QUANTUM COMPUTING INC. This quarterly report on Form 10-Q and other reports filed
Although the Company believes that the expectations reflected in the
forward-looking statements are reasonable, the Company cannot guarantee future
results, levels of activity, performance, or achievements. Except as required by
applicable law, including the securities laws of
Our consolidated financial statements are prepared in accordance with accounting
principles generally accepted in
Overview
The Company is focused on providing full-stack quantum computing systems. We believe there is significant business opportunity in the quantum computing industry, and that the quantum computing has the potential to disrupt several global industries. Independent of when quantum computing delivers compelling performance advantage over classical computing, the software tools and applications necessary for accelerating real-world problems must be developed to deliver on quantum computing's full promise.
Quantum computing is a fundamentally new paradigm compared with conventional silicon-based computing, requiring a new and highly technical set of skills to create the software that will drive quantum results. Organizations seeking to gain advantage from the promise of quantum technology must acquire and develop skills in quantum mechanics, mathematics and physics, and a deep knowledge of the ever-changing quantum hardware. The pool of people with those skills today is limited and in high demand.
In order to address the steep learning curve and highly particular skillset associated with quantum computing, the Company is developing "quantum ready" software applications and solutions for commercial and government entities looking to leverage the expected future performance of quantum computing. We are focused on being an enabler - creating software that provides the advantages of advanced computing hardware for forward-thinking clients.
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By reducing the barriers to adoption for commercial and government entities in using quantum computing technologies to solve their most complex problems, we believe our products will accelerate quantum technology adoption similar to the adoption curve that has been witnessed with artificial intelligence. To this end, we are leveraging our collective expertise in finance, computing, mathematics and physics to develop a suite of applications that may enable global industries to utilize quantum computers, quantum annealers and digital simulators to improve their processes, profitability, and security.
The Company's flagship software solution, Qatalyst, is the industry's only quantum application accelerator. It ensures that today's SMEs can continue to create and solve the complex computations demanded by organizations to optimize supply chains, logistics, emergency responses, clinical trials, and more. Qatalyst software masks the complexity of quantum programming via the Q API (Qatalyst Application Programming Interface), a powerful API comprised of six function calls for complex computations. Instead of spending months or years developing new applications and workflows requiring complex and extremely low-level coding, users or applications can submit a problem to Qatalyst after licensing the software, via the Q API. In practice, users have utilized Qatalyst's simple API and familiar constructs to solve their first complex problem within a week, as compared to the 6-12 months or more associated with writing a single quantum software program using vendor toolkits.
The Company is focused on solving real-world problems with Qatalyst, including supply chain and logistics optimization and crisis management, as well as community detection opportunities such as drug discovery and fraud detection.
The Company is actively partnering with quantum computing leaders in both hardware and software. As an Amazon AWS partner, the Company uses the AWS Braket service to connect to multiple quantum computers, including Rigetti, DWave, and IonQ. The same problem can be submitted to any of these QPUs or classical processing units (CPUs) with no need for API call changes. Users seamlessly can submit the same problem to diverse quantum computers (QPUs) to determine which QPU will provide the best answers to their complex problem.
Strategy
While the majority of the quantum computing market is focused on quantum computing hardware, the Company realized the traditional software development toolkit ("SDK") approach to creating quantum computing software is poorly suited for non-quantum experts, given the completely new programming paradigm.
This represents a significant barrier to entry for companies looking to leverage novel quantum computing capabilities for their business needs. Utilizing quantum computers for real-world problems requires an abstract blend of a wide range of computing and non-computing expertise, including:
? Subject Matter Expertise (SME): As with any problem, the first step is for
a business expert to rigorously define and describe what information
and/or results the business requires.
? Programming Excellence: In the classical computing world, a programmer
will take the problem defined by a SME (subject matter expert) and
implement it using standardized applications to run on the computer. In
quantum computing, programmers are required to explicitly program it for
the quantum computer they have access to, requiring a deep understanding
of sophisticated areas of expertise as described below.
? Mathematics: The problems that are attractive for being solved using
quantum computers require significant mathematical expertise to a)
optimize the data and problem for quantum computers, b) create the
quantum-specific algorithms and formulas required to solve the problem, c)
iterate upon the results in a way that optimizes the performance, cost and
quality of result. Mathematics is at the core of the many steps involved
in quantum computing for optimizing, compressing and applying algorithms
to the data for obtaining truly optimal results.
