Tech
HSBC collaborates on noisy qubit real-world application | Computer Weekly
HSBC has collaborated with quantum middleware developer Haiqu and a team of academic researchers on an efficient way to run financial models on commercially available quantum computing hardware. The publication of joint research in Physical Review Research discussed an approach to encoding real-world probability distributions into quantum circuits.
HSBC is among the financial institutes looking at how to secure financial transactions as quantum computing evolves into commercially viable products, such as protecting financial systems using post quantum cryptography. Quantum computers also offer banks such as HSBC a way to run more powerful financial market simulations.
The research team – which included experts from HSBC, Haiku, Czech Technical University, University of Zurich, the Akhiezer Institute for Theoretical Physics and Karazin Kharkiv National University in Ukraine, and Greece’s Athena Research Center – looked at Lévy distributions, which are used when modelling extreme variations of stock markets indexes worldwide.
“By developing methods to efficiently work with Lévy distributions on a quantum computer, we pave the way for more precise modeling of market behaviours, particularly in capturing heavy tails, skewness and volatility clustering,” the researchers stated in the paper.
According to Haiqu, while quantum computing can be used in derivative pricing, portfolio optimisation, fraud detection and machine learning, these applications need realistic financial distributions. This means data must first be loaded into a quantum computer. The process of encoding classical data into quantum states is widely recognised as a major bottleneck when implementing many quantum algorithms on hardware. The challenge is particularly relevant for applications such as financial risk modelling and simulation, where complex probability distributions must be loaded onto quantum devices.
Haiqu said that the number of required quantum operations in conventional algorithms can scale exponentially with the number of qubits, making it a significant bottleneck on today’s noisy, depth-limited hardware. To address this problem, the company has developed compact quantum circuits with linear, rather than exponential, scaling.
“One of the biggest practical barriers is getting realistic financial data onto today’s quantum hardware,” said Mykola Maksymenko, co-founder and CTO of Haiqu. “This work shows a scalable path around that barrier and helps move quantum finance workflows from theory toward execution.”
The researcher uses matrix product state (MPS) methods to construct shallow quantum circuits that encode smooth functions, including probability distributions, directly into quantum states.
Using a 25 qubit IBM quantum computer, the research paper stated that accuracy of the machine was sufficient to pass quantitative statistical tests, even on current noisy quantum computing devices. “The results on distribution loading may have importance to various domains of financial risk analysis, risk management and decision-making that include series of financial data,” the researchers noted.
They used a sampling-based workflow, running on 64-qubit hardware, which they said demonstrates the feasibility of their approach when running at larger scales. In the paper, they stated that similar behaviour was observed in simulations up to 156 qubits, which they claimed means the approach could extend to substantially larger problem sizes.
“Preparing complex probability distributions efficiently is a key step in many quantum algorithms,” said Philip Intallura, group head of quantum technologies at HSBC. “This work shows how they can be implemented with much shallower quantum circuits, bringing practical applications such as financial risk modelling closer.”
In the latest part of its 20-year concession to deliver high-speed mobile connectivity across the entire transport network, Boldyn Networks has been charged with delivering a 4G mobile network infrastructure that will enable the country’s Emergency Services Network (ESN) for London Underground.
Neutral host provider Boldyn Networks was awarded a 20-year concession by Transport for London (TfL) in June 2021 to deliver high-speed mobile connectivity across the entire London Underground network. TfL carries up to four million passengers a day on the London Underground network, and renewing and preparing the communications network for the future has long been regarded as essential to maintain and improve critical infrastructure.
The network upgrade is seen as an important step in updating London’s public safety critical communications, enhancing response times and improving the quality of information available to emergency services personnel addressing live incidents.
Boldyn’s delivery of infrastructure for ESN on the London Underground is being carried out in collaboration with leading UK mobile provider EE, TfL and the UK’s Home Office, with the primary aim of enabling more resilient and reliable communications services in the future for thousands of first responders including police, fire and ambulance services.
The ESN has endured a series of problems since its inception with the £2bn network project beset by delays and cost overruns. In 2015, the UK Home Office contracted suppliers to provide a new ESN to replace the existing and well-liked Airwave terrestrial trunked radio (Tetra) network used by all 108 police, fire and ambulance services across England, Scotland and Wales to communicate between the field and control rooms.
As part of its Emergency Services Mobile Communications Programme (ESMCP), the Home Office intended ESN to fully replace Airwave, be less expensive and provide users with access to “modern” mobile data. The government expected to turn off Airwave in 2019. In the same year, the Home Office contracted BT-owned EE to provide priority access to its mobile network and increase network coverage. It also contracted Motorola Solutions UK for software and systems including critical features not normally found on a mobile network, such as a first-of-a-kind “push-to-talk” functionality.
Numerous delays and criticism of the role of Motorola Solutions eventually led to the UK’s Competition and Markets Authority (CMA) opening an investigation into the role of the Airwave network in the ESN in October 2021, with a particular focus on the impact of Motorola’s dual role as the owner of the company providing the planned new mobile radio network and as a key existing supplier. In May 2023, the CMA recommended restricting how much Motorola can charge the emergency services to use Airwave.
In January 2025, after several further delays and much criticism from Parliament regarding the project and its leading technology stakeholder, the current government decided to embark on a different approach to deliver the infrastructure, appointing new IT and comms partners including IBM and Ericsson.
The deployment for London Underground will aim to provide “seamless” mobile coverage across the 137 Tube, Docklands Light Railway and London Overground stations located underground. It will provide first responders with immediate access to what could be lifesaving data, imagery, live video and public safety information, supporting faster and more coordinated responses to live situations.
Yet Boldyn also accepts that delivering these new capabilities within the London Underground presents unique engineering challenges because it is one of the UK’s most complex transport environments.
“Access to connectivity for the emergency services can’t be compromised, especially in an environment as complex as the London Underground. Critically, ESN will ensure first responders can stay connected when it matters most, with access to the data and tools they need to respond quickly, safely and successfully,” said Paul Osborne, chief commercial officer UK at Boldyn Networks. “We’re proud to continue our work with TfL and EE to help safeguard the millions of daily passengers across the London Underground network.”
In addition to the project to deliver mobile coverage across the Tube network, which remains on track for delivery by the end of 2026, Boldyn and TfL have committed to scaling the capital’s fibre backbone and installing small-cell technology on street furniture.
Commenting on the new project, TfL’s director of technology products and operations, Rebecca Bissell, said: “Keeping our customers and London’s emergency services personnel safe while they travel and operate across our network is our top priority. That means ensuring frontliners are equipped with immediate access to lifesaving information to respond more effectively to emergency situations and keep London moving safely.”
Faisal Mahomed, managing director of ESN mobile services at BT Group: “Extending ESN below ground marks another important milestone in our long-term commitment to empowering Britain’s emergency services with trusted, mission critical communications. We’re pleased to be working alongside Boldyn Networks and TfL to provide this service.”
Food handling is an area of work that still relies heavily on humans. Fruit, vegetables, meat, and other foods need to be handled quickly but gently. It is also hard to automate because no two pieces of fruit, vegetables, or chicken nuggets look exactly the same.
Eka’s demos suggest that the company may be onto something big. I found myself mentally comparing their robots to GPT-1, OpenAI’s first large language model, developed four years before ChatGPT. GPT-1 was often incoherent but showed glimmers of general linguistic intelligence.
The robots I saw seem to have a similar kind of nascent physical intelligence. When I watched a video of one reaching for a set of keys in slow motion, I noticed it did something that seemed remarkably human: It touched the tips of its grippers to the table and slid them along the surface before making contact with the keys and securing them between its digits. Eka’s algorithms seem to know instinctively how to recover from a fumble. This kind of thing is difficult for other robots to learn, unless the humans training them deliberately make a wide range of mistakes.
Unlike with any other robot I can think of, it’s almost possible to imagine what the world is like for the robot. Its sensors seem to feel the weight of its arm, the inertia as it sweeps toward the keys and slows down. Once it has the keys in its grasp, it seems to sense the weight of them dangling from its claw.
I don’t know if Eka’s approach really is the route to a ChatGPT-like breakthrough in robotics. Some very smart experts believe that mixing human demonstration with simulation will yield better results than simulation alone. Maybe some combination of the two approaches will ultimately be necessary? But it does seem clear that robots will eventually need to have the kind of tactile, physical intelligence that Eka is working on if they are to obtain humanlike dexterity.
Agrawal tells me that the same general approach should work for finer manipulation. The fiddly dexterity required to build an iPhone, for instance, could be achieved by building different actuators and sensors and practicing the task in simulation.
After spending a few hours at Eka, I decide to stop by the restaurant downstairs. I watch from the counter as the staff prepare food and make coffee. A descendant of the machine upstairs may be able to do these things just as well, if not better. But given how much I enjoy chatting with the people who work there, I think I would pay extra to keep humans around. Unless, that is, my hands get automated away too.
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