QIntern 2022 | The summer quantum internship program of QWorld.

QIntern is the summer quantum internship program of the QWorld Association, hosted by the QResearch Department. The goal of QIntern is to encourage and support collaborative work in quantum information science and technology, bringing together more experienced people (mentors) and those willing to learn more (interns).

In case of successful application, each intern is assigned to a project and gets involved in developing new software, education materials, or research results. The scope of the projects is broad and the mentors represent different areas of research and practice in the quantum world. Some internships may result in longer collaborations. 



QIntern 2022 | Your quantum internship at QWorld

Your quantum internship at QWorld 


QIntern 2022 will be a seven-week program from July 1 till August 22. As an intern, you will work remotely under the supervision of a mentor. QWorld will provide organizational support and communication platforms. Your internship will be an individual or a group project, depending on the topic and preferred mode of collaboration. In addition to acquiring new skills and professional experience, you will meet other interns and get acquainted with the QWorld community.
QIntern2022 is a program that will help you find the right way into the quantum ecosystem. 




See the interns’ publications from QIntern2021 edition

U. Azad, A. Lipińska, S. Mahato, R. Sachdeva, D. Bhoumik, R. Majumdar, Surface Code design for asymmetric error channel
Read the preprint >

Yash Wath, Hariprasad M, Freya Shah, Shashank Gupta, Eavesdropping a Quantum Key Distribution network using sequential quantum unsharp measurement attacks
Read the preprint >

Ashish Arya, Ludmila Botelho, Fabiola Cañete, Dhruvi Kapadia, Özlem Salehi, Music composition using quantum annealing
Read the preprint >

Check also other projects implemented in last year’s edition of internship program.


Quotes from participants from QIntern 2021

What is your opinion on the QIntern programme? QIntern is a unique opportunity to perform research breaking the barrier of physical distance. It allows students and mentors all over the world to meet and work on a project of interest. In QIntern 2021 I had the pleasure of working with some wonderful and bright students. I not only mentored them, but learned from them. We solved a problem of interest, which we are expecting to be published. It helped me gain experience on mentoring, added research experience and publication on my resume.
Ritajit Majumdar (Mentor)

What did you like most in QIntern 2021? It was an amazing experience in QIntern2021 as that was my first Internship. Was exposed to some amazing projects and ideas. Very good support and guidance from mentors. What I liked most about the internship is the projects that were showcased which is very innovative.
Tamal Acharya (Intern)

How was QIntern 2022 beneficial for your experience/knowledge/career? It helped me move forward research on solving routing problems using quantum computing, initiate new research directions, conduct new experiments, build a research team, prepare a quantum computing session at the Warsaw IT Days 2022 conference. Together with my team, we are still researching and working on publications (both scientific and popular science).
Paweł Gora (mentor)


Timeline for the quantum internship | QIntern 2022

  • 21 May: project proposal submission deadline
  • 24 May: official announcement of the list of projects
  • 25 May – 8 June: call for interns
  • 8 June: late project proposal submission deadline
  • 13 June – 26 June: recruitment phase
  • 1 July – 22 August: QIntern main part
  • 23 August and 24 August 27 and 28 August: mini-workshop for presenting the outcomes of projects

Get involved

If You are interested in mentoring a project or participating as an intern, please fill out the appropriate form below to join the event! Please make sure that you read and accept our rules available here. We would like to remind you that interns need to be at least 14 years old to participate in the event, and each minor (below 18) should send consent signed by his/her guardian available here to qintern [at] qworld.net.

The application form for interns>>

The application form for mentors >>

For any more information please contact us at qintern [at] qworld.net.


Projects

1. Demonstration of “Lambeq” Library
Mentor: Vandna Chaturvedi (CDAC Hyderabad)
Interns: Rishab Ghosh, Siddharth Golecha, Sanidhya Gupta, Vishal Mandal, Raja Singh
Project description: Lambeq, the first high-level open-source Python toolkit for quantum natural language processing developed by Cambridge Quantum Computing Group . This first release includes abstractions and tools for implementing all the necessary stages of a pipeline that converts sentences into quantum circuits and tensor networks. This internship includes the demonstration and analysis of mentioned Library over simple small sentences of English Language. This library is already demonstrated over Qiskit Aer simulator, our addition task is to run this library over Qiskit Density Matrix based simulator developed by CDAC and collaborations. Interns will be able to learn the NLP terminologies and a comparative study of two different quantum simulators. A constructive takeaway point for the interns is a literature review or a demonstration paper.

