Reader small image

You're reading from  Financial Modeling Using Quantum Computing

Product typeBook
Published inMay 2023
PublisherPackt
ISBN-139781804618424
Edition1st Edition
Right arrow
Authors (4):
Anshul Saxena
Anshul Saxena
author image
Anshul Saxena

Professor Anshul Saxena is a quantum finance instructor at Christ University. His current research focus is abouton discovering the role of quantum computing in solving complex financial problems. He has filed three Indian patents and holds an international patent. He has authored a popular book on HR Analytics and has developed an automated Ppython library "Cognito" for data preprocessing. He has over a decade of work experience spreading across IT and financial services companies like TCS and Northern Trust in various business analytics and decision sciences roles. He has worked as a consultant and trainer with IBM ICE group and has trained more than 500 faculties pan India. Mr. Saxena has also worked as a Corporate Trainer and has conducted training on data science for more than 600 IT employees. He is a SAS certified predictive modeler and has recently completed a certificate in "Quantum computing for managers" for BIMTECH. He holds an MBA degree in Finance from IBS Bangalore and is pursuing his Ph.D. in Financial Risk Analytics
Read more about Anshul Saxena

Javier Mancilla
Javier Mancilla
author image
Javier Mancilla

Javier Mancilla is a Senior Data Scientist, and a Quantum Business and Programming Consultant. He is a Ph.D. candidate and Master in Data Management and Innovation. He has more than 15 years of experience in digital transformation projects, withand in the last 8 years mostly dedicated to artificial intelligence, machine learning, and quantum computing, with more than 35 projects executed around these technologies. He has more than 8 certifications in quantum computing matters from institutions like MIT xPro, KAIST, IBM, Saint Petersburg University, and BIMTECH. He also was selected as one of the Top 20 Quantum Computing Linkedin Voices by Barcelonaqbit (quantum organization in Spain). Currently, he has the role of quantum machine learning advisor for different companies and organizations in Europe and Latin America and is also an I + D + i (Investigation, Development, and Innovation) evaluator for different governments in LATAM such as Chile and Paraguay
Read more about Javier Mancilla

Iraitz Montalban
Iraitz Montalban
author image
Iraitz Montalban

Iraitz Montalban is currently Quantum Software Engineer for Kipu Quantum GmbH and PhD candidate at the University of the Basque Country in Quantum Machine Learning. He holds several master's degrees in Mathematical modelling, Data Protection and Quantum Technologies as well. Has hold positions of responsability in large organizations as well as coordinated Innovation practices in all of then given his trajectory as a reseacrher in AI and ML disciplines and his more than 15 years of experience in this field. He activelly collaborates with different universities and education institutions designing the curriculum and teaching in programs around BigData and Advanced Analytics
Read more about Iraitz Montalban

Christophe Pere
Christophe Pere
author image
Christophe Pere

Christophe Pere is an Applied Quantum Machine Learning Researcher and Lead Scientist originally from Paris, France. He has a Ph.D. in Astrophysics from Université Côte d'Azur. After his Ph.D., he left the academic world for a career in Artificial Intelligence as an Applied Industry Researcher. He learned quantum computing during his Ph.D. in his free time, starting as a passion and becoming his new career. He actively democratizes Quantum Computing to help people and companies enter this new field.
Read more about Christophe Pere

View More author details
Right arrow

The business application of quantum computing

Although it is still in its infancy and yet to achieve a commercial application, quantum technology holds much promise. In the near future, quantum computers will be able to help accelerate the pace of solving complex problems in conjunction with classical computers. In this section, you will learn about the business applications of this wonderful technology.

Global players in the quantum computing domain across the value chain

According to a McKinsey report (Quantum computing funding remains strong, but talent gap raises concern, https://tinyurl.com/5d826t55), quantum technology has attracted a total investment of $700 million from various governments and funding agencies. The promise shown by this technology has prompted the industry to fund ongoing research in various universities and labs. D-Wave was the first company to pioneer the quantum computing solution in 1999, through quantum annealing. Since then, other companies such as IBM have built a robust community of researchers and end users alike to propagate the use of quantum computers. The following is a brief list of the companies doing pioneering work in the field of quantum technology:

