We hear from many students that they’re excited about quantum computing,

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]]>We hear from many students that they’re excited about quantum computing, but are not sure whether they should apply. So we’re going to demystify our internships by sharing some of the projects our past interns have worked on and how being a research intern with our team differs from being an engineering intern.

The Microsoft Quantum internship program started back in 2012 with just three research interns. The program has been growing steadily ever since, reaching a total of 21 interns during summer 2019. Research interns are typically graduate students pursuing a PhD in quantum computing or related subjects. Their internship projects involve exploring new research directions under guidance of full-time researchers on our team, resulting in a paper or even a patent. These internships can grow into a long-term research relationship, and several of our former interns have joined our team as full-time employees soon after their internships. Here are just a few examples:

- Bettina Heim worked on decoding surface codes using maximum likelihood decoding.
- Vadym Kliuchnikov developed an algorithm for circuit synthesis – approximating single-qubit unitary operations with a limited set of gates used by some topological quantum computers.
- Thomas Haner worked on reducing resource requirements for evaluating classical functions on quantum computers, including addition using dirty qubits and evaluating piecewise polynomial approximations.
- Adam Paetznick developed a decomposition technique that uses non-deterministic circuits to approximate single-qubit unitary operations.

In summer 2019, undergraduate students joined our internship program for the first time in software engineering positions. These students focused on software-oriented projects such as improving the Quantum Development Kit. Although our undergraduate software engineering internship are much newer, we already have some neat success stories to share:

- Sarah Marshall implemented code completion for Q# and a state visualization tool that allows you to track the state of the Q# program during the simulation – and just this week she joined the team as a full-time software engineer!
- Rory Soiffer built a framework for Q# code optimizations.
- Artem Astapchuk created a set of tutorials on the basics of quantum computing.

Most of our interns join us on the Microsoft Redmond campus. This means they can participate in all summer events there, from the all-Microsoft OneWeek Hackathon and celebration that bring together interns and employees across the company to intern-only events like Microsoft Intern Puzzle Day and workshops hosted by various teams.

*“Introduction to quantum computing” workshop hosted by our team for all Microsoft interns*

They also get ample exposure to various directions of ongoing quantum computing research, both via their fellow interns’ presentations of their projects and via a weekly journal club.

Does this sound like a great way to spend your summer? Apply to our open intern positions today! Application deadline is January 31

^{st}.

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]]>First,

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]]>- First, we open-sourced the QDK and deprecated the UserVoice channel, so there is no single channel for QDK feedback any longer.
- Second, our users don’t typically open GitHub issues just to thank the language creators for an especially nice feature!

Instead, we decided to poll our team members for their favorite Q# feature or a particularly useful tool. Check out their replies below – you might find something new to try!

- The partial application syntax to create closures is actually quite nifty and very useful… Here is an example. –
*Alan Geller* - The functor support is very straightforward and easy to use. Just put Adjoint in front of an adjointable operation and [the compiler] figures it out. –
*Scott Carda* - And that we support borrowing is neat too, for the more quantum savvy people. –
*Bettina Heim* - I would highlight that qubit management happens automatically in a well structured context. –
*Andres Paz* - apply … within and AssertProb. –
*Vadym Kliuchnikov* - QDK is open source! Plus first-class functions and operations + partial application lets you do just about everything. –
*Chris Granade* - Tools for testing and debugging and Jupyter Notebooks support: the first feature to make the Quantum Katas possible and the second one to make them beautiful! –
*Mariia Mykhailova* - It is hard to pick just one thing…
- Q# libraries, from simple (but really useful) tools in the Canon to more complex things like the multiplexer and state preparation tools to specialized libraries written in collaboration with domain experts like the chemistry library and the numerics library.
- The resource estimator that allows you to gather metrics such as number of qubits, circuit depth, and circuit size at scale, i.e., for quantum programs that may involve millions of qubits and billions of quantum gates!
- The effortless ease with which simple quantum algorithms such as Bernstein-Vazirani or hidden shift or Simon’s algorithm can be implemented. Simon’s algorithm needs complex post-processing (linear algebra over GF(2)) and I like how this can be done by using Q# in tandem with C#. Also, the synthesis of permutations is a cool feature.

*Martin Roetteler*

How about you – what is your favorite Q# feature?

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]]>Let me continue the topic of teaching and learning quantum computing that I touched upon yesterday and share with you the project done by my summer intern Artem Astapchuk –

The post New Tutorials: Learn the Basic Concepts of Quantum Computing appeared first on Q# Blog.

