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Amsterdam, 6 October 2021 - Quantum Chemistry with Qu&Co’s QUBEC on Amazon Braket.

this is a re-post of a blog written by Nihit Pokhrel (AWS), Vincent Elfving (Qu&Co) and Mario Dagrada (Qu&Co). The original post can be found on the AWS site.

In this post, we discuss the progress and limitations of chemistry simulations on current quantum computers, and introduce Qu&Co‘s QUBEC, a quantum computational platform that is specifically designed for chemistry and materials science simulations. The post describes QUBEC’s architecture and how it integrates with Amazon Braket. Finally, we show how you can register for the QUBEC beta release program.

Introduction

Computational quantum chemistry has succeeded in supporting the development of novel drugs, new materials, and a better understanding of matter at the nanoscale. However, the complexity of configurations on real-world chemical systems makes it intractable for researchers to attain accurate results, so computational chemistry is used to extract in silico physical properties of molecules and solids.

The computational effort required to simulate systems accurately scales exponentially with the complexity of drug molecules and materials. Even using approximation methods, current supercomputers cannot achieve the level of accuracy that these simulations demand. Quantum computation (QC) has the potential to solve some of the most challenging computational problems faced in chemistry, allowing the scientific community to do chemical simulations that are intractable today. [1]

Current quantum hardware is still under active development, but improving at a very fast pace. [2] Even though today’s chemistry simulations based on QC are not at the accuracy levels of conventional supercomputers, it is essential that we start developing quantum-inspired computational tools. These will allow researchers to benefit from the power of QC once full-tolerant devices at scale are available.

Here at Qu&Co we are getting ready for that future. We are a European quantum software developer specialized in computational chemistry and multi-physics simulations. QUBEC, a fully managed cloud solution, enables quantum chemists and materials scientists to run chemical simulations using QC in just a few clicks. Built on Amazon Braket, QUBEC removes the heavy lifting from simulation execution, and combines it with an intuitive graphical interface for modeling molecular systems. It is the initial step towards integrating QC routines with the classical chemistry workflows already adopted by the industry.

The current state of chemistry simulations on quantum computers

Although quantum algorithms have been under active development for decades, only the recent development of variational approaches to quantum computing allowed for practical executions of small-scale experiments on gate-based quantum computing devices. The main challenge is quantum hardware noise. This largely arises from either qubit operations being different than expected (coherent errors) or the coupling with a noisy environment yielding dephasing and other errors (incoherent errors).

Like on conventional computers, “Error Correction” can prevent noise by encoding information redundantly in multiple bits or qubits, respectively. However, due to the fundamental laws of quantum mechanics, more qubit overhead is required to achieve error-protected computations. A recent proposal by the team at AWS Center for Quantum Computing, shows an architecture with potential to achieve quantum advantage at the order of tens to hundreds of thousands of physical components. In contrast, in the current ‘Noisy Intermediate Quantum’ or NISQ era, we only have access to tens of noisy physical qubits, and the challenge is to identify algorithms that can still make use of quantum operations to speed up computations.

A recent proposal, the Variational Quantum Eigensolver [3], showed a feasible route to use noisy hardware for near-term experiments. The proposal led to a surge in development of comparable variational algorithms in chemistry and beyond. In such algorithms, the quantum computer is used to prepare a complex wave function as a trial solution to a computational problem, such as finding the ground state of a chemical system. Observables on this wave function can be measured by repeatedly sampling (measuring) the qubits at the output of a parametrized quantum circuit. In the variational loop, the quantum circuit parameters are optimized with respect to an objective function until the desired wave function is prepared. This combines the strength of the quantum processor in representing complex quantum states with the power of the classical processor to offset variational task. These algorithms are relatively robust against noise, because errors are partially mitigated by the variational aspect and sampled over many circuit evaluations. However, the computational scaling is expected to be worse than equivalent fault-tolerant quantum algorithms; the exact scaling of variational algorithms typically is hard to predict due to their heuristic nature.

To set expectations correctly, so far, no variational quantum algorithm has outperformed classical supercomputers in computational chemistry based on first principles (ab initio). However, recently quantum advantage has been demonstrated on a theoretical sampling task,[4] and an increasing number of academic and industrial works are bringing down the resource requirements, devising better quantum circuit strategies and more efficient optimization protocols. The race is on, and many believe chemistry or materials science applications to be one of the candidates to show early examples of industry relevant quantum advantage on near-term hardware.

