19 February 2021

Quantum Computing Inc. Introduces Qatalyst, a Quantum Application Accelerator

 


Qatalyst, a Quantum Application Accelerator

One of the best places where a quantum computer can be used for advantage over a classical approach is with optimization problems. These are problems where one seeks to find the lowest energy value in a mathematical equation expressed as a QUBO (Quadratic Unconstrained Binary Optimization) and they are applicable in a great many areas including finance, logistics, drug discovery, cybersecurity, machine learning, and many others. To this end, Quantum Computing Inc. (QCI) has announced commercial availability of their Qatalyst software (formerly called Mukai) to solve these types of problems efficiently on a variety of hardware platforms, both classical and quantum.

One advantage to the Qatalyst software is that many data scientists are quite familiar with using optimization problems with classical computing solvers and they should be able to quickly learn to use the software and compare the solutions of these problems on several different computing platforms, both classical and quantum, including quantum machines from Rigetti, D-Wave, and IonQ. So the big hurdle often faced by application developers with other QC approaches of learning completely new software algorithms, languages, and development kits is minimized. QCI has indicated that they software has solved large optimization problems that contain up to 110,000 variables with 8,000 constraints. The Los Alamos National Laboratory (LANL) tested the software and recently posted a paper on arXiv comparing the performance of the Qatalyst software (referred to as Mukai in the paper) with another QUBO solver available from D-Wave called Qbsolv and found that Qatalyst had better performance.

From qubits to Quantum Accelerator - The Full Stack Vision

Additional information about QCI’s announcement can be found in their announcement press release here. You can also view a previous articles we published about the Mukai software here and here. In addition, QCI has created a QikStart initiative for accelerating quantum use cases that we reported on here.

Majorana qubits for topological quantum computing Researchers are trying to store robust quantum information in Majorana particles and are generating quantum gates by exploiting the bizarre non-abelian statistics of Majorana zero modes bound to topological defects.

Soon after Enrico Fermi became a professor of physics at Italy’s University of Rome in 1927, Ettore Majorana joined his research group. Majorana’s colleagues described him as humble because he considered some of his work unexceptional. For example, Majorana correctly predicted in 1932 the existence of the neutron, which he dubbed a neutral proton, based on an atomic-structure experiment by Irène Joliot-Curie and Frédéric Joliot-Curie. Despite Fermi’s urging, Majorana didn’t write a paper. Later that year James Chadwick experimentally confirmed the neutron’s existence and was awarded the 1935 Nobel Prize in Physics for the discovery.

Nevertheless, Fermi thought highly of Majorana, as is captured in the following quote: “There are various categories of scientists, people of a secondary or tertiary standing, who do their best but do not go very far. There are also those of high standing, who come to discoveries of great importance, fundamental for the development of science. But then there are geniuses like Galileo and Newton. Well, Ettore was one of them.” Majorana only wrote nine papers, and the last one, about the now-eponymous fermions, was published in 1937 at Fermi’s insistence. A few months later, Majorana took a night boat to Palermo and was never seen again.

In that final article, Majorana presented an alternative representation of the relativistic Dirac equation in terms of real wave functions. The representation has profound consequences because a real wave function describes particles that are their own antiparticles, unlike electrons and positrons. Since particles and antiparticles have opposite charges, fermions in his new representation must have zero charge. Majorana postulated that the neutrino could be one of those exotic fermions.

Although physicists have observed neutrinos for more than 60 years, whether Majorana’s hypothesis is true remains unclear. For example, the discovery of neutrino oscillations, which earned Takaaki Kajita and Arthur McDonald the 2015 Nobel Prize in Physics, demonstrates that neutrinos have mass.

But the standard model requires that neutrinos be massless, so various possibilities have been hypothesized to explain the discrepancy. One answer could come from massive neutrinos that do not interact through the weak nuclear force. Such sterile neutrinos could be the particles that Majorana predicted. Whereas conclusive evidence for the existence of Majorana neutrinos remains elusive, researchers are now using Majorana’s idea for other applications, including exotic excitations in superconductors.

