QUANTUM COMPUTING INC. Management’s Discussion and Analysis of Financial Condition and Results of Operations, (Form 10-Q)

This quarterly report on Form 10-Q and other reports filed Quantum Computing,
Inc. (the "Company" "we", "our", and "us") from time to time with the U.S.
Securities and Exchange Commission (the "SEC") contain or may contain
forward-looking statements and information that are based upon beliefs of, and
information currently available to, the Company's management as well as
estimates and assumptions made by Company's management. Readers are cautioned
not to place undue reliance on these forward-looking statements, which are only
predictions and speak only as of the date hereof. When used in the filings, the
words "anticipate," "believe," "estimate," "expect," "future," "intend," "plan,"
or the negative of these terms and similar expressions as they relate to the
Company or the Company's management identify forward-looking statements. Such
statements reflect the current view of the Company with respect to future events
and are subject to risks, uncertainties, assumptions, and other factors,
including the risks contained in the "Risk Factors" section of the Company's
Annual Report on Form 10-K for the fiscal year ended December 31, 2021, relating
to the Company's industry, the Company's operations and results of operations,
and any businesses that the Company may acquire. Should one or more of these
risks or uncertainties materialize, or should the underlying assumptions prove
incorrect, actual results may differ significantly from those anticipated,
believed, estimated, expected, intended, or planned.



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 the United States, the Company
does not intend to update any of the forward-looking statements to conform these
statements to actual results.



Our consolidated financial statements are prepared in accordance with accounting
principles generally accepted in the United States ("GAAP"). These accounting
principles require us to make certain estimates, judgments and assumptions. We
believe that the estimates, judgments and assumptions upon which we rely are
reasonable based upon information available to us at the time that these
estimates, judgments and assumptions are made. These estimates, judgments and
assumptions can affect the reported amounts of assets and liabilities as of the
date of the consolidated financial statements as well as the reported amounts of
revenues and expenses during the periods presented. Our financial statements
would be affected to the extent there are material differences between these
estimates and actual results. In many cases, the accounting treatment of a
particular transaction is specifically dictated by GAAP and does not require
management's judgment in its application. There are also areas in which
management's judgment in selecting any available alternative would not produce a
materially different result. The following discussion should be read in
conjunction with our financial statements and notes thereto appearing elsewhere
in this report.



Overview



Quantum Computing Inc. ("QCI" or the "Company") is a full-stack quantum
solutions company. Our mission is to be the democratizing force that brings
quantum solutions to business, academia, and government clients. Our solutions
enable subject matter experts (SMEs) and end users to get answers to critical
business problems today, using the computing solutions that best deliver those
results.


Since our formation in 2018, the Company has focused on providing software tools
and applications for several commercially available quantum computers and we
remain committed to that goal. However, following the June 2022 acquisition of
QPhoton, Inc. ("QPhoton") and its associated IP and engineering team, the
Company is now able to provide full-stack quantum information services.



The core of our quantum information services today is our Entropy Quantum
Computing (EQC) technology. We have built room-temperature, photonic quantum
information processing systems underpinned by a series of patented and patent
pending technologies. We believe this will enable us to develop and produce
multiple generations of quantum information processors with increasing
computational power, capacity, and speed. Such systems are expected to deliver
compelling performance advantages over classical computational machines and will
eventually be able to solve complex problems more effectively and efficiently in
terms of scalability, power consumption, and cost compared with current
high-performance computing technology. This technology, supported by
professional services through our "Quantum Solutions" offering, helps our
clients benefit from the technology today.



In addition, our leading-edge photonic technology and engineering teams will
enable QCI to develop quantum LIDAR and sensing systems, imaging systems,
quantum-secured network solutions, and photonic quantum chips. These important
technologies are already under development today.



                                       2




Our short-term core business model will be based on generating revenue from
selling access to our advanced quantum data processing systems via the cloud,
with the long-term model focused on selling desktop or rack-sized quantum
devices and systems to commercial and individual users. We currently offer
access to our quantum computing machines via our own in-house cloud service and
plan to eventually offer access through other commercial service providers.



In the near term, we plan to generate revenue from our "Quantum Solutions" team,
collaborating directly with customers to take them from problem formulation to
solution. This end-to-end support empowers a spectrum of clientele, from users
with little to no experience in quantum processing to advanced users capable of
independent problem formulation and execution through the service.



