STAQ(ing) the Quantum Computing Deck

By John Russell

August 16, 2018

Quantum computers – at least for now – remain noisy. That’s another way of saying unreliable and in diverse ways that often depend on the specific quantum technology used. One idea is to mitigate noisiness and perhaps seamlessly capture some of the underlying quantum physics by mapping quantum algorithms more directly to the underlying hardware; this might make nearer-term quantum computers practical for some problems. This approach, at least in part, is central to the Software Tailored Architecture for Quantum Design (STAQ) project, announced by NSF last week and led by co-PIs Kenneth Brown and Jungsang Kim of Duke University.

Every project needs a goal and the big callout here is building a 64- (or more) qubit ion trap-based quantum computer capable of tackling problems that classical computers currently stumble on. But that doesn’t catch the scope of the project which is making a point of leveraging multidiscipline expertise to put co-design to work in the quantum domain, exploring specific algorithms for condensed matter physics and quantum chemistry, as well as more general quantum algorithm optimization. There’s also a requirement to run a summer school to share the learnings.

“I always joke that if I knew what the silicon transistor was of quantum computing, I would just do it. But I don’t.” Brown told HPCwire. “Right now I think both superconductors and ion traps have shown a lot of progress and demonstrated a large number of algorithms. The advantage of trapped ions is that every ion is the same. For these small chains [of ions in the trap] you do get this advantage of basically being able to achieve communication between any pair. In superconducting devices, typically, you are only able to talk to sort of neighbor qubits. So if you have an algorithm which requires a longer distance communication between qubits, there is some cost you have to pay to get the information from one to the other.”

There’s a lot going on here – as there is throughout the quantum computing research community. Zeroing in on ion traps for quantum computing isn’t new but it hasn’t received the same notice that semiconductor-based superconducting approaches have á la IBM, Google, D-Wave, Rigetti et. al. NIST (National Institute of Standards and Technology) has put ion trap technology for use as super accurate atomic clocks and a few academic groups have also explored ion trap quantum computing, but without the fanfare attendant other efforts. It turns out ion trap technology – somewhat similar to the mass spec we all know – has several strengths for use in quantum computing.

Brown, Kim, and colleague Christopher Monroe’s (University of Maryland) have written a nice paper on the topic, Co-Designing a Scalable Quantum Computer with Trapped Atomic Ions. Brown is quick to point out 1,000-qubit scale-up ideas presented in the 2016 paper far exceed STAQ’s goal, but that such scaling ambitions do seem reachable over time with ion trap technology.

Here’s brief excerpt from their paper touching on ion technology’s attraction:

“Superconducting circuitry exploits the significant advantages of modern lithography and fabrication technologies: it can be integrated on a solid-state platform and many qubits can simply be printed on a chip. However, they suffer from inhomogeneities and decoherence, as no two superconducting qubits are the same, and their connectivity cannot be reconfigured without replacing the chip or modifying the wires connecting them within a very low temperature environment.

“Trapped atomic ions, on the other hand, feature virtually identical qubits, and their wiring can be reconfigured by modifying externally applied electromagnetic fields. However, atomic qubit switching speeds are generally much slower than solid state devices, and the development of engineering infrastructure for trapped ion quantum computers and the mitigation of noise and decoherence from the applied control fields is just beginning.”

Perhaps a quick (and imperfect) description of ion trap technology is warranted. It’s similar to mass spec. Ions are loaded into traps by generating neutral atoms of the desired element and ionizing the atoms once in the trapping volume. Electrodes (rods) are used to generate forces to contain the ions. RF and laser emissions are used to control the ions, which can be lined in ‘stationary’ chains. Individual ions have their electron states manipulating using lasers which turns them into qubit registers. Brown’s group is using Ytterbium (Yb+) ions whose outer electron shell structure is well-suited for manipulation.

“The trap we use looks like a computer chip, sort of like metal on silicon chip. It’s similar to the four-rod trap (quadrupole) you probably know from mass spec. You cut one of the rods and then you’ve unfolded the trap onto a plate and advantage of that is it allows you to then move the ions around, break the break chains apart, and that sort of thing. It also gives you more control over fields that are containing the ions and the direction of the chain itself. That is housed in a vacuum chamber which is achieved with either vacuum system or with a cryogenic chamber. This is one of the designs questions we are working on right, deciding which way to go,” said Brown.

One important ion trap technology advantage, according to Brown, is the qubit type, something called ‘hyperfine’ qubits. “They basically have no memory error. So unlike many other qubits where you have a constant decay – and it’s all relative to the gate speeds – our relative decay-to-gate-speed is a long, long time. For example, the best result I know of is if you have a microsecond gate time, which is kind of typical for ions, you can have a memory time of ten minutes,” he said.

As explained in their paper, “Qubits stored in trapped atomic ions are represented by two stable electronic levels within each ion, often represented as an effective spin with the two states |↓⟩and |↑⟩corresponding to bit values 0 and 1. The qubits can be initialized and detected with nearly perfect accuracy using conventional optical pumping and state-dependent fluorescence techniques. This restricts the atomic species of trapped ion qubits to those with simple electronic structure (e.g., those with a single valence electron: Be+, Mg+, Ca+, Sr+, Ba+, Zn+, Hg+, Cd+, and Yb+)” Shown below is a schematic from their paper roughly describing a chip-based ion trap.

Co-design is the central tenet for STAQ. “This idea of the software tailored architecture, co-design, is basically we want to make the tools which optimize the mapping of the ideal mathematical algorithm to the actual device of interest. So there are a few things we plan to leverage. One is the at the bottom layer. We often abstract the physics of the quantum device. This has actually been really useful for quantum information as a whole. It allows people to talk about superconducting machines, or ion trap machines, or photon computers, so all these things using the same language. But the underlying physics beneath that gate layer [are] different and there might be some opportunities to simplify some algorithms such that we actually don’t completely remove that abstraction and allow some of the physics [specific to ion trap technology] to seep up to the programmer,” noted Brown.

Building a stack able to take advantage of this flexibility is one of STAQ’s goals. “The idea of the stack is to try to actually do what one of my colleagues says is like a crossword puzzle. We just don’t optimize the algorithm, and then optimize the gate set, and then optimize each gate on the hardware, but we try to modify the gates so that it’s the most appropriate for optimizing the algorithm given the problem,” said Brown.

The breadth of expertise on the STAQ team, said Brown, is a distinct advantage: “We have computer architects. We have quantum information theorists. We have people more on the applications side, and hardware people. You need all those people. You need those different layers working. I think what’s nice is we are reaching a point where these machines are reaching sufficient sophistication that it is easier to find people to think about architecture.”

In some sense flexibility in manipulating ion chains (breaking apart at different lengths, remote entanglement among qubits) allows an almost FPGA-programming-like quality to ion trap quantum computing. “You can do these two-qubit gates between any pair [of ions] and the reason is it’s not like a direct interaction with its neighbor but an interaction which is mediated by the collective motion of the ion chain. In terms of actually mapping algorithms to computers it’s quite nice because if I think about the connection between qubits it’s like a fully connected graph,” said Brown.

“Now that’s not going to scale to 1000 qubits but it’s not clear what the limit is. We know 10 qubits, 20 qubits is no problem. [And] we have some ideas on how to get to 50 qubits but at some point we are going to have to shift the way we put these things together.”

Quantum chemistry is one area of application being examined. “The challenge in doing quantum chemistry on a normal conventional computer is there’s a mismatch between how much classical data we need to store a quantum state,” said Brown. “With a quantum computer you already have this win where there’s a better match. The quantum state on the computer representing the molecule uses a comparable amount of space because they are both in some sense quantum memory. The next thing is each system has kind of its own natural interaction. With an ion trap system, the way the particular gate is performed, the underlying interaction looks a lot looks a lot like a magnetic interaction between two systems. So if the problem you are trying to solve maps nicely to this kind of magnetic interaction, there are actually a lot of shortcuts you can take.”

Given ion trap technology’s flexibility, STAQ hopes to learn whether it may be possible or worthwhile to create application-specific architectures.

“That is one of our big research questions,” according to Brown. “[The issue] is what is the gain there. If you think about a tablet computer or an iPad, it has a facial recognition chip. Its job is just to see faces, right. So we expect that quantum computers will be kind of like that, at least in near term, sort of an extra processor that is interacting with some classical computer. It may turn out to be possible to make quantum processors that are say specifically designed for quantum chemistry problems, that could be a great accelerator for all kinds of applications in chemistry.”

While STAQ plans to leverage the underlying characteristics ion trap technology which might include ASIC-like capabilities, “all of the devices we plan to make will be universal in that they will allow you to do universal quantum computing,” emphasized Brown.

STAQ will also run an annual summer school at Duke aimed at two different audiences, said Brown, one drawn from upper level undergraduate and early graduate school students looking to learn more about quantum information and another group drawn from industry.

Looking at near-term (~18-month) goals, Brown said, “On the algorithm side I hope to identify target algorithms for a computer on the scale of say 60 to 70 qubits. On the experimental side, that first year and a half will be building a new engineering design and building a new system based on our previous experiments with ion traps but moving more towards a functional computer and [something] less like a physics experiment.”

Link to NSF grant: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1818914

Link to Brown’s 2016 paper: https://arxiv.org/abs/1602.02840

Link to earlier HPCwire article: https://www.hpcwire.com/2018/08/07/nsf-invests-15-million-quantum-staq/

Images: Brown paper; NSF

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!

Nvidia Aims Clara Healthcare at Drug Discovery, Imaging via DGX

April 12, 2021

Nvidia Corp. continues to expand its Clara healthcare platform with the addition of computational drug discovery and medical imaging tools based on its DGX A100 platform, related InfiniBand networking and its AGX develop Read more…

Nvidia Serves Up Its First Arm Datacenter CPU ‘Grace’ During Kitchen Keynote

April 12, 2021

Today at Nvidia’s annual spring GPU technology conference, held virtually once more due to the ongoing pandemic, the company announced its first ever Arm-based CPU, called Grace in honor of the famous American programmer Grace Hopper. Read more…

Nvidia Debuts BlueField-3 – Its Next DPU with Big Plans for an Expanded Role

April 12, 2021

Nvidia today announced its next generation data processing unit (DPU) – BlueField-3 – adding more substance to its evolving concept of the DPU as a full-fledged partner to CPUs and GPUs in delivering advanced computi Read more…

Nvidia’s Newly DPU-Enabled SuperPOD Is a Multi-Tenant, Cloud-Native Supercomputer

April 12, 2021

At GTC 2021, Nvidia has announced an upgraded iteration of its DGX SuperPods, calling the new offering “the first cloud-native, multi-tenant supercomputer.” The newly announced SuperPods come just two years after the Read more…

Tune in to Watch Nvidia’s GTC21 Keynote with Jensen Huang – Recording Now Available

April 12, 2021

Join HPCwire right here on Monday, April 12, at 8:30 am PT to see the Nvidia GTC21 keynote from Nvidia’s CEO, Jensen Huang, livestreamed in its entirety. Hosted by HPCwire, you can click to join the Huang keynote on our livestream to hear Nvidia’s expected news and... Read more…

AWS Solution Channel

Volkswagen Passenger Cars Uses NICE DCV for High-Performance 3D Remote Visualization

 

Volkswagen Passenger Cars has been one of the world’s largest car manufacturers for over 70 years. The company delivers more than 6 million automobiles to global customers every year, from 50 production locations on five continents. Read more…

The US Places Seven Additional Chinese Supercomputing Entities on Blacklist

April 8, 2021

As tensions between the U.S. and China continue to simmer, the U.S. government today added seven Chinese supercomputing entities to an economic blacklist. The U.S. Entity List bars U.S. firms from supplying key technolog Read more…

Nvidia Serves Up Its First Arm Datacenter CPU ‘Grace’ During Kitchen Keynote

April 12, 2021

Today at Nvidia’s annual spring GPU technology conference, held virtually once more due to the ongoing pandemic, the company announced its first ever Arm-based CPU, called Grace in honor of the famous American programmer Grace Hopper. Read more…

Nvidia Debuts BlueField-3 – Its Next DPU with Big Plans for an Expanded Role

April 12, 2021

Nvidia today announced its next generation data processing unit (DPU) – BlueField-3 – adding more substance to its evolving concept of the DPU as a full-fle Read more…

Nvidia’s Newly DPU-Enabled SuperPOD Is a Multi-Tenant, Cloud-Native Supercomputer

April 12, 2021

At GTC 2021, Nvidia has announced an upgraded iteration of its DGX SuperPods, calling the new offering “the first cloud-native, multi-tenant supercomputer.” Read more…