? Quantum Mechanics: Quantum computing demands deep knowledge of the
principles driving the computing itself. Unlike classical computers which
utilize 0 or 1 bits, quantum computers utilize qubits, which leverage
concepts of quantum mechanics such as probabilistic computation,
superposition, and entanglement. Experts much understand these concepts to
create the algorithms necessary to solve problems on a quantum computer.
They must know how to "map" problems and their associated data into
problems that are optimized in the specific way required for a quantum
computer to accept and process the problem.
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? Quantum Hardware Knowledge: QPUs (Quantum Processing Units) require that
programmers manage the configuration, actions, and overall operations of
all the underlying circuits utilized in solving the problem. For example,
the programming to configure and access QPUs is low level and extremely
complicated. This coding is proprietary to each vendor's QPU idiosyncratic
requirements, not to mention, unique to the specific count and version of
QPUs in the system, right now. When the system is expended or a QPU
upgraded, all the code has to be rewritten.
As one would expect given the dramatic differences in quantum computer hardware architectures currently under development, quantum software requires a dramatic shift from classic software. A user would have to literally have to create every single circuit, gate, algorithm, action and process in low level software. Moreover, the collective requirements imposed upon companies looking to utilize quantum computers can require a training period of a year or longer, even for a highly qualified subject matter expert. Consequently, the time, difficult and expense of hiring such a diverse and deeply knowledgeable team to create quantum applications and workflows limits any organization's ability to move forward quickly with the power of quantum computing.
The Company's strategic goals are as follows:
1) Deliver production-ready software and the required quantum hardware in the
cloud that de-risks the shift to quantum computing and makes it simple and
cost effective for organizations to begin leveraging quantum computing.
2) Empower SMEs and programmers to access the power of quantum computing
without the prerequisite quantum expertise.
3) Eliminate the vendor lock-in created by the low-level coding required for
individual QPUs by allowing users to freely select the best QPU for their
specific problem with no low-level coding or programming changes.
4) Deliver the best performance results (speed, quality and diversity) at the
lowest cost for our users.
Products and Products in Development
Qatalyst
Qatalyst is our answer to the current state of the quantum computing industry. As the industry's first publicly available Quantum Application Accelerator, Qatalyst enables developers to create and execute quantum-ready applications on conventional computers, while being ready to run on quantum computers where those systems achieve performance advantage. Qatalyst performs the complex problem transformations necessary to be executed on a variety of quantum platforms today, and users can call upon the same Qatalyst APIs (Application Programming Interfaces) to achieve optimization performance advantages on conventional computers using our cloud-based solution.
Qatalyst dramatically reduces the time-to-quality results and the associated costs for both conventional and quantum computers. Unlike more common toolsets that require deep level quantum expertise to build new quantum problems and workflows, Qatalyst is not a tool kit, but a complete platform. It accelerates performance and results on classic and quantum computers, with no additional quantum programming or quantum computing expertise required. This is why it is unique in its approach to the quantum computing industry. Instead of invoking a team of quantum specialists to transform an optimization problem, an SME or programmer submits their current problem via a software API to the Qatalyst cloud-based platform. Qatalyst manages the workflow, optimizations, and results, without any further intervention by the user. Qatalyst provides a unique advantage to reduce applications development risks and costs by eliminating the need for scarce high-end quantum programmers.
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Qatalyst is integrated with the Amazon Cloud BRAKET API, offering access to multiple Quantum Processing Units ("QPUs") including DWave, Rigetti, and IonQ. Qatalyst also integrates directly with IBM's QPUs.
By using Qatalyst, application developers can run their applications on any or all of the available QPUs by merely selecting which QPU they prefer to run on based on the desired performance results of the application. We believe this provides a substantial advantage over any other toolkit or platform in the market today. These advantages are significant not just for application developers but for any company that is considering using or exploring quantum computing technology for business applications.
Qatalyst also eliminates the need for the low-level hardware programming expertise required by toolkits. This programming is time consuming and must be updated constantly as QPUs evolve and change, resulting in significant development costs. Qatalyst automatically optimizes the same problem submitted by a SME for multiple Quantum and Conventional Processors. The SME or programmer selects one, or many, processing resources and the problem is submitted by Qatalyst. This is an enormous advantage over any tool set in the market today. These advantages are significant not just for application developers but for any company that is considering using or exploring quantum computing technology for business applications.
The Company's innovative Qatalyst software masks the complexity of quantum programming via the Q API, a powerful six call API that users can learn in a day. Instead of spending months or years developing new applications and workflows requiring complex and extremely low-level coding, users, workflows or applications can immediately submit a problem to Qatalyst within a day, using the same familiar constructs they use right now, via the Q API. Users have utilized Qatalyst's simple API and familiar constructs to solve their first complex problem within a week, as compared to the 6-12 months associated with quantum software toolkits.