The next generation of Quantum Analyzers: SHFQA Launch Event

Majorana quasiparticles in superconductors

From the condensed-matter viewpoint, Majoranas are not elementary particles but rather emergent quasiparticles. Interestingly, the equation that describes quasiparticle excitations in superconductors has the same mathematical structure as the Majorana equation. The reason for the similarity arises from the underlying particle–hole symmetry in superconductors: Unlike quasiparticles in a metal, which have a well-defined charge, quasiparticles in a superconductor comprise coherent superpositions of electrons and holes. For the special zero-energy eigenmode, the electron and the hole, which each contribute half probability, form a quasiparticle. The operators describing the zero-energy particle–hole superpositions are invariant under charge conjugation, and zero-energy modes are therefore condensed-matter Majorana particles.

Particle–hole symmetry dictates that excitations in superconductors should occur in pairs at energies ±E. Therefore, zero-energy excitations are seemingly unreachable because they cannot emerge by any smooth deformation of the Hamiltonian, which would require that one of the solutions disappear. Rather, the only way to generate zero-energy excitations in superconductors is through a topological transition, a process that separates the phase of Majorana zero modes from the phase without them by closing and then reopening the superconducting gap (see the article by Nick Read, Physics Today, July 2012, page 38).

Majorana zero modes are located at topological defects, such as vortices, boundaries, and domain walls in topological superconductors. Remarkably, Majorana zero modes bound to defects do not obey fermion statistics. Unlike the original particles predicted by Majorana, the zero modes possess non-abelian exchange statistics, also known as non-abelian braiding, which makes them promising for applications in topological quantum computing, as detailed in box 1. Quasiparticles with non-abelian exchange statistics were first predicted in 1991 to occur in the filling factor ν = 5⁄2 of the fractional quantum Hall state. In 2000, researchers demonstrated that similar physics occur in superconductors with intrinsic p-wave pairing, an exotic form of superconductivity in which Cooper pairs bind through rare triplet-like pairing instead of the more standard singlet-like pairing in s-wave superconductors.2 Conventional s-wave pairing can be converted to p-wave pairing by combining the superconducting proximity effect in materials with strong spin–orbit interactions and an external magnetic field that breaks time-reversal symmetry.

Box 1. Non-abelian braiding

Quantum mechanics dictates that particles obey either Fermi–Dirac or Bose–Einstein statistics in three dimensions, which means that the wavefunction Ψ of a system of indistinguishable particles is necessarily bosonic or fermionic upon particle exchange. From that point of view, fermions and bosons are not exotic because exchanging them leaves the ground state invariant, up to a sign: Ψ → ±Ψ.

Two dimensions are richer. Now, the possibilities go beyond the fermionic or bosonic cases. A system can exhibit anyon statistics in which the wavefunction picks up an arbitrary phase under an exchange: Ψ → eiθ Ψ. Such behavior generalizes the boson and fermion cases, where the phases can only be θ = 0 or θ = π. Because the phase factors are ordinary commuting numbers, the order of successive exchanges doesn’t matter, and the anyon statistics are called abelian.

The weirdness starts in systems with a degenerate many-body ground state containing several quasiparticles. When quasiparticles are exchanged, the system goes from one ground state, Ψa, to another, MabΨb. Because the unitary transformations Mab that operate in the subspace of degenerate ground states are generally noncommuting, the anyonic statistics take a non-abelian form. The final state of the system, therefore, depends on the order of the exchange operations, similar to braiding cords in a necklace.

Using Majorana zero modes to store and manipulate quantum information is one case where non-abelian braiding statistics form the basis of topological quantum computation (see the article by Sankar Das Sarma, Michael Freedman, and Chetan Nayak, Physics Today, July 2006, page 32). Quantum computation in such a system also benefits from protection against environmental decoherence because of the nonlocal character of Majorana-based qubits.

The nanowire proposal

In 2010 two research groups made an elegant theoretical proposal, shown schematically in figure 1. If a semiconducting nanowire with strong spin–orbit coupling, such as indium arsenide or indium antimonide, is coupled to a standard s-wave superconductor, Majorana zero modes will emerge at both ends of the nanowire, provided that a magnetic field is applied parallel to it.3 The proposal realistically implements the paradigmatic one-dimensional model for p-wave superconductivity that was discussed in 2001 for the first time by Alexei Kitaev.4

Figure 1. (a) The nanowire proposal3 takes a nanowire of a semiconductor, such as indium arsenide or indium antimonide, that has strong spin–orbit coupling and places it in contact with an s-wave superconductor, such as aluminum, in the presence of an external magnetic field B. As in the original model for one-dimensional p-wave superconductors,4 the nanowire device experiences a topological nontrivial phase with exponentially decaying Majorana bound states, denoted γL, at both ends of the nanowire. (b) An actual device from Delft University of Technology includes various metallic gates for tuning it to the topological phase by adjusting the nanowire’s chemical potential. (Panel a adapted from ref. 3, R. M. Lutchyn, J. D. Sau, S. Das Sarma; panel b adapted from H. Zhang et al., Nature 556 74, 2018.)