2. QMap
Mentor: Abhishek Manhas (College of Wooster)
Interns: Gehad Ahmed, Shreesh Jha, Kriti, Hong Joo Ryoo, Mrithula Saravanan, Sairupa Thota, Muhammad Zain Yousuf
Project description: QMap is a project that was initiated in QIntern’21 under the mentorship of Mr. Zeki Seskir. The main motive of the project was to ‘bridge the gap’ between people by mapping the landscape of global quantum education. For this year, we plan to implement the next steps of the project which include Quantum Rotten Tomatoes, resources in different languages, improving the website and app, simplifying content on the website/app for new users, etc. keeping QMap in mind. Mr. Zeki Seskir will still be with us in an advisory capacity.

3. Quantum Natural Language Processing Approach to Music Compositional Intelligence
Mentor: Prateek Jain, Srinjoy Ganguly (Fractal.ai, Upm.es)
Interns: Prachi Jain, Tuyen Nguyen, Tejas Nirantar, Shubhalakshmi S, Denisa Vítková
Project description: Project description: There has been tremendous progress in Artificial Intelligence (AI) for music, in particular for musical composition. It is a widely known that musicians and sound engineers rely a lot on various mathematical and scientific research to forage novel techniques which can help them to compose and generate novel music and sound patterns. In this project we will try to advance this field, focusing on composition. The project is one of the first unique project which is based on QNLP Approach to Music Compositional Intelligence. Since this is a very new field, the aim of this project will be to use available resources to make educational tutorials and materials. It is expected that students will be writing detailed coding tutorials and documentation for the execution of this project as well as get hands-on experience in using various platforms and software packages related to quantum computation for music. During the course of the project we will also try to find out a novel approach or technique using one or combination of DisCoCat, Tket, QNLP with possibility of publication.

4. Unraveling the gender diversity in Quantum Science and Tech
Mentor: Oxana Mishina (Italian National Institute of Optics – CNR, c/o SISSA)
Interns: Amol Aggarwal, Eyad Elsenany, George Johny, Vaishnavi Markunde, Bruna Shinohara De Mendonça, Srijita Nandi, Nikhil Kumar Parida, Kritika Rag, Monica Ramchandani, Juweria Sayed, Amina Sellami, Ananya Shrivastava, Sammith Singamsetty
Project description: Researching and collaboration on well know and on-air figures in Quantum Science and Tech to shed a light on the impact of a broader community on the development in this domain. Such research was done for computer science and brought up a lot of surprises on gender diversity in the area, that was previously unspoken. This project aims to collect more diverse gender participation in the progress of Quantum Science and technology.

5. Continuous variable quantum random number generators
Mentor: Shashank Gupta (Qnu Labs, India)
Interns: Arnav Arora, Akash Chandra Behera, Aditya Dev, Akhil Gupta
Project description: There are two categories of random number generators, 1. Pseudo random number generators (PRNGs) use mathematical algorithms to generate random numbers. 2. True random number generators (TRNGs) that utilizes physical phenomenon to generate random numbers. The major disadvantage with PRNGs is the initial seed that if known, one can predict the sequence of the generated numbers. Quantum phenomena being intrinsically random are used to generate random numbers. Such random number generators are called Quantum random number generators (QRNGs). Single-photon source and detectors are the essential requirement for the traditional QRNGs based on discrete variables making them expensive as well as lesser rate. However, the other approach based on continuous variables uses a coherent light source along with homodyne or heterodyne detectors for this purpose offering higher rate and being cost-effective. In this project, the objective is to design a new QRNG protocol based on continuous variables to further improve the rate and strengthen security.

6. Pseudo Quantum random number generators using generalised permutation matrices
Mentor: Shashank Gupta (Qnu Labs)
Interns: Ieline Ahmed, Deepshikha Jangir, Shashwat Sharma, Yash Upadhyay
Project description: Random number generators are mainly of two types – algorithmic or based on physical phenomena. True random number generators based on quantum phenomena are quantum resilient but are costly and not agile for diverse applications. Here we will look forward to develops some algorithmic quantum resilient random number generators using generalised permutation matrices.

