Quantum parallelism is used to perform a large number of computations at the same time, and quantum interference is used to combine their results into something that is both meaningful and can be measured according to the laws of quantum mechanics. The biggest challenge is building a large-scale quantum computer.
Qulabs is one of the first company in India in Quantum computing ecosystem. Our team, which comprises of multidisciplinary groups of research scientists and engineers from various leading institutes of higher learning like IITs, ISI and IISc, are united by a common challenge theme for advancing the research frontiers in India.
Qulabs has created a business unit QuAcademy which aims to facilitate training of students with the combination of skills required for the conceptualization, development and translation of new quantum technologies.
Qulabs plans to facilitate Research, Development, Training and Education in Quantum technologies through exposure of trainees to theoretical frameworks, algorithmic techniques and experimental platforms and testbeds, as well as interaction with national laboratories, industry and international partners. It plans to build on various government agency funding from the likes of MeitY, DST and investments from Private Equity and Venture Capitalists in Quantum Technology and Engineering. Currently Qulabs’ Quantum Research Lab at IIT Roorkee in collaboration with Indian Institute of Sciences Bengaluru, CDAC Hyderabad and CDAC Bengaluru are creating the first Quantum Simulator in India.
Qulabs is also expected to coordinate and integrate with ongoing and new quantum initiatives like the one by Telangana State Government, Indian Institute of Technology, Hyderabad and Qulabs’ called “Quantum Valley”, which includes Quantum Incubation hub, called “inQubate™” with Quantum Qloud access to various quantum computing platforms, infrastructure and workforce development activities.
Quantum machine learning (QML) is a subdiscipline of quantum information processing research, with the goal of developing quantum algorithms that learn from data in order to improve existing methods in machine learning.
A quantum algorithm is a routine that can be implemented on a quantum computer, a device that exploits the laws of quantum theory in order to process information.
Quantum Networks for Secure Long-Range Communication
Long-haul and secure quantum communication could be an organizing theme for Qulabs’ Quantum Research Labs. Development of components such as quantum sources, detectors, memories and repeaters, along with networking protocols for generation, swapping, distillation and verification of entanglement all present formidable challenges. Losses, noise, decoherence and other technical challenges, such as operation at room temperature, may be overcome with the development of new concepts, materials, devices and techniques and algorithms for generation and processing of quantum signals.
Achieving a vision, for example, of a global fully secure quantum communication network will require foundational advances and technological innovation in multiple areas, involving both theorists and experimentalists, for the design and development of prototypes and scalable platforms.
Furthermore, co-designing platforms and testbeds to accomplish system-level goals for power, bandwidth, security, stability and scalability may benefit from whole new approaches founded on a convergence of engineering, computer science, mathematics, materials science and physics.
Fostering such convergence in one of the Qulabs’ Quantum Research Lab may provide additional benefits, e.g., revolutionary chip-scale photonics platforms that support a range of wavelengths, operational temperature and rates to enable new applications, such as distributed quantum sensing and computing.
The challenge to conceptualize, develop and implement a complete set of software solutions necessary for creating an efficient and usable quantum computer is a potential theme for another Qulabs’ Quantum Research Lab.
Development of algorithms, compilers, languages and programming solutions in conjunction with hardware platforms, architectures and circuits that are currently or soon-to-be available, including noisy intermediate scale quantum computing technologies, presents a myriad of scientific and engineering challenges.
Development of appropriate abstractions for different technology platforms, programming languages and algorithms for different applications, benchmarking, validation, error correction techniques and fault tolerant hardware platforms and architectures are among the technical challenges.
Furthermore, the formulation and identification of problems that are valuable to solve on near-term quantum computers may require a bold cross-disciplinary research program spanning computer science and engineering, mathematics and electrical engineering and domain areas such as chemistry, materials science, and physics.
The collection of scientists and engineers at various Qulabs’ Quantum Research Labs may also catalyze the development of new concepts, frameworks and interfaces for utilizing quantum coprocessing, distributed quantum computation and cloud-based quantum computing. These efforts, in turn, will enable a wider research community to benefit from quantum computing platforms and thus further accelerate innovation.