The Majorana zero modes are localized at opposite ends of the wire and decay with position x as e−x/ξ, where ξ is the localization length. But together they form a highly delocalized fermion, which can be seen mathematically as a fermion operator that decomposes to two real, self-adjoint operators. The nonlocal fermion defines two parity states—the empty state and the full fermion one—that are degenerate at zero energy except for exponentially small corrections e−L/ξ, where L is the length of the wire. Those two states can be used to define a qubit. Because the states are stored nonlocally, the qubit is resilient against local perturbations from the environment.

To induce a closing and reopening of an energy gap in the nanowire platform, researchers exploit the competition among three effects. The first, the s-wave superconducting proximity effect, pairs electrons of opposite spin and opens a superconducting gap Δ at the Fermi level. In the second effect, an external magnetic field B generates a Zeeman energy EZ = gμBB/2—with g the nanowire’s Landé factor and μB the Bohr magneton—which tends to break Cooper pairs by aligning their electron spins and closing the gap. The third effect, spin–orbit coupling, negates the external magnetic field by preventing the spins from reaching full alignment.

The competition between the second and third effects creates regions in parameter space where the gap closes and reopens again. At low electron densities, the transition occurs when the Zeeman energy is of the same magnitude as the induced superconducting gap, and it can be reached either by increasing the magnetic field, as shown in figure 2, or by tuning the wire’s chemical potential. Apart from choosing semiconductors with a large spin–orbit coupling and good proximity effect with conventional superconductors, researchers need large g factors to induce a large Zeeman effect with moderate magnetic fields below the critical field of the superconductor. Materials such as the heavy-element semiconductors InAs and InSb have proven to be excellent choices.

Figure 2. Andreev reflections of electrons and holes to form Cooper pairs at the semiconducting– superconducting interface induce superconductivity in a nanowire. As a result, Majorana zero modes (flat red line) emerge in the energy spectrum as the external magnetic field increases. The Majoranas appear beyond some critical value of the external field (black dotted line) where the superconducting gap closes and reopens again, which signals a topological phase transition. Theory predicts that the emergent Majorana zero modes can be detected as a zero-bias anomaly in electrical conductance dI/dV. (Image by R. Aguado and L. P. Kouwenhoven.)

Topological superconductivity can also be engineered using similar ideas in alternative platforms. Some examples include chains of magnetic impurities above superconductors; proximitized 2D materials; and vortices in proximitized topological insulators such as quantum spin-Hall insulators, quantum anomalous-Hall insulators, and iron-based topological surface states.

Measuring Majoranas

At energies below the superconducting gap, an electron incident on a superconductor (S) from a normal conductor (N) can be reflected either as an electron or as a hole. Whereas the electron process is a standard, normal reflection, the hole process, known as Andreev reflection, is subtler because electrons are reflected as holes in the normal side while creating a Cooper pair in the superconducting side. In a standard NS junction, such Andreev processes are rare in the tunneling limit, and the conductance is small. But in a topological NS junction containing Majorana bound states, an incident electron is always reflected as a hole with unitary probability.

As a result of that resonant Andreev process, the electrical conductance G at zero voltage is expected to be perfectly quantized: G = 2e2/h, where e is the electron charge and h, Planck’s constant. The Andreev process underscores the particle–antiparticle duality of Majorana bound states: Because the electron and hole contribute equally to form a Majorana quasiparticle, the tunneling rates for electrons and holes should be equal. Therefore, researchers can use tunneling spectroscopy to directly detect a Majorana bound state as a zero-bias anomaly (ZBA). The differential conductance dI/dV, with I the current across the junction, is a function of the applied bias voltage V, and the ZBA should emerge as an increasing magnetic field induces a topological transition in the nanowire.

