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References

1. Basic Quantum Algorithms.pdf

  • "Quantum computing is evolving so quickly that forces us to revisit, rewrite, and update the basis of the theory. Basic Quantum Algorithms revisits the first quantum algorithms."
  • qubit vs bit
    • The basic memory unit of a classical computer is the bit, which assumes 0 or 1. Usually, the bit is implemented using two distinct voltages, following the convention that null or low voltage represents bit 0 and high voltage represents bit 1. To determine whether the output is bit 0 or 1 at the end of the computation, it is necessary to measure the voltage. The basic memory unit of a quantum computer is the qubit, which also assumes, at the end of the computation, 0 or 1. The qubit is implemented using an electric current in a small super- conductor, following the convention that clockwise current represents 0 and counter-clockwisecurrent represents 1, or the other way around. The difference from the classical device happensduring the computation since the qubit admits the simultaneous coexistence of 0 and 1. Dur-ing the computation, that is, before the measurement, the state of a qubit is represented by a norm-1 two-dimensional vector and the states of a qubit corresponding to 0 and 1 are |0i and |1i. The definition of state is a vector of norm 1 in a complex vector space endowed with the inner product presented in the previous Section.1 The state can be thought of as the “value” of the qubit before the measurement. Quantum coexistence is represented mathematically by a linear combination of orthonormal vectors as follows:
    • For probability portion: !Pasted image 20221210222031.png
    • Most quantum algorithms analyzed in this work can be cast into the oracle-based framework.The query complexity of an algorithm based on an oracle or a black-box is the number of queries.It does not matter how difficult is to implement the oracle unless we aim to solve a practicalproblem. In practical problems, it is our task to implement the oracle, and then the cost of eachevaluation matters. Take Shor’s factoring algorithm as an example. The oracle in this case is ar-periodic function and our goal is to find r. We have seen that the function in Shor’s algorithmis the modular exponentiation, which can be implemented efficiently in terms of the input size using the repeated squaring method.

2. Educational Practices

  1. Defining the quantum workforce landscape- a review of global quantum education initiatives.pdf
  2. What is AQ and how will it change your world?
  3. Defining the quantum workforce landscape- a review of global quantum education initiatives.pdf
  4. Accelerating Quantum Computing Research.pdf
  5. https://learningjournals.co.uk/what-are-the-different-pedagogical-approaches-to-learning/
  6. High-Impact-Ed-Practices1.pdf
  7. https://stocks.apple.com/A6I-mirfmSN6XHYU7Wfv92g
  8. QIS-XML An Extensible Markup Language for Quantum Information Science.pdf
  9. PhysRevPhysEducRes.16.020131.pdf
  10. Quantum Computing Technology report.pdf
  11. Detection in Electrical Grids Using Quantum Annealing eon_dwave_weibnar_marina_fernandez.pdf
  12. Contextualiy in entanglement assisted
  13. https://www.jstor.org/stable/pdf/resrep26934.8.pdf?refreqid=fastly-default%3Ab5fc498801ec3637369f297493905a40&ab_segments=0%2FSYC-6704_basic_search%2Fcontrol&origin=search-results&acceptTC=1
  14. application in finance - https://arxiv.org/pdf/2012.03819.pdf

Main Citations

Extracting PDF Comments from pdfs

BasicQuantumAlgorithms.pdf

Quantum computing is evolving so quickly that forces us to revisit, rewrite, and update th basis of the theory. Basic Quantum Algorithms revisits the first quantum algorithms.

Quantum algorithm is a subarea of quantum computing that is evolving quickly not only in term of new algorithms but also in terms of applications and implementations. The basic algorithm are the pillars of this new edifice. The construction started with a change in the rules of th game. Instead of storing information in bits, which take either zero or one, we are allowed to store information in qubits, the state of which is a superposition of zeroes and ones. The rule based on classical mechanics were replaced by rules based on quantum mechanics

The goal of this Chapter is to define the concepts of qubit, logic gate, and quantum circuit. Before that, we briefly review key facts of linear algebra [2, 64] using the Dirac notation fro the beginning.

