United Kingdom

Time-correlated single-photon counting (TCSPC) has been established as the preferred detection approach for high performance lidar and depth profiling due to its excellent surface to surface resolution and high optical sensitivity. 
This presentation will show the results of laboratory-based experiments obtained using different optical transceiver configurations. Particular attention will be given to underwater depth imaging using an individual commercially available silicon single photon avalanche diode (Si-SPAD) detectors, and prototypes of Si-SPAD detector arrays fabricated in complementary metal-oxide semiconductor (CMOS) or in custom fabrication technology. 
Depth and intensity profiles of stationary and moving targets were obtained under several underwater scattering conditions. The spatial resolution of each system was investigated in order to provide an estimation of the image degradation as the level of scattering increased. Data were analyzed using a pixel wise cross correlation approach, however additional bespoke image processing approaches will be discussed.

Bristol Quantum Information Technologies Workshop

Underwater single-photon depth imaging

scattering

tcspc

underwater single-photon imaging

spad

### Welcome to the 9th annual workshop on Naval Applications of Machine Learning!

NAML is the premier annual event showcasing current machine learning research relevant to Naval applications. We welcome participation from the defense community, industry, and academia. The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team. 
<br>Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications
* To connect machine learning researchers with experts in military requirements
* To build and strengthen collaborations within the defense research community

#### *"What we do as a Navy is a human business. Don’t pass up an opportunity to come together as a team. Don’t pass up leadership opportunities, and don’t outsource them to a PowerPoint. If you have an opportunity to come together as a team, to increase belonging, do it."*
Admiral John M. Richardson, 31st Chief of Naval Operations
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NAML 2025

The 9th annual workshop on Naval Applications of Machine Learning is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team. The goals of NAML are to spread awareness of current machine learning research relevant to Naval applications, to connect machine learning researchers with experts in military requirements and to build and strengthen collaborations within the defense research community.

technical paper

**BQIT is a three day annual workshop** aimed at enabling leading UK and international academics and industrial partners to come together; to explore and discuss future ambitions and challenges in the field of **Quantum Information Technologies.** Since our conception in 2014 we have had 230 speakers and panellists who have presented their work and opinions on a range of topics, from quantum theory to innovation in industry.


### Welcome Message
The BQIT:21 team welcomes you to the eighth Bristol Quantum Information Technologies workshop! 

Last year was the first time in our workshop's history that we had gone fully virtual. The global circumstances that continue to impact us all professionally and personally have forced BQIT once again to be delivered as an all-virtual workshop for 2021. The access this creates to colleagues across the world who would otherwise be unable to join us, as well as being able to make the workshop free for all attendees due to the lower costs involved in delivering an online workshop, are just a couple of the extraordinary benefits of meeting online. This also means that we can welcome three times as many attendees to BQIT than previous years.   

We take this opportunity to thank each of our speakers and poster presenters for contributing their technical content, this year's sponsors, whose support this year enabled BQIT:21 to be free to all attendees, and to all of our attendees for joining us online this year. We recognise the extra energy required to stay connected and motivated during these difficult times, and are hugely encouraged to see so many of you willing to continue to connect with us on an online platform. 

It is our hope that you have a productive and enjoyable time while you engage and interact with BQIT:21, and to everyone that has helped take BQIT:21 online, thank you! 

**The BQIT board and organisation team **


![](https://assets.underline.io/uploads/markdown_image/1/image/a12e0c1ad3410144cb48557690e4ecaf.png)
### This year's workshop agenda is available here: [Virtual BQIT:21](https://drive.google.com/file/d/1QwsSM0ztnxC_lgUKf3TbO3GvnI44AQkY/view?usp=sharing)
For further information, please contact us at: **bqit-admin@bristol.ac.uk**

![](https://assets.underline.io/uploads/markdown_image/1/image/a12e0c1ad3410144cb48557690e4ecaf.png)

Photonics is a promising platform for demonstrating quantum computational supremacy (QCS) by convincingly outperforming the most powerful classical supercomputers on a well-defined computational task. Despite this promise, existing photonics proposals and demonstrations face significant hurdles. Experimentally, current implementations of Gaussian boson sampling lack programmability or have prohibitive loss rates. Theoretically, there is a comparative lack of rigorous evidence for the classical hardness of GBS. In this work, we make significant progress in improving both the theoretical evidence and experimental prospects. On the theory side, we provide strong evidence for the hardness of Gaussian boson sampling, placing it on par with the strongest theoretical proposals for QCS. On the experimental side, we propose a new QCS architecture, high-dimensional Gaussian boson sampling, which is programmable and can be implemented with low loss rates using few optical components. We show that particular classical algorithms for simulating GBS are vastly outperformed by high-dimensional Gaussian boson sampling experiments at modest system sizes. This work thus opens the path to demonstrating QCS with programmable photonic processors.

Quantum Computational Supremacy via High-Dimensional Gaussian Boson Sampling

The discrete time crystal (DTC) is a recently discovered out-of-equilibrium phase of matter that spontaneously breaks discrete time-translation symmetry. Experimental observation has proven elusive due to the necessity of disorder-induced many-body localization to stabilize the DTC phase. Here, we observe the hallmark long-lived spatiotemporal order of the DTC phase using a quantum simulation platform based on individually controllable carbon-13 nuclear spins in diamond. The observed subharmonic response is robust for states with different temperatures, distinguishing the DTC phase from the prethermal subharmonic responses attributed to previous experiments. Our results provide the experimental signatures of a new out-of-equilibrium phase of matter and introduce a programmable spin-based quantum simulator for many-body physics.

Quantum simulation of a discrete time crystal using solid-state spins in diamond

Integrated quantum photonics is a promising avenue for scaling up quantum optics beyond the proof of principle demonstrations. Such a future requires on-chip reconfigurable photonics where the integration with single-photon detectors remains a significant challenge. Heat as a standard method to tune photonic circuits makes superconducting detectors challenging. This work shows the cointegration of microelectromechanical reconfiguration with on-chip superconducting single-photon detectors (SSPD). As a demonstration of principle, we perform high-extinction routing, high-dynamic-range single-photon detection and power stabilization. This platform allows for heat-load free reconfiguration and all-integrated quantum optics experiments.


Reconfigurable photonics with on-chip single-photon detectors

Quantum computing machines have now entered a regime where tasks that were intractable on classical hardware can be solved. However, computational errors in such devices are still prohibitive for scaling to hundreds of good quality qubits.
In photonics, towards the achievement of a scalable platform for fault-tolerant universal quantum computing the reconfigurable generation of large entangled states is needed. These states can provide a flexible architecture which can naturally embed error-correction and be therefore useful for real applications in error-full scenarios.
Here we propose and experimentally demonstrate a novel integrated silicon photonic architecture that both entangles multiple photons and encodes multiple physical qubits on individual photons to produce error-correctable logical qubits. We realise reprogrammable entangled states for measurement-based quantum computing and compare a wide range of quantum information processing tasks with and without error correction. Moreover, we show the effectiveness of error
correction codes in quantum applications, such as the quantum phase estimation protocol, observing a significant success rate increase when running algorithms with error correction. We do it on an integrated silicon photonic platform which provides, fast-reconfigurable, high-precision, compact and mass-manufacturable circuitry, able to process tens of qubits. 
Our work represents a record for number of reconfigurable on-chip generated photonic qubits. Our results show how quantum error correcting schemes can provide advantages not only for faulttolerant machines, but also for near-term applications on pre-fault-tolerant devicesimplemented with resource-efficient photonic architectures that can already dramatically improve the performance of
quantum algorithms.

Error-protected measurement-based quantum computing on an eight-qubit silicon photonics processor

Rydberg atoms are highly excited atoms with exaggerated properties. In recent years, Rydberg atoms have emerged as a promising platform for numerous quantum technologies, ranging from quantum computation and simulation, single photon sources, RF communications and SI-traceable standards for electric fields. In this talk, I will explain how the properties of Rydberg atoms make them advantageous for such applications and I will present the results from two recent experiments at Durham. (1) High speed terahertz imaging in thermal atoms that achieves frame rates that are orders of magnitude faster than other terahertz sensors. (2) Collectively encoded qubits in cold-atom ensembles that demonstrate coherence properties that are robust to atom loss and electric field noise. 
(1) L. A. Downes et al. Physical Review X. 10, 011027 (2020) 
(2) N. L. R. Spong et al. arXiv:2010.11794

Rydberg Quantum Technologies

Honeywell Quantum Solutions launched its first commercial trapped-ion quantum computer in 2020, designed around the quantum charge-coupled device (QCCD) architecture. By applying fast transport operations to reorder and position ion qubits across multiple trapping zones simultaneously on the device, the QCCD architecture creates a fully-connected, high fidelity, and scalable quantum computer. These systems offer the unique capability of performing conditional quantum operations dependent on mid-circuit measurement outcomes, and qubits can be re-used in the same circuit after measurements. This feature allows users to perform efficient quantum simulations and execute repeated cycles of quantum error correction. Recently, the 10-qubit System Model H1 became the first quantum computer to pass the quantum volume 512 benchmark, the largest quantum volume ever measured on a commercial quantum computer. Future generation systems will incorporate new technologies such as 2D trap architectures and integrated photonics, in order to scale the number of physical qubits and further increase system performance.

High Performance Commercial Trapped Ion Quantum Computers

In this presentation, I will highlight our recent progress on developing AlGaAs-on-insulator (AlGaAsOI) integrated photonic devices for ultra-efficient quantum light generation, manipulation, and detection. AlGaAsOI boasts several advantages for integrated quantum photonics, including the brightest chip-scale entangled-photon pair sources, negligible two-photon absorption in the telecommunications band, low-loss reconfigurable interferometers with high extinction, high-efficiency and low-noise waveguide-integrated single-photon detectors, and prospects for low VL electro-optic modulators. Combined, these components offer exciting prospects for scalable, all-on-chip quantum photonic computing. I will also present our recent work on the integration of III-V gain with silicon-on-insulator entangled-pair sources for turn-key quantum light generation.

Heterogeneous III-V/Silicon Quantum Photonics

On-chip integration of single-photon detectors and reconfigurable optical circuits is a crucial step toward a fully scalable approach to quantum photonic technologies. By confining light inside lithographically patterned waveguides, single-photons can be actively routed and interfered in miniaturized reconfigurable optical networks, and their state can be read out with on-chip detectors. Integration of these two key elements on a common platform enhances the scalability of quantum photonic devices by minimizing their footprint and eliminating the need of lossy interconnects between separated optical systems. I will present recent progress on realizing cryo-compatible reconfigurable photonic circuits using hybrid integration. Our design is based on superconducting nanowire detectors for measuring single photon events combined with either electro-optomechanical or electro-optical phase shifters embedded in on-chip interferometers. These concepts enable the realization of programmable photonic circuits that feature low dissipation loss.

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