In 2012, researchers showed that the nanowire proposal could indeed be realized.5 A typical measurement from that experiment is illustrated in figure 3a, which shows conductance versus applied bias voltage and magnetic field. For intermediate values of the magnetic field, a clear ZBA emerges in the middle of the superconducting gap and is consistent with the existence of zero-energy Majorana bound states in the nanowire. Subsequent experiments showed similar results.

Noise is a qubit killer. This is the main challenge faced by quantum hardware makers and the reason why Microsoft decided to chase topological particles called Majoranas for their qubits, instead of the usual two-level systems. It is a “three-little-pigs” situation: you can choose the material that will give you a qubit faster, such as superconducting circuits, but you will build a fragile quantum processor. On the other end of the spectrum are the hard-to-build yet all-enduring topological qubits. The problem that topological-qubit advocates are facing now is that it seems that they are even harder to build than first thought. This creates a major setback to Microsoft’s main quantum hardware program, as discussed by Quantum Computing Report in a previous article.

Topological properties are believed to be impervious to noise because they are not easily affected by stray electromagnetic fields. As an analogy, think of a sailboat taking laps around a lake. While the changes in wind might make the path of the sailboat wiggle around its intended route, the number of laps that the boat takes is unaffected (unless you have catastrophic winds). In this analogy, the wiggly path would be the noise that affects traditional qubits, while the number of laps is the robust topological property. But topological states are not easy to synthesize – Majorana particles, for instance, do not occur naturally.

These Majorana particles were theorised to emerge in complex devices made from superconductors and special semiconducting nanowires. In 2018, a team led by Professor Leo Kouwenhoven from QuTech, in the Netherlands, developed ingenious fabrication techniques and brought together all the necessary ingredients (they had partial results before, but their main result only came in 2018). They then measured currents through these nanowires and concluded that they saw signs of these topological particles, kickstarting Microsoft’s global effort to make Majorana-based quantum computers. In a surprising twist, the authors of the original work decided now to retract the paper from Nature and publish extended data that reveals that their main conclusion was incorrect. Majoranas were not measured in those nanowires.

Why did it take two years for an extremely well-funded, globally-reaching scientific team to notice something was off? Firstly, it should be noted that the “extended data” published now is not new data acquired through more recent measurements – it is data that had been cut out from the original paper. This data was analysed by experts in the field and it contains enough information to discard the main conclusion in the original paper. If this information were made public before (as dictated by good scientific conduct), this issue could have been identified by trained eyes earlier.

But on top of that, the collective understanding of the physics behind these complex devices is in its infancy, and effects of unavoidable disorder in the nanowires are only now starting to be understood. That is the risk that Microsoft took for itself when deciding to embark on a journey to create quantum computers out of particles that had not yet been observed in laboratory.

Zurich Instruments talks - Scaling up quantum computing control systems to 100 qubits and beyond

This opened a Pandora’s box of reactions. The specialised media was fast to capitalise on the “Microsoft vs Google vs IBM vs Intel quantum race”, claiming that the result shows how far behind Microsoft is when compared, for instance, with Google’s 53 qubit superconducting chip. But anyone that has been paying close attention knows that Google is not the world leader in quantum computing – 53 qubits are an impressive display of engineering skills, but these are very faulty qubits that cannot be used for any real-life applications. While we wait for Google to show how its Sycamore processor performs when trying to perform quantum error corrections, it is hard to gauge whether Google really has something that could move forward as a viable universal quantum processor.

On the topic of quantum error correction, that could well be where other technologies stall and Microsoft’s Majoranas catch up. One of the theoretical masterminds behind the idea of topological qubits and co-author in the retracted paper, Professor Sankar Das Sarma from University of Maryland fired on Twitter that the “…idea of using surface codes to do error correction is in some crude sense trying to produce approximate topological qubits…”. Indeed, the surface code is largely based on the ideas from 2016 Nobel laureate Duncan Haldane. By organising qubits in a two-dimensional array and repetitively performing operations and measurements, one tries to force the faulty qubits into collectively maintaining bits of information that are protected from the local stray fields acting on each separate qubit. This is, once again, leveraging the idea that global properties (like the number of laps of a sailboat around a lake) are more resistant than local properties (such as the position of the sailboat at any given moment, as affected by winds and waves).