QUBEC: The quantum computational platform for chemistry and materials science

At Qu&Co, we developed QUBEC to offer our users a glimpse of what we believe the future of quantum chemistry simulations will look like. In that future, researchers and engineers will be able to apply quantum computational subroutines directly within their existing conventional workflows to benefit from the improved accuracy and scaling offered by future quantum processors. In an example workflow, one may compute a molecular geometry optimization first with mean-field self-consistent classical methods, and use that geometry as an input to an ab initio chemical simulation on a quantum backend. Then the results may be collected and analyzed using classical machine learning on high performance computing resources. In this way, workflows can make optimal use of the appropriate computing technologies where they make sense, all integrated in a seamless experience.

Furthermore, we know from experience that developing quantum computing solutions, and running quantum enhanced workloads is a highly specialized job. Building such expertise in-house would not be cost-effective for most corporations, given the cost in terms of time and money for recruiting a dedicated team. Therefore, we believe quantum solutions should include a high-level of process automation. Our aim is to provide quantum computational chemistry to a corporate researcher in such a way that she can obtain good results from our solutions with little to no time overhead.

With these guiding principles in mind, Qu&Co built QUBEC as a fully managed platform running on AWS enabling users to execute chemistry simulations on current quantum computers, thanks to native integration with Amazon Braket. QUBEC automates the heavy-lifting necessary to run quantum computational tasks from automatic provisioning of the computing infrastructure to running pre- and post-processing classical calculations and performing error mitigation tasks. QUBEC needs a minimal amount of configuration and pre-existing quantum-computational know-how to achieve state-of-the-art results on current day processors. Also, QUBEC is interfaced with Maestro, a fully-featured solution for modelling chemical systems developed by Schrödinger for the conventional chemistry simulations market. The integration with such a graphical user interface (GUI) allows chemists and material scientists to start experimenting with quantum computational chemistry from within a familiar environment, benefiting the adoption rate of quantum (see Figure 1).

quco maestro integration

QUBEC currently offers two types of quantum computational backends. To calculate properties of smaller chemical systems, users can use the quantum processors offered by Amazon Braket and local simulators managed by QUBEC. QUBEC also includes an automated quantum resource estimator, Q-time, which returns the quantum resources (runtime and number of physical and logical qubits) needed to perform calculations on a future fault-tolerant quantum processor. This is a very important value proposition of QUBEC because it allows customers to better understand, from today, the requirements of the future quantum technologies needed to solve their most challenging industry-sized problems.

Given the fact that many potential end-users of QUBEC are relatively unfamiliar with quantum computations for chemistry, we conduct an extensive virtual onboarding session with all clients to help them get started. The purpose of the onboarding is to both illustrate the current product features and limitations and give a hands-on tutorial on QUBEC. After the virtual onboarding, customers can access the QUBEC graphical interface integrated with the latest version of Schrödinger’s Maestro platform. Users can also interact directly with QUBEC using the programmatic API written in Python, thus easily integrating into existing notebooks and workflows.

In Figure 2 we show an example usage of this API for extracting ground state energy of the LiH molecule. These are the steps required:

- Authenticate to the QUBEC platform using Qu&Co account’s username and password
code snippet 1

- Define the chemical system giving atomic positions and basis set of the molecular wave function
code snippet 2

- Instruct QUBEC to run the simulations on the Amazon Braket state vector simulator and wait for the simulation results
code snippet 3

- Print out the resulting ground state energy and its evolution at each iteration of the variational loop
code snippet 4

variational plot

QUBEC architecture

Under the hood, QUBEC uses a service-oriented architecture where each service deals with a single step in the multi-step workflow composing a quantum computing simulation such as input validation, pre-processing calculations with conventional quantum chemistry methods, and post-processing of the results obtained on Amazon Braket. QUBEC core computational services run onmazon Elastic Container Service (ECS). Clients can interact with the QUBEC via a purpose-built REST API. This REST API can be either accessed programmatically using a Python interface provided by Qu&Co or with the QUBEC GUI described above.

The QUBEC engine constructs the proprietary Qu&Co quantum circuits and executes the hybrid quantum-classical optimization loop customary for current variational quantum algorithms. Quantum computing tasks can be either executed on local simulators running within QUBEC or sent to Amazon Braket. To guarantee a smooth onboarding of new users, QUBEC offers access to Amazon Braket from an AWS account fully managed by Qu&Co. Alternatively, QUBEC can also leverage AWS Identity and Access Management (IAM) roles to launch Amazon Braket tasks on behalf of the user on their AWS account, allowing existing customers to seamlessly integrate QUBEC into their AWS environment. In the first case, the Amazon Braket data resides in a Qu&Co owned Amazon S3 bucket which can be accessed by the user via the QUBEC programmatic API. In the second case, the S3 bucket where the results from Amazon Braket tasks are stored can be accessed directly from the user’s AWS account. Figure 3 shows the high-level QUBEC architecture on AWS when Amazon Braket tasks are executed on behalf of the user on their account.

