29 citations · 39 across the 7 of their papers we have counts for
7 papers
Compiling Quantum Regular Language States
Armando Bellante, Reinis Irmejs, Marta Florido-Llinàs +4
State preparation compilers for quantum computers typically sit at two extremes: general-purpose routines that treat the target as an opaque amplitude vector, and bespoke construct…
Efficient Simulation of Sparse, Non-Local Fermion Models
Reinis Irmejs, J. Ignacio Cirac
Efficient simulation of interacting fermionic systems is a key application of near-term quantum computers, but is hindered by the overhead required to encode fermionic operators on…
Quasi-Adiabatic Processing of Thermal States
Reinis Irmejs, Mari Carmen Bañuls, J. Ignacio Cirac
We investigate the performance of an adiabatic evolution protocol when initialized from a Gibbs state at finite temperature. Specifically, we identify the diagonality of the final…
Approximating dynamical correlation functions with constant depth quantum circuits
Reinis Irmejs, Raul A. Santos
One of the most important quantities characterizing the microscopic properties of quantum systems are dynamical correlation functions. These correlations are obtained by time-evolv…
Efficient Quantum Algorithm for Filtering Product States
Reinis Irmejs, Mari Carmen Bañuls, J. Ignacio Cirac
We introduce a quantum algorithm to efficiently prepare states with a small energy variance at the target energy. We achieve it by filtering a product state at the given energy wit…
Quantum Simulation of Z2 Lattice Gauge theory with minimal resources
Reinis Irmejs, Mari Carmen Banuls, J. Ignacio Cirac
The quantum simulation of fermionic gauge field theories is one of the anticipated uses of quantum computers in the NISQ era. Recently work has been done to simulate properties of…
Atomic Scattering For Chemical Analysis Of Surfaces
Reinis Irmejs, Nadav Avidor
The study explores machine learning methods for revealing chemical sensitivity in Helium spin-echo spectroscopy, in order to obtain ultra-sensitive surface analytic technique. We m…