The benefits of quantum computing application development, which can be defined as the design of software and algorithms for quantum computers, can be divided into two classifications: near-term and long-term. The near-term benefits are primarily research and development, as well as workforce development, in preparation for realizing the long-term benefits. The most commonly cited long-term benefits associated with quantum computing are:
- Solving certain classes of problems that are impossible with the supercomputers not only of today but also tomorrow
- For other classes of really hard problems, potentially solving them exponentially faster than known classical algorithms
- Revolutionizing data science by compressing huge amounts of classical data and exploring entire massive datasets for new insights
- Accelerating the training of classical machine learning models by improving the optimization of the model's parameters
- Boosting classical software and algorithms by accelerating specific calculations that are particularly well-suited for quantum computation
An Appventurez article titled “Demystifying the Impact of Quantum App Development on the Global Mobile App Industry” mentions three benefits that are cited a little less frequently than the above examples. First, quantum computers are generally recognized as being more energy efficient than supercomputers, which is good for the environment. Second, the costs associated with quantum computing can be less than using supercomputers, not only due to reduced energy consumption but also due to all the reduced overhead costs associated with solving problems in less time. And, finally, mobile applications inherently benefit from cloud-based resources, which quantum applications typically are. Our article titled “Exploring the Advantages of Cloud-Based Quantum Computing” discusses the benefits of cloud-based quantum computing, which are of course applicable to mobile enterprise applications.
Understanding Quantum App Development
A quantum app development system will usually require an understanding of the fundamental concepts of quantum computing, such as superposition and entanglement. Further knowledge of pulse control, whether of lasers, microwaves, or gate operations is usually also required. More broadly, quantum app development solutions generally require:
- The basics of quantum mechanics such as superposition and entanglement, sometimes also tunneling, and all the associated mathematics, including linear algebra
- Familiarity with either pulse control, aka analog quantum computing, or gate-based circuits, aka digital quantum computing
- The ability to distinguish between simulators, emulators, and the various modalities of real hardware, such as neutral atoms and their specific applications
- Skill with a quantum app development system, or framework, such as Bloqade, which makes development easier and faster
- Fluency in at least one programming language, typically Python, Julia, or C++; Bloqade supports both Python and Julia
- Knowledge of powerful quantum subroutines, such as quantum phase estimation (QPE), the quantum Fourier transform (QFT), and amplitude amplification
- An account through which real quantum computers can be accessed, such as the popular AWS Braket and qBraid platforms
- An understanding of the engineering challenges facing current quantum computers, such as error rates and the need for error correction (QEC)
- A grasp of “quantum advantage” and where it might be found; for example, Max Independent Set (MIS) problems are classically intractable, and yet easy to solve leveraging Rydberg blockades
- Up-to-date information concerning the latest in hardware capabilities and algorithms research; common sources include papers and conferences
- Membership in various Discord, Discourse, and Slack channels to learn from and share with the broader quantum community
A CoRLab Tech article titled “The Power of Quantum App Development in 2023” hints as to the widespread applicability of quantum app development solutions. Two of the broad use cases for quantum computing are optimization and machine learning, two problems at the heart of many enterprise applications.
Benefits of Quantum App Development
To the end user, the benefits of quantum computing are derived from the use cases. After all, there can be no benefits if a quantum computer can’t be leveraged to solve the particular problem. In addition to machine learning and optimization, our article titled “Top Applications Of Quantum Computing for Enterprises” identifies finance, material science, and natural language processing (NLP) as other high-level use cases. At the next lower level, we identify a dozen of the most popular use cases.
These numbers do not suggest that use cases are rare. Digging deeper just into optimization problems alone, we identify nine popular use cases. There are certainly not all the existing use cases, they are simply the most commonly mentioned use cases. These include algorithms with broad applicability, such as maximum independent set, minimum vertex cover, and minimum dominating set, although specific examples are given.
It is important to note that the existence of a use case indicates the exploration of quantum advantage for that specific problem. The end goal is not to use quantum computers simply because they exist, but to use quantum computers to solve problems more efficiently than we can today. Many more use cases have been researched, and many more are likely needed.
Overcoming Challenges in Quantum App Development
The initial challenge one usually faces in designing algorithms or developing software in this field is acquiring the requisite knowledge of quantum mechanics, quantum information science, and mathematics. In classical computing, one only needs knowledge of a programming language and the target subject matter, whereas in quantum computing one needs to know all that and quite a bit more. And because quantum computers are still in their earliest stages of development, yet additional challenges arise:
- Relatively few qubits are available, therefore only toy subsets of real-world problems can currently be solved experimentally
- The road to larger quantum computers is mapped out, but the road ahead for each qubit modality is not the same length
- The ability to better control qubits, as well as to control much larger numbers of qubits, is an ongoing challenge
- Hardware maintenance is not as simple as “reboot;” today’s quantum computers can not yet boast 24 x 7 x 365 availability
- Today’s qubits have high error rates as compared to transistors; error correction and mitigation techniques need further refinement
- Attempting to correct errors requires computational resources that are already scarce, and has the potential to introduce further errors
- Algorithms have to be designed that not only work, but that also demonstrate advantages in speed and precision over classical algorithms
- Not only does algorithm design become more challenging as problems scale in size, actually implementing large quantum circuits becomes a problem in its own right
- Integration with high performance computing (HPC) may be necessary to accelerate any classical bottlenecks within applications
- The frameworks and tools with which to develop applications are themselves still in development and potentially buggy
- Because of the wide range of knowledge and skills required, development is better suited for mufti-disciplinary teams than for individuals
- The use of cloud resources raises privacy and intellectual property concerns, especially in regard to the storage of personal information for medical applications
Fortunately, free quantum app development training is available from multiple hardware and software providers. QuEra, for example, routinely schedules training sessions, webinars, and informal online gatherings. We are continuously making additional educational resources available.
Free Quantum App Development Tools: The Key to Accessibility
Hardware providers, in particular, want you to use their hardware. Therefore, free quantum app development tools are abundant. These have a wide range of scope, however, from translating from one framework to another to a full-blown portal with hosted Jupyter notebooks. Some of what you may find out there includes:
- Portals such as qBraid that host Jupyter notebooks in both Python and Julia, have sample code libraries, as well as various training resources; includes credits for using real hardware
- Simpler development environments, such as Google Colab, which can be configured as-needed for different research projects
- Frameworks ranging from universal quantum computing to solving specific problems, such as machine learning and simulating quantum computation with neutral atoms
- Quantum computer simulators and emulators which allow algorithms to be tested at small scales before paying to access real hardware
- Textbooks, other books, university courses, summer schools, hackathons, webinars, tutorials, videos, podcasts, and blog articles covering every conceivable tool and topic
- Cloud hosting, such that users need not be concerned with purchasing, configuring, or maintaining anything, only using
- Community-building support sites, such as Discord, Discourse, and Slack, which facilitate both troubleshooting and collaboration
This list isn’t all-inclusive. While there are ongoing efforts to commercialize quantum computing, there are also efforts to keep it as democratized and accessible as possible. For the foreseeable future, free resources ought to continue to be abundant.