  • IonQ (NASDAQ: IONQ): IonQ was founded in 2015 by Christopher Monroe and Jungsang Kim. IonQ has received total funding of $432 million. IonQ builds quantum computers based on ion trap technology. It provides quantum computers as Platform as a Service (PaaS) to service providers.
  • Rigetti (NASDAQ: RGTI): Rigetti Computing was founded in 2013 by Chad Rigetti. It has currently received funding of $500 million. Rigetti has developed a quantum computer based on superconducting technology.
  • Quantum Computing Inc.: Quantum Computing Inc. focuses on providing software and hardware solutions to the end user. It is also focusing on developing business use cases for companies, thus showcasing the potential of quantum computing in the near future.
  • Archer (ASX: AXE): Archer is an Australian company that is conducting research on developing a quantum computer at room temperature. It was founded by Dr. Mohammad Choucair. It aims to produce a quantum computer that can have a widespread reach.
  • D-Wave (coming soon via SPAC merger): D-Wave is credited with introducing the world’s first quantum computer for commercial use. It uses the quantum annealing technique to develop quantum solutions for the end user. It offers a limited but powerful piece of technology with 5,000 qubits of quantum computer at its disposal, which has a lot of potential business applications.
  • Quantinuum: Quantinuum was formed as a result of a merger between Cambridge Quantum and Honeywell Quantum Solutions. While the primary focus of Cambridge Quantum was on developing the operating system and software for quantum computers, Honeywell has focused primarily on developing the quantum computer using ion trap technology.

Global players across the value chain in the quantum computing domain include giants such as IBM, Microsoft, and Google, and well-funded start-ups such as Rigetti, IQM, and Quantinuum. These companies have invested in different types of technologies (hardware as well as software) to catapult the research in this technology domain.

In the subsequent segment, we will evaluate the roadmap provided by different technology giants to achieve full-scale quantum supremacy.

Building a quantum computing strategy implementation roadmap

Building quantum advantage to solve real-time business problems is the end goal of many companies operating in the quantum realm. This technology is perceived to aid companies in solving large-scale problems. Recently, BMW has commissioned a million-dollar challenge to discover a solution to its inventory scheduling problem using the AWS Amazon Braket platform. In Figure 1.9, you can chart the route that could potentially lead to the era in which quantum supremacy can be achieved, and see how we can solve more problems using quantum computing:

Figure 1.9 – Quantum computing era

Figure 1.9 – Quantum computing era

Broadly, the quantum era can be divided into three parts:

  • Noisy intermediate-scale quantum (NISQ): This era is marked by the availability of a lesser number of good-quality qubits (<50 to 100) to solve real-world problems. The word noisy refers to the tendency of the qubits to lose their quantum state due to disturbances. It is expected that the current technology setup will be able to come out of the NISQ era by 2030.
  • Broad quantum advantage: IonQ has defined the broad quantum advantage as the advent of the era where quantum computers are available for developers and end users to solve real-life problems. Based on the consensus developed by industry practitioners, 72-qubit systems will start aiding the industry in solving commercial-grade problems. Thus, it will be possible in the future to access the platform enabled by demonstrating high-level application programming and HMI functions.
  • Full-scale fault tolerance: This era refers to large-scale quantum computers that have achieved two-qubit gate fidelity of 99.5%. By 2040, it is expected that the existing efforts will help in solving the problem of decoherence (leakage of information due to large numbers of qubits), and will enable organizations to take full advantage of this amazing technology.

Quantum technology in the near term is available for end users in the form of hybrid computing. To harness the full potential of existing quantum computers, players such as D-Wave and Rigetti have started providing an interface between classical and quantum computing via microprocessors. While classical components take care of communication with end users, quantum microprocessors are used in solving NP-hard problems. Quantum technology, through quantum annealers and universal quantum computers, and using technologies such as superconducting and ion trap, will be able to harness its full potential in the near future.

In the next section, let’s have a look at what kind of people are needed to build quantum technology and its ecosystem.

Building a workforce for a quantum leap

Quantum technology needs a variety of people in the workforce to harness its true potential. The entire technology stack can be divided into hardware, software, and related technologies. Currently, the technology has called for scientific research and technology implementation experts. According to a survey report prepared by Forbes, a graduate must have a primary degree in STEM to understand the basic workings of quantum computers. A research-oriented mindset is essential to further investigate the development of quantum computers. To achieve scientific breakthroughs related to the development of computer hardware, a researcher must have a deep understanding of the underlying technologies such as annealing, superconducting, and ion trap. These technologies are at the forefront of the scientific breakthroughs that can be achieved with the help of a knowledgeable workforce.

In addition to building a quantum computer, it is also challenging to operate one. The current focus of software development is to write low-level programs that can interface with the memory core of the quantum computer. IBM and Google are among the companies that have developed Python-based software development toolkits (SDKs) such as Qiskit and Cirq. Programs such as IBM Summer School are good starting points for developers to get acquainted with the methodology of software interfacing with quantum memory processors. Due to the limitations of the current technology in the quantum field, a lot of emphasis is given to developing a hybrid computer. A software developer needs to know about cloud computing to operate a quantum computer. Most quantum computers are nested in big rooms at below-freezing temperatures, and can be accessed remotely using cloud computing. The algorithms written for quantum computers are also used to boost the performance of existing machine learning algorithms.