Qatalyst Features
Today, SMEs can leverage the power of Qatalyst to solve high-value discrete optimization problems present in banking & finance, insurance underwriting, life sciences (bio/pharma), oil & gas, logistics & supply chain and cybersecurity. Currently, Qatalyst offers the following features:
? Quantum-ready engines tuned for complex computations. These engines
automatically optimize, submit, and iterate to return excellent, diverse
results for supply chain and other constrained optimization problems.
? Transparent abstraction from quantum hardware variance. Qatalyst
eliminates the need to write low-level, assembly-type code to support
different vendors' quantum hardware architectures, such as D-Wave,
Rigetti, IBM and ION-Q. The same problem can run seamlessly across all
quantum types and architectures.
? Qatalyst Core: an engine that utilizes sophisticated mathematics, quantum
transformation and iterative processing to find highly optimal answers
across both classic and quantum computers. For example, LaGrange
multipliers, which work to compress and simplify the problem prior to
constraint optimization. The Core applies these advanced mathematical
techniques, based on the type of problem and processing required.
? QGraph: a powerful transformation engine that empowers SMEs to submit and
analyze graph models as part of their complex optimizations. QGraph
accepts familiar graph models and functions including Clique Cover,
Community Detection and Partitioning.
? QAmplify: a suite of quantum software technologies that expands the
processing power of any current quantum computer by as much as twenty
times. QAmplify is capable of supercharging any quantum computer to solve
real-world realistic business problems, and is designed to work on gate
model quantum computers as well as quantum annealers.
? Qontrol: a portal that provides administrative management tools for user
administration, request control, statuses and alerts. Qontrol also enables
system administrators and users to import Qatalyst results into popular
analysis applications such as Excel or Tableau.
Entropy Quantum Computer
The Entropy Quantum Computer (EQC) is based on the principal that photons are intrinsically stable. Quantization of stable, photonic states can be achieved by coupling to the noise and loss from the "vacuum fluctuations" in the quantum environment (The Entropy). This approach runs completely counter to those being developed with other atom / ion-based systems. The quantum vacuum states are ubiquitous and can be used to capture every possible outcome in a very large system with many configurations, simultaneously, making the approach ideal for fast and accurate computations in optimization problems. The EQC consists of a rich manifold of quantum states that are fully connected through quantum entanglement and allows for unprecedented problem-solving scale and speed.
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Reservoir Quantum Computer
Reservoir computing is a framework for computation derived from recurrent neural network theory, which maps input signals into higher dimensional computational spaces through the dynamics of a fixed, non-linear system called a reservoir. The input signal is fed into the reservoir, which is treated as a "black box". A simple readout mechanism is trained to read the state of the reservoir and convert it to the desired output. There are several key benefits to this framework. The first key benefit of this framework is that training is performed only at the readout stage, as the reservoir dynamics are fixed. This makes the data training process very fast, since there is no recursive back projection of trained data through the reservoir. The second is that the computational power of naturally available systems, both classical and quantum mechanical, can be conveniently utilized to reduce the effective computational cost.
Results of Operations
Three Months Ended
Revenues
For the Three Months For the Three Months
Ended Ended
June 30, 2022 June 30, 2021
(In thousands) Amount Mix Amount Mix Change
Products 0 0 % 0 0 % 0 %
Services 65,484 100 % 0 0 % 100 %
Total $ 65,484 100 % $ 0 100.0 % 100 %
Revenues for the three months ended
Cost of Revenues
Cost of revenues for the three months ended
Gross Margin
Gross margin for the three months ended
Operating Expenses
Operating expenses for the three months ended
Net Income (Loss)
Our net loss for the three months ended
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Six Months Ended
Revenues
For the Six Months Ended For the Six Months Ended
June 30, 2022 June 30, 2021
(In thousands) Amount Mix Amount Mix Change
Products 0 0 % 0 0 % 0 %
Services $ 96,724 100.0 % 0 0 % 0 %
Total $ 96,724 100.0 % $ 0 100.0 % 0 %
Revenues for the six months ended
Cost of Revenues
Cost of revenues for the six months ended
Gross Margin
Gross margin for the six months ended
Operating Expenses
Operating expenses for the six months ended
Net Income (Loss)
Our net loss for the six months ended
Liquidity and Capital Resources
Since commencing operations as
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The following table summarizes total current assets, liabilities and working
capital at
June 30, December 31,
2022 2021 Increase/(Decrease)
Current Assets $ 7,250,401 $ 17,221,654 $ (9,971,253 )
Current Liabilities $ 1,298,851 $ 1,082,298 $ 216,553
Working Capital (Deficit) $ 5,951,550 $ 16,139,357 $ (10,187,807 )
At
Net Cash
Net cash used in operating activities for the six months ended
Net cash used in investing activities for the six months ended
Net cash provided by financing activities for the six months ended
Previously, we have funded our operations primarily through the sale of our
equity (or equity linked) and debt securities. During the first six months of
2022, we have funded our operations primarily through the use of cash on hand.
