Quantum Computing seeks to harness massive parallelism in computation by examining many entangled quantum states simultaneously rather than individual classical states sequentially.
It is anticipated there are a diverse range of applications particularly in previously unsolvable or lengthy computational problems. This is of particular importance for optimization, unstructured search, materials simulation and logistics.
In the near future quantum annealers, simulators and so called Noisy Intermediate Scale Quantum machines (NISQ) with fifty to a few hundred qubits are likely to prove both useful and commercially viable. Whether they will demonstrate quantum supremacy as a general-purpose machine or specific application functionality compared to classical equivalents is yet to be determined.
Many of the leading candidate qubit contenders require a low temperature environment for operation and to screen out noise sources. These noise sources both on and off chip cause decoherence and increased error rates. Fully fault tolerant quantum computers are expected to require a million qubits or more and this remains some decades in the future. In the meantime, low temperature performance and error avoidance is critical to deliver a useful and usable NISQ machine.
The energy level separation of the qubit 1’s and 0’s at the low temperatures required for operation are typically in the GHz frequency range, with carefully shaped nano second pulses required to control the computational operations. Maintaining precision and accuracy of pulse shape is challenging. Scaling engineering solutions to ensure low noise, wide band attenuated input lines and low impedance, low noise amplified output lines is required. Low noise performance, modularity and long-term reliability are features of our enhanced cabling solutions for quantum computation.
As with materials simulation; drug discovery, protein folding, catalysis and battery modelling are likely candidate problems to be tackled using quantum computing. Rather than simulating materials using qubits, modelling utilises computational techniques that lend themselves to quantum computing over classical computing to extend the range of species that can be investigated for both the speed and accuracy of the computation.
Many classes of problems cannot be solved analytically. These
classes of problems are widespread in logistics, medicine and finance. As the number of variables in a problem grows, the serial nature of classical computing stalls. A 270 variable problem already outstrips the number of atoms in the universe. The parallelism of quantum computing allows multi-variable optimization that could impact applications such as flight scheduling, traffic flow and cancer radiotherapy treatment.
Relational database searching with structured datasets is a requirement of Big Data applications from the high street to CERN.
Unstructured datasets such as text, multimedia and language
can prove difficult to search or impossible depending on its size.
Quantum computing offers the possibility of optimal unstructured
search techniques using Grover’s Algorithm. Security and drug
discovery are candidate areas for development.
In the absence of quantum cryptography, quantum computers
could pose a threat to encryption mechanisms. RSA-2048 encryption would go from many millions of years to break on a classical machine to days on a quantum computer with 2000 qubits and GHz clocking speed. To counter this threat, quantum technologies are also being employed to establish noncomputational security protocols, that will remain secure despite progress in quantum computation.
As part of the European Quantum Flagship QMiCS programme, Oxford Instruments is a key partner supporting the development of
a quantum microwave local area network. This architecture will enable quantum communication protocols such as teleportation
between two superconducting quantum nodes. This approach has future applications for distributed quantum computing and radar-style quantum sensing with microwaves.