Quantum solutions also include aided technologies, making quantum technologies an exciting field to work in. Quantum sensors, annealers, and the internet are the potential applications of quantum mechanics. In addition, quantum algorithms have also shown promise in solving problems related to finance, supply chain, healthcare, and cryptography. Figure 1.8 summarizes the discussion related to the aptitudes and qualifications related to starting a career in the field of quantum technologies:

Research Areas

Application

Potential Qualification

Hardware

Quantum Mechanics, Theoretical Physics, Applied Physics

Superconducting Ion Traps, Quantum Dot

PhD, Master’s in Quantum Physics

Software

Quantum Information Science

Quantum Algorithms, Quantum Machine Learning

Software Development, Master’s in Computer Science

Quantum Business Technologies

Optimization, Simulation and Cryptography

Finance, Supply-Chain, Healthcare

Business Evangelist, Domain Expert

Figure 1.10 – List of qualifications

From Figure 1.10, it can be observed that a potential candidate for quantum technologies needs some background in STEM. Research aptitude and a capacity to learn, unlearn, relearn, and apply new concepts are a must to sustain in this dynamic field. Since it’s a research-oriented field, companies’ inclination is more toward inducting doctoral candidates from relevant fields. However, there is a significant demand for software engineers who can write code for hybrid computers to solve problems in a faster and more accurate way.

Previous PageNext Page
You have been reading a chapter from
Financial Modeling Using Quantum Computing
Published in: May 2023Publisher: PacktISBN-13: 9781804618424
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
undefined
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime

Authors (4)

author image
Anshul Saxena

Professor Anshul Saxena is a quantum finance instructor at Christ University. His current research focus is abouton discovering the role of quantum computing in solving complex financial problems. He has filed three Indian patents and holds an international patent. He has authored a popular book on HR Analytics and has developed an automated Ppython library "Cognito" for data preprocessing. He has over a decade of work experience spreading across IT and financial services companies like TCS and Northern Trust in various business analytics and decision sciences roles. He has worked as a consultant and trainer with IBM ICE group and has trained more than 500 faculties pan India. Mr. Saxena has also worked as a Corporate Trainer and has conducted training on data science for more than 600 IT employees. He is a SAS certified predictive modeler and has recently completed a certificate in "Quantum computing for managers" for BIMTECH. He holds an MBA degree in Finance from IBS Bangalore and is pursuing his Ph.D. in Financial Risk Analytics
Read more about Anshul Saxena

author image
Javier Mancilla

Javier Mancilla is a Senior Data Scientist, and a Quantum Business and Programming Consultant. He is a Ph.D. candidate and Master in Data Management and Innovation. He has more than 15 years of experience in digital transformation projects, withand in the last 8 years mostly dedicated to artificial intelligence, machine learning, and quantum computing, with more than 35 projects executed around these technologies. He has more than 8 certifications in quantum computing matters from institutions like MIT xPro, KAIST, IBM, Saint Petersburg University, and BIMTECH. He also was selected as one of the Top 20 Quantum Computing Linkedin Voices by Barcelonaqbit (quantum organization in Spain). Currently, he has the role of quantum machine learning advisor for different companies and organizations in Europe and Latin America and is also an I + D + i (Investigation, Development, and Innovation) evaluator for different governments in LATAM such as Chile and Paraguay
Read more about Javier Mancilla

author image
Iraitz Montalban

Iraitz Montalban is currently Quantum Software Engineer for Kipu Quantum GmbH and PhD candidate at the University of the Basque Country in Quantum Machine Learning. He holds several master's degrees in Mathematical modelling, Data Protection and Quantum Technologies as well. Has hold positions of responsability in large organizations as well as coordinated Innovation practices in all of then given his trajectory as a reseacrher in AI and ML disciplines and his more than 15 years of experience in this field. He activelly collaborates with different universities and education institutions designing the curriculum and teaching in programs around BigData and Advanced Analytics
Read more about Iraitz Montalban

author image
Christophe Pere

Christophe Pere is an Applied Quantum Machine Learning Researcher and Lead Scientist originally from Paris, France. He has a Ph.D. in Astrophysics from Université Côte d'Azur. After his Ph.D., he left the academic world for a career in Artificial Intelligence as an Applied Industry Researcher. He learned quantum computing during his Ph.D. in his free time, starting as a passion and becoming his new career. He actively democratizes Quantum Computing to help people and companies enter this new field.
Read more about Christophe Pere