Quantum computing: super charging innovation
Quantum computing (QC) is a rapidly growing technology which leverages the laws of quantum mechanics to solve problems that are too complex for classical computers. Quantum computing has already begun to transform some fields, and there is significant ongoing work in developing the area.
Unprecedented precision and accuracy
Scaled, personal quantum computers that can solve hard problems which are out of reach of even the most powerful supercomputers are still years away. However, there already exist what are termed noisy intermediate-scale quantum (nisq) processors. Already these are helping to transform areas such as pharmaceutical and material science research. For instance, QC promises the possibility of modelling molecules, polymers and solids with unprecedented precision and accuracy, thus predicting molecular designs to achieve specific tasks before actually synthesising said molecules.
QC: the ultimate number cruncher
In this data era QC has the potential to create disruption at scale. Sectors, such as financial services, which are heavily reliant on statistics, will benefit enormously from quantum computing; particularly calculating data and computation intensive markers such as market risk and credit risk. A tier 1 bank taking a position on a financial instrument has, for instance, millions of such positions fed daily into a risk engine, and re-repriced using market data. These risks are then calculated by applying known risk factors to the re-priced positions. The correlations between the variables at play makes it hard for classical computers and simulations to accurately assess the risks, which is why banks often choose to approximate prices, making the risk by extension an approximation. QC would be an upgrade as it has two key advantages in modelling market risk:
- risk computation can be more accurate as correlation across variables can be built into the models;
- risks can be computed in near real time, which is a boon for handling intra-day stress scenarios.
In asset management, portfolio managers regularly perform portfolio rebalancing: making investment decisions and building portfolios of stocks, bonds, and commodities. Currently in portfolio optimisation one often uses statistical factor models based on a machine learning algorithm called Principal Component Analysis (PCA) to model the returns on portfolios and the model profit and loss of cash flows. PCA is highly computationally expensive, even prohibitively so in some cases. A quantum PCA (qPCA) algorithm greatly reduces the computational cost and would therefore open new vistas in portfolio optimisation. Given the huge number of financial applications of PCA (which include term structures of interest rates, forwards, futures, and volatility for example), such qPCA is sure to play a key role in transforming the financial industry.
Financial services constitute just one sector where QC could help overcome longstanding limitations.
Patent figures back QC innovation
The sheer number of areas where QC can be deployed has resulted in a rise in investment and research into the emerging technology. This has resulted in an increase in the number of patent applications involving quantum computation: the EPO recently reported that the number of such applications has grown by roughly 1060% in the decade from 2011 to 2021 compared to 200% for general technology applications over the same period.
The challenge of scaling up accuracy
One of the current hurdles blocking the path to scalable fault-tolerant quantum computers is protecting quantum information from errors. Quantum computers are built on qubits that are sensitive to the environment surrounding them and are unable to maintain their state for extended periods of time. With the quantum system in contact with a much larger, noisier environment, errors that corrupt the quantum information are unavoidable. While these errors can be minimised, they can never be truly eliminated and so the challenge becomes one of correcting the errors.
On classical computers, error correction is straightforward: one simply keeps several copies of each bit and either stores the copies or sends them over a noisy channel. A random error flipping a 1 to 0 or vice versa during storage or transmission can then simply be corrected via majority rule by checking the bits post storage or transmission (if 9 of the 10 copies are 1s, the bit is taken to be a 1).
Quantum error correction is trickier for several reasons. First the no-cloning theorem precludes the copying of an arbitrary quantum state, and so classical error correction schemes cannot be used. Second, unlike errors in classical bits (which are discrete: a bit goes wrong from 1 to 0 or vice versa), quantum errors are continuous, and any given state is a superposition of states. And third, any measurement destroys the quantum information contained in a state. In essence, the problem becomes one of determining if some qubits being stored or transmitted have changed without actually looking at the qubits themselves.
There are several quantum error correction (QEC) schemes, but fundamentally quantum error correction codes can be seen as the act of mapping a number k of qubits into another, larger number n of qubits. The k qubits are the ‘logical qubits’ which perform the computation and must be protected from error, the remaining n-k qubits enable one to store the logical qubits in a redundant fashion. Several terms are used to refer to these extra qubits, including auxiliary, ancillary, or even flag qubits.
While quantum computing (QC) is the most often mentioned sector when talking about quantum information processing (QIP), QIP encompasses the representation, storing, processing, and accessing of information by quantum mechanical systems, and is therefore not limited to QC. Beyond QC, quantum information processing includes quantum key distribution, quantum teleportation, quantum lithography, quantum memories, and quantum communication.
Real-life implementation of a QEC scheme
An example of a quantum processor using auxiliary and flag qubits alongside logical qubits can be seen in the use of diamond crystals, including a nitrogen vacancy (NV) centre. A diamond NV centre is a colour centre formed when a carbon atom in the diamond crystal is intentionally or otherwise replaced by a nitrogen atom, next to another lattice site that is itself missing a carbon atom. Electrons trapped in the NV centre form spin states which are optically accessible. In this paper, the authors used the nuclear spins of 5 carbon nuclei in the diamond crystal as the logical qubits, the spin of an electron trapped in the empty lattice site at the NV centre as an auxiliary qubit for stabilizer measurements, and the nuclear spin of the nitrogen atom at the NV centre as a flag qubit to realise the well-known five-qubit quantum error-correction code.
Diamond NV centres have been used in other areas of QIP, having for instance been leveraged to demonstrate quantum teleportation, quantum entanglement, multi-node quantum network, and quantum memory.
Companies working with diamond quantum computing include five companies which were the subject of a quantuminsider article. These are venture-backed Australian-German quantum hardware company quantum brilliance, the Massachusetts-based startup Quantum Dimond Tech Inc., Ulm university Institute for Quantum Optics spin-off Diatope, synthetic diamond maker Element Six, and Ulm university Institute of Theoretical Physics and Quantum Optics spin-off NVISION.
Patenting QC innovation
Having spent the time, money, and human resources to develop quantum computing technologies, in order to successfully protect it, commercialise it and build on it, securing important intellectual property rights is crucial for companies or individuals. A key protection is provided by patents.
Patent applications in this field however tend to face a few hurdles. One notable hurdle consists of objections raised by examiners that the invention falls in one or more of the categories of subject matter which are not considered patentable inventions. If the application falls into this category, it is because they are often considered a mathematical method or a computer program as such, which are excluded from patentability.
When filing a patent application it can be difficult to ascertain whether it relates to excluded subject matter, but obtaining patents will be crucial for companies or individuals developing quantum computing technologies.
Barker Brettell has a dedicated Computing & Software sector with a large team of patent attorneys experienced in quantum information processing.
If you would like any further information or assistance on IP matters in this field, please do not hesitate to contact the author, or your usual Barker Brettell attorney.