Professor Das Sarma goes on about the shortcomings of the usual two-level-system approach in his Twitter account (called Condensed Matter Theory Center after the UMD-based institution that he directs). He says most of the mediatic noise regarding this episode is the result of “…total ignorance of how a quantum computer works—you must have LOGICAL qubits which NOBODY is even close to having”. This is arguably incorrect – the group of Professor Christopher Monroe from the same University of Maryland posted to an online preprint repository a manuscript showing a logical qubit based on ion traps with fault-tolerant operation levels (as covered by Quantum Computing Report here).

One of the key findings by Professor Monroe is that a significant improvement is achieved when, unlike in the surface code, long range coupling between qubits is attained. The surface code assumes that a qubit can only be entangled with its immediate neighbours, but some technologies allow for qubits to be moved around or even to achieve pairwise interactions mediated by the collective movement of all qubits (which is the case for ions in a trap). Hard to believe that Professor Das Sarma is unaware of the work by Professor Monroe – it is unclear whether he thinks there is something wrong with Professor Monroe’s conclusions or if he is (perhaps ironically) waiting for the manuscript to be published in a peer-reviewed journal.

Declaring the topological qubits dead prematurely might be a mistake. But undoubtedly this retraction reveals how ignorant we still are about these ethereal topological particles and how Microsoft is not ready to firmly progress in harvesting them for technological applications. Scientists are not nearly ready to pass this baton to engineers.

It’s a tale oft told in physics: researchers are, yet again, excited about a phenomenon that may or may not exist. This time, it’s Majorana fermions—weird objects that act as their own antiparticles. Some condensed matter physicists think they’ve seen these elusive beasts, but others aren’t so sure. Either way, Microsoft has put out a bounty for the Majoranas and hopes one day to harness them for quantum computing.

While particle physicists also study a version of the Majorana fermion (neutrinos might be of this ilk), the ones of interest to quantum computing are quasiparticles—many electrons acting collectively in materials to mimic particles. In 2012, researchers at the Delft University of Technology in the Netherlands first reported experimental evidence of the quasiparticle in a semiconductor nanowire attached to a superconductor. Subsequent measurements by several other research groups also match theoretical predictions, although it is still possible that the signals could come from some other interaction in the nanowire.

Topological Defect Networks for Fractons of all Types (Dominic Williamson)

Trajectories of Majorana quasiparticles

Trajectories of Majorana quasiparticles can be arranged to be topologically distinct and might form the basis for robust qubits in quantum computing.

Because of these tantalizing experimental results, researchers think that someone will conclusively nail down the quasiparticle soon. "It looks like a dog, and it walks like a dog," says Mihir Pendharkar, a Microsoft-funded graduate student at the University of California, Santa Barbara (UCSB), who presented his research at the 2018 March Meeting. But still, he adds, it might not be a dog.

Quantum computing researchers want to use a specific kind of Majorana fermion, known as a Majorana zero mode, as a qubit. "In classical terms, a Majorana zero mode is like half an electron," says Pendharkar. Theory, along with supporting experiments, suggests that these half-electron quasiparticles can exist at the ends of one-dimensional semiconducting wires that are attached to a superconductor.

One predicted property of these quasiparticles is that they have a "memory" of how they’ve been moved around. For example, if you swap two quasiparticles’ positions on a nanowire, "they would remember whether they had been moved clockwise or counterclockwise around each other," says Pendharkar.

You can store information in a pair of quasiparticles by exploiting this property, says Christina Knapp, a graduate student at UCSB who also presented in the same session. For example, in a simplistic encoding scheme, moving one quasiparticle clockwise with respect to the other could correspond to a 1, while moving counterclockwise could correspond to a 0. To read out the qubit, in principle, you would collide the two half-electron quasiparticles together on the nanowire and measure the outcome, which would yield a different signal depending on whether they were in a 0, 1, or a superposition state.

Researchers predict that these quasiparticles will be more robust at holding information than the qubits that Google and IBM are currently building. The latter are error-prone because of "local" noise, such as ambient electromagnetic fields. Consequently, thousands of superconducting qubits are required to lower the error rate enough to perform a logical operation. Google, the current record-holder, has put only 72 of these qubits together. This constrains researchers to design algorithms that are still useful despite inevitable errors.

Zurich Instruments - Qubit control for 100 qubits and more

Unlike Google’s computer, which stores information in a single localized object, a Majorana-based qubit would encode a single bit of information in multiple quasiparticles. According to theory, this type of quantum information should be much less likely to go bad. The quasiparticle still "remembers" whether it has been moved clockwise or counterclockwise with respect to its twin, even if you move it around on a nanowire. The information is also immune to local environmental noise.