]]>Let me continue the topic of teaching and learning quantum computing that I touched upon yesterday and share with you the project done by my summer intern Artem Astapchuk – a set of tutorials that introduce the most basic concepts used in quantum computing.

The Quantum Katas start with the BasicGates kata – a set of exercises that ask the learner to identify the quantum gate that will perform the described transformation of a qubit state. It seems like a very easy thing to do – how hard can it be to look up a list of quantum gates and match one of them to the task?

Turns out, it is pretty hard for somebody who sees the quantum computing notation for the first time. Even the easiest task that asks to apply the Pauli X gate relies on a lot of implied knowledge. What is a qubit and its state? What are these weird symbols around 0 and 1? What kind of tools do you use to change the state of the qubit? And how do you express all this in Q#?

Historically the Katas sent the learner to find an external source for learning the basic concepts and notations used in quantum computing. However, eventually it started to make more sense to create a set of tutorials that would teach the learner everything they need to start solving the first katas in one place and using one style.

Well, here they are! Two tutorials that cover the math necessary for working with quantum computing – complex arithmetic and linear algebra – are written in Python, and the four that introduce the quantum computing concepts – qubits and superposition, multi-qubit systems and entanglement, and single- and multi-qubit gates – are implemented in Q#.

We tried to steer away from too much theory and to give just the definitions and the tools necessary for getting started (yes, qubit states are described using Hilbert spaces; no, you don’t need to know this to start learning). Instead, we focused on making the learning process as hands-on as possible, using demos and programming exercises to help learner internalize the new concepts and ideas by applying them to solving simple tasks.

For example, the definition of the imaginary unit *i* is immediately followed by a programming task that asks one to calculate the *n*-th power of *i* *iⁿ*; the introduction of the qubit states is followed by a demo that shows how to examine and interpret the qubit state in Q# using the DumpMachine function, and so on.

If you’re looking to get started with quantum computing, give these tutorials a try and let us know what you think!

Meanwhile, we’ll keep working on bringing you more tutorials. Next up: measurements!

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]]>This winter our team had an exciting opportunity to teach an introductory course on quantum computing at the University of Washington, led by Krysta Svore.

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]]>This winter our team had an exciting opportunity to teach an introductory course on quantum computing at the University of Washington, led by Krysta Svore. It was a special experience for all of us, but especially for me, since I’ve never been involved in the university education process in any role other than a student.

*If you prefer watching videos to reading, here are the videos from Microsoft Faculty Summit 2019, where Martin Roetteler and I talk about our experience teaching this course: part 1 and part 2.*

First of all we had to figure out what we are going to cover in the course and how to teach it. Quantum computing is a huge field, and can be taught from a variety of different angles, from quantum physics and the physical realization of quantum computers to pure quantum information theory. What to choose?

We decided to approach the subject from a computer scientist’s point of view, focusing on programming and solving practical problems. Indeed, a typical course in classical computing starts by introducing a programming language and teaching the students to use it to solve simple tasks; then it covers basic algorithms and data structures, with homework assignments centered around implementing the data structures and using the algorithms to solve more complicated tasks; finally, the students have a choice of courses on more advanced topics (again with practical applications), capstone projects etc. You don’t often see a classical software engineer who would be trained in transistor physics and computational complexity theory but who only ever implemented algorithms on paper!

We ended up creating a course leaning heavily towards the practical implementation of quantum algorithms; it included both written assignments and programming assignments, with the latter accounting for a larger share of the final grade than the former, and a final programming project instead of a more customary written exam or a presentation-style project.

Our main tool for teaching the students quantum programming were the Quantum Katas. I’ve mentioned them before once or twice, so I won’t go into great detail on them again – I’ll just note that they are as good for classroom learning as they are for self-paced. In addition, they did a really good job of preparing the students for their homework.

Programming assignments were structured exactly like the katas (that was before we introduced the Jupyter Notebooks, so all programming materials were Q# projects): the students would get a file with task descriptions and the skeleton operations for them, and they’d have to fill in the code that solves the tasks. Here, for example, is the first task from week 4 of the course, in which we covered quantum oracles:

The neatest thing about the programming assignments was that they were graded automatically. (I’ve never been in a TA’s shoes myself, but I can certainly sympathize with the need to grade over 30 assignments!) Similarly to the katas, each task of the assignment was covered by a test, and if the test passed, the solution was judged correct.