The Company already produces its own lithium niobate nanophotonic circuits and
has plans to scale production to meet projected demand. The Company has
announced plans to construct and operate a new state-of-the-art quantum
nanophotonics technology manufacturing and research center, which we believe
could be the world's first dedicated quantum-photonic chip manufacturer. The
plan for the facility is to produce a range of lithium niobate nanophotonic
circuits for internal use in our own product lines and for general sale in the
market. This initiative is expected to benefit from the US CHIPS and Science Act
of 2022 (the "CHIPS Act"), which allocates $52 billion for the revitalization
and onshoring of semiconductor manufacturing in the U.S. The CHIPS Act funding
includes $39 billion in manufacturing incentives and $13 billion to support
new
research and development.



QCI is focused on providing integrated quantum information acquisition,
transmission, and processing solutions, including both the user interface
software and the quantum hardware. With our proprietary full-stack technologies
that are designed using our solution-oriented system architectures, we believe
we will have a competitive advantage in the market. With an integrated
engineering team working across multiple quantum technology domains, we believe
we are uniquely positioned to leverage our expertise in software, hardware, and
nanophotonic circuits to develop quantum services and products, from quantum
chip design and manufacturing through cloud delivery and eventually sales of
hardware systems. We believe this full-stack development approach offers both
the fastest and lowest risk path to building commercially valuable quantum
machines.



Strategy



QCI's strategy has evolved to become a full stack quantum solutions company.
When QCI was formed quantum computing was a fundamentally new paradigm compared
with conventional computing, requiring a new and highly technical set of skills
to create the hardware and software to drive quantum results. The pool of people
with those skills today is limited and in high demand. In addition, the
predominant quantum software development approach, using one or more toolkits
("SDK's") to create a quantum computing program is slow and costly, and
therefore poorly suited for non-quantum experts attempting to solve real world
problems. Moreover, many types of quantum computing hardware require delicate
and expensive cryogenic isolation systems just to maintain stability, which
makes it difficult for users to interact with quantum computing systems. While
quantum computing is generally still used for research and science experiments,
the user community is demanding greater capabilities from quantum systems,
leading to frustration and comparisons to the similar market characteristics
faced by artificial intelligence in its early days - high expectations but
low
performance results.


QCI's acquisition of QPhoton, combined with QCI's significant IP work that
culminated in the development of the Company's Qatalyst software, enables the
Company to currently offer room temperature quantum computation systems through
cloud services now, as well as affordable, turn-key products in the future. This
combination of quantum hardware and software will address the steep learning
curve and highly particular skillsets generally associated with quantum
information processing, which have historically represented significant barriers
to adoption for companies and government entities looking to leverage novel
quantum computing capabilities to solve problems.



                                       3





For the past 45 years or so, silicon-based processor manufacturers have been
able to double their processing power every 18 to 24 months, a phenomenon known
in the computer industry as "Moore's Law." Recently, the computer processor
industry has found it increasingly difficult to offer faster, more powerful
processors due to fundamental physical effects limiting further size reduction
of transistors, according to We're not prepared for the end of Moore's Law, MIT
Technology Review, February 2020; https://
www.technologyreview.com/2020/02/24/905789/ (Information contained on, or that
can be accessed through, this website is not incorporated by reference in this
prospectus, and you should not consider information on this website to be part
of this prospectus). Despite this progress in transistors and computing power,
many of the world's most important computational problems are still considered
impractical to solve with classical computers of today and the foreseeable
future.



With this in mind, quantum computing represents a potential alternative approach
to the hard limits now being approached by conventional computers that utilize
silicon-based processors. This is because quantum computers apply the properties
of quantum physics to operate in a fundamentally different way. Classical
computer chips use binary bits (ones and zeros) to represent information.
Quantum computers utilize qubits, which leverage some of the properties of
quantum physics to potentially process computations that would otherwise be
intractably difficult using classical computers.