The researchers liken these qubits to a knot on a shoestring, so that how the knot is tied indicates the information stored. "The knot doesn’t really change if you tug at the part of the shoestring," says Knapp. "It doesn’t care about little changes in the system."

To be clear, no one is tying physical knots in a nanowire—but you can mathematically visualize the timeline of these quasiparticles as you swap their positions as knots or braids. These knots are known as topologically protected states; hence, the proposed quantum computers built with Majorana fermions are known as topological quantum computers.

Theorists have already begun designing solid-state qubits using the hypothesized quasiparticle, although Pendharkar and his adviser, physicist Chris Palmstrøm of UCSB, say that it will likely be decades before anyone makes a topological qubit. "Right now, we don’t even know if the fundamental thing actually exists," says Palmstrøm. To conclude once and for all that they’ve created Majorana zero modes, Pendharkar says, a research group must demonstrate that a pair of them yields the predicted properties when swapped.

However, Palmstrøm’s group is already working to design a chip-based architecture for the expected qubits. They have designed a layered chip made primarily of indium-based materials containing sheets of electrons that interact only two-dimensionally. They can then etch those sheets into one-dimensional "wires" that they can couple to a superconductor to create the Majorana edge modes. Etching is a much more feasible—and scalable—manufacturing process than laying single nanowires in parallel, says Pendharkar.

Pendharkar and Palmstrøm are careful not to over-promise their device. After all, unlike Google, IBM, and Intel’s quantum computers, theirs doesn’t exist yet. "There are different bottlenecks for different technologies," says Palmstrøm. "We’re at the bottleneck where we don’t even know whether the technology works."

But other quantum computing architectures could hit a different bottleneck, Palmstrøm says: They’ll be difficult to expand into the thousand and million qubit devices that will ultimately be broadly useful to society. Because a topological qubit doesn’t need the same type of error correction as superconducting qubits, it should be easier to make a working thousand-qubit quantum computer out of topological qubits. A topological qubit should be a fundamentally better piece of hardware—they just have to figure out how to make it.

Microsoft has been working on a qubit technology called a topological qubit that it expects will deliver benefits from quantum computing technology that today are mostly just a promise. After spending five years figuring out the complicated hardware of topological qubits, the company is almost ready to put them to use, said Krysta Svore, general manager of Microsoft's quantum computing software work.

"We've really spent the recent few years developing that technology," Svore said Thursday after a talk at the IEEE International Conference on Rebooting Computing. "We believe we're very close to having that."

The company claims it is leading the field in a type of quantum computing called a topological qubit, which it claims is far less error-prone than rival qubit systems.

“We are very close to figuring out a topological qubit. We are working on the cryogenic process to control it, and we are working on 3D nano printing,” said Todd Holmdahl, Microsoft corporate vice-president in charge of quantum computing.

“Competitors will need to connect a million qubits, compared with 1,000 in our quantum computing machine. It is about quality.”

Why Topological qubits are better

The reason Holmdahl believes Microsoft has the edge in quantum computing is because its researchers are close to cracking what is known as a topological qubit. It is also developing a system architecture at the Niels Bohr Institute in Copenhagen, where qubits operate at just above absolute zero, at 30 millikelvin. The extreme cold minimises interference. Microsoft has also created a high-level language Q# for Visual Studio, plus it is working on a quantum computer simulator, which will run locally on a PC or on Azure.

Full stack ahead: Pioneering quantum hardware allows for controlling up to thousands of qubits at cryogenic temperatures



The topological qubit is the centrepiece of Microsoft’s efforts in quantum computing. Work began two decades ago in Microsoft’s theoretical research centre, when mathematician Michael Freedman joined. Freedman is renowned for his research in a field of mathematics known as topology.

According to Microsoft, Freedman began a push into quantum computing 12 years ago, backed by the company’s chief research and strategy officer, Craig Mundie.

At the time, Mundie said quantum computing was in a bit of a doldrums. Although physicists had been talking about the possibility of building quantum computers for years, they were struggling to create a working qubit with high enough fidelity to be useful in building a working computer.

According to Holmdahl, physical qubits are error-prone so it requires roughly 10,000 of them to make one “logical” qubit – which is a qubit reliable enough for any truly useful computation.