7. QuiZX: Quantum Computation with ZX Calculus using Rust Programming
Mentor: Srinjoy Ganguly, Prateek Jain (Fractal Analytics)
Interns: Luis Gerardo Ayala Bertel, Vaishnavi Chandilkar, Calum Holker
Project description: In quantum computing, the tasks which we want to accomplish are encoded in the form of quantum circuits and they are executed on real quantum hardware to achieve desired results. These quantum circuits are unitary in nature and therefore can be easily written in various forms by using different quantum gates or rewriting with different quantum gates to simplify them. The ZX calculus is a graphical mathematics technique which helps in the efficient optimization (by using rewrite rules of simplification) of quantum circuits by representing them in terms of diagrams which look like spiders. ZX calculus has its foundations laid in category theory and is now utilized by several quantum computing companies for QNLP, Quantum Compositional Intelligence, MBQC, quantum software design, quantum compilers, quantum OS, circuit optimization, etc. This project proposes the exploration of QuiZX, a ZX calculus package based on the Rust programming language translated from its Python counterpart PyZX because of the performance boost Rust can provide to various applications. It has been found that Rust provides 5000x speedup compared to PyZX! The primary purpose of this project is threefold: Learning the basics Rust programming language with proper technical reports in LaTeX, exploration of QuiZX to develop detailed documentation and coding tutorials for its various features using GitHub pages and benchmarking QuiZX and PyZX together. The final outcomes of the project involves having a website developed and a detailed technical report ready outlining the work carried out during the internship period.

8. N-Queens Solver Implementation for Optimization of Communication System by Qiskit
Mentor: Kuan-Cheng Chen (Imperial College London)
Interns: Martyna Czuba, Cristian Galvis, Mohamed Amine Garrach, Adrian Harkness, Milan John, Manul Riteshkumar Patel, Stefan Talpa
Project description: The N-queens problem is to find the position of N queens on an N by N chess board such that no queens attack each other. The excluded diagonals N-queens problem is a variation where queens cannot be placed on some predefined fields along diagonals. This variation is proven NP-complete and the parameter regime to generate hard instances that are intractable with current classical algorithms is known. We want to propose a special purpose quantum simulator that implements the excluded diagonals N-queens completion problem using atoms in an optical lattice and cavity-mediated long-range interactions. The implementation of this project has no overhead from the embedding allowing to directly probe for a possible quantum advantage in near term devices for optimization problems.

9. References to Quantum Technologies in Cultural Artefacts
Mentor: Zeki Seskir (KIT-ITAS)
Interns: Natsai Chidavaenzi, Celestine Ikoki, Alizah Memon, Debarshi Mukherjee, Ivan Rojas, Jerin Saji, Samarjit Singh, Vimbai Zisengwe
Project description: Being referenced in cultural artefacts such as books, movies, games, and TV shows is an important indicator of the interest in and relevance of a technology to the society. Furthermore, the content and the context of the reference gives us insight into how the technology is perceived or envisioned by the public and creators of these cultural artefacts. In this regard, for this project we will be investigating how quantum technologies is covered by the mainstream cultural artefacts. We will investigate the references to QT in TV shows , mainstream games (like ANNO 2205, Stellaris, Call of Duty: Black Ops etc.), books, and movies. Although it may sound like just playing games and watching fun things, for the project we’ll ask the interns to employ coding techniques used for qualitative research in social sciences. This requires some initial training, so initially we’ll cover some qualitative research methods such as thematic analysis with the interns. The project requires some commitment by the interns, so please do not apply if you don’t have the time to read, write, attend meetings, and prepare presentations.

10. Understanding what makes quantum circuits difficult to simulate on classical machines
Mentor: Rajiv Krishnakumar (Goldman Sachs)
Interns: Ashish Arya, Beng Yee Gan, Lutfa Rahman, Leyla Rami, Sri Sowmya Tirukkovalluri
Project description: Typically when asked what is the reason quantum computers have a potential advantage over classical computers, most people (including myself) say that the concept of entanglement, which is unique to quantum systems, is a key component. However the Gottesman-Knill theorem proves that certain quantum circuits called “stabilizer circuits”, even some that produce highly entangled states, can be efficiently simulated on a classical computer. Another way of looking at these circuits is that they produce states with positive Wigner functions. Understanding the intuition behind what makes stabilizer circuits and positive Wigner function states easy to simulate (even those that lead to highly entangled states) can be useful in the path towards understanding what quantum algorithms could or couldn’t provide an advantage. As a first step, it would be useful to simulate very simple stabilizer circuits with classical (or probabilistic) circuits, to start to build some intuition. Then as we would like to go on to more complicated examples, we can read over the many previous works on this idea, including several papers discussing how to classically simulate these stabilizer circuits and even some software to do so. Currently, these works are phrased in the framework of understanding stabilizer circuits in the context of error correction or of creating probability distributions of positive Wigner functions. If we can then combine our intuition from the initial work with the insights from these papers/software packages, maybe we can find ways to think about stabilizers in terms of just purely classical simulations in a general and simpler way. This can either be in the theoretical direction, or in a more practical sense of implementing classical circuits/algorithms.

11. Survey of Quantum Research in India
Mentor: Jyoti Faujdar, Aritra Sarkar (C-DAC Mumbai, QuTech, TU Delft)
Interns: Ritu Dhaulakhandi, Shubhabrata Dutta, Shreya Hardas, Kumar Prateek, Huzefa Shaikh
Project description: The aim of the project is to build a comprehensive database of quantum related activities ongoing in India. This would allow various Indian and foreign stakeholders, like graduate students, investors, researchers, etc. to identify potential collaborators and engagements. The project will focus on a through survey of the landscape of Quantum research in India. This would include identifying research institutes, accomplished researchers, national and private funding, etc. The outputs will be compiled on the QIndia website and available publicly after the QIntern event. Interns who contribute considerably will be offered the position in QIndia to be the (co-)manager of that page after the QIntern, and will be acknowledged for their volunteering work.

12. Integer factorization through QAOA
Mentor: Adam Glos, Özlem Salehi Köken (Algorithmiq; Institute of Theoretical and Applied Informatics, Polish Academy of Sciences)
Interns: Mostafa Atallah, Siddhant Midha, Neelkanth Rawat, Shamim Al Mamun Riten, Rohan Sharma, Haemanth Velmurugan
Project description: QAOA is a well-known quantum optimization algorithm suitable for NISQ-era quantum computing. There have been attempts to solve the integer factorization problem which lies in the core of modern cryptography using variational quantum algorithms. In the scope of this project, we plan to propose a resource-efficient alternative representation for the integer factorization problem, with a particular focus on QAOA. We plan to summarize the results with an open-source code and a scientific publication.

13. Optimizing logistics using quantum computing
Mentor: Paweł Gora (Quantum AI Foundation)
Co-mentors: Meghashrita Das, Walid El Maouaki
Interns: Munawar Ali, Satvik Arya, Dhruv Bhatnagar, Artemiy Burov, Siddharth Chander, Francisco Del-Rio, Khadija Ech-Challaouy, Arthur Mendonça Faria, Sabri Gündüz, Naman Jain, Vojtěch Janáček, Soubhadra Maiti, Katarzyna Nałęcz-Charkiewicz, Rajarsi Pal, Priyanshu Pansari, Vardaan Sahgal, Soumya Sarkar, Shivalee Rk Shah, Anant Sharma, Aditya Sriram, Muhammad Usaid, Tarun Vikas Vinnakota, Louie Hong Yao, Burak Yilmaz, Tomás Ricardo Basile Álvarez, Fazlı Berk Ördek
Project description: This project will be a continuation and extension of a QIntern 2021 project aiming to solve the Vehicle Routing Problem and its variants using quantum computing. This time, we will consider new approaches (like local searches and higher-order formulations) and more logistics optimization problems. Scope: (1) Investigating optimization approaches based on local searches www.shorturl.at/mqBE3; (2) Investigating higher-order formulations for Capacitated Vehicle Routing Problem; (3) Designing QUBO formulations, running experiments with variants of QAOA, VQE and quantum annealing algorithms; (4) Review of logistics optimization problems – intern can review and summarize the existing approaches (Exploring Airline Gate-Scheduling Optimization Using Quantum Computers, Exploring quantum computing use cases for airlines, Airline scheduling problem, Quantum computing approach to railway dispatching and conflict management optimization on single-track railway lines, Optimizing train scheduling, Cargo optimization).

14. Quantum Computer Simulator for HPC
Mentor: Vivek Nainwal, Aritra Sarkar (C-DAC, Delft University of Technology)
Interns: Gaurang Belekar, Bappaditya Dey, Kianoosh Kargar, Atharva Manoj Khairnar, Aman Kumar
Project description: Quantum computing is the new paradigm of computing . As practical quantum computers are still far off , using quantum computer simulator is way to learn. QSim (https://github.com/indian-institute-of-science-qc/qiskit-aakash) is one of the python based opensource quantum computer simulator which can simulate noisy quantum logic circuits using the density matrix formalism and comes as a back end to Qiskit. However it takes long time to simulate large number of quantum bits. This work proposes to explore methodologies to make the current simulator more efficient in terms of memory footprint and accelerate the simulator execution by using multiple GPU / CPU or any hybrid approaches.

15. Quantum computing using photonics
Mentor: Anindita Banerjee (Centre for Development of Advanced Computing)
Interns: Ayan Banerjee, Mohammad Bayat, Gautam Manocha, Harish Kumar Maurya, Saroj Ray
Project description: The quantum information processing and computing using photonics is an emerging area of realizing computation which has impactful success stories. Particularly, Gaussian Boson sampling (GBS) provides a highly efficient approach to make use of squeezed states from parametric down-conversion to solve a classically hard-to-solve sampling problem. A quantum manager will finally translate a problem to algorithm and would want to implement on such devices. We make an attempt to understand the simulator (if available) for such devices and discuss the challenges and opportunities for potential quantum applications using photonics quantum processor. We also delve into the problem of which kind of problem statements / hybrid algorithm would need quantum optical processor or is it not required at all. In this project we explore these aspects.

16. Quantum Snake Game
Mentor: Kamil Hendzel (Quantumz.io Sp. z o.o.)
Interns: Linh Nguyen
Project description: The idea is to map Hamiltonian cycles onto the Ising spin-glass models, solve them with quantum annealers, and them incorporate solutions to play the classic snake game.

17. Protein Folding using Quantum Computer
Mentor: V Raghavendra ()
Interns: Buvan Prajwal A, Rea Bitri, Aparna Gupta, Durgesh Jha, Darshil Kikani, Taurean Lee, Priyanka Pandwar, Nikhil Sharma, Prashik Somkuwar, Shivesh Upadhyay, Malihe Yadavar
Project description: Understanding the nature of folding of macromolecules like proteins, DNA and RNA is central to the problems in the fields of molecular bio-physics/chemistry, bioinformatics etc. Predicting the 3D structures of proteins is of paramount significance for efficient drug discovery, medicine, crop production and other biotechnology based applications. Although conventional methods make use of classical molecular modeling techniques such as molecular dynamics to understand the protein folding problem, the classical approach has its own limitations and the problem becomes almost intractable for real life macromolecules. With the onset of quantum revolution, we aim to use the state-of-the-art quantum computer and coarse grained based technique to efficiently predict the 3D structure of the proteins.

18. Plant leaf disease detection using quantum variable neural network
Mentor: Jaykumar Lachure, Sagar Lachure (National Institute of Technology Raipur)
Interns: Reem Abdel-Salam, Rabab Azeem, Soham Bopardikar, Akash Dhingra, Ahmed Hajjem, Balusu Bhanu Prakash, Christian Lian Paulo Perez Rioflorido
Project description: First need to convert image data into quantum data through quantum circuit with minimum quantum gates. Then design of quantum variable neural network or hybrid quantum with classical architecture. Then feeding this to classify the disease types.

19. Resource-tailored multi-controlled NOT implementation
Mentor: Adam Glos, Özlem Salehi (Algorithmiq; Institute of Theoretical and Applied Informatics, Polish Academy of Sciences)
Interns: Shraddha Shankar Aangiras, Ankit Khandelwal, Handy Kurniawan, Maha Haj Meftah, Rutvij Menavlikar, Owais Ishtiaq Siddiqui
Project description: During our studies, we noticed a severe lack of good review of Multi-controlled NOT implementations. So far in the literature, multiple decompositions can be found, tailored to a different number of ancilla qubits and/or different hardware connectivity graphs. This is particularly important as the gate is frequently used in many algorithms. The principal purpose is to review the existing implementations, implement them using the qiskit programming language, and at the top of it, write a wrapper that chooses the best implementation given the size of the gate and the pre-specified resources allowed. In case of high-quality implementation, we plan to conclude it within an open-source package and possibly a scientific paper.

20. Designing a 20-Qubit Flip-chip Superconducting Processor
Mentor: Abeer Vaishnav, Nilay Awasthi (AiQyaM, Duke University, University of Pennsylvania)
Interns: Amal Alzamel, Bao Bach, Jeongwon Kim, Fabiola Cañete Leyva
Project description: This project deals with designing a 20-qubit flip-chip superconducting processor from scratch using open-source quantum hardware design tools like Qiskit Metal, KQCircuits, and SCQubits. This will involve designing custom quantum components consisting of different types of qubits, resonators, couplers, and other necessary structures to realise the full design. The design will also be optimized and tuned using various available methods involving concepts from circuit Quantum Electrodynamics (cQED), circuit quantisation and quantum analyses, to ensure optimal performance in the real-world and to make it fabrication-ready.


Coordinators of the QIntern 2022

  • Adam Glos, adam.glos [at] qworld.net
  • Aritra Sarkar, aritra.sarkar [at] qworld.net
  • Oskar Słowik, oskar.slowik [at] qworld.net
  • ‪Zoltán Zimborás‬, zoltan.zimboras [at] qworld.net

You can contact us at qintern2022 [at] qworld.net.


QIntern Team of the QIntern 2022

  • Engin Bahri Baç
  • Nouhaila Innan
  • Vikram Ravindra Kadam
  • Shantanu Misra
  • Saarah Nazar
  • Anand Nagesh
  • Yasir Ölmez