Developing algorithms, architectures and platforms for quantum simulators is another potential major thrust area for Qulabs’ Quantum Research Labs. Efforts to emulate molecules, materials, or nuclear matter with other more-controllable quantum systems such as trapped ions, superconducting circuits, or neutral atoms have identified many foundational challenges.
Digital approaches using algorithms for quantum circuits with qubits and quantum gates and analog approaches to Hamiltonian engineering or emulation, as well as hybrid approaches, are all of interest. In each case, challenges include developing simulator architectures, mapping one system to another, initializing quantum states, engineering interactions for controlled evolution of quantum states, suppressing decoherence and measuring results.
Moreover, interpreting results and pioneering new applications for quantum simulators may benefit from collaborations involving experts from chemistry, biology, materials science, physics, mathematics, computer science and engineering. Fostering such convergence in Qulabs’ Quantum Research Lab could provide additional insights, such as a deeper understanding of how entropy, topology, entanglement, imperfections, noise and environmental reservoirs affect the dynamics of strongly-interacting many-body quantum systems.
Quantum simulation may also offer transformative ways to study novel states of matter with exotic forms of magnetism or superconductivity and to discover possible new applications, for example, in metrology. Currently, Qulabs’ IT Roorkee Quantum Research Lab is working with IISc Bengaluru and CDAC Hyderabad and Bengaluru to create first Quantum Simulator in India.
Metrology and sensor technology based on quantum systems could be another focus area for Qulabs’ Quantum Research Labs. From precise measurements of fundamental constants to monitoring of environmental variables, the science and engineering of gaining metrological advantages from quantum state preparation, manipulation and detection presents many challenges. Precision measurements with entangled photons, atomic clocks, atom interferometers, nuclear magnetic resonance (NMR) spectrometers and color centers in diamond capitalize on quantum coherence, superposition and interference.
However, refining system architectures, making robust devices, engineering optimal input states, utilizing entanglement and pioneering new applications for quantum sensors are stimulating challenges.
Some inspiration for novel sensors can be gained from many-body systems where entanglement plays a role, for example in topological insulators, superconducting transition-edge sensors, quantum magnetism, quantum imaging, cavity quantum electrodynamics (QED) and hybrid quantum systems. Chemical, biological and biochemical sensors may be designed using entangled photons and quantum excitations.
Pursuing several of these topics concurrently at Qulabs’ Quantum Research Labs could stimulate transformative advances in sensor technology and measurement science. The foundational and technological principles discovered in the development of quantum sensors could also impact other applications of quantum information science and engineering, including communication, computing and simulation.
Rapid development of quantum technologies and sustained progress in scientific advances and commercial applications require a growing and qualified workforce with interdisciplinary skill sets. The QuAcademy aims to facilitate training of students with the combination of skills required for the conceptualization, development and translation of new quantum technologies. The QuAcademy provides activities to promote the training of students in environments that expose them to a convergent set of disciplines and help them acquire qualifications and skills needed in industry, national laboratories and academia. New approaches to collaboration with industry are anticipated in various Qulabs’ Quantum Research Labs with Industry partners and Quantum Computing cloud platform providers like IBM, Microsoft, D-Wave, Rigetti, Google and Xanadu to not only to increase the translational impact of research, but also as a tool to assure the training and generation of a well-qualified workforce in Quantum Information Science and Engineering.
The QuAcademy in tandem with various Institutes of higher learning like IITs, ISI, IISc and Qulabs’ Quantum Research Labs also provides opportunities to foster the growth of a vibrant cross-disciplinary research community through curriculum development, through research projects addressing various topics, as well as their integration. Relevant efforts may include: new degree programs and curriculum development within various academic departments (e.g., computer science and engineering, electrical engineering, physics, materials science and engineering, and mathematics) and coordination across departments to foster cross-disciplinary research; development of a common basic cross-disciplinary curriculum for potential degree programs to be shared across departments; organization of conferences targeted at critical cross-disciplinary research interfaces; development of experimental prototypes and testbeds for exploring different emerging technology platforms that are accessible to the wider research community; and creation of entrepreneurial opportunities for academia-industry collaboration, technology transfer and commercialization.