As of
On a long-term basis, our liquidity is dependent on continuation and expansion of operations and receipt of revenues. Demand for the products and services will be dependent on, among other things, market acceptance of our products and services, the technology market in general, and general economic conditions, which are cyclical in nature. In as much as a major portion of our activities will be the receipt of revenues from the sales of our products, our business operations may be adversely affected by our competitors and prolonged recession periods.
Critical Accounting Policies and Estimates
Certain of our accounting policies require the application of significant judgment by our management, and such judgments are reflected in the amounts reported in our condensed consolidated financial statements. In applying these policies, our management uses judgment to determine the appropriate assumptions to be used in the determination of estimates. Those estimates are based on our historical experience, terms of existing contracts, our observance of market trends, information provided by our strategic partners and information available from other outside sources, as appropriate. Actual results may differ significantly from the estimates contained in our condensed consolidated financial statements.
We have identified the accounting policies below as critical to our business operations and the understanding of our results of operations.
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Revenue
The Company recognizes revenue in accordance with ASC 606 - Revenue from Contracts with Customers. Revenue from time and materials-based contracts is recognized as the direct hours worked during the period times the contractual hourly rate, plus direct materials and other direct costs as appropriate, plus negotiated materials handling burdens, if any. Revenue from units-based contracts is recognized as the number of units delivered or performed during the period times the contractual unit price. Revenue from fixed price contracts is recognized as work is performed with estimated profits recorded on a percentage of completion basis. The Company has no cost reimbursement ("cost-plus") type contracts at this time.
Off Balance Sheet Arrangements
During the six months ended
Critical Accounting Estimates
We have identified the following critical accounting estimates. An accounting estimate is "critical" if it (a) requires Company management to make assumptions about matters that are highly uncertain at the time of the estimate, and also (b) Company management reasonably could have used different estimates in the current period, or changes in the accounting estimate that are reasonably likely to occur from period to period, would have a material impact on the presentation of the Company's financial condition, changes in financial condition or results of operations.
The Company uses the Black-Scholes model to calculate the fair value of stock options and derivatives. The Black-Scholes model, developed in 1973, is a differential equation which requires five input variables, the strike price of an option, the current stock price, the time to expiration, the risk-free rate, and the volatility of the Company common stock. The Black-Scholes model is widely used for pricing options but it does rely on certain assumptions about the market which may not be correct over time. Specifically,
? No dividends are paid out during the life of the option.
? Markets are random (i.e., market movements cannot be predicted).
? There are no transaction costs in buying the option.
? The risk-free rate and volatility of the underlying asset are known and
constant.
? The returns of the underlying asset are normally distributed.
? The option is European and can only be exercised at expiration.
To the extent that any of these assumptions is not correct, that could result in the over or under pricing of the stock options involved. The assumption that the risk-free rate (the Company uses the one-year US Treasury Bill rate as a proxy for the risk-free rate) can vary over time, and if the T-Bill rate varies substantially over the life of the stock option that could affect the pricing. Similarly, the volatility of the Company's common stock, also known as the Beta, has moved within a limited range over the past year, but the volatility of any security can change over time, which would affect the option pricing calculation. Another critical estimate relating to option pricing is the default rate, which means the estimate of granted options that will either expire unexercised, or be forfeited, over the life of the stock options. If the Company's estimate of the default rate turns out to be substantially different from the actual, experienced default rate, that could result in over or under estimating the total option expense.
The Black-Scholes model is not the only available approach for pricing stock
options, the Company could have used a Binomial pricing model or a Monte Carlo
simulation model. However, there is no assurance that either a Binomial or
Another area of critical accounting estimates involves determining the fair market value and useful life of the intangible assets acquired by the Company through the merger with QPhoton. In the absence of market pricing for the intangible assets, the Company relied on comparison with similar transactions to arrive at estimates of value as well as useful life. The Company will perform periodic assessments of the intangible assets for impairment, but if any of the initial estimates are incorrect, that could result in a calculation of amortization expense that is too high or too low.
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