file system (description below) and featu Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

GTC21: Nvidia Launches cuQuantum; Dips a Toe in Quantum Computing

April 13, 2021

Yesterday Nvidia officially dipped a toe into quantum computing with the launch of cuQuantum SDK, a development platform for simulating quantum circuits on GPU-accelerated systems. As Nvidia CEO Jensen Huang emphasized in his keynote, Nvidia doesn’t plan to build... Read more…

Microsoft to Provide World’s Most Powerful Weather & Climate Supercomputer for UK’s Met Office

April 22, 2021

More than 14 months ago, the UK government announced plans to invest £1.2 billion ($1.56 billion) into weather and climate supercomputing, including procuremen Read more…

Quantum Roundup: IBM, Rigetti, Phasecraft, Oxford QC, China, and More

July 13, 2021

IBM yesterday announced a proof for a quantum ML algorithm. A week ago, it unveiled a new topology for its quantum processors. Last Friday, the Technical Univer Read more…

Q&A with Jim Keller, CTO of Tenstorrent, and an HPCwire Person to Watch in 2021

April 22, 2021

As part of our HPCwire Person to Watch series, we are happy to present our interview with Jim Keller, president and chief technology officer of Tenstorrent. One of the top chip architects of our time, Keller has had an impactful career. Read more…

Senate Debate on Bill to Remake NSF – the Endless Frontier Act – Begins

May 18, 2021

The U.S. Senate today opened floor debate on the Endless Frontier Act which seeks to remake and expand the National Science Foundation by creating a technology Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire