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Sandia-Led Research Projects Aim at Speeding Up Quantum Algorithms over Classical Ones

Quantum computing appears periodically in the media similar to heat lightning in the desert—attention-getting, brilliant, and then disappearing from the people’s mind with no evident consequences.

Sandia National Laboratories researcher Mohan Sarovar is developing software for quantum testbeds. Sandia’s quantum computer will play a role analogous to those of graphics processing units in today’s high-performance computers. (Image credit: Randy Wong)

However, an international effort to develop quantum computers, worth several million dollars, doesn’t seem to fade away.

Currently, the goal of four new projects headed by Sandia National Laboratories is to bring the ambiguous subject into steady limelight by developing:

  • A quantum computing “testbed” including accessible components on which scientists from the academia, industry, and government can run their own algorithms
  • A test programs package to measure the performance of quantum hardware
  • Classical software to guarantee reliable operation of quantum computing testbeds and to coax the maximum utility from them.
  • High-level quantum algorithms that investigate connections with classical optimization, theoretical physics, and machine learning.

Funding for the three- to five-year projects amounts to $42 million and has been offered by the Department of Energy’s Office of Science’s Advanced Scientific Computing Research program, part of Sandia’s Advanced Science and Technology portfolio.

Quantum information science “represents the next frontier in the information age,” stated U.S. Secretary of Energy Rick Perry this fall when he announced $218 million in DOE funding for the study. “At a time of fierce international competition, these investments will ensure sustained American leadership in a field likely to shape the long-term future of information processing and yield multiple new technologies that benefit our economy and society.”

The California Institute of Technology, Los Alamos National Laboratory, Dartmouth College, Duke University, the University of Maryland, and Tufts University are partners on three of the four Sandia-headed projects.

Birth of a generally available quantum computer

Just the design and construction of the quantum computer—officially known as the Quantum Scientific Computing Open User Testbed (QSCOUT)—directed by Sandia researcher Peter Maunz, is a $25.1 million, five-year project that involves the use of trapped atomic ion technology.

According to Maunz, trapped ions are specifically appropriate for achieving a quantum computer since quantum bits—or qubits, which are the quantum generalization of classical bits—are encoded in the electronic states of individual trapped atomic ions.

Because trapped ions are identical and suspended by electric fields in a vacuum, they feature identical, nearly perfect qubits that are well isolated from the noise of the environment and therefore can store and process information faithfully. While current small-scale quantum computers without quantum error correction are still noisy devices, quantum gates with the lowest noise have been realized with trapped-ion technology.

Peter Maunz, Researcher, Sandia National Laboratories

A quantum gate is a basic building block of a quantum circuit that operates on a small number of qubits.

Moreover, Maunz stated that in trapped-ion systems, “It is possible to realize quantum gates between all pairs of ions in the same trap, a feature which can crucially reduce the number of gates needed to realize a quantum computation.”

The main aim for making QSCOUT is to develop a trapped-ion quantum computer that can be accessed by the DOE scientific community. According to Maunz, since it is an open platform, it will not just offer complete information related to all its classical and quantum processes, it will also allow scientists to analyze, modify, and optimize the innards of the testbed, or even to suggest more sophisticated implementations of the quantum operations.

Since the existing quantum computers can access just a limited number of qubits and their operation is still subject to errors, these devices do not yet have the ability to solve scientific problems that cannot be solved by classical computers. However, access to prototype quantum processors such as QSCOUT should enable scientists to optimize prevalent quantum algorithms, invent new ones, and evaluate the power of quantum computing to solve complex scientific problems, stated Maunz.

Proof of the pudding

But how can researchers be in a position to guarantee that the technical components of a quantum testbed perform as anticipated?

A group of researchers from Sandia headed by Robin Blume-Kohout, a quantum researcher, is working to create a toolbox of techniques to evaluate the performance of quantum computers in real-world scenarios.

Our goal is to devise methods and software that assess the accuracy of quantum computers.

Robin Blume-Kohout, Quantum Researcher, Sandia National Laboratories

The aim of the $3.7 million, five-year Quantum Performance Assessment project is to create a wide range of small quantum software programs, ranging from simple routines such as “flip this qubit and then stop,” to testbed-sized samples of real quantum algorithms for chemistry or machine learning that can be run nearly on any quantum processor.

These programs have not been written in a high-level computer language; rather, they are sequences of elementary instructions designed to run directly on the qubits and bring about a familiar outcome.

However, Blume-Kohout stated that “because we recognize that quantum mechanics is also intrinsically somewhat random, some of these test programs are intended to produce 50/50 random results. That means we need to run test programs thousands of times to confirm that the result really is 50/50 rather than, say, 70/30, to check a quantum computer’s math.”

The aim of the researchers is to use testbed outcomes to debug processors such as QSCOUT by identifying problems to enable engineers to fix them. This necessitates substantiate expertise in both physics and statistics, yet Blume-Kohout is optimistic.

This project builds on what Sandia has been doing for five years,” he said. “We’ve tackled similar problems in other situations for the U.S. government.”

For instance, he stated that the Intelligence Advanced Research Projects Activity reached out to Sandia to assess the outcomes of the performers on its LogiQ program, the goal of which is to enhance the fidelity of quantum computing. “We expect be able to say with a certain measure of reliability, ‘Here are the building blocks you need to achieve a goal,’” stated Blume-Kohout.

Quantum and classical computing meet up

As soon as Maunz’s team build the computer and Blume-Kohout’s group ascertain its reliability, how will it be used for computational tasks?

The aim of the four-year Optimization, Verification and Engineered Reliability of Quantum Computers project led by Sandia, amounting to $7.8 million, is to answer this question. LANL and Dartmouth College are partners.

Mohan Sarovar, project lead and physicist, anticipates that the first quantum computer built at Sandia will be a very specialized processor, having a role equivalent to that played by graphics processing units in high-performance computing.

Similarly, the quantum testbed will be good at doing some specialized things. It’ll also be ‘noisy.’ It won’t be perfect. My project will ask: What can you use such specialized units for? What concrete tasks can they perform, and how can we use them jointly with specialized algorithms connecting classical and quantum computers?

Mohan Sarovar, Project Lead and Physicist, Sandia National Laboratories

The goal of the researchers is to create classical “middleware” intended to make computational use of the QSCOUT testbed and analogous near-term quantum computers.

While we have excellent ideas for how to use fully developed, fault-tolerant quantum computers, we’re not really sure what computational use the limited devices we expect to see created in the near future will be. We think they will play the role of a very specialized co-processor within a larger, classical computational framework.

Mohan Sarovar, Project Lead and Physicist, Sandia National Laboratories

The aim of the project is to develop heuristics, tools, and software to obtain dependable, useful answers from such near-term quantum co-processors.

At the peak

Considering at the most theoretical level, the group of computer scientists and theoretical physicists, led by researcher Ojas Parekh, of the year-old, Sandia-led Quantum Optimization and Learning and Simulation (QOALAS) project have developed an innovative quantum algorithm for solving linear systems of equations—one of the most basic and universal challenges facing science and engineering.

Apart from Sandia, LANL, the University of Maryland, and Caltech are part of the three-year, $4.5 million project.

Our quantum linear systems algorithm, created at LANL, has the potential to provide an exponential speedup over classical algorithms in certain settings. Although similar quantum algorithms were already known for solving linear systems, ours is much simpler. For many problems in quantum physics we want to know what is the lowest energy state? Understanding such states can, for example, help us better understand how materials work. Classical discrete optimization techniques developed over the last 40 years can be used to approximate such states. We believe quantum physics will help us obtain better or faster approximations.

Ojas Parekh, Researcher, Sandia National Laboratories

The researchers are working on other quantum algorithms that might provide an exponential acceleration over the ever best classical algorithms. For instance, stated Parekh, “If a classical algorithm required 2100 steps—two times itself one hundred times, or 1,267,650,600,228,229,401,496,703,205,376 steps—to solve a problem, which is a number believed to be larger than all the particles in the universe, then the quantum algorithm providing an exponential speed-up would only take 100 steps. An exponential speedup is so massive that it might dwarf such practical hang-ups as, say, excessive noise.”

Sooner or later, quantum will be faster,” he stated.

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