Tune in to Watch Nvidia’s GTC21 Keynote with Jensen Huang – Recording Now Available

April 12, 2021

Join HPCwire right here on Monday, April 12, at 8:30 am PT to see the Nvidia GTC21 keynote from Nvidia’s CEO, Jensen Huang, livestreamed in its entirety. Hosted by HPCwire, you can click to join the Huang keynote on our livestream to hear Nvidia’s expected news and... Read more…

The US Places Seven Additional Chinese Supercomputing Entities on Blacklist

April 8, 2021

As tensions between the U.S. and China continue to simmer, the U.S. government today added seven Chinese supercomputing entities to an economic blacklist. The U Read more…

Habana’s AI Silicon Comes to San Diego Supercomputer Center

April 8, 2021

Habana Labs, an Intel-owned AI company, has partnered with server maker Supermicro to provide high-performance, high-efficiency AI computing in the form of new Read more…

Intel Partners Debut Latest Servers Based on the New Intel Gen 3 ‘Ice Lake’ Xeons

April 7, 2021

Fresh from Intel’s launch of the company’s latest third-generation Xeon Scalable “Ice Lake” processors on April 6 (Tuesday), Intel server partners Cisco, Dell EMC, HPE and Lenovo simultaneously unveiled their first server models built around the latest chips. And though arch-rival AMD may... 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…

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…

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…

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…

Programming the Soon-to-Be World’s Fastest Supercomputer, Frontier

January 5, 2021

What’s it like designing an app for the world’s fastest supercomputer, set to come online in the United States in 2021? The University of Delaware’s Sunita Chandrasekaran is leading an elite international team in just that task. Chandrasekaran, assistant professor of computer and information sciences, recently was named... Read more…

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…

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…

Saudi Aramco Unveils Dammam 7, Its New Top Ten Supercomputer

January 21, 2021

By revenue, oil and gas giant Saudi Aramco is one of the largest companies in the world, and it has historically employed commensurate amounts of supercomputing Read more…

Quantum Computer Start-up IonQ Plans IPO via SPAC

March 8, 2021

IonQ, a Maryland-based quantum computing start-up working with ion trap technology, plans to go public via a Special Purpose Acquisition Company (SPAC) merger a Read more…

Leading Solution Providers

Contributors

Can Deep Learning Replace Numerical Weather Prediction?

March 3, 2021

Numerical weather prediction (NWP) is a mainstay of supercomputing. Some of the first applications of the first supercomputers dealt with climate modeling, and Read more…

Livermore’s El Capitan Supercomputer to Debut HPE ‘Rabbit’ Near Node Local Storage

February 18, 2021

A near node local storage innovation called Rabbit factored heavily into Lawrence Livermore National Laboratory’s decision to select Cray’s proposal for its CORAL-2 machine, the lab’s first exascale-class supercomputer, El Capitan. Details of this new storage technology were revealed... Read more…

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

African Supercomputing Center Inaugurates ‘Toubkal,’ Most Powerful Supercomputer on the Continent

February 25, 2021

Historically, Africa hasn’t exactly been synonymous with supercomputing. There are only a handful of supercomputers on the continent, with few ranking on the Read more…

The History of Supercomputing vs. COVID-19

March 9, 2021

The COVID-19 pandemic poses a greater challenge to the high-performance computing community than any before. HPCwire's coverage of the supercomputing response t Read more…

HPE Names Justin Hotard New HPC Chief as Pete Ungaro Departs

March 2, 2021

HPE CEO Antonio Neri announced today (March 2, 2021) the appointment of Justin Hotard as general manager of HPC, mission critical solutions and labs, effective Read more…

AMD Launches Epyc ‘Milan’ with 19 SKUs for HPC, Enterprise and Hyperscale

March 15, 2021

At a virtual launch event held today (Monday), AMD revealed its third-generation Epyc “Milan” CPU lineup: a set of 19 SKUs -- including the flagship 64-core, 280-watt 7763 part --  aimed at HPC, enterprise and cloud workloads. Notably, the third-gen Epyc Milan chips achieve 19 percent... Read more…

Microsoft, HPE Bringing AI, Edge, Cloud to Earth Orbit in Preparation for Mars Missions

February 12, 2021

The International Space Station will soon get a delivery of powerful AI, edge and cloud computing tools from HPE and Microsoft Azure to expand technology experi Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire