A picture of Aleksander Kubica
Aleksander Kubica, a research scientist with the AWS quantum computing team, won the first ever quantum chess tournament.
Credit: Perimeter Institute for Theoretical Physics

The quantum gambit

How an Amazon quantum computing scientist won the first-ever quantum chess tournament.

Chess is experiencing a resurgence. Goliath Games told NPR its chess set sales were up 1,048% year-over-year in November 2020. That surge is thanks in part to the success of the wildly popular Netflix series, The Queen’s Gambit. But it wasn’t just traditional chess that broke ground: 2020 also marked the debut of the first-ever quantum chess tournament.

“Quantum chess is a variant of the classical game of chess with a few extra moves, which are designed to mimic some quantum phenomena,” said Aleksander Kubica, the winner of the inaugural quantum chess tournament, and a research scientist with the AWS quantum computing team. Not only did he win, he did so having started playing quantum chess only once — the weekend before the event. The tournament took place Dec. 7-9 at Q2B 2020, a quantum computing industry conference.

Quantum Chess Tournament | Semi-finals | Q2B20

“The game was developed by a graduate student at the University of Southern California, Chris Cantwell. Back in 2016, when I was a graduate student at Caltech, Chris would come to Caltech and talk to one of the quantum researchers, Spiros Michalakis. So, I knew of the game, but I never actually played it until a few days before the tournament.”

Cantwell has written that he developed the game in part because: “Games can provide an environment in which people can experience the strange behavior of the quantum world in a fun and mentally engaging way.”

While quantum chess was brand new, both to Kubica and most of the world, Kubica had an existing passion for conventional chess. “I like playing chess. When I was in middle school, I even participated in a few regional chess tournaments. I enjoy thinking about chess puzzles when I eat breakfast. Each morning I solve five puzzles on Chess.com.

Quantum Chess Tournament | Final | Q2B20

When the opportunity to enter the tournament arose, Kubica saw a chance to combine one of his passions with his profession. Kubica, who has a PhD in quantum physics from Caltech, spent three years as a postdoctoral fellow at Perimeter Institute for Theoretical Physics in Waterloo, Canada, before joining Amazon in October 2020.

Kubica spoke with Amazon Science about the tournament, his strategy, and his advice for those who might want to try their hands at quantum chess. He also noted that, while he enjoyed the series, he didn’t actually watch The Queen’s Gambit until after the tournament.

Q. How does quantum chess differ from standard chess?

Quantum chess is a two-player game which uses the same board with 64 squares and 32 pieces as classical chess — pun intended! All the moves which are allowed in classical chess are also allowed in quantum chess. However, in quantum chess there are a few extra moves, such as the split and merge moves. (Ed note: The game’s rules allow for “a trifecta of quantum evolutionary phenomena: superposition, entanglement, and interference.)

AWS scientists coauthor 13 QIP 2021 quantum computing papers

Researchers affiliated with Amazon Web Services' Center for Quantum Computing presented at the Conference on Quantum Information Processing. See the accepted papers here.

The split move, as its name suggests, consists of first splitting a piece into two parts and then moving them independently to two different unoccupied squares. For instance, on an empty chessboard a queen on d4 could be split and moved to b6 and h4. Such a move would then result in the queen being with equal chances on either b6 or h4. Interestingly, the precise location of the split queen would remain undetermined as long as the player makes no attempt to capture opponent's pieces with that queen. The merge move, on the other hand, tries to combine two parts of a split piece into one.

It is not, however, the inverse of the split move.

The split and merge moves demonstrate the ideas of superposition and constructive/destructive interference, which are some of the most fundamental concepts in quantum physics. The extra moves introduce an element of randomness into the game, making quantum chess non-deterministic.

I personally like it, as it makes the outcome of the game less predictable even if the players' skill levels differ significantly.
 

