qrdlab
QRDLab
A Quantum Research and Development Initiative
QRDLab is an Industry-first initiative originated in Kolkata, India to promote quantum research and education in multiple areas of Quantum Computing. Primary objective will be to pursue high end research in several areas of quantum-inspired software to simulate various real life problems. QRDLab will aim to collaborate with independent researchers and academic institutions to accelerate quantum research. The effort includes translating nascent research ideas and advancing entire Quantum Computing technology stack in India.
Inspired by Prof. (Dr.) Subhansu Bandyopadhyay sir to put potential impact on research and education to facilitate the path of projecting India as one of the core hubs of emerging technologies in near-term future, a pool of researchers, spawned out primarily from University of Calcutta, under the supervision of Prof. (Dr.) Amlan Chakrabarti as Principal Advisor of QRDLab, have made a vision to bulid up a quantum ecosystem through an Industry-Academia collaborative venture.
Partners
Proposed Education Partner
University of Calcutta
Proposed Research Partner
Indian Internet Foundation (IIFON)
Key Research Area
Research focus of QRDLAB
Quantum Cryptography
The main goal of the study of quantum cryptography is to design cryptographic algorithms and protocols, which is against quantum computing attacks. Exploring quantum cryptographic protocols will be an essential part of cyberspace security issues for future Internet.
Quantum AI and ML
The pace of development in quantum computing mirrors the rapid advances made in machine learning and artificial intelligence. It is natural to ask whether quantum technologies could boost learning algorithms. The goal of this study is to show what benefits current and future quantum technologies can provide to AI and ML, focusing on algorithms that are challenging with classical digital computers.
Quantum Internet
The transmission of information or data in quantum networks is done using quantum bits (qubits). The quantum internet enables quantum information transfer between any two separate quantum processors. The quantum internet along with the classical internet connect quantum information processors which open up new capabilities of unparalleled which are impossible by using classical internet.
Published and Ongoing Research
Submitted to Special Issue on QuantumComputing, IEEE Transactions on Computers, 2020
A Novel Quantum Algorithm for Ant Colony Optimization
M. Ghosh, N. Dey, D. Mitra, A. Chakrabarti
Ant colony optimization is one of the potential solutions to tackle intractable NP-Hard discrete combinatorial optimization problems. The metaphor of ant colony can be thought of as finding the best path from a given graph, as a globally optimal solution which is unaffected by earlier local convergence, achieving improved optimization efficiency. Quantum-inspired Evolutionary Algorithms can be transformed into Quantum Ant Colony Optimization, that deals with customizing and improving the quantum rotation gate through upgraded formation of the lookup table of rotation angle. Instead of relying on evolutionary algorithms, we have proposed a discrete-time quantum algorithm with encoded paths in the exhaustive search space as input to the ORACLE, based on adaptive quantum circuit for pheromone updation. Iterative model of exploration and exploitation of all possible paths by quantum ants results in global optimal path convergence through probabilistic measurement of selected path. Our novel approach attempts to accelerate the search space exploitation in a significant manner to obtain the best optimal path as a solution through quantum parallelization.
Will be submitted to ACM Computing Surveys (CSUR), 2020
Quantum Transformations of NP hard Graph Problems : A Review
M. Ghosh, N. Dey, D. Mitra, A. Chakrabarti
Quantum computation paradigm is introduced to achieve computational speedup for the classical hard problems. Several classical graph based algorithms are irreversible in nature as from the set of bijective mappings input vector cannot be deduced. Structural complexity of the input vectors in graph subspace also comes into consideration along with time and space complexity of classical graph algorithms. Since quantum algorithms ensure parallelism through superposition of input states into a single superposed quantum state, there is a subsequent reduction in number of query operations and size of memory. Graph based quantum algorithm discussed in this paper obey correlations among search state properties which in turn are applicable on an average over the whole space rather than on individual states for exploiting conventional heuristics.
Aug 2017 ACM Journal on Emerging Technologies in Computing Systems (JETC) , Volume 13 Issue 4
Automated quantum circuit synthesis and cost estimation for the binary welded tree oracle
M. Ghosh, A. Chakrabarti, N. K. Jha
Quantum computing is a new computational paradigm that promises an exponential speed-up over classical algorithms. To develop efficient quantum algorithms for problems of a non-deterministic nature, random walk is one of the most successful concepts employed. In this article, we target both continuous-time and discrete-time random walk in both the classical and quantum regimes. Binary Welded Tree (BWT), or glued tree, is one of the most well-known quantum walk algorithms in the continuous-time domain. Prior work implements quantum walk on the BWT with static welding. In this context, static welding is randomized but case-specific. We propose a solution to automatically generate the circuit for the Oracle for welding. We implement the circuit using the Quantum Assembly Language, which is a language for describing quantum circuits. We then optimize the generated circuit using the Fault-Tolerant Quantum Logic Synthesis tool for any BWT instance. Automatic welding enables us to provide a generalized solution for quantum walk on the BWT.
Aug 2019 Advanced Computing and Systems for Security, SpringerLink, Volume 10
2D Qubit Placement of Quantum Circuits using LONGPATH
M. Ghosh, N. Dey, D. Mitra, A. Chakrabarti
In order to achieve speedup over conventional classical computing for finding solution of computationally hard problems, quantum computing was introduced. Quantum algorithms can be simulated in a pseudo quantum environment, but implementation involves realization of quantum circuits through physical synthesis of quantum gates. This requires decomposition of complex quantum gates into a cascade of simple one-qubit and two-qubit gates. The methodological framework for physical synthesis imposes a constraint regarding placement of operands (qubits) and operators. If physical qubits can be placed on a grid, where each node of the grid represents a qubit, then quantum gates can only be operated on adjacent qubits, otherwise SWAP gates must be inserted to convert nonlinear nearest neighbour architecture to linear nearest neighbour architecture. Insertion of SWAP gates should be made optimal to reduce cumulative cost of physical implementation. A schedule layout generation is required for placement and routing a priori to actual implementation. In this paper, two algorithms are proposed to optimize the number of SWAP gates in any arbitrary quantum circuit. The first algorithm is intended to start with generation of an interaction graph followed by finding the longest path starting from the node with maximum degree. The second algorithm optimizes the number of SWAP gates between any pair of non-neighbouring qubits. Our proposed approach has a significant reduction in number of SWAP gates in 1D and 2D NTC architecture.
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