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Welcome

​​Dr. Siddhartha Patra


Assistant Professor,
Centre for Quantum Engineering, Research and Education (CQuERE), TCG CREST

 

​Quantum Simulation • Hybrid QPU-HPC Computing • Artificial Intelligence

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I am an Assistant Professor at the Centre for Quantum Engineering, Research and Education (CQuERE) at TCG CREST, working at the interface of theoretical condensed matter physics, quantum computing, and advanced quantum-simulation methodologies. My research combines rigorous many-body physics with modern computational approaches, including tensor networks, hybrid quantum–classical algorithms, and Quantum AI (Quantum for AI and AI for Quantum).

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Before joining CQuERE, I gained experience in quantum simulations, tensor network algorithms, hybrid QPU–HPC methods, and quantum-inspired machine learning through my work at the Donostia International Physics Center (DIPC) and Multiverse Computing in Spain. During this period, I developed high-performance tensor network simulators benchmarked against leading quantum processors, contributed to quantum-inspired neural network architectures, and participated in patent creation related to quantum circuit simulation and optimization.
 

My research focuses on advancing tensor network methods (MPS, PEPS, Flexible-PEPS), quantum circuit simulation and compression, and the development of scalable AI models using tensorized architectures. I aim to build computational tools that bring together quantum many-body physics, quantum technologies, and machine learning—enabling new possibilities in quantum chemistry, optimization, cryptography, and quantum materials research.

Research Themes

  • Tensor Network Algorithms (MPS, PEPS, Flexible-PEPS, DMRG, CTMRG)

  • Quantum Circuit Simulation and benchmarking against real hardware

  • Hybrid Classical–Quantum Algorithms for optimization and quantum simulation.

  • Tensorized Neural Networks and quantum-inspired AI models

  • Quantum Cryptographic Attacks using tensor VQE.

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These research directions advance our understanding of complex quantum systems and support scalable tools for simulation, optimization, and intelligent computing.

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