Quantum Programming News
Researchers at University of Exeter have proposed a quantum algorithm to solve systems of nonlinear differential equations. Using a quantum feature map encoding, they have defined functions as expectation values of parametrized quantum circuits. They
![AlgoDynamix, which operates from Barclays Eagle Labs in Cambridge, has launched powerful new quantum computing capabilities. [Picture: Keith Heppell / Cambridge Independent]](https://swissquantumhub.com/wp-content/uploads/2020/11/jeremy-sosabowski.jpg)
AlgoDynamix which operates from Barclays Eagle Labs in Cambridge, UK, has unveiled a new cloud-based service using technology provided by D-Wave Systems and says it is a world first in behavioural forecasting for financial analytics.
Using supercomputing and new tools for understanding quantum algorithms in advance of scaled hardware gives a view of what may be possible in a future with scaled quantum computing. Microsoft proposes Quantum Intermediate Representation (QIR)
Scientists have demonstrated a novel method for applying the quantum Grover Algorithm (GA) – to search for rare events in proton-proton collisions at 13 TeV collision energy using CERN’s Large Hadron Collider. The search is
Researchers have reported a quantum-classical hybrid scheme for factorization of bi-prime numbers (which are odd and square-free) using IBM’s quantum processors. The hybrid scheme has involved both classical optimization techniques and adiabatic quantum optimization techniques,
Researchers at University of Chicago announced they were able to turn IBM’s largest quantum computer into a quantum material itself. They programmed the computer such that it turned into a type of quantum material called
Achieving near-term quantum advantage will require effective methods for mitigating hardware noise. One approach is to optimize quantum circuits using compiling and machine learning, while another employs variational quantum algorithms to reduce circuit depth and
Researchers at IBM Research and Mercedez–Benz Research have demonstrated quantum simulations of electronic structure with a transformed Hamiltonian that includes some electron correlation effects. The transcorrelated Hamiltonian used in this work is efficiently constructed classically,
Researchers at Rensselaer Polytechnic Institute have explored the potential for Quantum Computing to facilitate Reinforcement Learning (RL) problems. Deep RL has accelerated at astounding speed in the last decade. Achieving superhuman performance in massively complex
Researcher at QuTech proposes QuAlg, an open-source symbolic algebra package for Quantum Computing. There are many packages and tools for representing and simulating quantum states and operations, such as nesquid, qutip or Qiskit. Most of