The basic memory unit of a classical computer is the bit, which assumes 0 or 1. Usually, th bit is implemented using two distinct voltages, following the convention that null or low voltag represents bit 0 and high voltage represents bit 1. To determine whether the output is bit 0 or 1 at the end of the computation, it is necessary to measure the voltage The basic memory unit of a quantum computer is the qubit, which also assumes, at the end of the computation, 0 or 1. The qubit is implemented using an electric current in a small super conductor, following the convention that clockwise current represents 0 and counter-clockwise current represents 1, or the other way around. The difference from the classical device happen during the computation since the qubit admits the simultaneous coexistence of 0 and 1. During the computation, that is, before the measurement, the state of a qubit is represented by norm-1 two-dimensional vector and the states of a qubit corresponding to 0 and 1 are |0〉 an |1〉. The definition of state is a vector of norm 1 in a complex vector space endowed with the 1 inner product presented in the previous Section.The state can be thought of as the “value” of the qubit before the measurement. Quantum coexistence is represented mathematically by a linear combination of orthonormal vectors as follows |ψ〉 = α|0〉 + β|1〉, where α and β are complex numbers that obey the constrain 2 2 |α|+ |β|= 1. The state of the qubit is vector |ψ〉 of norm 1 with the entries α and β. The complex numbers α and β are the amplitudes of the state |ψ〉

The coexistence of bits 0 and 1 cannot be implemented in a classical device, since it is not possible to have low and high voltage at the same time, as everyone knows. In quantum mechanics, it is hard to believe, it is possible to have a quantum system (usually microscopic) with low and high voltage at the same time. This coexistence can only be fully maintained if the quantum system is fully isolated from the surrounding macroscopic environment. When we measure the quantum system to determine the value of the voltage, the measuring device inevitably affects

the voltage, outputting a stochastic result, which is a low or high voltage, similar to the classical bit. In other words, coexistence is only maintained when no one (and no thing) is trying to de termine whether the voltage is high or low. Note that quantum mechanics is a scientific theory, that is, its laws and results can be tested objectively in laboratorie

The state of a qubit can be characterized by two angles θ and φ as follow θθiφ |ψ〉 = cos |0〉 + esin |1〉 |0〉 + esin 2 2 where 0 ≤ θ ≤ π and 0 ≤ φ < 2π. This notation shows that there is a one-to-one correspondence between the set of states of a qubit and points on the surface of a sphere of radius 1, called Bloc sphere.

A quantum circuit is a graphic representation of a quantum algorithm

The circuit shows that the output of the measurement of the qubit, whose state was |+〉, is 0 with probability 1/2 or 1 with the same probability. Fig. 2.2 shows the histogram of the 3 probability distribution generated in Qiskitwith two iterations.

Implementing on IBM quantum computers 5 At this point, it is a good idea to use IBM’s composer. After logging in IBM’s website(registration is needed), we have to launch the composer by clicking on Launch Composer . IBM’ composer is friendly because we can drag the available gates into the circuit. Let us keep it to a basic use at this moment. Fig. 2.3 shows a circuit with the Hadamard gate followed by a measurement. We simply drag H and drop it on the first wire of the circuit, then we drag the meter and drop it after H. The meter’s arrow shows that the output is re-directed to a auxiliary classical register at the bottom of the circuit

After the circuit is ready, we click on Setup and run , and then we have two options: (1) Ru the circuit on a quantum computer by selecting one of the available quantum systems, or (2) sim ulate the circuit by selecting a simulator. It is usually better to start with the second option as the provider, then we select the number of shots and then weWe select ibm qasm simulator click on Run at the bottom. Fig. 2.4 shows the output of an execution. The result 000 was obtained 503 times and 001 was obtained 521 times out of 1024 shots.

In the case of the Hadamard gate, the most probable result is 50% each, but results close to 50% have non-negligible probabilitie and frequently occur. To obtain results closer to 50%, we have to increase the number of shots. If we choose to run on a quantum computer, the circuit will be queued and may take a long time. We can check the size of the queue when we are selecting the system. The output of the quantum computer is usually different from the simulator because errors degrade the result Increasing the number of shots doesn’t guarantee that the probability distribution tends towards the correct distribution, and it is important to check the correctness of the circuit through th simulator before running on the quantum system.

The simplest way to decompose the multiqubit Toffoli gate in terms of the usual Toffoli gat is by using (n − 2) draft qubits called ancillas. The ancillary qubits are interlaced with the control qubits, the first ancilla qubit being inserted between the second and third qubits. The 5best way to explain the decomposition is to show an example. Consider the gate C(X), whos

decomposition requires three ancillas, as shown in the following circuit equivalence:

The multiqubit Toffoli gate can also be activated by zero. In this case, the control qubit i n shown as an empty circle. For n qubits, we have 2multiqubit Toffoli gates that can implemen any Boolean function of n bits,

s show how to obtain the quantum circuit of a truth table. We only need multiqubit Toffol gates. To show that the multiqubit Toffoli gates can implement any Boolean function on a quantum computer, let’s take the 3-bit Boolean function f (a, b, c) defined by the following truth table as an example

After this example, it is evident how the general case is obtained. Since f has three input bits, we use multiqubit Toffoli gates with three controls. The 4th qubit is the targe

The goal here is not to implement classical algorithms on quantum computers because it makes no sense to build a much mor expensive machine to run only classical algorithms. However, the implementation we have jus described can be used for inputs in superposition, which is not allowed on a classical computer. Unfortunately, this quantum circuit construction technique for calculating truth tables is not efficient, since the number of multiqubit Toffoli gates increases exponentially as a function o the number of qubits in the worst case

The initial state of each qubit is |0〉. Then, the Hadamard gate is applied to each qubit, preparing for the quantum parallelism.