Research suggests that quantum computers may be ideally suited to run
optimization algorithms, where further advancements in approaches and quantum
computing hardware could result in computational benefit over currently used
conventional systems. See Quantum Computing for Finance: Overview and Prospects,
https://www.sciencedirect.com/science/article/pii/S2405428318300571 (Information
contained on, or that can be accessed through, this website is not incorporated
by reference in this prospectus, and you should not consider information on this
website to be part of this prospectus). The ability to solve challenging
computational problems in a reasonable period of time is of particular interest
in compute-heavy fields that include, but are not limited to: big data,
artificial intelligence, healthcare, and cybersecurity. We believe these are
natural markets for quantum computing, due to the immense compute power required
to process large data sets, which have experienced rapid growth in size and
complexity in recent years.



Products and products in development



Qatalyst



QCI's evolution into full-stack quantum computing company was enabled by the
prior creation of its Qatalyst software. The Qatalyst development platform is
QCI's answer to the broader industry's current approach to quantum software
development, which relies on highly trained scientists working with SDK's at the
circuit level, which is analogous to programming in assembly language. Unlike
SDK's, which require deep level quantum expertise to create quantum workflows,
Qatalyst is not a tool kit, but a complete platform. Qatalyst enables developers
to create and execute quantum-ready applications on conventional computers,
while also being ready to run on multiple quantum computers. Qatalyst performs
the complex problem transformations necessary to be executed on a variety of
quantum processor platforms today. Users can call upon the same Qatalyst APIs
(Application Programming Interfaces) on conventional computers to achieve
optimization performance advantages using our cloud-based solution.



                                       4




Qatalyst dramatically reduces the required time, and the associated costs, for
obtaining results from both conventional and quantum computers. It accelerates
performance and results on classic and quantum computers, with no additional
quantum programming or quantum computing expertise required. 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. Building a quantum program with an SDK is time consuming and the
resulting program must be updated constantly as QPUs evolve and change,
resulting in significant development costs. Qatalyst automatically optimizes the
same problem submitted by a subject matter expert ("SME") for multiple quantum
and classical processors. With Qatalyst, users only have to learn to use six API
calls, which can be learned in a day by most programmers. Instead of spending
months or years developing new applications and workflows requiring complex and
extremely low-level coding with SDKs, 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 Qatalyst 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 is integrated with the Amazon Web Services (AWS) cloud-based Braket
service ("AWS Braket"), which offers access to multiple Quantum Processing Units
("QPUs") including Rigetti and IonQ. Qatalyst also integrates directly with
IBM's QPUs and with QCI's own EQC and RQC systems. By using Qatalyst, users 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.


In addition, Qatalyst contains QCI's proprietary QGraph and QAmplify tools.
QGraph is a powerful transformation engine that enables 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 is a patented software technology 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.



Entropy Quantum Computer


The core of QCI's hardware offering is the Entropy Quantum Computer (EQC). The
EQC leverages the principle of open quantum systems. The EQC differs
substantially from today's Noisy Intermediate Scale Quantum (NISQ) computers
offered by most of our competitors. Quantum systems are naturally "open",
meaning, they inevitably interact with their surrounding environment. However,
as a result of these interactions, the wavefunctions describing those systems
collapse, which is the point where quantum information is lost and the NISQ
system "decoheres" which causes significant processing challenges for NISQ
architectures.



The EQC works by coupling photonic states to their surrounding environment (the
Entropy), including quantum fluctuations of the electromagnetic vacuum. This
approach runs completely counter to those being developed with other atom /
ion-based NISQ systems.



The quantum vacuum fluctuations 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.



                                       5





Today's NISQ computers are designed to produce closed quantum systems in
pristine quantum states that are isolated from the environment, but there is a
significant engineering cost to protect quantum information from the environment
to eliminate noise. This is why NISQ quantum computers usually require cryogenic
cooling, pure vacuum, vibration isolation and electromagnetic shielding. Those
requirements introduce high cost, complex maintenance, and ongoing stability
issues.



Our EQC machines are not subject to those environmental isolation requirements
and can function effectively in normal device settings (desktop or rack sizes,
room temperature, battery-powered, turn-key, etc.). In addition to the Company's
announcement of Dirac 1, our first commercially-available EQC, QCI plans to
release a series of additional EQC products starting in 2023. This family of
products will include next generations of EQC that further expand the scale and
capabilities of the EQC to broader, larger, and more complex optimization
problems. Developing this family of products will involve improving the size and
capacity of the EQC machines by continuing to innovate in the number, quality
and operational fidelity of the qubits. This will include developing technology
that operates using quantum digits ("qudits") instead of quantum bits
("qubits"). A qudit-based computer may prove better at tackling complex problems
than qubit-based computers, and may allow more computational power with fewer
components.



