IIT Mandi officials are working on something new that will definitely create a sensation in the technical and scientific fields. The information provided indicates that they are creating an indigenous, first-of-its-kind room-temperature quantum computer that will use photons to speed up computations. It was further added that the National Quantum Mission's computer will be remarkable because it could analyze data and make recommendations for solutions with 86% accuracy.

Quantum computing is all the rage these days, with big names like IBM and Google building their own quantum computers.

Director of IIT-Mandi Laxmidhar Behera said CQST is advancing quantum computing technology and has the potential to transform a number of industries. He also stated that they are driving advances in the fields of genomics, astronomy, finance, and weather forecasting with novel improvements in feature learning and classification through the National Quantum Mission. 

What's unique about this computer?
The design of the room-temperature optical quantum computer allows it to quickly solve challenges related to feature learning and categorization. A computer will function as a graphics processor (GPU) rather than a CPU, smoothly processing inputs like videos or photos, thanks to a sophisticated user interface, a quantum simulator, and quantum processing capabilities.
It will take the input data, derive a model to describe the underlying dynamics, and provide an output in the form of a quantum live stream.

Light will be used by a room-temperature optical quantum computer to perform quick calculations. The computer will be able to function in numerous states at once by utilizing quantum bits, or qubits, which will enable extraordinarily quick computing. With the help of a unique gel, the system will be able to update itself and clear its memory.
Writing a quantum algorithm is time-consuming. Still, without the need for algorithms, this computer will resemble the natural curiosity of a scientist by quickly proposing an approximation theoretical model for unknown, huge data that is 86% accurate.

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