We Develop Technology
for Quantum
Supremacy
We develop Technology for a better Future & are moving towards a World where there can be Quantum Supremacy
G2Q FOUNDERS
G2Q is a scientific computing company, experts in developing advanced hybrid quantum-classical applications to solve complex real-world problems and help leading companies across all industries to boost their performance.
" Nature isn’t classical, damn it, & if you want to make a simulation of nature, you’d better make it quantum mechanical. " Richard Feynman in 1981
The users of our software, will have, considerable strategic technological advantage on certain computations and the possibility to dive into the race to quantum supremacy with the help of our quantum modules that have been studied to give new performing solutions, on the currently available quantum computing hardware.
02
OUR TECH
Quantum
Optimization
solve complex optimization problems on gate-based quantum computers with the help of our qubit efficient technology as well as representing combinatorial optimization problems as QUBO problems to be solved on quantum annealers
Quantum
Simulator
simulate within a quantum computer correlated complex stochastic processes that do not have analytical solutions and therefore do not have a defined distribution to load into a quantum computer before carrying out the simulation. This enables to give an effective quadratic speed up and allows to converge to accurate solutions especially when extreme events need to be modelled and simulated
Quantum
Search Algorithms
improve classical search algorithms for parameter calibration of complex SDE and PDEs used to model financial and physical systems. Within this technology sophisticated sampling techniques have been developed that have also proven to work exceptionally on classical computers
Quantum
AI
solve complex machine learning problems with less data and reduced computing times by better handling learning tasks and detecting hidden correlations and features that would classically require continuously increasing computational capabilities
02
OUR TECH
Quantum
Simulation
Solving Complex systems which suffer the curse of dimensionality and improving the convergence and accuracy of approximate techniques such as Monte Carlo and Markov Chain methods
– Significantly improve the simulation efficiency and accuracy in the pricing of financial derivative
– Get more reliable results when sampling from high dimensional spaces
– Efficiently generate probability distributions within a quantum computer thus allowing to price financial derivatives
Quantum
A.I.
Better handling learning tasks and detecting hidden correlations and features that would classically require continuously increasing computational capabilities
– Handling of complex correlations and less data requirements for extracting of hidden features
– More performing and accurate optimization algorithms with less probability of encountering barren plateaus
– Enhanced training with less and unbalanced data
Quantum
Simulations +
Algorithms
Models that solve the curse of dimensionality, which is common in Nature and Finance processes.
– With a classical computer such problems can be solved only approximately with the use of statistical methods, dimensionality reduction techniques or brute force.
– Quantum solutions are suited for modelling of such complex systems & resolve the limits of dimensional computing.
Global from the Start
Top Tier Talent & Expertise
Team Members have come together from top tier universities and various backgrounds in order to meet the mix required to deliver all aspects of our projects.
University of Oxford
Trinity College Dublin
University of Ottawa
Politecnico di Milano
University Melbourne
University of Milan
Warwick University
Bocconi University
Path Breaking Careers
Highlights of Academic Backgrounds
PhD in physics that has done cutting-edge research on quantum systems
PhD in Physics and IBM certified quantum developer with research areas in Quantum Machine Learning and AI, Application of Quantum technology in Space Exploration and Quantum Simulation of Physical Systems
Master in Mathematical and Theoretical Physics and a PhD in Quantum Machine Learning and computing in high energy physics with a previous experience as an exotic derivative trader at a major Financial institution
Researcher in Robotics and Electronic Engineering that has developed state of art concept of Fourier domain adaptation on datasets and novel classic machine learning and computer vision algorithms
Associate Professor in Mathematics and Data Science and with post-doctoral research in Stochastic Control, Mathematical Finance, Machine learning model of derivative pricing
Master in Mathematical Physics with Specialization in Quantum information and Quantum metrology
Master in Financial Mathematics who has worked with the European Central bank on the validation of financial models used to price complex financial instruments
Innovation with Validation
University Collaborations & Partners:
G2Q is part of NVIDIA Inception to Accelerate Hybrid Quantum-Classical Computing For AI
G2Q is in partnership with the University of Naples Federico II to test quntum software algorithms on the first Italian quantum computer made with superconducting qubits
In order to validate and formulate new theories and models to achieve breakthroughs we are collaborating with academics from Indian Institute of Science Education and Research