EQC Subscription Service



The combination of the Entropy Quantum Computer and Qatalyst has enabled QCI to
launch its cloud-based quantum computing solutions on a subscription basis.
Subscriptions are offered on an annual, quarterly, and proof of concept (short
term) basis with discounts provided for multiyear commitments. Subscription
prices are based on the expected usage from each customer. A dedicated system
subscription (currently offered as the "Dirac Dedicated Subscription"), is also
available that provides unlimited usage within the SLA included in our
agreement. QCI anticipates that our subscription service will be competitive
with the quantum computing subscription services offered by our competitors,
such as IBM, IonQ and Quantinuum. However, we believe our subscription service
will offer significant computational advantage that will differentiate it from
our competitors.


The Dirac Dedicated Subscription will provide a customer with exclusive use of a
Dirac EQC system from our datacenter without ever having to wait for other users
to complete their work nor having to worry about the time it will take to solve
their problem.



QCI is also offering potential clients the opportunity to run problems on our
EQC on an hourly-rate basis to demonstrate our computational value prior to
entering into a longer subscription. Our Dirac Introductory Rate, which can be
used for proof of concept evaluation, is an example of when this rate may apply.



Some companies utilize a per transaction-based model. Quantum computers
typically use "shots" (a shot is a single processing submission or 'run') to
measure usage on their machines and per shot models typically cost a small
fraction of a cent. Most quantum problems require hundreds of thousands of
shots. While the cost per shot is very low, the cost to solve a problem can
quickly rise to hundreds or thousands of dollars. AWS is one of the larger "per
shot" providers utilizing their AWS Braket services for companies including
IonQ, Rigetti, Oxford Quantum Circuits, and QuEra.



Usage of the Dirac EQC is done using a problem solution model, which is
different from most other quantum computers. Rather than measure the number of
shots made by our system; we solve the problem by finding the lowest ground
state energy and measure the completion of the solution in the number of seconds
or minutes it takes to complete solving the problem. While subscription sales
will be the primary strategy moving forward - we have not ruled out providing a
per usage-based model by partnering with 'per shot" providers such as AWS Braket
and Strangeworks.


Initially the EQC subscription services will all be hosted at the Company's data
center in Hoboken, New Jersey. As usage grows, we may utilize other data centers
including Amazon Web Services (AWS) for datacenter services. Many large
computing and datacenter companies like, Google and Microsoft also sell access
to third party Quantum Computers over their networks on a commission basis.
While we are focused on selling subscriptions on Dirac in our own datacenter,
there may be a time where we also provide subscriptions through Google,
Microsoft, and Amazon through their Marketplaces.



                                       6





In addition to shared subscription services and dedicated subscription services,
we intend in the future to provide to customers an on-premise implementation of
the Dirac EQC as customer demand grows and our service organization matures.
There are multiple markets which will require this type of delivery including:
the United States Government, United States Military and European Financial
Organizations, where European laws require customer data to be always be in the
control of the financial institutions. There are only a few on premise
implementations of quantum computers today and they require commitments of tens
of millions of dollars. While pricing has not been determined for the Dirac
on-premise implementation, we expect it will be very competitive with the few
on-premise quantum implementations available today from other firms.



As a full stack quantum solutions provider, while selling subscriptions in some
manner to Dirac EQCs will be the cornerstone of our business model, providing
professional services or quantum solutions support will likely be needed in many
cases, especially in the beginning of a customers' quantum journey. We partner
today with large management consulting companies as a way to scale our business
and we expect that consulting partners will continue to grow in numbers and as a
percentage of our customers. In addition, we plan to always provide a Quantum
Solutions offering for customers that prefer to work directly with a full
stack provider and customers who are using cutting edge technologies that may
not have become supported yet by our consulting partners.