In week 6 of the course we tried a different flavor of a programming assignment: the students had to do resource estimation for Shor’s algorithm implemented in our samples. These tools would come handy for them later in the course.

The last programming assignment was even more unusual for quantum computing courses than the previous ones: the students were to take part in the Q# Coding Contest, which was conveniently held during the last month of the course. Programming courses on algorithms or machine learning sometimes use a similar approach, offering problems from Kaggle, Codeforces or other online judges as assignments or even hosting small programming competitions for the students.

However exciting hosting the contest was for us, the students didn’t take it well. A lot of topics in the contest were covered in the course, but the contest tasks were much harder than the homework assignments. Add the extra pressure from the timed nature of the competition and the requirement to participate in it alone, and the results were disappointing: only one student solved all problems.

The final projects were small capstones for the course: the students would form teams of 2-3 people and work on a quantum computing problem of their choice, going through all the steps from choosing and defining the problem to solving it and implementing the solution in Q# to describing the solution in a mini-paper and presenting it to the class.

This was the favorite part of the course for a lot of students. On the one hand, it allowed them to focus on any topic they were excited about and to deep-dive into it. On the other hand, it was extremely practical: the students had a chance to actually experiment with their algorithms of choice, figure out how much resources are required to run them and how to construct a small instance of a problem that can be solved on a simulator, optimize their solutions and compare different implementations — in other words, do a lot of things that comprise a quantum software engineer’s day work!

The last two lectures of the course were dedicated to the final projects presentations. This was when I got to finally meet the students in person (before that I focused on behind-the-scenes parts of the course, so the students knew me only as a disembodied online presence). The range of projects done by the students was quite impressive — from entanglement games and key distribution protocols to quantum chemistry and a Bitcoin mining algorithm!

The course has completed over half a year ago, but it had more lasting outcomes than just a pass/fail grade for the students who took it.

First, several teams chose to frame their final projects as new katas and to contribute them back to the Quantum Katas project for the next generation of learners to use.

Second, several students went on to do internships at companies who work on quantum computing (well, most of those were on our team, but that still counts!) and quite possibly will make a career in it.

Finally, we learned a lot about the best ways to teach people quantum computing. We really hope to teach a new, updated and improved version of this course soon! Meanwhile, we are happy to share our materials and learnings with other instructors looking to teach quantum computing from a practical point of view (if you’re interested, contact me at mamykhai@microsoft.com).

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]]>The post Q# Advent Calendar 2019 appeared first on Q# Blog.

]]>The rules are simple:

- Reserve a slot by leaving a comment on this post. (You can also tweet about it, but you’ll have to mention @tcNickolas to make sure we’ve seen it!) The slots are assigned on the first come, first serve basis. You do not have to announce the topic of your blog post until you’re ready to publish it, but we’d really love to hear it beforehand
- Prepare a blog post (in English) about Q#, cool project you’ve done in Q#, learning Q#, teaching Q#, using Q# for research, tools for working with Q#… You got the idea. Don’t forget to check out last year’s calendar for inspiration!
- Publish your blog post on your assigned date. Don’t forget to link back to the Q# Advent Calendar from your post, so that your readers can find the entire advent.
- Leave the link to your blog post in a comment to this post, and we’ll add it to the calendar. If you share a link to your post on Twitter, use hashtags #qsharp and #QsAdvent.

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]]>The post Grace Hopper Celebration 2019: Recap appeared first on Q# Blog.

]]>We really enjoyed attending GHC! Let us share some of the highlights of the celebration.

Our workshop was held on the last day of the celebration when the attendees start feeling exhausted by the intense mix of sessions and networking events of the previous days. Nonetheless, over 150 people showed up for our session, eager to learn quantum computing!

We chose to do a high-level overview of Grover’s search algorithm – one of the most famous algorithms in quantum computing – and to discuss the kinds of problems it can be applied to and the kinds of problems it cannot. In the hands-on part of the workshop we offered the attendees the opportunity to apply the algorithm to solving Boolean satisfiability problems and to explore its behavior in various scenarios.

You can find the workshop materials (including the introduction slides) here.

For me, the main highlight of the conference was meeting new people and hearing their stories. The term “woman technologist” describes a very diverse group of people, and it was positively inspiring to put a new multitude of faces to the name!

