Antia Lamas-Linares, quantum networking lead at Amazon Web Services and an expert in quantum optics, is seen looking into the camera
Antia Lamas-Linares, quantum networking lead at Amazon Web Services and an expert in quantum optics, was among the ‘first wave’ of scientists to gain a PhD in quantum technology.

Antia Lamas-Linares’s path into the world of quantum

Among the ‘first wave’ of scientists to gain a PhD in quantum technology, the senior manager of research science discusses her two-decade-long career journey.

In January 2021, Antia Lamas-Linares joined Amazon Web Services (AWS) to work on quantum technologies.

A quantum information scientist, Lamas-Linares is an expert in quantum optics. More precisely, in photonic (optical) implementations of quantum-information protocols. Her career to date includes pioneering research on quantum key distribution — formerly known as quantum cryptography — superconducting single-photon detectors and space-based quantum technology (including several patents), in addition to high-performance computing.

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Quantum science and technologies are evolving fast, and for the first time, small prototype quantum computers are appearing around the world. Indeed, the Amazon Braket service provides access to these computers for researchers and institutions. AWS itself announced the opening of its Center for Quantum Computing in October 2021. While quantum processors already exhibit some interesting quantum mechanical behaviors, they have some way to go before they outperform “classical” computers in truly disruptive ways.

Quantum computers work through the manipulation of quantum bits, known as qubits, instead of conventional digital bits. Lamas-Linares joined AWS to focus on research related to connecting quantum devices with each other.

“You can think of quantum computing as dealing with stationary qubits and quantum networking as dealing with ‘flying qubits’ – qubits going from A to B,” says Lamas-Linares.

Quantum networking

To understand the coming importance of quantum networking, first consider a central disruption that quantum computers are ultimately expected to deliver: a potential, future threat to modern digital security. That is because quantum computers have the potential to outperform classical computers, including the ability to break encryption methods currently relied on for modern communications and data security.

The center's mission is to address fundamental scientific and engineering challenges and to develop new hardware, software, and applications for quantum networks.

“This once-remote threat of a hypothetical quantum computer breaking modern encryption is becoming less of a hypothetical and more of a ‘not if but when’,” says Lamas-Linares.

One potential solution to this challenge would be go “full quantum” in how information is protected in the first place, says Lamas-Linares, using quantum encryption keys.

“One of the main applications — and low-hanging fruit — of quantum networking is the ability to distribute those keys securely. This involves exploiting the inherent randomness and correlations that exist in quantum systems to create perfectly secure correlated numbers that can then be used for cryptography.”

In short, quantum networking has the potential to also deliver perfect privacy. It would be easy to fall down a quantum rabbit hole here. Suffice it to say, quantum entanglement — a fundamental quantum phenomenon — can be exploited to distribute these keys in such a way that no intermediary company involved in the warehousing or transmitting of data would be able to access that data.

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Only the possessor of the quantum keys — the data owners — can decrypt and access that data. In the future, such perfect protection of customer data will be crucial to every organization, from financial institutions and governments to hospitals and industry. The goal of quantum key distribution is to securely transmit those keys to where they need to be.

“At AWS we often say that security is job zero — more important than any other priority. That’s because if customers don't trust the cloud, then most business models just won’t work in the cloud. Customers need confidence that their data and transactions are secure,” says Lamas-Linares.

Mathematical games

The first quantum cryptography protocol, theoretical but provably secure, was called BB84 and published in 1984. At the time, a young Lamas-Linares was growing up in Santiago, Spain, busily getting hooked on mathematics and physics: she did not yet speak English, but recalls her parents owned the Spanish translation of a collection of classic “Mathematical Games” columns from Scientific American, written by Martin Gardner.

“That really caught my attention — I was fascinated,” says Lamas-Linares. Later, in 1988, Stephen Hawking’s “The Brief History of Time” further captivated her. “It’s kind of a cliché, but that book set me on my path.”

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It was a path that took Lamas-Linares to study physics at the University of Santiago de Compostela. After graduating, Lamas-Linares moved for a year to the University of Sheffield, UK, via the European Union’s Erasmus student exchange program, before spending a year completing a master’s in applied optics at Imperial College London.

Why the focus on optics?

[Optics] is one of these fields in physics where you can literally see the things that are happening. If you study optics from a mathematical point of view, it’ll tell you something that you can recreate perfectly with light and lenses.
Antia Lamas-Linares

“It’s one of these fields in physics where you can literally see the things that are happening. If you study optics from a mathematical point of view, it’ll tell you something that you can recreate perfectly with light and lenses. I thought that was really cool,” she said.

Then Lamas-Linares started learning about quantum optics, and so-called “squeezed states” of light. Being quantum, and therefore tiny, this is physics you cannot see with your eyes, but she thought it was cooler still. In 2003, Lamas-Linares completed her doctorate in physics at the University of Oxford.

Lamas-Linares’s subsequent career has continued an international trend. Highlights include becoming an assistant professor at the National University of Singapore (NUS), where she soon set up a new quantum optics lab and became principal investigator at the university’s Centre for Quantum Technologies. She later became a senior research fellow at the US National Institute of Standards and Technology in Boulder, Colorado, and a research associate doing high performance computing at the Texas Advanced Computing Center in Austin.

Moving into industry

When Lamas-Linares made the move from academia to industry, it was to join an NUS spinout company, SpeQtral, as chief quantum scientist in 2019. The switch resulted from an itch for her work to have more direct real-world impact.

“Academia is full of what we call hero experiments, where you make something work once, but maybe afterward it self-destructs or melts or something; the important thing is you showed something was possible; a viable effect. That’s great, but it’s nowhere near what you need to create a useful technology,” says Lamas-Linares. “First and foremost, I'm an experimentalist — I build devices. And I wanted to build robust versions of useful technology. That sort of engineering challenge doesn’t make sense for academia — you have to go to industry. I want to bring quantum technologies to the point where it is the ‘best’ solution to a technical problem and so it becomes part of the standard toolbox.”

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SpeQtral pioneers the development of miniaturized sources of quantum-entangled photons, designed to be deployed on satellites as a means to distribute quantum keys around the Earth. The company has successfully demonstrated such miniaturized technology in space, using its shoebox sized “cubesat”, SpooQy-1.

“SpeQtral had already put an entanglement source in space when I joined as chief quantum scientist,” Lamas-Linares recalls. “By this time I’d been working in the field for two decades, having done a lot of work on entanglement sources, but also on whole systems designed to implement quantum key distribution systems over free space, and in hacking those same systems to show which parts needed further thought.”

While at SpeQtral, industry networking meant Lamas-Linares talked with Amazon about this technology. “That’s how I became more aware of what that Amazon was doing things in quantum technologies,” says Lamas-Linares. “It turned out that one of my former colleagues, Simone Severini, was working at AWS in quantum computing. One day he said to me: ‘Hey, we're doing really interesting stuff. Would you be interested in joining us?’.”

What was it that Severini saw in Lamas-Linares?

“I’ve known Antia professionally for about 20 years, and have always been struck by her adaptability and the fact that she is a real ‘owner’,” he says. “Ownership is fundamental in a complex, pioneering environment like this. Nobody is telling you exactly what to do — you have to find your own way, and push when you find friction. “Antia fits Amazon very well — she has a strong bias for action.”

Amazon’s appeal

For Lamas-Linares’s part, she was attracted to Amazon’s resources, capability, and very long-term vision.

“Amazon is only interested in building things that have a clear application and benefit for their customers, but if they are convinced of that customer value, they will invest for as many years as necessary to reach the required level of technological readiness,” she explained. “That’s exciting, and it’s much harder to do in the start-up/venture capitalist environment, particularly with complicated hardware products.”

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One of the main challenges in making strides in quantum networking, says Lamas-Linares, is technological integration.

“Whatever quantum technology you develop, before it can be of any use to your customers, an entire ecosystem of additional technology needs to be built up around it, and the people needed to do that barely exist for quantum technologies. Finding that combination of expertise and building the required tools is a non-trivial challenge.”

As quantum technologies are taken up by industry, we’re starting to make the molds for what quantum engineers will be. That, to me, is really exciting.
Antia Lamas-Linares

The sheer newness of many quantum technologies makes it tricky to orchestrate a successful career in the field. Does Lamas-Linares, herself in the first wave of scientists to gain a PhD in quantum technology, have any advice to offer?

“I am definitively not qualified to give anyone advice, but I would say this: Don’t be afraid to take an unconventional path. Especially in emerging fields like this, you just don’t know what the right combination of skills and experience will turn out to be.”

Lamas-Linares points out that “quantum engineers” don’t really exist as yet.

“Engineers take established knowledge and they perfect it. As quantum technologies are taken up by industry, we’re starting to make the molds for what quantum engineers will be. That, to me, is really exciting.”

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Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of dexterous manipulation system that: - Enables unprecedented generalization across diverse tasks - Enables contact-rich manipulation in different environments - Seamlessly integrates low-level skills and high-level behaviors - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement methods for dexterous manipulation with single and dual arm manipulation - Leverage simulation and real-world data collection to create large datasets for model development - Develop a hierarchical system that combines low-level control with high-level planning - Utilize state-of-the-art manipulation models and optimal control techniques - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for dexterous manipulation
US, NY, New York
About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The Search Ranking and Interleaving (R&I) team within Sponsored Products and Brands is responsible for determining which ads to show and the quality of ads shown on the search page (e.g., relevance, personalized and contextualized ranking to improve shopper experience, where to place them, and how many ads to show on the search page. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of GenAI and ML techniques to continuously explore, learn, and optimize the ranking and allocation of ads on the search page. We are an interdisciplinary team with a focus on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. A day in the life As an Applied Scientist on this team, you will identify big opportunities for the team to make a direct impact on customers and the search experience. You will work closely with with search and retail partner teams, software engineers and product managers to build scalable real-time GenAI and ML solutions. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact while broadening your technical skillset. Key job responsibilities - Solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. - Drive end-to-end GenAI & Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. - Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them - Research new and innovative machine learning approaches.