As we evolve the LiDAR and sensing systems, imaging systems, and quantum-secured
networking technologies into products, the models described above will be reused
to evaluate the best pricing and routes to market for each new product. Some
will likely use the existing direct sale model that we are using for Dirac, some
may use an OEM model for inclusion in other companies' products, and others may
be sold through 1 or 2 tier distribution. Each product will be evaluated for the
best route to market to maximize the shareholder value based upon their
individual product attributes.



Quantum Reservoir Computer (RQC)




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, highly non-linear and complex 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. The third is to significantly reduce the total power consumption, by
off-loading complex and costly kernel functions to optics domains to achieve
speed-of-light processing with extreme parallelism, ultralow power, and nearly
no heat deposition. We plan to release a hybrid photonic-electronic machine for
reservoir computing in late 2022, which will be made available through the
Qatalyst platform.



                                       7




Quantum photonics applications

The acquisition of QPhoton has broadened the Company's technology portfolio and
enables us to develop a group of closely related products based on a common core
photonic technology. Products in development include:



Quantum photonics applications

The acquisition of QPhoton has broadened the Company's technology portfolio and
enables us to develop a group of closely related products, such as the EQC and
RQC, based on our common core photonic technology. Products in development
include:



Quantum Optical Chips



Optical chips will ultimately provide the greatest scalability and performance
advantages for quantum information processing, sensing and imaging. The Company
is actively working on the specification and design for a dedicated quantum
optical chip fabrication facility to develop and produce Lithium Niobate optical
chips ("Quantum Chips") for quantum information processing and other single
photon detection and sensing applications. The Company believes there is an
opportunity to benefit from the recently authorized CHIPS Act and will take
steps to establish a U.S.-based chip facility in 2023. The Company is evaluating
multiple options for a facility site, as well as potential federal, state and
regional funding incentives to help finance the project and advance quantum
technology innovation, but has not made a final decision. Construction of such a
fabrication facility for the Quantum Chips may take several years and there is
no assurance that the Company will be able to raise the necessary funding.


Quantum Imaging



One of the most exciting opportunities in development involves leveraging the
ability to count single photons and filter their associated wave functions
precisely to obtain optical imaging through otherwise opaque and dense
materials. At a minimum, quantum imaging will be a powerful supplement to modern
reconstructed computerized tomography (CT) imaging applications, where tissue
damage from high energy radiation can and needs to be avoided. Optical chips
will ultimately provide the greatest scalability and performance advantages for
quantum information processing, sensing and imaging. When all of the critical
optical components can be "embedded" on a fully integrated chip, the efficiency
and fidelity of the photonic quantum technologies will be fully realized. A
prototype has been built and is currently undergoing testing by the Company.



Cybersecurity – Quantum Networks and Quantum Authentication




The Cybersecurity field has been aware for some time of the potential threats
and benefits of quantum computing resulting from the expectation that quantum
computers will eventually have the capability to can "break" any of the
currently utilized non-quantum-based encryption methods. However, effective
cybersecurity goes well beyond encryption for protection. Effective
cybersecurity requires a holistic approach to protecting the enterprise. The
Company believes that our quantum computing capabilities may have applications
in encryption. However, initially we are applying our quantum technologies to
create secure transport layers (quantum networks) and endpoints (quantum
authentication) which will contribute greatly to the cybersecurity domain,
beyond encryption. QCI has several patents in the area of quantum-based
technologies for protection of data at rest and in quantum private
communication. QCI plans to begin commercial development of quantum networking
products in 2023 and partnerships are actively being explored.



Quantum Remote Sensing – QLiDAR




Our Quantum LiDAR ("QLiDAR") can see through dense fog and provide image
fidelity at great distances and through difficult environments such as snow,
ice, and water. Once again, by leveraging the power of quantum mechanics and
single photon detection, LiDAR systems can be greatly enhanced in their ability
to measure at improved resolution and distances as well as extend these photonic
signals to applications in vibrometry for material stress analysis, particle
size analysis, and potential remote sensing from aircraft, drones and even
satellites.