cloud architecture

QUBEC is tightly integrated with Amazon Braket; it leverages state vector (SV1), tensor network (TN1), and density matrix (DM1) simulators offered to efficiently execute large-scale variational quantum simulations. The high performance of these simulators allows QUBEC to carry out chemistry simulations on system sizes far beyond what is feasible with local simulators. Furthermore, QUBEC leverages the flexibility of Amazon Braket SDK to determine optimal qubit allocation to support the error mitigation routines implemented in QUBEC.

Conclusion

In this post, we briefly introduced concepts in quantum computing for chemistry, what the future of quantum computing promises for quantum chemistry simulations, and what are the limitations of quantum computational approaches today.

We also showed how the Qu&Co QUBEC platform, integrated with Amazon Braket, can offer a glimpse of what the future of quantum chemistry will look like. In that future, corporate researchers will be able to apply quantum computational subroutines directly in their existing conventional computational workflows, so that they can benefit from the improved accuracy and scaling offered by future quantum processors.

To request access to the beta release of QUBEC, register at www.quandco.com/product. For questions about our quantum-algorithm research activities, please contact us through www.quandco.com/contact; we are happy to talk.

The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post.

References

[1] Yudong Cao, Jonathan Romero, Jonathan P. Olson, Matthias Degroote, Peter D. Johnson, Mária Kieferová, Ian D. Kivlichan, Tim Menke, Borja Peropadre, Nicolas P. D. Sawaya, Sukin Sim, Libor Veis, and Alán Aspuru-Guzik, Quantum Chemistry in the Age of Quantum Computing, Chem. Rev. 2019, 119, 19, 10856–10915

[2] Christopher Chamberland, Kyungjoo Noh, Patricio Arrangoiz-Arriola, Earl T. Campbell, Connor T. Hann, Joseph Iverson, Harald Putterman, Thomas C. Bohdanowicz, Steven T. Flammia, Andrew Keller, Gil Refael, John Preskill, Liang Jiang, Amir H. Safavi-Naeini, Oskar Painter, Fernando G.S.L. Brandão, Building a fault-tolerant quantum computer using concatenated cat codes, arxiv.org [2012.04108] (2020)

[3] Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alán Aspuru-Guzik & Jeremy L. O’Brien. A variational eigenvalue solver on a photonic quantum processor, Nat Commun 5, 4213 (2014).

[4] Arute, F. et al. Quantum supremacy using a programmable superconducting processor. Nature 574 (2019).



Amsterdam, 9 August 2021 - Qu&Co closes new investment round to accelerate and expand the development of its quantum application platforms for chemistry, multiphysics and finance.

Qu&Co, a leading European quantum computational software developer, today announced the completion of a new round of funding led by Quantonation and with investments from Runa Capital and SPInvest. The company will use these additional funds to further accelerate and expand the research and development activities for its quantum platform products for chemistry and materials simulation, multiphysics simulation and computational finance.

A recent Boston Consulting Group study estimates that quantum computing could create value of $450-850 billion in the next 15 to 30 years, with $5-10 billion available within the next 3 to 5 years.  Qu&Co is tapping into this market by developing quantum computational algorithms and platform products for quantum enhanced simulation and quantum enhanced machine learning, which BCG estimates to account for about half of the total quantum computing market.

"We are thrilled to lead this round and support Benno and Vincent and the team in the next phase of their development." said Christophe Jurczak, managing partner at Quantonation. "We’re seeing tremendous progress on the quantum computing hardware side, Qu&Co’s current and future quantum software products will be key to bring enterprises to benefit from quantum advantage"

Dmitry Galperin, partner at Runa Capital, added: "World-leading companies are already turning to quantum to find solutions to their most challenging problems and stay competitive in the future. Qu&Co's platform and algorithms make the company exceptionally well positioned to capture this trend and we are happy to support them in this journey."

Qu&Co was founded by Benno Broer (CEO) and Vincent Elfving (CTO) in 2017 in Amsterdam, the Netherlands and has R&D activities in the Netherlands, the UK, France, Germany, and Spain. The company’s clients include Johnson & Johnson, LG Electronics, Covestro, BMW Group and Airbus, it has partnerships with most of the leading US and European quantum hardware players and R&D collaborations with prominent quantum academics from top Universities around the world. The company’s previous investment round closed in June 2020.