Q. What was your strategy and how well did it work? Did you have to adapt at all?

Before the tournament I practiced a bit with my friend, Tomas Jochym-O'Connor, a quantum researcher. We played a few games and thought about new strategies incorporating extra moves unique to quantum chess. To our surprise, we discovered that one of the most popular chess openings, the Sicilian Defence, is somehow flawed. Namely, by splitting a knight, white can set up a trap for black, and with a bit of luck white may capture black's king and win the game.

Stephen Hawking faces Paul Rudd in quantum chess

The tournament was organized in a knockout format with three rounds. There were eight participants representing various companies interested in developing quantum technologies, including Google, Microsoft, and Amazon. Each game was a 20-minute game with additional 20 seconds added after each move. The winning condition was to either capture the opponent’s king or win on time.

In my first tournament game I played white against Martin Roettler from Microsoft. I opened with standard 1.e4, to which my opponent replied 1…c5 — the Sicilian Defence! I realized that this could be my chance and decided to implement the split knight trap. Unaware of imminent danger, Martin continued to develop his position, falling into the trap and eventually losing the game in just a few moves. I was very happy and relieved that the gamble paid off.

The Q2B20 quantum chess bracket
Aleksander Kubica defeated three opponents to win the inaugural tournament, as show here in the Q2B20 quantum chess bracket.
Credit: Q2B20

I am sure that in classical chess Martin would have easily defeated me. However, we played quantum chess and I had a few quantum moves up my sleeve.

In the final game, I had to face Doug Strain from Google. Once again, my opponent was definitely better in classical chess than I am. I had to withstand the initial classical assault, but once we started making quantum moves I got lucky and gained the upper hand. Because the position became quite complicated, Doug ran out of time and I won.

Q. What would you say to someone who wanted to learn to play quantum chess?

I would encourage everyone to simply start playing quantum chess. You can download the game from Steam. I would suggest that, instead of learning the rules of quantum chess, you try to figure them out first. As a physicist and a researcher, that is what I do on an everyday basis — I try to figure out how things work. I hope that playing quantum chess will be a lot of fun for you. Nothing feels better than an innocuous pawn move, which simplifies a complicated chess position, causes many entangled pieces of your opponent to suddenly disappear from the chessboard and paves your way to victory.