Quantum parallelism is the simultaneous execution of an algorithm with more than one input to a single quantum processor. To execute the same task on a classical computer would require an exponential number of classical processors

Due to the linearity of linear algebra, U is applied to all kets of the sum abov n simultaneously. Therefore, it is possible to perform 2simultaneous computations on a n-qubit quantum computer. Note, however, that the result of these computations is a superpositio state and, after a measurement, the final output is a single n-bit string.

We can refine the standard model by adding an extra register for draft calculations. Sinc unitary gates are invertible, the whole calculation process without measurement is reversible This means that no information is erased. The number of output qubits must be equal to the number of input qubits.

Deutsch’s algorithm is the first algorithm exploiting quantum parallelism.

In the fina Section, we describe an implementation of Deutsch’s algorithm with only one qubit.

The Deutsch-Jozsa algorithm is a deterministic quantum algorithm, a generalization of Deutsch’s algorithm, and the first example that is exponentially faster than its equivalent classical deterministic algorithm.

the first deterministic quantum algorithm with linear gain over the best deterministic or randomized classical algorithm

It is a quantum algorithm exponentially faster than the best deterministic or randomized equivalent classical algorithm. It is a remarkable bu underestimated scientific contribution to quantum computing. Simon’s algorithm exploits not only quantum parallelism but also maximal entanglement.

In oracle-based algorithms, the oracle is not implemented by us—it is implemented by someone else. However, it is important to know how it is done in order to understand the whole process.

It describes two quantum algorithms for integer factoring and discrete logarithm that run in polynomial time. The best-known classical algorithm run in sub-exponential time. Shor’s algorithms exploit not only quantum parallelism but also entanglement, being a remarkable and celebrated scientific contribution to quantum comput ing

Grover’s algorithm [23, 24] is a search algorithm initially developed for unstructured data. It can also be described in terms of an oracle, which is a function with some promise or propert that can be evaluated as many times as we want, and our goal is to determine the property that the function has

the algorithm finds the eigenvalue exp(2πφ), so that U |ψ〉 = exp(2πφ)|ψ〉, where φ is the phase of the eigenvalue. This algorithm provides a alternative way of factoring integers and calculating discrete logarithms. Not only that, it is used in many applications such as quantum counting.

Application to order-findin

Deterministic assembly of a charged quantum dot - micropillar cavity device.pdf

Quantum-dot based spin-photon interfaces are highly sought systems to implement deterministic photon-photon gates as well as to generate photonic cluster states. This requires mastering the technological challenge of fully controlling the coupling of a charged quantum dot to a cavity mode

High-Impact-Ed-Practices1.pdf

through our ten-year successor initiative, Liberal Education and America’s Promise (LEAP). George Kuh, whose work stands at the center of this report, is a member of the LEAP National Leadership Council (NLC). In his NLC role, Kuh helped AAC&U spotlight and

Now, drawing on new research, Kuh takes the examination of effective educational practices to another level. Probing data collected through the National Survey of Student Engagement (NSSE), he shows that the practices the LEAP report authors initially described—with self-consciou caution—as “effective” can now be appropriately labeled “high-impact” because of the substantia educational benefits they provide to students.

Kuh tells us in these pages “what works” for student success, and especially for underserved student success. Now it is up to the higher education community to make use of this emerging evidence.

Such studies point to the retention effects of a welcoming campus climate, supportive mentoring, and cohort engagement. But they do not spea to students’ cumulative educational achievements across the multiple levels of the college curriculum Retention and graduation are best described as partial indicators of student success—necessary, but scarcely sufficient.The college degree is meaningful, after all, only when it represents forms o learning that are both valued by society and empowering to the individual.Twenty-first-centur metrics for student success need to capture that reality.They need to address evidence about the quality of learning as well as evidence about persistence and completion.

Today we are in the midst of transformative changes—environmental, global intercultural, technological, scientific—that have far-reaching implications for what counts a empowering knowledge. On every front, the world itself is demanding more from educated people Across the nation (and around the globe), designs for college learning are changing in response

essential learning outcomes demonstrably build on th enduring aims of a liberal education: broad knowledge, strong intellectual skills, a grounded sense o ethical and civic responsibility. But the essential learning outcomes also move beyond the traditiona limits of liberal or liberal arts education, especially its self-imposed “nonvocational” identity and its recent insistence on learning “for its own sake” rather than for its value in real-world contexts

Informed by vigorous faculty and campus dialogue across the nation, the LEAP vision for student learning places strong emphasis on global and intercultural learning, technological sophistication, collaborative problem-solving, transferable skills, and real-world applications—both civic and job-related. In all these emphases, LEAP repositions liberal education, no longer as just an optio for the fortunate few, but rather as the most practical and powerful preparation for “success” in al its meanings: economic, societal, civic, and personal

In principle, if not yet in practice, this vision challenges higher education to “make excellenc inclusive,” by reaching out with data-informed intentionality to the kinds of students who have th most to gain from this kind of learning, but who frequently are steered toward much narrower and more limiting degree programs.

All these findings set the stage for the set of questions that Ge How do we help students actually achieve the forms of learning that serve them best, in the economy, in civic society, and in their own personal and family lives? How do we dramaticall the levels of college engagement and achievement for students who, two decades ago or more, would not have been in college at all? How do we effectively raise the levels of accomplishme all students, with special attention to those whose life circumstances—first generation, low income—may put them at particular educational risk?

e college without the preparatio they need for this complex and volatile world, the long-term cost to them—and to our society— will be cumulative and ultimately devastating. achievement on essential learning outcomes, then wise leaders will find both the will and to make them a top priority. With so much at stake, how can we not?

The following teaching and learning practices have been widely tested and have been shown to be beneficial for college students from many backgrounds.10 These practices take man different forms, depending on learner characteristics and on institutional priorities and contexts. On many campuses, assessment of student involvement in active learning practices such as these has made it possible to assess the practices’ contribution to students’ cumulative learning. However, o almost all campuses, utilization of active learning practices is unsystematic, to the detriment of student learning. Presented below are brief descriptions of high-impact practices that educationa research suggests increase rates of student retention and student engagement.

Many schools now build into the curriculum first groups of students together with faculty or staff on a regular basis.The highest-quality first-year experiences place a strong emphasis on critical inquiry, frequent writing, information literacy, collaborative learning, and other skills that develop students’ intellectual and practical compet First-year seminars can also involve students with cutting-edge questions in scholarship and with faculty members’ own research.

Learning Communitie The key goals for learning communities are to encourage integration of learning across courses and to involve students with “big questions” that matter beyond the classroom. Students take two o more linked courses as a group and work closely with one another and with their professors. Many learning communities explore a common topic and/or common readings through the lenses of different disciplines

Collaborative Assignments and Project Collaborative learning combines two key goals: learning to work and solve problems in the company of others, and sharpening one’s own understanding by listening seriously to the insights of others especially those with different backgrounds and life experience

Service Learning, Community-Based Learnin In these programs, field-based “experiential learning” with community partners is an instructional strategy—and often a required part of the course.The idea is to give students direct experienc with issues they are studying in the curriculum and with ongoing efforts to analyze and solve problems in the community.A key element in these programs is the opportunity students have t both apply what they are learning in real-world settings and reflect in a classroom setting on their service experiences.

learning, undergraduate research, study abroad, and other experiences with diversity, internships, and capstone courses and projects.

Why Some Educational Activities Are Unusually Effective What is it about these high-impact activities that appear to be so effective with students? First, these practices typically demand that students devote considerable time and effort to purposeful tasks; most require daily decisions that deepen students’ investment in the activity as wel as their commitment to their academic program and the college.

and personally, and choose a research-related field as a career.14 Collaborative based assignments in the context of a course set the stage for developing a meaningful relationship

with another person on campus—a faculty or staff member, student, coworker, or supervisor.These and other high-impact practices put students in the company of mentors and advisers as well a peers who share intellectual interests and are committed to seeing that students succeed.

Fifth, participation in these activities provides opportunities for students to see how what they are learning works in different settings, on and off campus.These opportunities to integrate, synthesize, and apply knowledge are essential to deep, meaningful learning experiences.While internships an field placements are obvious venues, service learning and study abroad require students to work with their peers beyond the classroom and test what they are learning in unfamiliar situations. Similarly, working with a faculty member on research shows students firsthand how experts deal with th messy, unscripted problems that come up when experiments do not turn out as expected.A well designed culminating experience such as a performance or portfolio of best work can also be springboard for connecting learning to the world beyond the campus

Ideally, institutions would structure the curriculum and other learning opportunities so that on high-impact activity is available to every student every year.This is a goal worth striving for, but only after a school has scaled up the number of students—especially those from historically underserve groups—who have such experiences in the first year and later in their studies. In the short term making high-impact activities more widely experienced should have a demonstrable impact i terms of student persistence and satisfaction as well as desired learning outcomes

students¾who¾devote¾more¾time¾to¾an¾inquiry¾activity¾benefit¾more¾

What faculty think and value also makes a difference, especially as to whether students will participate in high-impact practices.

PhysRevPhysEducRes.16.020131.pdf

Through a qualitative study of the quantum industry in a series of interviews with 21 U.S. companies carried out in Fall 2019, we describe the types of activities being carried out in the quantum industry, profile the types of jobs that exist, and describe the skills valued across the quantum industry, as well as in each type of job. The current routes into the quantum industry are detailed, providing a picture of the current role of higher education in training the quantum workforce Finally, we present the training and hiring challenges the quantum industry is facing and how higher education may optimize the important role it is currently playing

who are currently considering how to incorporate the exciting new aspects of quantum technologies into thei curricula.

It is the aim of our research to begin to address this purpose in relation to the role of higher education institutions. We focus on the training of student (undergraduate and graduate) to enter the workforce and the retraining of the existing workforce. While we do not consider the training of academic researchers (for jobs a universities or national laboratories) or educators, ou conclusions may be relevant when considering these groups, especially as the skills needed by the quantu industry are closely aligned with academia. As a result, our goal is to provide a useful resource for faculty an administrative leaders at higher-education institution

e U.S. to consider how to provide their students with the skills needed for a career in the quantum industry. Workshops, such as the Kavli Futures Symposium on Achieving a Quantum Smart Workforc [9] and the National Science Foundation (NSF) funded Quantum Information Science and Technology training and

  1. Quantum sensors: A company that is developing sensor, such as a clock, magnetometer, gravimeter, or accelerometer, that has improved precision, compared to existing technology, by taking advantag of the ability to finely control the quantum states o the system, while still being able to be used fo commercial applications 2. Quantum networking and communication: A company that is producing quantum-key distributio technologies or software, or is engaged in th development of hardware technologies to distribute entangled states.
  1. Quantum computing hardware: A company tha is building a quantum computer using any one o many different hardware approaches, such as super conducting, trapped-ion, or photonic qubits. Additionally, this includes the software development required for the hardware to operate, including, bu not necessarily, all the way to a full-stack provision o quantum programming languages to end users wh want to run their own quantum algorithms. At th current time, these companies may also be developing software to simulate the operation of a quantu computer on a classical machine. 4. Quantum algorithms and applications: A com pany that takes a real-world problem and applie knowledge of quantum computation to that problem in an attempt to solve it, or at least to demonstrat that it is possible to solve, with the goal of achieving a solution faster than a classical computer. They ma also be involved with the development of ne algorithms to run on quantum computers. Thes are the current “end users” of quantum computin hardware. 5. Facilitating technologies: A company that builds often customized, hardware that is used in either quantum sensors, networking and communication, or computing hardware, such as laser, cryogenic, vacuum, and signal processing components

Coding skills are also needed for the collaborative development of software environments throug which a user may interact with the hardware. Dat analysis is required at both the fundamental, analog level of signal inputs and outputs from a piece of hardware, an at the abstracted level, such as processing the output fro a quantum system (repeated sampling from a probability distribution) and interpreting its meaning.

he most valued skill related to quantum informa tion science is knowledge of quantum algorithms an computer science (62%). This category is almost exclu sively related to quantum computing companies, though some algorithms for quantum information processing are utilized in sensor and communication (cryptography) activities. There are a number of different aspects of this skill (i) development of new algorithms; (ii) implementation o existing algorithms on hardware; and (iii) application o existing algorithms to specific problems.

Coding and data analysis skills are related to th expectations of most companies that employees would have laboratory experience (81%), which indicates tha hardware development is a key component of the quantum industry. Only pure quantum algorithm and applicatio companies do not need any experience in a laboratory Experimental scientists, with a Ph.D., would “hav experience starting an experiment in their lab and know what it takes to get something up and running.” For junior employees, with a bachelor’s or master’s degree, a senio design or capstone project in a quantum lab, or a simila internship, is a major plus. An essential aspect o laboratory experience is gained from teaching laborato ries, where it is expected that students have learned “ho to keep a lab book ... how to document what [they’ve done... how to prepare a report... how to propose hypothesis.

. By recruiting more from a diverse range of degre subjects and levels than the currently dominant physic Ph.D. programs, there is a larger pool of possible employees. This approach has been independently recommended by th Defense Science Board that the Military Departmen Academies “should add a one-semester quantum technolog class for engineering, science, and computer scientists” [6] Quantum awareness has also been highlighted in the National Strategic Overview for Quantum Information Science [7]. Furthermore, this trend fits with the growt of the companies as they move their products out o development into production and the ratio of engineers to physicists increases—the technology is “being transitioned to a product and so at that point we start wanting to pull i more engineers, more technicians.” This change occurs as the science problems are solved, and the main issue becomes ensuring the system is reliable, making classical engineerin skills become even more valuable.

Standard graduate physics courses taken during the first years of a Ph.D. are seen as adequat preparation (“what I expect is a standard, graduate-leve physics knowledge,” including quantum mechanics electromagnetism, atomic physics, statistical mechanics) In addition to the specific domain knowledge gained ove the years of a Ph.D., the experience of doing research an developing one’s own project are key strengths of com pleting a Ph.D.

There was a surprising lack of references to employee who have a computer science or a math background in the interviews. This is probably due to the current state of th quantum industry, but also the sampling of our study. If w assume our sample is representative, then the relative lac of computer science and math graduates in the industry i reflective of the hardware focus of the quantum industry and also on the absence of training directed towards an awareness of job opportunities in the quantum industry in undergraduate courses. Then again, if students are aware of the opportunity, but are risk averse and recognize the nascent nature of the quantum industry, they may prefe to accept jobs working in classical computing, or othe industries. Given that this study has been carried out b physicists, there is a possible bias in the phrasing o questions. We asked about employees who needed quantum knowledge, which led many interviewees to, initially, discuss only employees with a physics backgroun

Similarly, machine learning has not appeared in ou skills lists, despite 38% of companies mentioning it, whic is because it was not connected by the interviewees to any specific job or degree. Most of these companies described using machine learning to help analyze their data and optimize the design of their hardware. Only 14% of companies mentioned quantum machine learning and no in any detai

. When developing a new course, or even a larger program, the breadth of the quantum industry means that choices must b made: what area of the quantum industry should it focus on sensors, networking and communications, or computing Should it be a hardware focused course with hands-o activities? Or more abstract, focusing of quantum programming or pure quantum information theory? Who are thes courses for: students or professionals? In which departmen should these courses be given? These choices should be based on the expertise available at that institution, the needs of the students, and consideration of the local and nationa connections to industry of the institution.

QIS-XML An Extensible Markup Language for Quantum Information Science.pdf

xamines issues of interoperability and integration between the Classic Information Science (CIS) and Quantum Information Science (QIS). This paper provide a short introduction to the Extensible Markup Language (XML) and proceeds to describ the development steps that have lead to a prototype XML specification for quantum computing (QIS-XML). QIS-XML is a proposed framework, based on the widely use standard (XML) to describe, visualize, exchange and process quantum gates and quantum circuits. It also provides a potential approach to a generic programming language for quantum computers through the concept of XML driven compilers. Examples ar provided for the description of commonly used quantum gates and circuits, accompanie with tools to visualize them in standard web browsers

. By leveraging a widely accepted standard, QIS-XML also builds a bridge between classic and quantum IT, whic could foster the acceptance of QIS by the ICT community and facilitate th understanding of quantum technology by IT experts. This would support th consolidation of Classic Information Science and Quantum Information Science into a Complete Information Science, a challenge that could be referred to as the “Information Science Grand Unification Challenge”

Having a metadata structure in place will greatly facilitate the management and exchange of information by the QIS research community. I also see this as the foundation to - Build and share knowledge between experts and make it more accessible to th general public - Develop educational tool - Outline a basic programming language for quantum computers - Design a rudimentary compiler to transform programming instructions into a quantum circuit and universal quantum gates (an assembly language for quantum computing - Implement tools that will assemble circuits or program circuits to execute th algorithms Using an XML based approach ensures that the framework fits in the classic IC environment which will in turn facilitate adoption and interaction between classic and quantum based systems.

XML does not come with a complex number data type. I therefore created an element that can hold a real and imaginary value. Later on, as I started to practically describe gates, I quickly realized that a quantitativ value is sometimes not enough and it is useful to also have the option to provide symbolic expression that describe the complex number. As this symbolic expression can be software or environment dependent, it can be repeated as often as necessary.

The output of the validation transformation is an HTML document that reports errors and warnings for each < Gate > and < Circuit >. An example is shown below for the 9-qubi Shor code circuit (in which an error has been introduced). I expect the validation transform to grow as the QIS-XML increases in complexity

Quantum Computing Technology report.pdf

Quantum communication promises improved security of communication between two separate actors through entanglement of photons or atoms. Primarily, this could benefit actors attempting to secure their communications through advanced encryption and interference detection capabilities. However, a secondary effec is the impact that the application of quantum communication may have on actors who rely heavily on intelligence infiltration of other actors’systems

Quantum information processing encompasses a much broader category of technologies, and thus is associated with a wider set of security concerns; this is typically the implied category when discussed by scholars and practitioners. These concerns are generally less concrete but revolve around the increase computing capability of quantum systems. Identified concerns include increase decryption power, improved AI performance, and more robust data processing

80detection capabilities.

Additionally, technology leadership allows a country to maintain robust security and safety measures in non-military areas such as public utilities and critical 82 Furthermore, technology leadership in a field like quantuinfrastructure. computing, that may yield advances in other industries such as medicine, manufacturing, and AI, creates precedent for national leadership in other critical 83 areas.Although this motive for controls has received criticism, as a potential “weaponization” of trade,84it is worth noting that this may be a secondary drive of controls. Depending on the specific motive, different types of controls will be applied.

is means that export controls may be effective in limiting final users of the technology through directing the types of research that receive investmen in the private sector. Combined, these two factors (the security relevance and th early stage of development/high susceptibility to export controls), make quantu computing an ideal chokepoint technology for trade control policy. However given the immense promise of quantum computing, early trade controls attempt to mitigate security-relevant activities would likely have to be extremely targeted. Otherwise, overly broad controls risk meriting criticism from the private sector that may ultimately lead to non-compliance, or loss of American technological competence through excessive burden on economic benefits.85

d. Due to the influx of quantum computer hardwar ideas and the lack of a consensus over which development path will yield the best computer, there is a general push to make framework-agnostic quantum computing software. In many cases, the specific hardware or software decisions are made with respect to the applications or types of industries that companies are targeting.

Although there is still no clear technical direction driving quantum computer hardware development, a few pathways are gaining significant momentum and capturing large portions of funding and interest. Each of the different syste types vary with respect to the type of qubit, where a qubit is analogous to a bit in a traditional computer, that it relies o

Most of the pathways currently being pursued are gate-based quantum computing technologies, as they are touted as being building blocks for eventual universal quantum computers; this is in comparison to quantum annealing technologies, which are easier to develop but limited in application. Although quantum annealing technologies have been successfully produced with higher qubit numbers, they tend to not reflect the true quantum benefits of quantum computing and are only able to perform a limite range of tasks

The main gate-based quantum computer approaches being explored include: trapped ion qubits, superconducting qubits, spin qubits, photoni 88qubits, and topological qubits.

Trapped ion qubits, which served as the computing unit basis for the earlies quantum computer demonstration in 1995, rely on extensive ancillary hardware, including lasers to cool the ions inside vacuums in order to trap 89 and manipulate them.Trapped ion qubit systems have achieved success at smaller scales, but have faced obstacles in scaling up to larger systems, due to difficulties in maintaining appropriate, consistent ambient environments across qubits.90

Superconducting qubits , otherwise known as “artificial atoms,” are macroscopic electronic circuits that exhibit quantized energy levels when cooled to extreme temperatures. Superconducting qubits may be applicable to gate-based quantum computation as well as quantum annealing. Similar to trapped ion qubits, superconducting qubits also become more difficult to operate in higher quantities, as qubit quality may decrease due to interqubit interactions. Thus, higher order systems will require unique arrays tha spatially separate qubits.9

Spin qubits, which can be achieved through a number of different methods, have also received significant investment, including support from Intel Silicon is a leading contender for spin qubits; although silicon qubits require extreme temperatures in order to remain operable, they are known for their stability.9

hotonic qubits, based on single units of light, called photons, are in a mor experimental stage of research than those listed above. Photonic qubits offer unique strengths in that photons do not notably interact with the environmen or with one another. However, they are also uniquely challenging in that 9they are difficult to localize and manipulate.

Topological qubits, comprising an area that has received less funding and media focus to-date, rely on topological symmetry to increase the fidelity of qubits and to improve the error correction process. However, topological qubits are at such an early stage of research that their existence has yet to b experimentally observed.9

In addition to quantum computing, other areas are emerging in the realm of quantu technologies, including quantum metrology and quantum communication.

Compared to quantum computing, which encompasses technologies that are programmable and able to accomplish a number of different types of computation quantum metrology and quantum communication are areas that apply specific quantum mechanics principles in order to accomplish explicit tasks. Quantum communication typically applies the quantum entanglement phenomenon to increase the security of communication and to increase the ease of detection i an attempt to hack a communication link occurs.95 Quantum metrology applies quantized energy levels, quantum coherence, and quantum entanglement to measure extremely sensitive physical quantities.96

For example, early analyses have been conducted to determine ways in which quantum computers could be applied to solve complex 97problems in the financial industry.

American policymakers are eagerly pursuing strategies for governance in the quantum computing field for a variety of reasons. Specifically, policymaker are seeking actionable strategies that enable domestic firms to reap economi gains from developing quantum computers,

In an effort to encompass all of these objectives, the largest overarching policy agenda was introduced as a congressional bill in 2018 under the name of the National Quantum Initiativ Act.99This bill was quickly followed by an Executive Office publication titled th “National Strategic Overview for Quantum Information Science,” which outlines more specific steps in advancing U.S. quantum competency.

further this effort the National Institute of Standards and Technology convened the Quantu Economic Development Consortium (QED-C), in order to support a robust American manufacturing base and supply chain for quantum technologies.

In 2018, the Institute of Electrical and Electronic Engineers (IEEE) published two standards, P7130 and P7131, which establish specific terminologies for quantum technologies and performance metrics for quantum computers, respectively.102 Other members in the industry have also been calling for the development of quantum computing ethics research.103

For example, the sheer limit in the number of quantum computers is being tackled through quantum clouds, wher companies can provide software that allows users to access quantum computer time remotely. Another example is software that is able to compensate for high error rates in early generation quantum computers through highly specified and elaborate algorithms

With respect to the defense industry specifically, 40 organizations (translating to roughly 20 percent of the manufacturing base) have potential dual-use applications Of those organizations that indicated the defense industry as a target industry, many identified operation analysis and automation (for vehicles and drones) as potential industry applications. Additionally, cybersecurity, and the potential fo quantum computers to break standard encryption models, may be another key source of dual-use tension.

dditionally, for certain high-ris activities, such as quantum decryption, end-use controls could be applied to firms developing relevant software technologies. Importantly, as argued by many o the ANPRM comments, trade controls on the quantum computing manufacturin base must be highly targeted so as to avoid overarching controls that will result i the U.S. losing research prominence or economic gains to be secured by nations with leading quantum computing companies

Quantum Technology and Submarine Near-Invulnerability.pdf

quantum technology applications might affect nuclear weapon capable submarines (SSBN) near-invulnerability

“Although quantu technology has no made it into broa public security debates, it is vita to now have conversation on it possible impact o security and defence especially on nuclea weapons.”

“The NATO Scienc & Technolog Organization calle security and military applications of quantum technologies one of the “major strategic disruptors over the next 20-years.

The biggest obstacles to the development of quantum-based applications are aligning technology with end-user needs, reducing the size weight and power consumption of enabling technologies, reducing and surpressing hardware errors, correcting background noise, developing th quantum repeaters necessary for longdistance communication and increasin the number, quality and circuit depth o qubits in quantum computers

Quantum Positioning Systems promise increased accuracy, confidentialit protection, anti-interference ability and smaller energy consumption compared with traditional devices.54 For quantum detection in the underwate environment, scientists expect a 1000fold improvement in performance t existing inertial navigation sensors.5 Through “rapid re-acquisition of lost signals and the ability to keep time t an accuracy of a microsecond or less for hours or days”56, they could provide for additional navigational redundancy. Submarines also offer a stable, quie and controlled environment with tim and space for maintenance of heavy an bulky devices. Before miniaturisation hits in, we can expect submarines to be one of the first adopters of quantum inertial navigation

“The ramifications of quantum computing an communication ar far more likely t change the strategi security landscap in ways as ye undetermined...”

US Black Engineer Quantum.pdf

“We believe that to expand opportunit for diverse populations, we need a diverse talent pipeline of the nex generation of tech leaders from HBCUs, said Carla Grant Pickens, chief globa diversity and inclusion officer at IBM “Diversity and inclusion are what fuel innovation, and students from HBCUs will be positioned to play a significant part of what will drive innovations fo the future like quantum computing, cloud, and artificial intelligence.

Quantum computers, with their completely different way o processing information than today’ classical computers, could spur the development of breakthroughs in

science, medications to save lives, machine learning methods to diagnos illnesses sooner, materials to make mor efficient devices and structures, financial strategies to live well in retirement, and algorithms to direct resources such as ambulances quickly

Finally, quantum states can undergo interference due to a phenomeno known as phase. Quantum interferenc can be understood in a similar way t wave interference; when two waves are in phase, their amplitudes add, and whe they are out of phase, their amplitude cancel. This helps users determine th accuracy of an execution done on a qubit or set of qubits