                                       8





Results of Operations


Three months completed September 30, 2022 versus. September 30, 2021



Revenues



                                     For the Three Months Ended          

For the three months ended

                                         September 30, 2022                    September 30, 2021
(In thousands)                        Amount               Mix              Amount                Mix           Change
Products                                        0                0 %                  0                 0 %            0 %
Services                                   37,646              100 %                  0                 0 %          100 %
Total                             $        37,646              100 %   $   
          0             100.0 %          100 %




Revenues for the three months ended September 30, 2022 were $37,646 as compared
with $0 for the comparable prior year period. There is no revenue comparison for
the comparable prior year period because the Company had not yet sold any
products or services. All revenue in the current reporting period is derived
from professional services provided to multiple commercial customers under
multi-month contracts.



Cost of Revenues


Cost of revenues for the three months ended September 30, 2022 was $24,891 as
compared with $0 for the comparable prior year period. There is no cost of
revenues comparison for the comparable prior year period because the Company had
not yet sold any products or services. Cost of revenues for the current
reporting period consists primarily of salary expense.



Gross Margin



Gross margin for the three months ended September 30, 2022 was $12,755 or 34% as
compared with 0% for the comparable prior year period. There is no gross margin
comparison for the comparable prior year period because the Company had not yet
sold any products or services.



Operating Expenses



Operating expenses for the three months ended September 30, 2022 were $6,846,750
as compared with $4,779,988 for the comparable prior year period, an increase of
$2,066,762 or 43%. The increase in operating expenses is due in large part to
the $644,570 increase in salary expense due to changes in the number and
composition of staff, $2,096,240 increase in other SG&A costs, $653,432 increase
in research and development expenses related primarily to hiring additional
technical staff, offset in part by a $4,639 decrease in consultant and
professional services expense, and a $1,322,841 decrease in stock-based
compensation compared with the comparable prior year period.



Net Income (Loss)



Our net loss for the three months ended September 30, 2022 was $7,569,280 as
compared with a net loss of $4,777,957 for the comparable prior year period, an
increase of $2,791,323 or 58%. The increase in net loss is primarily due to the
increase in operating expenses, noted above, as well as $241,445 increase in
interest expense related to preferred stock dividends and interest on term loan,
recorded during the three months ended September 30, 2022 compared with interest
expense of $0 during the comparable prior year period.



                                       9




Nine month period ended September 30, 2022 versus. September 30, 2021



Revenues



                    For the Nine Months Ended           For the Nine Months Ended
                        September 30, 2022                  September 30, 2021
(In thousands)       Amount               Mix             Amount           
  Mix        Change

Products                      0                 0 %                 0              0 %         0 %
Services         $      134,370             100.0 %                 0              0 %         0 %
Total            $      134,370             100.0 %   $             0          100.0 %         0 %




Revenues for the nine months ended September 30, 2022 were $134,370 as compared
with $0 for the comparable prior year period. There is no revenue comparison for
the comparable prior year period because the Company had not yet sold any
products or services. Revenue in the current reporting period is derived from
professional services provided to multiple commercial customers under
multi-month contracts.



Cost of Revenues



Cost of revenues for the nine months ended September 30, 2022 was $41,692 as
compared with $0 for the comparable prior year period. There is no cost of
revenues comparison for the comparable prior year period because the Company had
not yet sold any products or services. Cost of revenues for the current
reporting period consists primarily of salary expense.



Gross Margin



Gross margin for the nine months ended September 30, 2022 was $92,678 or 69% as
compared with $0 for the comparable prior year period. There is no gross margin
comparison for the comparable prior year period because the Company had not yet
sold any products or services.



Operating Expenses



Operating expenses for the nine months ended September 30, 2022 were $18,443,966
as compared with $12,501,818 for the comparable prior year period, an increase
of $5,942,148 or 48%. The increase in operating expenses is due to the
$1,346,326 increase in research and development expenses offset by a $2,444,350
decrease in stock-based compensation expense in the first nine months of 2022
compared with the comparable period in 2021. In addition, changes in the number
and composition of staff resulted in a $2,367,269 increase in salary and benefit
expenses, $4,576,852 increase in other SG&A costs and a $96,051 increase in
consulting expenses compared to the comparable prior year period, largely
related to an increased focus on sales and marketing. There was an increase in
legal fees of $2,207,895 in the nine months ended September 30, 2022 compared
with the comparable period in 2021 due in large part to the costs of the merger
with QPhoton.