Research areas

Related content

US, WA, Seattle
Are you a brilliant mind seeking to push the boundaries of what's possible with intelligent robotics? Join our elite team of researchers and engineers - led by Pieter Abeel, Rocky Duan, and Peter Chen - at the forefront of applied science, where we're harnessing the latest advancements in large language models (LLMs) and generative AI to reshape the world of robotics and unlock new realms of innovation. As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge robotics technologies. You'll dive deep into exciting research projects at the intersection of AI and robotics. This internship is not just about executing tasks – it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning to tackle real-world problems and deliver impactful solutions. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied robotics and AI, where your contributions will shape the future of intelligent systems and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available in San Francisco, CA and Seattle, WA. The ideal candidate should possess: - Strong background in machine learning, deep learning, and/or robotics - Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR. - Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models. - Proficiency in Python, Experience with PyTorch or JAX - Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team Join us at the forefront of applied robotics and AI, and be a part of the team that's reshaping the future of intelligent systems. Apply now and embark on an extraordinary journey of discovery and innovation! Key job responsibilities - Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics - Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control - Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders
US, WA, Seattle
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers like Pieter Abbeel, Rocky Duan, and Peter Chen to lead key initiatives in robotic intelligence. As a Senior Applied Scientist, you'll spearhead the development of breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence in areas such as perception, manipulation, scence understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between cutting-edge research and real-world deployment at Amazon scale. In this role, you'll combine hands-on technical work with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. You'll leverage Amazon's vast computational resources to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for specific research initiatives, ensuring robust performance in production environments - Mentor fellow scientists while maintaining strong individual technical contributions - Collaborate with engineering teams to optimize and scale models for real-world applications - Influence technical decisions and implementation strategies within your area of focus A day in the life - Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure - Guide fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within your team and with key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster - Mentor team members while maintaining significant hands-on contribution to technical solutions Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team, led by pioneering AI researchers Pieter Abbeel, Rocky Duan, and Peter Chen, is building the future of intelligent robotics through groundbreaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
IL, Haifa
We’re looking for a Principal Applied Scientist in the Personalization team with experience in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problem Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
US, WA, Seattle
The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - 5+ yrs of relevant, broad research experience after PhD degree or equivalent. - Advanced expertise and knowledge of applying observational causal interference methods - Strong background in statistics methodology, applications to business problems, and/or big data. - Ability to work in a fast-paced business environment. - Strong research track record. - Effective verbal and written communications skills with both economists and non-economist audiences.
DE, Aachen
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
US, WA, Seattle
The AWS Marketplace & Partner Services Science team is hiring an Applied Scientist to develop science products that support AWS initiatives to grow AWS Partners. The team is seeking candidates with strong background in machine learning and engineering, creativity, curiosity, and great business judgment. As an applied scientist on the team, you will work on targeting and lead prioritization related AI/ML products, recommendation systems, and deliver them into the production ecosystem. You are comfortable with ambiguity and have a deep understanding of ML algorithms and an analytical mindset. You are capable of summarizing complex data and models through clear visual and written explanations. You thrive in a collaborative environment and are passionate about learning. Key job responsibilities - Work with scientists, product managers and engineers to deliver high-quality science products - Experiment with large amounts of data to deliver the best possible science solutions - Design, build, and deploy innovative ML solutions to impact AWS Co-Sell initiatives About the team The AWS Marketplace & Partner Services team is the center of Analytics, Insights, and Science supporting the AWS Specialist Partner Organization on its mission to provide customers with an outstanding experience while working with AWS partners. The Science team supports science models and recommendation systems that are deployed directly to AWS Customers, AWS partners, and internal AWS Sellers.
US, CA, Palo Alto
We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities We seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.
US, CA, Palo Alto
We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!
US, CA, East Palo Alto
The Customer Engagement Technology team leads AI/LLM-driven customer experience transformation using task-oriented dialogue systems. We develop multi-modal, multi-turn, goal-oriented dialog systems that can handle customer issues at Amazon scale across multiple languages. These systems are designed to adapt to changing company policies and invoke correct APIs to automate solutions to customer problems. Additionally, we enhance associate productivity through response/action recommendation, summarization to capture conversation context succinctly, retrieving precise information from documents to provide useful information to the agent, and machine translation to facilitate smoother conversations when the customer and agent speak different languages. Key job responsibilities Research and development of LLM-based chatbots and conversational AI systems for customer service applications. Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. 4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
US, MA, Boston
The Amazon Dash Cart team is seeking a highly motivated Research Scientist (Level 5) to join our team that is focused on building new technologies for grocery stores. We are a team of scientists invent new algorithms (especially artificial intelligence, computer vision and sensor fusion) to improve customer experiences in grocery shopping. The Amazon Dash Cart is a smart shopping cart that uses sensors to keep track of what a shopper has added. Once done, they can bypass the checkout lane and just walk out. The cart comes with convenience features like a store map, a basket that can weigh produce, and product recommendations. Amazon Dash Cart’s are available at Amazon Fresh, Whole Foods. Learn more about the Dash Cart at https://www.amazon.com/b?ie=UTF8&node=21289116011. Key job responsibilities As a research scientist, you will help solve a variety of technical challenges and mentor other engineers. You will play an active role in translating business and functional requirements into concrete deliverables and build quick prototypes or proofs of concept in partnership with other technology leaders within the team. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. About the team Amazon Dash cart allows shoppers to checkout without lines — you just place the items in the cart and the cart will take care of the rest. When you’re done shopping, you leave the store through a designated dash lane. We charge the payment method in your Amazon account as you walk through the dash lane and send you a receipt. Check it out at https://www.amazon.com/b?ie=UTF8&node=21289116011. Designed and custom-built by Amazonians, our Dash cart uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning.