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Quantum Intelligence Research Team

The quantum intelligence research team investigates the interplay between Quantum and Intelligence. The quantum, especially in modalities of Q computation and Q information, is studied as the underlying automata and logic. Intelligence is studied as the software running on the quantum substrate, as a way to use better and understand quantum systems. These encompass applications like artificial general intelligence, reinforcement learning, quantum programming, causal inference, quantum machine learning, etc.

The Quantum Intelligence research team is currently an independent group. Between 2022-24, it was embedded and affiliated with the Quantum Machine Learning research group of the Quantum Computing division of QuTech. The following list of projects are supervised by Dr. Aritra Sarkar. For other projects within the group, check the QML-Group GitHub organization.

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List of project repositories:

In active development:

• CutQAS (private) - Reinforcement Learning based Quantum Circuit Cutting
• DeQompile - A quantum circuit decompiler
• MLC4QPM - Machine Learning Control for Quantum Programmable Matter
• QPC (private) - Quantum Pulse Compiler
• AME_spin (private) - AME States for Spin Processor Characterization
• Q-NARR (private) - Quantum Noise-Aware Routing with Reinforcement Learning

Completed/Archived:

• AutoQECC - Automated Discovery of Quantum Error Correction Codes (via Simulated Annealing)
• HilbertCorps - Automated Discovery of Quantum Error Correction Codes (via Genetic Programming)
• YAQQ - An agent that searches for novel quantum universal gate set
• KANQAS - Kolmogorov Arnold Network for Quantum Architecture Search
• QIT-QAS - Quantum information theoretic analysis of reinforcement learning-assisted quantum architecture search
• QART (private) - Quantum Algorithmic Resource Theory
• EO-QCtrl - Energy-Optimized Quantum Control
• ArtA (private) - Artificial Architect for Spin Qubits
• ML4GST (private) - Machine Learning for Gate Set Tomography
• KetGPT - Dataset Augmentation of Quantum Circuits using Transformers
• QCMP-complexity-bound - Resource Bounds for Quantum Circuit Mapping via Quantum Circuit Complexity
• QCodonOpt - Quantum-accelerated RNA Codon Optimization
• QraftRNA - Quantum Algorithms for RNA Design
• QGym - A gymnasium environment for quantum circuit optimization
• QCircScape - Visualizing Quantum Circuit Probability
• QaCHT - Quantum-accelerated Causal Hypothesis Testing
• QLogicProg - A logic programming language for quantum accelerators
• QASM - Quantum Algorithmic Statistical Mechanics
• QuNets - using quantum information for problems in network theory
• QKSA - Evolving universal AGI agents for discovering physical laws
• QPS - Discord Bot for Quantum Process Simulator
• QPULBA - Qiskit implementation of Quantum Parallel Universal Linear Bounded Automata
• QuBio - Quantum-accelerated Bioinformatics
• QuantumSim - Quantum Computing Simulator
• quineAGI - Quine-Neuro-Evolution
• fractals
• automatic-logic-design

Group members:

Current members:

• Mark Cilissen (M.Sc. thesis student)
• Radu Cosmin Dumitru (B.Sc. honours student)
• Joris Henstra (M.Sc. thesis student)
• Alan Yu (Ph.D. candidate)
• Akash Kundu (Postdoc researcher)
• Abhishek Sadhu (Postdoc researcher)
• Meghashrita Das (Intern)
• Sarang Gosavi (Intern)
• Tamal Acharya (Researcher)

Past members:

• Anna Maria Krol (M.Sc. thesis 2019)
  • Unitary Decomposition - Implemented in the OpenQL programming language for quantum computation
• Neil Eelman (Intern 2019)
  • Quantum State Tomography and Quantum Assisted Quantum Compilation on OpenQL
• Karthik Krishnakumar (M.Sc. thesis 2020)
  • Distributed Quantum Circuit Simulation
• Ravish Budhrani (M.Sc. thesis 2020)
  • QuantumSim - A memory efficient quantum computing simulator
• João Lourenço Teixeira Vieira (M.Sc. thesis 2021)
  • A Generic Micro-Architecture for Quantum Accelerators
• Duarte Frazão (M.Sc. thesis 2021)
  • Quantum Algorithms for Portfolio Management
• Harshitta Gandhi (Researcher 2021)
  • QKSA: Quantum Knowledge Seeking Agent - resource-optimized reinforcement learning using quantum process tomography
• Luís Ricardo Matos Mendes (M.Sc. thesis 2022)
  • Scalable Parallelization of Quantum Computing Simulations
• Bao Gia Bach (Intern 2023)
  • Visualizing Quantum Circuit Probability: Estimating Quantum State Complexity for Quantum Program Synthesis
• Sacha Szkudlarek (M.Sc. thesis 2023)
  • Determining Minimal SWAP Operations for the Qubit-Mapping Problem using Quantum Information Theory
• Boran Apak (M.Sc. thesis 2023)
  • KetGPT: Generating Quantum Circuits Using Transformers
• David Hamel (M.Sc. thesis 2024)
  • [ArtA: Artificial Architect - Automating Design Space Exploration of Spin Qubit Architectures using Optimization Methods]
• Deepika Rajan (M.Tech. thesis 2024)
  • `Automated Discovery of Quantum Error Correction Codes'
• Sebastiaan Fauquenot (M.Sc. thesis 2024)
  • Energy Efficient Universal Quantum Optimal Control
• Sibasish Mishra (M.Sc. thesis 2024)
  • Dictionary-based Energy-efficient Coding of Quantum Instruction Set guided by Algorithmic Information
• Shubing Xie (M.Sc. thesis 2024)
  • Quantum Circuit Decompiler: Pattern Recognition of Quantum Circuits By Genetic Algorithm