For more information on Qu&Co please visit: https://www.quandco.com/

About Quantonation - Quantonation is an international venture capital firm headquartered in Paris, France that is dedicated to quantum technologies and innovative physics. Quantonation aims to support the transition of these disruptive deep technologies to marketable products for the industry. For more information, please visit: https://www.quantonation.com

About Runa Capital - Runa Capital is an international venture capital firm headquartered in Palo Alto, California, United States that invests in (deep) tech in areas areas like quantum computing, AI and machine learning, middleware, open-source software, cloud business software, fintech, edutech and digital health. For more information, please visit: https://runacap.com 

About SPInvest – SPInvest is the investment vehicle of Joseph Peeraer, a technology entrepreneur and deeptech investor. Later this year, Peeraer expects to formally launch an new early-stage deeptech focused venture capital fund and his investment in Qu&Co will be a cornerstone investment for this new fund.





Amsterdam, Leiden, Kyoto, 29 June 2021 - Qu&Co, Dutch and Japanese academics working together to bridge the gap between quantum computing theory and real-world applications

Qu&Co a leading European quantum software developer will be collaborating with Vedran Dunjko of the Leiden University applied Quantum algorithms (aQa) initiative and with Tomoyuki Morimae of Kyoto University on research into novel quantum computational algorithms and methods.

The collaboration will focus on the development of specialised classes of quantum algorithms for quantum enhanced machine learning and for complex system verification. Application areas of interest for the collaboration will be related to the financial sector including trading and asset management.

"Although machine learning may intuitively not seem like a quantum native problem, our recent progress in this field shows that, with the right approach, there is a lot of potential in quantum enhanced machine learning” said Benno Broer, CEO at Qu & Co.

"Quantum computing hardware is slowly becoming available, but quantum resources are still limited and so is our understanding of how we can best employ such devices. However, given the recent progress in quantum-enhanced machine learning, this application field seems a promising candidate for realizing a quantum advantage with near term quantum hardware.” Commented Vedran Dunjko, assistant professor in Leiden and a co-founder of aQa. 

One future obstacle to circumvent is how to guarantee the quality of quantum computational solutions, once these computations are beyond the reach of classical computers typically used to benchmark their results.

"Quantum computers offer not just faster computations, but also new fundamentally quantum methods to ensure the computations are correct. We will investigate if these methods can lead ways to guarantee the quality of results of quantum computations", explained Tomoyuki Morimae, associate professor in Kyoto University.

Results of this collaboration will come to benefit the budding quantum technology landscape in the Netherlands and Japan and of the wide spectrum of Qu&Co corporate clients.





Amsterdam, 8 June 2021 - Qu&Co to collaborate with Airbus on research, development and testing of quantum computational methods for flight physics simulations

Qu&Co, a leading European quantum computational software developer, has signed a collaboration agreement with Airbus for research, development and testing of quantum computational methods for flight physics simulations relevant for the European aerospace and defence sector.

The collaboration follows the recent publication by Qu&Co together with its research partner the University of Exeter (UK), of novel quantum computational methods for solving nonlinear differential equations, which in time could provide quantum advantages for solving multiphysics problems like those related to fluid dynamics.

Flight physics, the broad denomination of all scientific and engineering aspects related to the flight of aircraft, encompasses many computationally difficult problems including problems, which are governed by complex differential equations.

We are excited that Airbus recognized the relevance of our quantum computational algorithms and is willing to support our research efforts in this field.” Said Dr. Vincent Elfving, CTO at Qu&Co. “Airbus is a central player in the European aerospace and defense sector, and we would be honoured if, in time, our methods could make a significant contribution to the long-term technological sovereignty and competitiveness of this important European industry.

About Qu & Co
Qu&Co is a quantum computational software company founded in 2017 in Amsterdam, the Netherlands. Its software will empower corporate researchers to run complex chemistry and multiphysics simulations on future quantum processors with unprecedented accuracy and speed. Qu&Co’s SaaS quantum solutions include unique and patented quantum algorithms and are distributed as backend integrations to leading conventional software packages. Qu&Co clients include corporate researchers from a range of large multinationals, and it has partnerships with US and European quantum hardware players and R&D collaborations with leading Universities from around the world. For more information visit www.quandco.com.



Amsterdam, 31 May 2021 - Qu&Co announces multi-year research collaboration with Janssen Pharmaceuticals to develop and test quantum computational methods for applications in pharma R&D

Qu&Co, a European quantum computational software developer and Janssen Pharmaceuticals, Inc., one of the Janssen Pharmaceutical Companies of Johnson & Johnson, are launching a three-year research collaboration to develop and test novel quantum computational algorithms and software for applications in pharmaceutical R&D.

