Public Funding for Duality Quantum Photonics Ltd

Individual digital technologies that compute, communicate, image, and sense, deliver an altogether more powerful service when they are connected and work together. Similarly, a more comprehensive set of capabilities will be realised if we can coherently network the different quantum technologies that are individually progressing toward faster computing, securer communications, and higher precision sensing. Additionally, to meet their full potential, quantum computers must be designed and constructed as an architecture of modules that are coherently connected. A coherently connected network of quantum computers, quantum sensors, and quantum communication modules will provide transformative benefits for society. In healthcare, a network for quantum devices could help individuals privately monitor their health while enabling secure, efficient and personalised drug design. In clean energy, massive data from fusion reactors could be rapidly monitored to maintain energy availability, while in-parallel real-time modelling of their nuclear physics could increase energy generation. Turning this vision into a reality requires technology to coherently connect hardware modules that typically process quantum information at extremely low temperatures, inside a cryostat. This includes the _quantum repeater_ modules that will enable large area quantum networks. However, robustly inputting/outputting quantum information to/from a cryostat such that it can be connected to other cryostats with high fidelity, is challenging. Additionally, inputting/outputting relatively large sets of classical control and readout data is difficult with standard thermally conductive electronic wiring, which interfaces the inside of a cryostat to the outside world. The technology being developed by Duality Quantum Photonics (DQP) offers a powerful solution to these challenges. In this project, DQP will develop its NEXUS Quantum Photonics (NEXUS-QP) chipset to coherently connect different cryostats. NEXUS-QP will co-integrate components to generate, process, and detect quantum states of light, to generate and detect co-propagating classical control laser light, to perform fast photonic switching, and to support low-loss optical fibre connections for optical access to cryostats reducing the thermal load. NEXUS-QP will enable the exchange of quantum information and classical control signals among a network of cryostats that are co-located (same room/building) or geographically distributed (e.g. different cities). Working with leading national and international technology companies to help guide product development, DQP will use its UK fabrication site to manufacture components and systems in photonic chips that are suitable for mass scaling and will ultimately help deliver a national and global quantum network.

Integrated optical circuits are a cutting edge method of trapping and guiding light in millimetre sized chips that will be used to power the next generation of information and communication technologies. Optical chips are already ubiquitous in data centres that power the internet and enable an ever more interconnected digital society. Quantum technologies using single particles of light - photons - facilitate secure communications, enhanced environmental sensors, and ultra-fast computers. Since information is carried on individual photons, losing them represents an irretrievable loss of information. Switches that retain as much of the light as possible are a fundamental building block for all of these applications. Photons interact weakly and are mostly undisturbed by the environment at room temperature. The detectors used to measure photons, however, must be operated cryogenically. The next generation of scalable quantum photonics must solve the challenge of operating the optical chips, and switching light in the same environment as the detectors. The largest scale quantum information experiments to date have used switches that operate by creating a large temperature change in the material. These switches, however, cannot be operated en masse at cryogenic temperatures due to limited cooling power in cryostats. This roadblock can be overcome by using a different switch where an electric field is applied across the switch and facilitating active control with minimal heat dissipation. The H3Lo-QP (High-IO High-transmission High-voltage Low-temperature Quantum Photonics) project will address important challenges of designing, fabricating, post-processing, and developing the system-level architecture for cryogenically operating a large number of low heat-dissipation integrated photonics switches necessary for the next generation of optical quantum technologies. We will investigate the feasibility of two types of switches by post-processing silicon chips made using mass-manufacturing techniques, and by developing fabrication techniques to deliver optical switches in a cutting edge integrated photonics platform: thin-film lithium niobate. The architecture for the control electronics will be developed, enabling a large number of device switches to be rapidly reconfigured. We will package fabricated optical chips using special techniques where a polymer optical wire directly connects the silicon/lithium niobate chips to optical fibres used to transmit light in and out of the cryogenic environment. Finally, we will demonstrate a large-scale device operating at cryogenic temperatures using the electro-optic switches developed in this project. This work will ensure that photonic quantum technologies will flourish and with far reaching impacts across science, academia, industry, and society.

The need for secure, clean, reliable, and sustainable sources of energy has grown in both importance and urgency. Part of the solution to meet these needs is nuclear fusion. While experimental progress in fusion has evidenced its viability, a range of engineering challenges must be met and coordinated before fusion reactors can operate reliably for long periods, and to deliver a net energy gain. Among these challenges is the processing of large real-time data sets from cryogenically cooled superconducting magnetic coils that maintain the plasma from which energy is released. Superconductivity can break down if a hotspot forms in part of a coil; the subsequent rapid warming and loss of plasma confinement results in damage and downtime. To prevent this, hotspots must be rapidly located so individual coils can be protected. Hotspots can be detected using a process called optical frequency domain reflectometry (OFDR). Laser light is sent down an optical fibre that is co-wound with a coil; a hotspot affects some of the light reflected back along the fibre; its detection allows the hotspots to be located. However, precisely locating hotspots in multiple coils within fractions of a second, requires the rapid processing of vast amounts of data. This information processing challenge is a barrier to clean energy from fusion. As information processing has matured beyond the central processing unit (CPU), a variety of tailored control and computational hardware has emerged including graphics processing units (GPUs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), Neural Networks (NNs) and quantum computing. Each of these sacrifices a general purpose (classical) computing capability to enable much greater power for particular information processing tasks. The people at Duality Quantum Photonics have pioneered integrated photonics as a platform for both Optical Neural Nets (ONNs) and quantum information processing. Quantum Optical Neural Nets (QONNs), the combination of these two paradigms, in integrated photonics, provide an appealing platform for a range of information processing tasks, including the processing of real-time data required to sustain fusion energy generation. In this project, Duality will partner with the private fusion energy company Tokamak Energy, and with the UK Atomic Energy Authority, to design and fabricate QONNs in photonic chips to process OFDR data for the rapid location of hotspots. The project will demonstrate how quantum computing can help tackle some of the information processing challenges that stand in the way of net gain fusion energy.

Achieving Net Zero emissions is a critical and necessary step towards mitigating climate change and an essential component of a comprehensive strategy to limit global warming; meanwhile, the need for secure and reliable sources of energy has grown in importance. Nuclear fusion has the potential to be carbon-neutral and produce sustainable energy without significant greenhouse gas emissions. But although experimental progress increasingly evidences the viability of fusion, a range of engineering challenges must be met before fusion reactors can operate reliably for long periods, to deliver a net energy gain. Among these challenges is preventing disruptions of the plasma from which energy is released. In addition to reducing efficiency, disruption events can damage fusion reactors and cause significant power plant downtime. However the behaviour of a fusion plasma is complex and large data sets generated from diagnostics must be rapidly processed, making it very challenging to predict disruption events in sufficient time to allow mitigating action. Specialised computational hardware can be tailored to implement machine learning and provide real time data analysis. Popular special purpose processors include graphics processing units (GPUs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and Optical Neural Nets (ONNs). Each of these sacrifices a general purpose computing capability to enable much greater power for particular information processing tasks. More recently, quantum technologies have attracted attention for their ability to deliver exponential speedups for certain information processing tasks. As a platform for supporting both quantum information processing and machine learning, integrated photonics is versatile, robust, and manufacturable. In this project Duality Quantum Photonics (DQP) will develop Quantum Photonic Neural Nets (QPNNs) to rapidly analyse the large data sets from plasma diagnostics and predict disruption events. DQP will design and fabricate QPNNs in chips using new materials that are best suited to photonic quantum information processing and are resilient to radiation and large magnetic fields. DQP's QPNNs will be developed with advice from experts within the UK Atomic Energy Agency. QPNNs can ultimately be produced at scale so that large numbers of fusion reactor components can be individually monitored and controlled in real time. DQP have brought together several cutting edge approaches to photonic chip manufacture, quantum information processing and AI. Bringing this powerful set of technologies to bear on the grand engineering challenge of delivering net positive fusion energy opens an exciting new era of science and technology, and clean sustainable energy for all our futures.

Achieving Net Zero emissions is a critical and necessary step towards mitigating climate change and an essential component of a comprehensive strategy to limit global warming; meanwhile, the need for secure and reliable sources of energy has grown in importance. Nuclear fusion has the potential to be carbon-neutral and produce sustainable energy without significant greenhouse gas emissions. But although experimental progress increasingly evidences the viability of fusion, a range of engineering challenges must be met before fusion reactors can operate reliably for long periods, to deliver a net energy gain. Among these challenges is preventing disruptions of the plasma from which energy is released. In addition to reducing efficiency, disruption events can damage fusion reactors and cause significant power plant downtime. However the behaviour of a fusion plasma is complex and large data sets generated from diagnostics must be rapidly processed, making it very challenging to predict disruption events in sufficient time to allow mitigating action. Specialised computational hardware can be tailored to implement machine learning and provide real time data analysis. Popular special purpose processors include graphics processing units (GPUs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and Optical Neural Nets (ONNs). Each of these sacrifices a general purpose computing capability to enable much greater power for particular information processing tasks. More recently, quantum technologies have attracted attention for their ability to deliver exponential speedups for certain information processing tasks. As a platform for supporting both quantum information processing and machine learning, integrated photonics is versatile, robust, and manufacturable. In this project Duality Quantum Photonics (DQP) will develop Quantum Photonic Neural Nets (QPNNs) to rapidly analyse the large data sets from plasma diagnostics and predict disruption events. DQP will design and fabricate QPNNs in chips using new materials that are best suited to photonic quantum information processing and are resilient to radiation and large magnetic fields. DQP's QPNNs will be developed with advice from experts within the UK Atomic Energy Agency. QPNNs can ultimately be produced at scale so that large numbers of fusion reactor components can be individually monitored and controlled in real time. DQP have brought together several cutting edge approaches to photonic chip manufacture, quantum information processing and AI. Bringing this powerful set of technologies to bear on the grand engineering challenge of delivering net positive fusion energy opens an exciting new era of science and technology, and clean sustainable energy for all our futures.

Quantum information science is the discipline that studies the information present in quantum systems. Numerous new technological applications in communication and computing can be unlocked thanks to purely quantum phenomena. As opposed to classical information bits, which can be either 0s and 1s, the quantum bits (or qubits), are associated to the state of quantum objects. Because of the quantum superposition principle, the qubits can be 0s, 1s, or coherent superposition of both, thus giving access to an extraordinarily richer alphabet. Quantum information science also exploits quantum entanglement, i.e. strong correlation between quantum objects, as a resource for fast and secure quantum communication in the development of the so-called quantum networks. Thanks to the no-cloning theorem, quantum networks can detect whether shared cryptographic keys have been intercepted and/or compromised by the presence of an eavesdropper. At the same time, they prove prone to photonic loss because the no-cloning theorem forbids amplification of quantum states. Single- and two-photon sources and quantum memories are key components of quantum networks, as they allow the generation of quantum states encoded on photons and their long-term storage. The implementation of such devices on small chips has the potential to replicate the revolution of modern electronic miniaturization. The integration of quantum devices can in fact enhance the light-matter interaction and provide high-level scalability and intrinsic mechanical stability. However, current realizations are limited either by the low extraction/insertion efficiencies of the generated/stored photons in free-space or by the complexity of the setups which hinders the scalability potential. This proposal tackles the challenge of implementing **efficient and robust interconnects** between integrated quantum photonics devices and optical fibres with the aims of 1) **minimizing the optical losses** throughout the networks and 2) **making them scalable beyond simple proof-of-principle demonstrations**. The effort involves two quantum technology companies, Duality Quantum Photonics (DQP, UK) and OptoElectronic Component (OEC, Canada) and two research groups at the Institut National de la Recherche Scientifique (INRS, Canada) and Heriot-Watt University (HWU, UK). Such consortium gathers world-leading partners in integrated quantum photonics, with widely recognized expertise in all steps of the development: design and fabrication of integrated circuits and mode conversion structures (DQP), implementation of integrated quantum devices, as single photon sources (HWU), sources of photonic entanglement (INRS), and quantum memories (HWU), and efficient detection of quantum states of light (OEC). The project outcomes will provide a significant contribution towards the development of quantum secure communication networks.

Without an operating system, computers would be much less useful. Before the invention of operating systems, computers could only run one calculation at a time. All tasks had to be scheduled by hand. Operating systems automate the scheduling of tasks and make sure that resources such as memory and disk space are allocated properly. Because operating systems simplify computers, everyone can handle them and benefit from them. Quantum computers are a new type of powerful computer. Big and high-quality quantum computers can outperform conventional computers at specific tasks, such as predicting the properties of a drug. Currently, it is difficult for users to interact with quantum computers because there is no good operating system. The systems that exist don't schedule tasks optimally and cannot perform calculations quickly. Building this operating system is difficult -- many have tried and no solutions have worked. We have invented an operating system to overcome this technical challenge: NISQ.OS. While competitors present quantum computers as a "black box", NISQ.OS exposes all its different elements. Many of them look far more familiar than you might think. Quantum computers consist of a quantum processing unit, which contains the qubits, a couple of layers of special-purpose chips that control the qubits, and a conventional computer for overall control. By providing access to all these layers of the "quantum computing stack", we give the user the power to schedule tasks in an optimal way. This will improve the performance of quantum computers by a 1,000-fold compared to other leading approaches. Once we integrate hardware and software tightly, we expect that the performance will improve by 1,000,000-fold. We have assembled a group of experts from across the UK to build the operating system. This includes the UK's leading quantum hardware companies, Hitachi, Oxford Quantum Circuits, SeeQC, Duality Quantum Photonics, Oxford Ionics, and Universal Quantum; Riverlane, a quantum software company; Arm, a UK-based chip manufacturer; and the National Physical Laboratory. The National Physical Laboratory plays an important role because their expertise lies in developing technical standards for breakthrough technology. To build our operating system, we need to define a new standard interface between software and hardware that everyone can use. Our project will attract many important customers, such as pharmaceutical or chemical companies, as well as the financial industry. Because our operating system is so much better, they will want to run their applications on UK-based quantum computers.