Quantum computing researchers have found that if a qubit is disrupted, it will “decohere”, which means it stops being in a physical state where it can be used for computation.

According to Microsoft, Freedman had been exploring the idea that topological qubits are more robust because their topological properties potentially make them more stable and provide more innate error protection.

Holmdahl said a topological qubit would have far fewer errors, meaning more of its processing power could be used for solving problems rather than correcting errors. “The more qubits you have, the more errors you have,” he said. This, in turn, means that more qubits must be connected together.

According to Holmdahl, there is a theoretical limit to how much a quantum computer can scale, due to the complexity of networking all the qubits together and the error handling. “We are taking a different approach. Our error rate is three to four orders of magnitude better

Zurich Instruments QCCS Quantum Computing Control System

Key Features

  • Scalable design: new inputs and outputs can be added at any time, and a high channel density and consistent performance are guaranteed for all setup sizes.
  • Productivity-boosting software: LabOne efficiently connects high-level quantum algorithms with the analog signals from the quantum device.
  • Hardware specifications that match the application: low noise, high resolution, and large bandwidth.
  • A thought-through and tested systems approach: precise synchronization, reliable operation.
  • Feedback operation: fast data propagation across the system, powerful decoding capability.


Zurich Instruments talks - IEEE Quantum Week Workshop - part 1/3


Zurich Instruments introduced the first commercial Quantum Computing Control System (QCCS), designed to control more than 100 superconducting and spin qubits. Each component of the QCCS is conceived to play a specific role in qubit control, readout and feedback, and operates in a fully synchronized manner with the other parts of the system. LabOne®, the Zurich Instruments control software, enables fast access to qubit data and facilitates the integration into higher-level software frameworks.

Zurich Instruments talks - IEEE Quantum Week Workshop - part 2/3

The Zurich Instruments QCCS supports researchers and engineers by allowing them to focus on the development of quantum processors and other elements of the quantum stack while benefiting from the most advanced classical control electronics and software.

Efficient workflows, tailored specifications and feature sets, and a high degree of reliability are the characteristics most valued by our customers.

Zurich Instruments talks - IEEE Quantum Week Workshop - part 3/3

The scientific achievements already accomplished with the QCCS (see below for a list of publications) are a testimony to our close engagement with some of the most ambitious research groups in this area. The recent launch of the SHFQA Quantum Analyzer introduces the second generation of QCCS products, which operate directly at qubit frequencies, offer higher density and lower cost per qubit, and provide new features that take into account the most recent developments in quantum computing.

More Information:

https://en.wikipedia.org/wiki/Quadratic_unconstrained_binary_optimization

https://www.quantumcomputinginc.com/

https://arxiv.org/abs/2102.01225

https://quantumcomputingreport.com/news-2020/#QCIMUKAI

https://quantumcomputingreport.com/quantum-computing-inc-announces-new-support-for-cloud-based-quantum-computers-with-their-mukai-software/

https://quantumcomputingreport.com/news/#QCIQIKSTART

https://www.zhinst.com/europe/en/quantum-computing-systems/qccs?msclkid=821685a55de21cca3969e58a2427cb0f

https://escholarship.org/uc/item/04305656

https://www.qutube.nl/quantum-computer-12/topological-quantum-computing-majorana-fermions-and-where-to-find-them

https://www.hpcwire.com/2020/08/19/intel-connects-the-quantum-dots-in-accelerating-quantum-computing-effort/

https://arxiv.org/abs/2102.01225

https://www.zhinst.com/europe/en/quantum-computing-systems/qccs?msclkid=821685a55de21cca3969e58a2427cb0f

https://www.aps.org/publications/apsnews/201804/hunt.cfm

https://physicstoday.scitation.org/doi/10.1063/PT.3.4499#:~:text=Majorana%20qubits%20for%20topological%20quantum%20computing%20Researchers%20are,of%20Majorana%20zero%20modes%20bound%20to%20topological%20defects.

https://www.qutube.nl/quantum-computer-12/topological-quantum-computing-majorana-fermions-and-where-to-find-them

https://arxiv.org/abs/2004.02124

https://escholarship.org/uc/item/04305656

https://www.hpcwire.com/2021/01/28/microsoft-develops-cryo-controller-chip-gooseberry-for-quantum-computing/






























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