Net Income (Loss)



Our net loss for the nine months ended September 30, 2022 was $19,807,546 as
compared with a net loss of $12,278,422 for the comparable prior year period, an
increase of $7,529,124 or 61%. The increase in net loss is primarily due to the
increase in operating expenses, noted above, as well as $1,501,445 increase in
interest expense related to dividends and amortization of the Original Issue
Discount for the Series A Convertible Preferred Stock, Warrants and Investor
Note, and interest accrued on loans, recorded during the nine months ended
September 30, 2022 compared with interest expense of $0 during the comparable
prior year period, and $218,371 decrease in other income associated with the
forgiveness of the SBA PPP Loan during the three months ended September 30,
2021.



Cash and capital resources




Since commencing operations as Quantum Computing in February 2018, the Company
has raised $27,759,904 through private placement of equity and $12,633,000
through private placements of Convertible Promissory Notes and other debt for a
total of $40,392,904 in new investment. The Company has no line of credit, and
$8,250,000 in short and long-term debt obligations outstanding. As of September
30, 2022, the Company had cash and equivalents of $10,381,376 on hand.



                                       10




The following table summarizes the total current assets, liabilities and working capital as of September 30, 2022compared to December 31, 2021:



                             September 30,      December 31,
                                 2022               2021           Increase/(Decrease)
Current Assets              $    10,794,907     $  17,221,654     $          (6,426,747 )
Current Liabilities         $     3,626,151     $   1,082,298     $           2,543,853
Working Capital (Deficit)   $     7,168,756     $  16,139,357     $          (8,970,601 )



At September 30, 2022, we had working capital of $7,168,756 as compared to
working capital of $16,139,357 at December 31, 2021, a decrease of $8,970,601.
The decrease in working capital is primarily attributable to the use of cash to
pay for operating expenses, capital investments, including the Note Purchase
Agreement with QPhoton, and the costs relating to the merger with QPhoton.


Net Cash



Net cash used in operating activities for the nine months ended September 30,
2022 and 2021 was $11,565,125 and $4,863,392, respectively. The net loss for the
nine months ended September 30, 2022 and 2021, was $19,807,546 and $12,278,422,
respectively.



Net cash used in investing activities for the nine months ended September 30,
2022 and 2021 were $86,237,313 and $11,415. The increase in investment in the
current period is primarily due to the merger with QPhoton.



Net cash provided by financing activities for the nine months ended September
30, 2022 was $91,445,157 compared with $111,567 during the same period of 2021.
Cash flows provided in financing activities during the nine months ended
September 30, 2022 were attributable to the acquisition of QPhoton, the
amortization of the original issue discount for the Series A Convertible
Preferred stock, and the Streeterville Unsecured Note. The cash flow provided by
financing activities during the period ended September 30, 2021 was primarily
attributable to issuance of common stock for the exercise of options and the
exercise of warrants.


Previously, we have funded our operations primarily through the sale of our
equity (or equity linked) and debt securities. During the first nine months of
2022, we have funded our operations primarily through the use of cash on hand.
As of November 11, 2022, we had cash on hand of approximately $8,556,768. We
have approximately $94,772 in monthly lease and other mandatory payments, not
including payroll, employee benefits and ordinary expenses which are due
monthly.



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.


Significant 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 essential to our business activities and to understanding our results of operations.



                                       11





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 nine months ended September 30, 2022 and for fiscal 2021, we did not
engage in any material off-balance sheet activities or have any relationships or
arrangements with unconsolidated entities established for the purpose of
facilitating off-balance sheet arrangements or other contractually narrow or
limited purposes. Further, we have not guaranteed any obligations of
unconsolidated entities nor do we have any commitment or intent to provide
additional funding to any such entities.



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 Monte
Carlo pricing approach would be more accurate than the Black-Scholes model over
time. Moreover, both the Binomial model, which calculates the price of an option
at each point in time during the option period, or the Monte Carlo model, which
simulates the possible movements in future stock prices and uses them to
calculate the option value, rely on critical assumptions. The Binomial model
assumes that stock markets are perfectly efficient, which may not hold for all
periods of time. The Monte Carlo simulation model assumes changes in stock
prices over time cannot be predicted from the historical trends (known as a
"random walk"), which also may not hold for all periods.



                                       12




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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Sherry J. Basler