This was my first time attending the Grace Hopper Celebration, and I was so impressed by it! The main highlight for me was seeing the accomplishments of women in STEM celebrated. I loved the keynote speakers, and felt like I learned new definitions of what success looks like for women in STEM (and really, success in STEM in general), and found their stories truly empowering.

My main takeaway was the fact that I can walk on the stage and unexpectedly enjoy delivering a talk instead of freezing in panic, like I usually do .

Being new to the Microsoft Quantum team, and to quantum computing in general, it was really exciting for me to see the enthusiasm around quantum technology at GHC. I was extremely impressed with the level of engagement from the audience during our workshop, it demonstrated that people are curious and invested in the quantum space, and that was really empowering to witness.

*We are grateful for the opportunity we had to share some of the exciting work we’re doing with the Grace Hopper attendees, and we hope to be able to return to Orlando for GHC20!*

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]]>The post Quantum Koan: High Probability appeared first on Q# Blog.

]]>That evening at dinner the novice was served a separate bowl with a note: “This food is not poisoned with high probability”.

Upon seeing this the novice was enlightened.

*Had the novice implemented Deutsch–Jozsa,
They would not go to bed hungry.
Randomized algorithms are like that,
No matter quantum or classical.*

This pseudo-koan has been inspired by The Codeless Code – a collection of short metaphoric stories about software development.

If you need more insight in the nuances of Grover’s algorithm, try to implement it in the Grover’s algorithm quantum kata.

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]]>The post One Year of Quantum Katas appeared first on Q# Blog.

]]>The first release of the Quantum Katas had only 4 katas, covering basic gates used in quantum computing, the concept of superposition, the use of measurements, quantum oracles and Deutsch–Jozsa algorithm. Even with this seemingly scarce material they were very useful for people learning quantum computing, but it was obvious that we needed more topics.

The first big batch of the new katas came in from Microsoft’s OneWeek Hackathon – a yearly global event that brings together Microsoft employees and interns to tackle unusual and exciting projects. A group of hackers from different countries got together to learn something about quantum computing and to write new katas about the topics they’ve just learned.

This Hackathon brought in such gems as the katas on teleportation, superdense coding,

Simon’s algorithm and Grover’s algorithm – all of them essential stepping stones on the way to mastering quantum computing, and all of them already used in teaching these topics.

Outside of the Hackathon things looked quiet for a while: in the half a year since the katas were released we added only two new katas – the ones on joint measurements and on the bit-flip error correction code. But behind the scenes work was in full swing: we were preparing for the next big events – the course on quantum computing we were going to teach in University of Washington and the second Q# coding contest.

The impact of the course was two-fold. On one hand, we heavily relied on the katas for teaching the students Q#, but at that point the katas covered the introductory topics well enough that we only needed to write one new kata, the one on phase estimation. On the other hand, a lot of students elected to write a kata or several as their final project in the course and to contribute them back to the project. The set of three katas on quantum entanglement games was one of these final projects, as well as the prototype of the kata on solving graph coloring problems using Grover’s algorithm (and there are more lined up!).

For the second Q# coding contest, we took a brief detour from the usual learning path and wrote a very uncommon kata called UnitaryPatterns. It offers tasks of the following form: given a pattern of zero and non-zero elements in a square matrix of size 2^{N} × 2^{N}, write a Q# operation that implements a unitary transformation on N qubits described by a matrix that matches this pattern.

These are not the kind of tasks you’ll often see in a book, but they make for a really great brainteaser – and teach you a lot about what it means for a matrix to be unitary and about decomposing unitary transformations into Q# operations.

Another kata written for the contest aims to answer one of the most frequent questions about Grover’s search algorithm: how to implement an oracle for the search problem if you don’t know the answer yet, and what’s the point of implementing an oracle if you already know the answer? SAT problems are a perfect example of problems that can be expressed as oracles and tackled using Grover’s search, as shown by this kata.

The next big step for the evolution of the Quantum Katas were Jupyter Notebooks for Q#. I’ve already praised them for making an excellent front-end for the existing katas, so I won’t repeat the odes here – I’ll just point out that (due to relentless effort of our community) 13 of the katas are already available online as Jupyter Notebooks, and the rest of them are coming soon.