Computational chemistry and machine learning techniques have become powerful tools to accelerate pharmaceutical R&D and quantum computing, in-time, promises to bring further enhancements of such techniques and tools. This collaboration with Qu&Co will determine how pharmaceutical R&D could benefit from quantum computing and on what timeframe one could expect to see the earliest benefits.

Vincent Elfving, CTO at Qu&Co: “Collaborations with deep domain experts in computational chemistry are key for us to understand where the conventional best-in-class computational techniques are struggling, so that we focus our research on those areas where there is a potential promise of industry relevant quantum advantage

The collaboration will focus on developing quantum computational solutions and testing them on quantum processors. Part of the research will also employ ‘QUBEC’, Qu&Co’s platform for quantum computational chemistry and materials-science, which offers corporate researchers a glimpse of what the future of computational chemistry will look like.

About Qu & Co
Qu&Co is a quantum computational software company founded in 2017 in Amsterdam, the Netherlands. Its software will empower corporate researchers to run complex chemistry and multiphysics simulations on future quantum processors with unprecedented accuracy and speed. Qu&Co’s SaaS quantum solutions, like its chemistry and materials-science platform ‘QUBEC’, include unique and patented quantum algorithms and are distributed as backend integrations to leading conventional software packages. Qu&Co clients include corporate researchers from a range of large multinationals, and it has partnerships with US and European quantum hardware players and R&D collaborations with leading Universities from around the world. For more information visit www.quandco.com.

About Janssen Pharmaceuticals
At Janssen, we're creating a future where disease is a thing of the past. We're the Pharmaceutical Companies of Johnson & Johnson, working tirelessly to make that future a reality for patients everywhere by fighting sickness with science, improving access with ingenuity, and healing hopelessness with heart. We focus on areas of medicine where we can make the biggest difference: Cardiovascular & Metabolism, Immunology, Infectious Diseases & Vaccines, Neuroscience, Oncology, and Pulmonary Hypertension. Learn more at www.janssen.com.



Amsterdam and Seoul, 15 April 2021 - Qu&Co and LG Electronics announce multi-year research collaboration to develop and test quantum algorithms for multiphysics simulations.

Qu&Co, a leading quantum computational software developer from Europe, and LG Electronics (LG) are launching a three-year research collaboration to develop and test quantum algorithms for multiphysics simulations to solve some of LG’s most complex corporate research challenges. 

The collaboration follows the publication late last year by Qu&Co and its research partner, the University of Exeter (UK), of novel quantum computational methods which in time could provide industry-relevant quantum advantages for solving multiphysics problems.

For years it was uncertain whether quantum computers were able to treat complex nonlinear systems typical in multiphysics problems,” Said Dr. Vincent Elfving, CTO at Qu&Co. “With our new proprietary quantum algorithms for solving differential equations, we show a novel approach for treating nonlinearities directly and derivatives analytically that is compatible with near term quantum processors.”

"The disruptive potential of quantum computing will open up the boundaries of our imagination like never before," said Dr. I.P. Park, president and CTO of LG Electronics. "Quantum computing promises to change the world by transforming medicine, revolutionizing communication and improving artificial intelligence. And while we won't see quantum computers on our desks anytime soon, partnerships like the one we are initiating with Qu&Co are vital for elevating the level of applied research in this space."

About LG Electronics
LG Electonics is a global innovator in technology and consumer goods with a presence in almost every country in the world and a diverse workforce of 74,000. LG is composed of five companies – Home Appliance & Air Solution, Home Entertainment, Mobile Communications, Vehicle Component Solutions and Business Solutions. With 2019 global sales of USD 53 billion, LG is a leading manufacturer of a wide range of products from TVs, washing machines, refrigerators, air conditioners, mobile devices, digital signage and automotive components. LG is also known for its premium LG SIGNATURE and advanced LG ThinQ brands, which feature the company’s artificial intelligence technology. For more news on LG, go to www.LGnewsroom.com

About Qu & Co
Qu&Co is a quantum computational software company founded in 2017 in Amsterdam, the Netherlands. Its software will empower corporate researchers to run complex chemistry and multiphysics simulations on future quantum processors with unprecedented accuracy and speed. Qu&Co’s SaaS platform solutions include unique and patented quantum algorithms and are distributed as backend integrations to leading conventional software packages. Qu&Co serves corporate research clients from large multinationals, has partnerships with US and European quantum hardware players and R&D collaborations with leading Universities from around the world. Visit www.quandco.com for more information.




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