But the benefits of the Notebooks don’t end at the beautiful presentation for existing problems…

Jupyter Notebooks open the door to a whole world of new possibilities. The most obvious of them is writing proper tutorials that explain a topic using a mix of theory, visualization, Q# code samples/small demos and programming exercises. The first of such tutorials is already up – it offers you a rather extensive exploration of the Deutsch–Jozsa algorithm, including the classical solution to the problem and an introduction to phase oracles and implementing them in Q#.

We hope you find the growing Quantum Katas project useful. Stay tuned as we share with you new tutorials and programming exercises!

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]]>The post Solve the Quantum Katas Online with Jupyter Notebooks appeared first on Q# Blog.

]]>Today, we present the first batch of the Quantum Katas in Notebook format! Those of you who have already tried out the Quantum Katas or attended one of our workshops on quantum computing will recognize the benefits of the new format immediately:

- You don’t need to install anything locally to solve the katas. No more frenzied installations the night before the workshop (or even during the workshop!) – you can run the katas online in any browser using Binder.
- The presentation is a lot smoother and more polished. Even with the Unicode support in Q# comments, there is a dramatic difference in task rendering, since the Notebooks provide full HTML and LaTeX support, and allow images to be incorporated in the task descriptions.
Notebooks also allow hints to be hidden until they are needed, as opposed to just being visible in the code upfront. (For the best experience with the hints, we recommend using Firefox, Chrome or Microsoft Edge Dev build.)

- The solution template given in the Notebook does not have to compile, as long as you don’t attempt to solve the task. The solution template given in a Q# project must compile to tell you that your solution is incorrect, so the tasks frequently return a placeholder value just to make the code valid – and for some of the trickier tasks that value is not trivial and sometimes confusing.

We will eventually convert all the katas to Notebook format, so that you can solve them in your preferred environment. Meanwhile, try the katas that are already converted and let us know what you think!

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]]>The post The Women of QuArC appeared first on Q# Blog.

]]>**Traditionally it is celebrated on March 8th, but a belated celebration is better than none*

***In case you were wondering, our group is properly called the “Quantum Architectures and Computation” group, but that was a bit too long for the title*

Q: Tell us more about your role in QuArC. What exciting things are you working on right now?
I am the General Manager of Quantum Software and lead the QuArC team. Our team is developing the quantum applications that will enable solutions to some of today’s most challenging problems and writing the software that will enable programming those solutions on the quantum hardware. I am excited to have just co-taught with other members of QuArC an undergraduate course at the University of Washington on quantum algorithms and quantum programming in Q#, the first of its kind in the CSE department. It is so exciting to see more and more computer scientists, developers, engineers, and quantum enthusiasts learning about quantum computing! |

We also just launched the Northwest Quantum Nexus in partnership with the University of Washington and Pacific Northwest National Laboratories, to advance quantum information and computing in the greater northwest region. It is through growing a broader quantum community that we will discover even more incredible applications of this revolutionary technology. I am also excited to work with such an amazing group of people on a technology that has inspired me for over twenty years.

**Q: What was it that first attracted you to the technology field?**

When I was young, I was fascinated by puzzles and mathematical challenges. I loved solving math problems while also answering scientific questions. As an undergraduate, I pursued mathematics, and it was not until my junior year of college that I took a course in computer science. Immediately I was hooked; it was a field where I could use my math skills while able to perform computational experiments. Programming felt like the perfect way to go about solving a puzzle, and algorithms served as a great theoretical outlet. My deepening computing interest led me to pursue a PhD in theoretical computer science with a focus on how to make a quantum computer fault tolerant and programmable.

**Q: How and why did you decide to join the domain of quantum computing?**

It was also during my junior year of college when I learned about this amazing model of computation that could break most public-key cryptosystems. I was taking a seminar on cryptography from Professor Andrew Wiles (who solved Fermat’s Last Theorem) when I was exposed for the first time to quantum computing, and to Shor’s algorithm for factorization. I was completely fascinated that there was another model of computation that enabled factoring to be solved efficiently. I began reading as much as I could on the subject and the following year decided to pursue it as my focus area during my PhD. With an interest in both math and computer science, I spent my PhD researching how to program a quantum computer and how to error correct it. I saw an opportunity to develop methods for taking a quantum algorithm, such as Shor’s algorithm, and enabling a programmer to specify it and then map it to quantum hardware. Twenty years later, our QuArC team at Microsoft is defining how to program a quantum computer and the ground-breaking applications to run on it. Quantum computing is a lifelong passion for me; it also unveils the most fun, challenging problems to work on each day!

Q: Tell us more about your role in QuArC. What exciting things are you working on right now?
I am driving the Q# language design and compiler architecture. Right now, I am working towards getting to a 1.0 version of both the language and compiler. There is a long list of things that would be awesome to do, and I would love to make them available to the public. We are also working on providing a platform for the developer community around Q# where we hope to be able to share our excitement, progress and struggles such that we can grow and evolve this fascinating new technology together. |

**Q: What was it that first attracted you to the technology field?**

I don’t think there was anything in particular that compelled me to pursue my current line of work. I love puzzles and I love the challenge, so my career choice has mostly been driven by where I felt I can grow the most, and of course also a little by where I can help to make other people’s lives easier. I like to think about concepts and abstractions, how to model complex systems and what the limitations are of that model. At the same time, I like “hands on” engineering work – I like building things and pushing the boundaries of what is possible today.

**Q: How and why did you decide to join the domain of quantum computing?**

I majored in physics and never really liked relativity, so naturally I ended up pursuing a degree focused on quantum mechanics. I came across a book on quantum computing very early in my undergraduate studies and was immediately fascinated. I had some concerns regarding the feasibility at that time and thus initially focused on more conventional areas around optimization and high-performance computing. When I got to know the people in QuArC I couldn’t help but give in to the temptation of working alongside such an inspiring set of people to figure out how to make large-scale quantum computing a reality.

Q: Tell us more about your role in QuArC. What exciting things are you working on right now?
I had an opportunity to contribute to many different aspects of our developer tools, from the internals of our pre-Q# prototype to syntax highlight and Visual Studio integration for the 0.1 release of Q# to our documentation. In the past year I’ve gradually gravitated to the education and outreach work. Quantum computing is an exciting topic, and there are lots of people enthusiastic about learning it, but it has a reputation of being very hard to get started with. I’m focusing on making it more accessible and coming up with new ways of helping people learn quantum programming. |

Some of the projects I worked on in the last year include the Quantum Katas (self-paced tutorials on quantum computing and Q#), Q# coding contests, the quantum computing course at the University of Washington mentioned by Krysta, and the Q# Advent Calendar. I would be hard-pressed to pick the most exciting of them!

**Q: What was it that first attracted you to the technology field?**

I’m a software developer in third generation. My grandmother was one of the first computer science majors in Ukraine (well, in the part of Soviet Union that is now Ukraine). My mother followed in her steps, albeit with more modern technology, and I just always felt that’s what I would do for living. In fact, I don’t recall ever considering a different vocation.

**Q: How and why did you decide to join the domain of quantum computing?**

I had a very brief encounter with quantum computing as part of a quantum physics course back in university, but at that point it did not look like something one can do for a living. I graduated with a master’s degree in applied math and went on to work in finance industry, writing software for banks. Several years later I moved to US and joined Microsoft to work on cloud infrastructure.

Four years later, I felt I was ready to embark on my next adventure. Fortuitously, QuArC was hiring software engineers to develop programming tools for quantum computing (no PhD required).

As for “why?”, I’ve always loved science fiction, and quantum computing is practically the definition of science fiction, except it’s happening here and now!

Q: Tell us more about your role in QuArC. What exciting things are you working on right now?
I’m the program manager for the Quantum Development Kit. Right now, I’m working with the team to enable new capabilities to support Python as the host language for Q# and support Jupyter Notebooks. These will be great tools to help users learn how to program with Q# and help researchers publish their work with Q#. I’m also working with our quantum researchers to bring new libraries to the Quantum Development Kit, such as the chemistry library. Finally, I work closely with our new Microsoft Quantum Network partners to bring to the Quantum Development Kit those capabilities that they are looking for in developing their quantum solutions. |

**Q: What was it that first attracted you to the technology field?**

I didn’t know much about computer science, but I liked math, and my sister was a computer science major in college, so I chose that major too. It was a great choice for me. Over my career, I have been a part of so many challenging teams in high performance computing, research and big data. In 2016, GeekWire published a profile of several of my fellow Ph.D. women colleagues and me and our journeys through the tech world.

**Q: How and why did you decide to join the domain of quantum computing?**

One of the great things about Microsoft is the ability to try out new areas and take on new challenges. Quantum computing is a fantastic opportunity for me to grow in a new area of computing, but it is also an opportunity for me to bring those skills I learned in my prior roles to this team. I get to work with a great team of passionate engineers and researchers who are all working together to build the quantum computer. I didn’t realize when I joined the quantum team that I would also be working alongside some of the same people I worked with before I joined Microsoft 13 years ago. But I keep running into former colleagues in the hallway who are now hardware engineers working on building the quantum computer at Microsoft. I also didn’t realize when I joined the quantum team that I would be working with some of the same customers that I worked with on the Microsoft high performance team years ago, but these same customers are now looking at quantum computing to solve their most challenging problems.

Q: Tell us more about your role in QuArC. What exciting things are you working on right now?
I lead business development for Microsoft Quantum. We are working with customers and startups across sectors including energy, materials development, automotive, financial services, healthcare and more through the Microsoft Quantum Network, a program that we built to bring experts across domains together to solve real problems and make quantum computing more accessible. |

We bring bleeding-edge advancements in quantum computing together with the incredible work our customers and partners are doing to push the boundaries of what’s possible. For example, we are working with Case Western Reserve University to improve the diagnostic capability of MRIs. The work we are doing together has the potential to transform diagnostic medicine and ultimately change lives.

**Q: What was it that first attracted you to the technology field?**

I have always loved building things and solving tough problems. I taught myself programming in early high school and loved how it enabled me to create new things with very few resources. When I took my first physics classes, I was hooked on the idea that we could understand fundamental things about how the world works. The work I did as an experimental physicist brought these passions together. As an undergrad, I designed and built particle detectors including work on the Alpha Magnetic Spectrometer (AMS), a detector currently mounted on the International Space Station searching for antimatter and dark matter. In my Ph.D., I designed and built experiments to understand fundamental quantum effects in nanoscale quantum circuits and had the opportunity to work alongside pioneers in quantum computing.

I’ve pursued a variety of different roles in tech across hardware and software, on the technical side and on the business side. Now in the Microsoft Quantum group, I get to combine my skills and passions to work on tough problems with incredibly smart people aligned on the common mission of bringing this technology to life.

**Q: How and why did you decide to join the domain of quantum computing?**

I’ve been fascinated by quantum physics since I first learned about it in high school. As an undergrad, I devoured every course that MIT offered in quantum physics. When they first offered a quantum computing class in the graduate school, I jumped at the chance to combine two of my passions. What excited me when I first discovered quantum computing and what drives the work I’m doing today is the possibility of unlocking solutions to problems that will help us transform the world. We will be able to take on societal level challenges like climate change, sustainability, world hunger, and much more in a tangible way.

Q: Tell us more about your role in QuArC. What exciting things are you working on right now?
I am the program manager for the Qubit Workbench. This is an internal operations tool for the academics to use in order to enable a productive workflow, one that eliminates as many manual steps as possible in a researchers day to day efforts for topological qubit discovery. |

**Q: What was it that first attracted you to the technology field?**

I come from a mathematics background and have always loved the precision that math brings to problem solving. To me it’s the early days of data driven decision making – obviously, a huge industry term in technology today. I stumbled upon computer science when picking a bachelors. At the time I did not feel that a degree in mathematics would be very lucrative; I come from a working class background and was viewed as a “foreigner” growing up, so money was very tight to say the least. I chose computer science because there had to be money in that, and money would buy me freedom.

Once I started computer science, I was all in! I loved the mathematics behind it, I loved problem solving, writing code and being part of something that was going to change the world. This of course was before the internet, and when the internet became “real” I knew that this a field I would flourish in and continue to be a part of innovations of the future.

I care about people, the planet, animals and believe in alchemy and my part in technology is to improve lives. At the same understanding the “dark” side of technology is important for me, especially now that I have children, I know I want to stay in touch with how the youth are interacting with technology so that I am best equipped to support my family and exercise good judgement in parenting.

**Q: How and why did you decide to join the domain of quantum computing?**

I have been shipping software for twenty years now. I enjoy it, but I came to a point where after a while shipping the software was not enough. Now, being a big Stephen Hawking fan of course, quantum physics has always fascinated me. I am a sci-fi fan too and read most of the classics, H.G. Wells, Douglas Adams, Arthur C Clarke and even George Orwell. Just thinking about how those great minds saw the future nearly a century ago blows my mind. Then reading about Quantum and having the opportunity to be a part of it was enough for me to join the team. In my role today on the Quantum team, I find that I bring my software skills to the table, and the intellectual stimulation I receive in return just by being around brilliant scientists and learning every day is really second to none. I am humbled and grateful for the opportunity.

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